Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

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.

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

PubMed

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients). Copyright © 2018. Published by Elsevier Ltd.

Non-Poisson Processes: Regression to Equilibrium Versus Equilibrium Correlation Functions

DTIC Science & Technology

2004-07-07

ARTICLE IN PRESSPhysica A 347 (2005) 268–2880378-4371/$ - doi:10.1016/j Correspo E-mail adwww.elsevier.com/locate/physaNon- Poisson processes : regression...05.40.a; 89.75.k; 02.50.Ey Keywords: Stochastic processes; Non- Poisson processes ; Liouville and Liouville-like equations; Correlation function...which is not legitimate with renewal non- Poisson processes , is a correct property if the deviation from the exponential relaxation is obtained by time

Modeling health survey data with excessive zero and K responses.

PubMed

Lin, Ting Hsiang; Tsai, Min-Hsiao

2013-04-30

Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.

Bayesian semi-parametric analysis of Poisson change-point regression models: application to policy making in Cali, Colombia.

PubMed

Park, Taeyoung; Krafty, Robert T; Sánchez, Alvaro I

2012-07-27

A Poisson regression model with an offset assumes a constant baseline rate after accounting for measured covariates, which may lead to biased estimates of coefficients in an inhomogeneous Poisson process. To correctly estimate the effect of time-dependent covariates, we propose a Poisson change-point regression model with an offset that allows a time-varying baseline rate. When the nonconstant pattern of a log baseline rate is modeled with a nonparametric step function, the resulting semi-parametric model involves a model component of varying dimension and thus requires a sophisticated varying-dimensional inference to obtain correct estimates of model parameters of fixed dimension. To fit the proposed varying-dimensional model, we devise a state-of-the-art MCMC-type algorithm based on partial collapse. The proposed model and methods are used to investigate an association between daily homicide rates in Cali, Colombia and policies that restrict the hours during which the legal sale of alcoholic beverages is permitted. While simultaneously identifying the latent changes in the baseline homicide rate which correspond to the incidence of sociopolitical events, we explore the effect of policies governing the sale of alcohol on homicide rates and seek a policy that balances the economic and cultural dependencies on alcohol sales to the health of the public.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.

PubMed

Richardson, S; Monfort, C; Green, M; Draper, G; Muirhead, C

This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.

77 FR 13691 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-07

..., ocular hypertension, retinal detachment, cataracts and corneal scaring. In most cases, their eye... Application of Multiple Regression Analysis of a Poisson Process,'' Journal of American Statistical...

Relative age effect in elite soccer: More early-born players, but no better valued, and no paragon clubs or countries

PubMed Central

Doyle, John R.

2018-01-01

The paper analyses two datasets of elite soccer players (top 1000 professionals and UEFA Under-19 Youth League). In both, we find a Relative Age Effect (RAE) for frequency, but not for value. That is, while there are more players born at the start of the competition year, their transfer values are no higher, nor are they given more game time. We use Poisson regression to derive a transparent index of the discrimination present in RAE. Also, because Poisson is valid for small frequency counts, it supports analysis at the disaggregated levels of country and club. From this, we conclude there are no paragon clubs or countries immune to RAE; that is clubs and countries do not differ systematically in the RAE they experience; also, that Poisson regression is a powerful and flexible method of analysing RAE data. PMID:29420576

Marginalized zero-inflated Poisson models with missing covariates.

PubMed

Benecha, Habtamu K; Preisser, John S; Divaris, Kimon; Herring, Amy H; Das, Kalyan

2018-05-11

Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Geographically weighted poisson regression semiparametric on modeling of the number of tuberculosis cases (Case study: Bandung city)

NASA Astrophysics Data System (ADS)

Octavianty, Toharudin, Toni; Jaya, I. G. N. Mindra

2017-03-01

Tuberculosis (TB) is a disease caused by a bacterium, called Mycobacterium tuberculosis, which typically attacks the lungs but can also affect the kidney, spine, and brain (Centers for Disease Control and Prevention). Indonesia had the largest number of TB cases after India (Global Tuberculosis Report 2015 by WHO). The distribution of Mycobacterium tuberculosis genotypes in Indonesia showed the high genetic diversity and tended to vary by geographic regions. For instance, in Bandung city, the prevalence rate of TB morbidity is quite high. A number of TB patients belong to the counted data. To determine the factors that significantly influence the number of tuberculosis patients in each location of the observations can be used statistical analysis tool that is Geographically Weighted Poisson Regression Semiparametric (GWPRS). GWPRS is an extension of the Poisson regression and GWPR that is influenced by geographical factors, and there is also variables that influence globally and locally. Using the TB Data in Bandung city (in 2015), the results show that the global and local variables that influence the number of tuberculosis patients in every sub-district.

Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study.

PubMed

Christensen, A L; Lundbye-Christensen, S; Dethlefsen, C

2011-12-01

Several statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards' estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates. Based on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough[13]. Applying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model. This simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.

ERIC Educational Resources Information Center

Bockenholt, Ulf

1999-01-01

Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…

Zero-inflated Conway-Maxwell Poisson Distribution to Analyze Discrete Data.

PubMed

Sim, Shin Zhu; Gupta, Ramesh C; Ong, Seng Huat

2018-01-09

In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models. It is shown that the fit by ZICMP is comparable or better than these models.

A test of inflated zeros for Poisson regression models.

PubMed

He, Hua; Zhang, Hui; Ye, Peng; Tang, Wan

2017-01-01

Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for testing inflated zeros under the Poisson model. Unlike the Vuong test for inflated zeros, our method does not require a zero-inflated Poisson model to perform the test. Simulation studies show that when compared with the Vuong test our approach not only better at controlling type I error rate, but also yield more power.

Modeling the number of car theft using Poisson regression

NASA Astrophysics Data System (ADS)

Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura

2016-10-01

Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

PubMed

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Effect of motivational interviewing on rates of early childhood caries: a randomized trial.

PubMed

Harrison, Rosamund; Benton, Tonya; Everson-Stewart, Siobhan; Weinstein, Phil

2007-01-01

The purposes of this randomized controlled trial were to: (1) test motivational interviewing (MI) to prevent early childhood caries; and (2) use Poisson regression for data analysis. A total of 240 South Asian children 6 to 18 months old were enrolled and randomly assigned to either the MI or control condition. Children had a dental exam, and their mothers completed pretested instruments at baseline and 1 and 2 years postintervention. Other covariates that might explain outcomes over and above treatment differences were modeled using Poisson regression. Hazard ratios were produced. Analyses included all participants whenever possible. Poisson regression supported a protective effect of MI (hazard ratio [HR]=0.54 (95%CI=035-0.84)-that is, the M/ group had about a 46% lower rate of dmfs at 2 years than did control children. Similar treatment effect estimates were obtained from models that included, as alternative outcomes, ds, dms, and dmfs, including "white spot lesions." Exploratory analyses revealed that rates of dmfs were higher in children whose mothers had: (1) prechewed their food; (2) been raised in a rural environment; and (3) a higher family income (P<.05). A motivational interviewing-style intervention shows promise to promote preventive behaviors in mothers of young children at high risk for caries.

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.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Fuzzy classifier based support vector regression framework for Poisson ratio determination

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2013-09-01

Poisson ratio is considered as one of the most important rock mechanical properties of hydrocarbon reservoirs. Determination of this parameter through laboratory measurement is time, cost, and labor intensive. Furthermore, laboratory measurements do not provide continuous data along the reservoir intervals. Hence, a fast, accurate, and inexpensive way of determining Poisson ratio which produces continuous data over the whole reservoir interval is desirable. For this purpose, support vector regression (SVR) method based on statistical learning theory (SLT) was employed as a supervised learning algorithm to estimate Poisson ratio from conventional well log data. SVR is capable of accurately extracting the implicit knowledge contained in conventional well logs and converting the gained knowledge into Poisson ratio data. Structural risk minimization (SRM) principle which is embedded in the SVR structure in addition to empirical risk minimization (EMR) principle provides a robust model for finding quantitative formulation between conventional well log data and Poisson ratio. Although satisfying results were obtained from an individual SVR model, it had flaws of overestimation in low Poisson ratios and underestimation in high Poisson ratios. These errors were eliminated through implementation of fuzzy classifier based SVR (FCBSVR). The FCBSVR significantly improved accuracy of the final prediction. This strategy was successfully applied to data from carbonate reservoir rocks of an Iranian Oil Field. Results indicated that SVR predicted Poisson ratio values are in good agreement with measured values.

