Simulation on Poisson and negative binomial models of count road accident modeling

NASA Astrophysics Data System (ADS)

Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.

2016-11-01

Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.

[Association between cesarean birth and the risk of obesity in 6-17 year-olds].

PubMed

Wang, Z H; Xu, R B; Dong, Y H; Yang, Y D; Wang, S; Wang, X J; Yang, Z G; Zou, Z Y; Ma, J

2017-12-10

Objective: To explore the association between cesarean section and obesity in child and adolescent. Methods: In this study, a total number of 42 758 primary and middle school students aged between 6 and 17 were selected, using the stratified cluster sampling method in 93 primary and middle schools in Hunan, Ningxia, Tianjin, Chongqing, Liaoning, Shanghai and Guangdong provinces and autonomous regions. Log-Binomial regression model was used to analyze the association between cesarean section and obesity in childhood or adolescent. Results: Mean age of the subjects was (10.5±3.2) years. The overall rate of cesarean section among subjects attending primary or secondary schools was 42.3%, with 55.9% in boys and, 40.6% in girls respectively and with difference statistically significant ( P <0.001). The rate on obesity among those that received cesarean section (17.6%) was significantly higher than those who experienced vaginal delivery (10.2%) ( P <0.001). Results from the log-binomial regression model showed that cesarean section significantly increased the risk of obesity in child and adolescent ( OR =1.72, 95% CI : 1.63-1.82; P <0.001). After adjusting for factors as sex, residential areas (urban or rural), feeding patterns, frequencies of milk-feeding, eating high-energy foods, eating fried foods and the levels of parental education, family income, parental obesity, physical activity levels, gestational age and birth weight etc ., the differences were still statistically significant ( OR =1.48, 95% CI : 1.39-1.57; P <0.001). Conclusion: The rate of cesarean section among pregnant women in China appeared high which may significantly increase the risk of obesity in child or adolescent.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

PubMed Central

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

Selecting the right statistical model for analysis of insect count data by using information theoretic measures.

PubMed

Sileshi, G

2006-10-01

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero-inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike's and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Stål and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero-inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

The arcsine is asinine: the analysis of proportions in ecology.

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability and higher power than analyses of transformed data. However, it is important to check the data for additional unexplained variation, i.e., overdispersion, and to account for it via the inclusion of random effects in the model if found. For non-binomial data, the arcsine transform is undesirable on the grounds of interpretability, and because it can produce nonsensical predictions. The logit transformation is proposed as an alternative approach to address these issues. Examples are presented in both cases to illustrate these advantages, comparing various methods of analyzing proportions including untransformed, arcsine- and logit-transformed linear models and logistic regression (with or without random effects). Simulations demonstrate that logistic regression usually provides a gain in power over other methods.

A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.

PubMed

Ye, Xin; Wang, Ke; Zou, Yajie; Lord, Dominique

2018-01-01

This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.

The relationship between non-communicable disease occurrence and poverty-evidence from demographic surveillance in Matlab, Bangladesh.

PubMed

Mirelman, Andrew J; Rose, Sherri; Khan, Jahangir Am; Ahmed, Sayem; Peters, David H; Niessen, Louis W; Trujillo, Antonio J

2016-07-01

In low-income countries, a growing proportion of the disease burden is attributable to non-communicable diseases (NCDs). There is little knowledge, however, of their impact on wealth, human capital, economic growth or household poverty. This article estimates the risk of being poor after an NCD death in the rural, low-income area of Matlab, Bangladesh. In a matched cohort study, we estimated the 2-year relative risk (RR) of being poor in Matlab households with an NCD death in 2010. Three separate measures of household economic status were used as outcomes: an asset-based index, self-rated household economic condition and total household landholding. Several estimation methods were used including contingency tables, log-binomial regression and regression standardization and machine learning. Households with an NCD death had a large and significant risk of being poor. The unadjusted RR of being poor after death was 1.19, 1.14 and 1.10 for the asset quintile, self-rated condition and landholding outcomes. Adjusting for household and individual level independent variables with log-binomial regression gave RRs of 1.19 [standard error (SE) 0.09], 1.16 (SE 0.07) and 1.14 (SE 0.06), which were found to be exactly the same using regression standardization (SE: 0.09, 0.05, 0.03). Machine learning-based standardization produced slightly smaller RRs though still in the same order of magnitude. The findings show that efforts to address the burden of NCD may also combat household poverty and provide a return beyond improved health. Future work should attempt to disentangle the mechanisms through which economic impacts from an NCD death occur. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A Model Comparison for Count Data with a Positively Skewed Distribution with an Application to the Number of University Mathematics Courses Completed

ERIC Educational Resources Information Center

Liou, Pey-Yan

2009-01-01

The current study examines three regression models: OLS (ordinary least square) linear regression, Poisson regression, and negative binomial regression for analyzing count data. Simulation results show that the OLS regression model performed better than the others, since it did not produce more false statistically significant relationships than…

Period prevalence and factors associated with road traffic crashes among young adults in Kuwait.

PubMed

Aldhafeeri, Eisa; Alshammari, Farah; Jafar, Hana; Malhas, Haya; Botras, Marina; Alnasrallah, Noor; Akhtar, Saeed

2018-05-01

This cross-sectional study assessed one-year period prevalence of road traffic crashes (RTCs) and examined the factors associated with RTCs among young adults in Kuwait. During December 2016, 1500 students enrolled in 15 colleges of Kuwait University were invited to participate in the study. Students 18 years old or older and who drive by themselves were eligible. Data were collected using a structured self-administered questionnaire. One-year period prevalence of RTCs (≥1 vs. none) was computed. Multivariable log-binomial regression model was used to identify the risk factors associated with one-year period prevalence of RTCs. Of 1500 invited individuals, 1465 (97.7%) participated, of which 71.4% (1046/1465) were female, 56.4% (804/1426) were aged between 21 and 25 years, and 67.1% (980/1460) were Kuwaitis. One-year period prevalence of RTC was 38.9%. The final multivariable log-binomial regression model showed that after adjusting for the influences of other variables in the model, participants were more likely to have had at least one RTC during the past year, if they habitually sped over limit (adjusted PR = 1.19; 95% confidence interval (CI): 1.04-1.36), crossed a red light (adjusted PR = 1.33; 95% CI: 1.16-1.52), or if they have had three or more speeding tickets (adjusted PR = 1.40; 95% CI: 1.13-1.73) compared to those who reportedly had no RTC during the same period. One-year period prevalence of RTCs among university students in Kuwait, though relatively lower than the reported figures in similar populations elsewhere in the region, is yet high enough to warrant diligent attention. Habitual speeding, having had three or more speeding tickets, and the practice of crossing a red light were significantly and independently associated with at least one RTC during the past year. Targeted education and enforcement of existing traffic laws may reduce the RTCs frequency in this relatively young population. Future studies may look at impact of such interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Applied Prevalence Ratio estimation with different Regression models: An example from a cross-national study on substance use research.

PubMed

Espelt, Albert; Marí-Dell'Olmo, Marc; Penelo, Eva; Bosque-Prous, Marina

2016-06-14

To examine the differences between Prevalence Ratio (PR) and Odds Ratio (OR) in a cross-sectional study and to provide tools to calculate PR using two statistical packages widely used in substance use research (STATA and R). We used cross-sectional data from 41,263 participants of 16 European countries participating in the Survey on Health, Ageing and Retirement in Europe (SHARE). The dependent variable, hazardous drinking, was calculated using the Alcohol Use Disorders Identification Test - Consumption (AUDIT-C). The main independent variable was gender. Other variables used were: age, educational level and country of residence. PR of hazardous drinking in men with relation to women was estimated using Mantel-Haenszel method, log-binomial regression models and poisson regression models with robust variance. These estimations were compared to the OR calculated using logistic regression models. Prevalence of hazardous drinkers varied among countries. Generally, men have higher prevalence of hazardous drinking than women [PR=1.43 (1.38-1.47)]. Estimated PR was identical independently of the method and the statistical package used. However, OR overestimated PR, depending on the prevalence of hazardous drinking in the country. In cross-sectional studies, where comparisons between countries with differences in the prevalence of the disease or condition are made, it is advisable to use PR instead of OR.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Seroprevalence of HCV and HIV infection among clients of the nation's longest-standing statewide syringe exchange program: A cross-sectional study of Community Health Outreach Work to Prevent AIDS (CHOW).

PubMed

Salek, Thomas P; Katz, Alan R; Lenze, Stacy M; Lusk, Heather M; Li, Dongmei; Des Jarlais, Don C

2017-10-01

The Community Health Outreach Work to Prevent AIDS (CHOW) Project is the first and longest-standing statewide integrated and funded needle and syringe exchange program (SEP) in the US. Initiated on O'ahu in 1990, CHOW expanded statewide in 1993. The purpose of this study is to estimate the prevalences of hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infection, and to characterize risk behaviors associated with infection among clients of a long-standing SEP through the analysis of the 2012 CHOW evaluation data. A cross-sectional sample of 130 CHOW Project clients was selected from January 1, 2012 through December 31, 2012. Questionnaires captured self-reported exposure information. HIV and HCV antibodies were detected via rapid, point-of-care FDA-approved tests. Log-binomial regressions were used to estimate prevalence proportion ratios (PPRs). A piecewise linear log-binomial regression model containing 1 spline knot was used to fit the age-HCV relationship. The estimated seroprevalence of HCV was 67.7% (95% confidence interval [CI]=59.5-75.8%). HIV seroprevalence was 2.3% (95% CI=0-4.9%). Anti-HCV prevalence demonstrated age-specific patterns, ranging from 31.6% through 90.9% in people who inject drugs (PWID) <30 to ≥60 years respectively. Age (continuous/year) prior to spline knot at 51.5 years (adjusted PPR [APPR]=1.03; 95% CI=1.02-1.05) and months exchanging syringes (quartiles) (APPR=1.92; 95% CI=1.3-3.29) were independently associated with anti-HCV prevalence. In Hawai'i, HCV prevalence among PWID is hyperendemic demonstrating age- and SEP duration-specific trends. Relatively low HIV prevalence compared with HCV prevalence reflects differences in transmissibility of these 2 blood-borne pathogens and suggests much greater efficacy of SEP for HIV prevention. Copyright © 2017 Elsevier B.V. All rights reserved.

Narrow log-periodic modulations in non-Markovian random walks

NASA Astrophysics Data System (ADS)

Diniz, R. M. B.; Cressoni, J. C.; da Silva, M. A. A.; Mariz, A. M.; de Araújo, J. M.

2017-12-01

What are the necessary ingredients for log-periodicity to appear in the dynamics of a random walk model? Can they be subtle enough to be overlooked? Previous studies suggest that long-range damaged memory and negative feedback together are necessary conditions for the emergence of log-periodic oscillations. The role of negative feedback would then be crucial, forcing the system to change direction. In this paper we show that small-amplitude log-periodic oscillations can emerge when the system is driven by positive feedback. Due to their very small amplitude, these oscillations can easily be mistaken for numerical finite-size effects. The models we use consist of discrete-time random walks with strong memory correlations where the decision process is taken from memory profiles based either on a binomial distribution or on a delta distribution. Anomalous superdiffusive behavior and log-periodic modulations are shown to arise in the large time limit for convenient choices of the models parameters.

Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

Morbidity and Health Risk Factors Among New Mexico Miners: A Comparison Across Mining Sectors.

PubMed

Shumate, Alice M; Yeoman, Kristin; Victoroff, Tristan; Evans, Kandace; Karr, Roger; Sanchez, Tami; Sood, Akshay; Laney, Anthony Scott

2017-08-01

This study examines differences in chronic health outcomes between coal, uranium, metal, and nonmetal miners. In a cross-sectional study using data from a health screening program for current and former New Mexico miners, log-binomial logistic regression models were used to estimate relative risks of respiratory and heart disease, cancer, osteoarthritis, and back pain associated with mining in each sector as compared with coal, adjusting for other relevant risk factors. Differential risks in angina, pulmonary symptoms, asthma, cancer, osteoarthritis, and back pain between mining sectors were found. New Mexico miners experience different chronic health challenges across sectors. These results demonstrate the importance of using comparable data to understand how health risks differ across mining sectors. Further investigation among a broader geographic population of miners will help identify the health priorities and needs in each sector.

Employee resistance and injury during commercial robberies.

PubMed

Jones, Jennifer; Casteel, Carri; Peek-Asa, Corinne

2015-05-01

To examine the association between employee resistance and injury and examine whether type or location of property stolen was associated with employee resistance during commercial robberies in a large metropolitan city. Robbery data were abstracted from police crime reports between 2008 and 2012. Log binomial regression models were used to identify predictors of employee resistance and to evaluate the association between employee resistance and injury. Employees resisted a robber in nearly half of all robbery events. Active employee resistance was significantly associated with employee injury (Adj PR: 1.49, 95% confidence interval, 1.34 to 1.65). Goods being stolen were associated with active employee resistance and employee injury, whereas cash only being stolen was inversely associated with employee injury. Results suggest that employee training in nonresistance can be an important strategy in protecting employees working with the exchange of cash and goods.

On Models for Binomial Data with Random Numbers of Trials

PubMed Central

Comulada, W. Scott; Weiss, Robert E.

2010-01-01

Summary A binomial outcome is a count s of the number of successes out of the total number of independent trials n = s + f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability π of success that cannot be directly incorporated by the logistic regression model. Observations where n = 0 are excluded from the binomial analysis yet may be important to understanding how π is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study. PMID:17688514

Selecting a distributional assumption for modelling relative densities of benthic macroinvertebrates

USGS Publications Warehouse

Gray, B.R.

2005-01-01

The selection of a distributional assumption suitable for modelling macroinvertebrate density data is typically challenging. Macroinvertebrate data often exhibit substantially larger variances than expected under a standard count assumption, that of the Poisson distribution. Such overdispersion may derive from multiple sources, including heterogeneity of habitat (historically and spatially), differing life histories for organisms collected within a single collection in space and time, and autocorrelation. Taken to extreme, heterogeneity of habitat may be argued to explain the frequent large proportions of zero observations in macroinvertebrate data. Sampling locations may consist of habitats defined qualitatively as either suitable or unsuitable. The former category may yield random or stochastic zeroes and the latter structural zeroes. Heterogeneity among counts may be accommodated by treating the count mean itself as a random variable, while extra zeroes may be accommodated using zero-modified count assumptions, including zero-inflated and two-stage (or hurdle) approaches. These and linear assumptions (following log- and square root-transformations) were evaluated using 9 years of mayfly density data from a 52 km, ninth-order reach of the Upper Mississippi River (n = 959). The data exhibited substantial overdispersion relative to that expected under a Poisson assumption (i.e. variance:mean ratio = 23 ??? 1), and 43% of the sampling locations yielded zero mayflies. Based on the Akaike Information Criterion (AIC), count models were improved most by treating the count mean as a random variable (via a Poisson-gamma distributional assumption) and secondarily by zero modification (i.e. improvements in AIC values = 9184 units and 47-48 units, respectively). Zeroes were underestimated by the Poisson, log-transform and square root-transform models, slightly by the standard negative binomial model but not by the zero-modified models (61%, 24%, 32%, 7%, and 0%, respectively). However, the zero-modified Poisson models underestimated small counts (1 ??? y ??? 4) and overestimated intermediate counts (7 ??? y ??? 23). Counts greater than zero were estimated well by zero-modified negative binomial models, while counts greater than one were also estimated well by the standard negative binomial model. Based on AIC and percent zero estimation criteria, the two-stage and zero-inflated models performed similarly. The above inferences were largely confirmed when the models were used to predict values from a separate, evaluation data set (n = 110). An exception was that, using the evaluation data set, the standard negative binomial model appeared superior to its zero-modified counterparts using the AIC (but not percent zero criteria). This and other evidence suggest that a negative binomial distributional assumption should be routinely considered when modelling benthic macroinvertebrate data from low flow environments. Whether negative binomial models should themselves be routinely examined for extra zeroes requires, from a statistical perspective, more investigation. However, this question may best be answered by ecological arguments that may be specific to the sampled species and locations. ?? 2004 Elsevier B.V. All rights reserved.

Cocoa Farmers’ Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon

PubMed Central

2018-01-01

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers’ instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced (p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced (p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers’ instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers’ instructions and use PPE would enhance their safety in the course of spraying agrochemicals. PMID:29438333

Cocoa Farmers' Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon.

PubMed

Oyekale, Abayomi Samuel

2018-02-13

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers' instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced ( p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced ( p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers' instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers' instructions and use PPE would enhance their safety in the course of spraying agrochemicals.

Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

PubMed

Mi, Gu; Di, Yanming; Schafer, Daniel W

2015-01-01

This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

Martina, R; Kay, R; van Maanen, R; Ridder, A

2015-01-01

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.

Establishing endangered species recovery criteria using predictive simulation modeling

USGS Publications Warehouse

McGowan, Conor P.; Catlin, Daniel H.; Shaffer, Terry L.; Gratto-Trevor, Cheri L.; Aron, Carol

2014-01-01

Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

Differences in spousal influence on smoking cessation by gender and education among Japanese couples.

PubMed

Takagi, Daisuke; Kondo, Naoki; Takada, Misato; Hashimoto, Hideki

2014-11-19

Previous studies have reported that spousal non-smoking has a spillover effect on the partner's cessation. However, discussion is lacking on the factors modifying that association. We examined whether the spillover effect of spousal non-smoking was associated with the couple's educational attainment. We used paired marital data from the Japanese Study on Stratification, Health, Income, and Neighborhood (J-SHINE), which targeted residents aged 25-50 years in four Japanese municipalities. We selected a spouse smoker at the time of marriage (target respondent), and set his/her smoking status change (continued or quit smoking after marriage) as an outcome, regressed on the counterpart's smoking status (continued smoking or non-smoking) and combinations of each couple's educational attainment as explanatory variables using log-binomial regression models (n =1001 targets; 708 men and 293 women). Regression results showed that a counterpart who previously quit smoking or was a never-smoker was associated with the target male spouse's subsequent cessation. However, for women, the association between husband's non-smoking and their own cessation was significant only for couples in which both spouses were highly educated. Our findings suggest that a spouse's smoking status is important for smoking cessation interventions in men. For women, however, a couple's combined educational attainment may matter in the interventions.

Modeling species-abundance relationships in multi-species collections

USGS Publications Warehouse

Peng, S.; Yin, Z.; Ren, H.; Guo, Q.

2003-01-01

Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.

Comments Regarding the Binary Power Law for Heterogeneity of Disease Incidence

USDA-ARS?s Scientific Manuscript database

The binary power law (BPL) has been successfully used to characterize heterogeneity (over dispersion or small-scale aggregation) of disease incidence for many plant pathosystems. With the BPL, the log of the observed variance is a linear function of the log of the theoretical variance for a binomial...

Resistant to the recession: low-income adults' maintenance of cooking and away-from-home eating behaviors during times of economic turbulence.

PubMed

Smith, Lindsey P; Ng, Shu Wen; Popkin, Barry M

2014-05-01

We examined the effects of state-level unemployment rates during the recession of 2008 on patterns of home food preparation and away-from-home (AFH) eating among low-income and minority populations. We analyzed pooled cross-sectional data on 118 635 adults aged 18 years or older who took part in the American Time Use Study. Multinomial logistic regression models stratified by gender were used to evaluate the associations between state-level unemployment, poverty, race/ethnicity, and time spent cooking, and log binomial regression was used to assess respondents' AFH consumption patterns. High state-level unemployment was associated with only trivial increases in respondents' cooking patterns and virtually no change in their AFH eating patterns. Low-income and racial/ethnic minority groups were not disproportionately affected by the recession. Even during a major economic downturn, US adults are resistant to food-related behavior change. More work is needed to understand whether this reluctance to change is attributable to time limits, lack of knowledge or skill related to food preparation, or lack of access to fresh produce and raw ingredients.

Resistant to the Recession: Low-Income Adults’ Maintenance of Cooking and Away-From-Home Eating Behaviors During Times of Economic Turbulence

PubMed Central

Smith, Lindsey P.; Ng, Shu Wen

2014-01-01

Objectives. We examined the effects of state-level unemployment rates during the recession of 2008 on patterns of home food preparation and away-from-home (AFH) eating among low-income and minority populations. Methods. We analyzed pooled cross-sectional data on 118 635 adults aged 18 years or older who took part in the American Time Use Study. Multinomial logistic regression models stratified by gender were used to evaluate the associations between state-level unemployment, poverty, race/ethnicity, and time spent cooking, and log binomial regression was used to assess respondents’ AFH consumption patterns. Results. High state-level unemployment was associated with only trivial increases in respondents’ cooking patterns and virtually no change in their AFH eating patterns. Low-income and racial/ethnic minority groups were not disproportionately affected by the recession. Conclusions. Even during a major economic downturn, US adults are resistant to food-related behavior change. More work is needed to understand whether this reluctance to change is attributable to time limits, lack of knowledge or skill related to food preparation, or lack of access to fresh produce and raw ingredients. PMID:24625145

Mental health status and healthcare utilization among community dwelling older adults.

PubMed

Adepoju, Omolola; Lin, Szu-Hsuan; Mileski, Michael; Kruse, Clemens Scott; Mask, Andrew

2018-04-27

Shifts in mental health utilization patterns are necessary to allow for meaningful access to care for vulnerable populations. There have been long standing issues in how mental health is provided, which has caused problems in that care being efficacious for those seeking it. To assess the relationship between mental health status and healthcare utilization among adults ≥65 years. A negative binomial regression model was used to assess the relationship between mental health status and healthcare utilization related to office-based physician visits, while a two-part model, consisting of logistic regression and negative binomial regression, was used to separately model emergency visits and inpatient services. The receipt of care in office-based settings were marginally higher for subjects with mental health difficulties. Both probabilities and counts of inpatient hospitalizations were similar across mental health categories. The count of ER visits was similar across mental health categories; however, the probability of having an emergency department visit was marginally higher for older adults who reported mental health difficulties in 2012. These findings are encouraging and lend promise to the recent initiatives on addressing gaps in mental healthcare services.

Trend estimation in populations with imperfect detection

USGS Publications Warehouse

Kery, Marc; Dorazio, Robert M.; Soldaat, Leo; Van Strien, Arco; Zuiderwijk, Annie; Royle, J. Andrew

2009-01-01

1. Trends of animal populations are of great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts to estimate abundance, corrected for detection, in demographically closed populations. Here, we extend these models to open populations and illustrate them using sand lizard Lacerta agilis counts from the national Dutch reptile monitoring scheme. 2. Our model requires replicated counts from multiple sites in each of several periods, within which population closure is assumed. Counts are described by a hierarchical generalized linear model, where the state model deals with spatio-temporal patterns in true abundance and the observation model with imperfect counts, given that true state. We used WinBUGS to fit the model to lizard counts from 208 transects with 1–10 (mean 3) replicate surveys during each spring 1994–2005. 3. Our state model for abundance contained two independent log-linear Poisson regressions on year for coastal and inland sites, and random site effects to account for unexplained heterogeneity. The observation model for detection of an individual lizard contained effects of region, survey date, temperature, observer experience and random survey effects. 4. Lizard populations increased in both regions but more steeply on the coast. Detectability increased over the first few years of the study, was greater on the coast and for the most experienced observers, and highest around 1 June. Interestingly, the population increase inland was not detectable when the observed counts were analysed without account of detectability. The proportional increase between 1994 and 2005 in total lizard abundance across all sites was estimated at 86% (95% CRI 35–151). 5. Synthesis and applications. Open-population binomial mixture models are attractive for studying true population dynamics while explicitly accounting for the observation process, i.e. imperfect detection. We emphasize the important conceptual benefit provided by temporal replicate observations in terms of the interpretability of animal counts.

An examination of sources of sensitivity of consumer surplus estimates in travel cost models.

PubMed

Blaine, Thomas W; Lichtkoppler, Frank R; Bader, Timothy J; Hartman, Travis J; Lucente, Joseph E

2015-03-15

We examine sensitivity of estimates of recreation demand using the Travel Cost Method (TCM) to four factors. Three of the four have been routinely and widely discussed in the TCM literature: a) Poisson verses negative binomial regression; b) application of Englin correction to account for endogenous stratification; c) truncation of the data set to eliminate outliers. A fourth issue we address has not been widely modeled: the potential effect on recreation demand of the interaction between income and travel cost. We provide a straightforward comparison of all four factors, analyzing the impact of each on regression parameters and consumer surplus estimates. Truncation has a modest effect on estimates obtained from the Poisson models but a radical effect on the estimates obtained by way of the negative binomial. Inclusion of an income-travel cost interaction term generally produces a more conservative but not a statistically significantly different estimate of consumer surplus in both Poisson and negative binomial models. It also generates broader confidence intervals. Application of truncation, the Englin correction and the income-travel cost interaction produced the most conservative estimates of consumer surplus and eliminated the statistical difference between the Poisson and the negative binomial. Use of the income-travel cost interaction term reveals that for visitors who face relatively low travel costs, the relationship between income and travel demand is negative, while it is positive for those who face high travel costs. This provides an explanation of the ambiguities on the findings regarding the role of income widely observed in the TCM literature. Our results suggest that policies that reduce access to publicly owned resources inordinately impact local low income recreationists and are contrary to environmental justice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Influence of physician factors on the effectiveness of a continuing medical education intervention.

PubMed

Flores, Sergio; Reyes, Hortensia; Perez-Cuevas, Ricardo

2006-01-01

Continuing medical education (CME) is essential for improving the quality of care in primary health care settings. This study's objective was to determine how the characteristics of family physicians influenced the effectiveness of a multifaceted CME intervention to improve the management of acute respiratory infection (ARI) or type 2 diabetes (DM2). A secondary analysis was conducted based on data from 121 family physicians, who participated in the educational intervention study. The outcome variable was positive change in physician's performance for treatment of ARI or DM2. The exposure variable was multifaceted CME intervention. Independent variables were professional physicians and organizational characteristics. Analysis included log binomial regression modeling. Factors influencing positive change included, for ARI, participation in the CME intervention and medical director interested in that condition and for DM2, participation in the CME intervention, medical director interested in DM2, and being a teacher. Physicians' characteristics and organizational environment influence the effectiveness of educational intervention and are therefore relevant to the implementation of CME strategies.

Syphilis Among U.S.-Bound Refugees, 2009-2013.

PubMed

Nyangoma, E N; Olson, C K; Painter, J A; Posey, D L; Stauffer, W M; Naughton, M; Zhou, W; Kamb, M; Benoit, S R

2017-08-01

U.S. immigration regulations require clinical and serologic screening for syphilis for all U.S.-bound refugees 15 years of age and older. We reviewed syphilis screening results for all U.S.-bound refugees from January 1, 2009 through December 31, 2013. We calculated age-adjusted prevalence by region and nationality and assessed factors associated with syphilis seropositivity using multivariable log binomial regression models. Among 233,446 refugees, we identified 874 syphilis cases (373 cases per 100,000 refugees). The highest overall age-adjusted prevalence rates of syphilis seropositivity were observed among refugees from Africa (1340 cases per 100,000), followed by East Asia and the Pacific (397 cases per 100,000). In most regions, male sex, increasing age, and living in non-refugee camp settings were associated with syphilis seropositivity. Future analysis of test results, stage of infection, and treatment delivery overseas is warranted in order to determine the extent of transmission risk and benefits of the screening program.

Factors associated with stigma attitude towards people living with HIV among general individuals in Heilongjiang, Northeast China.

PubMed

Li, Xin; Yuan, Lili; Li, Xiaoxia; Shi, Jingli; Jiang, Liying; Zhang, Chundi; Yang, Xiujing; Zhang, Yeli; Zhao, Donghui; Zhao, Yashuang

2017-02-17

HIV-related stigma always is major obstacles to an effective HIV response worldwide. The effect of HIV-related stigma on HIV prevention and treatment is particularly serious in China. This study was to examine stigma attitude towards people living with HIV/AIDS (PLWHA) among general individuals in Heilongjiang Province, Northeast China and the factors associated with stigma attitude, including socio-demographic factors and HIV/AIDS Knowledge. A cross-sectional survey was carried out in Heilongjiang Province, China. A total of 4050 general individuals with age 15-69 years in four villages in rural areas and two communities in urban areas were drawn using stratified cluster sampling. Standardized questionnaire interviews were administered. Univariate and multivariate log-binomial regression were performed to assess factors affecting stigma attitude towards PLWHA. The proportions of participants holding stigma attitude towards PLWHA were 49.6% among rural respondents and 37.0% among urban respondents (P < 0.001). Multivariate log binomial regression analysis among both rural participants (RR = 0.89, 95% CI: 0.87-0.91, P < 0.001) and urban participants (RR = 0.89, 95% CI: 0.87-0.91, P < 0.001) showed that greater knowledge of HIV transmission misconceptions was significantly associated with lower stigma attitude towards people living with HIV. And among urban participants, higher education level (high school vs. primary school or less: RR = 0.73, 95%CI: 0.62-0.87, P < 0.001; middle school vs. primary school or less: RR = 0.83, 95%CI: 0.71-0.97, P = 0.018) were also significantly associated with lower stigma attitude towards PLWHA. The level of stigma attitude towards PLWHA is higher in rural areas than in urban areas in Heilongjiang. Meanwhile, individuals who better were aware of HIV/AIDS transmission misconceptions may hold lower stigma attitude toward PLWHA whether among rural or urban residents.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

Health care seeking patterns and determinants of out-of-pocket expenditure for Malaria for the children under-five in Uganda

PubMed Central

2013-01-01

Background The objectives of this study were to assess the patterns of treatment seeking behaviour for children under five with malaria; and to examine the statistical relationship between out-of-pocket expenditure (OOP) on malaria treatment for under-fives and source of treatment, place of residence, education and wealth characteristics of Uganda households. OOP expenditure on health care is now a development concern due to its negative effect on households’ ability to finance consumption of other basic needs. Methods The 2009 Uganda Malaria Indicator Survey was the source of data on treatment seeking behaviour for under-five children with malaria, and patterns and levels of OOP expenditure for malaria treatment. Binomial logit and Log-lin regression models were estimated. In logit model the dependent variable was a dummy (1=incurred some OOP, 0=none incurred) and independent variables were wealth quintiles, rural versus urban, place of treatment, education level, sub-region, and normal duty disruption. The dependent variable in Log-lin model was natural logarithm of OOP and the independent variables were the same as mentioned above. Results Five key descriptive analysis findings emerge. First, malaria is quite prevalent at 44.7% among children below the age of five. Second, a significant proportion seeks treatment (81.8%). Third, private providers are the preferred option for the under-fives for the treatment of malaria. Fourth, the majority pay about 70.9% for either consultation, medicines, transport or hospitalization but the biggest percent of those who pay, do so for medicines (54.0%). Fifth, hospitalization is the most expensive at an average expenditure of US$7.6 per child, even though only 2.9% of those that seek treatment are hospitalized. The binomial logit model slope coefficients for the variables richest wealth quintile, Private facility as first source of treatment, and sub-regions Central 2, East central, Mid-eastern, Mid-western, and Normal duties disrupted were positive and statistically significant at 99% level of confidence. On the other hand, the Log-lin model slope coefficients for Traditional healer, Sought treatment from one source, Primary educational level, North East, Mid Northern and West Nile variables had a negative sign and were statistically significant at 95% level of confidence. Conclusion The fact that OOP expenditure is still prevalent and private provider is the preferred choice, increasing public provision may not be the sole answer. Plans to improve malaria treatment should explicitly incorporate efforts to protect households from high OOP expenditures. This calls for provision of subsidies to enable the private sector to reduce prices, regulation of prices of malaria medicines, and reduction/removal of import duties on such medicines. PMID:23721217

Severity of maternal HIV-1 disease is associated with adverse birth outcomes in Malawian women: a cohort study

PubMed Central

Turner, Abigail Norris; Tabbah, Sammy; Mwapasa, Victor; Rogerson, Stephen J.; Meshnick, Steven R.; Ackerman, William; Kwiek, Jesse J.

2014-01-01

Background Compared to HIV-negative women, HIV-infected women have increased risk of low birth weight (LBW) and preterm delivery (PTD). We assessed whether severity of maternal HIV-1 disease was associated with LBW or PTD. Methods Secondary analysis of The Malaria and HIV in Pregnancy prospective cohort, which enrolled HIV-positive, pregnant Malawian women from 2000–2004. Included participants (n=809) were normotensive, antiretroviral treatment naïve women who delivered a live, singleton infant. Binomial regression models were used to assess the unadjusted and adjusted prevalence ratios (PRs) and 95% confidence intervals (CI) of the effect of severity of HIV-1 disease, defined by viral load and CD4-positive T-cell counts, on prevalence of LBW and PTD. Results In unadjusted analyses, among those with malaria (n=198), there was no association between severity of HIV-1 infection and LBW, while among women without malaria (n=611), we observed a harmful association between both increasing peripheral viral load and LBW (PR: 1.44 per one-log10 increase, 95% CI: 1.12, 1.86) and placental viral load and LBW (PR: 1.24 per one-log10 increase, 95% CI: 1.00, 1.53). We observed a similar association between increasing placental viral load and PTD (PR: 1.33 per one-log10 increase, 95% CI: 1.04, 1.69). These associations persisted in multivariate models adjusted for residence, maternal education, primigravid status, and maternal anemia. Conclusions In malaria-negative women, maternal HIV-1 disease severity was significantly associated with increased prevalence of LBW and PTD. Such an association was not found in the malaria-infected women. PMID:23846560

Severity of maternal HIV-1 disease is associated with adverse birth outcomes in Malawian women: a cohort study.

PubMed

Turner, Abigail Norris; Tabbah, Sammy; Mwapasa, Victor; Rogerson, Stephen J; Meshnick, Steven R; Ackerman, William E; Kwiek, Jesse J

2013-12-01

Compared with HIV-negative women, HIV-infected women have increased risk of low birthweight (LBW) and preterm delivery (PTD). We assessed whether severity of maternal HIV-1 disease was associated with LBW or PTD. Secondary analysis of The Malaria and HIV in Pregnancy prospective cohort, which enrolled HIV-positive, pregnant Malawian women from 2000 to 2004. Included participants (n = 809) were normotensive antiretroviral treatment-naive women who delivered a live singleton infant. Binomial regression models were used to assess the unadjusted and adjusted prevalence ratios (PRs) and 95% confidence intervals (CI) of the effect of severity of HIV-1 disease, defined by viral load and CD4 T-cell counts, on prevalence of LBW and PTD. In unadjusted analyses, among those with malaria (n = 198), there was no association between severity of HIV-1 infection and LBW, whereas among women without malaria (n = 611), we observed a harmful association between both increasing peripheral viral load and LBW (PR: 1.44 per 1-log10 increase, 95% CI: 1.12 to 1.86) and placental viral load and LBW (PR: 1.24 per 1-log10 increase, 95% CI: 1.00 to 1.53). We observed a similar association between increasing placental viral load and PTD (PR: 1.33 per one-log10 increase, 95% CI: 1.04 to 1.69). These associations persisted in multivariate models adjusted for residence, maternal education, primigravid status, and maternal anemia. In malaria-negative women, maternal HIV-1 disease severity was significantly associated with increased prevalence of LBW and PTD. Such an association was not found in the malaria-infected women.

Analyzing hospitalization data: potential limitations of Poisson regression.

PubMed

Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

2015-08-01

Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Multivariate regression model for predicting yields of grade lumber from yellow birch sawlogs

Treesearch

Andrew F. Howard; Daniel A. Yaussy

1986-01-01

A multivariate regression model was developed to predict green board-foot yields for the common grades of factory lumber processed from yellow birch factory-grade logs. The model incorporates the standard log measurements of scaling diameter, length, proportion of scalable defects, and the assigned USDA Forest Service log grade. Differences in yields between band and...

Gaussian Process Regression Model in Spatial Logistic Regression

NASA Astrophysics Data System (ADS)

Sofro, A.; Oktaviarina, A.

2018-01-01

Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

An empirical model for estimating annual consumption by freshwater fish populations

USGS Publications Warehouse

Liao, H.; Pierce, C.L.; Larscheid, J.G.

2005-01-01

Population consumption is an important process linking predator populations to their prey resources. Simple tools are needed to enable fisheries managers to estimate population consumption. We assembled 74 individual estimates of annual consumption by freshwater fish populations and their mean annual population size, 41 of which also included estimates of mean annual biomass. The data set included 14 freshwater fish species from 10 different bodies of water. From this data set we developed two simple linear regression models predicting annual population consumption. Log-transformed population size explained 94% of the variation in log-transformed annual population consumption. Log-transformed biomass explained 98% of the variation in log-transformed annual population consumption. We quantified the accuracy of our regressions and three alternative consumption models as the mean percent difference from observed (bioenergetics-derived) estimates in a test data set. Predictions from our population-size regression matched observed consumption estimates poorly (mean percent difference = 222%). Predictions from our biomass regression matched observed consumption reasonably well (mean percent difference = 24%). The biomass regression was superior to an alternative model, similar in complexity, and comparable to two alternative models that were more complex and difficult to apply. Our biomass regression model, log10(consumption) = 0.5442 + 0.9962??log10(biomass), will be a useful tool for fishery managers, enabling them to make reasonably accurate annual population consumption predictions from mean annual biomass estimates. ?? Copyright by the American Fisheries Society 2005.

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data.

PubMed

Holsclaw, Tracy; Hallgren, Kevin A; Steyvers, Mark; Smyth, Padhraic; Atkins, David C

2015-12-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials. (c) 2016 APA, all rights reserved).

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data

PubMed Central

Holsclaw, Tracy; Hallgren, Kevin A.; Steyvers, Mark; Smyth, Padhraic; Atkins, David C.

2015-01-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non-normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased type-I and type-II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally-technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in supplementary materials. PMID:26098126

Accounting for measurement error in log regression models with applications to accelerated testing.

PubMed

Richardson, Robert; Tolley, H Dennis; Evenson, William E; Lunt, Barry M

2018-01-01

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Estimation of the cure rate in Iranian breast cancer patients.

PubMed

Rahimzadeh, Mitra; Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Pourhoseingholi, Mohamad Amin

2014-01-01

Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

PubMed

Gierliński, Marek; Cole, Christian; Schofield, Pietà; Schurch, Nicholas J; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J

2015-11-15

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of 'bad' replicates, which can drastically affect the gene read-count distribution. RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. g.j.barton@dundee.ac.uk. © The Author 2015. Published by Oxford University Press.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

PubMed Central

Cole, Christian; Schofield, Pietà; Schurch, Nicholas J.; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J.

2015-01-01

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk PMID:26206307

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study.

PubMed

Shi, Xiao; Zhang, Ting-Ting; Hu, Wei-Ping; Ji, Qing-Hai

2017-04-25

The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187-1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266-1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role.

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study

PubMed Central

Shi, Xiao; Zhang, Ting-ting; Hu, Wei-ping; Ji, Qing-hai

2017-01-01

Background The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Results Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187–1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266–1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). Materials and Methods 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Conclusions Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role. PMID:28415710

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

Stability of a Model Explaining Selected Extramusical Influences on Solo and Small-Ensemble Festival Ratings

ERIC Educational Resources Information Center

Bergee, Martin J.; Westfall, Claude R.

2005-01-01

This is the third study in a line of inquiry whose purpose has been to develop a theoretical model of selected extra musical variables' influence on solo and small-ensemble festival ratings. Authors of the second of these (Bergee & McWhirter, 2005) had used binomial logistic regression as the basis for their model-formulation strategy. Their…

A Negative Binomial Regression Model for Accuracy Tests

ERIC Educational Resources Information Center

Hung, Lai-Fa

2012-01-01

Rasch used a Poisson model to analyze errors and speed in reading tests. An important property of the Poisson distribution is that the mean and variance are equal. However, in social science research, it is very common for the variance to be greater than the mean (i.e., the data are overdispersed). This study embeds the Rasch model within an…

Early-life mortality risks in opposite-sex and same-sex twins: a Danish cohort study of the twin testosterone transfer hypothesis

PubMed Central

Ahrenfeldt, Linda Juel; Larsen, Lisbeth Aagaard; Lindahl-Jacobsen, Rune; Skytthe, Axel; Hjelmborg, Jacob v.B.; Möller, Sören; Christensen, Kaare

2017-01-01

Purpose To investigate the twin testosterone transfer (TTT) hypothesis by comparing early-life mortality risks of opposite-sex (OS) and same-sex (SS) twins during the first 15 years of life. Methods We performed a population-based cohort study to compare mortality in OS and SS twins. We included 68,629 live-born Danish twins from 1973 to 2009 identified through the Danish Twin Registry and performed piecewise stratified Cox regression and log-binomial regression. Results Among 1933 deaths, we found significantly higher mortality for twin boys than for twin girls. For both sexes, OS twins had lower mortality than SS twins; the difference persisted for the first year of life for boys and for the first week of life for girls. Conclusions Although the mortality risk for OS boys was in the expected direction according to the TTT hypothesis, the results for OS girls pointed in the opposite direction, providing no clear evidence for the TTT hypothesis. PMID:28024904

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Treesearch

Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...

A Binomial Modeling Approach for Upscaling Colloid Transport Under Unfavorable Attachment Conditions: Emergent Prediction of Nonmonotonic Retention Profiles

NASA Astrophysics Data System (ADS)

Hilpert, Markus; Johnson, William P.

2018-01-01

We used a recently developed simple mathematical network model to upscale pore-scale colloid transport information determined under unfavorable attachment conditions. Classical log-linear and nonmonotonic retention profiles, both well-reported under favorable and unfavorable attachment conditions, respectively, emerged from our upscaling. The primary attribute of the network is colloid transfer between bulk pore fluid, the near-surface fluid domain (NSFD), and attachment (treated as irreversible). The network model accounts for colloid transfer to the NSFD of downgradient grains and for reentrainment to bulk pore fluid via diffusion or via expulsion at rear flow stagnation zones (RFSZs). The model describes colloid transport by a sequence of random trials in a one-dimensional (1-D) network of Happel cells, which contain a grain and a pore. Using combinatorial analysis that capitalizes on the binomial coefficient, we derived from the pore-scale information the theoretical residence time distribution of colloids in the network. The transition from log-linear to nonmonotonic retention profiles occurs when the conditions underlying classical filtration theory are not fulfilled, i.e., when an NSFD colloid population is maintained. Then, nonmonotonic retention profiles result potentially both for attached and NSFD colloids. The concentration maxima shift downgradient depending on specific parameter choice. The concentration maxima were also shown to shift downgradient temporally (with continued elution) under conditions where attachment is negligible, explaining experimentally observed downgradient transport of retained concentration maxima of adhesion-deficient bacteria. For the case of zero reentrainment, we develop closed-form, analytical expressions for the shape, and the maximum of the colloid retention profile.

Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; Dale, Pat; McMichael, Anthony J; Tong, Shilu

2009-02-01

To assess the socio-environmental predictors of Barmah forest virus (BFV) transmission in coastal areas, Queensland, Australia. Data on BFV notified cases, climate, tidal levels and socioeconomic index for area (SEIFA) in six coastal cities, Queensland, for the period 1992-2001 were obtained from the relevant government agencies. Negative binomial regression models were used to assess the socio-environmental predictors of BFV transmission. The results show that maximum and minimum temperature, rainfall, relative humidity, high and low tide were statistically significantly associated with BFV incidence at lags 0-2 months. The fitted negative binomial regression models indicate a significant independent association of each of maximum temperature (beta = 0.139, P = 0.000), high tide (beta = 0.005, P = 0.000) and SEIFA index (beta = -0.010, P = 0.000) with BFV transmission after adjustment for confounding variables. The transmission of BFV disease in Queensland coastal areas seemed to be determined by a combination of local social and environmental factors. The model developed in this study may have applications in the control and prevention of BFV disease in these areas.

Some considerations for excess zeroes in substance abuse research.

PubMed

Bandyopadhyay, Dipankar; DeSantis, Stacia M; Korte, Jeffrey E; Brady, Kathleen T

2011-09-01

Count data collected in substance abuse research often come with an excess of "zeroes," which are typically handled using zero-inflated regression models. However, there is a need to consider the design aspects of those studies before using such a statistical model to ascertain the sources of zeroes. We sought to illustrate hurdle models as alternatives to zero-inflated models to validate a two-stage decision-making process in situations of "excess zeroes." We use data from a study of 45 cocaine-dependent subjects where the primary scientific question was to evaluate whether study participation influences drug-seeking behavior. The outcome, "the frequency (count) of cocaine use days per week," is bounded (ranging from 0 to 7). We fit and compare binomial, Poisson, negative binomial, and the hurdle version of these models to study the effect of gender, age, time, and study participation on cocaine use. The hurdle binomial model provides the best fit. Gender and time are not predictive of use. Higher odds of use versus no use are associated with age; however once use is experienced, odds of further use decrease with increase in age. Participation was associated with higher odds of no-cocaine use; once there is use, participation reduced the odds of further use. Age and study participation are significantly predictive of cocaine-use behavior. The two-stage decision process as modeled by a hurdle binomial model (appropriate for bounded count data with excess zeroes) provides interesting insights into the study of covariate effects on count responses of substance use, when all enrolled subjects are believed to be "at-risk" of use.

Occupational injury among hospital patient-care workers: what is the association with workplace verbal abuse?

PubMed

Sabbath, Erika L; Hurtado, David A; Okechukwu, Cassandra A; Tamers, Sara L; Nelson, Candace; Kim, Seung-Sup; Wagner, Gregory; Sorenson, Glorian

2014-02-01

To test the association between workplace abuse exposure and injury risk among hospital workers. We hypothesized that exposed workers would have higher injury rates than unexposed workers. Survey of direct-care workers (n = 1,497) in two hospitals. Exposure to workplace abuse was assessed through self-report; occupational injury reports were extracted from employee records. We tested associations between non-physical workplace violence and injury using log-binomial regression and multilevel modeling. Adjusted prevalence ratio (PR) for injury associated with being yelled at was 1.52 (95% CI 1.19, 1.95); for experiencing hostile/offensive gestures 1.43 (1.11, 1.82); and for being sworn at 1.41 (1.09, 1.81). In analyses by injury subtypes, musculoskeletal injuries were more strongly associated with abuse than were acute traumatic injuries. Associations operated on group and individual levels and were most consistently associated with abuse perpetrated by patients. Exposure to workplace abuse may be a risk factor for injuries among hospital workers. © 2013 Wiley Periodicals, Inc.

Trends and correlates of child passenger restraint use in 6 Northwest tribes: the Native Children Always Ride Safe (Native CARS) project.

PubMed

Lapidus, Jodi A; Smith, Nicole Holdaway; Lutz, Tam; Ebel, Beth E

2013-02-01

We compared proportions of children properly restrained in vehicles in 6 Northwest American Indian tribes in 2003 and 2009, and evaluated risks for improper restraint. During spring 2009 we conducted a vehicle observation survey in Oregon, Washington, and Idaho tribal communities. We estimated the proportions of children riding properly restrained and evaluated correlates of improper restraint via log-binomial regression models for clustered data. We observed 1853 children aged 12 years and younger in 1207 vehicles; 49% rode properly restrained. More children aged 8 years and younger rode properly restrained in 2009 than 2003 (51% vs 29%; P < .001). Older booster seat-eligible children were least likely to ride properly restrained in 2009 (25%). American Indian children were more likely to ride improperly restrained than nonnative children in the same communities. Other risk factors included riding with an unrestrained or nonparent driver, riding where child passenger restraint laws were weaker than national guidelines, and taking a short trip. Although proper restraint has increased, it remains low. Tribe-initiated interventions to improve child passenger restraint use are under way.

Electronic fetal heart rate monitoring and its relationship to neonatal and infant mortality in the United States.

PubMed

Chen, Han-Yang; Chauhan, Suneet P; Ananth, Cande V; Vintzileos, Anthony M; Abuhamad, Alfred Z

2011-06-01

To examine the association between electronic fetal heart rate monitoring and neonatal and infant mortality, as well as neonatal morbidity. We used the United States 2004 linked birth and infant death data. Multivariable log-binomial regression models were fitted to estimate risk ratio for association between electronic fetal heart rate monitoring and mortality, while adjusting for potential confounders. In 2004, 89% of singleton pregnancies had electronic fetal heart rate monitoring. Electronic fetal heart rate monitoring was associated with significantly lower infant mortality (adjusted relative risk, 0.75); this was mainly driven by the lower risk of early neonatal mortality (adjusted relative risk, 0.50). In low-risk pregnancies, electronic fetal heart rate monitoring was associated with decreased risk for Apgar scores <4 at 5 minutes (relative risk, 0.54); in high-risk pregnancies, with decreased risk of neonatal seizures (relative risk, 0.65). In the United States, the use of electronic fetal heart rate monitoring was associated with a substantial decrease in early neonatal mortality and morbidity that lowered infant mortality. Copyright © 2011 Mosby, Inc. All rights reserved.

Risk factors for persistent cervical intraepithelial neoplasia grades 1 and 2: managed by watchful waiting.

PubMed

Ho, Gloria Y F; Einstein, Mark H; Romney, Seymour L; Kadish, Anna S; Abadi, Maria; Mikhail, Magdy; Basu, Jayasri; Thysen, Benjamin; Reimers, Laura; Palan, Prabhudas R; Trim, Shelly; Soroudi, Nafisseh; Burk, Robert D

2011-10-01

: This study examines risk factors for persistent cervical intraepithelial neoplasia (CIN) and examines whether human papillomavirus (HPV) testing predicts persistent lesions. : Women with histologically diagnosed CIN 1 or CIN 2 (n = 206) were followed up every 3 months without treatment. Human papillomavirus genotyping, plasma levels of ascorbic acid, and red blood cell folate levels were obtained. Cervical biopsy at 12 months determined the presence of CIN. Relative risk (RR) was estimated by log-linked binomial regression models. : At 12 months, 70% of CIN 1 versus 54% of CIN 2 lesions spontaneously regressed (p < .001). Levels of folate or ascorbic acid were not associated with persistent CIN at 12 months. Compared with HPV-negative women, those with multiple HPV types (RRs ranged from 1.68 to 2.17 at each follow-up visit) or high-risk types (RRs range = 1.74-2.09) were at increased risk for persistent CIN; women with HPV-16/18 had the highest risk (RRs range = 1.91-2.21). Persistent infection with a high-risk type was also associated with persistent CIN (RRs range = 1.50-2.35). Typing for high-risk HPVs at 6 months only had a sensitivity of 46% in predicting persistence of any lesions at 12 months. : Spontaneous regression of CIN 1 and 2 occurs frequently within 12 months. Human papillomavirus infection is the major risk factor for persistent CIN. However, HPV testing cannot reliably predict persistence of any lesion.

Multivariate regression model for predicting lumber grade volumes of northern red oak sawlogs

Treesearch

Daniel A. Yaussy; Robert L. Brisbin

1983-01-01

A multivariate regression model was developed to predict green board-foot yields for the seven common factory lumber grades processed from northern red oak (Quercus rubra L.) factory grade logs. The model uses the standard log measurements of grade, scaling diameter, length, and percent defect. It was validated with an independent data set. The model...

Predicting Children's Asthma Hospitalizations: Rural and Urban Differences in Texas

ERIC Educational Resources Information Center

Grineski, Sara E.

2009-01-01

Asthma is the number one chronic health condition facing children today; however, little is known about rural-urban inequalities in asthma. This "area effects on health" study examines rural-urban differences in childhood asthma hospitalizations within the state of Texas using negative binomial regression models. Effects associated with…

The role of obesity in the relation between total water intake and urine osmolality in US adults, 2009-2012.

PubMed

Rosinger, Asher Y; Lawman, Hannah G; Akinbami, Lara J; Ogden, Cynthia L

2016-12-01

Adequate water intake is critical to physiologic and cognitive functioning. Although water requirements increase with body size, it remains unclear whether weight status modifies the relation between water intake and hydration status. We examined how the association between water intake and urine osmolality, which is a hydration biomarker, varied by weight status. NHANES cross-sectional data (2009-2012) were analyzed in 9601 nonpregnant adults aged ≥20 y who did not have kidney failure. Weight status was categorized with the use of body mass index on the basis of measured height and weight (underweight or normal weight, overweight, and obesity). Urine osmolality was determined with the use of freezing-point depression osmometry. Hypohydration was classified according to the following age-dependent formula: ≥831 mOsm/kg - [3.4 × (age - 20 y)]. Total water intake was determined with the use of a 24-h dietary recall and was dichotomized as adequate or low on the basis of the Institute of Medicine's adequate intake recommendations for men and women (men: ≥3.7 or <3.7 L; nonlactating women: ≥2.7 or <2.7 L; lactating women: ≥3.8 or <3.8 L for adequate or low intakes, respectively). We tested interactions and conducted linear and log-binomial regressions. Total water intake (P = 0.002), urine osmolality (P < 0.001), and hypohydration prevalence (P < 0.001) all increased with higher weight status. Interactions between weight status and water intake status were significant in linear (P = 0.005) and log-binomial (P = 0.015) models, which were then stratified. The prevalence ratio of hypohydration between subjects with adequate water intake and those with low water intake was 0.56 (95% CI: 0.43, 0.73) in adults who were underweight or normal weight, 0.67 (95% CI: 0.57, 0.79) in adults who were overweight, and 0.78 (95% CI: 0.70, 0.88) in adults who were obese. On a population level, obesity modifies the association between water intake and hydration status. © 2016 American Society for Nutrition.

A statistical model to estimate the impact of a hepatitis A vaccination programme.

PubMed

Oviedo, Manuel; Pilar Muñoz, M; Domínguez, Angela; Borras, Eva; Carmona, Gloria

2008-11-11

A program of routine hepatitis A+B vaccination in preadolescents was introduced in 1998 in Catalonia, a region situated in the northeast of Spain. The objective of this study was to quantify the reduction in the incidence of hepatitis A in order to differentiate the natural reduction of the incidence of hepatitis A from that produced due to the vaccination programme and to predict the evolution of the disease in forthcoming years. A generalized linear model (GLM) using negative binomial regression was used to estimate the incidence rates of hepatitis A in Catalonia by year, age group and vaccination. Introduction of the vaccine reduced cases by 5.5 by year (p-value<0.001), but there was a significant interaction between the year of report and vaccination that smoothed this reduction (p-value<0.001). The reduction was not equal in all age groups, being greater in the 12-18 years age group, which fell from a mean rate of 8.15 per 100,000 person/years in the pre-vaccination period (1992-1998) to 1.4 in the vaccination period (1999-2005). The model predicts the evolution accurately for the group of vaccinated subjects. Negative binomial regression is more appropriate than Poisson regression when observed variance exceeds the observed mean (overdispersed count data), can cause a variable apparently contribute more on the model of what really makes it.

Five-Year Incidence of Visual Impairment in Middle-Aged Iranians: The Shahroud Eye Cohort Study.

PubMed

Hashemi, Hassan; Mehravaran, Shiva; Emamian, Mohammad Hassan; Fotouhi, Akbar

2017-02-01

To study the 5-year incidence of visual impairment and its causes and risk factors, in the middle-aged Iranian sample of the Shahroud Eye Cohort Study (ShECS). Data from subjects who had participated in both phases of the ShECS were used to determine age- and sex-specific incidence rates of visual impairment using the World Health Organization (WHO) definitions for bilateral low vision (visual acuity, VA, >0.5 and ≤1.3 LogMAR in the better eye) and blindness (VA worse than 1.3 LogMAR in the better eye). Risk ratios (RR) and 95% confidence intervals (CIs) were calculated using multivariable log-binomial regression. Of the 5079 ShECS I survivors, 4737 (93.3%) completed the 5-year follow-up. Their mean age at baseline was 50.9 ± 6.2 years, and 58.9% were female. The incidence of visual impairment was 1.12% (95% CI 0.82-1.42%) by presenting VA and 0.19% (95% CI 0.07-0.32%) by best-corrected VA; leading causes of the former were uncorrected refractive error (81.3%) and diabetic retinopathy (15.1%). In the multivariable model, risk factors for incident visual impairment by presenting VA were older age (RR 1.05, p = 0.044), lower education (RR 0.89, p = 0.002), and diabetes (RR 3.74, p < 0.001). This is the first incidence study of visual impairment in a middle-aged Iranian population. Since age is a major risk factor, the number of visually impaired is expected to increase as the population ages, and less treatable causes such as diabetic retinopathy begin to surface. Measures for tackling uncorrected refractive error and enhancing diabetes screening and preventive programs are recommended.

Minimizing bias in biomass allometry: Model selection and log transformation of data

Treesearch

Joseph Mascaro; undefined undefined; Flint Hughes; Amanda Uowolo; Stefan A. Schnitzer

2011-01-01

Nonlinear regression is increasingly used to develop allometric equations for forest biomass estimation (i.e., as opposed to the raditional approach of log-transformation followed by linear regression). Most statistical software packages, however, assume additive errors by default, violating a key assumption of allometric theory and possibly producing spurious models....

A Multi-temporal Analysis of Logging Impacts on Tropical Forest Structure Using Airborne Lidar Data

NASA Astrophysics Data System (ADS)

Keller, M. M.; Pinagé, E. R.; Duffy, P.; Longo, M.; dos-Santos, M. N.; Leitold, V.; Morton, D. C.

2017-12-01

The long-term impacts of selective logging on carbon cycling and ecosystem function in tropical-forests are still uncertain. Despite improvements in selective logging detection using satellite data, quantifying changes in forest structure from logging and recovery following logging is difficult using orbital data. We analyzed the dynamics of forest structure comparing logged and unlogged forests in the Eastern Brazilian Amazon (Paragominas Municipality, Pará State) using small footprint discrete return airborne lidar data acquired in 2012 and 2014. Logging operations were conducted at the 1200 ha study site from 2006 through 2013 using reduced impact logging techniques—management practices that minimize canopy and ground damage compared to more common conventional logging. Nevertheless, logging still reduced aboveground biomass by 10% to 20% in logged areas compared to intact forests. We aggregated lidar point-cloud data at spatial scales ranging from 50 m to 250 m and developed a binomial classification model based on the height distribution of lidar returns in 2012 and validated the model against the 2014 lidar acquisition. We accurately classified intact and logged forest classes compared with field data. Classification performance improved as spatial resolution increased (AUC = 0.974 at 250 m). We analyzed the differences in canopy gaps, understory damage (based on a relative density model), and biomass (estimated from total canopy height) of intact and logged classes. As expected, logging greatly increased both canopy gap formation and understory damage. However, while the area identified as canopy gap persisted for at least 8 years (from the oldest logging treatments in 2006 to the most recent lidar acquisition in 2014), the effects of ground damage were mostly erased by vigorous understory regrowth after about 5 years. The rate of new gap formation was 6 to 7 times greater in recently logged forests compared to undisturbed forests. New gaps opened at a rate of 1.8 times greater than background even 8 years following logging demonstrating the occurrence of delayed tree mortality. Our study showed that even low-intensity anthropogenic disturbances can cause persistent changes in tropical forest structure and dynamics.