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

Isolated and synergistic effects of PM10 and average temperature on cardiovascular and respiratory mortality.

PubMed

Pinheiro, Samya de Lara Lins de Araujo; Saldiva, Paulo Hilário Nascimento; Schwartz, Joel; Zanobetti, Antonella

2014-12-01

OBJECTIVE To analyze the effect of air pollution and temperature on mortality due to cardiovascular and respiratory diseases. METHODS We evaluated the isolated and synergistic effects of temperature and particulate matter with aerodynamic diameter < 10 µm (PM10) on the mortality of individuals > 40 years old due to cardiovascular disease and that of individuals > 60 years old due to respiratory diseases in Sao Paulo, SP, Southeastern Brazil, between 1998 and 2008. Three methodologies were used to evaluate the isolated association: time-series analysis using Poisson regression model, bidirectional case-crossover analysis matched by period, and case-crossover analysis matched by the confounding factor, i.e., average temperature or pollutant concentration. The graphical representation of the response surface, generated by the interaction term between these factors added to the Poisson regression model, was interpreted to evaluate the synergistic effect of the risk factors. RESULTS No differences were observed between the results of the case-crossover and time-series analyses. The percentage change in the relative risk of cardiovascular and respiratory mortality was 0.85% (0.45;1.25) and 1.60% (0.74;2.46), respectively, due to an increase of 10 μg/m3 in the PM10 concentration. The pattern of correlation of the temperature with cardiovascular mortality was U-shaped and that with respiratory mortality was J-shaped, indicating an increased relative risk at high temperatures. The values for the interaction term indicated a higher relative risk for cardiovascular and respiratory mortalities at low temperatures and high temperatures, respectively, when the pollution levels reached approximately 60 μg/m3. CONCLUSIONS The positive association standardized in the Poisson regression model for pollutant concentration is not confounded by temperature, and the effect of temperature is not confounded by the pollutant levels in the time-series analysis. The simultaneous exposure to different levels of environmental factors can create synergistic effects that are as disturbing as those caused by extreme concentrations.

Paramedic-Initiated Home Care Referrals and Use of Home Care and Emergency Medical Services.

PubMed

Verma, Amol A; Klich, John; Thurston, Adam; Scantlebury, Jordan; Kiss, Alex; Seddon, Gayle; Sinha, Samir K

2018-01-01

We examined the association between paramedic-initiated home care referrals and utilization of home care, 9-1-1, and Emergency Department (ED) services. This was a retrospective cohort study of individuals who received a paramedic-initiated home care referral after a 9-1-1 call between January 1, 2011 and December 31, 2012 in Toronto, Ontario, Canada. Home care, 9-1-1, and ED utilization were compared in the 6 months before and after home care referral. Nonparametric longitudinal regression was performed to assess changes in hours of home care service use and zero-inflated Poisson regression was performed to assess changes in the number of 9-1-1 calls and ambulance transports to ED. During the 24-month study period, 2,382 individuals received a paramedic-initiated home care referral. After excluding individuals who died, were hospitalized, or were admitted to a nursing home, the final study cohort was 1,851. The proportion of the study population receiving home care services increased from 18.2% to 42.5% after referral, representing 450 additional people receiving services. In longitudinal regression analysis, there was an increase of 17.4 hours in total services per person in the six months after referral (95% CI: 1.7-33.1, p = 0.03). The mean number of 9-1-1 calls per person was 1.44 (SD 9.58) before home care referral and 1.20 (SD 7.04) after home care referral in the overall study cohort. This represented a 10% reduction in 9-1-1 calls (95% CI: 7-13%, p < 0.001) in Poisson regression analysis. The mean number of ambulance transports to ED per person was 0.91 (SD 8.90) before home care referral and 0.79 (SD 6.27) after home care referral, representing a 7% reduction (95% CI: 3-11%, p < 0.001) in Poisson regression analysis. When only the participants with complete paramedic and home care records were included in the analysis, the reductions in 9-1-1 calls and ambulance transports to ED were attenuated but remained statistically significant. Paramedic-initiated home care referrals in Toronto were associated with improved access to and use of home care services and may have been associated with reduced 9-1-1 calls and ambulance transports to ED.