Re-employment, job quality, health and allostatic load biomarkers: prospective evidence from the UK Household Longitudinal Study

PubMed Central

Chandola, Tarani; Zhang, Nan

2018-01-01

Abstract Background There is little evidence on whether becoming re-employed in poor quality work is better for health and well-being than remaining unemployed. We examined associations of job transition with health and chronic stress-related biomarkers among a population-representative cohort of unemployed British adults. Methods A prospective cohort of 1116 eligible participants aged 35 to 75 years, who were unemployed at wave 1 (2009/10) of the UK Household Longitudinal Study, were followed up at waves 2 (2010/11) and 3 (2011/12) for allostatic load biomarkers and self-reported health. Negative binomial and multiple regression models estimated the association between job adversity and these outcomes. Results Compared with adults who remained unemployed, formerly unemployed adults who transitioned into poor quality jobs had higher levels of overall allostatic load (0.51, 0.32–0.71), log HbA1c (0.06, <0.001–0.12), log triglycerides (0.39, 0.22–0.56), log C-reactive protein (0.45, 0.16–0.75), log fibrinogen (0.09, 0.01–0.17) and total cholesterol to high-density lipoprotein (HDL) ratio (1.38, 0.88–1.88). Moreover, physically healthier respondents at wave 1 were more likely to transition into good quality and poor quality jobs after 1 year than those who remained unemployed. Conclusions Formerly unemployed adults who transitioned into poor quality work had greater adverse levels of biomarkers compared with their peers who remained unemployed. The selection of healthier unemployed adults into these poor quality or stressful jobs was unlikely to explain their elevated levels of chronic stress-related biomarkers. Job quality cannot be disregarded from the employment success of the unemployed, and may have important implications for their health and well-being. PMID:29024973

Serum Vitamin D Levels and Markers of Severity of Childhood Asthma in Costa Rica

PubMed Central

Brehm, John M.; Celedón, Juan C.; Soto-Quiros, Manuel E.; Avila, Lydiana; Hunninghake, Gary M.; Forno, Erick; Laskey, Daniel; Sylvia, Jody S.; Hollis, Bruce W.; Weiss, Scott T.; Litonjua, Augusto A.

2009-01-01

Rationale: Maternal vitamin D intake during pregnancy has been inversely associated with asthma symptoms in early childhood. However, no study has examined the relationship between measured vitamin D levels and markers of asthma severity in childhood. Objectives: To determine the relationship between measured vitamin D levels and both markers of asthma severity and allergy in childhood. Methods: We examined the relation between 25-hydroxyvitamin D levels (the major circulating form of vitamin D) and markers of allergy and asthma severity in a cross-sectional study of 616 Costa Rican children between the ages of 6 and 14 years. Linear, logistic, and negative binomial regressions were used for the univariate and multivariate analyses. Measurements and Main Results: Of the 616 children with asthma, 175 (28%) had insufficient levels of vitamin D (<30 ng/ml). In multivariate linear regression models, vitamin D levels were significantly and inversely associated with total IgE and eosinophil count. In multivariate logistic regression models, a log10 unit increase in vitamin D levels was associated with reduced odds of any hospitalization in the previous year (odds ratio [OR], 0.05; 95% confidence interval [CI], 0.004–0.71; P = 0.03), any use of antiinflammatory medications in the previous year (OR, 0.18; 95% CI, 0.05–0.67; P = 0.01), and increased airway responsiveness (a ≤8.58-μmol provocative dose of methacholine producing a 20% fall in baseline FEV1 [OR, 0.15; 95% CI, 0.024–0.97; P = 0.05]). Conclusions: Our results suggest that vitamin D insufficiency is relatively frequent in an equatorial population of children with asthma. In these children, lower vitamin D levels are associated with increased markers of allergy and asthma severity. PMID:19179486

Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

Racial Threat and White Opposition to Bilingual Education in Texas

ERIC Educational Resources Information Center

Hempel, Lynn M.; Dowling, Julie A.; Boardman, Jason D.; Ellison, Christopher G.

2013-01-01

This study examines local contextual conditions that influence opposition to bilingual education among non-Hispanic Whites, net of individual-level characteristics. Data from the Texas Poll (N = 615) are used in conjunction with U.S. Census data to test five competing hypotheses using binomial and multinomial logistic regression models. Our…

Predicting clicks of PubMed articles.

PubMed

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed.

Predicting clicks of PubMed articles

PubMed Central

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed. PMID:24551386

Neighborhood educational disparities in active commuting among women: the effect of distance between the place of residence and the place of work/study (an ACTI-Cités study).

PubMed

Perchoux, Camille; Nazare, Julie-Anne; Benmarhnia, Tarik; Salze, Paul; Feuillet, Thierry; Hercberg, Serge; Hess, Franck; Menai, Mehdi; Weber, Christiane; Charreire, Hélène; Enaux, Christophe; Oppert, Jean-Michel; Simon, Chantal

2017-06-12

Active transportation has been associated with favorable health outcomes. Previous research highlighted the influence of neighborhood educational level on active transportation. However, little is known regarding the effect of commuting distance on social disparities in active commuting. In this regard, women have been poorly studied. The objective of this paper was to evaluate the relationship between neighborhood educational level and active commuting, and to assess whether the commuting distance modifies this relationship in adult women. This cross-sectional study is based on a subsample of women from the Nutrinet-Santé web-cohort (N = 1169). Binomial, log-binomial and negative binomial regressions were used to assess the associations between neighborhood education level and (i) the likelihood of reporting any active commuting time, and (ii) the share of commuting time made by active transportation modes. Potential effect measure modification of distance to work on the previous associations was assessed both on the additive and the multiplicative scales. Neighborhood education level was positively associated with the probability of reporting any active commuting time (relative risk = 1.774; p < 0.05) and the share of commuting time spent active (relative risk = 1.423; p < 0.05). The impact of neighborhood education was greater at long distances to work for both outcomes. Our results suggest that neighborhood educational disparities in active commuting tend to increase with commuting distance among women. Further research is needed to provide geographically driven guidance for health promotion intervention aiming at reducing disparities in active transportation among socioeconomic groups.

QSPR study of polychlorinated diphenyl ethers by molecular electronegativity distance vector (MEDV-4).

PubMed

Sun, Lili; Zhou, Liping; Yu, Yu; Lan, Yukun; Li, Zhiliang

2007-01-01

Polychlorinated diphenyl ethers (PCDEs) have received more and more concerns as a group of ubiquitous potential persistent organic pollutants (POPs). By using molecular electronegativity distance vector (MEDV-4), multiple linear regression (MLR) models are developed for sub-cooled liquid vapor pressures (P(L)), n-octanol/water partition coefficients (K(OW)) and sub-cooled liquid water solubilities (S(W,L)) of 209 PCDEs and diphenyl ether. The correlation coefficients (R) and the leave-one-out cross-validation (LOO) correlation coefficients (R(CV)) of all the 6-descriptor models for logP(L), logK(OW) and logS(W,L) are more than 0.98. By using stepwise multiple regression (SMR), the descriptors are selected and the resulting models are 5-descriptor model for logP(L), 4-descriptor model for logK(OW), and 6-descriptor model for logS(W,L), respectively. All these models exhibit excellent estimate capabilities for internal sample set and good predictive capabilities for external samples set. The consistency between observed and estimated/predicted values for logP(L) is the best (R=0.996, R(CV)=0.996), followed by logK(OW) (R=0.992, R(CV)=0.992) and logS(W,L) (R=0.983, R(CV)=0.980). By using MEDV-4 descriptors, the QSPR models can be used for prediction and the model predictions can hence extend the current database of experimental values.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

Early-life mortality risks in opposite-sex and same-sex twins: a Danish cohort study of the twin testosterone transfer hypothesis.

PubMed

Ahrenfeldt, Linda Juel; Larsen, Lisbeth Aagaard; Lindahl-Jacobsen, Rune; Skytthe, Axel; Hjelmborg, Jacob V B; Möller, Sören; Christensen, Kaare

2017-02-01

To investigate the twin testosterone transfer (TTT) hypothesis by comparing early-life mortality risks of opposite-sex (OS) and same-sex (SS) twins during the first 15 years of life. We performed a population-based cohort study to compare mortality in OS and SS twins. We included 68,629 live-born Danish twins from 1973 to 2009 identified through the Danish Twin Registry and performed piecewise stratified Cox regression and log-binomial regression. Among 1933 deaths, we found significantly higher mortality for twin boys than for twin girls. For both sexes, OS twins had lower mortality than SS twins; the difference persisted for the first year of life for boys and for the first week of life for girls. Although the mortality risk for OS boys was in the expected direction according to the TTT hypothesis, the results for OS girls pointed in the opposite direction, providing no clear evidence for the TTT hypothesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

Maternal Language and Adverse Birth Outcomes in a Statewide Analysis

PubMed Central

Sentell, Tetine; Chang, Ann; Jun Ahn, Hyeong; Miyamura, Jill

2016-01-01

Background Limited English proficiency is associated with disparities across diverse health outcomes. However, evidence regarding adverse birth outcomes across languages is limited, particularly among US Asian and Pacific Islander populations. The study goal was to consider the relationship of maternal language to birth outcomes using statewide hospitalization data. Methods Detailed discharge data from Hawai‘i childbirth hospitalizations from 2012 (n=11,419) were compared by maternal language (English language or not) for adverse outcomes using descriptive and multivariable log-binomial regression models, controlling for race/ethnicity, age group, and payer. Results Ten percent of mothers spoke a language other than English; 93% of these spoke an Asian or Pacific Islander language. In multivariable models, compared to English speakers non-English speakers had significantly higher risk (adjusted relative risk [ARR]: 2.02; 95% Confidence Interval [CI]: 1.34–3.04) of obstetric trauma in vaginal deliveries without instrumentation. Some significant variation was seen by language for other birth outcomes, including an increased rate of primary Caesarean sections and vaginal births after Caesarean among non-English speakers. Conclusions Non-English speakers had approximately two times higher risk of having an obstetric trauma during a vaginal birth when other factors, including race/ethnicity, were controlled. Non-English speakers also had higher rates of potentially high-risk deliveries. PMID:26361937

Maternal language and adverse birth outcomes in a statewide analysis.

PubMed

Sentell, Tetine; Chang, Ann; Ahn, Hyeong Jun; Miyamura, Jill

2016-01-01

Limited English proficiency is associated with disparities across diverse health outcomes. However, evidence regarding adverse birth outcomes across languages is limited, particularly among U.S. Asian and Pacific Islander populations. The study goal was to consider the relationship of maternal language to birth outcomes using statewide hospitalization data. Detailed discharge data from Hawaii childbirth hospitalizations from 2012 (n = 11,419) were compared by maternal language (English language or not) for adverse outcomes using descriptive and multivariable log-binomial regression models, controlling for race/ethnicity, age group, and payer. Ten percent of mothers spoke a language other than English; 93% of these spoke an Asian or Pacific Islander language. In multivariable models, compared to English speakers, non-English speakers had significantly higher risk (adjusted relative risk [ARR]: 2.02; 95% confidence interval [CI]: 1.34-3.04) of obstetric trauma in vaginal deliveries without instrumentation. Some significant variation was seen by language for other birth outcomes, including an increased rate of primary Caesarean sections and vaginal births after Caesarean, among non-English speakers. Non-English speakers had approximately two times higher risk of having an obstetric trauma during a vaginal birth when other factors, including race/ethnicity, were controlled. Non-English speakers also had higher rates of potentially high-risk deliveries.

Robust inference in the negative binomial regression model with an application to falls data.

PubMed

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effects of Cognition, Function, and Behavioral and Psychological Symptoms on Medicare Expenditures and Health Care Utilization for Persons With Dementia.

PubMed

Jutkowitz, Eric; Kane, Robert L; Dowd, Bryan; Gaugler, Joseph E; MacLehose, Richard F; Kuntz, Karen M

2017-06-01

Clinical features of dementia (cognition, function, and behavioral/psychological symptoms [BPSD]) may differentially affect Medicare expenditures/health care utilization. We linked cross-sectional data from the Aging, Demographics, and Memory Study to Medicare data to evaluate the association between dementia clinical features among those with dementia and Medicare expenditures/health care utilization (n = 234). Cognition was evaluated using the Mini-Mental State Examination (MMSE). Function was evaluated as the number of functional limitations (0-10). BPSD was evaluated as the number of symptoms (0-12). Expenditures were estimated with a generalized linear model (log-link and gamma distribution). Number of hospitalizations, institutional outpatient visits, and physician visits were estimated with a negative binomial regression. Medicare covered skilled nursing days were estimated with a zero-inflated negative binomial model. Cognition and BPSD were not associated with expenditures. Among individuals with less than seven functional limitations, one additional limitation was associated with $123 (95% confidence interval: $19-$227) additional monthly Medicare spending. Better cognition and poorer function were associated with more hospitalizations among those with an MMSE less than three and less than six functional limitations, respectively. BPSD had no effect on hospitalizations. Poorer function and fewer BPSD were associated with more skilled nursing among individuals with one to seven functional limitations and more than four symptoms, respectively. Cognition had no effect on skilled nursing care. No clinical feature was associated with institutional outpatient care. Of individuals with an MMSE less than 15, poorer cognition was associated with fewer physician visits. Among those with more than six functional limitations, poorer function was associated with fewer physician visits. Poorer function, not cognition or BPSD, was associated with higher Medicare expenditures. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Green lumber grade yields from factory grade logs of three oak species

Treesearch

Daniel A. Yaussy

1986-01-01

Multivariate regression models were developed to predict green board foot yields for the seven common factory lumber grades processed from white, black, and chestnut oak factory grade logs. These models use the standard log measurements of grade, scaling diameter, log length, and proportion of scaling defect. Any combination of lumber grades (such as 1 Common and...

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts

PubMed Central

Preisser, John S.; Long, D. Leann; Stamm, John W.

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two datasets, one consisting of fictional dmft counts in two groups and the other on DMFS among schoolchildren from a randomized clinical trial (RCT) comparing three toothpaste formulations to prevent incident dental caries, are analysed with negative binomial hurdle (NBH), zero-inflated negative binomial (ZINB), and marginalized zero-inflated negative binomial (MZINB) models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the RCT were similar despite their distinctive interpretations. Choice of statistical model class should match the study’s purpose, while accounting for the broad decline in children’s caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. PMID:28291962

Brief Report: HIV Assisted Partner Services Among Those With and Without a History of Intimate Partner Violence in Kenya.

PubMed

Goyette, Marielle S; Mutiti, Peter M; Bukusi, David; Wamuti, Beatrice M; Otieno, Felix A; Cherutich, Peter; Golden, Matthew R; Spiegel, Hans; Richardson, Barbra A; Ngʼangʼa, Anne; Farquhar, Carey

2018-05-01

HIV assisted partner services (APS) are a notification and testing strategy for sex partners of HIV-infected index patients. This cluster-randomized controlled trial secondary data analysis investigated whether history of intimate partner violence (IPV) modified APS effectiveness and risk of relationship dissolution. Eighteen HIV testing and counseling sites in Kenya randomized to provide immediate APS (intervention) or APS delayed for 6 weeks (control). History of IPV was ascertained at study enrollment and defined as reporting ever experiencing physical or sexual IPV. Those reporting IPV in the month before enrollment were excluded. We tested whether history of IPV modified intervention effectiveness and risk of relationship dissolution using population-averaged Poisson and log-binomial generalized estimating equation models. Exploratory analyses investigated associations between history of IPV and events that occurred after HIV diagnosis using log-binomial generalized estimating equation models. The study enrolled 1119 index participants and 1286 partners. Among index participants, 81 (7%) had history of IPV. History of IPV did not modify APS effectiveness in testing, newly diagnosing, or linking partners to care. History of IPV did not modify the association between receiving immediate APS and relationship dissolution during the study. Among participants who had not experienced IPV in the last month but had experienced IPV in their lifetimes, our results suggest that APS is an effective and safe partner notification strategy in Kenya. As APS is scaled up in different contexts, these data support including those reporting past IPV and closely monitoring adverse events.

Regular exercise and related factors in patients with Parkinson's disease: Applying zero-inflated negative binomial modeling of exercise count data.

PubMed

Lee, JuHee; Park, Chang Gi; Choi, Moonki

2016-05-01

This study was conducted to identify risk factors that influence regular exercise among patients with Parkinson's disease in Korea. Parkinson's disease is prevalent in the elderly, and may lead to a sedentary lifestyle. Exercise can enhance physical and psychological health. However, patients with Parkinson's disease are less likely to exercise than are other populations due to physical disability. A secondary data analysis and cross-sectional descriptive study were conducted. A convenience sample of 106 patients with Parkinson's disease was recruited at an outpatient neurology clinic of a tertiary hospital in Korea. Demographic characteristics, disease-related characteristics (including disease duration and motor symptoms), self-efficacy for exercise, balance, and exercise level were investigated. Negative binomial regression and zero-inflated negative binomial regression for exercise count data were utilized to determine factors involved in exercise. The mean age of participants was 65.85 ± 8.77 years, and the mean duration of Parkinson's disease was 7.23 ± 6.02 years. Most participants indicated that they engaged in regular exercise (80.19%). Approximately half of participants exercised at least 5 days per week for 30 min, as recommended (51.9%). Motor symptoms were a significant predictor of exercise in the count model, and self-efficacy for exercise was a significant predictor of exercise in the zero model. Severity of motor symptoms was related to frequency of exercise. Self-efficacy contributed to the probability of exercise. Symptom management and improvement of self-efficacy for exercise are important to encourage regular exercise in patients with Parkinson's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

PubMed

Sauzet, Odile; Peacock, Janet L

2017-07-20

The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

Trends and Correlates of Child Passenger Restraint Use in 6 Northwest Tribes: The Native Children Always Ride Safe (Native CARS) Project

PubMed Central

Smith, Nicole Holdaway; Lutz, Tam; Ebel, Beth E.

2013-01-01

Objectives. We compared proportions of children properly restrained in vehicles in 6 Northwest American Indian tribes in 2003 and 2009, and evaluated risks for improper restraint. Methods. During spring 2009 we conducted a vehicle observation survey in Oregon, Washington, and Idaho tribal communities. We estimated the proportions of children riding properly restrained and evaluated correlates of improper restraint via log-binomial regression models for clustered data. Results. We observed 1853 children aged 12 years and younger in 1207 vehicles; 49% rode properly restrained. More children aged 8 years and younger rode properly restrained in 2009 than 2003 (51% vs 29%; P < .001). Older booster seat–eligible children were least likely to ride properly restrained in 2009 (25%). American Indian children were more likely to ride improperly restrained than nonnative children in the same communities. Other risk factors included riding with an unrestrained or nonparent driver, riding where child passenger restraint laws were weaker than national guidelines, and taking a short trip. Conclusions. Although proper restraint has increased, it remains low. Tribe-initiated interventions to improve child passenger restraint use are under way. PMID:23237177

Maternal sleep and small for gestational age infants in the Japan Environment and Children's Study: a cohort study.

PubMed

Morokuma, Seiichi; Shimokawa, Mototsugu; Kato, Kiyoko; Sanefuji, Masafumi; Shibata, Eiji; Tsuji, Mayumi; Senju, Ayako; Kawamoto, Toshihiro; Kusuhara, Koichi

2017-08-11

Small for gestational age infants have an increased risk of immediate complications, short-term morbidity and mortality, and long-term neurologic and metabolic disorders in adulthood. Previous research has shown that reduced sleep duration is a risk factor for SGA birth. However, only a few studies have evaluated maternal sleep as a risk factor for SGA birth. In the present study, we investigated the relationship between the amount and quality of mothers' sleep and infants' birth weight. This cohort study (n = 8631) used data from the Japan Environment and Children's Study, an ongoing cohort study that began in January 2011. Data on sleep status (sleep duration and one indicator of sleep quality) and potential confounding factors were recorded. A log-binomial regression model was used to estimate the risk of small for gestational age birth, and the results were expressed as risk ratios and their respective 95% confidence interval. No significant results were observed for sleep duration or tiredness upon waking. Neither the amount nor the quality of mothers' sleep was associated with the risk of small for gestational age birth.

Effect of asthma and PTSD on persistence and onset of gastroesophageal reflux symptoms among adults exposed to the September 11, 2001, terrorist attacks.

PubMed

Li, Jiehui; Brackbill, Robert M; Jordan, Hannah T; Cone, James E; Farfel, Mark R; Stellman, Steven D

2016-09-01

Little is known about the direction of causality among asthma, posttraumatic stress disorder (PTSD), and onset of gastroesophageal reflux symptoms (GERS) after exposure to the 9/11/2001 World Trade Center (WTC) disaster. Using data from the WTC Health Registry, we investigated the effects of early diagnosed post-9/11 asthma and PTSD on the late onset and persistence of GERS using log-binomial regression, and examined whether PTSD mediated the asthma-GERS association using structural equation modeling. Of 29,406 enrollees, 23% reported GERS at follow-up in 2011-2012. Early post-9/11 asthma and PTSD were each independently associated with both the persistence of GERS that was present at baseline and the development of GERS in persons without a prior history. PTSD mediated the association between early post-9/11 asthma and late-onset GERS. Clinicians should assess patients with post-9/11 GERS for comorbid asthma and PTSD, and plan medical care for these conditions in an integrated fashion. Am. J. Ind. Med. 59:805-814, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Integrating HIV Surveillance and Field Services: Data Quality and Care Continuum in King County, Washington, 2010-2015.

PubMed

Hood, Julia E; Katz, David A; Bennett, Amy B; Buskin, Susan E; Dombrowski, Julia C; Hawes, Stephen E; Golden, Matthew R

2017-12-01

To assess how integration of HIV surveillance and field services might influence surveillance data and linkage to care metrics. We used HIV surveillance and field services data from King County, Washington, to assess potential impact of misclassification of prior diagnoses on numbers of new diagnoses. The relationship between partner services and linkage to care was evaluated with multivariable log-binomial regression models. Of the 2842 people who entered the King County HIV Surveillance System in 2010 to 2015, 52% were newly diagnosed, 41% had a confirmed prior diagnosis in another state, and 7% had an unconfirmed prior diagnosis. Twelve percent of those classified as newly diagnosed for purposes of national HIV surveillance self-reported a prior HIV diagnosis that was unconfirmed. Partner services recipients were more likely than nonrecipients to link to care within 30 days (adjusted risk ratio [RR] = 1.10; 95% confidence interval [CI] = 1.03, 1.18) and 90 days (adjusted RR = 1.07; 95% CI = 1.01, 1.14) of diagnosis. Integration of HIV surveillance, partner services, and care linkage efforts may improve the accuracy of HIV surveillance data and facilitate timely linkage to care.

Prevalence and risk factors of musculoskeletal disorders among Sri Lankan rubber tappers

PubMed Central

de Silva, Vijitha; Tharindra, Hemajith; Ostbye, Truls

2016-01-01

Background Rubber tapping exposes workers to risk factors for musculoskeletal disorders (MSDs). Objectives This cross-sectional study assessed the prevalence and factors associated with MSDs among Sri Lankan rubber tappers. Methods Questionnaires were administered to 300 rubber tappers to measure MSDs and potential associated factors. Ergonomic exposure levels were measured for 90 tappers using the Quick Exposure Check instrument. MSD prevalence and prevalence ratios were calculated using log-binomial regression. Results In the past 12 months, 66% of rubber tappers in our sample experienced an MSD. Ergonomic exposure levels were high or very high in the back (94.4%), shoulders (96.7%), and neck (83.3%). Being female, older, Tamil, working two jobs, alternating tapping hands, and depression were significantly associated with increased risk of MSDs. Conclusions MSDs are common among rubber tappers in Sri Lanka. These results suggest a need for work process modifications to prevent MSDs. PMID:27092589

Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

PubMed

Taslimitehrani, Vahid; Dong, Guozhu; Pereira, Naveen L; Panahiazar, Maryam; Pathak, Jyotishman

2016-04-01

Computerized survival prediction in healthcare identifying the risk of disease mortality, helps healthcare providers to effectively manage their patients by providing appropriate treatment options. In this study, we propose to apply a classification algorithm, Contrast Pattern Aided Logistic Regression (CPXR(Log)) with the probabilistic loss function, to develop and validate prognostic risk models to predict 1, 2, and 5year survival in heart failure (HF) using data from electronic health records (EHRs) at Mayo Clinic. The CPXR(Log) constructs a pattern aided logistic regression model defined by several patterns and corresponding local logistic regression models. One of the models generated by CPXR(Log) achieved an AUC and accuracy of 0.94 and 0.91, respectively, and significantly outperformed prognostic models reported in prior studies. Data extracted from EHRs allowed incorporation of patient co-morbidities into our models which helped improve the performance of the CPXR(Log) models (15.9% AUC improvement), although did not improve the accuracy of the models built by other classifiers. We also propose a probabilistic loss function to determine the large error and small error instances. The new loss function used in the algorithm outperforms other functions used in the previous studies by 1% improvement in the AUC. This study revealed that using EHR data to build prediction models can be very challenging using existing classification methods due to the high dimensionality and complexity of EHR data. The risk models developed by CPXR(Log) also reveal that HF is a highly heterogeneous disease, i.e., different subgroups of HF patients require different types of considerations with their diagnosis and treatment. Our risk models provided two valuable insights for application of predictive modeling techniques in biomedicine: Logistic risk models often make systematic prediction errors, and it is prudent to use subgroup based prediction models such as those given by CPXR(Log) when investigating heterogeneous diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

Understanding poisson regression.

PubMed

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

[Analysis on prevalence of physical activity time <1 hour and related factors in students aged 9-22 years in China, 2014].

PubMed

Wang, Z H; Dong, Y H; Song, Y; Yang, Z P; Ma, J

2017-03-10

Objective: To explore the prevalence of physical activity time <1 hour and related factors in students aged 9-22 years in China. Methods: A total of 220 159 students (110 039 boys and 110 120 girls) aged 9-22 years who completed the questionnaire of physical activity and lifestyle behaviors were selected from " 2014 National Physical Fitness and Health Surveillance" for the current study. All the participants were divided into 2 groups, i.e. physical activity time <1 hour and physical activity time ≥1 hour according the suggestion of Central Government, stratified by age and gender. χ (2) tests were used to compare the difference in the prevalence of physical activity time <1 hour between boys and girls in every age groups. Univariate and multivariate log-binomial regression models were used to explore the factors that influenced the prevalence of physical activity time <1 hour. Results: The boy's prevalence of physical activity time <1 hour was 73.3%, with the lowest (57.0%) in 9-years-old group, and highest (82.5%) in 18 years old group. The girl's prevalence of physical activity time <1 hour was 79.1%, with the lowest (60.1%) in 9-years-old group, and highest (89.8%) in 21 years old group. Overall, The prevalence of physical activity time <1 hour was significantly higher in girls than in boys ( P <0.001), and the prevalence were significantly higher in girls than in boys in all the age groups ( P <0.001), and it was observed that the prevalence of physical activity <1 hour increased with age in both boys and girls ( P <0.001). Multivariate log-binomial regression model found that being girl ( PR =1.05, 95 %CI : 1.05-1.06), parents' disliking children to participate physical activity ( PR =1.08, 95 % CI : 1.07-1.09), heavy homework ( PR =1.13, 95 % CI : 1.12-1.14), long homework time ( PR =1.08, 95 %CI : 1.07-1.08), long time spending on electronic screen watching ( PR =1.01, 95 %CI : 1.00-1.01) and disliking physical class ( PR =1.11, 95 %CI : 1.10-1.12) could be the risk factors for physical activity time <1 hour, however, living in rural area ( PR =0.99, 95 % CI : 0.98-0.99) and no supporting from parents for children to participate physical activity ( PR =0.99, 95 %CI : 1.98-1.00) could be the protective factors, but no consistent association with the time of TV watching was observed ( P =0.226). Conclusions: The prevalence of physical activity time <1 hour was high in students aged 9-22 years in China. Female, parents; disliking children to participate physical activity, heavy homework, long homework time, long electronic screen watching time and disliking physical class might be the risk factors.

A comparison of methods to handle skew distributed cost variables in the analysis of the resource consumption in schizophrenia treatment.

PubMed

Kilian, Reinhold; Matschinger, Herbert; Löeffler, Walter; Roick, Christiane; Angermeyer, Matthias C

2002-03-01

Transformation of the dependent cost variable is often used to solve the problems of heteroscedasticity and skewness in linear ordinary least square regression of health service cost data. However, transformation may cause difficulties in the interpretation of regression coefficients and the retransformation of predicted values. The study compares the advantages and disadvantages of different methods to estimate regression based cost functions using data on the annual costs of schizophrenia treatment. Annual costs of psychiatric service use and clinical and socio-demographic characteristics of the patients were assessed for a sample of 254 patients with a diagnosis of schizophrenia (ICD-10 F 20.0) living in Leipzig. The clinical characteristics of the participants were assessed by means of the BPRS 4.0, the GAF, and the CAN for service needs. Quality of life was measured by WHOQOL-BREF. A linear OLS regression model with non-parametric standard errors, a log-transformed OLS model and a generalized linear model with a log-link and a gamma distribution were used to estimate service costs. For the estimation of robust non-parametric standard errors, the variance estimator by White and a bootstrap estimator based on 2000 replications were employed. Models were evaluated by the comparison of the R2 and the root mean squared error (RMSE). RMSE of the log-transformed OLS model was computed with three different methods of bias-correction. The 95% confidence intervals for the differences between the RMSE were computed by means of bootstrapping. A split-sample-cross-validation procedure was used to forecast the costs for the one half of the sample on the basis of a regression equation computed for the other half of the sample. All three methods showed significant positive influences of psychiatric symptoms and met psychiatric service needs on service costs. Only the log- transformed OLS model showed a significant negative impact of age, and only the GLM shows a significant negative influences of employment status and partnership on costs. All three models provided a R2 of about.31. The Residuals of the linear OLS model revealed significant deviances from normality and homoscedasticity. The residuals of the log-transformed model are normally distributed but still heteroscedastic. The linear OLS model provided the lowest prediction error and the best forecast of the dependent cost variable. The log-transformed model provided the lowest RMSE if the heteroscedastic bias correction was used. The RMSE of the GLM with a log link and a gamma distribution was higher than those of the linear OLS model and the log-transformed OLS model. The difference between the RMSE of the linear OLS model and that of the log-transformed OLS model without bias correction was significant at the 95% level. As result of the cross-validation procedure, the linear OLS model provided the lowest RMSE followed by the log-transformed OLS model with a heteroscedastic bias correction. The GLM showed the weakest model fit again. None of the differences between the RMSE resulting form the cross- validation procedure were found to be significant. The comparison of the fit indices of the different regression models revealed that the linear OLS model provided a better fit than the log-transformed model and the GLM, but the differences between the models RMSE were not significant. Due to the small number of cases in the study the lack of significance does not sufficiently proof that the differences between the RSME for the different models are zero and the superiority of the linear OLS model can not be generalized. The lack of significant differences among the alternative estimators may reflect a lack of sample size adequate to detect important differences among the estimators employed. Further studies with larger case number are necessary to confirm the results. Specification of an adequate regression models requires a careful examination of the characteristics of the data. Estimation of standard errors and confidence intervals by nonparametric methods which are robust against deviations from the normal distribution and the homoscedasticity of residuals are suitable alternatives to the transformation of the skew distributed dependent variable. Further studies with more adequate case numbers are needed to confirm the results.

Development of a mobbing short scale in the Gutenberg Health Study.

PubMed

Garthus-Niegel, Susan; Nübling, Matthias; Letzel, Stephan; Hegewald, Janice; Wagner, Mandy; Wild, Philipp S; Blettner, Maria; Zwiener, Isabella; Latza, Ute; Jankowiak, Sylvia; Liebers, Falk; Seidler, Andreas

2016-01-01

Despite its highly detrimental potential, most standard questionnaires assessing psychosocial stress at work do not include mobbing as a risk factor. In the German standard version of COPSOQ, mobbing is assessed with a single item. In the Gutenberg Health Study, this version was used together with a newly developed short scale based on the Leymann Inventory of Psychological Terror. The purpose of the present study was to evaluate the psychometric properties of these two measures, to compare them and to test their differential impact on relevant outcome parameters. This analysis is based on a population-based sample of 1441 employees participating in the Gutenberg Health Study. Exploratory and confirmatory factor analyses and reliability analyses were used to assess the mobbing scale. To determine their predictive validities, multiple linear regression analyses with six outcome parameters and log-binomial regression models for two of the outcome aspects were run. Factor analyses of the five-item scale confirmed a one-factor solution, reliability was α = 0.65. Both the single-item and the five-item scales were associated with all six outcome scales. Effect sizes were similar for both mobbing measures. Mobbing is an important risk factor for health-related outcomes. For the purpose of psychosocial risk assessment in the workplace, both the single-item and the five-item constructs were psychometrically appropriate. Associations with outcomes were about equivalent. However, the single item has the advantage of parsimony, whereas the five-item construct depicts several distinct forms of mobbing.

Financial Data Analysis by means of Coupled Continuous-Time Random Walk in Rachev-Rűschendorf Model

NASA Astrophysics Data System (ADS)

Jurlewicz, A.; Wyłomańska, A.; Żebrowski, P.

2008-09-01

We adapt the continuous-time random walk formalism to describe asset price evolution. We expand the idea proposed by Rachev and Rűschendorf who analyzed the binomial pricing model in the discrete time with randomization of the number of price changes. As a result, in the framework of the proposed model we obtain a mixture of the Gaussian and a generalized arcsine laws as the limiting distribution of log-returns. Moreover, we derive an European-call-option price that is an extension of the Black-Scholes formula. We apply the obtained theoretical results to model actual financial data and try to show that the continuous-time random walk offers alternative tools to deal with several complex issues of financial markets.

Do Barriers to Crime Prevention Moderate the Effects of Situational Crime Prevention Policies on Violent Crime in High Schools?

ERIC Educational Resources Information Center

Sevigny, Eric L.; Zhang, Gary

2018-01-01

This study investigates how barriers to school-based crime prevention programming moderate the effects of situational crime prevention (SCP) policies on levels of violent crime in U.S. public high schools. Using data from the 2008 School Survey on Crime and Safety, we estimate a series of negative binomial regression models with interactions to…

Green lumber grade yields from black cherry and red maple factory grade logs sawed at band and circular mills

Treesearch

Daniel A. Yaussy

1989-01-01

Multivariate regression models were developed to predict green board-foot yields (1 board ft. = 2.360 dm 3) for the standard factory lumber grades processed from black cherry (Prunus serotina Ehrh.) and red maple (Acer rubrum L.) factory grade logs sawed at band and circular sawmills. The models use log...

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany

PubMed Central

Wang, Zhu; Shuangge, Ma; Wang, Ching-Yun

2017-01-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using an open-source R package mpath. PMID:26059498

Three-parameter modeling of the soil sorption of acetanilide and triazine herbicide derivatives.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2014-02-01

Herbicides have widely variable toxicity and many of them are persistent soil contaminants. Acetanilide and triazine family of herbicides have widespread use, but increasing interest for the development of new herbicides has been rising to increase their effectiveness and to diminish environmental hazard. The environmental risk of new herbicides can be accessed by estimating their soil sorption (logKoc), which is usually correlated to the octanol/water partition coefficient (logKow). However, earlier findings have shown that this correlation is not valid for some acetanilide and triazine herbicides. Thus, easily accessible quantitative structure-property relationship models are required to predict logKoc of analogues of the these compounds. Octanol/water partition coefficient, molecular weight and volume were calculated and then regressed against logKoc for two series of acetanilide and triazine herbicides using multiple linear regression, resulting in predictive and validated models.

Review and Recommendations for Zero-inflated Count Regression Modeling of Dental Caries Indices in Epidemiological Studies

PubMed Central

Stamm, John W.; Long, D. Leann; Kincade, Megan E.

2012-01-01

Over the past five to ten years, zero-inflated count regression models have been increasingly applied to the analysis of dental caries indices (e.g., DMFT, dfms, etc). The main reason for that is linked to the broad decline in children’s caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of zero-inflated Poisson and zero-inflated negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries. PMID:22710271

Olfactory function and neurocognitive outcomes in old age: The Atherosclerosis Risk in Communities Neurocognitive Study.

PubMed

Palta, Priya; Chen, Honglei; Deal, Jennifer A; Sharrett, A Richey; Gross, Alden; Knopman, David; Griswold, Michael; Heiss, Gerardo; Mosley, Thomas H

2018-03-30

We tested the hypothesis that poor sense of smell is associated with lower cognitive function and higher mild cognitive impairment (MCI) prevalence. Olfaction, measured by the Sniffin' Sticks test, was categorized as olfactory impairment (OI) (score ≤6) or no OI (score >6). MCI was adjudicated based on review of a neuropsychological examination. Linear regression estimated the mean difference in cognitive factor scores, and log-binomial regression quantified MCI prevalence among participants with versus without OI. Participants with OI had lower mean factor scores (memory: -0.27 standard deviation [SD], 95% confidence interval [CI]: -0.35 to -0.19; language: -0.24 SD, 95% CI: -0.30 to -0.17; executive function/processing speed: -0.09 SD, 95% CI: -0.12 to -0.06; and general cognitive performance: -0.25 SD, 95% CI: -0.30 to -0.20). OI was also associated with MCI (n = 204; prevalence ratio = 1.56, 95% CI: 1.37, 1.78). An impaired sense of smell may serve as a readily accessible early marker of neurodegeneration and improve upon the prevailing delayed diagnoses and underascertainment of MCI/dementia. Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Sickness absence and psychosocial job quality: an analysis from a longitudinal survey of working Australians, 2005-2012.

PubMed

Milner, Allison; Butterworth, Peter; Bentley, Rebecca; Kavanagh, Anne M; LaMontagne, Anthony D

2015-05-15

Sickness absence is associated with adverse health, organizational, and societal outcomes. Using data from a longitudinal cohort study of working Australians (the Household, Income and Labour Dynamics in Australia (HILDA) Survey), we examined the relationship between changes in individuals' overall psychosocial job quality and variation in sickness absence. The outcome variables were paid sickness absence (yes/no) and number of days of paid sickness absence in the past year (2005-2012). The main exposure variable was psychosocial job quality, measured using a psychosocial job quality index (levels of job control, demands and complexity, insecurity, and perceptions of unfair pay). Analysis was conducted using longitudinal fixed-effects logistic regression models and negative binomial regression models. There was a dose-response relationship between the number of psychosocial job stressors reported by an individual and the odds of paid sickness absence (1 adversity: odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.09, 1.45 (P = 0.002); 2 adversities: OR = 1.28, 95% CI: 1.09, 1.51 (P = 0.002); ≥3 adversities: OR = 1.58, 95% CI: 1.29, 1.94 (P < 0.001)). The negative binomial regression models also indicated that respondents reported a greater number of days of sickness absence in response to worsening psychosocial job quality. These results suggest that workplace interventions aiming to improve the quality of work could help reduce sickness absence. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

PubMed

Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

2016-10-01

In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

Angiogenic and inflammatory biomarkers in mid-pregnancy and small-for-gestational age outcomes in Tanzania

PubMed Central

DARLING, Anne Marie; MCDONALD, Chloe R.; CONROY, Andrea L.; HAYFORD, Kyla T.; RAJWANS, Nimerta; WANG, Molin; ABOUD, Said; URASSA, Willy S.; KAIN, Kevin C.; FAWZI, Wafaie W.

2014-01-01

OBJECTIVE To investigate the relationship between a panel of angiogenic and inflammatory biomarkers measured in mid-pregnancy and small-for-gestational age (SGA) outcomes in sub-Saharan Africa. STUDY DESIGN Concentrations of 18 angiogenic and inflammatory biomarkers were determined in 432 pregnant women in Dar es Salaam, Tanzania who participated in a trial examining the effect of multivitamins on pregnancy outcomes. Infants falling below the 10th percentile of birth weight for gestational age relative to the applied growth standards were considered SGA. Multivariate binomial regression models with the log link function were used to determine the relative risk of SGA associated with increasing quartiles of each biomarker. Stepwise cubic restricted splines were used to test for non-linearity of these associations. Receiver operating curves obtained from multivariate logistic regression models were used to assess the discriminatory capability of selected biomarkers. RESULTS A total of 60 participants (13.9%) gave birth to SGA infants. Compared to those in the first quartile, the risk of SGA was reduced among those in the fourth quartiles of VEGF-A (adjusted risk ratio (RR) 0.38, 95% Confidence Interval (CI), 0.19-0.74), PGF (adjusted RR 0.28, 95% CI, 0.12-0.61), sFlt-1 (adjusted RR 0.48, 95% CI, 0.23-1.01), MCP-1 (adjusted RR 0.48, 95% CI, 0.25-0.92), and Leptin (adjusted RR 0.46, 95% CI, 0.22-0.96) CONCLUSION Our findings provide evidence of altered angiogenic and inflammatory mediators, at mid-pregnancy, in women who went on to deliver small for gestational age infants. PMID:24881826

U.S. military service and the prevalence of metabolic syndrome: Findings from a cross-sectional analysis of the Cooper Center Longitudinal Study, 1979-2013.

PubMed

Janak, Jud C; Pérez, Adriana; Alamgir, Hasanat; Orman, Jean A; Cooper, Sharon P; Shuval, Kerem; DeFina, Laura; Barlow, Carolyn E; Gabriel, Kelley Pettee

2017-02-01

U.S. military service confers both health benefits and risks potentially associated with a clustering of cardiovascular risk factors called metabolic syndrome. However, the association between prior military service and metabolic syndrome has not sufficiently been examined. The purpose of the study was to compare the prevalence of metabolic syndrome by prior military service status. Among 42,370 men (887 with prior military service) examined from 1979 to 2013 at the Cooper Clinic (Dallas, TX), we used a cross-sectional study design to examine the association between military service and metabolic syndrome. First, an unadjusted log binomial regression model was performed by regressing the prevalence of metabolic syndrome on prior service. This was followed by performing Kleinbaum's modeling strategy for assessing confounding. The same methodology was used to explore the association between individual metabolic syndrome risk factors and prior service. Prior military service was not significantly associated with the prevalence of metabolic syndrome (PR=0.98, 0.89-1.07). None of the variables explored were identified as confounders. Participants with prior military service had lower prevalence of both elevated levels of triglycerides (PR=0.89, 0.80-0.99) and low levels of high-density lipoprotein-cholesterol (PR=0.78, 0.70-0.88). They had a higher prevalence of elevated resting systolic blood pressure (PR=1.23, 1.12-1.35). However, none of these associations were significant after adjusting for identified confounders: age; cardiorespiratory fitness; and exam year. Study findings indicate that military service was not independently associated with the prevalence of metabolic syndrome or its components. Future research is warranted longitudinally assessing the impact of military service on long-term outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Escherichia coli bacteria density in relation to turbidity, streamflow characteristics, and season in the Chattahoochee River near Atlanta, Georgia, October 2000 through September 2008—Description, statistical analysis, and predictive modeling

USGS Publications Warehouse

Lawrence, Stephen J.

2012-01-01

Regression analyses show that E. coli density in samples was strongly related to turbidity, streamflow characteristics, and season at both sites. The regression equation chosen for the Norcross data showed that 78 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), streamflow event (dry-weather flow or stormflow), season (cool or warm), and an interaction term that is the cross product of streamflow event and turbidity. The regression equation chosen for the Atlanta data showed that 76 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), water temperature, streamflow event, and an interaction term that is the cross product of streamflow event and turbidity. Residual analysis and model confirmation using new data indicated the regression equations selected at both sites predicted E. coli density within the 90 percent prediction intervals of the equations and could be used to predict E. coli density in real time at both sites.

Weighted log-linear models for service delivery points in Ethiopia: a case of modern contraceptive users at health facilities.

PubMed

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen; Mekonnen, Mulusew Admasu

2018-05-10

Ethiopia is among countries with low contraceptive usage prevalence rate and resulted in high total fertility rate and unwanted pregnancy which intern affects the maternal and child health status. This study aimed to investigate the major factors that affect the number of modern contraceptive users at service delivery point in Ethiopia. The Performance Monitoring and Accountability2020/Ethiopia data collected between March and April 2016 at round-4 from 461 eligible service delivery points were in this study. The weighted log-linear negative binomial model applied to analyze the service delivery point's data. Fifty percent of service delivery points in Ethiopia given service for 61 modern contraceptive users with the interquartile range of 0.62. The expected log number of modern contraceptive users at rural was 1.05 (95% Wald CI: - 1.42 to - 0.68) lower than the expected log number of modern contraceptive users at urban. In addition, the expected log count of modern contraceptive users at others facility type was 0.58 lower than the expected log count of modern contraceptive users at the health center. The numbers of nurses/midwives were affecting the number of modern contraceptive users. Since, the incidence rate of modern contraceptive users increased by one due to an additional nurse in the delivery point. Among different factors considered in this study, residence, region, facility type, the number of days per week family planning offered, the number of nurses/midwives and number of medical assistants were to be associated with the number of modern contraceptive users. Thus, the Government of Ethiopia would take immediate steps to address causes of the number of modern contraceptive users in Ethiopia.

Enrollment Management in Medical School Admissions: A Novel Evidence-Based Approach at One Institution.

PubMed

Burkhardt, John C; DesJardins, Stephen L; Teener, Carol A; Gay, Steven E; Santen, Sally A

2016-11-01

In higher education, enrollment management has been developed to accurately predict the likelihood of enrollment of admitted students. This allows evidence to dictate numbers of interviews scheduled, offers of admission, and financial aid package distribution. The applicability of enrollment management techniques for use in medical education was tested through creation of a predictive enrollment model at the University of Michigan Medical School (U-M). U-M and American Medical College Application Service data (2006-2014) were combined to create a database including applicant demographics, academic application scores, institutional financial aid offer, and choice of school attended. Binomial logistic regression and multinomial logistic regression models were estimated in order to study factors related to enrollment at the local institution versus elsewhere and to groupings of competing peer institutions. A predictive analytic "dashboard" was created for practical use. Both models were significant at P < .001 and had similar predictive performance. In the binomial model female, underrepresented minority students, grade point average, Medical College Admission Test score, admissions committee desirability score, and most individual financial aid offers were significant (P < .05). The significant covariates were similar in the multinomial model (excluding female) and provided separate likelihoods of students enrolling at different institutional types. An enrollment-management-based approach would allow medical schools to better manage the number of students they admit and target recruitment efforts to improve their likelihood of success. It also performs a key institutional research function for understanding failed recruitment of highly desirable candidates.

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

PubMed

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Oral health of schoolchildren in Western Australia.

PubMed

Arrow, P

2016-09-01

The West Australian School Dental Service (SDS) provides free, statewide, primary dental care to schoolchildren aged 5-17 years. This study reports on an evaluation of the oral health of children examined during the 2014 calendar year. Children were sampled, based on their date of birth, and SDS clinicians collected the clinical information. Weighted mean values of caries experience were presented. Negative binomial regression modelling was undertaken to test for factors of significance in the rate of caries occurrence. Data from children aged 5-15 years were used (girls = 4616, boys = 4900). Mean dmft (5-10-year-olds), 1.42 SE 0.03; mean DMFT (6-15-year-olds), 0.51 SE 0.01. Negative binomial regression model of permanent tooth caries found higher rates of caries in children who were from non-fluoridated areas (RR 2.1); Aboriginal (RR 2.4); had gingival inflammation (RR 1.5); lower ICSEA level (RR 1.4); and recalled at more than 24-month interval (RR 1.8). The study highlighted poor dental health associated with living in non-fluoridated areas, Aboriginal identity, poor oral hygiene, lower socioeconomic level and having extended intervals between dental checkups. Timely assessments and preventive measures targeted at groups, including extending community water fluoridation, may assist in further improving the oral health of children in Western Australia. © 2015 Australian Dental Association.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Statistical Models for the Analysis and Design of Digital Polymerase Chain Reaction (dPCR) Experiments.

PubMed

Dorazio, Robert M; Hunter, Margaret E

2015-11-03

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log-log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model's parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

PubMed

Kong, Shengchun; Nan, Bin

2014-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso

PubMed Central

Kong, Shengchun; Nan, Bin

2013-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses. PMID:24516328

Dose-response association between salivary cotinine levels and Mycobacterium tuberculosis infection.

PubMed

Shin, S S; Laniado-Laborin, R; Moreno, P G; Novotny, T E; Strathdee, S A; Garfein, R S

2013-11-01

Tijuana, Mexico. To describe the association between salivary cotinine levels and interferon-gamma (IFN-γ) release assay results. We conducted a cross-sectional study among injection drug users. Salivary cotinine levels were measured using NicAlert, a semi-quantitative dipstick assay. QuantiFERON©-TB Gold In-Tube (QFT-GIT) was used to determine Mycobacterium tuberculosis infection. Among 234 participants, the prevalence of QFT-GIT positivity for NicAlert cotinine categories 0 (non-smoking), 1 (second-hand smoke exposure or low-level smoking) and 26 (regular smoking) were respectively 42.1%, 46.4% and 65.2% (Ptrend 0.012). We found increasing trends in QFT-GIT positivity (Ptrend 0.003) and IFN-γ concentrations (Spearman's r 0.200, P 0.002) across cotinine levels 0 to 6. In multivariable log-binomial regression models adjusted for education, cotinine levels were not associated with QFT-GIT positivity when included as smoking categories (1 and 26 vs. 0), but were independently associated with QFT-GIT positivity when included as an ordinal variable (prevalence ratio 1.09 per 1 cotinine level, 95%CI 1.021.16). Our findings suggest that a dose-response relationship exists between tobacco smoke exposure and M. tuberculosis infection. Longitudinal studies that use biochemical measures for smoking status are needed to confirm our findings.

Older maternal age is associated with depression, anxiety, and stress symptoms in young adult female offspring.

PubMed

Tearne, Jessica E; Robinson, Monique; Jacoby, Peter; Allen, Karina L; Cunningham, Nadia K; Li, Jianghong; McLean, Neil J

2016-01-01

The evidence regarding older parental age and incidence of mood disorder symptoms in offspring is limited, and that which exists is mixed. We sought to clarify these relationships by using data from the Western Australian Pregnancy Cohort (Raine) Study. The Raine Study provided comprehensive data from 2,900 pregnancies, resulting in 2,868 live born children. A total of 1,220 participants completed the short form of the Depression Anxiety Stress Scale (DASS-21) at the 20-year cohort follow-up. We used negative binomial regression analyses with log link and with adjustment for known perinatal risk factors to examine the extent to which maternal and paternal age at childbirth predicted continuous DASS-21 index scores. In the final multivariate models, a maternal age of 30-34 years was associated with significant increases in stress DASS-21 scores in female offspring relative to female offspring of 25- to 29-year-old mothers. A maternal age of 35 years and over was associated with increased scores on all DASS-21 scales in female offspring. Our results indicate that older maternal age is associated with depression, anxiety, and stress symptoms in young adult females. Further research into the mechanisms underpinning this relationship is needed. (c) 2016 APA, all rights reserved.

Individual and Environmental Correlates to Quality of Life in Park Users in Colombia

PubMed Central

Camargo, Diana Marina

2017-01-01

Purpose: To explore individual and environmental correlates to quality of life (QoL) in park users in Colombia. Methods: A cross-sectional study with face-to-face interviews was conducted with 1392 park users from ten parks in Colombia. The survey included sociodemographic questions, health condition assessed with EuroQuol-5-Dimensions-5-Levels; in addition, questions about accessibility to the parks and perceptions about quality of infrastructure and green areas were asked. The Spanish version of the questionnaire EUROHIS-QOL-8 items was applied to assess QoL. Log-binomial regression models were applied for analyses. Results: Years of schooling, visits to the park with a companion, active use of the park, a maximum score for quality of trees and walking paths, and the perception of safety on the way to the park were positively associated with a better QoL (p < 0.05). Health conditions related to problems in the ability to perform activities of daily living and anxiety/depression showed negative associations. Conclusions: The present study contributes to the Latin American studies by providing information on how parks in an intermediate city may contribute to increased QoL of park users through safety in neighborhoods, social support, active use, and aesthetics, cleanliness, and care of green areas. PMID:29048373

Prevalence and predictors of sunburn among beachgoers.

PubMed

de Troya-Martín, Magdalena; de Gálvez-Aranda, María Victoria; Rivas-Ruiz, Francisco; Blázquez-Sánchez, Nuria; Fernández-Morano, Maria Teresa; Padilla-España, Laura; Herrera-Ceballos, Enrique

2018-03-01

Painful sunburns at any age are one of the main risk factors for skin cancer. To determine the prevalence and predictors of sunburn among beachgoers. A cross-sectional health survey was conducted at the beach during the summer. Adults >18 years with an understanding of Spanish were interviewed using a questionnaire about behaviours, attitudes and knowledge related to sun exposure at the beach. A descriptive analysis was performed, and a log-binomial regression model was used to determine predictors of sunburn. The survey was completed by 1054 beachgoers, with a mean age of 43.8 (SD: 18.7) years, 61.2% women, skin phototypes i (13.6%), ii (22.3%), iii (34.0%) and iv (30.2%). 46.9% of responders reported at least one painful sunburn during the previous summer. Age, sex, education, skin phototype, midday sun exposure, sun protection habits, attitudes towards tanning and knowledge about skin cancer were identified as independent predictors of sunburn. It is necessary to develop photoprotection campaigns aimed at beachgoers, particularly in young people, men, those with skin phototypes I-III and secondary or university education. Educational strategies should be aimed at discouraging sun exposure at midday, changing attitudes towards tanning and improving knowledge about skin cancer. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Recall of anti-tobacco advertisements and effects on quitting behavior: results from the California smokers cohort.

PubMed

Leas, Eric C; Myers, Mark G; Strong, David R; Hofstetter, C Richard; Al-Delaimy, Wael K

2015-02-01

We assessed whether an anti-tobacco television advertisement called "Stages," which depicted a woman giving a brief emotional narrative of her experiences with tobacco use, would be recalled more often and have a greater effect on smoking cessation than 3 other advertisements with different intended themes. Our data were derived from a sample of 2596 California adult smokers. We used multivariable log-binomial and modified Poisson regression models to calculate respondents' probability of quitting as a result of advertisement recall. More respondents recalled the "Stages" ad (58.5%) than the 3 other ads (23.1%, 23.4%, and 25.6%; P<.001). Respondents who recalled "Stages" at baseline had a higher probability than those who did not recall the ad of making a quit attempt between baseline and follow-up (adjusted risk ratio [RR]=1.18; 95% confidence interval [CI]=1.03, 1.34) and a higher probability of being in a period of smoking abstinence for at least a month at follow-up (adjusted RR=1.55; 95% CI=1.02, 2.37). Anti-tobacco television advertisements that depict visceral and personal messages may be recalled by a larger percentage of smokers and may have a greater impact on smoking cessation than other types of advertisements.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Albumin, a marker for post-operative myocardial damage in cardiac surgery.

PubMed

van Beek, Dianne E C; van der Horst, Iwan C C; de Geus, A Fred; Mariani, Massimo A; Scheeren, Thomas W L

2018-06-06

Low serum albumin (SA) is a prognostic factor for poor outcome after cardiac surgery. The aim of this study was to estimate the association between pre-operative SA, early post-operative SA and postoperative myocardial injury. This single center cohort study included adult patients undergoing cardiac surgery during 4 consecutive years. Postoperative myocardial damage was defined by calculating the area under the curve (AUC) of troponin (Tn) values during the first 72 h after surgery and its association with SA analyzed using linear regression and with multivariable linear regression to account for patient related and procedural confounders. The association between SA and the secondary outcomes (peri-operative myocardial infarction [PMI], requiring ventilation >24 h, rhythm disturbances, 30-day mortality) was studied using (multivariable) log binomial regression analysis. In total 2757 patients were included. The mean pre-operative SA was 29 ± 13 g/l and the mean post-operative SA was 26 ± 6 g/l. Post-operative SA levels (on average 26 min after surgery) were inversely associated with postoperative myocardial damage in both univariable analysis (regression coefficient - 0.019, 95%CI -0.022/-0.015, p < 0.005) and after adjustment for patient related and surgical confounders (regression coefficient - 0.014 [95% CI -0.020/-0.008], p < 0.0005). Post-operative albumin levels were significantly correlated with the amount of postoperative myocardial damage in patients undergoing cardiac surgery independent of typical confounders. Copyright © 2018. Published by Elsevier Inc.

Novelty helmet use and motorcycle rider fatality

PubMed Central

Rice, Thomas M.; Troszak, Lara; Erhardt, Taryn; Trent, Roger B.; Zhu, Motao

2018-01-01

Objectives To compare the risk of fatal injury across helmet types among collision-involved motorcyclists. Methods We used data from a cohort of motorcyclists involved in police-reported traffic collisions. Eighty-four law enforcement agencies in California collected detailed information on helmet and rider characteristics during collision investigations in June 2012 through July 2013. Multiply-adjusted risk ratios were estimated with log-binomial regression. Results The adjusted fatal injury risk ratio for novelty helmets was 1.95 (95% CI 1.11–3.40, p 0.019), comparing novelty helmets with full-face helmets. The risk ratios for modular, open-face, and half-helmets, compared with full-face helmets, were not significant. Conclusions A more complete understanding of the inadequacy of novelty helmets can be used in educational and law enforcement countermeasures to improve helmet use among motorcycling populations in California and other US states. Law enforcement approaches to mitigating novelty helmet use would seem attractive given that novelty helmets can be visually identified by law enforcement officers with sufficient training. PMID:28431344

Contact dermatitis is an unrecognized problem in the construction industry: Comparison of four different assessment methods.

PubMed

Timmerman, Johan G; Heederik, Dick; Spee, Ton; van Rooy, Frits G; Krop, Esmeralda J M; Rustemeyer, Thomas; Smit, Lidwien A M

2017-10-01

A high contact dermatitis symptoms prevalence has been observed in Dutch construction workers. Contact dermatitis was diagnosed by an expert panel using questionnaire data and photographs of 751 subjects' hands. A subset was evaluated by two occupational physicians. Their diagnoses were compared to those of the expert panel. In addition, two self-reported questionnaire-based assessment methods were compared to the expert panel evaluation. Associations between contact dermatitis and determinants were assessed using log-binomial regression analysis. Contact dermatitis prevalence was high: 61.4% (expert panel's diagnosis) and 32.9% (self-reported). Agreement between occupational physicians and the expert panel was low but increased after training. Washing hands with solvents and performing job-related tasks at home were related to contact dermatitis. Contact dermatitis prevalence among construction workers is high. Recognition of contact dermatitis by occupational physicians is poor but can be improved by training. Awareness of skin disorders should be raised. © 2017 Wiley Periodicals, Inc.

Individual, network, and neighborhood correlates of exchange sex among female non-injection drug users in Baltimore, MD (2005–2007)

PubMed Central

Rudolph, Abby E; Linton, Sabriya; Dyer, Typhanye Penniman; Latkin, Carl

2012-01-01

The “HIV risk environment” has been characterized as a dynamic interplay between structural and network factors. However, most HIV prevention research has not examined the independent and combined impact of network and structural factors. We aimed to identify individual, network, and neighborhood correlates of exchange sex (≥1 exchange sex partner, past 90 days) among female non-injection drug users (NIDUs). We used baseline data from 417 NIDUs enrolled in a randomized HIV prevention trial in Baltimore (2005–2007). Surveys ascertained demographic variables, drug/sex risk behaviors, neighborhood perceptions, and social/sexual network characteristics. Correlates of exchange sex were identified with descriptive statistics and log-binomial regression. Our findings suggest that sex and drug relationships among female NIDUs are interlinked and may be difficult to modify without altering social norms. Strengthening ties that provide social support but not drug support and reducing ties that provide both drug and social support may facilitate reductions in individual-level HIV-risk behaviors. PMID:22983502

[Multidimensional measurement of precarious employment: social distribution and its association with health in Catalonia (Spain)].