A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep

PubMed Central

Naya, Hugo; Urioste, Jorge I; Chang, Yu-Mei; Rodrigues-Motta, Mariana; Kremer, Roberto; Gianola, Daniel

2008-01-01

Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep. PMID:18558072

Estimating the Depth of the Navy Recruiting Market

DTIC Science & Technology

2016-09-01

recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. 14. SUBJECT...recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. vi THIS PAGE INTENTIONALLY LEFT...DEPTH OF THE NAVY RECRUITING MARKET by Emilie M. Monaghan September 2016 Thesis Advisor: Lyn R. Whitaker Second Reader: Jonathan K. Alt

Analyzing Seasonal Variations in Suicide With Fourier Poisson Time-Series Regression: A Registry-Based Study From Norway, 1969-2007.

PubMed

Bramness, Jørgen G; Walby, Fredrik A; Morken, Gunnar; Røislien, Jo

2015-08-01

Seasonal variation in the number of suicides has long been acknowledged. It has been suggested that this seasonality has declined in recent years, but studies have generally used statistical methods incapable of confirming this. We examined all suicides occurring in Norway during 1969-2007 (more than 20,000 suicides in total) to establish whether seasonality decreased over time. Fitting of additive Fourier Poisson time-series regression models allowed for formal testing of a possible linear decrease in seasonality, or a reduction at a specific point in time, while adjusting for a possible smooth nonlinear long-term change without having to categorize time into discrete yearly units. The models were compared using Akaike's Information Criterion and analysis of variance. A model with a seasonal pattern was significantly superior to a model without one. There was a reduction in seasonality during the period. Both the model assuming a linear decrease in seasonality and the model assuming a change at a specific point in time were both superior to a model assuming constant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonality in suicides has diminished. The additive Fourier Poisson time-series regression model would also be useful for studying other temporal phenomena with seasonal components. © 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.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

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.

Stagnation in Mortality Decline among Elders in the Netherlands

ERIC Educational Resources Information Center

Janssen, Fanny; Nusselder, Wilma J.; Looman, Caspar W. N.; Mackenbach, Johan P.; Kunst, Anton E.

2003-01-01

Purpose: This study assesses whether the stagnation of old-age (80+) mortality decline observed in The Netherlands in the 1980s continued in the 1990s and determines which factors contributed to this stagnation. Emphasis is on the role of smoking. Design and Methods: Poisson regression analysis with linear splines was applied to total and…

Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr × Holstein F2 population

PubMed Central

Silva, Fabyano Fonseca; Tunin, Karen P.; Rosa, Guilherme J.M.; da Silva, Marcos V.B.; Azevedo, Ana Luisa Souza; da Silva Verneque, Rui; Machado, Marco Antonio; Packer, Irineu Umberto

2011-01-01

Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable. PMID:22215960

Does attitude matter in computer use in Australian general practice? A zero-inflated Poisson regression analysis.

PubMed

Khan, Asaduzzaman; Western, Mark

The purpose of this study was to explore factors that facilitate or hinder effective use of computers in Australian general medical practice. This study is based on data extracted from a national telephone survey of 480 general practitioners (GPs) across Australia. Clinical functions performed by GPs using computers were examined using a zero-inflated Poisson (ZIP) regression modelling. About 17% of GPs were not using computer for any clinical function, while 18% reported using computers for all clinical functions. The ZIP model showed that computer anxiety was negatively associated with effective computer use, while practitioners' belief about usefulness of computers was positively associated with effective computer use. Being a female GP or working in partnership or group practice increased the odds of effectively using computers for clinical functions. To fully capitalise on the benefits of computer technology, GPs need to be convinced that this technology is useful and can make a difference.

Systematic review of treatment modalities for gingival depigmentation: a random-effects poisson regression analysis.

PubMed

Lin, Yi Hung; Tu, Yu Kang; Lu, Chun Tai; Chung, Wen Chen; Huang, Chiung Fang; Huang, Mao Suan; Lu, Hsein Kun

2014-01-01

Repigmentation variably occurs with different treatment methods in patients with gingival pigmentation. A systemic review was conducted of various treatment modalities for eliminating melanin pigmentation of the gingiva, comprising bur abrasion, scalpel surgery, cryosurgery, electrosurgery, gingival grafts, and laser techniques, to compare the recurrence rates (Rrs) of these treatment procedures. Electronic databases, including PubMed, Web of Science, Google, and Medline were comprehensively searched, and manual searches were conducted for studies published from January 1951 to June 2013. After applying inclusion and exclusion criteria, the final list of articles was reviewed in depth to achieve the objectives of this review. A Poisson regression was used to analyze the outcome of depigmentation using the various treatment methods. The systematic review was based on case reports mainly. In total, 61 eligible publications met the defined criteria. The various therapeutic procedures showed variable clinical results with a wide range of Rrs. A random-effects Poisson regression showed that cryosurgery (Rr = 0.32%), electrosurgery (Rr = 0.74%), and laser depigmentation (Rr = 1.16%) yielded superior result, whereas bur abrasion yielded the highest Rr (8.89%). Within the limit of the sampling level, the present evidence-based results show that cryosurgery exhibits the optimal predictability for depigmentation of the gingiva among all procedures examined, followed by electrosurgery and laser techniques. It is possible to treat melanin pigmentation of the gingiva with various methods and prevent repigmentation. Among those treatment modalities, cryosurgery, electrosurgery, and laser surgery appear to be the best choices for treating gingival pigmentation. © 2014 Wiley Periodicals, Inc.

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Poisson-Based Inference for Perturbation Models in Adaptive Spelling Training

ERIC Educational Resources Information Center

Baschera, Gian-Marco; Gross, Markus

2010-01-01

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

Tuberculosis and the role of war in the modern era.

PubMed

Drobniewski, F A; Verlander, N Q

2000-12-01

Tuberculosis (TB) remains a major global health problem; historically, major wars have increased TB notifications. This study evaluated whether modern conflicts worldwide affected TB notifications between 1975 and 1995. Dates of conflicts were obtained and matched with national TB notification data reported to the World Health Organization. Overall notification rates were calculated pre and post conflict. Poisson regression analysis was applied to all conflicts with sufficient data for detailed trend analysis. Thirty-six conflicts were identified, for which 3-year population and notification data were obtained. Overall crude TB notification rates were 81.9 and 105.1/100,000 pre and post start of conflict in these countries. Sufficient data existed in 16 countries to apply Poisson regression analysis to model 5-year pre and post start of conflict trends. This analysis indicated that the risk of presenting with TB in any country 2.5 years after the outbreak of conflict relative to 2.5 years before the outbreak was 1.016 (95%CI 0.9435-1.095). The modelling suggested that in the modern era war may not significantly damage efforts to control TB in the long term. This might be due to the limited scale of most of these conflicts compared to the large-scale civilian disruption associated with 'world wars'. The management of TB should be considered in planning post-conflict refugee and reconstruction programmes.

Differences in passenger car and large truck involved crash frequencies at urban signalized intersections: an exploratory analysis.

PubMed

Dong, Chunjiao; Clarke, David B; Richards, Stephen H; Huang, Baoshan

2014-01-01

The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car-truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method

PubMed Central

Zhang, Tingting; Kou, S. C.

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure. PMID:21258615

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.

PubMed

Zhang, Tingting; Kou, S C

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

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.

Predicting Hospital Admissions With Poisson Regression Analysis

DTIC Science & Technology

2009-06-01

East and Four West. Four East is where bariatric , general, neurologic, otolaryngology (ENT), ophthalmologic, orthopedic, and plastic surgery ...where care is provided for cardiovascular, thoracic, and vascular surgery patients. Figure 1 shows a bar graph for each unit, giving the proportion of...provided at NMCSD, or a study could be conducted on the amount of time that patients generally wait for elective surgeries . There is also the

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…

Does Group-Level Commitment Predict Employee Well-Being?: A Prospective Analysis.