PubMed

Benach, Joan; Julià, Mireia; Tarafa, Gemma; Mir, Jordi; Molinero, Emilia; Vives, Alejandra

2015-01-01

To show the prevalence of precarious employment in Catalonia (Spain) for the first time and its association with mental and self-rated health, measured with a multidimensional scale. A cross-sectional study was conducted using data from the II Catalan Working Conditions Survey (2010) with a subsample of employed workers with a contract. The prevalence of precarious employment using a multidimensional scale and its association with health was calculated using multivariate log-binomial regression stratified by gender. The prevalence of precarious employment in Catalonia was high (42.6%). We found higher precariousness in women, youth, immigrants, and manual and less educated workers. There was a positive gradient in the association between precarious employment and poor health. Precarious employment is associated with poor health in the working population. Working conditions surveys should include questions on precarious employment and health indicators, which would allow monitoring and subsequent analyses of health inequalities. Copyright © 2015 SESPAS. Published by Elsevier Espana. All rights reserved.

Contingency Management Voucher Redemption as an Indicator of Delayed Gratification

PubMed Central

Fletcher, Jesse B.; Dierst-Davies, Rhodri; Reback, Cathy J.

2014-01-01

This prospective analysis tested whether frequency of voucher redemptions during a contingency management (CM) substance use intervention was significantly associated with participants’ ongoing substance use. Homeless, substance-dependent men who have sex with men (N=131) were randomized into either a “full” or “lite” voucher-based CM intervention. All participants earned vouchers for attendance and participation; participants in the CM-full condition also received vouchers for substance abstinence and enactment of prosocial and/or health-promoting behaviors. Multivariate longitudinal negative binomial regression analyses (n = 118) assessed the association between substance use during the intervention and frequency of voucher redemptions. Participants who used methamphetamine (IRR = 0.66; 95% CI=0.44–0.99) and/or opiates (IRR=0.60; 95% CI=0.40–0.99) during the intervention exhibited less time between voucher redemptions than individuals who achieved abstinence from these substances. Voucher redemption logs can be cost-effective and unobtrusive tools for measuring study participants’ tendency to delay gratification. PMID:24674235

Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

PubMed

Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

2018-02-01

1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE < 10.3%. The external data evaluation showed that the models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

Dispersion models and sampling of cacao mirid bug Sahlbergella singularis (Hemiptera: Miridae) on Theobroma Cacao in southern Cameroon.

PubMed

Bisseleua, D H B; Vidal, Stefan

2011-02-01

The spatio-temporal distribution of Sahlbergella singularis Haglung, a major pest of cacao trees (Theobroma cacao) (Malvaceae), was studied for 2 yr in traditional cacao forest gardens in the humid forest area of southern Cameroon. The first objective was to analyze the dispersion of this insect on cacao trees. The second objective was to develop sampling plans based on fixed levels of precision for estimating S. singularis populations. The following models were used to analyze the data: Taylor's power law, Iwao's patchiness regression, the Nachman model, and the negative binomial distribution. Our results document that Taylor's power law was a better fit for the data than the Iwao and Nachman models. Taylor's b and Iwao's β were both significantly >1, indicating that S. singularis aggregated on specific trees. This result was further supported by the calculated common k of 1.75444. Iwao's α was significantly <0, indicating that the basic distribution component of S. singularis was the individual insect. Comparison of negative binomial (NBD) and Nachman models indicated that the NBD model was appropriate for studying S. singularis distribution. Optimal sample sizes for fixed precision levels of 0.10, 0.15, and 0.25 were estimated with Taylor's regression coefficients. Required sample sizes increased dramatically with increasing levels of precision. This is the first study on S. singularis dispersion in cacao plantations. Sampling plans, presented here, should be a tool for research on population dynamics and pest management decisions of mirid bugs on cacao. © 2011 Entomological Society of America

Identifiability in N-mixture models: a large-scale screening test with bird data.

PubMed

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

[Distribution of individuals by spontaneous frequencies of lymphocytes with micronuclei. Particularity and consequences].

PubMed

Serebrianyĭ, A M; Akleev, A V; Aleshchenko, A V; Antoshchina, M M; Kudriashova, O V; Riabchenko, N I; Semenova, L P; Pelevina, I I

2011-01-01

By micronucleus (MN) assay with cytokinetic cytochalasin B block, the mean frequency of blood lymphocytes with MN has been determined in 76 Moscow inhabitants, 35 people from Obninsk and 122 from Chelyabinsk region. In contrast to the distribution of individuals on spontaneous frequency of cells with aberrations, which was shown to be binomial (Kusnetzov et al., 1980), the distribution of individuals on the spontaneous frequency of cells with MN in all three massif can be acknowledged as log-normal (chi2 test). Distribution of individuals in the joined massifs (Moscow and Obninsk inhabitants) and in the unique massif of all inspected with great reliability must be acknowledged as log-normal (0.70 and 0.86 correspondingly), but it cannot be regarded as Poisson, binomial or normal. Taking into account that log-normal distribution of children by spontaneous frequency of lymphocytes with MN has been observed by the inspection of 473 children from different kindergartens in Moscow we can make the conclusion that log-normal is regularity inherent in this type of damage of lymphocytes genome. On the contrary the distribution of individuals on induced by irradiation in vitro lymphocytes with MN frequency in most cases must be acknowledged as normal. This distribution character points out that damage appearance in the individual (genomic instability) in a single lymphocytes increases the probability of the damage appearance in another lymphocytes. We can propose that damaged stem cells lymphocyte progenitor's exchange by information with undamaged cells--the type of the bystander effect process. It can also be supposed that transmission of damage to daughter cells occurs in the time of stem cells division.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

PubMed

Wang, Zhu; Ma, Shuangge; Wang, Ching-Yun

2015-09-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using beta binomials to estimate classification uncertainty for ensemble models.

PubMed

Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

2014-01-01

Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

School shootings during 2013-2015 in the USA.

PubMed

Kalesan, Bindu; Lagast, Kinan; Villarreal, Marcos; Pino, Elizabeth; Fagan, Jeffrey; Galea, Sandro

2017-10-01

Data on the factors associated with school shootings in the USA are limited. The public conversation has often suggested several factors that may be linked to these events, however with little empirical support. Aiming to fill this gap, we describe the characteristics of school shooting incidents in the USA between 2013 and 2015 and explore whether four factors that represent domains of firearm policy, educational policy and epidemiological risk factors for intentional firearm injuries-background check (BC) policies, per capita mental health expenditures (MHE), K-12 education expenditure (KEE) and urbanicity-were associated with school shootings during this period. We searched LexisNexis, a newspaper and broadcast media databases for school shooting incidents from 1 January 2013 to 31 December 2015. Presence of BC laws was extracted from legal information in LexisNexis. State-level covariates of per capita MHE (2013), KEE (2013) and urbanicity (2010) rates were obtained from publicly available data sources. We used negative binomial regression models accounting for clustering by state to explore unadjusted associations between the BC laws, state-level covariates and school shootings to report IRR and 95% CI. We documented 154 school shootings (35, 55 and 64 each year). In unadjusted models, BC for firearm purchase (IRR=0.55, 95% CI 0.39 to 0.76), ammunition purchase (IRR=0.11, 95% CI 0.05 to 0.27), log per capita MHE (IRR=0.58, 95% CI 0.37 to 0.90), log per-capita KEE (IRR=0.09, 9% CI 0.02 to 0.29) and urbanicity (IRR=0.97, 95% CI 0.96 to 0.99) were associated with school shooting. School shootings are less likely in states with BC laws, higher MHE and KEE, and with greater per cent urban population. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

USING LINEAR AND POLYNOMIAL MODELS TO EXAMINE THE ENVIRONMENTAL STABILITY OF VIRUSES

EPA Science Inventory

The article presents the development of model equations for describing the fate of viral infectivity in environmental samples. Most of the models were based upon the use of a two-step linear regression approach. The first step employs regression of log base 10 transformed viral t...

Tobit analysis of vehicle accident rates on interstate highways.

PubMed

Anastasopoulos, Panagiotis Ch; Tarko, Andrew P; Mannering, Fred L

2008-03-01

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory.

PubMed

Lord, Dominique; Washington, Simon P; Ivan, John N

2005-01-01

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

PubMed

Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J; Ma, Keping

2013-01-01

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Writing and overwriting short-term memory

PubMed Central

Killeen, Peter R.

2008-01-01

An integrative account of short-term memory is based on data from pigeons trained to report the majority color in a sequence of lights. Performance showed strong recency effects, was invariant over changes in the interstimulus interval, and improved with increases in the intertrial interval. A compound model of binomial variance around geometrically decreasing memory described the data; a logit transformation rendered it isomorphic with other memory models. The model was generalized for variance in the parameters, where it was shown that averaging exponential and power functions from individuals or items with different decay rates generates new functions that are hyperbolic in time and in log time, respectively. The compound model provides a unified treatment of both the accrual and the dissipation of memory and is consistent with data from various experiments, including the choose-short bias in delayed recall, multielement stimuli, and Rubin and Wenzel’s (1996) meta-analyses of forgetting. PMID:11340865

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

PubMed

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Random forest models to predict aqueous solubility.

PubMed

Palmer, David S; O'Boyle, Noel M; Glen, Robert C; Mitchell, John B O

2007-01-01

Random Forest regression (RF), Partial-Least-Squares (PLS) regression, Support Vector Machines (SVM), and Artificial Neural Networks (ANN) were used to develop QSPR models for the prediction of aqueous solubility, based on experimental data for 988 organic molecules. The Random Forest regression model predicted aqueous solubility more accurately than those created by PLS, SVM, and ANN and offered methods for automatic descriptor selection, an assessment of descriptor importance, and an in-parallel measure of predictive ability, all of which serve to recommend its use. The prediction of log molar solubility for an external test set of 330 molecules that are solid at 25 degrees C gave an r2 = 0.89 and RMSE = 0.69 log S units. For a standard data set selected from the literature, the model performed well with respect to other documented methods. Finally, the diversity of the training and test sets are compared to the chemical space occupied by molecules in the MDL drug data report, on the basis of molecular descriptors selected by the regression analysis.

Scoring in genetically modified organism proficiency tests based on log-transformed results.

PubMed

Thompson, Michael; Ellison, Stephen L R; Owen, Linda; Mathieson, Kenneth; Powell, Joanne; Key, Pauline; Wood, Roger; Damant, Andrew P

2006-01-01

The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distributions that are sufficiently close to normal to justify interpretation on the basis of the normal distribution.

Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

ERIC Educational Resources Information Center

Lee, Young-Jin

2015-01-01

This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

Clashing paradigms: an empirical examination of cultural proxies and socioeconomic condition shaping Latino health.

PubMed

Echeverría, Sandra E; Pentakota, Sri Ram; Abraído-Lanza, Ana F; Janevic, Teresa; Gundersen, Daniel A; Ramirez, Sarah M; Delnevo, Cristine D

2013-10-01

Much debate exists regarding the role of culture versus socioeconomic position in shaping the health of Latino populations. We propose that both may matter for health and explicitly test their independent and joint effects on smoking and physical activity. We used the 2010 National Health Interview Survey, a population-based survey of the U.S. population, to estimate the prevalence of smoking and physical activity by language use (cultural proxy) and education among Latino adults (n = 4929). We fit log binomial regression models to estimate prevalence ratios and test for interaction. English-language use and educational attainment were each independently associated with smoking and physical activity. Joint effect models showed that individuals with both greater use of the English language and low levels of education were nearly three times more likely to smoke (prevalence ratio, 2.59; 95% confidence interval, 1.83-3.65) than those with low English language use and high education (referent group); high acculturation and high education were jointly associated with increased activity (prevalence ratio 2.24, 95% confidence interval, 1.79-2.81). Cultural proxies such as language use and educational attainment are both important determinants of health among Latinos. Their joint effect suggests the need to simultaneously consider Latinos' socioeconomic position and their increased risk of adopting health-damaging behaviors while addressing culturally-specific factors that may mitigate risk. Copyright © 2013 Elsevier Inc. All rights reserved.

A Three-Parameter Generalisation of the Beta-Binomial Distribution with Applications

DTIC Science & Technology

1987-07-01

York. Rust, R.T. and Klompmaker, J.E. (1981). Improving the estimation procedure for the beta binomial t.v. exposure model. Journal of Marketing ... Research . 18, 442-448. Sabavala, D.J. and Morrison, D.G. (1977). Television show loyalty: a beta- binomial model using recall data. Journal of Advertiuing

Use of Proteomic and Hematology Biomarkers for Prediction of Hematopoietic Acute Radiation Syndrome Severity in Baboon Radiation Models.

PubMed

Blakely, William F; Bolduc, David L; Debad, Jeff; Sigal, George; Port, Matthias; Abend, Michael; Valente, Marco; Drouet, Michel; Hérodin, Francis

2018-07-01

Use of plasma proteomic and hematological biomarkers represents a promising approach to provide useful diagnostic information for assessment of the severity of hematopoietic acute radiation syndrome. Eighteen baboons were evaluated in a radiation model that underwent total-body and partial-body irradiations at doses of Co gamma rays from 2.5 to 15 Gy at dose rates of 6.25 cGy min and 32 cGy min. Hematopoietic acute radiation syndrome severity levels determined by an analysis of blood count changes measured up to 60 d after irradiation were used to gauge overall hematopoietic acute radiation syndrome severity classifications. A panel of protein biomarkers was measured on plasma samples collected at 0 to 28 d after exposure using electrochemiluminescence-detection technology. The database was split into two distinct groups (i.e., "calibration," n = 11; "validation," n = 7). The calibration database was used in an initial stepwise regression multivariate model-fitting approach followed by down selection of biomarkers for identification of subpanels of hematopoietic acute radiation syndrome-responsive biomarkers for three time windows (i.e., 0-2 d, 2-7 d, 7-28 d). Model 1 (0-2 d) includes log C-reactive protein (p < 0.0001), log interleukin-13 (p < 0.0054), and procalcitonin (p < 0.0316) biomarkers; model 2 (2-7 d) includes log CD27 (p < 0.0001), log FMS-related tyrosine kinase 3 ligand (p < 0.0001), log serum amyloid A (p < 0.0007), and log interleukin-6 (p < 0.0002); and model 3 (7-28 d) includes log CD27 (p < 0.0012), log serum amyloid A (p < 0.0002), log erythropoietin (p < 0.0001), and log CD177 (p < 0.0001). The predicted risk of radiation injury categorization values, representing the hematopoietic acute radiation syndrome severity outcome for the three models, produced least squares multiple regression fit confidences of R = 0.73, 0.82, and 0.75, respectively. The resultant algorithms support the proof of concept that plasma proteomic biomarkers can supplement clinical signs and symptoms to assess hematopoietic acute radiation syndrome risk severity.

Distribution-free Inference of Zero-inated Binomial Data for Longitudinal Studies.

PubMed

He, H; Wang, W J; Hu, J; Gallop, R; Crits-Christoph, P; Xia, Y L

2015-10-01

Count reponses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated poisson (ZIP) and zero-inflated negative binomial (ZINB) models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or zero-inflated Poisson (ZIP) distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling zero-inflated binomial (ZIB)-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.

Atmospheric concentrations, sources and gas-particle partitioning of PAHs in Beijing after the 29th Olympic Games.

PubMed

Ma, Wan-Li; Sun, De-Zhi; Shen, Wei-Guo; Yang, Meng; Qi, Hong; Liu, Li-Yan; Shen, Ji-Min; Li, Yi-Fan

2011-07-01

A comprehensive sampling campaign was carried out to study atmospheric concentration of polycyclic aromatic hydrocarbons (PAHs) in Beijing and to evaluate the effectiveness of source control strategies in reducing PAHs pollution after the 29th Olympic Games. The sub-cooled liquid vapor pressure (logP(L)(o))-based model and octanol-air partition coefficient (K(oa))-based model were applied based on each seasonal dateset. Regression analysis among log K(P), logP(L)(o) and log K(oa) exhibited high significant correlations for four seasons. Source factors were identified by principle component analysis and contributions were further estimated by multiple linear regression. Pyrogenic sources and coke oven emission were identified as major sources for both the non-heating and heating seasons. As compared with literatures, the mean PAH concentrations before and after the 29th Olympic Games were reduced by more than 60%, indicating that the source control measures were effective for reducing PAHs pollution in Beijing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Alternative Regression Equations for Estimation of Annual Peak-Streamflow Frequency for Undeveloped Watersheds in Texas using PRESS Minimization

USGS Publications Warehouse

Asquith, William H.; Thompson, David B.

2008-01-01

The U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, investigated a refinement of the regional regression method and developed alternative equations for estimation of peak-streamflow frequency for undeveloped watersheds in Texas. A common model for estimation of peak-streamflow frequency is based on the regional regression method. The current (2008) regional regression equations for 11 regions of Texas are based on log10 transformations of all regression variables (drainage area, main-channel slope, and watershed shape). Exclusive use of log10-transformation does not fully linearize the relations between the variables. As a result, some systematic bias remains in the current equations. The bias results in overestimation of peak streamflow for both the smallest and largest watersheds. The bias increases with increasing recurrence interval. The primary source of the bias is the discernible curvilinear relation in log10 space between peak streamflow and drainage area. Bias is demonstrated by selected residual plots with superimposed LOWESS trend lines. To address the bias, a statistical framework based on minimization of the PRESS statistic through power transformation of drainage area is described and implemented, and the resulting regression equations are reported. Compared to log10-exclusive equations, the equations derived from PRESS minimization have PRESS statistics and residual standard errors less than the log10 exclusive equations. Selected residual plots for the PRESS-minimized equations are presented to demonstrate that systematic bias in regional regression equations for peak-streamflow frequency estimation in Texas can be reduced. Because the overall error is similar to the error associated with previous equations and because the bias is reduced, the PRESS-minimized equations reported here provide alternative equations for peak-streamflow frequency estimation.

Disclosure of HIV serostatus to male partner and use of modern contraceptives among women receiving HIV care services in Kampala, Uganda.

PubMed

Zalwango, Vivian W; Tweheyo, Raymond; Makumbi, Fredrick

2013-11-01

To investigate whether disclosure of HIV status is associated with use of modern contraceptives (MCs) among women attending HIV care services at an AIDS Information Center (AIC) in an urban setting in Uganda. In a cross-sectional study between March and April 2010, HIV-positive married women aged 15-49years who had received their HIV-positive serostatus results at least 4weeks previously were interviewed at the AIC, Kampala, Uganda. Female use of MCs was compared by HIV disclosure to male marital partners. Log-binomial regression models were used to obtain crude and adjusted prevalence risk ratios (PRRs) and corresponding 95% confidence intervals (CIs). Nearly three-quarters (72.6%) of the women had disclosed their HIV-positive status to their partner. Overall, use of MCs was reported by 41.0% of the participants. Use of only 1 MC method was similar between those disclosing (81.1%) and those not disclosing (84.3%), but use of dual methods tended to be higher among disclosers (14.4%) than among non-disclosers (10.8%). In adjusted analyses, MC use was 41.0% lower among disclosers than among non-disclosers (adjusted PRR, 0.59; 95% CI, 0.46-0.77). HIV serostatus disclosure was associated with lower use of MCs among HIV-positive women in Kampala, Uganda. © 2013.

Social determinants of leprosy in a hyperendemic State in North Brazil

PubMed Central

Monteiro, Lorena Dias; Mota, Rosa Maria Salani; Martins-Melo, Francisco Rogerlândio; Alencar, Carlos Henrique; Heukelbach, Jorg

2017-01-01

ABSTRACT OBJECTIVE To identify the socioeconomic, demographic, operational, and health service-related factors associated with the occurrence of leprosy in a hyperendemic State in North Brazil. METHODS This is an ecological study based on secondary data from the Sistema de Informações de Agravos de Notificação in municipalities of the State of Tocantins from 2001 to 2012. Units of analysis were the 139 municipalities of the State. Negative binomial log linear regression models were used to estimate incidence rate ratios. RESULTS In bivariate analysis, the incidence rate ratios were significantly higher for municipalities with higher income ratio of the poorest 20.0% (1.47; 95%CI 1.19–1.81) and better Municipal Human Development Index (1.53; 95%CI 1.14–2.06). In multivariate analysis, the incidence rate ratios were significantly higher in municipalities with higher proportion of immigrants (1.31; 95%CI 1.11–1.55) and higher proportion of households with waste collection (1.37; 95%CI 1.11–1.69). There was a significant reduction in the incidence rate ratio with increased coverage of the Bolsa Família Program (0.98; 95%CI 0.96–0.99). CONCLUSIONS Control programs need to focus on activities in municipalities of greater social vulnerability with intersectoral investment for the improvement of the living conditions of the population. PMID:28746575

Effects of prediabetes mellitus alone or plus hypertension on subsequent occurrence of cardiovascular disease and diabetes mellitus: longitudinal study.

PubMed

Qiu, Miaoyan; Shen, Weili; Song, Xiaomin; Ju, Liping; Tong, Wenxin; Wang, Haiyan; Zheng, Sheng; Jin, Yan; Wu, Yixin; Wang, Weiqing; Tian, Jingyan

2015-03-01

Whether prediabetes mellitus alone or combined with other disorders means a higher risk for cardiovascular disease (CVD) is still controversial. This study aimed to investigate the association between prediabetes mellitus and CVD and diabetes mellitus and to explore whether prediabetes mellitus alone or combined with other syndromes, such as hypertension, could promote CVD risks significantly. This longitudinal population-based study of 1609 residents from Shanghai in Southern China was conducted between 2002 and 2014. Participants with a history of CVD at baseline were excluded from analysis. Multivariate log-binomial regression models were used to adjust possible coexisting factors. Incidence of CVD during follow-up was 10.1%. After adjusting for age, sex, and other factors, the association between prediabetes mellitus and CVD was not observed. When hypertension was incorporated in stratifying factors, adjusted CVD risk was elevated significantly (odds ratio, 2.41; 95% confidence interval, 1.25-4.64) in prediabetes mellitus and hypertension combined group, and coexistence of diabetes mellitus and hypertension made CVD risk highly significantly increased, reaching 3.43-fold higher than the reference group. Blood glucose level within prediabetic range is significantly associated with elevated risks for diabetes mellitus after multivariable adjustment, but only when it is concurrent with other disorders, such as hypertension, it will significantly increase CVD risk. © 2015 American Heart Association, Inc.

Playgroup Participation and Social Support Outcomes for Mothers of Young Children: A Longitudinal Cohort Study

PubMed Central

Hancock, Kirsten J.; Cunningham, Nadia K.; Lawrence, David; Zarb, David; Zubrick, Stephen R.

2015-01-01

Objective This study aimed to examine friendship networks and social support outcomes for mothers according to patterns of playgroup participation. Methods Data from the Longitudinal Study of Australian Children were used to examine the extent to which patterns of playgroup participation across the ages of 3–19 months (Wave 1) and 2–3 years (Wave 2) were associated with social support outcomes for mothers at Wave 3 (4–5 years) and four years later at Wave 5 (8–9 years). Analyses were adjusted for initial friendship attachments at Wave 1 and other socio-demographic characteristics. Results Log-binomial regression models estimating relative risks showed that mothers who never participated in a playgroup, or who participated at either Wave 1 or Wave 2 only, were 1.7 and 1.8 times as likely to report having no support from friends when the child was 4–5 years, and 2.0 times as likely to have no support at age 8–9 years, compared with mothers who persistently participated in playgroup at both Wave 1 and Wave 2. Conclusion These results provide evidence that persistent playgroup participation may acts as a protective factor against poor social support outcomes. Socially isolated parents may find playgroups a useful resource to build their social support networks. PMID:26181426

Recall of Anti-Tobacco Advertisements and Effects on Quitting Behavior: Results From the California Smokers Cohort

PubMed Central

Leas, Eric C.; Myers, Mark G.; Strong, David R.; Hofstetter, C. Richard

2015-01-01

Objectives. We assessed whether an anti-tobacco television advertisement called “Stages,” which depicted a woman giving a brief emotional narrative of her experiences with tobacco use, would be recalled more often and have a greater effect on smoking cessation than 3 other advertisements with different intended themes. Methods. Our data were derived from a sample of 2596 California adult smokers. We used multivariable log-binomial and modified Poisson regression models to calculate respondents’ probability of quitting as a result of advertisement recall. Results. More respondents recalled the “Stages” ad (58.5%) than the 3 other ads (23.1%, 23.4%, and 25.6%; P < .001). Respondents who recalled “Stages” at baseline had a higher probability than those who did not recall the ad of making a quit attempt between baseline and follow-up (adjusted risk ratio [RR] = 1.18; 95% confidence interval [CI] = 1.03, 1.34) and a higher probability of being in a period of smoking abstinence for at least a month at follow-up (adjusted RR = 1.55; 95% CI = 1.02, 2.37). Conclusions. Anti-tobacco television advertisements that depict visceral and personal messages may be recalled by a larger percentage of smokers and may have a greater impact on smoking cessation than other types of advertisements. PMID:25521871

On the p, q-binomial distribution and the Ising model

NASA Astrophysics Data System (ADS)

Lundow, P. H.; Rosengren, A.

2010-08-01

We employ p, q-binomial coefficients, a generalisation of the binomial coefficients, to describe the magnetisation distributions of the Ising model. For the complete graph this distribution corresponds exactly to the limit case p = q. We apply our investigation to the simple d-dimensional lattices for d = 1, 2, 3, 4, 5 and fit p, q-binomial distributions to our data, some of which are exact but most are sampled. For d = 1 and d = 5, the magnetisation distributions are remarkably well-fitted by p,q-binomial distributions. For d = 4 we are only slightly less successful, while for d = 2, 3 we see some deviations (with exceptions!) between the p, q-binomial and the Ising distribution. However, at certain temperatures near T c the statistical moments of the fitted distribution agree with the moments of the sampled data within the precision of sampling. We begin the paper by giving results of the behaviour of the p, q-distribution and its moment growth exponents given a certain parameterisation of p, q. Since the moment exponents are known for the Ising model (or at least approximately for d = 3) we can predict how p, q should behave and compare this to our measured p, q. The results speak in favour of the p, q-binomial distribution's correctness regarding its general behaviour in comparison to the Ising model. The full extent to which they correctly model the Ising distribution, however, is not settled.

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Choosing a Transformation in Analyses of Insect Counts from Contagious Distributions with Low Means

Treesearch

W.D. Pepper; S.J. Zarnoch; G.L. DeBarr; P. de Groot; C.D. Tangren

1997-01-01

Guidelines based on computer simulation are suggested for choosing a transformation of insect counts from negative binomial distributions with low mean counts and high levels of contagion. Typical values and ranges of negative binomial model parameters were determined by fitting the model to data from 19 entomological field studies. Random sampling of negative binomial...

Chromatographic behaviour predicts the ability of potential nootropics to permeate the blood-brain barrier.

PubMed

Farsa, Oldřich

2013-01-01

The log BB parameter is the logarithm of the ratio of a compound's equilibrium concentrations in the brain tissue versus the blood plasma. This parameter is a useful descriptor in assessing the ability of a compound to permeate the blood-brain barrier. The aim of this study was to develop a Hansch-type linear regression QSAR model that correlates the parameter log BB and the retention time of drugs and other organic compounds on a reversed-phase HPLC containing an embedded amide moiety. The retention time was expressed by the capacity factor log k'. The second aim was to estimate the brain's absorption of 2-(azacycloalkyl)acetamidophenoxyacetic acids, which are analogues of piracetam, nefiracetam, and meclofenoxate. Notably, these acids may be novel nootropics. Two simple regression models that relate log BB and log k' were developed from an assay performed using a reversed-phase HPLC that contained an embedded amide moiety. Both the quadratic and linear models yielded statistical parameters comparable to previously published models of log BB dependence on various structural characteristics. The models predict that four members of the substituted phenoxyacetic acid series have a strong chance of permeating the barrier and being absorbed in the brain. The results of this study show that a reversed-phase HPLC system containing an embedded amide moiety is a functional in vitro surrogate of the blood-brain barrier. These results suggest that racetam-type nootropic drugs containing a carboxylic moiety could be more poorly absorbed than analogues devoid of the carboxyl group, especially if the compounds penetrate the barrier by a simple diffusion mechanism.

The effect of a major cigarette price change on smoking behavior in california: a zero-inflated negative binomial model.

PubMed

Sheu, Mei-Ling; Hu, Teh-Wei; Keeler, Theodore E; Ong, Michael; Sung, Hai-Yen

2004-08-01

The objective of this paper is to determine the price sensitivity of smokers in their consumption of cigarettes, using evidence from a major increase in California cigarette prices due to Proposition 10 and the Tobacco Settlement. The study sample consists of individual survey data from Behavioral Risk Factor Survey (BRFS) and price data from the Bureau of Labor Statistics between 1996 and 1999. A zero-inflated negative binomial (ZINB) regression model was applied for the statistical analysis. The statistical model showed that price did not have an effect on reducing the estimated prevalence of smoking. However, it indicated that among smokers the price elasticity was at the level of -0.46 and statistically significant. Since smoking prevalence is significantly lower than it was a decade ago, price increases are becoming less effective as an inducement for hard-core smokers to quit, although they may respond by decreasing consumption. For those who only smoke occasionally (many of them being young adults) price increases alone may not be an effective inducement to quit smoking. Additional underlying behavioral factors need to be identified so that more effective anti-smoking strategies can be developed.

Trends and Regional Variation in Hospital Mortality, Length of Stay and Cost in Hospital of Ischemic Stroke Patients in Alberta Accompanying the Provincial Reorganization of Stroke Care.

PubMed

Ohinmaa, Arto; Zheng, Yufei; Jeerakathil, Thomas; Klarenbach, Scott; Häkkinen, Unto; Nguyen, Thanh; Friesen, Dan; Ruseski, Jane; Kaul, Padma; Ariste, Ruolz; Jacobs, Philip

2016-12-01

This study aimed to evaluate the trends and regional variation of stroke hospital care in 30-day in-hospital mortality, hospital length of stay (LOS), and 1-year total hospitalization cost after implementation of the Alberta Provincial Stroke Strategy. New ischemic stroke patients (N = 7632) admitted to Alberta acute care hospitals between 2006 and 2011 were followed for 1 year. We analyzed in-hospital mortality with logistic regression, LOS with negative binomial regression, and the hospital costs with generalized gamma model (log link). The risk-adjusted results were compared over years and between zones using observed/expected results. The risk-adjusted mortality rates decreased from 12.6% in 2006/2007 to 9.9% in 2010/2011. The regional variations in mortality decreased from 8.3% units in 2008/2009 to 5.6 in 2010/2011. The LOS of the first episode dropped significantly in 2010/2011 after a 4-year slight increase. The regional variation in LOS was 15.5 days in 2006/2007 and decreased to 10.9 days in 2010/2011. The 1-year hospitalization cost increased initially, and then kept on declining during the last 3 years. The South and Calgary zones had the lowest costs over the study period. However, this gap was diminishing. After implementation of the Alberta Provincial Stroke Strategy, both mortality and hospital costs demonstrated a decreasing trend during the later years of study. The LOS increased slightly during the first 4 years but had a significant drop at the last year. In general, the regional variations in all 3 indicators had a diminishing trend. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Accident prediction model for public highway-rail grade crossings.

PubMed

Lu, Pan; Tolliver, Denver

2016-05-01

Considerable research has focused on roadway accident frequency analysis, but relatively little research has examined safety evaluation at highway-rail grade crossings. Highway-rail grade crossings are critical spatial locations of utmost importance for transportation safety because traffic crashes at highway-rail grade crossings are often catastrophic with serious consequences. The Poisson regression model has been employed to analyze vehicle accident frequency as a good starting point for many years. The most commonly applied variations of Poisson including negative binomial, and zero-inflated Poisson. These models are used to deal with common crash data issues such as over-dispersion (sample variance is larger than the sample mean) and preponderance of zeros (low sample mean and small sample size). On rare occasions traffic crash data have been shown to be under-dispersed (sample variance is smaller than the sample mean) and traditional distributions such as Poisson or negative binomial cannot handle under-dispersion well. The objective of this study is to investigate and compare various alternate highway-rail grade crossing accident frequency models that can handle the under-dispersion issue. The contributions of the paper are two-fold: (1) application of probability models to deal with under-dispersion issues and (2) obtain insights regarding to vehicle crashes at public highway-rail grade crossings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of reportable disease incidence after Hurricane Sandy, New York City, 2012.

PubMed

Greene, Sharon K; Wilson, Elisha L; Konty, Kevin J; Fine, Annie D

2013-10-01

Hurricane Sandy's October 29, 2012 arrival in New York City caused flooding, power disruption, and population displacement. Infectious disease risk may have been affected by floodwater exposure, residence in emergency shelters, overcrowding, and lack of refrigeration or heating. For 42 reportable diseases that could have been affected by hurricane-related exposures, we developed methods to assess whether hurricane-affected areas had higher disease incidence than other areas of NYC. We identified post-hurricane cases as confirmed, probable, or suspected cases with onset or diagnosis between October 30 and November 26 that were reported via routine passive surveillance. Pre-hurricane cases for the same 4-week period were identified in 5 prior years, 2007-2011. Cases were geocoded to the census tract of residence. Using data compiled by the NYC Office of Emergency Management, we determined (1) the proportion of the population in each census tract living in a flooded block and (2) the subset of flooded tracts severely "impacted", e.g., by prolonged service outages or physical damage. A separate multivariable regression model was constructed for each disease, modeling the outcome of case counts using a negative binomial distribution. Independent variables were: neighborhood poverty; whether cases were pre- or post-hurricane (time); the proportion of the population flooded in impacted and not impacted tracts; and interaction terms between the flood/impact variables and time. Models used repeated measures to adjust for correlated observations from the same tract and an offset term of the log of the population size. Sensitivity analyses assessed the effects of case count fluctuations and accounted for variations in reporting volume by using an offset term of the log of total cases. Only legionellosis was statistically significantly associated with increased occurrence in flooded/impacted areas post-hurricane, adjusting for baseline differences (P = .04). However, there was only 1 legionellosis case post-hurricane in a flooded/impacted area. Hurricane Sandy did not appear to elevate reportable disease incidence in NYC. Defining and acquiring reliable data and meta-data regarding hurricane-affected areas was a challenge in the weeks post-storm. Relevant metrics could be developed during disaster preparedness planning. These methods to detect excess disease can be adapted for future emergencies.

On comparison of net survival curves.

PubMed

Pavlič, Klemen; Perme, Maja Pohar

2017-05-02

Relative survival analysis is a subfield of survival analysis where competing risks data are observed, but the causes of death are unknown. A first step in the analysis of such data is usually the estimation of a net survival curve, possibly followed by regression modelling. Recently, a log-rank type test for comparison of net survival curves has been introduced and the goal of this paper is to explore its properties and put this methodological advance into the context of the field. We build on the association between the log-rank test and the univariate or stratified Cox model and show the analogy in the relative survival setting. We study the properties of the methods using both the theoretical arguments as well as simulations. We provide an R function to enable practical usage of the log-rank type test. Both the log-rank type test and its model alternatives perform satisfactory under the null, even if the correlation between their p-values is rather low, implying that both approaches cannot be used simultaneously. The stratified version has a higher power in case of non-homogeneous hazards, but also carries a different interpretation. The log-rank type test and its stratified version can be interpreted in the same way as the results of an analogous semi-parametric additive regression model despite the fact that no direct theoretical link can be established between the test statistics.

Investigation of the factors influencing the survival of Bifidobacterium longum in model acidic solutions and fruit juices.

PubMed

Nualkaekul, Sawaminee; Salmeron, Ivan; Charalampopoulos, Dimitris

2011-12-01

The survival of Bifidobacterium longum NCIMB 8809 was studied during refrigerated storage for 6weeks in model solutions, based on which a mathematical model was constructed describing cell survival as a function of pH, citric acid, protein and dietary fibre. A Central Composite Design (CCD) was developed studying the influence of four factors at three levels, i.e., pH (3.2-4), citric acid (2-15g/l), protein (0-10g/l), and dietary fibre (0-8g/l). In total, 31 experimental runs were carried out. Analysis of variance (ANOVA) of the regression model demonstrated that the model fitted well the data. From the regression coefficients it was deduced that all four factors had a statistically significant (P<0.05) negative effect on the log decrease [log10N0 week-log10N6 week], with the pH and citric acid being the most influential ones. Cell survival during storage was also investigated in various types of juices, including orange, grapefruit, blackcurrant, pineapple, pomegranate and strawberry. The highest cell survival (less than 0.4log decrease) after 6weeks of storage was observed in orange and pineapple, both of which had a pH of about 3.8. Although the pH of grapefruit and blackcurrant was similar (pH ∼3.2), the log decrease of the former was ∼0.5log, whereas of the latter was ∼0.7log. One reason for this could be the fact that grapefruit contained a high amount of citric acid (15.3g/l). The log decrease in pomegranate and strawberry juices was extremely high (∼8logs). The mathematical model was able to predict adequately the cell survival in orange, grapefruit, blackcurrant, and pineapple juices. However, the model failed to predict the cell survival in pomegranate and strawberry, most likely due to the very high levels of phenolic compounds in these two juices. Copyright © 2011 Elsevier Ltd. All rights reserved.

Economic independence in survivors of cancer diagnosed at a young age: A Norwegian national cohort study.

PubMed

Gunnes, Maria W; Lie, Rolv Terje; Bjørge, Tone; Syse, Astri; Ruud, Ellen; Wesenberg, Finn; Moster, Dag

2016-12-15

The impact of cancer on socioeconomic outcomes is attracting attention as the number of survivors of cancer in young age continues to rise. This study examines economic independence in a national cohort of survivors of cancer at a young age in Norway. Through the linkage of several national registries, the study cohort comprised 1,212,013 individuals born in Norway during 1965 through 1985, of which 5440 had received a cancer diagnosis before age 25 years. Follow-up was through 2007, and the main outcomes were receipt of governmental financial assistance, employment, income, and occupation. Analytic methods included Cox proportional hazard regression, log-binomial regression, and quantile regression models. Individuals in the cancer survivor group had an increased probability of receiving governmental financial assistance (men: hazard ratio [HR], 1.4; 95% confidence interval [CI], 1.3-1.5; women: HR, 1.5; 95% CI, 1.3-1.6) and of not being employed (men: HR, 1.4; 95% CI, 1.2-1.7; women: HR, 1.4; 95% CI, 1.2-1.6) compared with those in the noncancer group. Income discrepancies were particularly pronounced for survivors of central nervous system tumors. There was no difference in representation in higher skilled occupations. Survivors of cancer at a young age in Norway had an increased risk of being economically dependent and unemployed. This was evident in several tumor groups and was most pronounced in female survivors. There were only small differences in income or representation in higher skilled occupations for most employed survivors compared with the noncancer group. The current results are important for understanding the impact of a cancer diagnosis at a young age on subsequent job market outcomes. Cancer 2016;122:3873-3882. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

Technology diffusion in hospitals: a log odds random effects regression model.

PubMed

Blank, Jos L T; Valdmanis, Vivian G

2015-01-01

This study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to describe the diffusion of technologies. We distinguish a number of determinants, such as service, physician, and environmental, financial and organizational characteristics of the 60 Dutch hospitals in our sample. On the basis of this data set on Dutch general hospitals over the period 1995-2002, we conclude that there is a relation between a number of determinants and the diffusion of innovations underlining conclusions from earlier research. Positive effects were found on the basis of the size of the hospitals, competition and a hospital's commitment to innovation. It appears that if a policy is developed to further diffuse innovations, the external effects of demand and market competition need to be examined, which would de facto lead to an efficient use of technology. For the individual hospital, instituting an innovations office appears to be the most prudent course of action. © 2013 The Authors. International Journal of Health Planning and Management published by John Wiley & Sons, Ltd.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Community covariates of malnutrition based mortality among older adults.

PubMed

Lee, Matthew R; Berthelot, Emily R

2010-05-01

The purpose of this study was to identify community level covariates of malnutrition-based mortality among older adults. A community level framework was delineated which explains rates of malnutrition-related mortality among older adults as a function of community levels of socioeconomic disadvantage, disability, and social isolation among members of this group. County level data on malnutrition mortality of people 65 years of age and older for the period 2000-2003 were drawn from the CDC WONDER system databases. County level measures of older adult socioeconomic disadvantage, disability, and social isolation were derived from the 2000 US Census of Population and Housing. Negative binomial regression models adjusting for the size of the population at risk, racial composition, urbanism, and region were estimated to assess the relationships among these indicators. Results from negative binomial regression analysis yielded the following: a standard deviation increase in socioeconomic/physical disadvantage was associated with a 12% increase in the rate of malnutrition mortality among older adults (p < 0.001), whereas a standard deviation increase in social isolation was associated with a 5% increase in malnutrition mortality among older adults (p < 0.05). Community patterns of malnutrition based mortality among older adults are partly a function of levels of socioeconomic and physical disadvantage and social isolation among older adults. 2010 Elsevier Inc. All rights reserved.

Association between adherence to physical activity guidelines and health-related quality of life among individuals with physician-diagnosed arthritis.

PubMed

Austin, Shamly; Qu, Haiyan; Shewchuk, Richard M

2012-10-01

To examine the association between adherence to physical activity guidelines and health-related quality of life (HRQOL) among individuals with arthritis. A cross-sectional sample with 33,071 US adults, 45 years or older with physician-diagnosed arthritis was obtained from 2007 Behavioral Risk Factor Surveillance System survey. We conducted negative binomial regression analysis to examine HRQOL as a function of adherence to physical activity guidelines controlling for physicians' recommendations for physical activity, age, sex, race, education, marital status, employment, annual income, health insurance, personal physician, emotional support, body mass index, activity limitations, health status, and co-morbidities based on Behavioral Model of Health Services Utilization. Descriptive statistics showed that 60% adults with arthritis did not adhere to physical activity guidelines, mean physically and mentally unhealthy days were 7.7 and 4.4 days, respectively. Results from negative binomial regression indicated that individuals who did not adhere to physical activity guidelines had 1.14 days more physically unhealthy days and 1.12 days more mentally unhealthy days than those who adhered controlling for covariates. Adherence to physical activity is important to improve HRQOL for individuals with arthritis. However, adherence is low among this population. Interventions are required to engage individuals with arthritis in physical activity.

Prediction of Compressional Wave Velocity Using Regression and Neural Network Modeling and Estimation of Stress Orientation in Bokaro Coalfield, India

NASA Astrophysics Data System (ADS)

Paul, Suman; Ali, Muhammad; Chatterjee, Rima

2018-01-01

Velocity of compressional wave ( V P) of coal and non-coal lithology is predicted from five wells from the Bokaro coalfield (CF), India. Shear sonic travel time logs are not recorded for all wells under the study area. Shear wave velocity ( Vs) is available only for two wells: one from east and other from west Bokaro CF. The major lithologies of this CF are dominated by coal, shaly coal of Barakar formation. This paper focuses on the (a) relationship between Vp and Vs, (b) prediction of Vp using regression and neural network modeling and (c) estimation of maximum horizontal stress from image log. Coal characterizes with low acoustic impedance (AI) as compared to the overlying and underlying strata. The cross-plot between AI and Vp/ Vs is able to identify coal, shaly coal, shale and sandstone from wells in Bokaro CF. The relationship between Vp and Vs is obtained with excellent goodness of fit ( R 2) ranging from 0.90 to 0.93. Linear multiple regression and multi-layered feed-forward neural network (MLFN) models are developed for prediction Vp from two wells using four input log parameters: gamma ray, resistivity, bulk density and neutron porosity. Regression model predicted Vp shows poor fit (from R 2 = 0.28) to good fit ( R 2 = 0.79) with the observed velocity. MLFN model predicted Vp indicates satisfactory to good R2 values varying from 0.62 to 0.92 with the observed velocity. Maximum horizontal stress orientation from a well at west Bokaro CF is studied from Formation Micro-Imager (FMI) log. Breakouts and drilling-induced fractures (DIFs) are identified from the FMI log. Breakout length of 4.5 m is oriented towards N60°W whereas the orientation of DIFs for a cumulative length of 26.5 m is varying from N15°E to N35°E. The mean maximum horizontal stress in this CF is towards N28°E.

On the equivalence of case-crossover and time series methods in environmental epidemiology.

PubMed

Lu, Yun; Zeger, Scott L

2007-04-01

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.

Association of stressful life events with accelerated bone loss in older men: the Osteoporotic Fractures in Men (MrOS) Study

PubMed Central

Fink, Howard A.; Kuskowski, Michael A.; Cauley, Jane A.; Taylor, Brent C.; Schousboe, John T.; Cawthon, Peggy M.; Ensrud, Kristine E.

2015-01-01

Purpose/Introduction Prior studies suggest that stressful life events may increase adverse health outcomes, including falls and possibly fractures. The current study builds on these findings and examines whether stressful life events are associated with increased bone loss. Methods 4388 men aged ≥65 years in the Osteoporotic Fractures in Men study completed total hip bone mineral density (BMD) measures at baseline and visit 2, approximately 4.6 years later, and self-reported stressful life events data mid-way between baseline and visit 2, and at visit 2. We used linear regression to model the association of stressful life events with concurrent annualized total hip BMD loss, and log binomial regression or Poisson regression to model risk of concurrent accelerated BMD loss (>1 SD more than mean annualized change). Results 75.3% of men reported ≥1 type of stressful life event, including 43.3% with ≥2 types of stressful life events. Mean annualized BMD loss was −0.36% (SD 0.88) and 13.9% of men were categorized with accelerated BMD loss (about 5.7% or more total loss). Rate of annualized BMD loss increased with the number of types of stressful life events after adjustment for age (p<0.001), but not after multivariable adjustment (p=0.07). Multivariable-adjusted risk of accelerated BMD loss increased with the number of types of stressful life events (RR, 1.10 [95% CI, 1.04–1.16]) per increase of 1 type of stressful life event). Fracture risk was not significantly different between stressful life event-accelerated bone loss subgroups (p=0.08). Conclusions In these older men, stressful life events were associated with a small, dose-related increase in risk of concurrent accelerated hip bone loss. Low frequency of fractures limited assessment of whether rapid bone loss mediates any association of stressful life events with incident fractures. Future studies are needed to confirm these findings and to investigate the mechanism that may underlie this association. PMID:25169421

Increased symptom reporting persists in 1990-1991 Gulf War veterans 20 years post deployment.

PubMed

Gwini, Stella M; Forbes, Andrew B; Kelsall, Helen L; Ikin, Jillian F; Sim, Malcolm R

2015-12-01

Following the 1990-1991 Gulf War, Gulf War veterans (veterans) reported health symptoms more commonly than non-deployed groups. This article examines symptom persistence, incidence and prevalence 20 years on. In 2000-2003 and 2011-2012, a 63-item symptom checklist was administered to 697 veterans and 659 comparison group. Symptomatology was compared using log-binomial regression. Both veterans and comparison group reported significantly increased prevalence (3-52%) over time in more than half the symptoms, with a similar overall rate of increase. Half the symptoms had higher incidence (risk-ratios ranged 1.43-1.50) and a quarter were more persistent (risk-ratios ranged 1.12-1.20) in veterans than the comparison group. Symptomatology increased in both groups over time, but persisted to a similar extent and had higher incidence among veterans than the comparison group. The gap in symptom prevalence between the two groups remained unchanged. These findings suggest enduring health consequences of Gulf War service. © 2015 Commonwealth of Australia. American Journal of Industrial Medicine © 2015 Wiley Periodicals, Inc.

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City.

PubMed

Furr-Holden, C Debra M; Milam, Adam J; Nesoff, Elizabeth D; Johnson, Renee M; Fakunle, David O; Jennings, Jacky M; Thorpe, Roland J

2016-01-01

This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores.

[Epidemiology of scrub typhus and influencing factors in Yunnan province, 2006-2013].

PubMed

Sun, Y; Shi, C; Li, X L; Fang, L Q; Cao, W C

2018-01-10

Objective: To understand the epidemiological characteristics of scrub typhu s and influencing factors in Yunnan province, and provide further information for the prevention and control of scrub typhus. Methods: Based on the incidence data of scrub typhus reported in Yunnan from 2006 to 2013, the epidemiological characteristics of scrub typhus were analyzed and related environmental factors were identified with panel negative binomial regression model. Results: A total of 8 980 scrub typhus cases were reported during 2006-2013 in Yunnan. The average annual incidence was 2.46/100 000, with an uptrend observed. Natural focus expansion was found, affecting 71.3% of the counties in 2013. The epidemic mainly occurred in summer and autumn with the incidence peak during July-October. The annual incidence was higher in females than in males. More cases occurred in children and farmers, the proportions of cases in farmers and pre-school aged children showed an obvious increase. Panel negative binomial regression model indicated that the transmission risk of scrub typhus was positive associated with monthly temperature and monthly relative humidity. Furthermore, an "U" pattern between the risk and the increased coverage of cropland and grassland as well as an "inverted-U" pattern between the risk and increased coverage of shrub were observed. Conclusion: It is necessary to strengthen the scrub typhus surveillance in warm and moist areas as well as the areas with high coverage of cropland and grassland in Yunnan, and the health education in children and farmers who are at high risk.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

Statistical methods for the beta-binomial model in teratology.

PubMed Central

Yamamoto, E; Yanagimoto, T

1994-01-01

The beta-binomial model is widely used for analyzing teratological data involving littermates. Recent developments in statistical analyses of teratological data are briefly reviewed with emphasis on the model. For statistical inference of the parameters in the beta-binomial distribution, separation of the likelihood introduces an likelihood inference. This leads to reducing biases of estimators and also to improving accuracy of empirical significance levels of tests. Separate inference of the parameters can be conducted in a unified way. PMID:8187716

Early-Life Exposure to Outdoor Air Pollution and Respiratory Health, Ear Infections, and Eczema in Infants from the INMA Study

PubMed Central

Pedersen, Marie; Garcia-Esteban, Raquel; Ballester, Ferran; Basterrechea, Mikel; Esplugues, Ana; Fernández-Somoano, Ana; Lertxundi, Aitana; Tardón, Adonina; Sunyer, Jordi

2012-01-01

Background: Prenatal and early-life periods may be critical windows for harmful effects of air pollution on infant health. Objectives: We studied the association of air pollution exposure during pregnancy and the first year of life with respiratory illnesses, ear infections, and eczema during the first 12–18 months of age in a Spanish birth cohort of 2,199 infants. Methods: We obtained parentally reported information on doctor-diagnosed lower respiratory tract infections (LRTI) and parental reports of wheezing, eczema, and ear infections. We estimated individual exposures to nitrogen dioxide (NO2) and benzene with temporally adjusted land use regression models. We used log-binomial regression models and a combined random-effects meta-analysis to estimate the effects of air pollution exposure on health outcomes across the four study locations. Results: A 10-µg/m3 increase in average NO2 during pregnancy was associated with LRTI [relative risk (RR) = 1.05; 95% CI: 0.98, 1.12] and ear infections (RR = 1.18; 95% CI: 0.98, 1.41). The RRs for an interquartile range (IQR) increase in NO2 were 1.08 (95% CI: 0.97, 1.21) for LRTI and 1.31 (95% CI: 0.97, 1.76) for ear infections. Compared with NO2, the association for an IQR increase in average benzene exposure was similar for LRTI (RR = 1.06; 95% CI: 0.94, 1.19) and slightly lower for ear infections (RR = 1.17; 95% CI: 0.93, 1.46). Associations were slightly stronger among infants whose mothers spent more time at home during pregnancy. Air pollution exposure during the first year was highly correlated with prenatal exposure, so we were unable to discern the relative importance of each exposure period. Conclusions: Our findings support the hypothesis that early-life exposure to ambient air pollution may increase the risk of upper and lower respiratory tract infections in infants. PMID:23221880

Reducing lost to follow-up in a large clinical trial of prevention of mother-to-child transmission of HIV: The Breastfeeding, Antiretrovirals and Nutrition (BAN) study experience

PubMed Central

Sellers, Christopher J; Lee, Hana; Chasela, Charles; Kayira, Dumbani; Soko, Alice; Mofolo, Innocent; Ellington, Sascha; Hudgens, Michael G; Kourtis, Athena P; King, Caroline C; Jamieson, Denise J; van der Horst, Charles

2014-01-01

Background/Aims Retaining patients in prevention of mother-to-child transmission of HIV studies can be challenging in resource limited settings, where high lost to follow-up (LTFU) rates have been reported. In this paper, we describe the effectiveness of methods used to encourage retention in the Breastfeeding, Antiretrovirals, and Nutrition (BAN) study and analyze factors associated with LTFU in the study. Methods The BAN clinical trial was designed to evaluate the efficacy of 3 different mother-to-child HIV transmission prevention strategies. Lower than expected participant retention prompted enhanced efforts to reduce LTFU during the conduct of the trial. Following study completion, we employed regression modeling to determine predictors of perfect attendance and variables associated with being LTFU. Results During the study, intensive tracing efforts were initiated after the first 1686 mother-infant pairs had been enrolled, and 327 pairs were missing. Sixty of these pairs were located and had complete data obtained. Among the 683 participants enrolling after initiation of intensive tracing efforts, the LTFU rate was 3.4%. At study's end, 290 (12.2%) of the 2369 mother-infant pairs were LTFU. Among successfully traced missing pairs, relocation was common and three were deceased. Log-binomial regression modeling revealed higher maternal hemoglobin and older maternal age to be significant predictors of perfect attendance. These factors and the presence of food insecurity were also significantly associated with lower rates of LTFU. Conclusions In this large HIV prevention trial, intensive tracing efforts centered on reaching study participants at their homes succeeded in finding a substantial proportion of LTFU participants, and were very effective in preventing further LTFU during the remainder of the trial. The association between food insecurity and lower rates of LTFU is likely related to the study's provision of nutritional support, including a family maize supplement, which may have contributed to patient retention. PMID:25518956

Factors Associated with Dental Caries in a Group of American Indian Children at age 36 Months

PubMed Central

Warren, John J.; Blanchette, Derek; Dawson, Deborah V.; Marshall, Teresa A.; Phipps, Kathy R.; Starr, Delores; Drake, David R.

2015-01-01

Objectives Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This paper reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Methods Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28 and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary and behavioral factors. Non-parametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Results Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only non-cavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (p<0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. Conclusions By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size and maternal factors, but further analyses are needed to better understand caries in this population. PMID:26544674

Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center.

PubMed

Baghestani, Ahmad Reza; Zayeri, Farid; Akbari, Mohammad Esmaeil; Shojaee, Leyla; Khadembashi, Naghmeh; Shahmirzalou, Parviz

2015-01-01

The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

Social determinants of leprosy in a hyperendemic State in North Brazil.

PubMed

Monteiro, Lorena Dias; Mota, Rosa Maria Salani; Martins-Melo, Francisco Rogerlândio; Alencar, Carlos Henrique; Heukelbach, Jorg

2017-07-20

To identify the socioeconomic, demographic, operational, and health service-related factors associated with the occurrence of leprosy in a hyperendemic State in North Brazil. This is an ecological study based on secondary data from the Sistema de Informações de Agravos de Notificação in municipalities of the State of Tocantins from 2001 to 2012. Units of analysis were the 139 municipalities of the State. Negative binomial log linear regression models were used to estimate incidence rate ratios. In bivariate analysis, the incidence rate ratios were significantly higher for municipalities with higher income ratio of the poorest 20.0% (1.47; 95%CI 1.19-1.81) and better Municipal Human Development Index (1.53; 95%CI 1.14-2.06). In multivariate analysis, the incidence rate ratios were significantly higher in municipalities with higher proportion of immigrants (1.31; 95%CI 1.11-1.55) and higher proportion of households with waste collection (1.37; 95%CI 1.11-1.69). There was a significant reduction in the incidence rate ratio with increased coverage of the Bolsa Família Program (0.98; 95%CI 0.96-0.99). Control programs need to focus on activities in municipalities of greater social vulnerability with intersectoral investment for the improvement of the living conditions of the population. Identificar fatores socioeconômicos, demográficos, operacionais e de serviços de saúde associados à ocorrência da hanseníase em um estado hiperendêmico do norte do Brasil. Estudo ecológico com dados secundários do Sistema de Informações de Agravos de Notificação em municípios do estado do Tocantins de 2001 a 2012. As unidades de análise foram os 139 municípios do estado. Modelos de regressão log linear binomial negativa foram utilizados para estimar as razões de taxas de incidência. Na análise bivariada, a razão de taxa de incidência foi significativamente maior para os municípios com maior razão de renda dos 20,0% mais pobres (1,47; IC95% 1,19-1,81) e melhor Índice de Desenvolvimento Humano Municipal (1,53; IC95% 1,14-2,06). Na múltipla, a razão de taxa de incidência foi significativamente superior em municípios com maior concentração de imigrantes (1,31; IC95% 1,11-1,55) e proporção de domicílios com coleta de lixo (1,37; IC95% 1,11-1,69). Houve redução significativa da razão de taxa de incidência com o aumento da cobertura do programa bolsa família (0,98; IC95% 0,96-0,99). Os programas de controle precisam focar as atividades em municípios de maior vulnerabilidade social com investimentos intersetoriais para a melhoria das condições de vida da população.

Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models.

PubMed

Cai, Qing; Lee, Jaeyoung; Eluru, Naveen; Abdel-Aty, Mohamed

2016-08-01

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chromatographic Behaviour Predicts the Ability of Potential Nootropics to Permeate the Blood-Brain Barrier

PubMed Central

Farsa, Oldřich

2013-01-01

The log BB parameter is the logarithm of the ratio of a compound’s equilibrium concentrations in the brain tissue versus the blood plasma. This parameter is a useful descriptor in assessing the ability of a compound to permeate the blood-brain barrier. The aim of this study was to develop a Hansch-type linear regression QSAR model that correlates the parameter log BB and the retention time of drugs and other organic compounds on a reversed-phase HPLC containing an embedded amide moiety. The retention time was expressed by the capacity factor log k′. The second aim was to estimate the brain’s absorption of 2-(azacycloalkyl)acetamidophenoxyacetic acids, which are analogues of piracetam, nefiracetam, and meclofenoxate. Notably, these acids may be novel nootropics. Two simple regression models that relate log BB and log k′ were developed from an assay performed using a reversed-phase HPLC that contained an embedded amide moiety. Both the quadratic and linear models yielded statistical parameters comparable to previously published models of log BB dependence on various structural characteristics. The models predict that four members of the substituted phenoxyacetic acid series have a strong chance of permeating the barrier and being absorbed in the brain. The results of this study show that a reversed-phase HPLC system containing an embedded amide moiety is a functional in vitro surrogate of the blood-brain barrier. These results suggest that racetam-type nootropic drugs containing a carboxylic moiety could be more poorly absorbed than analogues devoid of the carboxyl group, especially if the compounds penetrate the barrier by a simple diffusion mechanism. PMID:23641330

Modeling surficial sand and gravel deposits

USGS Publications Warehouse

Bliss, J.D.; Page, N.J.

1994-01-01

Mineral-deposit models are an integral part of quantitative mineral-resource assessment. As the focus of mineral-deposit modeling has moved from metals to industrial minerals, procedure has been modified and may be sufficient to model surficial sand and gravel deposits. Sand and gravel models are needed to assess resource-supply analyses for planning future development and renewal of infrastructure. Successful modeling of sand and gravel deposits must address (1) deposit volumes and geometries, (2) sizes of fragments within the deposits, (3) physical characteristics of the material, and (4) chemical composition and chemical reactivity of the material. Several models of sand and gravel volumes and geometries have been prepared and suggest the following: Sand and gravel deposits in alluvial fans have a median volume of 35 million m3. Deposits in all other geologic settings have a median volume of 5.4 million m3, a median area of 120 ha, and a median thickness of 4 m. The area of a sand and gravel deposit can be predicted from volume using a regression model (log [area (ha)] =1.47+0.79 log [volume (million m3)]). In similar fashion, the volume of a sand and gravel deposit can be predicted from area using the regression (log [volume (million m3)]=-1.45+1.07 log [area (ha)]). Classifying deposits by fragment size can be done using models of the percentage of sand, gravel, and silt within deposits. A classification scheme based on fragment size is sufficiently general to be applied anywhere. ?? 1994 Oxford University Press.

The magnetisation distribution of the Ising model - a new approach

NASA Astrophysics Data System (ADS)

Hakan Lundow, Per; Rosengren, Anders

2010-03-01

A completely new approach to the Ising model in 1 to 5 dimensions is developed. We employ a generalisation of the binomial coefficients to describe the magnetisation distributions of the Ising model. For the complete graph this distribution is exact. For simple lattices of dimensions d=1 and d=5 the magnetisation distributions are remarkably well-fitted by the generalized binomial distributions. For d=4 we are only slightly less successful, while for d=2,3 we see some deviations (with exceptions!) between the generalized binomial and the Ising distribution. The results speak in favour of the generalized binomial distribution's correctness regarding their general behaviour in comparison to the Ising model. A theoretical analysis of the distribution's moments also lends support their being correct asymptotically, including the logarithmic corrections in d=4. The full extent to which they correctly model the Ising distribution, and for which graph families, is not settled though.

Quantifying the safety effects of horizontal curves on two-way, two-lane rural roads.

PubMed

Gooch, Jeffrey P; Gayah, Vikash V; Donnell, Eric T

2016-07-01

The objective of this study is to quantify the safety performance of horizontal curves on two-way, two-lane rural roads relative to tangent segments. Past research is limited by small samples sizes, outdated statistical evaluation methods, and unreported standard errors. This study overcomes these drawbacks by using the propensity scores-potential outcomes framework. The impact of adjacent curves on horizontal curve safety is also explored using a cross-sectional regression model of only horizontal curves. The models estimated in the present study used eight years of crash data (2005-2012) obtained from over 10,000 miles of state-owned two-lane rural roads in Pennsylvania. These data included information on roadway geometry (e.g., horizontal curvature, lane width, and shoulder width), traffic volume, roadside hazard rating, and the presence of various low-cost safety countermeasures (e.g., centerline and shoulder rumble strips, curve and intersection warning pavement markings, and aggressive driving pavement dots). Crash prediction is performed by means of mixed effects negative binomial regression using the explanatory variables noted previously, as well as attributes of adjacent horizontal curves. The results indicate that both the presence of a horizontal curve and its degree of curvature must be considered when predicting the frequency of total crashes on horizontal curves. Both are associated with an increase in crash frequency, which is consistent with previous findings in the literature. Mixed effects negative binomial regression models for total crash frequency on horizontal curves indicate that the distance to adjacent curves is not statistically significant. However, the degree of curvature of adjacent curves in close proximity (within 0.75 miles) was found to be statistically significant and negatively correlated with crash frequency on the subject curve. This is logical, as drivers exiting a sharp curve are likely to be driving slower and with more awareness as they approach the next horizontal curve. Copyright © 2016 Elsevier Ltd. All rights reserved.

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

PubMed

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

Environmental, Spatial, and Sociodemographic Factors Associated with Nonfatal Injuries in Indonesia.

PubMed

Irianti, Sri; Prasetyoputra, Puguh

2017-01-01

Background . The determinants of injuries and their reoccurrence in Indonesia are not well understood, despite their importance in the prevention of injuries. Therefore, this study seeks to investigate the environmental, spatial, and sociodemographic factors associated with the reoccurrence of injuries among Indonesian people. Methods . Data from the 2013 round of the Indonesia Baseline Health Research (IBHR 2013) were analysed using a two-part hurdle regression model. A logit regression model was chosen for the zero-hurdle part , while a zero-truncated negative binomial regression model was selected for the counts part . Odds ratio (OR) and incidence rate ratio (IRR) were the measures of association, respectively. Results . The results suggest that living in a household with distant drinking water source, residing in slum areas, residing in Eastern Indonesia, having low educational attainment, being men, and being poorer are positively related to the likelihood of experiencing injury. Moreover, being a farmer or fishermen, having low educational attainment, and being men are positively associated with the frequency of injuries. Conclusion . This study would be useful to prioritise injury prevention programs in Indonesia based on the environmental, spatial, and sociodemographic characteristics.

The effect of cotrimoxazole prophylactic treatment on malaria, birth outcomes, and postpartum CD4 count in HIV-infected women.

PubMed

Dow, Anna; Kayira, Dumbani; Hudgens, Michael G; Van Rie, Annelies; King, Caroline C; Ellington, Sascha; Chome, Nelecy; Kourtis, Athena; Turner, Abigail Norris; Kacheche, Zebrone; Jamieson, Denise J; Chasela, Charles; van der Horst, Charles

2013-01-01

Limited data exist on cotrimoxazole prophylactic treatment (CPT) in pregnant women, including protection against malaria versus standard intermittent preventive therapy with sulfadoxine-pyrimethamine (IPTp). Using observational data we examined the effect of CPT in HIV-infected pregnant women on malaria during pregnancy, low birth weight and preterm birth using proportional hazards, logistic, and log binomial regression, respectively. We used linear regression to assess effect of CPT on CD4 count. Data from 468 CPT-exposed and 768 CPT-unexposed women were analyzed. CPT was associated with protection against malaria versus IPTp (hazard ratio: 0.35, 95% Confidence Interval (CI): 0.20, 0.60). After adjustment for time period this effect was not statistically significant (adjusted hazard ratio: 0.66, 95% CI: 0.28, 1.52). Among women receiving and not receiving CPT, rates of low birth weight (7.1% versus 7.6%) and preterm birth (23.5% versus 23.6%) were similar. CPT was associated with lower CD4 counts 24 weeks postpartum in women receiving (-77.6 cells/ μ L, 95% CI: -125.2, -30.1) and not receiving antiretrovirals (-33.7 cells/ μ L, 95% CI: -58.6, -8.8). Compared to IPTp, CPT provided comparable protection against malaria in HIV-infected pregnant women and against preterm birth or low birth weight. Possible implications of CPT-associated lower CD4 postpartum warrant further examination.

Gender-specific associations between leisure-time physical activity and symptoms of anxiety: the HUNT study.

PubMed

Brunes, Audun; Gudmundsdottir, Sigridur Lara; Augestad, Liv Berit

2015-03-01

The underlying goal of the study was to examine gender-specific effects of leisure-time physical activity on the development of symptoms of anxiety. The second wave of a prospective cohort survey (HUNT 2) was conducted during 1995-1997 in the county of Nord-Trøndelag, Norway, with a follow-up in 2006-2008 (HUNT 3). The sample consisted of 12,796 women and 11,195 men with an age range of 19-85 years. A binomial model with a log-link function and generalized linear model analysis with gamma distribution was used to assess the association between physical activity and anxiety symptoms (Hospital Anxiety and Depression Scale anxiety subscale, HADS-A). A total of 1,211 (9.5 %) women and 650 (5.8 %) men developed HADS-defined anxiety (≥8 on the HADS-A scale). Men who scored in the middle tertile of the calculated physical activity index developed significantly fewer cases of HADS-defined anxiety compared with men in the lowest tertile (p < 0.05). In the gamma regression analysis for women, having higher scores on the moderate-high physical activity was associated with fewer symptoms of anxiety (p < 0.01). Women developed almost twice as many cases of HADS-defined anxiety compared to men. Significant associations were found between general leisure-time physical activity and anxiety symptoms among women and men, but the true effect is likely to be different from the observed associations due to several threats to the internal validity in the study.

Coronary artery calcium distributions in older persons in the AGES-Reykjavik study

PubMed Central

Gudmundsson, Elias Freyr; Gudnason, Vilmundur; Sigurdsson, Sigurdur; Launer, Lenore J.; Harris, Tamara B.; Aspelund, Thor

2013-01-01

Coronary Artery Calcium (CAC) is a sign of advanced atherosclerosis and an independent risk factor for cardiac events. Here, we describe CAC-distributions in an unselected aged population and compare modelling methods to characterize CAC-distribution. CAC is difficult to model because it has a skewed and zero inflated distribution with over-dispersion. Data are from the AGES-Reykjavik sample, a large population based study [2002-2006] in Iceland of 5,764 persons aged 66-96 years. Linear regressions using logarithmic- and Box-Cox transformations on CAC+1, quantile regression and a Zero-Inflated Negative Binomial model (ZINB) were applied. Methods were compared visually and with the PRESS-statistic, R2 and number of detected associations with concurrently measured variables. There were pronounced differences in CAC according to sex, age, history of coronary events and presence of plaque in the carotid artery. Associations with conventional coronary artery disease (CAD) risk factors varied between the sexes. The ZINB model provided the best results with respect to the PRESS-statistic, R2, and predicted proportion of zero scores. The ZINB model detected similar numbers of associations as the linear regression on ln(CAC+1) and usually with the same risk factors. PMID:22990371

Factors affecting road mortality of white-tailed deer in eastern South Dakota

USGS Publications Warehouse

Grovenburg, Troy W.; Jenks, Jonathan A.; Klaver, Robert W.; Monteith, Kevin L.; Galster, Dwight H.; Schauer, Ron J.; Morlock, Wilbert W.; Delger, Joshua A.

2008-01-01

White-tailed deer (Odocoileus virginianus) mortalities (n = 4,433) caused by collisions with automobiles during 2003 were modeled in 35 counties in eastern South Dakota. Seventeen independent variables and 5 independent variable interactions were evaluated to explain deer mortalities. A negative binomial regression model (Ln Y = 1.25 – 0.12 [percentage tree coverage] + 0.0002 [county area] + 5.39 [county hunter success rate] + 0.0023 [vehicle proxy 96–104 km/hr roads], model deviance = 33.43, χ2 = 27.53, df = 27) was chosen using a combination of a priori model selection and AICc. Management options include use of the model to predict road mortalities and to increase the number of hunting licenses, which could result in fewer DVCs.

Environmental factors and flow paths related to Escherichia coli concentrations at two beaches on Lake St. Clair, Michigan, 2002–2005

USGS Publications Warehouse

Holtschlag, David J.; Shively, Dawn; Whitman, Richard L.; Haack, Sheridan K.; Fogarty, Lisa R.

2008-01-01

Regression analyses and hydrodynamic modeling were used to identify environmental factors and flow paths associated with Escherichia coli (E. coli) concentrations at Memorial and Metropolitan Beaches on Lake St. Clair in Macomb County, Mich. Lake St. Clair is part of the binational waterway between the United States and Canada that connects Lake Huron with Lake Erie in the Great Lakes Basin. Linear regression, regression-tree, and logistic regression models were developed from E. coli concentration and ancillary environmental data. Linear regression models on log10 E. coli concentrations indicated that rainfall prior to sampling, water temperature, and turbidity were positively associated with bacteria concentrations at both beaches. Flow from Clinton River, changes in water levels, wind conditions, and log10 E. coli concentrations 2 days before or after the target bacteria concentrations were statistically significant at one or both beaches. In addition, various interaction terms were significant at Memorial Beach. Linear regression models for both beaches explained only about 30 percent of the variability in log10 E. coli concentrations. Regression-tree models were developed from data from both Memorial and Metropolitan Beaches but were found to have limited predictive capability in this study. The results indicate that too few observations were available to develop reliable regression-tree models. Linear logistic models were developed to estimate the probability of E. coli concentrations exceeding 300 most probable number (MPN) per 100 milliliters (mL). Rainfall amounts before bacteria sampling were positively associated with exceedance probabilities at both beaches. Flow of Clinton River, turbidity, and log10 E. coli concentrations measured before or after the target E. coli measurements were related to exceedances at one or both beaches. The linear logistic models were effective in estimating bacteria exceedances at both beaches. A receiver operating characteristic (ROC) analysis was used to determine cut points for maximizing the true positive rate prediction while minimizing the false positive rate. A two-dimensional hydrodynamic model was developed to simulate horizontal current patterns on Lake St. Clair in response to wind, flow, and water-level conditions at model boundaries. Simulated velocity fields were used to track hypothetical massless particles backward in time from the beaches along flow paths toward source areas. Reverse particle tracking for idealized steady-state conditions shows changes in expected flow paths and traveltimes with wind speeds and directions from 24 sectors. The results indicate that three to four sets of contiguous wind sectors have similar effects on flow paths in the vicinity of the beaches. In addition, reverse particle tracking was used for transient conditions to identify expected flow paths for 10 E. coli sampling events in 2004. These results demonstrate the ability to track hypothetical particles from the beaches, backward in time, to likely source areas. This ability, coupled with a greater frequency of bacteria sampling, may provide insight into changes in bacteria concentrations between source and sink areas.

Interrelationships Between Receiver/Relative Operating Characteristics Display, Binomial, Logit, and Bayes' Rule Probability of Detection Methodologies

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2014-01-01

Unknown risks are introduced into failure critical systems when probability of detection (POD) capabilities are accepted without a complete understanding of the statistical method applied and the interpretation of the statistical results. The presence of this risk in the nondestructive evaluation (NDE) community is revealed in common statements about POD. These statements are often interpreted in a variety of ways and therefore, the very existence of the statements identifies the need for a more comprehensive understanding of POD methodologies. Statistical methodologies have data requirements to be met, procedures to be followed, and requirements for validation or demonstration of adequacy of the POD estimates. Risks are further enhanced due to the wide range of statistical methodologies used for determining the POD capability. Receiver/Relative Operating Characteristics (ROC) Display, simple binomial, logistic regression, and Bayes' rule POD methodologies are widely used in determining POD capability. This work focuses on Hit-Miss data to reveal the framework of the interrelationships between Receiver/Relative Operating Characteristics Display, simple binomial, logistic regression, and Bayes' Rule methodologies as they are applied to POD. Knowledge of these interrelationships leads to an intuitive and global understanding of the statistical data, procedural and validation requirements for establishing credible POD estimates.

Speech-discrimination scores modeled as a binomial variable.

PubMed

Thornton, A R; Raffin, M J

1978-09-01

Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

Comparison and Field Validation of Binomial Sampling Plans for Oligonychus perseae (Acari: Tetranychidae) on Hass Avocado in Southern California.

PubMed

Lara, Jesus R; Hoddle, Mark S

2015-08-01

Oligonychus perseae Tuttle, Baker, & Abatiello is a foliar pest of 'Hass' avocados [Persea americana Miller (Lauraceae)]. The recommended action threshold is 50-100 motile mites per leaf, but this count range and other ecological factors associated with O. perseae infestations limit the application of enumerative sampling plans in the field. Consequently, a comprehensive modeling approach was implemented to compare the practical application of various binomial sampling models for decision-making of O. perseae in California. An initial set of sequential binomial sampling models were developed using three mean-proportion modeling techniques (i.e., Taylor's power law, maximum likelihood, and an empirical model) in combination with two-leaf infestation tally thresholds of either one or two mites. Model performance was evaluated using a robust mite count database consisting of >20,000 Hass avocado leaves infested with varying densities of O. perseae and collected from multiple locations. Operating characteristic and average sample number results for sequential binomial models were used as the basis to develop and validate a standardized fixed-size binomial sampling model with guidelines on sample tree and leaf selection within blocks of avocado trees. This final validated model requires a leaf sampling cost of 30 leaves and takes into account the spatial dynamics of O. perseae to make reliable mite density classifications for a 50-mite action threshold. Recommendations for implementing this fixed-size binomial sampling plan to assess densities of O. perseae in commercial California avocado orchards are discussed. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Introductory Statistics in the Garden

ERIC Educational Resources Information Center

Wagaman, John C.

2017-01-01

This article describes four semesters of introductory statistics courses that incorporate service learning and gardening into the curriculum with applications of the binomial distribution, least squares regression and hypothesis testing. The activities span multiple semesters and are iterative in nature.

Determinants of High-School Dropout: A Longitudinal Study in a Deprived Area of Japan.

PubMed

Tabuchi, Takahiro; Fujihara, Sho; Shinozaki, Tomohiro; Fukuhara, Hiroyuki

2018-05-19

Our objective in this study was to find determinants of high-school dropout in a deprived area of Japan using longitudinal data, including socio-demographic and junior high school-period information. We followed 695 students who graduated the junior high school located in a deprived area of Japan between 2002 and 2010 for 3 years after graduation (614 students: follow-up rate, 88.3%). Multivariable log-binomial regression models were used to calculate the prevalence ratios (PRs) for high-school dropout, using multiple imputation (MI) to account for non-response at follow-up. The MI model estimated that 18.7% of students dropped out of high school in approximately 3 years. In the covariates-adjusted model, three factors were significantly associated with high-school dropout: ≥10 days of tardy arrival in junior high school (PR 6.44; 95% confidence interval [CI], 1.69-24.6 for "10-29 days of tardy arrival" and PR 8.01; 95% CI, 2.05-31.3 for "≥30 days of tardy arrival" compared with "0 day of tardy arrival"), daily smoking (PR 2.01; 95% CI, 1.41-2.86) and severe problems, such as abuse and neglect (PR 1.66; 95% CI, 1.16-2.39). Among students with ≥30 days of tardy arrival in addition to daily smoking or experience of severe problems, ≥50% high-school dropout rates were observed. Three determinants of high-school dropout were found: smoking, tardy arrival, and experience of severe problems. These factors were correlated and should be treated as warning signs of complex behavioral and academic problems. Parents, educators, and policy makers should work together to implement effective strategies to prevent school dropout.

Factors Influencing Early Feeding of Foods and Drinks Containing Free Sugars-A Birth Cohort Study.

PubMed

Ha, Diep H; Do, Loc G; Spencer, Andrew John; Thomson, William Murray; Golley, Rebecca K; Rugg-Gunn, Andrew J; Levy, Steven M; Scott, Jane A

2017-10-23

Early feeding of free sugars to young children can increase the preference for sweetness and the risk of consuming a cariogenic diet high in free sugars later in life. This study aimed to investigate early life factors influencing early introduction of foods/drinks containing free sugars. Data from an ongoing population-based birth cohort study in Australia were used. Mothers of newborn children completed questionnaires at birth and subsequently at ages 3, 6, 12, and 24 months. The outcome was reported feeding (Yes/No) at age 6-9 months of common foods/drinks sources of free sugars (hereafter referred as foods/drinks with free sugars). Household income quartiles, mother's sugar-sweetened beverage (SSB) consumption, and other maternal factors were exposure variables. Analysis was conducted progressively from bivariate to multivariable log-binomial regression with robust standard error estimation to calculate prevalence ratios (PR) of being fed foods/drinks with free sugars at an early age (by 6-9 months). Models for both complete cases and with multiple imputations (MI) for missing data were generated. Of 1479 mother/child dyads, 21% of children had been fed foods/drinks with free sugars. There was a strong income gradient and a significant positive association with maternal SSB consumption. In the complete-case model, income Q1 and Q2 had PRs of 1.9 (1.2-3.1) and 1.8 (1.2-2.6) against Q4, respectively. The PR for mothers ingesting SSB everyday was 1.6 (1.2-2.3). The PR for children who had been breastfed to at least three months was 0.6 (0.5-0.8). Similar findings were observed in the MI model. Household income at birth and maternal behaviours were significant determinants of early feeding of foods/drinks with free sugars.

Short Operative Duration and Surgical Site Infection Risk in Hip and Knee Arthroplasty Procedures

PubMed Central

Dicks, Kristen V.; Baker, Arthur W.; Durkin, Michael J.; Anderson, Deverick J.; Moehring, Rebekah W.; Chen, Luke F.; Sexton, Daniel J.; Weber, David J.; Lewis, Sarah S.

2016-01-01

OBJECTIVE To determine the association (1) between shorter operative duration and surgical site infection (SSI) and (2) between surgeon median operative duration and SSI risk among first-time hip and knee arthroplasties. DESIGN Retrospective cohort study SETTING A total of 43 community hospitals located in the southeastern United States. PATIENTS Adults who developed SSIs according to National Healthcare Safety Network criteria within 365 days of first-time knee or hip arthroplasties performed between January 1, 2008 and December 31, 2012. METHODS Log-binomial regression models estimated the association (1) between operative duration and SSI outcome and (2) between surgeon median operative duration and SSI outcome. Hip and knee arthroplasties were evaluated in separate models. Each model was adjusted for American Society of Anesthesiology score and patient age. RESULTS A total of 25,531 hip arthroplasties and 42,187 knee arthroplasties were included in the study. The risk of SSI in knee arthroplasties with an operative duration shorter than the 25th percentile was 0.40 times the risk of SSI in knee arthroplasties with an operative duration between the 25th and 75th percentile (risk ratio [RR], 0.40; 95% confidence interval [CI], 0.38–0.56; P <.01). Short operative duration did not demonstrate significant association with SSI for hip arthroplasties (RR, 1.04; 95% CI, 0.79–1.37; P =.36). Knee arthroplasty surgeons with shorter median operative durations had a lower risk of SSI than surgeons with typical median operative durations (RR, 0.52; 95% CI, 0.43–0.64; P <.01). CONCLUSIONS Short operative durations were not associated with a higher SSI risk for knee or hip arthroplasty procedures in our analysis. PMID:26391277

Time series regression model for infectious disease and weather.

PubMed

Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

2015-10-01

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Zero adjusted models with applications to analysing helminths count data.

PubMed

Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

2014-11-27

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

Four Bootstrap Confidence Intervals for the Binomial-Error Model.

ERIC Educational Resources Information Center

Lin, Miao-Hsiang; Hsiung, Chao A.

1992-01-01

Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)

Phase transition and information cascade in a voting model

NASA Astrophysics Data System (ADS)

Hisakado, M.; Mori, S.

2010-08-01

In this paper, we introduce a voting model that is similar to a Keynesian beauty contest and analyse it from a mathematical point of view. There are two types of voters—copycat and independent—and two candidates. Our voting model is a binomial distribution (independent voters) doped in a beta binomial distribution (copycat voters). We find that the phase transition in this system is at the upper limit of t, where t is the time (or the number of the votes). Our model contains three phases. If copycats constitute a majority or even half of the total voters, the voting rate converges more slowly than it would in a binomial distribution. If independents constitute the majority of voters, the voting rate converges at the same rate as it would in a binomial distribution. We also study why it is difficult to estimate the conclusion of a Keynesian beauty contest when there is an information cascade.

Simulation of flight maneuver-load distributions by utilizing stationary, non-Gaussian random load histories

NASA Technical Reports Server (NTRS)

Leybold, H. A.

1971-01-01

Random numbers were generated with the aid of a digital computer and transformed such that the probability density function of a discrete random load history composed of these random numbers had one of the following non-Gaussian distributions: Poisson, binomial, log-normal, Weibull, and exponential. The resulting random load histories were analyzed to determine their peak statistics and were compared with cumulative peak maneuver-load distributions for fighter and transport aircraft in flight.

A comparison of different statistical methods analyzing hypoglycemia data using bootstrap simulations.

PubMed

Jiang, Honghua; Ni, Xiao; Huster, William; Heilmann, Cory

2015-01-01

Hypoglycemia has long been recognized as a major barrier to achieving normoglycemia with intensive diabetic therapies. It is a common safety concern for the diabetes patients. Therefore, it is important to apply appropriate statistical methods when analyzing hypoglycemia data. Here, we carried out bootstrap simulations to investigate the performance of the four commonly used statistical models (Poisson, negative binomial, analysis of covariance [ANCOVA], and rank ANCOVA) based on the data from a diabetes clinical trial. Zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model were also evaluated. Simulation results showed that Poisson model inflated type I error, while negative binomial model was overly conservative. However, after adjusting for dispersion, both Poisson and negative binomial models yielded slightly inflated type I errors, which were close to the nominal level and reasonable power. Reasonable control of type I error was associated with ANCOVA model. Rank ANCOVA model was associated with the greatest power and with reasonable control of type I error. Inflated type I error was observed with ZIP and ZINB models.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Making sense of the noise: The effect of hydrology on silver carp eDNA detection in the Chicago area waterway system.

PubMed

Song, Jeffery W; Small, Mitchell J; Casman, Elizabeth A

2017-12-15

Environmental DNA (eDNA) sampling is an emerging tool for monitoring the spread of aquatic invasive species. One confounding factor when interpreting eDNA sampling evidence is that eDNA can be present in the water in the absence of living target organisms, originating from excreta, dead tissue, boats, or sewage effluent, etc. In the Chicago Area Waterway System (CAWS), electric fish dispersal barriers were built to prevent non-native Asian carp species from invading Lake Michigan, and yet Asian carp eDNA has been detected above the barriers sporadically since 2009. In this paper the influence of stream flow characteristics in the CAWS on the probability of invasive Asian carp eDNA detection in the CAWS from 2009 to 2012 was examined. In the CAWS, the direction of stream flow is mostly away from Lake Michigan, though there are infrequent reversals in flow direction towards Lake Michigan during dry spells. We find that the flow reversal volume into the Lake has a statistically significant positive relationship with eDNA detection probability, while other covariates, like gage height, precipitation, season, water temperature, dissolved oxygen concentration, pH and chlorophyll concentration do not. This suggests that stream flow direction is highly influential on eDNA detection in the CAWS and should be considered when interpreting eDNA evidence. We also find that the beta-binomial regression model provides a stronger fit for eDNA detection probability compared to a binomial regression model. This paper provides a statistical modeling framework for interpreting eDNA sampling evidence and for evaluating covariates influencing eDNA detection. Copyright © 2017 Elsevier B.V. All rights reserved.

Quality of maternity care and its determinants along the continuum in Kenya: A structural equation modeling analysis

PubMed Central

Mendez, Bomar Rojas

2017-01-01

Background Improving access to delivery services does not guarantee access to quality obstetric care and better survival, and therefore, concerns for quality of maternal and newborn care in low- and middle-income countries have been raised. Our study explored characteristics associated with the quality of initial assessment, intrapartum, and immediate postpartum and newborn care, and further assessed the relationships along the continuum of care. Methods The 2010 Service Provision Assessment data of Kenya for 627 routine deliveries of women aged 15–49 were used. Quality of care measures were assessed using recently validated quality of care measures during initial assessment, intrapartum, and postpartum periods. Data were analyzed with negative binomial regression and structural equation modeling technique. Results The negative binomial regression results identified a number of determinants of quality, such as the level of health facilities, managing authority, presence of delivery fee, central electricity supply and clinical guideline for maternal and neonatal care. Our structural equation modeling (SEM) further demonstrated that facility characteristics were important determinants of quality for initial assessment and postpartum care, while characteristics at the provider level became more important in shaping the quality of intrapartum care. Furthermore we also noted that quality of initial assessment had a positive association with quality of intrapartum care (β = 0.71, p < 0.001), which in turn was positively associated with the quality of newborn and immediate postpartum care (β = 1.29, p = 0.004). Conclusions A continued focus on quality of care along the continuum of maternity care is important not only to mothers but also their newborns. Policymakers should therefore ensure that required resources, as well as adequate supervision and emphasis on the quality of obstetric care, are available. PMID:28520771

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

PubMed Central

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

Systems with Many Degrees of Freedom: from Mean - Theories of Non-Fermi Liquid Behavior in Impurity Models to Implied Binomial Trees for Modeling Financial Markets

NASA Astrophysics Data System (ADS)

Barle, Stanko

In this dissertation, two dynamical systems with many degrees of freedom are analyzed. One is the system of highly correlated electrons in the two-impurity Kondo problem. The other deals with building a realistic model of diffusion underlying financial markets. The simplest mean-field theory capable of mimicking the non-Fermi liquid behavior of the critical point in the two-impurity Kondo problem is presented. In this approach Landau's adiabaticity assumption--of a one-to-one correspondence between the low-energy excitations of the interacting and noninteracting systems--is violated through the presence of decoupled local degrees of freedom. These do not couple directly to external fields but appear indirectly in the physical properties leading, for example, to the log(T, omega) behavior of the staggered magnetic susceptibility. Also, as observed previously, the correlation function <{bf S}_1 cdot{bf S}_2> = -1/4 is a consequence of the equal weights of the singlet and triplet impurity configurations at the critical point. In the second problem, a numerical model is developed to describe the diffusion of prices in the market. Implied binomial (or multinomial) trees are constructed to enable practical pricing of derivative securities in consistency with the existing market. The method developed here is capable of accounting for both the strike price and term structure of the implied volatility. It includes the correct treatment of interest rate and dividends which proves robust even if these quantities are unusually large. The method is explained both as a set of individual innovations and, from a different prospective, as a consequence of a single plausible transformation from the tree of spot prices to the tree of futures prices.

Efficacy and cost-effectiveness of a physiotherapy program for chronic rotator cuff pathology: A protocol for a randomised, double-blind, placebo-controlled trial

PubMed Central

Bennell, Kim; Coburn, Sally; Wee, Elin; Green, Sally; Harris, Anthony; Forbes, Andrew; Buchbinder, Rachelle

2007-01-01

Background Chronic rotator cuff pathology (CRCP) is a common shoulder condition causing pain and disability. Physiotherapy is often the first line of management for CRCP yet there is little conclusive evidence to support or refute its effectiveness and no formal evaluation of its cost-effectiveness. Methods/Design This randomised, double-blind, placebo-controlled trial will involve 200 participants with CRCP recruited from medical practices, outpatient departments and the community via print and radio media. Participants will be randomly allocated to a physiotherapy or placebo group using concealed allocation stratified by treating physiotherapist. Both groups will receive 10 sessions of individual standardised treatment over 10 weeks from one of 10 project physiotherapists. For the following 12 weeks, the physiotherapy group will continue a home exercise program and the placebo group will receive no treatment. The physiotherapy program will comprise shoulder joint and spinal mobilisation, soft tissue massage, postural taping, and home exercises for scapular control, posture and rotator cuff strengthening. The placebo group will receive inactive ultrasound and gentle application of an inert gel over the shoulder region. Blinded assessment will be conducted at baseline and at 10 weeks and 22 weeks after randomisation. The primary outcome measures are self reported questionnaires including the shoulder pain and disability index (SPADI), average pain on an 11-point numeric rating scale and participant perceived global rating of change. Secondary measures include Medical Outcomes Study 36-item short form (SF-36), Assessment of Quality of Life index, numeric rating scales for shoulder pain and stiffness, participant perceived rating of change for pain, strength and stiffness, and manual muscle testing for shoulder strength using a handheld dynamometer. To evaluate cost-effectiveness, participants will record the use of all health-related treatments in a log-book returned to the assessor monthly. To test the effect of the intervention using an intention-to-treat analysis, linear regression modelling will be applied adjusting for baseline outcome values and other demographic characteristics. Participant measures of perceived change will be compared between groups by calculating the relative risks and their 95% confidence intervals at each time point using log binomial regression. Discussion Results from this trial will contribute to the evidence regarding the effectiveness of a physiotherapy program for the management of CRCP. Trial registration NIH Clinical Trials Registry # NCT00415441 PMID:17761004

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Estimating magnitude and frequency of peak discharges for rural, unregulated, streams in West Virginia

USGS Publications Warehouse

Wiley, J.B.; Atkins, John T.; Tasker, Gary D.

2000-01-01

Multiple and simple least-squares regression models for the log10-transformed 100-year discharge with independent variables describing the basin characteristics (log10-transformed and untransformed) for 267 streamflow-gaging stations were evaluated, and the regression residuals were plotted as areal distributions that defined three regions of the State, designated East, North, and South. Exploratory data analysis procedures identified 31 gaging stations at which discharges are different than would be expected for West Virginia. Regional equations for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year peak discharges were determined by generalized least-squares regression using data from 236 gaging stations. Log10-transformed drainage area was the most significant independent variable for all regions.Equations developed in this study are applicable only to rural, unregulated, streams within the boundaries of West Virginia. The accuracy of estimating equations is quantified by measuring the average prediction error (from 27.7 to 44.7 percent) and equivalent years of record (from 1.6 to 20.0 years).

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

PubMed

Janik, Leslie J; Forrester, Sean T; Soriano-Disla, José M; Kirby, Jason K; McLaughlin, Michael J; Reimann, Clemens

2015-02-01

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2)  = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2)  = 0.62-0.79), compared with those from PSLR-DRIFT (R(2)  = 0.61-0.72) and MLR (R(2)  = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration. © 2014 SETAC.

The association between major depression prevalence and sex becomes weaker with age.

PubMed

Patten, Scott B; Williams, Jeanne V A; Lavorato, Dina H; Wang, Jian Li; Bulloch, Andrew G M; Sajobi, Tolulope

2016-02-01

Women have a higher prevalence of major depressive episodes (MDE) than men, and the annual prevalence of MDE declines with age. Age by sex interactions may occur (a weakening of the sex effect with age), but are easily overlooked since individual studies lack statistical power to detect interactions. The objective of this study was to evaluate age by sex interactions in MDE prevalence. In Canada, a series of 10 national surveys conducted between 1996 and 2013 assessed MDE prevalence in respondents over the age of 14. Treating age as a continuous variable, binomial and linear regression was used to model age by sex interactions in each survey. To increase power, the survey-specific interaction coefficients were then pooled using meta-analytic methods. The estimated interaction terms were homogeneous. In the binomial regression model I (2) was 31.2 % and was not statistically significant (Q statistic = 13.1, df = 9, p = 0.159). The pooled estimate (-0.004) was significant (z = 3.13, p = 0.002), indicating that the effect of sex became weaker with increasing age. This resulted in near disappearance of the sex difference in the 75+ age group. This finding was also supported by an examination of age- and sex-specific estimates pooled across the surveys. The association of MDE prevalence with sex becomes weaker with age. The interaction may reflect biological effect modification. Investigators should test for, and consider inclusion of age by sex interactions in epidemiological analyses of MDE prevalence.

Association between month of birth and melanoma risk: fact or fiction?

PubMed

Fiessler, Cornelia; Pfahlberg, Annette B; Keller, Andrea K; Radespiel-Tröger, Martin; Uter, Wolfgang; Gefeller, Olaf

2017-04-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suggest that people born in spring carry a higher melanoma risk. Our study aimed at verifying whether such a seasonal pattern of melanoma risk actually exists. Data from the population-based Cancer Registry Bavaria (CRB) on the birth months of 28 374 incident melanoma cases between 2002 and 2012 were analysed and compared with data from the Bavarian State Office for Statistics and Data Processing on the birth month distribution in the Bavarian population. Crude and adjusted analyses using negative binomial regression models were performed in the total study group and supplemented by several subgroup analyses. In the crude analysis, the birth months March-May were over-represented among melanoma cases. Negative binomial regression models adjusted only for sex and birth year revealed a seasonal association between melanoma risk and birth month with 13-21% higher relative incidence rates for March, April and May compared with the reference December. However, after additionally adjusting for the birth month distribution of the Bavarian population, these risk estimates decreased markedly and no association with the birth month was observed any more. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR susceptibility during the first months of life. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City

PubMed Central

Furr-Holden, C. Debra M.; Milam, Adam J.; Nesoff, Elizabeth D.; Johnson, Renee M.; Fakunle, David O.; Jennings, Jacky M.; Thorpe, Roland J.

2016-01-01

Objective: This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Method: Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Results: Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Conclusions: Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores. PMID:26751351

On extinction time of a generalized endemic chain-binomial model.

PubMed

Aydogmus, Ozgur

2016-09-01

We considered a chain-binomial epidemic model not conferring immunity after infection. Mean field dynamics of the model has been analyzed and conditions for the existence of a stable endemic equilibrium are determined. The behavior of the chain-binomial process is probabilistically linked to the mean field equation. As a result of this link, we were able to show that the mean extinction time of the epidemic increases at least exponentially as the population size grows. We also present simulation results for the process to validate our analytical findings. Copyright © 2016 Elsevier Inc. All rights reserved.

QSAR models for predicting octanol/water and organic carbon/water partition coefficients of polychlorinated biphenyls.

PubMed

Yu, S; Gao, S; Gan, Y; Zhang, Y; Ruan, X; Wang, Y; Yang, L; Shi, J

2016-04-01

Quantitative structure-property relationship modelling can be a valuable alternative method to replace or reduce experimental testing. In particular, some endpoints such as octanol-water (KOW) and organic carbon-water (KOC) partition coefficients of polychlorinated biphenyls (PCBs) are easier to predict and various models have been already developed. In this paper, two different methods, which are multiple linear regression based on the descriptors generated using Dragon software and hologram quantitative structure-activity relationships, were employed to predict suspended particulate matter (SPM) derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of 209 PCBs. The predictive ability of the derived models was validated using a test set. The performances of all these models were compared with EPI Suite™ software. The results indicated that the proposed models were robust and satisfactory, and could provide feasible and promising tools for the rapid assessment of the SPM derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of PCBs.

Increased Prevalence of Chronic Lymphocytic Thyroiditis in Korean Patients with Papillary Thyroid Cancer

PubMed Central

Oh, Chang-Mo; Park, Sohee; Lee, Joo Young; Won, Young-Joo; Shin, Aesun; Kong, Hyun-Joo; Choi, Kui-Sun; Lee, You Jin; Chung, Ki- Wook; Jung, Kyu-Won

2014-01-01

Background In recent years, some reports have suggested that papillary thyroid cancers are more frequently associated with lymphocytic thyroiditis or Hashimoto's thyroiditis. This study investigated a potential increase in the prevalence of chronic lymphocytic thyroiditis among papillary thyroid cancer patients. Materials and Methods We used national epidemiological survey data on thyroid cancer patients diagnosed in 1999, 2005, and 2008. A retrospective medical record survey was conducted by representative sampling of a national cancer incidence database. The analysis included 5,378 papillary thyroid cancer patients aged 20–79 years. We calculated the age-standardized prevalence and age-adjusted prevalence ratios using a binomial regression model with a log link for the prevalence of chronic lymphocytic thyroiditis among papillary thyroid cancer patients by sex for each year. Results The prevalence of chronic lymphocytic thyroiditis among papillary thyroid cancer patients was 4.0% and 12.8% for men and women in 1999, 6.5% and 24.6% in 2005, and 10.7% and 27.6% in 2008, respectively. Between 1999 and 2008, the age-standardized prevalence of chronic lymphocytic thyroiditis increased 4.1-fold in male patients and 2.0-fold in female patients with papillary thyroid cancer. The prevalence of other thyroid diseases, however, did not increase in either gender. Conclusions Among Korean papillary thyroid cancer patients, the prevalence of chronic lymphocytic thyroiditis increased between 1999 and 2008, whereas the prevalence of other thyroid disorders did not change. PMID:24927027

Missed Work Due to Occupational Illness among Hispanic Horse Workers.

PubMed

Bush, Ashley M; Westneat, Susan; Browning, Steven R; Swanberg, Jennifer

2018-05-07

Occupational illnesses are inadequately reported for agriculture, an industry dominated by a vulnerable Hispanic population and high fatal and nonfatal injury rates. Work-related illnesses can contribute to missed work, caused by a combination of personal and work factors, with costs to the individual, employer, and society. To better understand agricultural occupational illnesses, 225 Hispanic horse workers were interviewed via community-based convenience sampling. Descriptive statistics, bivariate analyses, and log binomial regression modeling were used to: (1) describe the prevalence of missed work due to work-related illnesses among Hispanic horse workers, (2) examine work-related and personal factors associated with missed work, and (3) identify health symptoms and work-related characteristics potentially associated with missed work. Key findings reveal that having at least one child (PR = 1.71, 95% CI = 1.03, 2.84), having poor self-reported general health (PR = 0.72, 95% CI = 0.48, 1.08), experiencing stress during a typical workday (PR = 2.58, 95% CI = 1.25, 5.32), or spending less time with horses (PR = 1.87, 95% CI = 1.15, 3.05) are significant predictors of missing work. Interventions can be designed to identify workers most susceptible to missing work and provide resources to reduce absenteeism. Future research should examine work-related illness in agricultural horse production, including personal and work-related factors, in order to diminish occupational health disparities among these workers, who are more likely to be employed in hazardous agricultural work. Copyright© by the American Society of Agricultural Engineers.

[Associated factors to availability and use of electronic media in children from preschool to 4th grade].

PubMed

Camargo, Diana Marina; Orozco, Luis Carlos

2013-01-01

The increased availability of electronic media has changed the behavior in children and young people by encouraging sedentary lifestile, with health effects from a very young age. To characterize the availability and use of electronic media and its associated factors in children from preschool through 4 th grade. A cross-sectional study with cluster sampling was carried out. Parents filled out the demographic survey, the availability and use of electronic media at home and in the child´s room. Log-binomial regression models were applied to estimate prevalence ratios adjusted for the sampling. Seven hundred and ten parents answered. The average age of the children was 6.7 years and 49.7% were male. Factors such as the mother working out of the house and family income were positively associated with the availability of electronic media at home and in the child´s room. The availability of a TV, computer and console in the child´s room, contributes to longer use of these electronic media. Both, the male gender and age of the child, were positively associated with the availability and use of electronic media. This is the first study in Colombia that reports the availability and use of electronic media in children. It is clear that modern life encourages sedentary behavior from the earliest years of life, which has been associated with health problems from early childhood. Intervention studies are needed aimed at reducing these behaviors in our context.

Activity space-based measures of the food environment and their relationships to food purchasing behaviours for young urban adults in Canada.

PubMed

Widener, Michael J; Minaker, Leia M; Reid, Jessica L; Patterson, Zachary; Ahmadi, Tara Kamal; Hammond, David

2018-03-16

To examine the potential links between activity spaces, the food retail environment and food shopping behaviours for the population of young, urban adults. Participants took part in the Canada Food Study, which collected information on demographics, food behaviour, diet and health, as well as an additional smartphone study that included a seven-day period of logging GPS (global positioning system) location and food purchases. Using a time-weighted, continuous representation of participant activity spaces generated from GPS trajectory data, the locations of food purchases and a geocoded food retail data set, negative binomial regression models were used to explore what types of food retailers participants were exposed to and where food purchases were made. Toronto, Montreal, Vancouver, Edmonton and Halifax, Canada. Young adults aged 16-30 years (n 496). These participants were a subset of the larger Canada Food Study. Demographics, household food shopper status and city of residence were significantly associated with different levels of exposure to various types of food retailers. Food shopping behaviours were also statistically significantly associated with demographics, the activity space-based food environment, self-reported health and city of residence. The study confirms that food behaviours are related to activity space-based food environment measures, which provide a more comprehensive accounting of food retail exposure than home-based measures. In addition, exposure to food retail and food purchasing behaviours of an understudied population are described.

Drug use Discrimination Predicts Formation of High-Risk Social Networks: Examining Social Pathways of Discrimination.

PubMed

Crawford, Natalie D; Ford, Chandra; Rudolph, Abby; Kim, BoRin; Lewis, Crystal M

2017-09-01

Experiences of discrimination, or social marginalization and ostracism, may lead to the formation of social networks characterized by inequality. For example, those who experience discrimination may be more likely to develop drug use and sexual partnerships with others who are at increased risk for HIV compared to those without experiences of discrimination. This is critical as engaging in risk behaviors with others who are more likely to be HIV positive can increase one's risk of HIV. We used log-binomial regression models to examine the relationship between drug use, racial and incarceration discrimination with changes in the composition of one's risk network among 502 persons who use drugs. We examined both absolute and proportional changes with respect to sex partners, drug use partners, and injecting partners, after accounting for individual risk behaviors. At baseline, participants were predominately male (70%), black or Latino (91%), un-married (85%), and used crack (64%). Among those followed-up (67%), having experienced discrimination due to drug use was significantly related to increases in the absolute number of sex networks and drug networks over time. No types of discrimination were related to changes in the proportion of high-risk network members. Discrimination may increase one's risk of HIV acquisition by leading them to preferentially form risk relationships with higher-risk individuals, thereby perpetuating racial and ethnic inequities in HIV. Future social network studies and behavioral interventions should consider whether social discrimination plays a role in HIV transmission.

A kinetic energy model of two-vehicle crash injury severity.

PubMed

Sobhani, Amir; Young, William; Logan, David; Bahrololoom, Sareh

2011-05-01

An important part of any model of vehicle crashes is the development of a procedure to estimate crash injury severity. After reviewing existing models of crash severity, this paper outlines the development of a modelling approach aimed at measuring the injury severity of people in two-vehicle road crashes. This model can be incorporated into a discrete event traffic simulation model, using simulation model outputs as its input. The model can then serve as an integral part of a simulation model estimating the crash potential of components of the traffic system. The model is developed using Newtonian Mechanics and Generalised Linear Regression. The factors contributing to the speed change (ΔV(s)) of a subject vehicle are identified using the law of conservation of momentum. A Log-Gamma regression model is fitted to measure speed change (ΔV(s)) of the subject vehicle based on the identified crash characteristics. The kinetic energy applied to the subject vehicle is calculated by the model, which in turn uses a Log-Gamma Regression Model to estimate the Injury Severity Score of the crash from the calculated kinetic energy, crash impact type, presence of airbag and/or seat belt and occupant age. Copyright © 2010 Elsevier Ltd. All rights reserved.

Developing a dengue forecast model using machine learning: A case study in China.

PubMed

Guo, Pi; Liu, Tao; Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-10-01

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

Investigation of shipping accident injury severity and mortality.

PubMed

Weng, Jinxian; Yang, Dong

2015-03-01

Shipping movements are operated in a complex and high-risk environment. Fatal shipping accidents are the nightmares of seafarers. With ten years' worldwide ship accident data, this study develops a binary logistic regression model and a zero-truncated binomial regression model to predict the probability of fatal shipping accidents and corresponding mortalities. The model results show that both the probability of fatal accidents and mortalities are greater for collision, fire/explosion, contact, grounding, sinking accidents occurred in adverse weather conditions and darkness conditions. Sinking has the largest effects on the increment of fatal accident probability and mortalities. The results also show that the bigger number of mortalities is associated with shipping accidents occurred far away from the coastal area/harbor/port. In addition, cruise ships are found to have more mortalities than non-cruise ships. The results of this study are beneficial for policy-makers in proposing efficient strategies to prevent fatal shipping accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Determinants of The Grade A Embryos in Infertile Women; Zero-Inflated Regression Model.

PubMed

Almasi-Hashiani, Amir; Ghaheri, Azadeh; Omani Samani, Reza

2017-10-01

In assisted reproductive technology, it is important to choose high quality embryos for embryo transfer. The aim of the present study was to determine the grade A embryo count and factors related to it in infertile women. This historical cohort study included 996 infertile women. The main outcome was the number of grade A embryos. Zero-Inflated Poisson (ZIP) regression and Zero-Inflated Negative Binomial (ZINB) regression were used to model the count data as it contained excessive zeros. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. After adjusting for potential confounders, results from the ZINB model show that for each unit increase in the number 2 pronuclear (2PN) zygotes, we get an increase of 1.45 times as incidence rate ratio (95% confidence interval (CI): 1.23-1.69, P=0.001) in the expected grade A embryo count number, and for each increase in the cleavage day we get a decrease 0.35 times (95% CI: 0.20-0.61, P=0.001) in expected grade A embryo count. There is a significant association between both the number of 2PN zygotes and cleavage day with the number of grade A embryos in both ZINB and ZIP regression models. The estimated coefficients are more plausible than values found in earlier studies using less relevant models. Copyright© by Royan Institute. All rights reserved.

ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM.

PubMed

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems.

Magnitude of virologic blips is associated with a higher risk for virologic rebound in HIV-infected individuals: a recurrent events analysis.

PubMed

Grennan, J Troy; Loutfy, Mona R; Su, DeSheng; Harrigan, P Richard; Cooper, Curtis; Klein, Marina; Machouf, Nima; Montaner, Julio S G; Rourke, Sean; Tsoukas, Christos; Hogg, Bob; Raboud, Janet

2012-04-15

The importance of human immunodeficiency virus (HIV) blip magnitude on virologic rebound has been raised in clinical guidelines relating to viral load assays. Antiretroviral-naive individuals initiating combination antiretroviral therapy (cART) after 1 January 2000 and achieving virologic suppression were studied. Negative binomial models were used to identify blip correlates. Recurrent event models were used to determine the association between blips and rebound by incorporating multiple periods of virologic suppression per individual. 3550 participants (82% male; median age, 40 years) were included. In a multivariable negative binomial regression model, the Amplicor assay was associated with a lower blip rate than branched DNA (rate ratio, 0.69; P < .01), controlling for age, sex, region, baseline HIV-1 RNA and CD4 count, AIDS-defining illnesses, year of cART initiation, cART type, and HIV-1 RNA testing frequency. In a multivariable recurrent event model controlling for age, sex, intravenous drug use, cART start year, cART type, assay type, and HIV-1 RNA testing frequency, blips of 500-999 copies/mL were associated with virologic rebound (hazard ratio, 2.70; P = .002), whereas blips of 50-499 were not. HIV-1 RNA assay was an important determinant of blip rates and should be considered in clinical guidelines. Blips ≥500 copies/mL were associated with increased rebound risk.

Discrimination of numerical proportions: A comparison of binomial and Gaussian models.

PubMed

Raidvee, Aire; Lember, Jüri; Allik, Jüri

2017-01-01

Observers discriminated the numerical proportion of two sets of elements (N = 9, 13, 33, and 65) that differed either by color or orientation. According to the standard Thurstonian approach, the accuracy of proportion discrimination is determined by irreducible noise in the nervous system that stochastically transforms the number of presented visual elements onto a continuum of psychological states representing numerosity. As an alternative to this customary approach, we propose a Thurstonian-binomial model, which assumes discrete perceptual states, each of which is associated with a certain visual element. It is shown that the probability β with which each visual element can be noticed and registered by the perceptual system can explain data of numerical proportion discrimination at least as well as the continuous Thurstonian-Gaussian model, and better, if the greater parsimony of the Thurstonian-binomial model is taken into account using AIC model selection. We conclude that Gaussian and binomial models represent two different fundamental principles-internal noise vs. using only a fraction of available information-which are both plausible descriptions of visual perception.

Random parameter models of interstate crash frequencies by severity, number of vehicles involved, collision and location type.

PubMed

Venkataraman, Narayan; Ulfarsson, Gudmundur F; Shankar, Venky N

2013-10-01

A nine-year (1999-2007) continuous panel of crash histories on interstates in Washington State, USA, was used to estimate random parameter negative binomial (RPNB) models for various aggregations of crashes. A total of 21 different models were assessed in terms of four ways to aggregate crashes, by: (a) severity, (b) number of vehicles involved, (c) crash type, and by (d) location characteristics. The models within these aggregations include specifications for all severities (property damage only, possible injury, evident injury, disabling injury, and fatality), number of vehicles involved (one-vehicle to five-or-more-vehicle), crash type (sideswipe, same direction, overturn, head-on, fixed object, rear-end, and other), and location types (urban interchange, rural interchange, urban non-interchange, rural non-interchange). A total of 1153 directional road segments comprising of the seven Washington State interstates were analyzed, yielding statistical models of crash frequency based on 10,377 observations. These results suggest that in general there was a significant improvement in log-likelihood when using RPNB compared to a fixed parameter negative binomial baseline model. Heterogeneity effects are most noticeable for lighting type, road curvature, and traffic volume (ADT). Median lighting or right-side lighting are linked to increased crash frequencies in many models for more than half of the road segments compared to both-sides lighting. Both-sides lighting thereby appears to generally lead to a safety improvement. Traffic volume has a random parameter but the effect is always toward increasing crash frequencies as expected. However that the effect is random shows that the effect of traffic volume on crash frequency is complex and varies by road segment. The number of lanes has a random parameter effect only in the interchange type models. The results show that road segment-specific insights into crash frequency occurrence can lead to improved design policy and project prioritization. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models

PubMed Central

Mahara, Gehendra; Wang, Chao; Yang, Kun; Chen, Sipeng; Guo, Jin; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-01

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran’s I statistic and Anselin’s local Moran’s I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R2 = 0.0741, log likelihood = −1819.69, AIC = 3665.38), SLM (R2 = 0.0786, log likelihood = −1819.04, AIC = 3665.08) and SEM (R2 = 0.0743, log likelihood = −1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide (p = 0.027), rainfall (p = 0.036) and sunshine hour (p = 0.048), while the relative humidity (p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention. PMID:27827946

The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models.

PubMed

Mahara, Gehendra; Wang, Chao; Yang, Kun; Chen, Sipeng; Guo, Jin; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-11-04

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran's I statistic and Anselin's local Moran's I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R² = 0.0741, log likelihood = -1819.69, AIC = 3665.38), SLM (R² = 0.0786, log likelihood = -1819.04, AIC = 3665.08) and SEM (R² = 0.0743, log likelihood = -1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide ( p = 0.027), rainfall ( p = 0.036) and sunshine hour ( p = 0.048), while the relative humidity ( p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention.

Understanding logistic regression analysis.

PubMed

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

LogCauchy, log-sech and lognormal distributions of species abundances in forest communities

USGS Publications Warehouse

Yin, Z.-Y.; Peng, S.-L.; Ren, H.; Guo, Q.; Chen, Z.-H.

2005-01-01

Species-abundance (SA) pattern is one of the most fundamental aspects of biological community structure, providing important information regarding species richness, species-area relation and succession. To better describe the SA distribution (SAD) in a community, based on the widely used lognormal (LN) distribution model with exp(-x2) roll-off on Preston's octave scale, this study proposed two additional models, logCauchy (LC) and log-sech (LS), respectively with roll-offs of simple x-2 and e-x. The estimation of the theoretical total number of species in the whole community, S*, including very rare species not yet collected in sample, was derived from the left-truncation of each distribution. We fitted these three models by Levenberg-Marquardt nonlinear regression and measured the model fit to the data using coefficient of determination of regression, parameters' t-test and distribution's Kolmogorov-Smirnov (KS) test. Examining the SA data from six forest communities (five in lower subtropics and one in tropics), we found that: (1) on a log scale, all three models that are bell-shaped and left-truncated statistically adequately fitted the observed SADs, and the LC and LS did better than the LN; (2) from each model and for each community the S* values estimated by the integral and summation methods were almost equal, allowing us to estimate S* using a simple integral formula and to estimate its asymptotic confidence internals by regression of a transformed model containing it; (3) following the order of LC, LS, and LN, the fitted distributions became lower in the peak, less concave in the side, and shorter in the tail, and overall the LC tended to overestimate, the LN tended to underestimate, while the LS was intermediate but slightly tended to underestimate, the observed SADs (particularly the number of common species in the right tail); (4) the six communities had some similar structural properties such as following similar distribution models, having a common modal octave and a similar proportion of common species. We suggested that what follows the LN distribution should follow (or better follow) the LC and LS, and that the LC, LS and LN distributions represent a "sequential distribution set" in which one can find a best fit to the observed SAD. ?? 2004 Elsevier B.V. All rights reserved.

Demonstration of the Web-based Interspecies Correlation Estimation (Web-ICE) modeling application

EPA Science Inventory

The Web-based Interspecies Correlation Estimation (Web-ICE) modeling application is available to the risk assessment community through a user-friendly internet platform (http://epa.gov/ceampubl/fchain/webice/). ICE models are log-linear least square regressions that predict acute...

Selecting Tools to Model Integer and Binomial Multiplication

ERIC Educational Resources Information Center

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia

PubMed Central

Singh, Minerva; Evans, Damian; Coomes, David A.; Friess, Daniel A.; Suy Tan, Boun; Samean Nin, Chan

2016-01-01

This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests. PMID:27176218

Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia.

PubMed

Singh, Minerva; Evans, Damian; Coomes, David A; Friess, Daniel A; Suy Tan, Boun; Samean Nin, Chan

2016-01-01

This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests.

Work and family stress is associated with menstrual disorders but not with fibrocystic changes: cross-sectional findings in Chinese working women.

PubMed

Zhou, Mei; Wege, Natalia; Gu, Huakang; Shang, Li; Li, Jian; Siegrist, Johannes

2010-01-01

To explore the separate and combined effects of work and family stress on menstrual disorders and fibrocystic changes in Chinese working women. Data were obtained from a cross-sectional study of 1,642 female railway workers. The Effort-Reward Imbalance Questionnaire and Family Stress Scale were used to measure work stress and family stress, respectively; the menstrual and breast conditions were evaluated by gynecologic interview and a medical examination. Multivariate log-binomial regression was performed to analyze the associations. Menstrual disorders were found in 59.3% of female workers, and 54.8% had fibrocystic changes. The risk of menstrual disorders was significantly elevated with respect to work and family stress. The highest risk was found in the group with combined exposure to both work and family stress (RR with 95% CI 1.33 (1.18-1.49)). No significant association between stress and fibrocystic changes was observed. Menstrual disorders were associated with stress from work and family life, but not fibrocystic changes, in working women. Tailored intervention measures reducing the burden of stressful psychosocial work and family environment are needed to improve women's reproductive well-being.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

NASA Technical Reports Server (NTRS)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

The Effect of Cotrimoxazole Prophylactic Treatment on Malaria, Birth Outcomes, and Postpartum CD4 Count in HIV-Infected Women

PubMed Central

Dow, Anna; Hudgens, Michael G.; Van Rie, Annelies; King, Caroline C.; Ellington, Sascha; Chome, Nelecy; Turner, Abigail Norris; Kacheche, Zebrone; Jamieson, Denise J.; Chasela, Charles; van der Horst, Charles

2013-01-01

Background. Limited data exist on cotrimoxazole prophylactic treatment (CPT) in pregnant women, including protection against malaria versus standard intermittent preventive therapy with sulfadoxine-pyrimethamine (IPTp). Methods. Using observational data we examined the effect of CPT in HIV-infected pregnant women on malaria during pregnancy, low birth weight and preterm birth using proportional hazards, logistic, and log binomial regression, respectively. We used linear regression to assess effect of CPT on CD4 count. Results. Data from 468 CPT-exposed and 768 CPT-unexposed women were analyzed. CPT was associated with protection against malaria versus IPTp (hazard ratio: 0.35, 95% Confidence Interval (CI): 0.20, 0.60). After adjustment for time period this effect was not statistically significant (adjusted hazard ratio: 0.66, 95% CI: 0.28, 1.52). Among women receiving and not receiving CPT, rates of low birth weight (7.1% versus 7.6%) and preterm birth (23.5% versus 23.6%) were similar. CPT was associated with lower CD4 counts 24 weeks postpartum in women receiving (−77.6 cells/μL, 95% CI: −125.2, −30.1) and not receiving antiretrovirals (−33.7 cells/μL, 95% CI: −58.6, −8.8). Conclusions. Compared to IPTp, CPT provided comparable protection against malaria in HIV-infected pregnant women and against preterm birth or low birth weight. Possible implications of CPT-associated lower CD4 postpartum warrant further examination. PMID:24363547

Seroprevalence of Helicobacter pylori in Hispanics living in Puerto Rico: A population-based study.

PubMed

González-Pons, María; Soto-Salgado, Marievelisse; Sevilla, Javier; Márquez-Lespier, Juan M; Morgan, Douglas; Pérez, Cynthia M; Cruz-Correa, Marcia

2018-02-01

Helicobacter pylori is an important etiologic factor for peptic ulcers and gastric cancer, one of the top ten leading causes of cancer death in Puerto Rico. However, the prevalence of H. pylori infections in this population was previously unknown. The aim of this study was to examine the seroprevalence of H. pylori and its associated risk factors in Puerto Rico. A cross-sectional study was designed using an existing population-based biorepository. Seropositivity was determined using the Premier ™ H. pylori immunoassay. Helicobacter pylori seroprevalence was estimated with 95% confidence using marginal standardization following logistic regression. To assess the risk factors associated with H. pylori seropositivity, a multivariable log-binomial model was fitted to estimate the prevalence ratio (PR) and its 95% confidence interval (95% CI). A total of 528 population-based serum samples were analyzed. The mean age of the study population was 41 ± 12 years, of whom 55.3% were females. The overall seroprevalence of H. pylori was 33.0% (95% CI = 28.3%-38.1%). Increasing age and having <12 years of education were significantly (P < .05) associated with H. pylori seropositivity in the multivariable model; however, residing in counties with low population density reached marginal significance (P = .085). We report that H. pylori infection is common among Hispanics living in Puerto Rico. The H. pylori seroprevalence observed in Puerto Rico is similar to the seroprevalence reported in the overall population of the United States. The association between H. pylori seroprevalence and the risk factors analyzed offers insight into the epidemiology of gastric cancer in Puerto Rico and warrants further investigation. © 2017 The Authors. Helicobacter Published by John Wiley & Sons Ltd.

Prevalence and sociodemographic characteristics of women with induced abortion in a population sample of São Paulo, Brazil.

PubMed

Souza, Milena Goulart; Fusco, Carmen L B; Andreoni, Solange A; de Souza e Silva, Rebeca

2014-01-01

This study aims at estimating the prevalence of women with induced abortion among women of childbearing age (15-49 years) who had any previous pregnancy, in the city of Sao Paulo, Brazil, in the last quarter of 2008, and identifying the Sociodemographic Characteristics (SC) associated with it. A cross-sectional survey was carried out. The dependent variable was dichotomized as: no abortion and induced abortion. The independent variables were: age, paid work/activity, familial monthly income, schooling, marital status, contraceptive use and number of live births. Statistical analysis was performed using log-binomial regression models with approximation of Poisson to estimate the Prevalance Ratios (PR). Of all women with any previous pregnancy (n = 683), 4.5% (n = 31) reported induced abortion. The final multivariate model showed that having now between 40 and 44 years (PR = 2.76, p = 0.0043), being single (PR = 2.79, p = 0.0159), having 5 or more live births (PR = 3.97, p = 0.0013), current oral contraception or IUD use (PR = 2.70, p = 0.454) and using a "non effective" (or of low efficacy) contraceptive method (PR = 4.18, p = 0.0009) were sociodemographic characteristics associated with induced abortion in this population. Induced abortion seems to be used to limit fertility, more precisely after having reached the desired number of children. The inadequate use or non-use of effective contraceptive methods, and / or the use of contraceptives " non effective", exposed also the women to the risk of unintended pregnancies and, therefore, induced abortions. In addition, when faced with a pregnancy, single women were more likely to have an abortion than married women.

Eggs in Early Complementary Feeding and Child Growth: A Randomized Controlled Trial.

PubMed

Iannotti, Lora L; Lutter, Chessa K; Stewart, Christine P; Gallegos Riofrío, Carlos Andres; Malo, Carla; Reinhart, Gregory; Palacios, Ana; Karp, Celia; Chapnick, Melissa; Cox, Katherine; Waters, William F

2017-07-01

Eggs are a good source of nutrients for growth and development. We hypothesized that introducing eggs early during complementary feeding would improve child nutrition. A randomized controlled trial was conducted in Cotopaxi Province, Ecuador, from March to December 2015. Children ages 6 to 9 months were randomly assigned to treatment (1 egg per day for 6 months [ n = 83]) and control (no intervention [ n = 80]) groups. Both arms received social marketing messages to encourage participation in the Lulun Project ( lulun meaning "egg" in Kichwa). All households were visited once per week to monitor morbidity symptoms, distribute eggs, and monitor egg intakes (for egg group only). Baseline and end point outcome measures included anthropometry, dietary intake frequencies, and morbidity symptoms. Mothers or other caregivers reported no allergic reactions to the eggs. Generalized linear regression modeling showed the egg intervention increased length-for-age z score by 0.63 (95% confidence interval [CI], 0.38-0.88) and weight-for-age z score by 0.61 (95% CI, 0.45-0.77). Log-binomial models with robust Poisson indicated a reduced prevalence of stunting by 47% (prevalence ratio [PR], 0.53; 95% CI, 0.37-0.77) and underweight by 74% (PR, 0.26; 95% CI, 0.10-0.70). Children in the treatment group had higher dietary intakes of eggs (PR, 1.57; 95% CI, 1.28-1.92) and reduced intake of sugar-sweetened foods (PR, 0.71; 95% CI, 0.51-0.97) compared with control. The findings supported our hypothesis that early introduction of eggs significantly improved growth in young children. Generally accessible to vulnerable groups, eggs have the potential to contribute to global targets to reduce stunting. Copyright © 2017 by the American Academy of Pediatrics.

Heavy metal and trace element concentrations in blood and follicular fluid affect ART outcome.

PubMed

Tolunay, Harun Egemen; Şükür, Yavuz Emre; Ozkavukcu, Sinan; Seval, Mehmet Murat; Ateş, Can; Türksoy, Vugar Ali; Ecemiş, Tolga; Atabekoğlu, Cem Somer; Özmen, Batuhan; Berker, Bülent; Sönmezer, Murat

2016-03-01

To assess the effects of heavy metal and trace element concentrations in blood and follicular fluid on assisted reproductive technology cycle outcome. A prospective study was conducted between January 2012 and July 2012 in a university hospital infertility clinic. One hundred and one patients with unexplained infertility who underwent intracytoplasmic sperm injection using GnRH-antagonist protocol were recruited. Concentrations of four toxic metals (Cd, Pb, Hg, As) and three trace elements (Cu, Zn, Fe) were measured both in blood and follicular fluid specimens. Patients were evaluated in two groups; the study group consisted of patients with ongoing pregnancy (n=20) and the reference group consisted of patients experienced assisted reproductive technology failure, miscarriage or biochemical pregnancy (n=81). Demographics and cycle parameters were comparable between the groups except for median number of day 3 Grade A embryos. Statistically significant negative correlations were found between blood Pb levels and number of MII oocytes, implantation, clinical pregnancy and ongoing pregnancy rates. Results of the log binomial regression revealed 2.2% lower risk for ongoing pregnancy for each 1μg/dL higher blood Pb concentration while holding the other variables in the model constant (RR 0.978; 95% CI 0.956-0.998; P=.041). Also, the results revealed 71.9% lower risk for ongoing pregnancy for each 1μg/dL higher follicular fluid Cu concentration while holding the other variables in the model constant (RR 0.288; 95% CI 0.085-0.92; P=.039). Blood concentrations of Pb and follicular fluid concentrations of Cu seem to have significant impacts on assisted reproductive technology cycle outcome. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Intracerebral hemorrhage and sleep-disordered breathing.

PubMed

Lisabeth, Lynda D; Scheer, Richard V; Li, Chengwei; Case, Erin; Chervin, Ronald D; Zahuranec, Darin B; Morgenstern, Lewis B; Garcia, Nelda M; Tower, Susan; Brown, Devin L

2018-06-01

Limited data are available on sleep-disordered breathing (SDB) following intracerebral hemorrhage (ICH). Our aim was to characterize the objective measures of post-ICH SDB and questionnaire-reported pre-ICH sleep characteristics, overall and by ethnicity. Participants with ICH who were enrolled in the population-based Brain Attack Surveillance in Corpus Christi project (2010-2016) reported their pre-ICH sleep duration and completed the Berlin Questionnaire to characterize pre-ICH risk of SDB. A subsample was screened for SDB (respiratory event index ≥10) using ApneaLink Plus portable monitoring. Ethnic differences in post-ICH SDB or questionnaire-reported pre-ICH sleep characteristics were assessed using a log binomial model or a linear regression model or a Fisher's exact test. ICH cases (n = 298) were enrolled (median age = 68 years, 67% Mexican American). Among 62 cases with complete ApneaLink data, median time to post-ICH SDB screening was 11 days (IQR: 6, 19). Post-ICH SDB prevalence was 46.8% (95% CI: 34.4-59.2), and this rate did not differ by ethnicity (p = 1.0). Berlin Questionnaires for 109 of the 298 ICH cases (36.6% (95% CI: 31.1-42.0)) suggested a high risk for pre-ICH SDB, and the median pre-ICH sleep duration was eight hours (IQR: 6, 8). After adjusting for confounders, there was no difference in ethnicity in high risk for pre-ICH SDB or pre-ICH sleep duration. Nearly half of the patients had objective confirmation of SDB after ICH, and more than one-third had questionnaire evidence of high risk for pre-ICH SDB. Opportunities to address SDB may be common both before and after ICH. Copyright © 2018 Elsevier B.V. All rights reserved.

Association of filaggrin variants with asthma and rhinitis: is eczema or allergic sensitization status an effect modifier?

PubMed Central

Ziyab, Ali H.; Karmaus, Wilfried; Zhang, Hongmei; Holloway, John W.; Steck, Susan E.; Ewart, Susan; Arshad, Syed Hasan

2014-01-01

Background Associations of filaggrin (FLG) variants with asthma and rhinitis have been shown to be modulated by eczema status. However, it is unknown whether allergic sensitization status modifies this association. The aim of this study was to determine whether FLG variants need eczema and/or allergic sensitization as a necessary component to execute its adverse effect on coexisting and subsequent asthma and rhinitis. Methods Repeated measurements of asthma, rhinitis, eczema, and allergic sensitization (documented by skin prick tests) at ages 1, 2, 4, 10, and 18 years were ascertained in the Isle of Wight birth cohort (n = 1,456). FLG haploinsufficiency was defined as having at least the minor allele of R501X, 2282del4, or S3247X variants. Log binomial regression models were used to test associations and statistical interactions. Results FLG variants increased the risk of asthma (RR = 1.39, 95% CI: 1.06 – 1.80) and rhinitis (RR = 1.37, 95% CI: 1.16 – 1.63). In delayed effect models, ‘FLG variants plus allergic sensitization’ and ‘FLG variants plus eczema’ increased the risk of subsequent asthma by 4.93-fold (95% CI: 3.61 – 6.71) and 3.33-fold (95% CI: 2.45 – 4.51), respectively, during the first 18 years of life. In contrast, neither eczema nor allergic sensitization in combination with FLG variants increased the risk of later rhinitis. Conclusions Allergic sensitization and eczema modulated the association between FLG variants and asthma, but not rhinitis. Results of our study imply that the mechanisms and pathways through which FLG variants predispose to increased risk of asthma and rhinitis may be different. PMID:25277085

The role of maternal education in the 15-year trajectory of malnutrition in children under 5 years of age in Bangladesh.

PubMed

Hasan, Md Tanvir; Soares Magalhaes, Ricardo J; Williams, Gail M; Mamun, Abdullah A

2016-10-01

Malnutrition in children under 5 years of age (U5s) is a serious public health problem in low- and middle-income countries including Bangladesh. Improved maternal education can contribute effectively to reduce child malnutrition. We examined the long-term impact of maternal education on the risk of malnutrition in U5s and quantified the level of education required for the mothers to reduce the risk. We used pooled data from five nationwide demographic and health surveys conducted in 1996-1997, 1999-2000, 2004, 2007 and 2011 in Bangladesh involving 28 941 U5s. A log-binomial regression model was used to examine the association between maternal education (no education, primary, secondary or more) and malnutrition in children, measured by stunting, underweight and wasting controlling for survey time, maternal age, maternal body mass index, maternal working status, parity, paternal education and wealth quintile. An overall improvement in maternal educational attainment was observed between 1996 and 2011. The prevalence of malnutrition although decreasing was consistently high among children of mothers with lower education compared with those of mothers with higher education. In adjusted models incorporating time effects, children of mothers with secondary or higher education were at lower risk of childhood stunting [risk ratio (RR): 0.86, 95% confidence interval (CI): 0.81, 0.89], underweight (RR: 0.83, 95% CI: 0.78, 0.88) and wasting (RR: 0.82, 95% CI: 0.74, 0.91) compared with children of mothers with no education. We demonstrated the importance of promoting women's education at least up to the secondary level as a means to tackle malnutrition in Bangladesh. © 2015 John Wiley & Sons Ltd.

Mediterranean diet adherence during pregnancy and fetal growth: INMA (Spain) and RHEA (Greece) mother-child cohort studies.

PubMed

Chatzi, Leda; Mendez, Michelle; Garcia, Raquel; Roumeliotaki, Theano; Ibarluzea, Jesús; Tardón, Adonina; Amiano, Pilar; Lertxundi, Aitana; Iñiguez, Carmen; Vioque, Jesus; Kogevinas, Manolis; Sunyer, Jordi

2012-01-01

Dietary intake of specific nutrients or food groups during pregnancy could influence fetal growth, but scant evidence is available on effects of dietary patterns. The aim of this study was to evaluate the impact of Mediterranean diet (MD) adherence during pregnancy on fetal growth in two population-based mother-child cohorts in Spain and Greece. We studied 2461 mother-newborn pairs from the Spanish multi-centre 'INMA' study (Atlantic area: INMA-Atlantic; Mediterranean area: INMA-Mediterranean), and 889 pairs from the 'RHEA' study in Crete, Greece. Maternal diet during pregnancy was assessed by FFQ and MD adherence was evaluated through an a priori score. Fetal growth restriction was based on a customised model, and multivariate log-binomial and linear regression models were used to adjust for several confounders. MD scores differ significantly between the cohorts with women in INMA-Atlantic reporting higher intakes of fish and dairy products, while women in the Mediterranean area reported higher intakes of cereals, vegetables and fruits. Women with high MD adherence had a significantly lower risk of delivering a fetal growth-restricted infant for weight (risk ratios: 0·5; 95 % CI 0·3, 0·9) in the INMA-Mediterranean cohort. Stratified analysis by smoking revealed that higher MD adherence increased birth weight and birth length in smoking mothers, whereas this effect was not apparent in non-smoking mothers. The results of the present study show that several types of MD exist across European Mediterranean regions. High MD adherence may modify the detrimental effect of smoking on birth size, but overall effects of diet were not universal for the studies in this analysis.

Relationships between training load, injury, and fitness in sub-elite collision sport athletes.

PubMed

Gabbett, Tim J; Domrow, Nathan

2007-11-01

The purpose of this study was to develop statistical models that estimate the influence of training load on training injury and physical fitness in collision sport athletes. The incidence of training injuries was studied in 183 rugby league players over two competitive seasons. Participants were assessed for height, body mass, skinfold thickness, vertical jump, 10-m, 20-m and 40-m sprint time, agility, and estimated maximal aerobic power in the off-season, pre-season, mid-season, and end-season. Training load and injury data were summarised into pre-season, early-competition, and late-competition training phases. Individual training load, fitness, and injury data were modelled using a logistic regression model with a binomial distribution and logit link function, while team training load and injury data were modelled using a linear regression model. While physical fitness improved with training, there was no association (P=0.16-0.99) between training load and changes in physical fitness during any of the training phases. However, increases in training load during the early-competition training phase decreased (P= 0.04) agility performance. A relationship (P= 0.01-0.04) was observed between the log of training load and odds of injury during each training phase, resulting in a 1.50 - 2.85 increase in the odds of injury for each arbitrary unit increase in training load. Furthermore, during the pre-season training phase there was a relationship (P= 0.01) between training load and injury incidence within the training load range of 155 and 590 arbitrary units. During the early and late-competition training phases, increases in training load of 175-620 arbitrary units and 145-410 arbitrary units, respectively, resulted in no further increase in injury incidence. These findings demonstrate that increases in training load, particularly during the pre-season training phase, increase the odds of injury in collision sport athletes. However, while increases in training load from 175 to 620 arbitrary units during the early-competition training phase result in no further increase in injury incidence, marked reductions in agility performances can occur. These findings suggest that reductions in training load during the early-competition training phase can reduce the odds of injury without compromising agility performances in collision sport athletes.

Topics in Bayesian Hierarchical Modeling and its Monte Carlo Computations

NASA Astrophysics Data System (ADS)

Tak, Hyung Suk

The first chapter addresses a Beta-Binomial-Logit model that is a Beta-Binomial conjugate hierarchical model with covariate information incorporated via a logistic regression. Various researchers in the literature have unknowingly used improper posterior distributions or have given incorrect statements about posterior propriety because checking posterior propriety can be challenging due to the complicated functional form of a Beta-Binomial-Logit model. We derive data-dependent necessary and sufficient conditions for posterior propriety within a class of hyper-prior distributions that encompass those used in previous studies. Frequency coverage properties of several hyper-prior distributions are also investigated to see when and whether Bayesian interval estimates of random effects meet their nominal confidence levels. The second chapter deals with a time delay estimation problem in astrophysics. When the gravitational field of an intervening galaxy between a quasar and the Earth is strong enough to split light into two or more images, the time delay is defined as the difference between their travel times. The time delay can be used to constrain cosmological parameters and can be inferred from the time series of brightness data of each image. To estimate the time delay, we construct a Gaussian hierarchical model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian approach jointly infers model parameters via a Gibbs sampler. We also introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The last chapter specifies a repelling-attracting Metropolis algorithm, a new Markov chain Monte Carlo method to explore multi-modal distributions in a simple and fast manner. This algorithm is essentially a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so that the algorithm prefers downward movement. The uphill move does the opposite using the standard Metropolis ratio which prefers upward movement. This down-up movement in density increases the probability of a proposed move to a different mode.

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

PubMed

Rocheleau, J P; Michel, P; Lindsay, L R; Drebot, M; Dibernardo, A; Ogden, N H; Fortin, A; Arsenault, J

2017-10-01

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Estimating the magnitude of annual peak discharges with recurrence intervals between 1.1 and 3.0 years for rural, unregulated streams in West Virginia

USGS Publications Warehouse

Wiley, Jeffrey B.; Atkins, John T.; Newell, Dawn A.

2002-01-01

Multiple and simple least-squares regression models for the log10-transformed 1.5- and 2-year recurrence intervals of peak discharges with independent variables describing the basin characteristics (log10-transformed and untransformed) for 236 streamflow-gaging stations were evaluated, and the regression residuals were plotted as areal distributions that defined three regions in West Virginia designated as East, North, and South. Regional equations for the 1.1-, 1.2-, 1.3-, 1.4-, 1.5-, 1.6-, 1.7-, 1.8-, 1.9-, 2.0-, 2.5-, and 3-year recurrence intervals of peak discharges were determined by generalized least-squares regression. Log10-transformed drainage area was the most significant independent variable for all regions. Equations developed in this study are applicable only to rural, unregulated streams within the boundaries of West Virginia. The accuracies of estimating equations are quantified by measuring the average prediction error (from 27.4 to 52.4 percent) and equivalent years of record (from 1.1 to 3.4 years).

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

Factors associated with dental caries in a group of American Indian children at age 36 months.

PubMed

Warren, John J; Blanchette, Derek; Dawson, Deborah V; Marshall, Teresa A; Phipps, Kathy R; Starr, Delores; Drake, David R

2016-04-01

Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This article reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children, and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28, and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary, and behavioral factors. Nonparametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only noncavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added-sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (P < 0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size, and maternal factors, but further analyses are needed to better understand caries in this population. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Self-harm amongst people of Chinese origin versus White people living in England: a cohort study.

PubMed

Chang, Shu-Sen; Steeg, Sarah; Kapur, Navneet; Webb, Roger T; Yip, Paul S F; Cooper, Jayne

2015-04-14

There has been little previous research on self-harm among people of Chinese origin living in the UK, although this population has grown substantially in recent years and China is now the largest source of international students at UK universities. We conducted a prospective cohort study using self-harm presentation data (1997-2011) collected from three hospitals in the City of Manchester, which has the largest Chinese population across all UK Local Authorities. Rate ratios between the Chinese and White groups were calculated using Poisson regression models. Chi-square tests (or Fisher's exact tests), logistic regression, and log-binomial regression were used to examine differences in characteristics and clinical management between groups. Ethnicity was known in the study cohort for 23,297 (87%) amongst 26,894 individuals aged 15 years and above. A total number of 97/23,297 (0.4%) people of Chinese ethnic origin presented with self-harm over the study period and 20,419 (88%) were White people. Incidence of self-harm in the Chinese group (aged 16-64 years) was less than one fifth of that found in White people (0.6 versus 3.2 per 1000 person-years; rate ratio 0.18, 95% confidence interval 0.13-0.24), and was particularly low amongst men of Chinese origin. Individuals of Chinese origin who presented with self-harm were younger, more likely to be female and students, and more likely to self-injure and describe relationship problems as a precipitant than White people. They were less likely to have clinical risk factors such as drug/alcohol misuse and receiving psychiatric treatment, and were rated to have lower risk of self-harm repetition by treating clinicians. Future research needs to investigate whether the low incidence of self-harm presenting to hospitals amongst people of Chinese origin truly reflects a lower frequency of self-harm, or alternatively is due to markedly different post-episode help-seeking behaviours or student overrepresentation in this ethnic group. Relevant healthcare professionals need to be aware of the risk characteristics of people of Chinese origin who self-harm.

Estimating a Logistic Discrimination Functions When One of the Training Samples Is Subject to Misclassification: A Maximum Likelihood Approach.

PubMed

Nagelkerke, Nico; Fidler, Vaclav

2015-01-01

The problem of discrimination and classification is central to much of epidemiology. Here we consider the estimation of a logistic regression/discrimination function from training samples, when one of the training samples is subject to misclassification or mislabeling, e.g. diseased individuals are incorrectly classified/labeled as healthy controls. We show that this leads to zero-inflated binomial model with a defective logistic regression or discrimination function, whose parameters can be estimated using standard statistical methods such as maximum likelihood. These parameters can be used to estimate the probability of true group membership among those, possibly erroneously, classified as controls. Two examples are analyzed and discussed. A simulation study explores properties of the maximum likelihood parameter estimates and the estimates of the number of mislabeled observations.

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6–9 years of Leon, Nicaragua

PubMed Central

del Socorro Herrera, Miriam; Medina-Solis, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-01-01

Background Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. Material/Methods A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Results Mean age was 7.49±1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54±3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. Conclusions The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators. PMID:24247119

Gingival recession and associated factors in a homogeneous Mexican adult male population: A cross-sectional study

PubMed Central

Minaya-Sánchez, Mirna; Medina-Solís, Carlo E.; Vallejos-Sánchez, Ana A.; Marquez-Corona, Maria L.; Pontigo-Loyola, América P.; Islas-Granillo, Horacio; Maupomé, Gerardo

2012-01-01

Background: Diverse variables are implicated in the pathogenesis of gingival recession; more detailed knowledge about the relationship between the clinical presentation of gingival recession and assorted risk indicators may lead to improved patient monitoring, early intervention, and subsequent prevention. The objective was to evaluate clinically gingival recession in a homogeneous Mexican adult male population and to determine the strength of association with related factors. Method: A cross-sectional study was carried out in a largely homogeneous group in terms of ethnic background, socioeconomic status, gender, occupation, and medical/dental insurance, in Campeche, Mexico. Periodontal examinations were undertaken to determine diverse clinical dental variables. All periodontal clinical examinations were assessed using the Florida Probe System, a dental chair and one examiner. Questionnaires were used to collect diverse risk indicators. Statistical analyses were undertaken with negative binomial regression models. Results: The mean number of sites with gingival recession per subject was 6.73±5.81; the prevalence was 87.6%. In the negative binomial regression model we observed that for (i) each year of age, and (ii) each percentage unit of increase in sites with plaque, and (iii) with suppuration, mean sites with gingival recession increased 2.9%, 1.0% and 13.0%, respectively. Having a spouse was associated with gingival recession. Conclusions: We observed association between gingival recession, and sociodemographic and clinical parameters. Patients need to be educated about risk indicators for gingival recession as well as the preventive maneuvers that may be implemented to minimize its occurrence. The potential of improved oral self-care to prevent a largely benign condition such as gingival recession is important, given the associated disorders that may ensue root exposure, such as root caries and root hypersensitivity. Key words:Oral health, periodontal health, gingival recession, adults, Mexico. PMID:22549678

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6-9 years of Leon, Nicaragua.

PubMed

Herrera, Miriam del Socorro; Medina-Solís, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-11-19

Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Mean age was 7.49 ± 1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54 ± 3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

Comparing Environmental Influences on Coral Bleaching Across and within Species using Clustered Binomial Regression

EPA Science Inventory

Differential susceptibility among reef-building coral species can lead to community shifts and loss of diversity as a result of temperature-induced mass bleaching events. However, the influence of the local environment on species-specific bleaching susceptibilities has not been ...

Confidence Intervals for Weighted Composite Scores under the Compound Binomial Error Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2018-01-01

Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID:28620609

Inflammation, homocysteine and carotid intima-media thickness.

PubMed

Baptista, Alexandre P; Cacdocar, Sanjiva; Palmeiro, Hugo; Faísca, Marília; Carrasqueira, Herménio; Morgado, Elsa; Sampaio, Sandra; Cabrita, Ana; Silva, Ana Paula; Bernardo, Idalécio; Gome, Veloso; Neves, Pedro L

2008-01-01

Cardiovascular disease is the main cause of morbidity and mortality in chronic renal patients. Carotid intima-media thickness (CIMT) is one of the most accurate markers of atherosclerosis risk. In this study, the authors set out to evaluate a population of chronic renal patients to determine which factors are associated with an increase in intima-media thickness. We included 56 patients (F=22, M=34), with a mean age of 68.6 years, and an estimated glomerular filtration rate of 15.8 ml/min (calculated by the MDRD equation). Various laboratory and inflammatory parameters (hsCRP, IL-6 and TNF-alpha) were evaluated. All subjects underwent measurement of internal carotid artery intima-media thickness by high-resolution real-time B-mode ultrasonography using a 10 MHz linear transducer. Intima-media thickness was used as a dependent variable in a simple linear regression model, with the various laboratory parameters as independent variables. Only parameters showing a significant correlation with CIMT were evaluated in a multiple regression model: age (p=0.001), hemoglobin (p=00.3), logCRP (p=0.042), logIL-6 (p=0.004) and homocysteine (p=0.002). In the multiple regression model we found that age (p=0.001) and homocysteine (p=0.027) were independently correlated with CIMT. LogIL-6 did not reach statistical significance (p=0.057), probably due to the small population size. The authors conclude that age and homocysteine correlate with carotid intima-media thickness, and thus can be considered as markers/risk factors in chronic renal patients.

ELASTIC NET FOR COX’S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM

PubMed Central

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox’s proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox’s proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems. PMID:23226932

Active and uncontrolled asthma among children exposed to air stack emissions of sulphur dioxide from petroleum refineries in Montreal, Quebec: A cross-sectional study

PubMed Central

Deger, Leylâ; Plante, Céline; Jacques, Louis; Goudreau, Sophie; Perron, Stéphane; Hicks, John; Kosatsky, Tom; Smargiassi, Audrey

2012-01-01

BACKGROUND: Little attention has been devoted to the effects on children’s respiratory health of exposure to sulphur dioxide (SO2) in ambient air from local industrial emissions. Most studies on the effects of SO2 have assessed its impact as part of the regional ambient air pollutant mix. OBJECTIVE: To examine the association between exposure to stack emissions of SO2 from petroleum refineries located in Montreal’s (Quebec) east-end industrial complex and the prevalence of active asthma and poor asthma control among children living nearby. METHODS: The present cross-sectional study used data from a respiratory health survey of Montreal children six months to 12 years of age conducted in 2006. Of 7964 eligible households that completed the survey, 842 children between six months and 12 years of age lived in an area impacted by refinery emissions. Ambient SO2 exposure levels were estimated using dispersion modelling. Log-binomial regression models were used to estimate crude and adjusted prevalence ratios (PRs) and 95% CIs for the association between yearly school and residential SO2 exposure estimates and asthma outcomes. Adjustments were made for child’s age, sex, parental history of atopy and tobacco smoke exposure at home. RESULTS: The adjusted PR for the association between active asthma and SO2 levels was 1.14 (95% CI 0.94 to 1.39) per interquartile range increase in modelled annual SO2. The effect on poor asthma control was greater (PR=1.39 per interquartile range increase in modelled SO2 [95% CI 1.00 to 1.94]). CONCLUSIONS: Results of the present study suggest a relationship between exposure to refinery stack emissions of SO2 and the prevalence of active and poor asthma control in children who live and attend school in proximity to refineries. PMID:22536578

A Preliminary Analysis on Empirical Attenuation of Absolute Velocity Response Spectra (1 to 10s) in Japan

NASA Astrophysics Data System (ADS)

Dhakal, Y. P.; Kunugi, T.; Suzuki, W.; Aoi, S.

2013-12-01

The Mw 9.1 Tohoku-oki earthquake caused strong shakings of super high rise and high rise buildings constructed on deep sedimentary basins in Japan. Many people felt difficulty in moving inside the high rise buildings even on the Osaka basin located at distances as far as 800 km from the epicentral area. Several empirical equations are proposed to estimate the peak ground motions and absolute acceleration response spectra applicable mainly within 300 to 500km from the source area. On the other hand, Japan Meteorological Agency has recently proposed four classes of absolute velocity response spectra as suitable indices to qualitatively describe the intensity of long-period ground motions based on the observed earthquake records, human experiences, and actual damages that occurred in the high rise and super high rise buildings. The empirical prediction equations have been used in disaster mitigation planning as well as earthquake early warning. In this study, we discuss the results of our preliminary analysis on attenuation relation of absolute velocity response spectra calculated from the observed strong motion records including those from the Mw 9.1 Tohoku-oki earthquake using simple regression models with various model parameters. We used earthquakes, having Mw 6.5 or greater, and focal depths shallower than 50km, which occurred in and around Japanese archipelago. We selected those earthquakes for which the good quality records are available over 50 observation sites combined from K-NET and KiK-net. After a visual inspection on approximately 21,000 three component records from 36 earthquakes, we used about 15,000 good quality records in the period range of 1 to 10s within the hypocentral distance (R) of 800km. We performed regression analyses assuming the following five regression models. (1) log10Y (T) = c+ aMw - log10R - bR (2) log10Y (T) = c+ aMw - log10R - bR +gS (3) log10Y (T) = c+ aMw - log10R - bR + hD (4) log10Y (T) = c+ aMw - log10R - bR +gS +hD (5) log10Y (T) = c+ aMw - log10R - bR +∑gS +hD where Y (T) is the 5% damped peak vector response in cm/s derived from two horizontal component records for a natural period T in second; in (2) S is a dummy variable which is one if a site is located inside a sedimentary basin, otherwise zero. In (3), D is depth to the top of layer having a particular S-wave velocity. We used the deep underground S-wave velocity model available from Japan Seismic Hazard Information Station (J-SHIS). In (5), sites are classified to various sedimentary basins. Analyses show that the standard deviations decrease in the order of the models listed and the all coefficients are significant. Interestingly, coefficients g are found to be different from basin to basin at most periods, and the depth to the top of layer having S-wave velocity of 1.7km/s gives the smallest standard deviation of 0.31 at T=4.4s in (5). This study shows the possibility of describing the observed peak absolute velocity response values by using simple model parameters like site location and sedimentary depth soon after the location and magnitude of an earthquake are known.

School Violence: The Role of Parental and Community Involvement

ERIC Educational Resources Information Center

Lesneskie, Eric; Block, Steven

2017-01-01

This study utilizes the School Survey on Crime and Safety to identify variables that predict lower levels of violence from four domains: school security, school climate, parental involvement, and community involvement. Negative binomial regression was performed and the findings indicate that statistically significant results come from all four…

Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.

PubMed

Moineddin, Rahim; Meaney, Christopher; Agha, Mohammad; Zagorski, Brandon; Glazier, Richard Henry

2011-08-19

Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic. The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases. Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.

Transformation Model Choice in Nonlinear Regression Analysis of Fluorescence-based Serial Dilution Assays

PubMed Central

Fong, Youyi; Yu, Xuesong

2016-01-01

Many modern serial dilution assays are based on fluorescence intensity (FI) readouts. We study optimal transformation model choice for fitting five parameter logistic curves (5PL) to FI-based serial dilution assay data. We first develop a generalized least squares-pseudolikelihood type algorithm for fitting heteroscedastic logistic models. Next we show that the 5PL and log 5PL functions can approximate each other well. We then compare four 5PL models with different choices of log transformation and variance modeling through a Monte Carlo study and real data. Our findings are that the optimal choice depends on the intended use of the fitted curves. PMID:27642502

Risk of central nervous system defects in offspring of women with and without mental illness.

PubMed

Ayoub, Aimina; Fraser, William D; Low, Nancy; Arbour, Laura; Healy-Profitós, Jessica; Auger, Nathalie

2018-02-22

We sought to determine the relationship between maternal mental illness and the risk of having an infant with a central nervous system defect. We analyzed a cohort of 654,882 women aged less than 20 years between 1989 and 2013 who later delivered a live born infant in any hospital in Quebec, Canada. The primary exposure was mental illness during pregnancy or hospitalization for mental illness before pregnancy. The outcomes were neural and non-neural tube defects of the central nervous system in any offspring. We computed risk ratios (RR) and 95% confidence intervals (CI) for the association between mental disorders and risk of central nervous system defects in log-binomial regression models adjusted for age at delivery, total parity, comorbidity, socioeconomic deprivation, place of residence, and time period. Maternal mental illness was associated with an increased risk of nervous system defects in offspring (RR 1.76, 95% CI 1.64-1.89). Hospitalization for any mental disorder was more strongly associated with non-neural tube (RR 1.84, 95% CI 1.71-1.99) than neural tube defects (RR 1.31, 95% CI 1.08-1.59). Women at greater risk of nervous system defects in offspring tended to be diagnosed with multiple mental disorders, have more than one hospitalization for mental disease, or be 17 or older at first hospitalization. A history of mental illness is associated with central nervous system defects in offspring. Women hospitalized for mental illness may merit counseling at first symptoms to prevent central nervous system defects at pregnancy.

The role of intersection and street design on severity of bicycle-motor vehicle crashes

PubMed Central

Verma, Santosh; Mekary, Rania A; Courtney, Theodore K; Christiani, David C

2017-01-01

Background Safety concerns are a major barrier to cycling. Intersection and street design variables such as intersection angles and street width might contribute to the severity of crashes and the safety concerns. In this study we examined whether these design variables were associated with bicycle-motor vehicle crashes (BMVC) severity. Methods Using the geographical information system and latitudes/longitudes recorded by the police using a global positioning device, we extracted intersection angles, street width, bicycle facilities, posted speed limits and annual average daily traffic from 3266 BMVC data from New York City police records. Additional variables about BMVC, including age and sex of the bicyclist, time of the day, road surface conditions, road character, vehicle type and injury severity, were obtained from police reports. Injury severity was classified as severe (incapacitating or killed) or non-severe (non-incapacitating, possible injury). The associations between injury severity and environment design variables were examined using multivariate log-binomial regression model. Findings Compared with crashes at orthogonal intersections, crashes at non-orthogonal intersections had 1.37 times (95% CI 1.05 to 1.80) and non-intersection street segments had 1.31 times (95% CI 1.01 to 1.70) higher risk of a severe injury. Crashes that involved a truck or a bus were twice as likely to result in a severe injury outcome; street width was not significantly associated with injury severity. Conclusion Crashes at non-orthogonal intersections and non-intersection segments are more likely to result in higher injury severity. The findings can be used to improve road design and develop effective safety interventions. PMID:27881469

Preterm birth time trends in Europe: a study of 19 countries

PubMed Central

Zeitlin, J; Szamotulska, K; Drewniak, N; Mohangoo, AD; Chalmers, J; Sakkeus, L; Irgens, L; Gatt, M; Gissler, M; Blondel, B

2013-01-01

Objective To investigate time trends in preterm birth in Europe by multiplicity, gestational age, and onset of delivery. Design Analysis of aggregate data from routine sources. Setting Nineteen European countries. Population Live births in 1996, 2000, 2004, and 2008. Methods Annual risk ratios of preterm birth in each country were estimated with year as a continuous variable for all births and by subgroup using log-binomial regression models. Main outcome measures Overall preterm birth rate and rate by multiplicity, gestational age group, and spontaneous versus non-spontaneous (induced or prelabour caesarean section) onset of labour. Results Preterm birth rates rose in most countries, but the magnitude of these increases varied. Rises in the multiple birth rate as well as in the preterm birth rate for multiple births contributed to increases in the overall preterm birth rate. About half of countries experienced no change or decreases in the rates of singleton preterm birth. Where preterm birth rates rose, increases were no more prominent at 35–36 weeks of gestation than at 32–34 weeks of gestation. Variable trends were observed for spontaneous and non-spontaneous preterm births in the 13 countries with mode of onset data; increases were not solely attributed to non-spontaneous preterm births. Conclusions There was a wide variation in preterm birth trends in European countries. Many countries maintained or reduced rates of singleton preterm birth over the past 15 years, challenging a widespread belief that rising rates are the norm. Understanding these cross-country differences could inform strategies for the prevention of preterm birth. PMID:23700966

Does age modify the association between psychosocial factors at work and deterioration of self-rated health?

PubMed

Burr, Hermann; Hasselhorn, Hans Martin; Kersten, Norbert; Pohrt, Anne; Rugulies, Reiner

2017-09-01

Objectives Few epidemiological studies have examined whether associations of psychosocial working conditions with risk of poor health differ by age. Based on results from mostly cross-sectional studies, we test whether (i) psychosocial relational factors (social support) are more strongly associated with declining health of older than younger employees and (ii) psychosocial job factors (workpace, influence, possibilities for development) are more strongly associated with declining health of younger than older employees. Methods We extracted two cohorts from the Danish Work Environment Cohort Study (DWECS): the 2000-2005 and 2005-2010 cohorts. The participating 5281 employees with good self-rated health (SRH) at baseline were observed in 6585 5-year time windows. Using log-binomial regression analyses, we analysed whether psychosocial factors at work predicted 5-year deterioration of SRH. Effect modification by age was estimated by calculating relative excess risk due to interaction (RERI). Results High workpace among men, low influence at work as well as low social support from colleagues among women, and low possibilities for development and low social support from supervisors among both genders predicted 5-year decline in SRH. Of the 20 interaction analyses, only 1 was statistically significant and in the opposite direction of what was hypothesized (higher risk for declining SRH among middle-aged men with low possibilities for development compared to the young men with high possibilities for development). Conclusions Psychosocial working conditions predicted decline in SRH in this 5-year follow-up study. The model did not support our hypotheses about modifying effects by age.

Early Posttherapy Hospitalizations Among Survivors of Childhood Leukemia and Lymphoma.

PubMed

Smitherman, Andrew B; Wilkins, Tania M; Blatt, Julie; Dusetzina, Stacie B

2016-08-01

Long-term survivors of childhood cancers are at increased risk for hospitalization. To test the hypothesis that many treatment-related morbidities are identifiable in the early posttherapy period, we determined the rates and causes for hospitalization among survivors of leukemia and lymphoma during the first 3 years posttherapy. Using a health plan claims database, we identified patients aged 0 to 21 years old treated for leukemia or lymphoma from 2000 to 2010. Survivors were matched 10:1 with similar children without a history of cancer. Hospitalization rates over 3 years were compared using Cox proportional hazards regression and risks of cause-specific hospitalization were compared using log-binomial models. Nineteen percent of childhood leukemia and lymphoma survivors were hospitalized in the first 3 years off therapy. Leukemia survivors (N=529) experienced over 6 times (hazard ratio=6.3; 95% confidence interval [CI], 4.9-8.0) and lymphoma survivors (N=454) over 3 times the hospitalization rate of controls (hazard ratio=3.2; 95% CI, 2.5-4.2). Compared with children without a cancer history, survivors were at increased risk for hospitalization due to infectious causes (leukemia: relative risk [RR], 60.0; 95% CI, 23.4-154.0; lymphoma: RR, 10.0; 95% CI, 4.4-22.9). In addition, lymphoma survivors were at increased risk for cardiovascular-related (RR, 15.0; 95% CI, 5.4-42.0) and pulmonary-related (RR, 8.1; 95% CI, 3.9-16.8) hospitalizations. These findings highlight the morbidity experienced by survivors and suggest that treatment-associated complications may be emerging soon after therapy completion.

Maternal uptake of pertussis cocooning strategy and other pregnancy related recommended immunizations.

PubMed

Wong, C Y; Thomas, N J; Clarke, M; Boros, C; Tuckerman, J; Marshall, H S

2015-01-01

Maternal immunization is an important strategy to prevent severe morbidity and mortality in mothers and their offspring. This study aimed to identify whether new parents were following immunization recommendations prior to pregnancy, during pregnancy, and postnatally. A cross-sectional survey was conducted by a questionnaire administered antenatally to pregnant women attending a maternity hospital with a follow-up telephone interview at 8-10 weeks post-delivery. Factors associated with uptake of pertussis vaccination within the previous 5 y or postnatally and influenza vaccination during pregnancy were explored using log binomial regression models. A total of 297 pregnant women completed the questionnaire. For influenza vaccine, 20.3% were immunized during pregnancy and 3.0% postnatally. For pertussis vaccine, 13.1% were vaccinated within 5 y prior to pregnancy and 31 women received the vaccine postnatally, 16 (51.6%) received the vaccine >4 weeks after delivery. Receiving a recommendation from a healthcare provider (HCP) was an independent predictor for receipt of both pertussis (RR 2.07, p < 0.001) and influenza vaccine (RR 2.26, p = 0.001). Non-English speaking mothers were significantly less likely to have received pertussis vaccination prior to pregnancy or postnatally (RR 0.24, p = 0.011). Multiparous pregnant women were less likely to have received an influenza vaccine during their current pregnancy (p = 0.015). Uptake of pregnancy related immunization is low and likely due to poor knowledge of availability, language barriers and lack of recommendations from HCPs. Strategies to improve maternal vaccine uptake should include education about recommended vaccines for both HCPs and parents and written information in a variety of languages.

Maternal History of Child Abuse and Obesity Risk in Offspring: Mediation by Weight in Pregnancy.

PubMed

Leonard, Stephanie A; Petito, Lucia C; Rehkopf, David H; Ritchie, Lorrene D; Abrams, Barbara

2017-08-01

Women's experience of childhood adversity may contribute to their children's risk of obesity. Possible causal pathways include higher maternal weight and gestational weight gain, which have been associated with both maternal childhood adversity and obesity in offspring. This study included 6718 mother-child pairs from the National Longitudinal Survey of Youth 1979 in the United States (1979-2012). We applied multiple log-binomial regression models to estimate associations between three markers of childhood adversity (physical abuse, household alcoholism, and household mental illness) and offspring obesity in childhood. We estimated natural direct effects to evaluate mediation by prepregnancy BMI and gestational weight gain. Among every 100 mothers who reported physical abuse in childhood, there were 3.7 (95% confidence interval: -0.1 to 7.5) excess cases of obesity in 2- to 5-year olds compared with mothers who did not report physical abuse. Differences in prepregnancy BMI, but not gestational weight gain, accounted for 25.7% of these excess cases. There was no evidence of a similar relationship for household alcoholism or mental illness or for obesity in older children. In this national, prospective cohort study, prepregnancy BMI partially explained an association between maternal physical abuse in childhood and obesity in preschool-age children. These findings underscore the importance of life-course exposures in the etiology of child obesity and the potential multi-generational consequences of child abuse. Research is needed to determine whether screening for childhood abuse and treatment of its sequelae could strengthen efforts to prevent obesity in mothers and their children.

[Socioeconomic inequalities in subjective health among 11- to 15-year-olds in Germany. A trend analysis from 2002-2010].

PubMed

Moor, I; Pförtner, T K; Lampert, T; Ravens-Sieberer, U; Richter, M

2012-07-01

Health is strongly linked to social position. Several studies showed consistent or increasing health inequalities in the last decades. So far, few studies focused on trends in social inequalities in health among children and adolescents. The objective of this study was to determine changes in socioeconomic differences in subjective health between 2002 and 2010 of 11- to 15-year-old students in Germany.Data were obtained from the German part of the cross-sectional WHO "Health Behaviour in School-aged Children" survey in 2002 (n=5.221), 2006 (n=6.896) and 2010 (n=4.723). Log binomial regression models were used to assess the extent of inequalities in self-rated health across the survey years. Socioeconomic position was measured using the family affluence scale (FAS) and perceived family wealth.A relatively small improvement in good/excellent self-rated health was observed in both boys and girls from 2002 (85.2%) to 2010 (87%). Despite this improvement, inequalities in self-rated health could be identified for all survey years, regardless of which socioeconomic indicator was used (RR 1.4 up to 1.8). The level of these differences remained virtually unchanged in girls and boys in that time period.The same relationship of family affluence, family wealth and self-rated health has persisted for almost a decade in Germany. Recent strategies could not tackle existing inequalities in self-rated health which indicates an increasing need to develop and implement innovative measures and to intensify efforts of social and health policy. © Georg Thieme Verlag KG Stuttgart · New York.

Family caregivers' reported nonadherence to the controller medication of asthma in children in Casablanca (Morocco): Extent and associated factors.

PubMed

Ménard, Sandra; Jbilou, Jalila; Lauzier, Sophie

2018-01-16

Recent statistics show a relatively high prevalence of asthma among Moroccan children and a weak control over their symptoms. To our knowledge, no research has been carried out to document adherence to the controller treatment in this population. This study aims 1) to assess the extent of children's nonadherence to the controller treatment of asthma in an urban region of Morocco as reported by a family caregiver, and 2) to identify the associated factors. We conducted a cross-sectional study among caregivers of asthmatic children (2-12 years old) in different health and education facilities of Casablanca-Settat. We administered face-to-face questionnaires incorporating validated instruments (Medication Adherence Rating Scale-Asthma (MARS-A), Beliefs about Medicines Questionnaire (BMQ), Asthma Knowledge Questionnaire). Univariate and multivariate log-binomial regressions evaluating the association between several factors and reported nonadherence were performed (prevalence ratios (PR) and 95% confidence intervals (CI)). Through two public hospitals, three private medical clinics, and one private school, 103 caregivers were recruited. Low adherence to the controller treatment of asthma was reported by 48% of the caregivers (MARS-A <45). In the multivariate model, caregivers with the lowest level of knowledge about asthma were almost three times more likely to report low adherence compared to caregivers with the highest level (PR = 2.93; 95% CI: 1.14-7.52). This study highlights the finding that low adherence is widespread in this context and also the importance of targeting caregivers' knowledge of asthma for interventions.

Relationship between Nutritional Support and Tuberculosis Treatment Outcomes in West Bengal, India.

PubMed

Samuel, Blesson; Volkmann, Tyson; Cornelius, Sushma; Mukhopadhay, Sugata; MejoJose; Mitra, Kaushik; Kumar, Ajay M V; Oeltmann, John E; Parija, Sidhajyoti; Prabhakaran, Aslesh Ottapura; Moonan, Patrick K; Chadha, Vineet K

2016-12-01

Poverty and poor nutrition are associated with the risk of developing tuberculosis (TB). Socioeconomic factors may interfere with anti-tuberculosis treatment compliance and its outcome. We examined whether providing nutritional support (monthly supply of rice and lentil beans) to TB patients who live below the poverty line was associated with TB treatment outcome. This was a retrospective cohort study of sputum smear-positive pulmonary TB patients living below the poverty line (income of <$1.25 per day) registered for anti-tuberculosis treatment in two rural districts of West Bengal, India during 2012 to 2013. We compared treatment outcomes among patients who received nutritional support with those who did not. A log-binomial regression model was used to assess the relation between nutritional support and unsuccessful treatment outcome (loss-to-follow-up, treatment failure and death). Of 173 TB patients provided nutritional support, 15 (9%) had unsuccessful treatment outcomes, while 84 (21%) of the 400 not provided nutrition support had unsuccessful treatment outcomes (p < 0.001). After adjusting for age, sex and previous treatment, those who received nutritional support had a 50% reduced risk of unsuccessful treatment outcome than those who did not receive nutritional support (Relative Risk: 0.51; 95% Confidence Intervals: 0.30 - 0.86). Under programmatic conditions, monthly rations of rice and lentils were associated with lower risk of unsuccessful treatment outcome among impoverished TB patients. Given the relatively small financial commitment needed per patient ($10 per patient per month), the national TB programme should consider scaling up nutritional support among TB patients living below the poverty line.

Relationship between Nutritional Support and Tuberculosis Treatment Outcomes in West Bengal, India

PubMed Central

Samuel, Blesson; Volkmann, Tyson; Cornelius, Sushma; Mukhopadhay, Sugata; MejoJose; Mitra, Kaushik; Kumar, Ajay M. V.; Oeltmann, John E.; Parija, Sidhajyoti; Prabhakaran, Aslesh Ottapura; Moonan, Patrick K.; Chadha, Vineet K.

2016-01-01

Introduction Poverty and poor nutrition are associated with the risk of developing tuberculosis (TB). Socioeconomic factors may interfere with anti-tuberculosis treatment compliance and its outcome. We examined whether providing nutritional support (monthly supply of rice and lentil beans) to TB patients who live below the poverty line was associated with TB treatment outcome. Methods This was a retrospective cohort study of sputum smear-positive pulmonary TB patients living below the poverty line (income of <$1.25 per day) registered for anti-tuberculosis treatment in two rural districts of West Bengal, India during 2012 to 2013. We compared treatment outcomes among patients who received nutritional support with those who did not. A log-binomial regression model was used to assess the relation between nutritional support and unsuccessful treatment outcome (loss-to-follow-up, treatment failure and death). Results Of 173 TB patients provided nutritional support, 15 (9%) had unsuccessful treatment outcomes, while 84 (21%) of the 400 not provided nutrition support had unsuccessful treatment outcomes (p < 0.001). After adjusting for age, sex and previous treatment, those who received nutritional support had a 50% reduced risk of unsuccessful treatment outcome than those who did not receive nutritional support (Relative Risk: 0.51; 95% Confidence Intervals: 0.30 - 0.86). Conclusion Under programmatic conditions, monthly rations of rice and lentils were associated with lower risk of unsuccessful treatment outcome among impoverished TB patients. Given the relatively small financial commitment needed per patient ($10 per patient per month), the national TB programme should consider scaling up nutritional support among TB patients living below the poverty line. PMID:28042591

Beyond access: barriers to internet health information seeking among the urban poor

PubMed Central

Okechukwu, Cassandra A; Sorensen, Glorian; Viswanath, K

2016-01-01

Objective Communication inequalities deepen health disparities even when internet access is achieved. The goal of this study is to understand how a range of barriers may inhibit individuals from low socioeconomic position (SEP) from engaging with online health information even when it is freely available. Materials and methods Detailed data were collected from 118 low-SEP individuals from a randomized controlled trial providing internet access. Measures triangulated the health-seeking experience through internet use tracked in real-time, call log data, and self-reported barriers. Negative binomial regression models were fitted with technology and perceived predictors, and our outcome, health information seeking, and then stratified by medical status. Results Participants experienced a median of two computer issues (median 6 days) and two internet issues (median 6.5 days). Duration of internet problems was associated with a decrease in the rate of internet health information seeking by a factor of 0.990 (P = .03) for each additional day. Participants with a medical problem who were frustrated in their search for health information had half the rate of health information seeking of those who were not frustrated (incidence rate ratio = 0.395, P = .030). Discussion Despite IT support, participants still experienced internet connectivity issues that negatively impacted their health information seeking. Frustration in their search to find information may serve as an additional barrier to those who have medical issues. Conclusion After initial internet access, a second-level digital divide emerged due to connectivity issues, highlighting the need to understand the complex network of barriers experienced by low-SEP internet users. PMID:27206459

Hydroxyurea Use in Young Children With Sickle Cell Anemia in New York State.

PubMed

Anders, David G; Tang, Fei; Ledneva, Tatania; Caggana, Michele; Green, Nancy S; Wang, Ying; Sturman, Lawrence S

2016-07-01

This study examined hydroxyurea usage in young children with sickle cell anemia within New York State (NYS). The cohort was 273 children with sickle cell anemia born in NYS in 2006-2009 and enrolled essentially continuously in Medicaid for the first 4 years of life. Medicaid data were used to examine hydroxyurea usage in this group by age at first prescription fill, persistence, region, treatment institution, and year. Log-binomial regression models were used to estimate the likelihood of receiving hydroxyurea treatment. Data from birth through 2014 for all members of the study group were assembled and analyzed in 2015. About 25% of the cohort had at least one filled hydroxyurea prescription by their fifth birthday, and nearly 40% by the end of the study period. The mean proportion of days covered for the first year of therapy was 56.3%. Adherence was also assessed by calculating medication possession ratios for individual treatment periods. Slightly more than one third of treated children showed 80% coverage by these measures. There was a consistent, but not statistically significant, trend toward younger age at first fill. Significant regional and treatment center differences in initiation of hydroxyurea use, but not in persistence after initiation, were noted among NYS centers. Subsequent to clinical studies demonstrating safety, current NYS-wide use of hydroxyurea in young children with sickle cell anemia appears to be widespread and increasing. However, practice differences between treatment centers and inadequate adherence may limit the full disease-modifying effects of hydroxyurea. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

A Health Profile of Arab Americans in Michigan: A Novel Approach to Using a Hospital Administrative Database.

PubMed

Dallo, Florence J; Ruterbusch, Julie J; Kirma, Joseph David; Schwartz, Kendra; Fakhouri, Monty

2016-12-01

The objectives of this study were to estimate and compare the prevalence of heart disease, cancer, chronic lower respiratory disease, stroke, Alzheimer's, diabetes, nephrosis, flu/pneumonia, hypertension, and atherosclerosis between Arab Americans and whites attending a large, metropolitan hospital system. The sample included 68,047 patients, 18 years of age or older, who visited the hospital during 2012. Demographic and disease variables were electronically abstracted. Demographic characteristics were compared between Arab Americans and whites using Chi square tests. Sex specific, age-adjusted prevalence ratios (PR) and 95 % confidence intervals were estimated for these two groups using a log-binomial regression model. Compared to white men, Arab American men had a higher prevalence of diabetes (PR 1.40, 95 % CI 1.29-1.52) and hypertension (PR 1.07, 95 % CI 1.04-1.10), and a lower prevalence of chronic lower respiratory disease (PR 0.74, 95 % CI 0.66-0.83). Compared to white women, Arab American women had a higher prevalence of chronic lower respiratory disease (PR 1.12, 95 % CI 1.01-1.25), diabetes (PR 1.49, 95 % CI 1.38-1.60), influenza/pneumonia (PR 1.26, 95 % CI 1.05-1.51) and hypertension (PR 1.04, 95 % CI 1.01-1.08). This study supports previous findings that health disparities exist for Arab Americans, who are classified as "white" in health statistics. Standard inclusion of Arab American as a separate ethnicity category will aid researchers in assessing the health care needs of this growing minority community.

Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

PubMed

Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei

2016-05-18

Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

PubMed Central

2013-01-01

Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699

Developing a dengue forecast model using machine learning: A case study in China

PubMed Central

Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-01-01

Background In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Methodology/Principal findings Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011–2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. Conclusion and significance The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics. PMID:29036169

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

General regression neural network model for behavior of Salmonella on chicken meat during cold storage.

PubMed

Oscar, Thomas P

2014-05-01

A study was undertaken to investigate and model behavior of Salmonella on chicken meat during cold storage at constant temperatures. Chicken meat (white, dark, or skin) portions (0.75 cm(3)) were inoculated with a single strain of Salmonella Typhimurium DT104 (2.8 log) followed by storage for 0 to 8 d at -8, 0, 8, 12, 14, or 16 °C for model development and at -4, 4, 10, or 14 °C for model validation. A general regression neural network model was developed with commercial software. Performance of the model was considered acceptable when the proportion of residuals (observed--predicted) in an acceptable prediction zone (pAPZ) from -1 log (fail-safe) to 0.5 logs (fail-dangerous) was ≥ 0.7. Growth of Salmonella Typhimurium DT104 on chicken meat was observed at 12, 14, and 16 °C and was highest on dark meat, intermediate on skin, and lowest on white meat. At lower temperatures (-8 to 10 °C) Salmonella Typhimurium DT104 remained at initial levels throughout 8 d of storage except at 4 °C where there was a small (0.4 log) but significant decline. The model had acceptable performance (pAPZ = 0.929) for dependent data (n = 482) and acceptable performance (pAPZ = 0.923) for independent data (n = 235). Results indicated that it is important to include type of meat as an independent variable in the model and that the model provided valid predictions of the behavior of Salmonella Typhimurium DT104 on chicken skin, white, and dark meat during storage for 0 to 8 d at constant temperatures from -8 to 16 °C. A model for predicting behavior of Salmonella on chicken meat during cold storage was developed and validated. The model will help the chicken industry to better predict and manage this risk to public health. Journal of Food Science © 2014 Institute of Food Technologists® No claim to original US government works.

Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models.

PubMed

Chan, Ta-Chien; Teng, Yung-Chu; Hwang, Jing-Shiang

2015-02-21

Emerging novel influenza outbreaks have increasingly been a threat to the public and a major concern of public health departments. Real-time data in seamless surveillance systems such as health insurance claims data for influenza-like illnesses (ILI) are ready for analysis, making it highly desirable to develop practical techniques to analyze such readymade data for outbreak detection so that the public can receive timely influenza epidemic warnings. This study proposes a simple and effective approach to analyze area-based health insurance claims data including outpatient and emergency department (ED) visits for early detection of any aberrations of ILI. The health insurance claims data during 2004-2009 from a national health insurance research database were used for developing early detection methods. The proposed approach fitted the daily new ILI visits and monitored the Pearson residuals directly for aberration detection. First, negative binomial regression was used for both outpatient and ED visits to adjust for potentially influential factors such as holidays, weekends, seasons, temporal dependence and temperature. Second, if the Pearson residuals exceeded 1.96, aberration signals were issued. The empirical validation of the model was done in 2008 and 2009. In addition, we designed a simulation study to compare the time of outbreak detection, non-detection probability and false alarm rate between the proposed method and modified CUSUM. The model successfully detected the aberrations of 2009 pandemic (H1N1) influenza virus in northern, central and southern Taiwan. The proposed approach was more sensitive in identifying aberrations in ED visits than those in outpatient visits. Simulation studies demonstrated that the proposed approach could detect the aberrations earlier, and with lower non-detection probability and mean false alarm rate in detecting aberrations compared to modified CUSUM methods. The proposed simple approach was able to filter out temporal trends, adjust for temperature, and issue warning signals for the first wave of the influenza epidemic in a timely and accurate manner.

Large biases in regression-based constituent flux estimates: causes and diagnostic tools

USGS Publications Warehouse

Hirsch, Robert M.

2014-01-01

It has been documented in the literature that, in some cases, widely used regression-based models can produce severely biased estimates of long-term mean river fluxes of various constituents. These models, estimated using sample values of concentration, discharge, and date, are used to compute estimated fluxes for a multiyear period at a daily time step. This study compares results of the LOADEST seven-parameter model, LOADEST five-parameter model, and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model using subsampling of six very large datasets to better understand this bias problem. This analysis considers sample datasets for dissolved nitrate and total phosphorus. The results show that LOADEST-7 and LOADEST-5, although they often produce very nearly unbiased results, can produce highly biased results. This study identifies three conditions that can give rise to these severe biases: (1) lack of fit of the log of concentration vs. log discharge relationship, (2) substantial differences in the shape of this relationship across seasons, and (3) severely heteroscedastic residuals. The WRTDS model is more resistant to the bias problem than the LOADEST models but is not immune to them. Understanding the causes of the bias problem is crucial to selecting an appropriate method for flux computations. Diagnostic tools for identifying the potential for bias problems are introduced, and strategies for resolving bias problems are described.

Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents.

PubMed

Spertus, Jacob V; Normand, Sharon-Lise T

2018-04-23

High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Work-related injuries involving a hand or fingers among union carpenters in Washington State, 1989 to 2008.

PubMed

Lipscomb, Hester J; Schoenfisch, Ashley; Cameron, Wilfrid

2013-07-01

We evaluated work-related injuries involving a hand or fingers and associated costs among a cohort of 24,830 carpenters between 1989 and 2008. Injury rates and rate ratios were calculated by using Poisson regression to explore higher risk on the basis of age, sex, time in the union, predominant work, and calendar time. Negative binomial regression was used to model dollars paid per claim after adjustment for inflation and discounting. Hand injuries accounted for 21.1% of reported injuries and 9.5% of paid lost time injuries. Older carpenters had proportionately more amputations, fractures, and multiple injuries, but their rates of these more severe injuries were not higher. Costs exceeded $21 million, a cost burden of $0.11 per hour worked. Older carpenters' higher proportion of serious injuries in the absence of higher rates likely reflects age-related reporting differences.

Mental Health Symptoms Among Student Service Members/Veterans and Civilian College Students.

PubMed

Cleveland, Sandi D; Branscum, Adam J; Bovbjerg, Viktor E; Thorburn, Sheryl

2015-01-01

The aim of this study was to investigate if and to what extent student service members/veterans differ from civilian college students in the prevalence of self-reported symptoms of poor mental health. The Fall 2011 implementation of the American College Health Association-National College Health Assessment included 27,774 respondents from 44 colleges and universities. Participants were matched using propensity scores, and the prevalence of symptoms was compared using logistic regression and zero-inflated negative binomial regression models. The odds of feeling overwhelmed in the last 12 months were significantly lower among student service members/veterans with a history of hazardous duty (odd ratio [OR] = 0.46, adjusted p value <.05) compared with civilian students. Military service, with and without hazardous duty deployment, was not a significant predictor of the total number of symptoms of poor mental health. Current student service members/veterans may not be disproportionately affected by poor psychological functioning.

Work performance decrements are associated with Australian working conditions, particularly the demand to work longer hours.

PubMed

Holden, Libby; Scuffham, Paul A; Hilton, Michael F; Vecchio, Nerina N; Whiteford, Harvey A

2010-03-01

To demonstrate the importance of including a range of working conditions in models exploring the association between health- and work-related performance. The Australian Work Outcomes Research Cost-benefit study cross-sectional screening data set was used to explore health-related absenteeism and work performance losses on a sample of approximately 78,000 working Australians, including available demographic and working condition factors. Data collected using the World Health Organization Health and Productivity Questionnaire were analyzed with negative binomial logistic regression and multinomial logistic regressions for absenteeism and work performance, respectively. Hours expected to work, annual wage, and job insecurity play a vital role in the association between health- and work-related performance for both work attendance and self-reported work performance. Australian working conditions are contributing to both absenteeism and low work performance, regardless of health status.

Perceived health status and daily activity participation of older Malaysians.

PubMed

Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

2011-07-01

This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

A Mixed-Effects Heterogeneous Negative Binomial Model for Postfire Conifer Regeneration in Northeastern California, USA

Treesearch

Justin S. Crotteau; Martin W. Ritchie; J. Morgan Varner

2014-01-01

Many western USA fire regimes are typified by mixed-severity fire, which compounds the variability inherent to natural regeneration densities in associated forests. Tree regeneration data are often discrete and nonnegative; accordingly, we fit a series of Poisson and negative binomial variation models to conifer seedling counts across four distinct burn severities and...

A Monte Carlo Risk Analysis of Life Cycle Cost Prediction.

DTIC Science & Technology

1975-09-01

process which occurs with each FLU failure. With this in mind there is no alternative other than the binomial distribution. 24 GOR/SM/75D-6 With all of...Weibull distribution of failures as selected by user. For each failure of the ith FLU, the model then samples from the binomial distribution to deter- mine...which is sampled from the binomial . Neither of the two conditions for normality are met, i.e., that RTS Ie close to .5 and the number of samples close

Risk factors related to Toxoplasma gondii seroprevalence in indoor-housed Dutch dairy goats.

PubMed

Deng, Huifang; Dam-Deisz, Cecile; Luttikholt, Saskia; Maas, Miriam; Nielen, Mirjam; Swart, Arno; Vellema, Piet; van der Giessen, Joke; Opsteegh, Marieke

2016-02-01

Toxoplasma gondii can cause disease in goats, but also has impact on human health through food-borne transmission. Our aims were to determine the seroprevalence of T. gondii infection in indoor-housed Dutch dairy goats and to identify the risk factors related to T. gondii seroprevalence. Fifty-two out of ninety approached farmers with indoor-kept goats (58%) participated by answering a standardized questionnaire and contributing 32 goat blood samples each. Serum samples were tested for T. gondii SAG1 antibodies by ELISA and results showed that the frequency distribution of the log10-transformed OD-values fitted well with a binary mixture of a shifted gamma and a shifted reflected gamma distribution. The overall animal seroprevalence was 13.3% (95% CI: 11.7–14.9%), and at least one seropositive animal was found on 61.5% (95% CI: 48.3–74.7%) of the farms. To evaluate potential risk factors on herd level, three modeling strategies (Poisson, negative binomial and zero-inflated) were compared. The negative binomial model fitted the data best with the number of cats (1–4 cats: IR: 2.6, 95% CI: 1.1–6.5; > = 5 cats:IR: 14.2, 95% CI: 3.9–51.1) and mean animal age (IR: 1.5, 95% CI: 1.1–2.1) related to herd positivity. In conclusion, the ELISA test was 100% sensitive and specific based on binary mixture analysis. T. gondii infection is prevalent in indoor housed Dutch dairy goats but at a lower overall animal level seroprevalence than outdoor farmed goats in other European countries, and cat exposure is an important risk factor.

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

PubMed

Martínez-Ferrer, María Teresa; Ripollés, José Luís; Garcia-Marí, Ferran

2006-06-01

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

Predicting length of stay from an electronic patient record system: a primary total knee replacement example.

PubMed

Carter, Evelene M; Potts, Henry W W

2014-04-04

To investigate whether factors can be identified that significantly affect hospital length of stay from those available in an electronic patient record system, using primary total knee replacements as an example. To investigate whether a model can be produced to predict the length of stay based on these factors to help resource planning and patient expectations on their length of stay. Data were extracted from the electronic patient record system for discharges from primary total knee operations from January 2007 to December 2011 (n=2,130) at one UK hospital and analysed for their effect on length of stay using Mann-Whitney and Kruskal-Wallis tests for discrete data and Spearman's correlation coefficient for continuous data. Models for predicting length of stay for primary total knee replacements were tested using the Poisson regression and the negative binomial modelling techniques. Factors found to have a significant effect on length of stay were age, gender, consultant, discharge destination, deprivation and ethnicity. Applying a negative binomial model to these variables was successful. The model predicted the length of stay of those patients who stayed 4-6 days (~50% of admissions) with 75% accuracy within 2 days (model data). Overall, the model predicted the total days stayed over 5 years to be only 88 days more than actual, a 6.9% uplift (test data). Valuable information can be found about length of stay from the analysis of variables easily extracted from an electronic patient record system. Models can be successfully created to help improve resource planning and from which a simple decision support system can be produced to help patient expectation on their length of stay.

General Strain Theory as a Basis for the Design of School Interventions

ERIC Educational Resources Information Center

Moon, Byongook; Morash, Merry

2013-01-01

The research described in this article applies general strain theory to identify possible points of intervention for reducing delinquency of students in two middle schools. Data were collected from 296 youths, and separate negative binomial regression analyses were used to identify predictors of violent, property, and status delinquency. Emotional…

The Effectiveness of an Electronic Security Management System in a Privately Owned Apartment Complex

ERIC Educational Resources Information Center

Greenberg, David F.; Roush, Jeffrey B.

2009-01-01

Poisson and negative binomial regression methods are used to analyze the monthly time series data to determine the effects of introducing an integrated security management system including closed-circuit television (CCTV), door alarm monitoring, proximity card access, and emergency call boxes to a large privately-owned complex of apartment…

Campaign Strategies and Voter Approval of School Referenda: A Mixed Methods Analysis

ERIC Educational Resources Information Center

Johnson, Paul A.; Ingle, William Kyle

2009-01-01

Drawing from state administrative data and surveys of superintendents in Ohio, this mixed methods study examined factors associated with voters' approval of local school levies. Utilizing binomial logistic regression, this study found that new levies and poverty rates were significantly associated with a decrease in the likelihood of passage.…

Predicting Error Bars for QSAR Models

NASA Astrophysics Data System (ADS)

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches.

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018

PubMed Central

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-01-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks. PMID:29717695

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018.

PubMed

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-04-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks.

Pulmonary function tests do not predict mortality in patients undergoing continuous-flow left ventricular assist device implantation.

PubMed

Bedzra, Edo K S; Dardas, Todd F; Cheng, Richard K; Pal, Jay D; Mahr, Claudius; Smith, Jason W; Shively, Kent; Masri, S Carolina; Levy, Wayne C; Mokadam, Nahush A

2017-12-01

To investigate the effect of pulmonary function testing on outcomes after continuous flow left ventricular assist device implantation. A total of 263 and 239 patients, respectively, had tests of forced expiratory volume in 1 second and diffusing capacity of the lungs for carbon monoxide preoperatively for left ventricular assist device implantations between July 2005 and September 2015. Kaplan-Meier analysis and multivariable Cox regressions were performed to evaluate mortality. Patients were analyzed in a single cohort and across 5 groups. Postoperative intensive care unit and hospital lengths of stay were evaluated with negative binomial regressions. There is no association of forced expiratory volume in 1 second and diffusing capacity of the lungs for carbon monoxide with survival and no difference in mortality at 1 and 3 years between the groups (log rank P = .841 and .713, respectively). Greater values in either parameter were associated with decreased hospital lengths of stay. Only diffusing capacity of the lungs for carbon monoxide was associated with increased intensive care unit length of stay in the group analysis (P = .001). Ventilator times, postoperative pneumonia, reintubation, and tracheostomy rates were similar across the groups. Forced expiratory volume in 1 second and diffusing capacity of the lungs for carbon monoxide are not associated with operative or long-term mortality in patients undergoing continuous flow left ventricular assist device implantation. These findings suggest that these abnormal pulmonary function tests alone should not preclude mechanical circulatory support candidacy. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Validation of a questionnaire on hand hygiene in the construction industry.

PubMed

Timmerman, Johan G; Zilaout, Hicham; Heederik, Dick; Spee, Ton; Smit, Lidwien A M

2014-10-01

Construction workers are at risk of developing occupational contact dermatitis. Gloves, when used properly, may protect against chemicals and coarse materials. We investigated the prevalence and determinants of contact dermatitis in a population of Dutch construction workers and aimed at validating questionnaire items on hand hygiene. A cross-sectional study was conducted at 13 construction sites, yielding data of 177 subjects (95% response rate). A questionnaire covering questions on hand hygiene and contact dermatitis symptoms was used. Agreement between workplace observations and a number of questionnaire items was assessed by calculating Cohen's kappa. Log-binomial regression analysis was used to assess the association between contact dermatitis and various hand hygiene-related determinants. The 1-year prevalence of self-reported contact dermatitis in our study sample was 46.9%. Multiple regression analysis showed a positive association with difficulties with hand cleaning (prevalence ratio [PR]: 1.26, 95% confidence interval [CI]: 1.05-1.52), hand contamination at the end of the working day (PR: 2.30, 95% CI: 1.14-4.65), and intensive hand cream use (PR: 2.07, 95% CI: 1.42-3.01). Observations of hand contamination, glove use, and glove types were found to agree well with the self-reported data from the questionnaire (Cohen's kappa's 0.75, 0.97, and 0.88). Self-reported contact dermatitis prevalence in construction workers was high and related to hand hygiene. A strong agreement was found between workplace observations and self-reported questionnaire data. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface methodology].

PubMed

Lv, Shao-Wa; Liu, Dong; Hu, Pan-Pan; Ye, Xu-Yan; Xiao, Hong-Bin; Kuang, Hai-Xue

2010-03-01

To optimize the process of extracting effective constituents from Aralia elata by response surface methodology. The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values. Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%. It shows the optimum model is highly predictive.

Factors Influencing Early Feeding of Foods and Drinks Containing Free Sugars—A Birth Cohort Study

PubMed Central

Ha, Diep H.; Do, Loc G.; Spencer, Andrew John; Golley, Rebecca K.; Rugg-Gunn, Andrew J.; Levy, Steven M.

2017-01-01

Early feeding of free sugars to young children can increase the preference for sweetness and the risk of consuming a cariogenic diet high in free sugars later in life. This study aimed to investigate early life factors influencing early introduction of foods/drinks containing free sugars. Data from an ongoing population-based birth cohort study in Australia were used. Mothers of newborn children completed questionnaires at birth and subsequently at ages 3, 6, 12, and 24 months. The outcome was reported feeding (Yes/No) at age 6–9 months of common foods/drinks sources of free sugars (hereafter referred as foods/drinks with free sugars). Household income quartiles, mother’s sugar-sweetened beverage (SSB) consumption, and other maternal factors were exposure variables. Analysis was conducted progressively from bivariate to multivariable log-binomial regression with robust standard error estimation to calculate prevalence ratios (PR) of being fed foods/drinks with free sugars at an early age (by 6–9 months). Models for both complete cases and with multiple imputations (MI) for missing data were generated. Of 1479 mother/child dyads, 21% of children had been fed foods/drinks with free sugars. There was a strong income gradient and a significant positive association with maternal SSB consumption. In the complete-case model, income Q1 and Q2 had PRs of 1.9 (1.2–3.1) and 1.8 (1.2–2.6) against Q4, respectively. The PR for mothers ingesting SSB everyday was 1.6 (1.2–2.3). The PR for children who had been breastfed to at least three months was 0.6 (0.5–0.8). Similar findings were observed in the MI model. Household income at birth and maternal behaviours were significant determinants of early feeding of foods/drinks with free sugars. PMID:29065527

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Brooker, John; Mallis, Melissa; Hursh, Steve; Caldwell, Lynn; Myers, Jerry

2011-01-01

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Use of the negative binomial-truncated Poisson distribution in thunderstorm prediction

NASA Technical Reports Server (NTRS)

Cohen, A. C.

1971-01-01

A probability model is presented for the distribution of thunderstorms over a small area given that thunderstorm events (1 or more thunderstorms) are occurring over a larger area. The model incorporates the negative binomial and truncated Poisson distributions. Probability tables for Cape Kennedy for spring, summer, and fall months and seasons are presented. The computer program used to compute these probabilities is appended.

Use of the binomial distribution to predict impairment: application in a nonclinical sample.

PubMed

Axelrod, Bradley N; Wall, Jacqueline R; Estes, Bradley W

2008-01-01

A mathematical model based on the binomial theory was developed to illustrate when abnormal score variations occur by chance in a multitest battery (Ingraham & Aiken, 1996). It has been successfully used as a comparison for obtained test scores in clinical samples, but not in nonclinical samples. In the current study, this model has been applied to demographically corrected scores on the Halstead-Reitan Neuropsychological Test Battery, obtained from a sample of 94 nonclinical college students. Results found that 15% of the sample had impairments suggested by the Halstead Impairment Index, using criteria established by Reitan and Wolfson (1993). In addition, one-half of the sample obtained impaired scores on one or two tests. These results were compared to that predicted by the binomial model and found to be consistent. The model therefore serves as a useful resource for clinicians considering the probability of impaired test performance.

Apgar score and dental caries risk in the primary dentition of five year olds.

PubMed

Sanders, A E; Slade, G D

2010-09-01

Conditions in utero and early life underlie risk for several childhood disorders. This study tested the hypothesis that the Apgar score predicted dental caries in the primary dentition. A retrospective cohort study conducted in 2003 examined associations between conditions at birth and early life with dental caries experience at five years. Dental examination data for a random sample of five-year-old South Australian children were obtained from School Dental Service electronic records. A questionnaire mailed to the parents obtained information about neonatal status at delivery (five-minute Apgar score, birthweight, plurality, gestational age) and details about birth order, weaning, and behavioural, familial and sociodemographic characteristics. Of the 1398 sampled children with a completed questionnaire (response rate=64.6%), 1058 were singleton term deliveries among whom prevalence of dental caries was 40.1%. In weighted log-binomial regression analysis, children with an Apgar score of <=8 relative to a score of 9-10 had greater probability of dental caries in the primary dentition after adjusting for sociodemographic and behavioural covariates and water fluoridation concentration (adjusted PR=1.47, 95% CI=1.11, 1.95). Readily accessible markers of early life, such as the Apgar score, may guide clinicians in identifying children at potentially heightened risk for dental caries and aid decision-making in allocating preventive services.

Induced abortion in a Southern European region: examining inequalities between native and immigrant women.

PubMed

Rodriguez-Alvarez, Elena; Borrell, Luisa N; González-Rábago, Yolanda; Martín, Unai; Lanborena, Nerea

2016-09-01

To examine induced abortion (IA) inequalities between native and immigrant women in a Southern European region and whether these inequalities depend on a 2010 Law facilitating IA. We conducted two analyses: (1) prevalence of total IAs, repeat and second trimester IA, in native and immigrant women aged 12-49 years for years 2009-2013 according to country of origin; and (2) log-binomial regression was used to quantify the association of place of origin with repeat and second trimester IAs among women with IAs. Immigrants were more likely to have an IA than Spanish women, with the highest probability in Sub-Saharan Africa (PR 8.32 95 % CI 3.66-18.92). Immigrant women with an IA from countries other than Maghreb and Asia have higher probabilities of a repeat IA than women from Spain. Women from Europe non-EU/Romania were 50 % (95 % CI 0.30-0.79) less likely to have a second trimester IA, while women from Central America/Caribbean were 45 % (95 % CI 1.11-1.89) more likely than Spanish women. The 2010 Law did not affect these associations. There is a need for parenthood planning programs and more information and access to contraception methods especially in immigrant women to help decrease IAs.

Gender and socioeconomic status in relation to weight perception and weight control behavior in Korean adults.

PubMed

Joh, Hee-Kyung; Oh, Juhwan; Lee, Hae-Jeung; Kawachi, Ichiro

2013-01-01

In Korea, obesity is more prevalent among men and lower socioeconomic groups. To explain this obesity disparity, we compared weight perception and weight control behavior across gender and socioeconomic status (SES). We analyzed data from 16,260 participants aged 20 years or older in a nationally representative cross-sectional survey. SES indicators included education and income levels. Weight under-perception was defined when participants considered themselves lighter than their measured BMI status. Either no active or inappropriate weight control (i.e., trying to gain weight in obese individuals) was considered to be unhealthy patterns. Multivariate prevalence ratios were calculated using log-binomial regressions. Men had a higher prevalence of weight under-perception (24.5 vs. 11.9%) and unhealthy patterns of weight control behavior (57 vs. 40%) than women. Low education level was associated with weight under-perception (ptrend = 0.022 in men, ptrend < 0.001 in women). Both education and income levels were significantly associated with patterns of weight control behavior (for education: ptrend < 0.001 in men and women; for income: ptrend = 0.047 in men, ptrend < 0.001 in women). Weight perception and weight control behavior significantly varied by gender and SES. Public actions should be directed toward improving perception and behavior of high-risk populations.

Physical activity patterns and metabolic syndrome in Costa Rica

PubMed Central

Hastert, Theresa A.; Gong, Jian; Campos, Hannia; Baylin, Ana

2015-01-01

Objective To examine whether total physical activity or activity patterns are associated with metabolic syndrome and its components. Methods Participants include 1,994 controls from a case-control study of non-fatal myocardial infarction in Costa Rica (1994–2004). Physical activity was assessed via self-administered questionnaire and patterns were identified using principal components analysis. Metabolic syndrome was assessed via blood samples and anthropometry measurements from in-home study visits. Prevalence ratios (PR) and 95% confidence intervals (CI) were calculated using log binomial regression. Adjusted least squares means of metabolic syndrome components were calculated by quintile of total activity and pattern scores. Results Four activity patterns were identified: rest/sleep, agricultural, light indoor activity, and manual labor. Total activity was not associated with metabolic syndrome. Metabolic syndrome prevalence was 20% lower in participants with the highest scores on the agricultural job pattern compared to those with the lowest (PR: 0.80, 95% CI: 0.68–0.94). Higher total activity was associated with lower triglycerides and lower HDL cholesterol. Higher scores on each pattern were inversely associated with metabolic syndrome components, particularly waist circumference and fasting blood glucose. Conclusions Patterns or types of physical activity may be more strongly associated with metabolic syndrome and its components than total activity levels. PMID:25445330

Social-environmental factors and protective sexual behavior among sex workers: the Encontros intervention in Brazil.

PubMed

Lippman, Sheri A; Donini, Angela; Díaz, Juan; Chinaglia, Magda; Reingold, Arthur; Kerrigan, Deanna

2010-04-01

We sought to determine the association of social-environmental factors with condom use and sexually transmitted infections (STIs) among 420 sex workers participating in an STI/HIV prevention study in Corumbá, Brazil, to inform future intervention efforts. Participants provided urine samples for polymerase chain reaction testing of chlamydia and gonorrhea and responded to multi-item scales addressing perceived social cohesion, participation in networks, and access to and management of resources. We conducted multivariate log-linear and negative binomial regression analyses of these data. Increased social cohesion was inversely associated with number of unprotected sex acts in the preceding week among women (adjusted incidence rate ratio [IRR] = 0.80; P < .01), and there was a marginal association among men (adjusted IRR = 0.41; P = .08). Women's increased participation in social networks was associated with a decrease in frequency of unprotected sex acts (adjusted IRR = 0.83; P = .04), as was men's access to and management of social and material resources (IRR = 0.15; P = .01). Social-environmental factors were not associated with STIs. The social context within which populations negotiate sexual behaviors is associated with condom use. Future efforts to prevent STI/HIV should incorporate strategies to modify the social environment.

Social-Environmental Factors and Protective Sexual Behavior Among Sex Workers: The Encontros Intervention in Brazil

PubMed Central

Donini, Angela; Díaz, Juan; Chinaglia, Magda; Reingold, Arthur; Kerrigan, Deanna

2010-01-01

Objectives. We sought to determine the association of social–environmental factors with condom use and sexually transmitted infections (STIs) among 420 sex workers participating in an STI/HIV prevention study in Corumbá, Brazil, to inform future intervention efforts. Methods. Participants provided urine samples for polymerase chain reaction testing of chlamydia and gonorrhea and responded to multi-item scales addressing perceived social cohesion, participation in networks, and access to and management of resources. We conducted multivariate log-linear and negative binomial regression analyses of these data. Results. Increased social cohesion was inversely associated with number of unprotected sex acts in the preceding week among women (adjusted incidence rate ratio [IRR] = 0.80; P < .01), and there was a marginal association among men (adjusted IRR = 0.41; P = .08). Women's increased participation in social networks was associated with a decrease in frequency of unprotected sex acts (adjusted IRR = 0.83; P = .04), as was men's access to and management of social and material resources (IRR = 0.15; P = .01). Social–environmental factors were not associated with STIs. Conclusions. The social context within which populations negotiate sexual behaviors is associated with condom use. Future efforts to prevent STI/HIV should incorporate strategies to modify the social environment. PMID:19762673

Perceived discrimination and self-rated health in the immigrant population of the Basque Country, Spain.

PubMed

Rodríguez-Álvarez, Elena; González-Rábago, Yolanda; Borrell, Luisa N; Lanborena, Nerea

To examine the effect of perceived discrimination and self-rated health among the immigrant population in the Basque Country, Spain, and determine whether this effect varies according to region of origin, age, sex and education. Descriptive cross-sectional study. The study population included immigrants aged 18 and older residing in the Basque Country. Data from the 2014 Foreign Immigrant Population Survey (n=3,456) were used. Log-binomial regression was used to quantify the association between perceived discrimination and self-rated health before and after checking for the selected characteristics. Almost 1 in 10 immigrant adults reports perceiving discrimination. In adjusted analyses, the immigrants perceiving discrimination were almost were 1.92 more likely to rate their health as poor (prevalence ratio: 1.92; 95% CI: 1.44-2.56) than those who did not report discrimination. This association did not vary according to region of origin, age, sex or educational level. Perceived discrimination shows a consistent relationship with perceived health. Moreover, this association did not depend on the region of origin, age, sex or educational level of immigrants. These results show the need for implementing inclusive policies to eliminate individual and institutional discrimination and reduce health inequalities between the immigrant and native populations. Copyright © 2017. Publicado por Elsevier España, S.L.U.

A modified fetal heart rate tracing interpretation system for prediction of cesarean section

PubMed Central

Schnettler, William T.; Rogers, Jennifer; Barber, Rachel E.; Hacker, Michele R.

2013-01-01

Objective To investigate whether a modified version of the 2008 National Institute of Child Health and Human Development (NICHD) interpretation system upon admission decreases cesarean delivery risk. Methods This retrospective cohort study ascribed a modified category to the first 30 min of fetal heart rate (FHR) tracings in labor. Category I was divided into two subsets (Ia and Ib) by the presence of accelerations. Category II was divided into four subsets (IIa–IId) based on baseline FHR, variability, response to stimulation and decelerations. Log-binomial regression was used to calculate risk ratios (RR) and 95% confidence intervals (CI). Results A category was ascribed to 910 women. Most FHR tracings were Category Ia (65.8%), Ib (7.7%), IIb (11.8%) and IId (14.0%). Category Ib tracings (fewer than two accelerations) were 2.26 (95% CI: 1.13–4.52) times more likely to result in cesarean delivery for abnormal FHR tracing than Category Ia tracings. A similar increase in risk was seen when comparing Category IIb and Category IId with Category Ia. Conclusion Application of a modified version of the 2008 NICHD FHR interpretation system to the initial 30 min of labor can identify women at increased risk of cesarean delivery for abnormal FHR tracing. PMID:21942513

Racial and ethnic disparities in universal cervical length screening with transvaginal ultrasound

PubMed Central

Haviland, Miriam J; Shainker, Scott A; Hacker, Michele R; Burris, Heather H

2016-01-01

Objective Determine if race or ethnicity is associated with missed or late transvaginal cervical length screening in a universal screening program. Methods Retrospective cohort study of nulliparous women with singleton gestations and a fetal anatomical ultrasound from 16-24 weeks' gestation from January, 2012 through November, 2013. We classified women into mutually exclusive racial and ethnic groups: non-Hispanic black (black), Hispanic, Asian, non-Hispanic white (white), and other or unknown race. We used log-binomial regression to calculate the risk ratio (RR) and 95% confidence interval (CI) of missed or late (≥ 20 weeks' gestation) screening vs. optimally-timed screening between the different racial and ethnic groups. Results Among the 2 967 women in our study population, 971 (32.7%) had either missed or late cervical length screening. Compared to white women, black (RR: 1.3; 95% CI:1.1-1.5) and Hispanic (RR:1.2; 95% CI:1.01-1.5) women were more likely to have missed or late screening. Among women screened, black (vs. white) women were more likely to be screened late (RR: 2.2; 95% CI: 1.6-3.1). Conclusions Black and Hispanic women may be more likely to have missed or late cervical length screenings. PMID:26987873

Attachment to employment and education before work disability pension due to a mental disorder among young adults.

PubMed

Mattila-Holappa, Pauliina; Joensuu, Matti; Ahola, Kirsi; Vahtera, Jussi; Virtanen, Marianna

2016-05-13

We examined attachment to employment and education among young adults before they were granted a fixed-term work disability pension due to psychiatric diagnosis, and the factors associated with this attachment. The data comprised all persons aged 18-34 who received a new-onset fixed-term disability pension compensation due to a mental disorder in Finland in 2008 (N = 1163). The data were derived from pension applications and the enclosed medical records, and were linked to employment records from a period of three years before the disability pension. We analysed the factors associated with attachment to employment or education with log-binomial regression analysis. Fifty percent of the participants were attached to employment or education before work disability pension. The attached were more often women; had higher basic and vocational education; had mood disorder rather than psychosis diagnosis as a primary diagnosis; and had no record of harmful alcohol use or drug use, or recorded symptoms of mental disorders already at school-age. The level of attachment to employment or education before work disability pension is low among young adults with mental disorders and several risk factors predict poor attachment; severe or comorbid mental disorder, early-life psychiatric morbidity, substance use, male sex, low basic education, and lacking vocational education.

Acute Rejection in Renal Transplant Patients of a Hospital in Bogota, Colombia

PubMed Central

García, P.; Huerfano, M; Rodríguez, M; Caicedo, A; Berrío, F; Gonzalez, C

2016-01-01

Background: Renal transplantation is the best treatment for end stage renal disease. Acute graft rejection is one of the main complications and may influence graft survival. Objective: To determine the incidence and features of acute cellular rejection (ACR) episodes confirmed by biopsy. Methods: We studied a cohort of 175 patients who underwent renal transplantation between 2004 and 2012 to determine the cumulative incidence of ACR confirmed by biopsy and to identify the associated risk factors using multivariate analysis. Results: The one-year patient survival was 96.6%; the graft survival was 93.7%. The incidence of ACR within one year was 14.3%, of which 46% were observed within 6 months following transplantation. The most frequently observed ACR type was 1B according to the Banff classification system (42%). A relationship between ACR and receipt of a kidney from expanded criteria donors was observed, both in univariate and adjusted multiple log-binomial regression analyses, but only 6.3% of patients received extended criteria donor kidneys. No other relationships between variables were found. Conclusion: ACR frequency in this study was similar to that of other cohorts reported previously. We need a bigger sample of renal transplants from expanded criteria donors, PRA and DSA test to support the results. PMID:27721962

Correspondence analysis to evaluate the transmission of Staphylococcus aureus strains in two New York State maximum-security prisons.

PubMed

Befus, M; Mukherjee, D V; Herzig, C T A; Lowy, F D; Larson, E

2017-07-01

Prisons/jails are thought to amplify the transmission of Staphylococcus aureus (SA) particularly methicillin-resistant SA infection and colonisation. Two independently pooled cross-sectional samples of detainees being admitted or discharged from two New York State maximum-security prisons were used to explore this concept. Private interviews of participants were conducted, during which the anterior nares and oropharynx were sampled and assessed for SA colonisation. Log-binomial regression and correspondence analysis (CA) were used to evaluate the prevalence of colonisation at entry as compared with discharge. Approximately 51% of admitted (N = 404) and 41% of discharged (N = 439) female detainees were colonised with SA. Among males, 59% of those admitted (N = 427) and 49% of those discharged (N = 393) were colonised. Females had a statistically significant higher prevalence (1·26: P = 0·003) whereas males showed no significant difference (1·06; P = 0·003) in SA prevalence between entry and discharge. CA demonstrated that some strains, such as spa types t571 and t002, might have an affinity for certain mucosal sites. Contrary to our hypothesis, the prison setting did not amplify SA transmission, and CA proved to be a useful tool in describing the population structure of strains according to time and/or mucosal site.

Psychotherapeutic and vocational interventions among young adults with work disability due to mental disorders in Finland.

PubMed

Mattila-Holappa, Pauliina; Joensuu, Matti; Ahola, Kirsi; Kivekäs, Teija; Kivimäki, Mika; Koskinen, Aki; Virtanen, Marianna

2018-05-01

Backround: Little is known about treatment and rehabilitation received and planned among young adults with work disability due to a mental disorder. To examine the implemented psychotherapeutic and vocational interventions and treatment plans among young adults with work disability due to a mental disorder. Data were collected from medical records of young Finnish adults aged 18-34 with a long-term work disability history due to a mental disorder (N = 1163). The participant characteristics associated with four types of interventions were analyzed using log-binomial regression analysis. In total, 34% had participated in a psychotherapeutic intervention. Of the non-students, 26% had participated in vocational intervention. For 46% of the non-students, neither type of intervention was planned. Both implemented and planned psychotherapeutic interventions were associated with female sex, high education, attachment to employment, and absence of substance abuse. Low education and childhood adversity were associated with implemented vocational interventions and absence of substance abuse with planned vocational interventions. There is an unmet need for psychotherapeutic interventions among men, among those with lower socio-economic status, and among those with poor attachment to labor market. In addition, there is a lack of vocational interventions for those with high education. People with substance abuse are largely excluded from both types of interventions.

Comparison of modeling methods to predict the spatial distribution of deep-sea coral and sponge in the Gulf of Alaska

NASA Astrophysics Data System (ADS)

Rooper, Christopher N.; Zimmermann, Mark; Prescott, Megan M.

2017-08-01

Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska's marine waters, and are associated with many different species of fishes and invertebrates. These ecosystems are vulnerable to the effects of commercial fishing activities and climate change. We compared four commonly used species distribution models (general linear models, generalized additive models, boosted regression trees and random forest models) and an ensemble model to predict the presence or absence and abundance of six groups of benthic invertebrate taxa in the Gulf of Alaska. All four model types performed adequately on training data for predicting presence and absence, with regression forest models having the best overall performance measured by the area under the receiver-operating-curve (AUC). The models also performed well on the test data for presence and absence with average AUCs ranging from 0.66 to 0.82. For the test data, ensemble models performed the best. For abundance data, there was an obvious demarcation in performance between the two regression-based methods (general linear models and generalized additive models), and the tree-based models. The boosted regression tree and random forest models out-performed the other models by a wide margin on both the training and testing data. However, there was a significant drop-off in performance for all models of invertebrate abundance ( 50%) when moving from the training data to the testing data. Ensemble model performance was between the tree-based and regression-based methods. The maps of predictions from the models for both presence and abundance agreed very well across model types, with an increase in variability in predictions for the abundance data. We conclude that where data conforms well to the modeled distribution (such as the presence-absence data and binomial distribution in this study), the four types of models will provide similar results, although the regression-type models may be more consistent with biological theory. For data with highly zero-inflated distributions and non-normal distributions such as the abundance data from this study, the tree-based methods performed better. Ensemble models that averaged predictions across the four model types, performed better than the GLM or GAM models but slightly poorer than the tree-based methods, suggesting ensemble models might be more robust to overfitting than tree methods, while mitigating some of the disadvantages in predictive performance of regression methods.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors.

PubMed

Hansson, Mari; Pemberton, John; Engkvist, Ola; Feierberg, Isabella; Brive, Lars; Jarvis, Philip; Zander-Balderud, Linda; Chen, Hongming

2014-06-01

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp(3)-hybridized carbons (Fsp3), and fraction of molecular framework (f(MF)). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. f(MF) has only a minor influence besides its correlation with the other molecular descriptors. © 2013 Society for Laboratory Automation and Screening.

Performance and structure of single-mode bosonic codes

NASA Astrophysics Data System (ADS)

Albert, Victor V.; Noh, Kyungjoo; Duivenvoorden, Kasper; Young, Dylan J.; Brierley, R. T.; Reinhold, Philip; Vuillot, Christophe; Li, Linshu; Shen, Chao; Girvin, S. M.; Terhal, Barbara M.; Jiang, Liang

2018-03-01

The early Gottesman, Kitaev, and Preskill (GKP) proposal for encoding a qubit in an oscillator has recently been followed by cat- and binomial-code proposals. Numerically optimized codes have also been proposed, and we introduce codes of this type here. These codes have yet to be compared using the same error model; we provide such a comparison by determining the entanglement fidelity of all codes with respect to the bosonic pure-loss channel (i.e., photon loss) after the optimal recovery operation. We then compare achievable communication rates of the combined encoding-error-recovery channel by calculating the channel's hashing bound for each code. Cat and binomial codes perform similarly, with binomial codes outperforming cat codes at small loss rates. Despite not being designed to protect against the pure-loss channel, GKP codes significantly outperform all other codes for most values of the loss rate. We show that the performance of GKP and some binomial codes increases monotonically with increasing average photon number of the codes. In order to corroborate our numerical evidence of the cat-binomial-GKP order of performance occurring at small loss rates, we analytically evaluate the quantum error-correction conditions of those codes. For GKP codes, we find an essential singularity in the entanglement fidelity in the limit of vanishing loss rate. In addition to comparing the codes, we draw parallels between binomial codes and discrete-variable systems. First, we characterize one- and two-mode binomial as well as multiqubit permutation-invariant codes in terms of spin-coherent states. Such a characterization allows us to introduce check operators and error-correction procedures for binomial codes. Second, we introduce a generalization of spin-coherent states, extending our characterization to qudit binomial codes and yielding a multiqudit code.

Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.

PubMed

Hosseinpour, Mehdi; Yahaya, Ahmad Shukri; Sadullah, Ahmad Farhan

2014-01-01

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

PubMed

Golmohammadi, Hassan

2009-11-30

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.

EM Adaptive LASSO—A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes

PubMed Central

Mallick, Himel; Tiwari, Hemant K.

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice. PMID:27066062

EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

Mallick, Himel; Tiwari, Hemant K

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.

Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

PubMed

Mpundu-Kaambwa, Christine; Chen, Gang; Russo, Remo; Stevens, Katherine; Petersen, Karin Dam; Ratcliffe, Julie

2017-04-01

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

Forecast of severe fever with thrombocytopenia syndrome incidence with meteorological factors.

PubMed

Sun, Ji-Min; Lu, Liang; Liu, Ke-Ke; Yang, Jun; Wu, Hai-Xia; Liu, Qi-Yong

2018-06-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and some studies reported that SFTS incidence was associated with meteorological factors, while no report on SFTS forecast models was reported up to date. In this study, we constructed and compared three forecast models using autoregressive integrated moving average (ARIMA) model, negative binomial regression model (NBM), and quasi-Poisson generalized additive model (GAM). The dataset from 2011 to 2015 were used for model construction and the dataset in 2016 were used for external validity assessment. All the three models fitted the SFTS cases reasonably well during the training process and forecast process, while the NBM model forecasted better than other two models. Moreover, we demonstrated that temperature and relative humidity played key roles in explaining the temporal dynamics of SFTS occurrence. Our study contributes to better understanding of SFTS dynamics and provides predictive tools for the control and prevention of SFTS. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling number of claims and prediction of total claim amount

NASA Astrophysics Data System (ADS)

Acar, Aslıhan Şentürk; Karabey, Uǧur

2017-07-01

In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

Usage and users of online self-management programs for adult patients with atopic dermatitis and food allergy: an explorative study.

PubMed

van Os-Medendorp, Harmieke; van Leent-de Wit, Ilse; de Bruin-Weller, Marjolein; Knulst, André

2015-05-23

Two online self-management programs for patients with atopic dermatitis (AD) or food allergy (FA) were developed with the aim of helping patients cope with their condition, follow the prescribed treatment regimen, and deal with the consequences of their illness in daily life. Both programs consist of several modules containing information, personal stories by fellow patients, videos, and exercises with feedback. Health care professionals can refer their patients to the programs. However, the use of the program in daily practice is unknown. The aim of this study was to explore the use and characteristics of users of the online self-management programs "Living with eczema," and "Living with food allergy," and to investigate factors related to the use of the trainings. A cross-sectional design was carried out in which the outcome parameters were the number of log-ins by patients, the number of hits on the system's core features, disease severity, quality of life, and domains of self-management. Descriptive statistics were used to summarize sample characteristics and to describe number of log-ins and hits per module and per functionality. Correlation and regression analyses were used to explore the relation between the number of log-ins and patient characteristics. Since the start, 299 adult patients have been referred to the online AD program; 173 logged in for at least one occasion. Data from 75 AD patients were available for analyses. Mean number of log-ins was 3.1 (range 1-11). Linear regression with the number of log-ins as dependent variable showed that age and quality of life contributed most to the model, with betas of .35 ( P=.002) and .26 (P=.05), respectively, and an R(2) of .23. Two hundred fourteen adult FA patients were referred to the online FA training, 124 logged in for at least one occasion and data from 45 patients were available for analysis. Mean number of log-ins was 3.0 (range 1-11). Linear regression with the number of log-ins as dependent variable revealed that adding the self-management domain "social integration and support" to the model led to an R(2) of .13. The modules with information about the disease, diagnosis, and treatment were most visited. Most hits were on the information parts of the modules (55-58%), followed by exercises (30-32%). The online self-management programs "Living with eczema" and "Living with food allergy" were used by patients in addition to the usual face-to-face care. Almost 60% of all referred patients logged in, with an average of three log-ins. All modules seemed to be relevant, but there is room for improvement in the use of the training. Age, quality of life, and lower social integration and support were related to the use of the training, but only part of the variance in use could be explained by these variables.

Traumatic Brain Injury among US Active Duty Military Personnel and Negative Drinking-Related Consequences

PubMed Central

Adams, Rachel Sayko; Larson, Mary Jo; Corrigan, John D.; Ritter, Grant A.; Williams, Thomas V.

2013-01-01

This study used the 2008 Department of Defense Survey of Health Related Behaviors among Active Duty Military Personnel to determine whether traumatic brain injury (TBI) is associated with past year drinking-related consequences. The study sample included currently-drinking personnel who had a combat deployment in the past year and were home for ≥6 months (N = 3,350). Negative binomial regression models were used to assess the incidence rate ratios of consequences, by TBI-level. Experiencing a TBI with a loss of consciousness >20 minutes was significantly associated with consequences independent of demographics, combat exposure, posttraumatic stress disorder, and binge drinking. The study’s limitations are noted. PMID:23869456

Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents.

PubMed

Qiao, Yuanhua; Keren, Nir; Mannan, M Sam

2009-08-15

Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.

Statistical procedures for analyzing mental health services data.

PubMed

Elhai, Jon D; Calhoun, Patrick S; Ford, Julian D

2008-08-15

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

Perceived Prevalence of Teasing and Bullying Predicts High School Dropout Rates

ERIC Educational Resources Information Center

Cornell, Dewey; Gregory, Anne; Huang, Francis; Fan, Xitao

2013-01-01

This prospective study of 276 Virginia public high schools found that the prevalence of teasing and bullying (PTB) as perceived by both 9th-grade students and teachers was predictive of dropout rates for this cohort 4 years later. Negative binomial regression indicated that one standard deviation increases in student- and teacher-reported PTB were…

Assessing Trauma, Substance Abuse, and Mental Health in a Sample of Homeless Men

ERIC Educational Resources Information Center

Kim, Mimi M.; Ford, Julian D.; Howard, Daniel L.; Bradford, Daniel W.

2010-01-01

This study examined the impact of physical and sexual trauma on a sample of 239 homeless men. Study participants completed a self-administered survey that collected data on demographics, exposure to psychological trauma, physical health and mental health problems, and substance use or misuse. Binomial logistic regression analyses were used to…

Predicting Error Bars for QSAR Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schroeter, Timon; Technische Universitaet Berlin, Department of Computer Science, Franklinstrasse 28/29, 10587 Berlin; Schwaighofer, Anton

2007-09-18

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D{sub 7} models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniquesmore » for the other modelling approaches.« less

Biological activity of aldose reductase and lipophilicity of pyrrolyl-acetic acid derivatives

NASA Astrophysics Data System (ADS)

Kumari, A.; Kumari, R.; Kumar, R.; Gupta, M.

2011-12-01

Quantitative Structure-Activity Relationship modeling is a powerful approach for correlating an organic compound to its lipophilicity. In this paper QSAR models are established for estimation of correlation of the lipophilicity of a series of pyrrolyl-acetic acid derivatives, inhibitors of the aldose reductase enzyme, in the n-octanol-water system with biological activity of aldose reductase. Lipophilicity, expressed by the logarithm of n-octnol-water partition coefficient log P and biological activity of aldose reductase inhibitory activity by log it. Result obtained by QSAR modeling of compound series reveal a definite trend in biological activity and a further improvement in quantitative relationships are established if, beside log P, Hammett electronic constant σ and connectivity index chi-3 (3 χ) term included in the regression equation. The tri-parametric model with log P, 3 χ and σ as correlating parameters have been found to be the best which gives a variance of 87% ( R 2 = 0.8743). A compound has been found to be serious outlier and when the same has been excluded the model explains about 94% variance of the data set ( R 2 = 0.9447). The topological index (3 χ) has been found to be a good parameter for modeling the biological activity.

A Systematic Review of the Literature on Cystic Echinococcosis Frequency Worldwide and Its Associated Clinical Manifestations

PubMed Central

Budke, Christine M.; Carabin, Hélène; Ndimubanzi, Patrick C.; Nguyen, Hai; Rainwater, Elizabeth; Dickey, Mary; Bhattarai, Rachana; Zeziulin, Oleksandr; Qian, Men-Bao

2013-01-01

A systematic literature review of cystic echinoccocosis (CE) frequency and symptoms was conducted. Studies without denominators, original data, or using one serological test were excluded. Random-effect log-binomial models were run for CE frequency and proportion of reported symptoms where appropriate. A total of 45 and 25 articles on CE frequency and symptoms met all inclusion criteria. Prevalence of CE ranged from 1% to 7% in community-based studies and incidence rates ranged from 0 to 32 cases per 100,000 in hospital-based studies. The CE prevalence was higher in females (Prevalence Proportion Ratio: 1.35 [95% Bayesian Credible Interval: 1.16–1.53]) and increased with age. The most common manifestations of hepatic and pulmonary CE were abdominal pain (57.3% [95% confidence interval [CI]: 37.3–76.1%]) and cough (51.3% [95% CI: 35.7–66.7%]), respectively. The results are limited by the small number of unbiased studies. Nonetheless, the age/gender prevalence differences could be used to inform future models of CE burden. PMID:23546806

A systematic review of the literature on cystic echinococcosis frequency worldwide and its associated clinical manifestations.

PubMed

Budke, Christine M; Carabin, Hélène; Ndimubanzi, Patrick C; Nguyen, Hai; Rainwater, Elizabeth; Dickey, Mary; Bhattarai, Rachana; Zeziulin, Oleksandr; Qian, Men-Bao

2013-06-01

A systematic literature review of cystic echinoccocosis (CE) frequency and symptoms was conducted. Studies without denominators, original data, or using one serological test were excluded. Random-effect log-binomial models were run for CE frequency and proportion of reported symptoms where appropriate. A total of 45 and 25 articles on CE frequency and symptoms met all inclusion criteria. Prevalence of CE ranged from 1% to 7% in community-based studies and incidence rates ranged from 0 to 32 cases per 100,000 in hospital-based studies. The CE prevalence was higher in females (Prevalence Proportion Ratio: 1.35 [95% Bayesian Credible Interval: 1.16-1.53]) and increased with age. The most common manifestations of hepatic and pulmonary CE were abdominal pain (57.3% [95% confidence interval [CI]: 37.3-76.1%]) and cough (51.3% [95% CI: 35.7-66.7%]), respectively. The results are limited by the small number of unbiased studies. Nonetheless, the age/gender prevalence differences could be used to inform future models of CE burden.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

An empirical tool to evaluate the safety of cyclists: Community based, macro-level collision prediction models using negative binomial regression.

PubMed

Wei, Feng; Lovegrove, Gordon

2013-12-01

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists' road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle-auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle-auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial-local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown 'critical' level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs. Copyright © 2012. Published by Elsevier Ltd.

Techniques for estimating flood-peak discharges of rural, unregulated streams in Ohio

USGS Publications Warehouse

Koltun, G.F.

2003-01-01

Regional equations for estimating 2-, 5-, 10-, 25-, 50-, 100-, and 500-year flood-peak discharges at ungaged sites on rural, unregulated streams in Ohio were developed by means of ordinary and generalized least-squares (GLS) regression techniques. One-variable, simple equations and three-variable, full-model equations were developed on the basis of selected basin characteristics and flood-frequency estimates determined for 305 streamflow-gaging stations in Ohio and adjacent states. The average standard errors of prediction ranged from about 39 to 49 percent for the simple equations, and from about 34 to 41 percent for the full-model equations. Flood-frequency estimates determined by means of log-Pearson Type III analyses are reported along with weighted flood-frequency estimates, computed as a function of the log-Pearson Type III estimates and the regression estimates. Values of explanatory variables used in the regression models were determined from digital spatial data sets by means of a geographic information system (GIS), with the exception of drainage area, which was determined by digitizing the area within basin boundaries manually delineated on topographic maps. Use of GIS-based explanatory variables represents a major departure in methodology from that described in previous reports on estimating flood-frequency characteristics of Ohio streams. Examples are presented illustrating application of the regression equations to ungaged sites on ungaged and gaged streams. A method is provided to adjust regression estimates for ungaged sites by use of weighted and regression estimates for a gaged site on the same stream. A region-of-influence method, which employs a computer program to estimate flood-frequency characteristics for ungaged sites based on data from gaged sites with similar characteristics, was also tested and compared to the GLS full-model equations. For all recurrence intervals, the GLS full-model equations had superior prediction accuracy relative to the simple equations and therefore are recommended for use.

Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets.

PubMed

Feng, Yao-Ze; Elmasry, Gamal; Sun, Da-Wen; Scannell, Amalia G M; Walsh, Des; Morcy, Noha

2013-06-01

Bacterial pathogens are the main culprits for outbreaks of food-borne illnesses. This study aimed to use the hyperspectral imaging technique as a non-destructive tool for quantitative and direct determination of Enterobacteriaceae loads on chicken fillets. Partial least squares regression (PLSR) models were established and the best model using full wavelengths was obtained in the spectral range 930-1450 nm with coefficients of determination R(2)≥ 0.82 and root mean squared errors (RMSEs) ≤ 0.47 log(10)CFUg(-1). In further development of simplified models, second derivative spectra and weighted PLS regression coefficients (BW) were utilised to select important wavelengths. However, the three wavelengths (930, 1121 and 1345 nm) selected from BW were competent and more preferred for predicting Enterobacteriaceae loads with R(2) of 0.89, 0.86 and 0.87 and RMSEs of 0.33, 0.40 and 0.45 log(10)CFUg(-1) for calibration, cross-validation and prediction, respectively. Besides, the constructed prediction map provided the distribution of Enterobacteriaceae bacteria on chicken fillets, which cannot be achieved by conventional methods. It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

PubMed

Hoyer, A; Kuss, O

2015-05-20

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.

Combined computational-experimental approach to predict blood-brain barrier (BBB) permeation based on "green" salting-out thin layer chromatography supported by simple molecular descriptors.

PubMed

Ciura, Krzesimir; Belka, Mariusz; Kawczak, Piotr; Bączek, Tomasz; Markuszewski, Michał J; Nowakowska, Joanna

2017-09-05

The objective of this paper is to build QSRR/QSAR model for predicting the blood-brain barrier (BBB) permeability. The obtained models are based on salting-out thin layer chromatography (SOTLC) constants and calculated molecular descriptors. Among chromatographic methods SOTLC was chosen, since the mobile phases are free of organic solvent. As consequences, there are less toxic, and have lower environmental impact compared to classical reserved phases liquid chromatography (RPLC). During the study three stationary phase silica gel, cellulose plates and neutral aluminum oxide were examined. The model set of solutes presents a wide range of log BB values, containing compounds which cross the BBB readily and molecules poorly distributed to the brain including drugs acting on the nervous system as well as peripheral acting drugs. Additionally, the comparison of three regression models: multiple linear regression (MLR), partial least-squares (PLS) and orthogonal partial least squares (OPLS) were performed. The designed QSRR/QSAR models could be useful to predict BBB of systematically synthesized newly compounds in the drug development pipeline and are attractive alternatives of time-consuming and demanding directed methods for log BB measurement. The study also shown that among several regression techniques, significant differences can be obtained in models performance, measured by R 2 and Q 2 , hence it is strongly suggested to evaluate all available options as MLR, PLS and OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

Using the β-binomial distribution to characterize forest health

Treesearch

S.J. Zarnoch; R.L. Anderson; R.M. Sheffield

1995-01-01

The β-binomial distribution is suggested as a model for describing and analyzing the dichotomous data obtained from programs monitoring the health of forests in the United States. Maximum likelihood estimation of the parameters is given as well as asymptotic likelihood ratio tests. The procedure is illustrated with data on dogwood anthracnose infection (caused...

Seasonal variation and partitioning of endocrine disrupting chemicals in waters and sediments of the Pearl River system, South China.

PubMed

Gong, Jian; Duan, Dandan; Yang, Yu; Ran, Yong; Chen, Diyun

2016-12-01

Endocrine disrupting chemicals (EDCs) were seasonally investigated in surface water, suspended particulate matter, and sediments of the Pearl River Delta (PRD), South China. EDC concentrations in the surface water were generally higher in the summer than in winter. The surface water in the investigated rivers was heavily contaminated by the phenolic xenoestrogens. Moreover, the in-situ log K soc and log K poc values and their regression with log K ow in the field experiments suggest that binding mechanisms other than hydrophobic interaction are present for the sedimentary organic carbon and particulate organic carbon (SOC/POC). The logK soc -logK ow and logK poc -logK ow regression analyses imply that higher complexity of nonhydrophobic interactions with EDCs is present on the SOC samples comparing with the POC samples, which is related to their different sources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pricing American Asian options with higher moments in the underlying distribution

NASA Astrophysics Data System (ADS)

Lo, Keng-Hsin; Wang, Kehluh; Hsu, Ming-Feng

2009-01-01

We develop a modified Edgeworth binomial model with higher moment consideration for pricing American Asian options. With lognormal underlying distribution for benchmark comparison, our algorithm is as precise as that of Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] if the number of the time steps increases. If the underlying distribution displays negative skewness and leptokurtosis as often observed for stock index returns, our estimates can work better than those in Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] and are very similar to the benchmarks in Hull and White [J. Hull, A. White, Efficient procedures for valuing European and American path-dependent options, J. Derivatives 1 (Fall) (1993) 21-31]. The numerical analysis shows that our modified Edgeworth binomial model can value American Asian options with greater accuracy and speed given higher moments in their underlying distribution.

Genetic ancestry is associated with subclinical cardiovascular disease in African Americans and Hispanics from the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Wassel, Christina L.; Pankow, James S.; Peralta, Carmen A.; Choudhry, Shweta; Seldin, Michael F.; Arnett, Donna K.

2009-01-01

Background Differences in cardiovascular disease (CVD) burden exist among racial/ethnic groups in the United States, with African Americans having the highest prevalence. Subclinical CVD measures have also been shown to differ by race/ethnicity. In the United States, there has been significant intermixing among racial/ethnic groups creating admixed populations. Very little research exists on the relationship of genetic ancestry and subclinical CVD measures. Methods and Results These associations were investigated in 712 African-American and 705 Hispanic participants from the MESA candidate gene sub-study. Individual ancestry was estimated from 199 genetic markers using STRUCTURE. Associations of ancestry and coronary artery calcium (CAC) and common and internal carotid intima media thickness (cIMT) were evaluated using log-binomial and linear regression models. Splines indicated linear associations of ancestry with subclinical CVD measures in African-Americans, but presence of threshold effects in Hispanics. Among African Americans, each standard deviation (SD) increase in European ancestry was associated with an 8% (95% CI (1.02, 1.15), p=0.01) greater CAC prevalence. Each SD increase in European ancestry was also associated with a 2% (95% CI (−3.4%, −0.5%), p=0.008) lower common cIMT in African Americans. Among Hispanics, the highest tertile of European ancestry was associated with a 34% greater CAC prevalence, p=0.02 as compared to lowest tertile. Conclusions The linear association of ancestry and subclinical CVD suggests that genetic effects may be important in determining CAC and cIMT among African-Americans. Our results also suggest that CAC and common cIMT may be important phenotypes for further study with admixture mapping. PMID:20031644

Opting for natural birth: A survey of birth intentions among young Icelandic women.

PubMed

Swift, Emma Marie; Gottfredsdottir, Helga; Zoega, Helga; Gross, Mechthild M; Stoll, Kathrin

2017-03-01

To describe and analyse factors associated with natural birth intentions in a sample of pre-pregnant Icelandic women. An internationally validated tool was used to survey pre-pregnant women about their attitudes towards birth. The online survey was sent to all students at the University of Iceland in November 2014. Log binomial regression was used to calculate crude and adjusted relative risks (RR a ), and corresponding 95% confidence intervals (CI), for intentions of natural birth (defined as vaginal birth without epidural analgesia) by high, moderate and low childbirth fear and by high, moderate and low confidence in birth knowledge. Models were adjusted for socio-demographic and psychological factors. 410 eligible women completed the cross-sectional survey. Women with low fear of birth were more likely to have natural birth intentions when compared to women with moderate (RR a  = 2.83; 95% CI; 1.48-5.41) and high (RR a  = 4.86; 95% CI; 1.37-17.27) fear. Women with high confidence in their birth knowledge were more likely to have natural birth intentions compared to women with moderate (RR a  = 2.81; 95% CI; 1.51-5.22) and low (RR a  = 3.42; 95% CI; 1.43-8.18) confidence in their birth knowledge. Pre-pregnant women with low fear of birth and high confidence in their birth knowledge are more likely to have natural birth intentions. Addressing concerns about pain, safety, the perceived unpredictability of birth and worries about the physical impact of childbirth may strengthen natural birth intentions. Copyright © 2016 Elsevier B.V. All rights reserved.

Child and Adolescent Abuse in Relation to Obesity in Adulthood: The Black Women’s Health Study

PubMed Central

Rosenberg, Lynn; Palmer, Julie R; Boggs, Deborah A.; Wise, Lauren A.

2012-01-01

OBJECTIVE: To investigate the association of physical and sexual abuse in childhood and adolescence with risk of adult obesity among black women in the United States. METHODS: Participants were women enrolled in the Black Women’s Health Study, an ongoing prospective cohort study begun in 1995. In 2005, 33 298 participants completed a self-administered questionnaire on early life experiences of abuse. Log-binomial regression models were used to derive risk ratios (RRs) and 95% confidence intervals (CIs) for the relation of child/teenager abuse with obesity (BMI ≥30) and central adiposity (waist circumference >35 inches) reported in 2005. RESULTS: The RR for BMI ≥30, a measure of overall obesity, was 1.29 (95% CI 1.20–1.38) for the highest severity of exposure to child/teenager physical and sexual abuse relative to no abuse. After controlling for postulated intermediates, including reproductive history, diet, physical activity, depressive symptoms, and socioeconomic status, the RR was 1.14 (95% CI 1.08–1.21). The RR for waist circumference >35 inches, which measures central obesity, for severe physical and sexual abuse relative to no abuse was 1.29 (95% CI 1.19–1.38) before adjustment for intermediates and 1.18 (95% CI 1.10–1.27) after adjustment. CONCLUSIONS: Early life sexual and physical abuse was associated with an increased risk of overall and central obesity in adulthood. Although the association between abuse and obesity was explained to some extent by health behaviors, reproductive history, and mental health, these factors did not fully account for the associations. Our data suggest that early life adversity is related to adult body size and weight distribution. PMID:22753562

Anal Human Papillomavirus (HPV) Prevalences and Factors Associated with Abnormal Anal Cytology in HIV-Infected Women in an Urban Cohort from Rio de Janeiro, Brazil

PubMed Central

Luz, Paula M.; Lake, Jordan E.; Levi, José Eduardo; Coutinho, José Ricardo; de Andrade, Angela; Heinke, Thais; Derrico, Mônica; Veloso, Valdilea G.; Friedman, Ruth K.; Grinsztejn, Beatriz

2015-01-01

Abstract Identifying factors, including human papillomavirus (HPV) genotypes, associated with abnormal anal cytology in HIV-infected women have implications for anal squamous cell cancer (SCC) prevention in HIV-infected women. Anal and cervical samples were collected for cytology, and tested for high-(HR-HPV) and low-risk HPV (LR-HPV) genotypes in a cross-sectional analysis of the IPEC Women's HIV Cohort (Rio de Janeiro, Brazil). Multivariate log-binomial regression models estimated prevalence ratios for factors associated with abnormal anal cytology [≥atypical squamous cells of undetermined significance, (ASC-US)]. Characteristics of the 863 participants included: median age 42 years, 57% non-white, 79% current CD4+ T-cell count >350 cells/mm3, 53% HIV-1 viral load <50 copies/mL, median ART duration 5.8 years. Fifty-one percent of anal specimens contained ≥1 HR-HPV genotype; 31% had abnormal anal cytology [14% ASC-US, 11% low-grade squamous intra-epithelial lesion, (LSIL); 2% atypical squamous cells-cannot exclude high-grade SIL (ASC-H); 4% high-grade SIL/cancer (HSIL+)]. In multivariate analysis, cervical LSIL+, nadir CD4+ T-cell count ≤50 cells/mm3, HIV-1 viral load ≥50 copies/mL, and anal HPV 6, 11, 16, 18, 33, 45, 52, 56, and 58 were associated with ≥anal ASC-US (p<0.05). Abnormal anal cytology and HR-HPV prevalences were high. HIV-infected women with cervical LSIL+, low nadir CD4+ counts, or detectable HIV-1 viral loads should be a particular focus for enhanced anal SCC screening efforts. PMID:25361401

Public support for intergenerational oocyte donation in the United States.

PubMed

Bortoletto, Pietro; Farland, Leslie V; Ginsburg, Elizabeth S; Goldman, Randi H

2018-02-01

To determine whether the general public supports intergenerational oocyte donation. Cross-sectional study. Not applicable. A nationally representative sample based on age distribution of United States residents. Not applicable. Characteristics of respondents who supported (strongly agree and agree) various oocyte donation practices were compared with participants who did not support them (disagree and strongly disagree) using log binomial regression to calculate risk ratios (RRs) and 95% confidence intervals of support (95% CIs). Models were adjusted for age, gender, and religion to yield adjusted risk ratios (aRR). A total of 1,915 people responded to the Web-based survey; 53% were female, and 24% were racial/ethnic minorities. Eighty-five percent had prior knowledge of oocyte donation, and 74% felt that a woman should be able to donate oocytes to a family member. The desire to help a family member was the most commonly perceived motivation for donors (79%). Christian-Catholics compared with Christian-non-Catholics (aRR 0.91, 95% CI 0.86-0.98), African Americans compared with non-Hispanic Caucasians (aRR 0.86, 95% CI 0.76-0.97), and Republicans compared with Democrats (RR 0.93, 95% CI 0.88-0.98) were less likely to support intergenerational oocyte donation. Respondents with three or more biological children (RR 1.06, 95% CI 1.00-1.11) compared with those with no children were less likely to support this practice. Eight percent of participants disapproved of donation to any family member. The most common reason for disapproval was the potential negative impact on the child (53%). A majority of Americans support the practice of intergenerational oocyte donation; however, support varies according to demographic characteristics. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Physical and psychosocial ergonomic risk factors for low back pain in automobile manufacturing workers.

PubMed

Vandergrift, Jonathan L; Gold, Judith E; Hanlon, Alexandra; Punnett, Laura

2012-01-01

To examine the association between ergonomic physical and psychosocial exposures and the risk of prevalent and incident low back pain (LBP) in a longitudinal cohort of automobile manufacturing workers. Ergonomic exposure intensity and LBP presence were determined through questionnaires at baseline (n=1181) and to workers in the same job 1 year later (n=505). Models were constructed using log-binomial regression with special attention to interactions between ergonomic exposures. Awkward back posture (prevalence ratio (PR) 1.12, 95% CI 1.07 to 1.17), hand force (PR 1.06, 95% CI 1.02 to 1.10), physical effort (PR 1.10, 95% CI 1.04 to 1.16) and whole body vibration (PR 1.04, 95% CI 1.01 to 1.08) were each associated cross-sectionally with LBP. Awkward back posture (RR 1.13, 95% CI 0.98 to 1.31) and hand force (RR 1.07, 95% CI 0.93 to 1.22) also predicted incident LBP, although estimates were statistically less precise. Neither job control, psychological demands, nor job strain was independently related to risk of incident LBP. Among participants reporting high physical ergonomic exposures and moderate to high job control, increasing job demands was associated with a reduced LBP risk (RR 0.72, 95% CI 0.52 to 1.00). Among participants reporting high physical exposures and low job control, psychological demands was associated with an increased LBP risk (RR 1.30, 95% CI 1.02 to 1.66). Psychosocial workplace interventions for LBP should prioritise jobs in which there are high physical ergonomic exposures. Future studies of LBP should examine the interactions between physical ergonomic risk factors.

Leprosy in Brazil and its association with characteristics of municipalities: ecological study, 2009-2011.

PubMed

Freitas, Lúcia R S; Duarte, Elisabeth C; Garcia, Leila P

2014-10-01

To analyse the ecological association between the demographic and socio-economic characteristics of the Brazilian municipalities and average leprosy incidence rate in the period 2009-2011. An ecological study taking the Brazilian municipalities as its units of analysis. The local empirical Bayes estimation method was used to obtain smoothed incidence rates (SIR) for leprosy. The mean, median, first quartile (Q1) and third quartile (Q3) of the SIR were calculated per 100 000 inhabitants. Hierarchical log-linear negative binomial regression models were used to estimate the incidence rate ratios (IRR). In the period 2009-2011, the average SIR of leprosy in Brazil was 20.2 per 100 000 inhabitants, and the median incidence rate among municipalities was 9.1 per 100 000 inhabitants. Significantly higher adjusted IRR were identified for large municipalities (IRR = 1.67) compared to small municipalities, as well as in municipalities with higher illiteracy rates (IRR = 2.15), more urbanised municipalities (IRR = 1.53), those with greater social inequality as per the Gini index (IRR = 1.26), high percentage of households with inadequate sanitation (IRR = 1.63), higher average number of people per room (IRR = 1.41), high proportions of Family Health Programme coverage (IRR = 1.29), high percentage of household contacts investigated (IRR = 2.30) and those with percentage of cases with grade 2 disability considered to be the medium (IRR = 1.26). In this study, SIR was significantly associated with municipalities with low socio-economic status. Disease control activities need to be focused on these municipalities, and investments need to be made in improving the population's living conditions. © 2014 John Wiley & Sons Ltd.

Reduced vaginal elasticity, reduced lubrication, and deep and superficial dyspareunia in irradiated gynecological cancer survivors.

PubMed

Stinesen Kollberg, Karin; Waldenström, Ann-Charlotte; Bergmark, Karin; Dunberger, Gail; Rossander, Anna; Wilderäng, Ulrica; Åvall-Lundqvist, Elisabeth; Steineck, Gunnar

2015-05-01

The purpose of this study was to examine whether or not vaginal elasticity or lack of lubrication is associated with deep or superficial dyspareunia. We investigated gynecological cancer survivors treated with radiation therapy. In a population-based study with 616 women answering a questionnaire (participation rate 78%) and who were treated with radiotherapy for gynecological cancer, we analyzed information from 243 women (39%) who reported that they had had intercourse during the previous six months. Analyses included log-binomial regression (relative risks) and multiple imputations by chained equations in combination with Bayesian Model Averaging, yielding a posterior probability value. Age range of this cancer recurrent-free group of women was 29-80. Dyspareunia affected 164 of 243 of the women (67%). One hundred thirty-four women (55%) reported superficial pain, 97 women (40%) reported deep pain, and 87 women (36%) reported both types of dyspareunia. The relative risk (RR) of deep dyspareunia was 1.87 (CI 1.41-2.49) with impaired vaginal elasticity compared to normal vaginal elasticity. Age and lower abdominal swelling were separate risk factors for deep dyspareunia. However, effects remain after adjusting for these factors. The relative risk of deep dyspareunia was almost twice as high with impaired vaginal elasticity compared to normal vaginal elasticity. If we wish to treat or even prevent deep dyspareunia in women with gynecological cancer, we may use our knowledge of the pathophysiology of deep dyspareunia and increasingly provide dilators together with instructions on how to use them for stretching exercises in order to retain vaginal elasticity. Results highlight the need for studies with more precise questions distinguishing superficial from deep dyspareunia so that in the future we may be able to primarily try to avoid reduced vaginal elasticity and secondarily reduce the symptoms.

Understanding Predictors of Early Antenatal Care Initiation in Relationship to Timing of HIV Diagnosis in South Africa.

PubMed

Nattey, Cornelius; Jinga, Nelly; Mongwenyana, Constance; Mokhele, Idah; Mohomi, Given; Fox, Matthew P; Onoya, Dorina

2018-06-01

Effective prevention of mother-to-child transmission benefits from early presentation to antenatal care (ANC). It is, however, unclear whether a previous HIV diagnosis results in earlier initiation of ANC. We estimated the probability of early ANC initiation among women with a previous HIV-positive diagnosis compared to those who first tested for HIV during ANC and explored determinants of early ANC among HIV-positive women. We conducted an analysis of a cross-sectional survey among 411 HIV-positive adult (>18 years) women who gave birth at midwife obstetrics units in Gauteng between October 2016 and May 2017. Predictors of early ANC (defined as initiating ANC before or at 14 weeks of gestation) were assessed by multivariate log-binomial regression model. Overall, 51% (210) were diagnosed during pregnancy with 89% (188) initiating antiretroviral therapy on the same day of diagnosis. There was no meaningful difference in the timing of ANC initiation between women with previous HIV diagnosis [adjusted risk ratio (aRR) = 1.2; 95% confidence interval (95% CI): 0.9-1.7] compared with those diagnosed during pregnancy. Early ANC was predicted by planned pregnancy [aRR = 1.3; 95% CI: 1.1-1.7], parity (>2 children) [aRR = 0.6; 95% CI: 0.2-0.9] compared to not having a child, and tuberculosis diagnosis [aRR = 2.9; 95% CI: 1.4-6.1]. Our results suggest the need for a targeted intervention among HIV-positive women by improving the quality, content and outreach of ANC services to enhance early ANC uptake, and minimize mother-to-child transmission risk.

Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.

PubMed

Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J

2016-12-01

Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.

Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.

PubMed

Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J

Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.

Beyond access: barriers to internet health information seeking among the urban poor.

PubMed

McCloud, Rachel F; Okechukwu, Cassandra A; Sorensen, Glorian; Viswanath, K

2016-11-01

Communication inequalities deepen health disparities even when internet access is achieved. The goal of this study is to understand how a range of barriers may inhibit individuals from low socioeconomic position (SEP) from engaging with online health information even when it is freely available. Detailed data were collected from 118 low-SEP individuals from a randomized controlled trial providing internet access. Measures triangulated the health-seeking experience through internet use tracked in real-time, call log data, and self-reported barriers. Negative binomial regression models were fitted with technology and perceived predictors, and our outcome, health information seeking, and then stratified by medical status. Participants experienced a median of two computer issues (median 6 days) and two internet issues (median 6.5 days). Duration of internet problems was associated with a decrease in the rate of internet health information seeking by a factor of 0.990 (P = .03) for each additional day. Participants with a medical problem who were frustrated in their search for health information had half the rate of health information seeking of those who were not frustrated (incidence rate ratio = 0.395, P = .030). Despite IT support, participants still experienced internet connectivity issues that negatively impacted their health information seeking. Frustration in their search to find information may serve as an additional barrier to those who have medical issues. After initial internet access, a second-level digital divide emerged due to connectivity issues, highlighting the need to understand the complex network of barriers experienced by low-SEP internet users. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Executive function associated with sexual risk in young South African women: Findings from the HPTN 068 cohort

PubMed Central

Pettifor, Audrey; Duta, Mihaela; Demeyere, Nele; Wagner, Ryan G.; Selin, Amanda; MacPhail, Catherine; Laeyendecker, Oliver; Hughes, James P.; Stein, Alan; Tollman, Stephen; Kahn, Kathleen

2018-01-01

Purpose Heightened sexual risk in adolescence and young adulthood may be partially explained by deficits in executive functioning, the set of cognitive processes used to make reasoned decisions. However, the association between executive function and sexual risk is understudied among adolescent girls and young women, particularly in low- and middle-income countries. Methods In a cohort of 853 young women age 18–25 in rural Mpumalanga province, South Africa, we evaluated executive function with three non-verbal cognitive tests: I. a rule-finding test, II. a trail-making test, and III. a figure drawing test. Using log-binomial regression models, we estimated the association between lower executive function test scores and indicators of sexual risk (unprotected sex acts, concurrent partnerships, transactional sex, and recent HSV-2 infection). Results In general, young women with lower executive function scores reported higher frequencies of sexual risk outcomes, though associations tended to be small with wide confidence intervals. Testing in the lowest quintile of Test I was associated with more unprotected sex [aPR (95% CI): 1.4 (1.0, 1.8)]. Testing in the lowest quintile of Test II was associated with more concurrent relationships and transactional sex [aPR (95% CI): 1.6 (1.1, 2.5) and 1.7 (1.3, 2.4), respectively], and testing in the lowest four quintiles of Test III was associated with more concurrent relationships [aPR (95% CI): 1.7 (1.0, 2.7)]. Conclusions These results demonstrate an association between low executive function and sexual risk in South African young women. Future work should seek to understand the nature of this association and whether there is promise in developing interventions to enhance executive function to reduce sexual risk. PMID:29608615

Clinical prediction rule for delayed hemothorax after minor thoracic injury: a multicentre derivation and validation study

PubMed Central

Émond, Marcel; Guimont, Chantal; Chauny, Jean-Marc; Daoust, Raoul; Bergeron, Éric; Vanier, Laurent; Moore, Lynne; Plourde, Miville; Kuimi, Batomen; Boucher, Valérie; Allain-Boulé, Nadine; Le Sage, Natalie

2017-01-01

Background: About 75% of patients with minor thoracic injury are discharged after an emergency department visit. However, complications such as delayed hemothorax can occur. We sought to derive and validate a clinical decision rule to predict hemothorax in patients discharged from the emergency department. Methods: We conducted a 6-year prospective cohort study in 4 university-affiliated emergency departments. Patients aged 16 years or older presenting with a minor thoracic injury were assessed at 5 time points (initial visit and 7, 14, 30 and 90 d after the injury). Radiologists' reports were reviewed for the presence of hemothorax. We used log-binomial regression models to identify predictors of hemothorax. Results: A total of 1382 patients were included: 830 in the derivation phase and 552 in the validation phase. Of these, 151 (10.9%) had hemothorax at the 14-day follow-up. Patients 65 years of age or older represented 25.3% (210/830) and 23.7% (131/552) of the derivation and validation cohorts, respectively. The final clinical decision rule included a combination of age (> 70 yr, 2 points; 45-70 yr, 1 point), fracture of any high to mid thorax rib (ribs 3-9, 2 points) and presence of 3 or more rib fractures (1 point). Twenty (30.8%) of the 65 high-risk patients (score ≥ 4) experienced hemothorax during the follow-up period. The clinical decision rule had a high specificity (90.7%, 95% confidence interval 87.7%-93.1%) in this high-risk group, thus guiding appropriate post-emergency care. Interpretation: One patient out of every 10 presented with delayed hemothorax after discharge from the emergency department. Implementation of this validated clinical decision rule for minor thoracic injury could guide emergency discharge plans. PMID:28611156

Unmetabolized Folic Acid, Tetrahydrofolate, and Colorectal Adenoma Risk.

PubMed

Rees, Judy R; Morris, Carolyn B; Peacock, Janet L; Ueland, Per M; Barry, Elizabeth L; McKeown-Eyssen, Gail E; Figueiredo, Jane C; Snover, Dale C; Baron, John A

2017-08-01

In a randomized trial of folic acid supplementation for the prevention of colorectal adenomas, we previously found indications of increased risk during later treatment and follow-up. This could have been due to the unmetabolized folic acid (UFA) or natural reduced and methylated folates (mF) to which it is metabolized. In post hoc analyses, we measured mF (the sum of 5-methyl-tetrahydrofolate and 4-alfa-hydroxy-5-methyl-THF) and UFA concentrations in the serum of 924 participants. Using binomial regression models with a log link, we assessed the associations between plasma mF or UFA and adenoma occurrence. We found no association between plasma mF or UFA and overall adenoma risk. However, during later follow-up, the prespecified, composite endpoint of high-risk findings (advanced or multiple adenomas) was positively associated with plasma mF ( P linear trend = 0.009), with a 58% increased risk for participants in the upper versus lowest quartile. An irregular association was seen with plasma UFA, with suggestions of an inverse trend ( P linear trend =0.049). A modest, significant inverse association was also seen between mF and risk of serrated lesions, with a 39% lower risk for upper versus lower quartile participants ( P linear trend = 0.03). In conclusion, during the later follow-up period in which folic acid supplementation was previously seen to increase the risk of advanced and multiple adenomas, higher serum mF was associated with a higher risk of multiple and/or advanced adenomas, but no clear indication that UFA played a direct role. There were indications that higher mF was associated with reduced risk of serrated polyps. Cancer Prev Res; 10(8); 451-8. ©2017 AACR . ©2017 American Association for Cancer Research.

Prevalence and risk factors for skin diseases among antiretroviral-naïve HIV-infected pregnant women in Dar es Salaam, Tanzania.

PubMed

Shayo, Grace A; Moshiro, Candida; Spiegelman, Donna; Mugusi, Ferdinand M; Chalamilla, Guerino; Msamanga, Gernard; Hawkins, Claudia; Fawzi, Wafaie

2014-10-01

Reduced cell-mediated immunity associated with pregnancy may cause a flaring or exacerbation of some skin conditions. Little is known about the magnitude of and risk factors for skin diseases among human immunodeficiency virus (HIV)-infected antiretroviral therapy-naïve pregnant women. Cross-sectional study of 1078 HIV-infected antiretroviral therapy-naïve pregnant women was conducted in Dar es Salaam, Tanzania. Skin diagnoses were mainly clinical. Log-binomial regression models were used to explore factors associated with the outcomes. About 84% of the women were in World Health Organization (WHO) HIV stage I. Median CD4(+) count was 405 × 10(6)  cells/l. The prevalence of any skin disease was 18%. Fungal infections (11%), genital ulcers (7%), and viral infections (5%) were the most common skin conditions. Skin infections were 2.64 times more common in HIV stage III (95% CI 1.51-4.62) compared to stage I. Fungal infections were 1.77 times common among single, divorced, and widowed women than among married women (95% CI 1.16-2.69), 2.8 times common among women in HIV stage III (95% CI 1.18-6.64) compared to stage I. Genital ulcers were significantly more common among women whose source of income was their own compared with those who got full support from partners, and among WHO HIV stage III disease compared to stage I. The burden of skin diseases was relatively low. Advanced HIV stage was associated with a range of skin conditions. CD4(+) cell count was not related to skin infection prevalence. © 2014 The International Society of Dermatology.

Social capital, tolerance of diversity and adherence to Mediterranean diet: the Rhea Mother-Child Cohort in Crete, Greece.

PubMed

Kritsotakis, George; Chatzi, Leda; Vassilaki, Maria; Georgiou, Vaggelis; Kogevinas, Manolis; Philalithis, Anastassios E; Koutis, Antonis

2015-05-01

To estimate the associations of individual maternal social capital and social capital dimensions (Participation in the Community, Feelings of Safety, Value of Life and Social Agency, Tolerance of Diversity) with adherence to the Mediterranean diet during pregnancy. This is a cross-sectional analysis of data from a prospective mother-child cohort (Rhea Study). Participants completed a social capital questionnaire and an FFQ in mid-pregnancy. Mediterranean diet adherence was evaluated through an a priori score ranging from 0 to 8 (minimal-maximal adherence). Maternal social capital scores were categorized into three groups: the upper 10 % was the high social capital group, the middle 80 % was the medium and the lowest 10 % was the low social capital group. Multivariable log-binomial and linear regression models adjusted for confounders were performed. Heraklion, Crete, Greece. A total of 377 women with singleton pregnancies. High maternal Total Social Capital was associated with an increase of almost 1 point in Mediterranean diet score (highest v. lowest group: β coefficient=0·95, 95 % CI 0·23, 1·68), after adjustment for confounders. Similar dose-response effects were noted for the scale Tolerance of Diversity (highest v. lowest group: adjusted β coefficient=1·08, 95 % CI 0·39, 1·77). Individual social capital and tolerance of diversity are associated with adherence to the Mediterranean diet in pregnancy. Women with higher social capital may exhibit a higher sense of obligation to themselves and to others that may lead to proactive nutrition-related activities. Less tolerant women may not provide the opportunity to new healthier, but unfamiliar, nutritional recommendations to become part of their regular diet.

Variation in symptoms of depression and anxiety in midlife women by menopausal status.

PubMed

Mulhall, Stephanie; Andel, Ross; Anstey, Kaarin J

2018-02-01

To examine the association between menopausal status and the risk of symptoms of depression and anxiety in a community-based sample of Australian midlife women. Female participants (mean age 50.6±1.5) who were premenopausal (n=237), perimenopausal (n=249) or naturally postmenopausal (n=225) were drawn from the Personality and Total Health (PATH) Through Life Project, a longitudinal study. Symptoms of depression and anxiety were measured using the Goldberg Depression Scale and Goldberg Anxiety Scale. Generalised linear regression models with a negative binomial log link were used. Relative to premenopause and after adjusting for all relevant covariates, being perimenopausal was associated with increased risk of greater symptoms of depression (incidence rate ratio [IRR]=1.29, p=0.001), while being postmenopausal was associated with increased risk of greater symptoms of anxiety (IRR=1.15, p=0.041). Being perimenopausal or postmenopausal was associated with an increased risk of greater symptoms of depression (IRR=1.35, p=0.008; IRR=1.31, p=0.029) and anxiety (IRR=1.22, p=0.030; IRR=1.32, p=0.006) in women without a history of probable major depressive disorder or generalised anxiety disorder. Risk of symptoms did not differ with menopausal status in women with this history. Menopausal status is associated with the risk of symptoms of depression and anxiety. There is a greater likelihood of increased symptoms of depression during perimenopause and symptoms of anxiety during postmenopause. In women without a history of depression or anxiety, the perimenopause and postmenopausal stages are associated with increased risk of greater symptoms of anxiety and depression relative to premenopause. Copyright © 2017 Elsevier B.V. All rights reserved.

Alcohol Use and Associations With Biological Markers and Self-Reported Indicators of Unprotected Sex in Human Immunodeficiency Virus-Positive Female Sex Workers in Mombasa, Kenya.

PubMed

White, Darcy; Wilson, Kate S; Masese, Linnet N; Wanje, George; Jaoko, Walter; Mandaliya, Kishorchandra; Richardson, Barbra A; Kinuthia, John; Simoni, Jane M; McClelland, R Scott

2016-10-01

Studies of alcohol use and sexual behavior in African populations have primarily been cross-sectional, used nonvalidated measures of alcohol use, or relied on self-reported sexual risk endpoints. Few have focused on human immunodeficiency virus (HIV)-positive women. Longitudinal data were collected from a cohort of HIV-positive Kenyan female sex workers. At enrollment and annual visits, participants were asked about past-year alcohol use using the Alcohol Use Disorders Identification Test (AUDIT). The primary endpoint was detection of prostate-specific antigen (PSA) in vaginal secretions at quarterly examinations. Associations between hazardous/harmful alcohol use (AUDIT score ≥7), PSA detection, and secondary measures of sexual risk were evaluated using generalized estimating equations with a log binomial regression model. A total of 405 women contributed 2750 vaginal samples over 606 person-years of follow-up. Hazardous/harmful alcohol use was reported at 16.6% of AUDIT assessments and was associated with higher risk of PSA detection (relative risk 1.50; 95% confidence interval, 1.11-2.01) relative to no alcohol use. This association was attenuated and no longer statistically significant, after adjusting for age, work venue, intimate partner violence, depression, and partnership status (adjusted relative risk, 1.13; 95% confidence interval, 0.82-1.56). In exploratory analyses, alcohol use was associated with self-report of unprotected sex and with sexually transmitted infection acquisition. Although hazardous/harmful alcohol use was not associated with detection of PSA in adjusted analysis, associations with secondary outcomes suggest that alcohol use is at least a marker of sexual risk behavior.

Occupational solvent exposure and cognition

PubMed Central

Sabbath, E.L.; Glymour, M.M.; Berr, C.; Singh-Manoux, A.; Zins, M.; Goldberg, M.

2012-01-01

Objective: Chronic occupational solvent exposure is associated with long-term cognitive deficits. Cognitive reserve may protect solvent-exposed workers from cognitive impairment. We tested whether the association between chronic solvent exposure and cognition varied by educational attainment, a proxy for cognitive reserve. Methods: Data were drawn from a prospective cohort of French national gas and electricity (GAZEL) employees (n = 4,134). Lifetime exposure to 4 solvent types (chlorinated solvents, petroleum solvents, benzene, and nonbenzene aromatic solvents) was assessed using a validated job-exposure matrix. Education was dichotomized at less than secondary school or below. Cognitive impairment was defined as scoring below the 25th percentile on the Digit Symbol Substitution Test at mean age 59 (SD 2.8; 88% of participants were retired at testing). Log-binomial regression was used to model risk ratios (RRs) for poor cognition as predicted by solvent exposure, stratified by education and adjusted for sociodemographic and behavioral factors. Results: Solvent exposure rates were higher among less-educated patients. Within this group, there was a dose-response relationship between lifetime exposure to each solvent type and RR for poor cognition (e.g., for high exposure to benzene, RR = 1.24, 95% confidence interval 1.09–1.41), with significant linear trends (p < 0.05) in 3 out of 4 solvent types. Recency of solvent exposure also predicted worse cognition among less-educated patients. Among those with secondary education or higher, there was no significant or near-significant relationship between any quantification of solvent exposure and cognition. Conclusions: Solvent exposure is associated with poor cognition only among less-educated individuals. Higher cognitive reserve in the more-educated group may explain this finding. PMID:22641403

Age-specific prevalence of human papilloma virus infection among Nigerian women.

PubMed

Akarolo-Anthony, Sally N; Famooto, Ayo O; Dareng, Eileen O; Olaniyan, Olayinka B; Offiong, Richard; Wheeler, Cosette M; Adebamowo, Clement A

2014-06-27

Inconsistent trends in HPV prevalence by age have been described in Africa. We examined the age prevalence pattern and distribution of 37 HPV-DNA types among urban Nigerian women. The study population was a sample of 278 women who presented to cervical cancer screening programs in Abuja, Nigeria, between April and August 2012. Using a nurse administered questionnaire, information on demographic characteristics and risk factors of cervical cancer was collected and samples of cervical exfoliated cells were obtained from all participants. Roche Linear Array HPV Genotyping Test® was used to characterize prevalent HPV and log-binomial regression models were used to examine the association between potential correlates and the prevalence of HPV infection. The mean age (SD) of the women enrolled was 38 (8) years. The overall prevalence of HPV was 37%. HPV 35 was the most prevalent HPV type in the study population. Among women age ≤ 30 years, 52% had HPV infection compared to 23% of those women who were older than 45 years (p = 0.006). We observed a significant linear association between age and the prevalence of HPV infections. The prevalence ratio (PR) and 95% confidence interval (CI) was 2.26 (1.17, 4.34) for any HPV infection, 3.83 (1.23, 11.94) for Group 1 HPV (definite carcinogens), and 2.19 (0.99, 4.84) for Group 2a or 2b HPV (probable or possible carcinogens) types, among women aged 18-30 years, compared to women who were older than 45 years. The prevalence of HPV infection was highest among younger women and decreased steadily with age among this population of urban Nigerian women.

Preterm birth time trends in Europe: a study of 19 countries.

PubMed

Zeitlin, J; Szamotulska, K; Drewniak, N; Mohangoo, A D; Chalmers, J; Sakkeus, L; Irgens, L; Gatt, M; Gissler, M; Blondel, B

2013-10-01

To investigate time trends in preterm birth in Europe by multiplicity, gestational age, and onset of delivery. Analysis of aggregate data from routine sources. Nineteen European countries. Live births in 1996, 2000, 2004, and 2008. Annual risk ratios of preterm birth in each country were estimated with year as a continuous variable for all births and by subgroup using log-binomial regression models. Overall preterm birth rate and rate by multiplicity, gestational age group, and spontaneous versus non-spontaneous (induced or prelabour caesarean section) onset of labour. Preterm birth rates rose in most countries, but the magnitude of these increases varied. Rises in the multiple birth rate as well as in the preterm birth rate for multiple births contributed to increases in the overall preterm birth rate. About half of countries experienced no change or decreases in the rates of singleton preterm birth. Where preterm birth rates rose, increases were no more prominent at 35-36 weeks of gestation than at 32-34 weeks of gestation. Variable trends were observed for spontaneous and non-spontaneous preterm births in the 13 countries with mode of onset data; increases were not solely attributed to non-spontaneous preterm births. There was a wide variation in preterm birth trends in European countries. Many countries maintained or reduced rates of singleton preterm birth over the past 15 years, challenging a widespread belief that rising rates are the norm. Understanding these cross-country differences could inform strategies for the prevention of preterm birth. © 2013 The Authors. BJOG: An International Journal of Obstetrics & Gynaecology published by John Wiley and Sons on behalf of the Royal College of Obstetricians and Gynaecologists.

Vaccine effectiveness of tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis vaccine during a pertussis outbreak in Maine.

PubMed

Terranella, Andrew; Rea, Vicki; Griffith, Matthew; Manning, Susan; Sears, Steven; Farmer, Ann; Martin, Stacey; Patel, Manisha

2016-05-11

Multiple school-associated pertussis outbreaks were reported in Maine from 2010 to 2011. These outbreaks were associated with an overall increase in pertussis cases statewide. Waning of protection in students recently vaccinated with tetanus, diphtheria, and acellular pertussis (Tdap) has been implicated in the increase in reported rates of pertussis nationally. We conducted a retrospective cohort study to evaluate Tdap vaccine effectiveness (VE) among students aged 11-19 years in two schools reporting outbreaks in 2011. All pertussis cases reported from August through November, 2011 at the two schools were included. Vaccination history was verified using provider information, state vaccine registry data, and parental verification. Attack rates (AR) were calculated. VE and duration of protection was calculated as VE=1-(ARvaccinated/ARunvaccinated)×100% using a log binomial regression model. Of 416 students enrolled, 314 were included in the analyses. Twenty-nine cases collectively in Schools A and B. Tdap coverage was 65% at School A and 42% at School B before the start of the outbreak. Among students enrolled in the study, attack rates were 11.9% and 7.7% at Schools A and B, respectively. Overall VE was 68.5% (95% confidence interval (CI) 37.7-86.2). VE was 70.4% (95% CI 17.5-89.4) for School A and 65.2% (95% CI -19.2 to 89.9) for School B. VE <2 years versus ≥2 years from outbreak onset was not significantly different. Tdap was moderately effective in preventing disease among vaccinated students. Vaccine coverage of 65% or less was suboptimal and might contribute to outbreaks. Waning VE was not demonstrated. Increased vaccination coverage rates as well as further evaluation of the role of acellular vaccine on VE is needed. Published by Elsevier Ltd.

The relationship between adiposity-associated inflammation and coronary artery and abdominal aortic calcium differs by strata of central adiposity: The Multi-Ethnic Study of Atherosclerosis (MESA).

PubMed

Hughes-Austin, Jan M; Wassel, Christina L; Jiménez, Jessica; Criqui, Michael H; Ix, Joachim H; Rasmussen-Torvik, Laura J; Budoff, Matthew J; Jenny, Nancy S; Allison, Matthew A

2014-08-01

Adipokines regulate metabolic processes linked to coronary artery (CAC) and abdominal aorta calcification (AAC). Because adipokine and other adiposity-associated inflammatory marker (AAIM) secretions differ between visceral and subcutaneous adipose tissue, we hypothesized that central adiposity modifies associations between AAIMs and CAC and AAC. We evaluated 1878 MESA participants with complete measures of AAIMs, anthropometry, CAC, and AAC. Associations of AAIMs with CAC and AAC prevalence and severity were analyzed per standard deviation of predictors (SD) using log binomial and linear regression models. The waist-to-hip ratio (WHR) was dichotomized at median WHR values based on sex/ethnicity. CAC and AAC prevalence were defined as any calcium (Agatston score >0). Severity was defined as ln (Agatston score). Analyses examined interactions with WHR and were adjusted for traditional cardiovascular disease risk factors. Each SD higher interleukin-6 (IL-6), fibrinogen and CRP was associated with 5% higher CAC prevalence; and each SD higher IL-6 and fibrinogen was associated with 4% higher AAC prevalence. Associations of IL-6 and fibrinogen with CAC severity, but not CAC prevalence, were significantly different among WHR strata. Median-and-above WHR: each SD higher IL-6 was associated with 24.8% higher CAC severity. Below-median WHR: no association (p interaction =0.012). Median-and-above WHR: each SD higher fibrinogen was associated with 19.6% higher CAC severity. Below-median WHR: no association (p interaction =0.034). Adiponectin, leptin, resistin, and tumor necrosis factor-alpha were not associated with CAC or AAC prevalence or severity. These results support findings that adiposity-associated inflammation is associated with arterial calcification, and further add that central adiposity may modify this association. © The Author(s) 2014.

Evaluating Iowa Severe Maternal Morbidity Trends and Maternal Risk Factors: 2009-2014.

PubMed

Frederiksen, Brittni N; Lillehoj, Catherine J; Kane, Debra J; Goodman, Dave; Rankin, Kristin

2017-09-01

Objectives To describe statewide SMM trends in Iowa from 2009 to 2014 and identify maternal characteristics associated with SMM, overall and by age group. Methods We used 2009-2014 linked Iowa birth certificate and hospital discharge data to calculate SMM based on a 25-condition definition and 24-condition definition. The 24-condition definition parallels the 25-condition definition, but excludes blood transfusions. We calculated SMM rates for all delivery hospitalizations (N = 196,788) using ICD-9-CM diagnosis and procedure codes. We used log-binomial regression to assess the association of SMM with maternal characteristics, overall and stratified by age groupings. Results In contrast to national rates, Iowa's 25-condition SMM rate decreased from 2009 to 2014. Based on the 25-condition definition, SMM rates were significantly higher among women <20 years and >34 years compared to women 25-34 years. Blood transfusion was the most prevalent indicator, with hysterectomy and disseminated intravascular coagulation (DIC) among the top five conditions. Based on the 24-condition definition, younger women had the lowest SMM rates and older women had the highest SMM rates. SMM rates were also significantly higher among racial/ethnic minorities compared to non-Hispanic white women. Payer was the only risk factor differentially associated with SMM across age groups. First trimester prenatal care initiation was protective for SMM in all models. Conclusions High rates of blood transfusion, hysterectomy, and DIC indicate a need to focus on reducing hemorrhage in Iowa. Both younger and older women and racial/ethnic minorities are identified as high risk groups for SMM that may benefit from special consideration and focus.

Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments

USGS Publications Warehouse

Dorazio, Robert; Hunter, Margaret

2015-01-01

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

A big data approach to the development of mixed-effects models for seizure count data.

PubMed

Tharayil, Joseph J; Chiang, Sharon; Moss, Robert; Stern, John M; Theodore, William H; Goldenholz, Daniel M

2017-05-01

Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy. Using data from SeizureTracker.com, a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies. For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day. The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Quantitative property-property relationship (QPPR) approach in predicting flotation efficiency of chelating agents as mineral collectors.

PubMed

Natarajan, R; Nirdosh, I; Venuvanalingam, P; Ramalingam, M

2002-07-01

The QPPR approach has been used to model cupferrons as mineral collectors. Separation efficiencies (Es) of these chelating agents have been correlated with property parameters namely, log P, log Koc, substituent-constant sigma, Mullikan and ESP derived charges using multiple regression analysis. Es of substituted-cupferrons in the flotation of a uranium ore could be predicted within experimental error either by log P or log Koc and an electronic parameter. However, when a halo, methoxy or phenyl substituent was in para to the chelating group, experimental Es was greater than the predicted values. Inclusion of a Boolean type indicative parameter improved significantly the predictability power. This approach has been extended to 2-aminothiophenols that were used to float a zinc ore and the correlations were found to be reasonably good.

Factors associated with the frequency of monitoring of liver enzymes, renal function and lipid laboratory markers among individuals initiating combination antiretroviral therapy: a cohort study.

PubMed

Gillis, Jennifer; Bayoumi, Ahmed M; Burchell, Ann N; Cooper, Curtis; Klein, Marina B; Loutfy, Mona; Machouf, Nima; Montaner, Julio Sg; Tsoukas, Chris; Hogg, Robert S; Raboud, Janet

2015-10-26

As the average age of the HIV-positive population increases, there is increasing need to monitor patients for the development of comorbidities as well as for drug toxicities. We examined factors associated with the frequency of measurement of liver enzymes, renal function tests, and lipid levels among participants of the Canadian Observational Cohort (CANOC) collaboration which follows people who initiated HIV antiretroviral therapy in 2000 or later. We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up. Generalized estimating equations with a logit link were used to examine factors associated with gaps of 12 months or more between measurements. Electronic laboratory data were available for 3940 of 7718 CANOC participants. The median duration of electronic follow-up was 3.5 years. The median (interquartile) rates of tests per year were 2.76 (1.60, 3.73), 2.55 (1.44, 3.38) and 1.42 (0.50, 2.52) for liver, renal and lipid parameters, respectively. In multivariable zero-inflated negative binomial regression models, individuals infected through injection drug use (IDU) were significantly less likely to have any measurements. Among participants with at least one measurement, rates of measurement of liver, renal and lipid tests were significantly lower for younger individuals and Aboriginal Peoples. Hepatitis C co-infected individuals with a history of IDU had lower rates of measurement and were at greater risk of having 12 month gaps between measurements. Hepatitis C co-infected participants infected through IDU were at increased risk of gaps in testing, despite publicly funded health care and increased risk of comorbid conditions. This should be taken into consideration in analyses examining factors associated with outcomes based on laboratory parameters.

Serum levels of the immune activation marker neopterin change with age and gender and are modified by race, BMI, and percentage of body fat.

PubMed

Spencer, Monique E; Jain, Alka; Matteini, Amy; Beamer, Brock A; Wang, Nae-Yuh; Leng, Sean X; Punjabi, Naresh M; Walston, Jeremy D; Fedarko, Neal S

2010-08-01

Neopterin, a GTP metabolite expressed by macrophages, is a marker of immune activation. We hypothesize that levels of this serum marker alter with donor age, reflecting increased chronic immune activation in normal aging. In addition to age, we assessed gender, race, body mass index (BMI), and percentage of body fat (%fat) as potential covariates. Serum was obtained from 426 healthy participants whose age ranged from 18 to 87 years. Anthropometric measures included %fat and BMI. Neopterin concentrations were measured by competitive ELISA. The paired associations between neopterin and age, BMI, or %fat were analyzed by Spearman's correlation or by linear regression of log-transformed neopterin, whereas overall associations were modeled by multiple regression of log-transformed neopterin as a function of age, gender, race, BMI, %fat, and interaction terms. Across all participants, neopterin exhibited a positive association with age, BMI, and %fat. Multiple regression modeling of neopterin in women and men as a function of age, BMI, and race revealed that each covariate contributed significantly to neopterin values and that optimal modeling required an interaction term between race and BMI. The covariate %fat was highly correlated with BMI and could be substituted for BMI to yield similar regression coefficients. The association of age and gender with neopterin levels and their modification by race, BMI, or %fat reflect the biology underlying chronic immune activation and perhaps gender differences in disease incidence, morbidity, and mortality.

Which Types of Televised Anti-Tobacco Campaigns Prompt More Quitline Calls from Disadvantaged Groups?

ERIC Educational Resources Information Center

Durkin, Sarah J.; Wakefield, Melanie A.; Spittal, Matthew J.

2011-01-01

To examine the efficacy of different types of mass media ads in driving lower socio-economic smokers (SES) to utilize quitlines. This study collected all 33 719 calls to the Victorian quitline in Australia over a 2-year period. Negative binomial regressions examined the relationship between weekly levels of exposure to different types of…

Distribution pattern of public transport passenger in Yogyakarta, Indonesia

NASA Astrophysics Data System (ADS)

Narendra, Alfa; Malkhamah, Siti; Sopha, Bertha Maya

2018-03-01

The arrival and departure distribution pattern of Trans Jogja bus passenger is one of the fundamental model for simulation. The purpose of this paper is to build models of passengers flows. This research used passengers data from January to May 2014. There is no policy that change the operation system affecting the nature of this pattern nowadays. The roads, buses, land uses, schedule, and people are relatively still the same. The data then categorized based on the direction, days, and location. Moreover, each category was fitted into some well-known discrete distributions. Those distributions are compared based on its AIC value and BIC. The chosen distribution model has the smallest AIC and BIC value and the negative binomial distribution found has the smallest AIC and BIC value. Probability mass function (PMF) plots of those models were compared to draw generic model from each categorical negative binomial distribution models. The value of accepted generic negative binomial distribution is 0.7064 and 1.4504 of mu. The minimum and maximum passenger vector value of distribution are is 0 and 41.

Child Schooling in Ethiopia: The Role of Maternal Autonomy.

PubMed

Gebremedhin, Tesfaye Alemayehu; Mohanty, Itismita

2016-01-01

This paper examines the effects of maternal autonomy on child schooling outcomes in Ethiopia using a nationally representative Ethiopian Demographic and Health survey for 2011. The empirical strategy uses a Hurdle Negative Binomial Regression model to estimate years of schooling. An ordered probit model is also estimated to examine age grade distortion using a trichotomous dependent variable that captures three states of child schooling. The large sample size and the range of questions available in this dataset allow us to explore the influence of individual and household level social, economic and cultural factors on child schooling. The analysis finds statistically significant effects of maternal autonomy variables on child schooling in Ethiopia. The roles of maternal autonomy and other household-level factors on child schooling are important issues in Ethiopia, where health and education outcomes are poor for large segments of the population.

The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles.

PubMed

Wall, Stephen P; Lee, David C; Frangos, Spiros G; Sethi, Monica; Heyer, Jessica H; Ayoung-Chee, Patricia; DiMaggio, Charles J

2016-01-01

We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

PubMed

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).

Recurrent suicide attempts in patients with depressive and anxiety disorders: the role of borderline personality traits.

PubMed

Stringer, Barbara; van Meijel, Berno; Eikelenboom, Merijn; Koekkoek, Bauke; Licht, Carmilla M M; Kerkhof, Ad J F M; Penninx, Brenda W J H; Beekman, Aartjan T F

2013-10-01

The presence of a comorbid borderline personality disorder (BPD) may be associated with an increase of suicidal behaviors in patients with depressive and anxiety disorders. The aim of this study is to examine the role of borderline personality traits on recurrent suicide attempts. The Netherlands Study on Depression and Anxiety included 1838 respondents with lifetime depressive and/or anxiety disorders, of whom 309 reported at least one previous suicide attempt. A univariable negative binomial regression analysis was performed to examine the association between comorbid borderline personality traits and suicide attempts. Univariable and multivariable negative binomial regression analyses were performed to identify risk factors for the number of recurrent suicide attempts in four clusters (type and severity of axis-I disorders, BPD traits, determinants of suicide attempts and socio-demographics). In the total sample the suicide attempt rate ratio increased with 33% for every unit increase in BPD traits. A lifetime diagnosis of dysthymia and comorbid BPD traits, especially the symptoms anger and fights, were independently and significantly associated with recurrent suicide attempts in the final model (n=309). The screening of personality disorders was added to the NESDA assessments at the 4-year follow-up for the first time. Therefore we were not able to examine the influence of comorbid BPD traits on suicide attempts over time. Persons with a lifetime diagnosis of dysthymia combined with borderline personality traits especially difficulties in coping with anger seemed to be at high risk for recurrent suicide attempts. For clinical practice, it is recommended to screen for comorbid borderline personality traits and to strengthen the patient's coping skills with regard to anger. © 2013 Elsevier B.V. All rights reserved.

Homicide mortality rates in Canada, 2000-2009: Youth at increased risk.

PubMed

Basham, C Andrew; Snider, Carolyn

2016-10-20

To estimate and compare Canadian homicide mortality rates (HMRs) and trends in HMRs across age groups, with a focus on trends for youth. Data for the period of 2000 to 2009 were collected from Statistics Canada's CANSIM (Canadian Statistical Information Management) Table 102-0540 with the following ICD-10-CA coded external causes of death: X85 to Y09 (assault) and Y87.1 (sequelae of assault). Annual population counts from 2000 to 2009 were obtained from Statistics Canada's CANSIM Table 051-0001. Both death and population counts were organized into five-year age groups. A random effects negative binomial regression analysis was conducted to estimate age group-specific rates, rate ratios, and trends in homicide mortality. There were 9,878 homicide deaths in Canada during the study period. The increase in the overall homicide mortality rate (HMR) of 0.3% per year was not statistically significant (95% CI: -1.1% to +1.8%). Canadians aged 15-19 years and 20-24 years had the highest HMRs during the study period, and experienced statistically significant annual increases in their HMRs of 3% and 4% respectively (p < 0.05). A general, though not statistically significant, decrease in the HMR was observed for all age groups 50+ years. A fixed effects negative binomial regression model showed that the HMR for males was higher than for females over the study period [RRfemale/male = 0.473 (95% CI: 0.361, 0.621)], but no significant difference in sex-specific trends in the HMR was found. An increasing risk of homicide mortality was identified among Canadian youth, ages 15-24, over the 10-year study period. Research that seeks to understand the reasons for the increased homicide risk facing Canada's youth, and public policy responses to reduce this risk, are warranted.

Endogenous Sex Steroid Hormones, Lipid Subfractions, and Ectopic Adiposity in Asian Indians.

PubMed

Kim, Catherine; Kong, Shengchun; Krauss, Ronald M; Stanczyk, Frank Z; Reddy, Srinivasa T; Needham, Belinda L; Kanaya, Alka M

2015-12-01

Estradiol, testosterone (T), and sex hormone binding globulin (SHBG) levels are associated with lipid subfractions in men and women. Our objective was to determine if associations are independent from adipose tissue area among Asian Indians. We used data from 42 women and 57 Asian Indian men who did not use exogenous steroids or lipid-lowering medications. Lipoprotein subfractions including low-density lipoprotein cholesterol (LDL), very low-density lipoprotein cholesterol (VLDL), and intermediate density lipoprotein (IDL) were assessed by ion mobility spectrometry. Intra-abdominal adiposity was assessed by computed tomography. Multivariable regression models estimated the association between sex hormones with lipoprotein subfractions before and after adjustment for adiposity. Among women, lower logSHBG levels were associated with smaller logLDL particle size and higher logtriglycerides, logVLDL, and logIDL, although these associations were attenuated with adjustment for visceral adiposity in particular. Among women, lower logSHBG levels was significantly associated with lower logmedium LDL and logsmall LDL concentrations even after consideration of visceral and hepatic adiposity and insulin resistance as represented by the homeostasis model assessment of insulin resistance (HOMA-IR). Among men, lower logSHBG was also associated with smaller logLDL peak diameter size and higher logtriglycerides and logVLDL, even after adjustment for HOMA-IR and adiposity. Relationships between sex steroids and lipid subfractions were not significant among women. Among men, higher total testosterone was associated with higher logHDL and logLDL particle size, and lower logtriglycerides and logVLDL, but these associations were partially attenuated with adjustment for adiposity and HOMA-IR. Among Asian Indians, SHBG is associated with more favorable lipid subfraction concentrations, independent of hepatic and visceral fat.

Partitioning Detectability Components in Populations Subject to Within-Season Temporary Emigration Using Binomial Mixture Models

PubMed Central

O’Donnell, Katherine M.; Thompson, Frank R.; Semlitsch, Raymond D.

2015-01-01

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model’s potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3–5 surveys each spring and fall 2010–2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability. PMID:25775182

Background stratified Poisson regression analysis of cohort data.

PubMed

Richardson, David B; Langholz, Bryan

2012-03-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

Prevalence and Correlates of Smoking among Low-Income Adults Residing in New York City Public Housing Developments-2015.

PubMed

Feinberg, A; Lopez, P M; Wyka, K; Islam, N; Seidl, L; Drackett, E; Mata, A; Pinzon, J; Baker, M R; Lopez, J; Trinh-Shevrin, C; Shelley, D; Bailey, Z; Maybank, K A; Thorpe, L E

2017-08-01

To guide targeted cessation and prevention programming, this study assessed smoking prevalence and described sociodemographic, health, and healthcare use characteristics of adult smokers in public housing. Self-reported data were analyzed from a random sample of 1664 residents aged 35 and older in ten New York City public housing developments in East/Central Harlem. Smoking prevalence was 20.8%. Weighted log-binomial models identified to be having Medicaid, not having a personal doctor, and using health clinics for routine care were positively associated with smoking. Smokers without a personal doctor were less likely to receive provider quit advice. While most smokers in these public housing developments had health insurance, a personal doctor, and received provider cessation advice in the last year (72.4%), persistently high smoking rates suggest that such cessation advice may be insufficient. Efforts to eliminate differences in tobacco use should consider place-based smoking cessation interventions that extend cessation support beyond clinical settings.

Weibull mixture regression for marginal inference in zero-heavy continuous outcomes.

PubMed

Gebregziabher, Mulugeta; Voronca, Delia; Teklehaimanot, Abeba; Santa Ana, Elizabeth J

2017-06-01

Continuous outcomes with preponderance of zero values are ubiquitous in data that arise from biomedical studies, for example studies of addictive disorders. This is known to lead to violation of standard assumptions in parametric inference and enhances the risk of misleading conclusions unless managed properly. Two-part models are commonly used to deal with this problem. However, standard two-part models have limitations with respect to obtaining parameter estimates that have marginal interpretation of covariate effects which are important in many biomedical applications. Recently marginalized two-part models are proposed but their development is limited to log-normal and log-skew-normal distributions. Thus, in this paper, we propose a finite mixture approach, with Weibull mixture regression as a special case, to deal with the problem. We use extensive simulation study to assess the performance of the proposed model in finite samples and to make comparisons with other family of models via statistical information and mean squared error criteria. We demonstrate its application on real data from a randomized controlled trial of addictive disorders. Our results show that a two-component Weibull mixture model is preferred for modeling zero-heavy continuous data when the non-zero part are simulated from Weibull or similar distributions such as Gamma or truncated Gauss.

Quantitative prediction of ionization effect on human skin permeability.

PubMed

Baba, Hiromi; Ueno, Yusuke; Hashida, Mitsuru; Yamashita, Fumiyoshi

2017-04-30

Although skin permeability of an active ingredient can be severely affected by its ionization in a dose solution, most of the existing prediction models cannot predict such impacts. To provide reliable predictors, we curated a novel large dataset of in vitro human skin permeability coefficients for 322 entries comprising chemically diverse permeants whose ionization fractions can be calculated. Subsequently, we generated thousands of computational descriptors, including LogD (octanol-water distribution coefficient at a specific pH), and analyzed the dataset using nonlinear support vector regression (SVR) and Gaussian process regression (GPR) combined with greedy descriptor selection. The SVR model was slightly superior to the GPR model, with externally validated squared correlation coefficient, root mean square error, and mean absolute error values of 0.94, 0.29, and 0.21, respectively. These models indicate that Log D is effective for a comprehensive prediction of ionization effects on skin permeability. In addition, the proposed models satisfied the statistical criteria endorsed in recent model validation studies. These models can evaluate virtually generated compounds at any pH; therefore, they can be used for high-throughput evaluations of numerous active ingredients and optimization of their skin permeability with respect to permeant ionization. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling recall memory for emotional objects in Alzheimer's disease.

PubMed

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p < .003). EM was not found for recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p < .014) and object status (p < .0001) as gift or non-gift. Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

I Remember You: Independence and the Binomial Model

ERIC Educational Resources Information Center

Levine, Douglas W.; Rockhill, Beverly

2006-01-01

We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how…

Analysis of multiple tank car releases in train accidents.

PubMed

Liu, Xiang; Liu, Chang; Hong, Yili

2017-10-01

There are annually over two million carloads of hazardous materials transported by rail in the United States. The American railroads use large blocks of tank cars to transport petroleum crude oil and other flammable liquids from production to consumption sites. Being different from roadway transport of hazardous materials, a train accident can potentially result in the derailment and release of multiple tank cars, which may result in significant consequences. The prior literature predominantly assumes that the occurrence of multiple tank car releases in a train accident is a series of independent Bernoulli processes, and thus uses the binomial distribution to estimate the total number of tank car releases given the number of tank cars derailing or damaged. This paper shows that the traditional binomial model can incorrectly estimate multiple tank car release probability by magnitudes in certain circumstances, thereby significantly affecting railroad safety and risk analysis. To bridge this knowledge gap, this paper proposes a novel, alternative Correlated Binomial (CB) model that accounts for the possible correlations of multiple tank car releases in the same train. We test three distinct correlation structures in the CB model, and find that they all outperform the conventional binomial model based on empirical tank car accident data. The analysis shows that considering tank car release correlations would result in a significantly improved fit of the empirical data than otherwise. Consequently, it is prudent to consider alternative modeling techniques when analyzing the probability of multiple tank car releases in railroad accidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of octanol/water partition coefficients using LSER parameters

USGS Publications Warehouse

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

A randomized trial of maternal influenza immunization decision-making: A test of persuasive messaging models.

PubMed

Frew, Paula M; Kriss, Jennifer L; Chamberlain, Allison T; Malik, Fauzia; Chung, Yunmi; Cortés, Marielysse; Omer, Saad B

2016-08-02

We sought to examine the effectiveness of persuasive communication interventions on influenza vaccination uptake among black/African American pregnant women in Atlanta, Georgia. We recruited black/African American pregnant women ages 18 to 50 y from Atlanta, GA to participate in a prospective, randomized controlled trial of influenza immunization messaging conducted from January to April 2013. Eligible participants were randomized to 3 study arms. We conducted follow-up questionnaires on influenza immunization at 30-days post-partum with all groups. Chi-square and t tests evaluated group differences, and outcome intention-to-treat assessment utilized log-binomial regression models. Of the 106 enrolled, 95 women completed the study (90% retention), of which 31 were randomly assigned to affective messaging intervention ("Pregnant Pause" video), 30 to cognitive messaging intervention ("Vaccines for a Healthy Pregnancy" video), and 34 to a comparison condition (receipt of the Influenza Vaccine Information Statement). The three groups were balanced on baseline demographic characteristics and reported health behaviors. At baseline, most women (63%, n = 60) reported no receipt of seasonal influenza immunization during the previous 5 y. They expressed a low likelihood (2.1 ± 2.8 on 0-10 scale) of obtaining influenza immunization during their current pregnancy. At 30-days postpartum follow-up, influenza immunization was low among all participants (7-13%) demonstrating no effect after a single exposure to either affective messaging (RR = 1.10; 95% CI: 0.30-4.01) or cognitive messaging interventions (RR = 0.57; 95% CI: 0.11-2.88). Women cited various reasons for not obtaining maternal influenza immunizations. These included concern about vaccine harm (47%, n = 40), low perceived influenza infection risk (31%, n = 26), and a history of immunization nonreceipt (24%, n = 20). The findings reflect the limitations associated with a single exposure to varying maternal influenza immunization message approaches on vaccine behavior. For this population, repeated influenza immunization exposures may be warranted with alterations in message format, content, and relevance for coverage improvement.

The Impact of Integrated Infant and Young Child Feeding and Micronutrient Powder Intervention on Feeding Practices and Anemia in Children Aged 6-23 Months in Madagascar.

PubMed

Locks, Lindsey M; Reerink, Ietje; Tucker Brown, Amal; Gnegne, Smaila; Ramalanjaona, Noelimanjaka; Nanama, Simeon; Duggan, Christopher P; Garg, Aashima

2017-06-07

This study assesses the impact of an integrated infant and young child feeding (IYCF) and micronutrient powder (MNP) intervention on children's risk of anemia and IYCF practices in Madagascar. Quantitative baseline and endline surveys were conducted in representative households with children 6-23 months from two districts, where an 18-month IYCF-MNP intervention was implemented. Relative risks comparing children's risk of anemia and maternal IYCF knowledge and practices at baseline versus endline, and also at endline among MNP-users versus non-users were estimated using log-binomial regression models. 372 and 475 children aged 6-23 months were assessed at baseline and endline respectively. Prevalence of anemia fell from 75.3% to 64.9% from baseline to endline ( p = 0.002); the reduction in the risk of anemia remained significant in models adjusting for sociodemographic characteristics (ARR (95% CI): 0.86 (0.78, 0.95), p = 0.003). In endline assessments, 229 out of 474 (48.3%) of children had consumed MNPs. MNP-users had a lower risk of anemia (ARR (95% CI): 0.86 (0.74, 0.99), p = 0.04) than non-users, after controlling for child's dietary diversity and morbidity, maternal counseling by community-health-workers, and sociodemographic characteristics. Mothers interviewed at endline also had greater nutrition knowledge and were more likely to feed their children ≥4 food groups (ARR (95% CI): 2.92 (2.24, 3.80), p < 0.001), and the minimum acceptable diet (ARR (95% CI): 2.88 (2.17, 3.82), p < 0.001) than mothers interviewed at baseline. Integration of MNP into IYCF interventions is a viable strategy for improving children's consumption of micronutrients and reducing risk of anemia. The addition of MNP does not negatively impact, and may improve, IYCF practices.

A school based cluster randomised health education intervention trial for improving knowledge and attitudes related to Taenia solium cysticercosis and taeniasis in Mbulu district, northern Tanzania.

PubMed

Mwidunda, Sylvester A; Carabin, Hélène; Matuja, William B M; Winkler, Andrea S; Ngowi, Helena A

2015-01-01

Taenia solium causes significant economic and public health impacts in endemic countries. This study determined effectiveness of a health education intervention at improving school children's knowledge and attitudes related to T. solium cysticercosis and taeniasis in Tanzania. A cluster randomised controlled health education intervention trial was conducted in 60 schools (30 primary, 30 secondary) in Mbulu district. Baseline data were collected using a structured questionnaire in the 60 schools and group discussions in three other schools. The 60 schools stratified by baseline knowledge were randomised to receive the intervention or serve as control. The health education consisted of an address by a trained teacher, a video show and a leaflet given to each pupil. Two post-intervention re-assessments (immediately and 6 months post-intervention) were conducted in all schools and the third (12 months post-intervention) was conducted in 28 secondary schools. Data were analysed using Bayesian hierarchical log-binomial models for individual knowledge and attitude questions and Bayesian hierarchical linear regression models for scores. The overall score (percentage of correct answers) improved by about 10% in all schools after 6 months, but was slightly lower among secondary schools. Monitoring alone was associated with improvement in scores by about 6%. The intervention was linked to improvements in knowledge regarding taeniasis, porcine cysticercosis, human cysticercosis, epilepsy, the attitude of condemning infected meat but it reduced the attitude of contacting a veterinarian if a pig was found to be infected with cysticercosis. Monitoring alone was linked to an improvement in how best to raise pigs. This study demonstrates the potential value of school children as targets for health messages to control T. solium cysticercosis and taeniasis in endemic areas. Studies are needed to assess effectiveness of message transmission from children to parents and the general community and their impacts in improving behaviours facilitating disease transmission.

A School Based Cluster Randomised Health Education Intervention Trial for Improving Knowledge and Attitudes Related to Taenia solium Cysticercosis and Taeniasis in Mbulu District, Northern Tanzania

PubMed Central

Mwidunda, Sylvester A.; Carabin, Hélène; Matuja, William B. M.; Winkler, Andrea S.; Ngowi, Helena A.

2015-01-01

Taenia solium causes significant economic and public health impacts in endemic countries. This study determined effectiveness of a health education intervention at improving school children’s knowledge and attitudes related to T. solium cysticercosis and taeniasis in Tanzania. A cluster randomised controlled health education intervention trial was conducted in 60 schools (30 primary, 30 secondary) in Mbulu district. Baseline data were collected using a structured questionnaire in the 60 schools and group discussions in three other schools. The 60 schools stratified by baseline knowledge were randomised to receive the intervention or serve as control. The health education consisted of an address by a trained teacher, a video show and a leaflet given to each pupil. Two post-intervention re-assessments (immediately and 6 months post-intervention) were conducted in all schools and the third (12 months post-intervention) was conducted in 28 secondary schools. Data were analysed using Bayesian hierarchical log-binomial models for individual knowledge and attitude questions and Bayesian hierarchical linear regression models for scores. The overall score (percentage of correct answers) improved by about 10% in all schools after 6 months, but was slightly lower among secondary schools. Monitoring alone was associated with improvement in scores by about 6%. The intervention was linked to improvements in knowledge regarding taeniasis, porcine cysticercosis, human cysticercosis, epilepsy, the attitude of condemning infected meat but it reduced the attitude of contacting a veterinarian if a pig was found to be infected with cysticercosis. Monitoring alone was linked to an improvement in how best to raise pigs. This study demonstrates the potential value of school children as targets for health messages to control T. solium cysticercosis and taeniasis in endemic areas. Studies are needed to assess effectiveness of message transmission from children to parents and the general community and their impacts in improving behaviours facilitating disease transmission. PMID:25719902

Dental enamel defects predict adolescent health indicators: A cohort study among the Tsimane' of Bolivia.

PubMed

Masterson, Erin E; Fitzpatrick, Annette L; Enquobahrie, Daniel A; Mancl, Lloyd A; Eisenberg, Dan T A; Conde, Esther; Hujoel, Philippe P

2018-05-01

Bioarchaeological findings have linked defective enamel formation in preadulthood with adult mortality. We investigated how defective enamel formation in infancy and childhood is associated with risk factors for adult morbidity and mortality in adolescents. This cohort study of 349 Amerindian adolescents (10-17 years of age) related extent of enamel defects on the central maxillary incisors (none, less than 1/3, 1/3 to 2/3, more than 2/3) to adolescent anthropometrics (height, weight) and biomarkers (hemoglobin, glycated hemoglobin, white blood cell count, and blood pressure). Risk differences and 95% confidence intervals were estimated using multiple linear regression. Enamel defects and stunted growth were compared in their ability to predict adolescent health indicators using log-binomial regression and receiver operating characteristics (ROCs). Greater extent of defective enamel formation on the tooth surface was associated with shorter height (-1.35 cm, 95% CI: -2.17, -0.53), lower weight (-0.98 kg, 95% CI: -1.70, -0.26), lower hemoglobin (-0.36 g/dL, 95% CI: -0.59, -0.13), lower glycated hemoglobin (-0.04 %A 1c , 95% CI: -0.08, -0.00008), and higher white blood cell count (0.74 10 9 /L, 95% CI: 0.35, 1.14) in adolescence. Extent of enamel defects and stunted growth independently performed similarly as risk factors for adverse adolescent outcomes, including anemia, prediabetes/type II diabetes, elevated WBC count, prehypertension/hypertension, and metabolic health. Defective enamel formation in infancy and childhood predicted adolescent health outcomes and may be primarily associated with infection. Extent of enamel defects and stunted growth may be equally predictive of adverse adolescent health outcomes. © 2018 Wiley Periodicals, Inc.

Reactivation of Herpes Simplex Virus Type 2 After Initiation of Antiretroviral Therapy

PubMed Central

Tobian, Aaron A. R.; Grabowski, Mary K.; Serwadda, David; Newell, Kevin; Ssebbowa, Paschal; Franco, Veronica; Nalugoda, Fred; Wawer, Maria J.; Gray, Ronald H.; Quinn, Thomas C.; Reynolds, Steven J.

2013-01-01

Background. The association between initiation of antiretroviral therapy (ART) for human immunodeficiency virus (HIV) infection and possible herpes simplex virus type 2 (HSV-2) shedding and genital ulcer disease (GUD) has not been evaluated. Methods. GUD and vaginal HSV-2 shedding were evaluated among women coinfected with HIV and HSV-2 (n = 440 for GUD and n = 96 for HSV-2 shedding) who began ART while enrolled in a placebo-controlled trial of HSV-2 suppression with acyclovir in Rakai, Uganda. Monthly vaginal swabs were tested for HSV-2 shedding, using a real-time quantitative polymerase chain reaction assay. Prevalence risk ratios (PRRs) of GUD were estimated using log binomial regression. Random effects logistic regression was used to estimate odds ratios (ORs) of HSV-2 shedding. Results. Compared with pre-ART values, GUD prevalence increased significantly within the first 3 months after ART initiation (adjusted PRR, 1.94; 95% confidence interval [CI], 1.04–3.62) and returned to baseline after 6 months of ART (adjusted PRR, 0.80; 95% CI, .35–1.80). Detection of HSV-2 shedding was highest in the first 3 months after ART initiation (adjusted OR, 2.58; 95% CI, 1.48–4.49). HSV-2 shedding was significantly less common among women receiving acyclovir (adjusted OR, 0.13; 95% CI, .04–.41). Conclusions. The prevalence of HSV-2 shedding and GUD increased significantly after ART initiation, possibly because of immune reconstitution inflammatory syndrome. Acyclovir significantly reduced both GUD and HSV-2 shedding and should be considered to mitigate these effects following ART initiation. PMID:23812240

High Rates of Exclusive Breastfeeding in Both Arms of a Peer Counseling Study Promoting EBF Among HIV-Infected Kenyan Women.

PubMed

Bosire, Rose; Betz, Bourke; Aluisio, Adam; Hughes, James P; Nduati, Ruth; Kiarie, James; Chohan, Bhavna H; Merkel, Michele; Lohman-Payne, Barbara; John-Stewart, Grace; Farquhar, Carey

2016-03-01

Exclusive breastfeeding (EBF) is recommended for 6 months after delivery as the optimal infant feeding method and is especially important for prevention of mother-to-child HIV transmission (PMTCT). However, EBF promotion efforts among HIV-infected mothers in sub-Saharan Africa have achieved mixed success and require context-specific interventions. HIV-positive, pregnant women from six clinics in Nairobi were enrolled into a clinic-level, before-after counseling intervention study. All women received standard perinatal and HIV care. Women in the intervention arm were offered three counseling sessions that promoted EBF, described its benefits, and explained breastfeeding techniques. Mother-infant pairs were followed until 14 weeks postpartum, with infant HIV testing at 6 weeks. EBF prevalence at 14 weeks postpartum was compared between study arms using log-binomial regression. Proportions of 6-week HIV-free survival and 14-week infant survival were assessed using Cox regression. Risk estimates were adjusted for clinic, relationship status, and antiretroviral therapy. Between 2009 and 2013, 833 women were enrolled of whom 94% planned to practice EBF for 6 months and 95% were taking therapeutic or prophylactic antiretrovirals. Median age was 27 years; median CD4 count was 403 cells/μL. EBF prevalence at 14 weeks postpartum was 86% in the control and 81% in the intervention group (p = 0.19). No differences were observed between groups for 6-week HIV-free survival and 14-week infant survival. Women who received breastfeeding counseling were not more likely to breastfeed exclusively, in part due to high overall EBF prevalence in this study population. The high EBF prevalence is an important finding, given recent efforts to promote EBF in Kenya.

A comparison of resource utilization following chemotherapy for acute myeloid leukemia in children discharged versus children that remain hospitalized during neutropenia

PubMed Central

Getz, Kelly D; Miller, Tamara P; Seif, Alix E; Li, Yimei; Huang, Yuan-Shung; Bagatell, Rochelle; Fisher, Brian T; Aplenc, Richard

2015-01-01

Comparisons of early discharge and outpatient postchemotherapy supportive care in pediatric acute myeloid leukemia (AML) patients are limited. We used data from the Pediatric Health Information System on a cohort of children treated for newly diagnosed AML to compare course-specific mortality and resource utilization in patients who were discharged after chemotherapy to outpatient management during neutropenia relative to patients who remained hospitalized. Patients were categorized at each course as early or standard discharge. Discharges within 3 days after chemotherapy completion were considered “early”. Resource utilization was determined based on daily billing data and reported as days of use per 1000 hospital days. Inpatient mortality, occurrence of intensive care unit (ICU)-level care, and duration of hospitalization were compared using logistic, log-binomial and linear regression methods, respectively. Poisson regression with inpatient days as offset was used to compare resource use by discharge status. The study population included 996 patients contributing 2358 treatment courses. Fewer patients were discharged early following Induction I (7%) than subsequent courses (22–24%). Across courses, patients discharged early experienced high readmission rates (69–84%), yet 9–12 fewer inpatient days (all P < 0.001). Inpatient mortality was low across courses and did not differ significantly by discharge status. The overall risk for ICU-level care was 116% higher for early compared to standard discharge patients (adjusted risk ratio: 2.16, 95% confidence interval: 1.50, 3.11). Rates of antibiotic, vasopressor, and supplemental oxygen use were consistently elevated for early discharge patients. Despite similar inpatient mortality to standard discharge patients, early discharge patients may be at greater risk for life-threatening chemotherapy-related complications, including infections. PMID:26105201

The influence of marital status on the stage at diagnosis, treatment, and survival of adult patients with gastric cancer: a population-based study.

PubMed

Zhang, Jieyun; Gan, Lu; Wu, Zhenhua; Yan, Shican; Liu, Xiyu; Guo, Weijian

2017-04-04

Marital status was reported as a prognostic factor in many cancers. However, its role in gastric cancer (GC) hasn't been thoroughly explored. In this study, we aimed to investigate the effect of marital status on survival, stage, treatment, and survival in subgroups. We used the Surveillance, Epidemiology and End Results (SEER) database and identified 16910 GC patients. These patients were categorized into married (58.44%) and unmarred (41.56%) groups. Pearson chi-square, Wilcoxon-Mann-Whitney, Log-rank, multivariate Cox regression, univariate and multivariate binomial or multinomial logistic regression analysis were used in our analysis. Subgroup analyses of married versus unmarried patients were summarized in a forest plot. Married patients had better 5-year overall survival (OS) (32.09% VS 24.61%, P<0.001) and 5-year cancer-caused special survival (CSS) (37.74% VS 32.79%, P<0.001) than unmarried ones. Then we studied several underlying mechanisms. Firstly, married patients weren't in earlier stage at diagnosis (P=0.159). Secondly, married patients were more likely to receive surgery (P < 0.001) or radiotherapy (P < 0.001) compared with the unmarried. Thirdly, in subgroup analyses, married patients still had survival advantage in subgroups with stage II-IV and no radiotherapy. These results showed that marital status was an independently prognostic factor for both OS and CSS in GC patients. Undertreatment and lack of social support in unmarried patients were potential explanations. With the knowledge of heterogeneous effects of marriage in subgroups, we can target unmarried patients with better social support, especially who are diagnosed at late stage and undergo no treatment.

The influence of marital status on the stage at diagnosis, treatment, and survival of adult patients with gastric cancer: a population-based study

PubMed Central

Yan, Shican; Liu, Xiyu; Guo, Weijian

2017-01-01

Background & Aims Marital status was reported as a prognostic factor in many cancers. However, its role in gastric cancer (GC) hasn't been thoroughly explored. In this study, we aimed to investigate the effect of marital status on survival, stage, treatment, and survival in subgroups. Methods We used the Surveillance, Epidemiology and End Results (SEER) database and identified 16910 GC patients. These patients were categorized into married (58.44%) and unmarred (41.56%) groups. Pearson chi-square, Wilcoxon-Mann-Whitney, Log-rank, multivariate Cox regression, univariate and multivariate binomial or multinomial logistic regression analysis were used in our analysis. Subgroup analyses of married versus unmarried patients were summarized in a forest plot. Results Married patients had better 5-year overall survival (OS) (32.09% VS 24.61%, P<0.001) and 5-year cancer-caused special survival (CSS) (37.74% VS 32.79%, P<0.001) than unmarried ones. Then we studied several underlying mechanisms. Firstly, married patients weren't in earlier stage at diagnosis (P=0.159). Secondly, married patients were more likely to receive surgery (P < 0.001) or radiotherapy (P < 0.001) compared with the unmarried. Thirdly, in subgroup analyses, married patients still had survival advantage in subgroups with stage II-IV and no radiotherapy. Conclusions These results showed that marital status was an independently prognostic factor for both OS and CSS in GC patients. Undertreatment and lack of social support in unmarried patients were potential explanations. With the knowledge of heterogeneous effects of marriage in subgroups, we can target unmarried patients with better social support, especially who are diagnosed at late stage and undergo no treatment. PMID:26894860

National Trends in Emergency Room Visits of Dialysis Patients for Adverse Drug Reactions.

PubMed

Chan, Lili; Saha, Aparna; Poojary, Priti; Chauhan, Kinsuk; Naik, Nidhi; Coca, Steven; Garimella, Pranav S; Nadkarni, Girish N

2018-06-12

Various medications are cleared by the kidneys, therefore patients with impaired renal function, especially dialysis patients are at risk for adverse drug events (ADEs). There are limited studies on ADEs in maintenance dialysis patients. We utilized a nationally representative database, the Nationwide Emergency Department Sample, from 2008 to 2013, to compare emergency department (ED) visits for dialysis and propensity matched non-dialysis patients. Log binomial regression was used to calculate relative risk of hospital admission and logistic regression to calculate ORs for in-hospital mortality while adjusting for patient and hospital characteristics. While ED visits for ADEs decreased in both groups, they were over 10-fold higher in dialysis patients than non-dialysis patients (65.8-88.5 per 1,000 patients vs. 4.6-5.4 per 1,000 patients respectively, p < 0.001). The top medication category associated with ED visits for ADEs in dialysis patients is agents primarily affecting blood constituents, which has increased. After propensity matching, patient admission was higher in dialysis patients than non-dialysis patients, (88 vs. 76%, p < 0.001). Dialysis was associated with a 3% increase in risk of admission and 3 times the odds of in-hospital mortality (adjusted OR 3, 95% CI 2.7-2.3.3). ED visits for ADEs are substantially higher in dialysis patients than non-dialysis patients. In dialysis patients, ADEs associated with agents primarily affecting blood constituents are on the rise. ED visits for ADEs in dialysis patients have higher inpatient admissions and in-hospital mortality. Further studies are needed to identify and implement measures aimed at reducing ADEs in dialysis patients. © 2018 S. Karger AG, Basel.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

USGS Publications Warehouse

Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

2013-01-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

PubMed

Dorazio, Robert M; Martin, Julien; Edwards, Holly H

2013-07-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

A quantile count model of water depth constraints on Cape Sable seaside sparrows

USGS Publications Warehouse

Cade, B.S.; Dong, Q.

2008-01-01

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Analysis of petroleum contaminated soils by spectral modeling and pure response profile recovery of n-hexane.

PubMed

Chakraborty, Somsubhra; Weindorf, David C; Li, Bin; Ali, Md Nasim; Majumdar, K; Ray, D P

2014-07-01

This pilot study compared penalized spline regression (PSR) and random forest (RF) regression using visible and near-infrared diffuse reflectance spectroscopy (VisNIR DRS) derived spectra of 164 petroleum contaminated soils after two different spectral pretreatments [first derivative (FD) and standard normal variate (SNV) followed by detrending] for rapid quantification of soil petroleum contamination. Additionally, a new analytical approach was proposed for the recovery of the pure spectral and concentration profiles of n-hexane present in the unresolved mixture of petroleum contaminated soils using multivariate curve resolution alternating least squares (MCR-ALS). The PSR model using FD spectra (r(2) = 0.87, RMSE = 0.580 log10 mg kg(-1), and residual prediction deviation = 2.78) outperformed all other models tested. Quantitative results obtained by MCR-ALS for n-hexane in presence of interferences (r(2) = 0.65 and RMSE 0.261 log10 mg kg(-1)) were comparable to those obtained using FD (PSR) model. Furthermore, MCR ALS was able to recover pure spectra of n-hexane. Copyright © 2014 Elsevier Ltd. All rights reserved.

Payment systems and oral health in Swedish dental care: Observations over six years.

PubMed

Andås, C A; Hakeberg, M

2016-12-01

The aim of this longitudinal study of patients in regular dental care was to compare the findings of manifest caries and fillings after a 6-year adherence to either of two optional payment models, the traditional fee-for service (FFS) model, or the new capitation model 'Dental Care for Health' (DCH). Data on manifest caries lesions, the number of fillings and a number of background variables were collected from both a register and a questionnaire completed by 6,299 regular dental patients who met the inclusion criteria. The influence of payment system adherence and background variables on the number of manifest caries lesions at study end was examined by the means of negative binomial regression analysis. The incidence rate ratio of manifest caries lesions after six years in FFS was 1.5 compared to DCH, after controlling for age, gender, education and pre-baseline caries incidence. The number of fillings was higher in FFS than in DCH at study start and at study end, and was also described by a steeper slope. At group level, this study showed a statistically significant difference between the caries situation after six years in DCH compared with FFS, when some important background factors, including pre-baseline caries, were kept constant in a regression model. Copyright© 2016 Dennis Barber Ltd

High-risk regions and outbreak modelling of tularemia in humans.

PubMed

Desvars-Larrive, A; Liu, X; Hjertqvist, M; Sjöstedt, A; Johansson, A; Rydén, P

2017-02-01

Sweden reports large and variable numbers of human tularemia cases, but the high-risk regions are anecdotally defined and factors explaining annual variations are poorly understood. Here, high-risk regions were identified by spatial cluster analysis on disease surveillance data for 1984-2012. Negative binomial regression with five previously validated predictors (including predicted mosquito abundance and predictors based on local weather data) was used to model the annual number of tularemia cases within the high-risk regions. Seven high-risk regions were identified with annual incidences of 3·8-44 cases/100 000 inhabitants, accounting for 56·4% of the tularemia cases but only 9·3% of Sweden's population. For all high-risk regions, most cases occurred between July and September. The regression models explained the annual variation of tularemia cases within most high-risk regions and discriminated between years with and without outbreaks. In conclusion, tularemia in Sweden is concentrated in a few high-risk regions and shows high annual and seasonal variations. We present reproducible methods for identifying tularemia high-risk regions and modelling tularemia cases within these regions. The results may help health authorities to target populations at risk and lay the foundation for developing an early warning system for outbreaks.

Abstract knowledge versus direct experience in processing of binomial expressions

PubMed Central

Morgan, Emily; Levy, Roger

2016-01-01

We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. PMID:27776281

Using Financial Ratios to Select Companies for Tax Auditing: A Preliminary Study

NASA Astrophysics Data System (ADS)

Marghescu, Dorina; Kallio, Minna; Back, Barbro

Tax auditing procedures include an investigation of the accounting records of a company and of other sources of information in order to assess whether the taxation has been based on correct and complete information. When there are found discrepancies between the accounting information and the real situation, the taxation should be corrected so that the eventual tax defaults are assessed and debited. The paper analyzes to what extent the financial performance of a company can be used as an indicator of tax defaults. We focus on one type of tax, namely employer's contribution, and four financial ratios. We evaluate the model in a study of Finnish companies by using a binomial logistic regression analysis. The study is exploratory and at a preliminary stage.

Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old.

PubMed

Oliveira, André; Cabral, António J R; Mendes, Jorge M; Martins, Maria R O; Cabral, Pedro

2015-11-04

Stroke risk has been shown to display varying patterns of geographic distribution amongst countries but also between regions of the same country. Traditionally a disease of older persons, a global 25% increase in incidence instead was noticed between 1990 and 2010 in persons aged 20-≤64 years, particularly in low- and medium-income countries. Understanding spatial disparities in the association between socioeconomic factors and stroke is critical to target public health initiatives aiming to mitigate or prevent this disease, including in younger persons. We aimed to identify socioeconomic determinants of geographic disparities of stroke risk in people <65 years old, in municipalities of mainland Portugal, and the spatiotemporal variation of the association between these determinants and stroke risk during two study periods (1992-1996 and 2002-2006). Poisson and negative binomial global regression models were used to explore determinants of disease risk. Geographically weighted regression (GWR) represents a distinctive approach, allowing estimation of local regression coefficients. Models for both study periods were identified. Significant variables included education attainment, work hours per week and unemployment. Local Poisson GWR models achieved the best fit and evidenced spatially varying regression coefficients. Spatiotemporal inequalities were observed in significant variables, with dissimilarities between men and women. This study contributes to a better understanding of the relationship between stroke and socioeconomic factors in the population <65 years of age, one age group seldom analysed separately. It can thus help to improve the targeting of public health initiatives, even more in a context of economic crisis.

Binomial test statistics using Psi functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Kimiko o

2007-01-01

For the negative binomial model (probability generating function (p + 1 - pt){sup -k}) a logarithmic derivative is the Psi function difference {psi}(k + x) - {psi}(k); this and its derivatives lead to a test statistic to decide on the validity of a specified model. The test statistic uses a data base so there exists a comparison available between theory and application. Note that the test function is not dominated by outliers. Applications to (i) Fisher's tick data, (ii) accidents data, (iii) Weldon's dice data are included.

Changes in public attitudes towards confidential adolescent sexual and reproductive health services in Lithuania after the introduction of new legislation: findings from the cross-sectional surveys conducted in 2005 and 2012.

PubMed

Jaruseviciene, Lina; Zaborskis, Apolinaras; Sauliune, Skirmante; Jarusevicius, Gediminas; Lazarus, Jeffrey V

2015-09-04

In Lithuania, the right to confidentiality in healthcare for adolescents over the age of 16 was guaranteed in 2010 through the adoption of new legislation. This study sets out to explore changes in Lithuanian residents' attitudes towards confidentiality protection in adolescent sexual and reproductive healthcare (SRH) by comparing data from surveys administered in 2005 and 2012. For both surveys, the participants were random samples of the Lithuanian residents aged 16 to 74. A 23-item questionnaire was used in 2005 and complemented with 2 items in 2012. Linear regression analysis was employed to estimate absolute differences in prevalence of belief in whether or not adolescents would find confidentiality important when consulting a physician on SRH issues. A log-binomial regression model was fitted to estimate the relative changes (prevalence ratio) of the independent variables. The total number of respondents was 1054 (response rate 83%) in 2005 and 1002 (response rate 80%) in 2012. The proportion of respondents who reported a belief that adolescents would find confidentiality important when seeing a physician for SRH issues increased significantly from 62% in 2005 to 73% in 2012. Regardless of their belief in the importance of confidentiality, in 2012 respondents more often indicated positive outcomes on the relations between the physician and the minor patient, such as increased trust of the adolescent in the physician and more frequent visits to physicians. However, study participants who believed that adolescents would find confidentiality important in 2012 were less optimistic about potential positive outcomes of further legal consolidation of adolescents' right to confidentiality than in 2005. Younger respondents were the most optimistic about potential outcomes if laws were enacted to further protect adolescent confidentiality. This study uncovers the dynamics of public attitudes towards the socially and ethically sensitive issue of adolescent SRH. Our study suggests that legislation could be a factor prompting changes in public opinion, but not sufficient in and of itself for its social acceptance.

Coffee consumption is not associated with prevalent subclinical cardiovascular disease (CVD) or the risk of CVD events, in nonalcoholic fatty liver disease: results from the multi-ethnic study of atherosclerosis.

PubMed

Simon, Tracey G; Trejo, Maria Esther Perez; Zeb, Irfan; Frazier-Wood, Alexis C; McClelland, Robyn L; Chung, Raymond T; Budoff, Matthew J

2017-10-01

Atherosclerosis and its clinical sequelae represent the leading cause of mortality among patients with nonalcoholic fatty liver disease (NAFLD). While epidemiologic data support the hepatoprotective benefits of coffee in NAFLD, whether coffee improves NAFLD-associated CVD risk is unknown. We examined 3710 ethnically-diverse participants from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, without history of known liver disease, and with available coffee data from a validated 120-item food frequency questionnaire. All participants underwent baseline non-contrast cardiac CT from which NAFLD was defined by liver:spleen ratio (L:S<1.0), and subclinical CVD was defined by coronary artery calcium (CAC)>0. Major CVD events were defined by the first occurrence of myocardial infarction, cardiac arrest, angina, stroke, or CVD death. We used log-binomial regression to calculate the adjusted prevalence ratio (PR) for CAC>0 by coffee intake and NAFLD status, and events were compared between groups using frequency of events within adjusted Cox proportional hazard regression models. Seventeen percent (N=637) of participants met criteria for NAFLD. NAFLD participants were more likely to have elevated BMI (mean 31.1±5.5kg/m 2 vs. 28.0±5.2kg/m 2 , p<0.0001), and diabetes (22% vs. 11%, p<0.0001), but did not differ in daily coffee consumption (p=0.97). Among NAFLD participants, coffee consumption was not associated with prevalent, baseline CAC>0 (PR=1.02 [0.98-1.07]). Over 12.8years of follow-up, 93 NAFLD and 415 non-NAFLD participants experienced a CV event. However, coffee intake was not associated with incident CVD events, in either NAFLD (HR=1.05 [0.91-1.21]) or non-NAFLD participants (HR=1.03 [0.97-1.11]). In a large, population-based cohort, coffee consumption was not associated with the prevalence of subclinical CVD, nor did coffee impact the future risk of major CVD events, regardless of underlying NAFLD status. Copyright © 2017 Elsevier Inc. All rights reserved.

Using mixed treatment comparisons and meta-regression to perform indirect comparisons to estimate the efficacy of biologic treatments in rheumatoid arthritis.

PubMed

Nixon, R M; Bansback, N; Brennan, A

2007-03-15

Mixed treatment comparison (MTC) is a generalization of meta-analysis. Instead of the same treatment for a disease being tested in a number of studies, a number of different interventions are considered. Meta-regression is also a generalization of meta-analysis where an attempt is made to explain the heterogeneity between the treatment effects in the studies by regressing on study-level covariables. Our focus is where there are several different treatments considered in a number of randomized controlled trials in a specific disease, the same treatment can be applied in several arms within a study, and where differences in efficacy can be explained by differences in the study settings. We develop methods for simultaneously comparing several treatments and adjusting for study-level covariables by combining ideas from MTC and meta-regression. We use a case study from rheumatoid arthritis. We identified relevant trials of biologic verses standard therapy or placebo and extracted the doses, comparators and patient baseline characteristics. Efficacy is measured using the log odds ratio of achieving six-month ACR50 responder status. A random-effects meta-regression model is fitted which adjusts the log odds ratio for study-level prognostic factors. A different random-effect distribution on the log odds ratios is allowed for each different treatment. The odds ratio is found as a function of the prognostic factors for each treatment. The apparent differences in the randomized trials between tumour necrosis factor alpha (TNF- alpha) antagonists are explained by differences in prognostic factors and the analysis suggests that these drugs as a class are not different from each other. Copyright (c) 2006 John Wiley & Sons, Ltd.

An approach to checking case-crossover analyses based on equivalence with time-series methods.

PubMed

Lu, Yun; Symons, James Morel; Geyh, Alison S; Zeger, Scott L

2008-03-01

The case-crossover design has been increasingly applied to epidemiologic investigations of acute adverse health effects associated with ambient air pollution. The correspondence of the design to that of matched case-control studies makes it inferentially appealing for epidemiologic studies. Case-crossover analyses generally use conditional logistic regression modeling. This technique is equivalent to time-series log-linear regression models when there is a common exposure across individuals, as in air pollution studies. Previous methods for obtaining unbiased estimates for case-crossover analyses have assumed that time-varying risk factors are constant within reference windows. In this paper, we rely on the connection between case-crossover and time-series methods to illustrate model-checking procedures from log-linear model diagnostics for time-stratified case-crossover analyses. Additionally, we compare the relative performance of the time-stratified case-crossover approach to time-series methods under 3 simulated scenarios representing different temporal patterns of daily mortality associated with air pollution in Chicago, Illinois, during 1995 and 1996. Whenever a model-be it time-series or case-crossover-fails to account appropriately for fluctuations in time that confound the exposure, the effect estimate will be biased. It is therefore important to perform model-checking in time-stratified case-crossover analyses rather than assume the estimator is unbiased.

Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study.

PubMed

Asselbergs, Joost; Ruwaard, Jeroen; Ejdys, Michal; Schrader, Niels; Sijbrandij, Marit; Riper, Heleen

2016-03-29

Ecological momentary assessment (EMA) is a useful method to tap the dynamics of psychological and behavioral phenomena in real-world contexts. However, the response burden of (self-report) EMA limits its clinical utility. The aim was to explore mobile phone-based unobtrusive EMA, in which mobile phone usage logs are considered as proxy measures of clinically relevant user states and contexts. This was an uncontrolled explorative pilot study. Our study consisted of 6 weeks of EMA/unobtrusive EMA data collection in a Dutch student population (N=33), followed by a regression modeling analysis. Participants self-monitored their mood on their mobile phone (EMA) with a one-dimensional mood measure (1 to 10) and a two-dimensional circumplex measure (arousal/valence, -2 to 2). Meanwhile, with participants' consent, a mobile phone app unobtrusively collected (meta) data from six smartphone sensor logs (unobtrusive EMA: calls/short message service (SMS) text messages, screen time, application usage, accelerometer, and phone camera events). Through forward stepwise regression (FSR), we built personalized regression models from the unobtrusive EMA variables to predict day-to-day variation in EMA mood ratings. The predictive performance of these models (ie, cross-validated mean squared error and percentage of correct predictions) was compared to naive benchmark regression models (the mean model and a lag-2 history model). A total of 27 participants (81%) provided a mean 35.5 days (SD 3.8) of valid EMA/unobtrusive EMA data. The FSR models accurately predicted 55% to 76% of EMA mood scores. However, the predictive performance of these models was significantly inferior to that of naive benchmark models. Mobile phone-based unobtrusive EMA is a technically feasible and potentially powerful EMA variant. The method is young and positive findings may not replicate. At present, we do not recommend the application of FSR-based mood prediction in real-world clinical settings. Further psychometric studies and more advanced data mining techniques are needed to unlock unobtrusive EMA's true potential.

A novel prediction approach for antimalarial activities of Trimethoprim, Pyrimethamine, and Cycloguanil analogues using extremely randomized trees.

PubMed

Nattee, Cholwich; Khamsemanan, Nirattaya; Lawtrakul, Luckhana; Toochinda, Pisanu; Hannongbua, Supa

2017-01-01

Malaria is still one of the most serious diseases in tropical regions. This is due in part to the high resistance against available drugs for the inhibition of parasites, Plasmodium, the cause of the disease. New potent compounds with high clinical utility are urgently needed. In this work, we created a novel model using a regression tree to study structure-activity relationships and predict the inhibition constant, K i of three different antimalarial analogues (Trimethoprim, Pyrimethamine, and Cycloguanil) based on their molecular descriptors. To the best of our knowledge, this work is the first attempt to study the structure-activity relationships of all three analogues combined. The most relevant descriptors and appropriate parameters of the regression tree are harvested using extremely randomized trees. These descriptors are water accessible surface area, Log of the aqueous solubility, total hydrophobic van der Waals surface area, and molecular refractivity. Out of all possible combinations of these selected parameters and descriptors, the tree with the strongest coefficient of determination is selected to be our prediction model. Predicted K i values from the proposed model show a strong coefficient of determination, R 2 =0.996, to experimental K i values. From the structure of the regression tree, compounds with high accessible surface area of all hydrophobic atoms (ASA_H) and low aqueous solubility of inhibitors (Log S) generally possess low K i values. Our prediction model can also be utilized as a screening test for new antimalarial drug compounds which may reduce the time and expenses for new drug development. New compounds with high predicted K i should be excluded from further drug development. It is also our inference that a threshold of ASA_H greater than 575.80 and Log S less than or equal to -4.36 is a sufficient condition for a new compound to possess a low K i . Copyright © 2016 Elsevier Inc. All rights reserved.

Study of the partition coefficients Kp/f of seven model migrants from LDPE polymer in contact with food simulants.

PubMed

Paseiro-Cerrato, Rafael; Tongchat, Chinawat; Franz, Roland

2016-05-01

This study evaluated the influence of parameters such as temperature and type of low-density polyethylene (LDPE) film on the log Kp/f values of seven model migrants in food simulants. Two different types of LDPE films contaminated by extrusion and immersion were placed in contact with three food simulants including 20% ethanol, 50% ethanol and olive oil under several time-temperature conditions. Results suggest that most log Kp/f values are little affected by these parameters in this study. In addition, the relation between log Kp/f and log Po/w was established for each food simulant and regression lines, as well as correlation coefficients, were calculated. Correlations were compared with data from real foodstuffs. Data presented in this study could be valuable in assigning certain foods to particular food simulants as well as predicting the mass transfer of potential migrants into different types of food or food simulants, avoiding tedious and expensive laboratory analysis. The results could be especially useful for regulatory agencies as well as for the food industry.

Effects of health intervention programs and arsenic exposure on child mortality from acute lower respiratory infections in rural Bangladesh.

PubMed

Jochem, Warren C; Razzaque, Abdur; Root, Elisabeth Dowling

2016-09-01

Respiratory infections continue to be a public health threat, particularly to young children in developing countries. Understanding the geographic patterns of diseases and the role of potential risk factors can help improve future mitigation efforts. Toward this goal, this paper applies a spatial scan statistic combined with a zero-inflated negative-binomial regression to re-examine the impacts of a community-based treatment program on the geographic patterns of acute lower respiratory infection (ALRI) mortality in an area of rural Bangladesh. Exposure to arsenic-contaminated drinking water is also a serious threat to the health of children in this area, and the variation in exposure to arsenic must be considered when evaluating the health interventions. ALRI mortality data were obtained for children under 2 years old from 1989 to 1996 in the Matlab Health and Demographic Surveillance System. This study period covers the years immediately following the implementation of an ALRI control program. A zero-inflated negative binomial (ZINB) regression model was first used to simultaneously estimate mortality rates and the likelihood of no deaths in groups of related households while controlling for socioeconomic status, potential arsenic exposure, and access to care. Next a spatial scan statistic was used to assess the location and magnitude of clusters of ALRI mortality. The ZINB model was used to adjust the scan statistic for multiple social and environmental risk factors. The results of the ZINB models and spatial scan statistic suggest that the ALRI control program was successful in reducing child mortality in the study area. Exposure to arsenic-contaminated drinking water was not associated with increased mortality. Higher socioeconomic status also significantly reduced mortality rates, even among households who were in the treatment program area. Community-based ALRI interventions can be effective at reducing child mortality, though socioeconomic factors may continue to influence mortality patterns. The combination of spatial and non-spatial methods used in this paper has not been applied previously in the literature, and this study demonstrates the importance of such approaches for evaluating and improving public health intervention programs.

Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1, 4-dihydropyridine derivatives with potential antihypertensive effects.

PubMed

Jardínez, Christiaan; Vela, Alberto; Cruz-Borbolla, Julián; Alvarez-Mendez, Rodrigo J; Alvarado-Rodríguez, José G

2016-12-01

The relationship between the chemical structure and biological activity (log IC 50 ) of 40 derivatives of 1,4-dihydropyridines (DHPs) was studied using density functional theory (DFT) and multiple linear regression analysis methods. With the aim of improving the quantitative structure-activity relationship (QSAR) model, the reduced density gradient s( r) of the optimized equilibrium geometries was used as a descriptor to include weak non-covalent interactions. The QSAR model highlights the correlation between the log IC 50 with highest molecular orbital energy (E HOMO ), molecular volume (V), partition coefficient (log P), non-covalent interactions NCI(H4-G) and the dual descriptor [Δf(r)]. The model yielded values of R 2 =79.57 and Q 2 =69.67 that were validated with the next four internal analytical validations DK=0.076, DQ=-0.006, R P =0.056, and R N =0.000, and the external validation Q 2 boot =64.26. The QSAR model found can be used to estimate biological activity with high reliability in new compounds based on a DHP series. Graphical abstract The good correlation between the log IC 50 with the NCI (H4-G) estimated by the reduced density gradient approach of the DHP derivatives.

A Comparison of Strategies for Estimating Conditional DIF

ERIC Educational Resources Information Center

Moses, Tim; Miao, Jing; Dorans, Neil J.

2010-01-01

In this study, the accuracies of four strategies were compared for estimating conditional differential item functioning (DIF), including raw data, logistic regression, log-linear models, and kernel smoothing. Real data simulations were used to evaluate the estimation strategies across six items, DIF and No DIF situations, and four sample size…

Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

USGS Publications Warehouse

Zipkin, Elise F.; Leirness, Jeffery B.; Kinlan, Brian P.; O'Connell, Allan F.; Silverman, Emily D.

2014-01-01

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes.

Knowledge, attitudes and beliefs related to seasonal influenza vaccine among pregnant women in Thailand.

PubMed

Ditsungnoen, Darunee; Greenbaum, Adena; Praphasiri, Prabda; Dawood, Fatimah S; Thompson, Mark G; Yoocharoen, Pornsak; Lindblade, Kim A; Olsen, Sonja J; Muangchana, Charung

2016-04-19

In 2009, Thailand recommended pregnant women be prioritized for influenza vaccination. Vaccine uptake among Thai pregnant women is lower than other high-risk groups. During December 2012-April 2013, we conducted a cross-sectional survey of a convenience sample of Thai pregnant women aged ≥ 15 years attending antenatal clinics at public hospitals in 8 of 77 provinces. A self-administered questionnaire covered knowledge, attitudes, and beliefs related to influenza vaccination using the Health Belief Model. We examined factors associated with willingness to be vaccinated using log-binomial regression models. The survey was completed by 1031 (96%) of 1072 pregnant women approached. A total of 627 (61%) women had heard about influenza vaccine and were included in the analysis, of whom 262 (42%) were willing to be vaccinated, 155 (25%) had received a healthcare provider recommendation for influenza vaccination and 25 (4%) had received the influenza vaccine during the current pregnancy. In unadjusted models, high levels of perceptions of susceptibility (prevalence ratio [PR] 1.5, 95% CI 1.2-2.0), high levels of belief in the benefits of vaccination (PR 2.3, 95% CI 1.7-3.1), moderate (PR 1.7, 95% CI 1.2-2.3) and high (PR 3.4, 95% CI 2.6-4.5) levels of encouragement by others to be vaccinated (i.e., cues to action) were positively associated with willingness to be vaccinated. Moderate (PR 0.5, 95% CI 0.4-0.7) and high levels of (PR 0.5, 95% CI 0.4-0.8) perceived barriers were negatively associated with willingness to be vaccinated. In the final adjusted model, only moderate (PR 1.5, 95% CI 1.1-2.0) and high levels of cues to action (PR 2.7, 95% CI 2.0-3.6) were statistically associated with willingness to be vaccinated. Cues to action were associated with willingness to be vaccinated and can be used to inform communication strategies during the vaccine campaign to increase influenza vaccination among Thai pregnant women. Published by Elsevier Ltd.

Relationship between suicide rate and economic growth and stock market in the People's Republic of China: 2004-2013.

PubMed

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People's Republic of China. Official data were gathered and analyzed in the People's Republic of China during the period 2004-2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People's Republic of China. Suicide rate in the People's Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Suicide rate decreased in 2004-2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People's Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study.

Relationship between suicide rate and economic growth and stock market in the People’s Republic of China: 2004–2013

PubMed Central

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

Objectives The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People’s Republic of China. Methods Official data were gathered and analyzed in the People’s Republic of China during the period 2004–2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Results Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People’s Republic of China. Suicide rate in the People’s Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Conclusion Suicide rate decreased in 2004–2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People’s Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study. PMID:27994468

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

PubMed Central

Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J

2009-01-01

Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590

A Generalized Approach for the Interpretation of Geophysical Well Logs in Ground-Water Studies - Theory and Application

USGS Publications Warehouse

Paillet, Frederick L.; Crowder, R.E.

1996-01-01

Quantitative analysis of geophysical logs in ground-water studies often involves at least as broad a range of applications and variation in lithology as is typically encountered in petroleum exploration, making such logs difficult to calibrate and complicating inversion problem formulation. At the same time, data inversion and analysis depend on inversion model formulation and refinement, so that log interpretation cannot be deferred to a geophysical log specialist unless active involvement with interpretation can be maintained by such an expert over the lifetime of the project. We propose a generalized log-interpretation procedure designed to guide hydrogeologists in the interpretation of geophysical logs, and in the integration of log data into ground-water models that may be systematically refined and improved in an iterative way. The procedure is designed to maximize the effective use of three primary contributions from geophysical logs: (1) The continuous depth scale of the measurements along the well bore; (2) The in situ measurement of lithologic properties and the correlation with hydraulic properties of the formations over a finite sample volume; and (3) Multiple independent measurements that can potentially be inverted for multiple physical or hydraulic properties of interest. The approach is formulated in the context of geophysical inversion theory, and is designed to be interfaced with surface geophysical soundings and conventional hydraulic testing. The step-by-step procedures given in our generalized interpretation and inversion technique are based on both qualitative analysis designed to assist formulation of the interpretation model, and quantitative analysis used to assign numerical values to model parameters. The approach bases a decision as to whether quantitative inversion is statistically warranted by formulating an over-determined inversion. If no such inversion is consistent with the inversion model, quantitative inversion is judged not possible with the given data set. Additional statistical criteria such as the statistical significance of regressions are used to guide the subsequent calibration of geophysical data in terms of hydraulic variables in those situations where quantitative data inversion is considered appropriate.

Gender and Socioeconomic Status in Relation to Weight Perception and Weight Control Behavior in Korean Adults

PubMed Central

Joh, Hee-Kyung; Oh, Juhwan; Lee, Hae-Jeung; Kawachi, Ichiro

2013-01-01

Aim In Korea, obesity is more prevalent among men and lower socioeconomic groups. To explain this obesity disparity, we compared weight perception and weight control behavior across gender and socioeconomic status (SES). Methods We analyzed data from 16,260 participants aged 20 years or older in a nationally representative cross-sectional survey. SES indicators included education and income levels. Weight under-perception was defined when participants considered themselves lighter than their measured BMI status. Either no active or inappropriate weight control (i.e., trying to gain weight in obese individuals) was considered to be unhealthy patterns. Multivariate prevalence ratios were calculated using log-binomial regressions. Results Men had a higher prevalence of weight under-perception (24.5 vs. 11.9%) and unhealthy patterns of weight control behavior (57 vs. 40%) than women. Low education level was associated with weight under-perception (ptrend = 0.022 in men, ptrend ℋ 0.001 in women). Both education and income levels were significantly associated with patterns of weight control behavior (for education: ptrend ℋ 0.001 in men and women; for income: ptrend = 0.047 in men, ptrend ℋ 0.001 in women). Conclusion Weight perception and weight control behavior significantly varied by gender and SES. Public actions should be directed toward improving perception and behavior of high-risk populations. PMID:23429009

The association between states' texting regulations and the prevalence of texting while driving among U.S. high school students.

PubMed

Rudisill, Toni M; Zhu, Motao

2015-12-01

To determine which distracted driving laws were associated with decreased texting while driving among U.S. teenage drivers. Data from the 2013 Youth Risk Behavior Surveillance System survey were merged with states' distracted driving legislation. The prevalence of texting while driving was assessed for different laws using log-binomial regression. Approximately 39.0% of students reported texting while driving at least once in the 30 days before survey. Compared to states with universal texting bans along with young driver all cellphone bans, the adjusted ratio of texting while driving was 0.94 (95% confidence interval [CI], 0.77-1.16) in states with no bans, 1.33 (95% CI, 1.11-1.58) for young driver bans only, 1.24 (95% CI, 1.00-1.52) in states with bans for young drivers but no young driver all cellphone bans, and 0.89 (95% CI, 0.66-1.19) in states with universal texting bans. The prevalence of texting was 28% less in states with delays of full licensure for texting offenses (prevalence ratio = 0.72; 95% CI, 0.59-0.88). Universal texting bans along with young driver all cellphone bans may be more effective in reducing texting while driving. Delays of full licensure may dissuade young drivers from texting and driving. Copyright © 2015 Elsevier Inc. All rights reserved.

Social networks and patterns of health risk behaviours over two decades: A multi-cohort study.

PubMed

Kauppi, Maarit; Elovainio, Marko; Stenholm, Sari; Virtanen, Marianna; Aalto, Ville; Koskenvuo, Markku; Kivimäki, Mika; Vahtera, Jussi

2017-08-01

To determine the associations between social network size and subsequent long-term health behaviour patterns, as indicated by alcohol use, smoking, and physical activity. Repeat data from up to six surveys over a 15- or 20-year follow-up were drawn from the Finnish Public Sector study (Raisio-Turku cohort, n=986; Hospital cohort, n=7307), and the Health and Social Support study (n=20,115). Social network size was determined at baseline, and health risk behaviours were assessed using repeated data from baseline and follow-up. We pooled cohort-specific results from repeated-measures log-binomial regression with the generalized estimating equations (GEE) method using fixed-effects meta-analysis. Participants with up to 10 members in their social network at baseline had an unhealthy risk factor profile throughout the follow-up. The pooled relative risks adjusted for age, gender, survey year, chronic conditions and education were 1.15 for heavy alcohol use (95% CI: 1.06-1.24), 1.19 for smoking (95% CI: 1.12-1.27), and 1.25 for low physical activity (95% CI: 1.21-1.29), as compared with those with >20 members in their social network. These associations appeared to be similar in subgroups stratified according to gender, age and education. Social network size predicted persistent behaviour-related health risk patterns up to at least two decades. Copyright © 2017 Elsevier Inc. All rights reserved.

Driving kids to smoke? Children's reported exposure to smoke in cars and early smoking initiation.

PubMed

Glover, Marewa; Scragg, Robert; Min, Sandar; Kira, Anette; Nosa, Vili; McCool, Judith; Bullen, Chris

2011-11-01

The health risks associated with second hand smoke (SHS) are well-known. However, little is known about exposure to SHS in cars and risk of smoking uptake. This paper investigates the association between pre-adolescents reported exposure to smoking in cars and prevalence of early stage smoking activity. Data from Keeping Kids Smokefree baseline surveys of students were used to investigate smoking status and reported exposure to smoking in cars. Log binomial regression analyses were used to investigate if reported exposure to SHS in cars was associated with smoking prevalence. 83% of 5676 students invited took part. After controlling for all variables reported exposure to smoking in cars and homes were significantly associated with increased risk of initiated smoking (RR 1.87, 95% CI 1.43-2.44, and RR 1.5, 95% CI 1.13-1.97, respectively). Exposure to smoking in cars was substantially and significantly associated with risk of current smoking (RR 3.21, 95% CI 1.45-7.08). Early smoking uptake is associated with students' reported exposure to smoking in cars which confirms the importance of protecting children from SHS. Smoking in cars is under parental control and therefore modifiable. Moreover, children's reports of SHlS exposure offer a simple way of identifying families who can be targeted for tobacco control interventions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Timeliness and completeness of vaccination and risk factors for low and late vaccine uptake in young children living in rural southern Tanzania.

PubMed

Le Polain de Waroux, Olivier; Schellenberg, Joanna R Armstrong; Manzi, Fatuma; Mrisho, Mwifadhi; Shirima, Kizito; Mshinda, Hassan; Alonso, Pedro; Tanner, Marcel; Schellenberg, David M

2013-06-01

We studied coverage and timeliness of vaccination and risk factors for low and delayed vaccine uptake in children aged <2 years in rural Tanzania. We used data from a cluster survey conducted in 2004, which included 1403 children. Risk factors were analysed by log-binomial regression adjusted for the clustering. The analysis was restricted to BCG, first and third dose of Diphtheria-Tetanus-Pertussis vaccines (DTP-1 and DTP-3) and first dose of measles-containing vaccine (MCV-1). Coverage for BCG, DTP-1, DTP-3 and MCV-1 was 94%, 96%, 90% and 86%, respectively. Delayed vaccination (>1 month after the recommended age) occurred in 398/1205 (33%) children for BCG, 404/1189 (34%) for DTP-1, 683/990 (69%) for DTP-3 and 296/643 (46%) for MCV-1. Coverage was lower for all vaccines except DTP-1 in children living ≥5 km from a healthcare facility. Delayed uptake was associated with poverty. Low and delayed MCV-1 vaccination was associated with low maternal education. Delayed BCG vaccination was associated with ethnicity and rainy season. Despite reasonably high vaccination coverage, we observed substantial vaccination delays, particularly for DTP-3 and MCV-1. We found specific factors associated with low and/or delayed vaccine uptake. These findings can help to improve strategies to reach children who remain inadequately protected.

[Tobacco and alcohol consumption according to workday in Spain].

PubMed

García-Díaz, Vanesa; Fernández-Feito, Ana; Arias, Lucía; Lana, Alberto

2015-01-01

To examine the association between smoking and alcohol consumption and the type of working day in the Spanish population Cross-sectional study among employees residing in Spain aged >18 years (N=8,736). We took data from the National Health Survey (2011-2012). Information was collected on the type of working day (morning, afternoon, evening, part-time, reduced hours, and shift-work) and smoking and drinking habits. Demographic characteristics and health- and work-related factors were also taken into account. Adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) were calculated through log-binomial regressions. Among respondents, 32.1% smoked regularly, especially those working the night shift (43.5%). Moderate alcohol consumption was found in 54.8% of workers and excessive consumption in 1.5%. Most of the moderate and heavy drinkers worked part-time, with 57.6% and 1.8% respectively. The aOR of being a smoker was higher among night workers (OR=1.58; 95% CI: 1.01-2.46). None of the work shifts were significantly associated with alcohol consumption. Night shift work was associated with regular smoking. This collective of workers should be monitored closely by occupational health services and regularly undergo programs to control tobacco consumption and smoking-related diseases. Additional research to elucidate the reasons for this association could help to achieve preventive and therapeutic success. Copyright © 2015 SESPAS. Published by Elsevier Espana. All rights reserved.

Recurrence of preterm birth and perinatal mortality in northern Tanzania: registry-based cohort study.

PubMed

Mahande, Michael J; Daltveit, Anne K; Obure, Joseph; Mmbaga, Blandina T; Masenga, Gileard; Manongi, Rachel; Lie, Rolv T

2013-08-01

To estimate the recurrence risk of preterm delivery and estimate the perinatal mortality in repeated preterm deliveries. Prospective study in Tanzania of 18 176 women who delivered a singleton between 2000 and 2008 at KCMC hospital. The women were followed up to 2010 for consecutive births. A total of 3359 women were identified with a total of 3867 subsequent deliveries in the follow-up period. Recurrence risk of preterm birth and perinatal mortality was estimated using log-binomial regression and adjusted for potential confounders. For women with a previous preterm birth, the risk of preterm birth in a subsequent pregnancy was 17%. This recurrence risk was estimated to be 2.7-fold (95% CI: 2.1-3.4) of the risk of women with a previous term birth. The perinatal mortality of babies in a second preterm birth of the same woman was 15%. Babies born at term who had an older sibling that was born preterm had a perinatal mortality of 10%. Babies born at term who had an older sibling who was also born at term had a perinatal mortality of 1.7%. Previous delivery of a preterm infant is a strong predictor of future preterm births in Tanzania. Previous or repeated preterm births increase the risk of perinatal death substantially in the subsequent pregnancy. © 2013 Blackwell Publishing Ltd.

The association between states’ texting regulations and the prevalence of texting while driving among U.S. high school students

PubMed Central

Rudisill, Toni M.; Zhu, Motao

2015-01-01

Purpose To determine which distracted driving laws were associated with decreased texting while driving among U.S. teenage drivers. Methods Data from the 2013 Youth Risk Behavior Surveillance System survey were merged with state’s distracted driving legislation. The prevalence of texting while driving was assessed for different laws using log-binomial regression. Results Approximately 39.0% of students reported texting while driving at least once in the 30 days before survey. Compared to states with universal texting bans along with young driver all cellphone bans, the adjusted ratio of texting while driving was 0.94 (95% confidence interval [CI], 0.77–1.16) in states with no bans, 1.33 (95% CI, 1.11–1.58) for young driver bans only, 1.24 (95% CI, 1.00–1.52) in states with bans for young drivers but no young driver all cellphone bans, and 0.89 (95% CI, 0.66–1.19) in states with universal texting bans. The prevalence of texting was 28% less in states with delays of full licensure for texting offenses (prevalence ratio = 0.72; 95% CI, 0.59–0.88). Conclusions Universal texting bans along with young driver all cellphone bans may be more effective in reducing texting while driving. Delays of full licensure may dissuade young drivers from texting and driving. PMID:26688117

Acquired Color Vision Defects and Hexane Exposure: A Study of San Francisco Bay Area Automotive Mechanics

PubMed Central

Beckman, Stella; Eisen, Ellen A.; Bates, Michael N.; Liu, Sa; Haegerstrom-Portnoy, Gunilla; Hammond, S. Katharine

2016-01-01

Occupational exposure to solvents, including n-hexane, has been associated with acquired color vision defects. Blue-yellow defects are most common and may be due to neurotoxicity or retinal damage. Acetone may potentiate the neurotoxicity of n-hexane. We present results on nonhexane solvent and hexane exposure and color vision from a cross-sectional study of 835 automotive repair workers in the San Francisco Bay Area, California (2007–2013). Cumulative exposure was estimated from self-reported work history, and color vision was assessed using the Lanthony desaturated D-15 panel test. Log-binomial regression was used to estimate prevalence ratios for color vision defects. Acquired color vision defects were present in 29% of participants, of which 70% were blue-yellow. Elevated prevalence ratios were found for nonhexane solvent exposure, with a maximum of 1.31 (95% confidence interval (CI): 0.86, 2.00) for blue-yellow. Among participants aged ≤50 years, the prevalence ratio for blue-yellow defects was 2.17 (95% CI: 1.03, 4.56) in the highest quartile of nonhexane solvent exposure and 1.62 (95% CI: 0.97, 2.72) in the highest category of exposure to hexane with acetone coexposure. Cumulative exposures to hexane and nonhexane solvents in the highest exposure categories were associated with elevated prevalence ratios for color vision defects in younger participants. PMID:27188942

Mycobacterium tuberculosis infection among persons who inject drugs in San Diego, California.

PubMed

Armenta, R F; Collins, K M; Strathdee, S A; Bulterys, M A; Munoz, F; Cuevas-Mota, J; Chiles, P; Garfein, R S

2017-04-01

Persons who inject drugs (PWID) might be at increased risk for Mycobacterium tuberculosis infection and reactivation of latent tuberculous infection (LTBI) due to their injection drug use. To determine prevalence and correlates of M. tuberculosis infection among PWID in San Diego, California, USA. PWID aged 18 years underwent standardized interviews and serologic testing using an interferon-gamma release assay (IGRA) for LTBI and rapid point-of-care assays for human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections. Independent correlates of M. tuberculosis infection were identified using multivariable log-binomial regression. A total of 500 participants met the eligibility criteria. The mean age was 43.2 years (standard deviation 11.6); most subjects were White (52%) or Hispanic (30.8%), and male (75%). Overall, 86.7% reported having ever traveled to Mexico. Prevalence of M. tuberculosis infection was 23.6%; 0.8% were co-infected with HIV and 81.7% were co-infected with HCV. Almost all participants (95%) had been previously tested for M. tuberculosis; 7.6% had been previously told they were infected. M. tuberculosis infection was independently associated with being Hispanic, having longer injection histories, testing HCV-positive, and correctly reporting that people with 'sleeping' TB cannot infect others. Strategies are needed to increase awareness about and treatment for M. tuberculosis infection among PWID in the US/Mexico border region.

Employment Precariousness and Poor Mental Health: Evidence from Spain on a New Social Determinant of Health

PubMed Central

Vives, Alejandra; Amable, Marcelo; Ferrer, Montserrat; Moncada, Salvador; Llorens, Clara; Muntaner, Carles; Benavides, Fernando G.; Benach, Joan

2013-01-01

Background. Evidence on the health-damaging effects of precarious employment is limited by the use of one-dimensional approaches focused on employment instability. This study assesses the association between precarious employment and poor mental health using the multidimensional Employment Precariousness Scale. Methods. Cross-sectional study of 5679 temporary and permanent workers from the population-based Psychosocial Factors Survey was carried out in 2004-2005 in Spain. Poor mental health was defined as SF-36 mental health scores below the 25th percentile of the Spanish reference for each respondent's sex and age. Prevalence proportion ratios (PPRs) of poor mental health across quintiles of employment precariousness (reference: 1st quintile) were calculated with log-binomial regressions, separately for women and men. Results. Crude PPRs showed a gradient association with poor mental health and remained generally unchanged after adjustments for age, immigrant status, socioeconomic position, and previous unemployment. Fully adjusted PPRs for the 5th quintile were 2.54 (95% CI: 1.95–3.31) for women and 2.23 (95% CI: 1.86–2.68) for men. Conclusion. The study finds a gradient association between employment precariousness and poor mental health, which was somewhat stronger among women, suggesting an interaction with gender-related power asymmetries. Further research is needed to strengthen the epidemiological evidence base and to inform labour market policy-making. PMID:23431322