PubMed

Clausen, Thomas; Christensen, Karl Bang; Nielsen, Karina

2015-11-01

To investigate the links between group-level affective organizational commitment (AOC) and individual-level psychological well-being, self-reported sickness absence, and sleep disturbances. A total of 5085 care workers from 301 workgroups in the Danish eldercare services participated in both waves of the study (T1 [2005] and T2 [2006]). The three outcomes were analyzed using linear multilevel regression analysis, multilevel Poisson regression analysis, and multilevel logistic regression analysis, respectively. Group-level AOC (T1) significantly predicted individual-level psychological well-being, self-reported sickness absence, and sleep disturbances (T2). The association between group-level AOC (T1) and psychological well-being (T2) was fully mediated by individual-level AOC (T1), and the associations between group-level AOC (T1) and self-reported sickness absence and sleep disturbances (T2) were partially mediated by individual-level AOC (T1). Group-level AOC is an important predictor of employee well-being in contemporary health care organizations.

Hospitalizations for primary care-sensitive conditions in Pelotas, Brazil: 1998 to 2012.

PubMed

Costa, Juvenal Soares Dias da; Teixeira, Ana Maria Ferreira Borges; Moraes, Mauricio; Strauch, Eliane Schneider; Silveira, Denise Silva da; Carret, Maria Laura Vidal; Fantinel, Everton

2017-01-01

To verify the hospitalization trend for primary care sensitive-conditions in Pelotas, Rio Grande do Sul, Brazil from 1998 to 2012. An ecological study compared hospitalizations rates of the city of Pelotas with the rest of state of Rio Grande do Sul. Analysis was conducted using direct standardization of rates, coefficients were stratified by sex and the Poisson regression was used. Hospitalizations for sensitive conditions decreased in Pelotas and Rio Grande do Sul. In Pelotas, a 63.8% decrease was detected in the period observed, and there was a 43.1% decrease in the state of Rio Grande do Sul. Poisson regression coefficients showed a decrease of 7% in Pelotas and of 4% in the rest of Rio Grande do Sul each year. During the study period, several changes were introduced in the Brazilian Unified Health System ("Sistema Único de Saúde") that may have influenced the results, including changes in administration, health funding, and a complete reworking of primary care through the creation of the Family Health Strategy program ("Estratégia Saúde da Família").

The Use of Illegal Drugs and Infectious Contagious Diseases: Knowledge and Intervention among Dockworkers

PubMed Central

Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; da Silva, Mara Regina Santos; de Farias, Francisca Lucélia Ribeiro; de Almeida, Marlise Capa Verde

2016-01-01

This study’s objective was to analyze the use of illegal drugs by dockworkers and provide risk communication regarding the use of illegal drugs and test for infectious contagious diseases among dockworkers. This cross-sectional study including an intervention addressed to 232 dockworkers, who were individually interviewed, as well as communication of risk with testing for infectious contagious diseases for 93 dockworkers from a city in the interior of Rio Grande do Sul, Brazil. Poisson regression analysis was used. Twenty-nine workers reported the use of illegal drugs. Poisson regression indicated that being a wharfage worker, smoker, having a high income, and heavier workload increases the prevalence of the use of illegal drugs. During risk communication, two workers were diagnosed with hepatitis B (2.2%), three (3.2%) with hepatitis C, two (2.2%) with syphilis. None of the workers, though, had HIV. This study provides evidence that can motivate further research on the topic and also lead to treatment of individuals to improve work safety, productivity, and the health of workers. PMID:26771625

The Use of Illegal Drugs and Infectious Contagious Diseases: Knowledge and Intervention among Dockworkers.

PubMed

Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; da Silva, Mara Regina Santos; de Farias, Francisca Lucélia Ribeiro; de Almeida, Marlise Capa Verde

2016-01-12

This study's objective was to analyze the use of illegal drugs by dockworkers and provide risk communication regarding the use of illegal drugs and test for infectious contagious diseases among dockworkers. This cross-sectional study including an intervention addressed to 232 dockworkers, who were individually interviewed, as well as communication of risk with testing for infectious contagious diseases for 93 dockworkers from a city in the interior of Rio Grande do Sul, Brazil. Poisson regression analysis was used. Twenty-nine workers reported the use of illegal drugs. Poisson regression indicated that being a wharfage worker, smoker, having a high income, and heavier workload increases the prevalence of the use of illegal drugs. During risk communication, two workers were diagnosed with hepatitis B (2.2%), three (3.2%) with hepatitis C, two (2.2%) with syphilis. None of the workers, though, had HIV. This study provides evidence that can motivate further research on the topic and also lead to treatment of individuals to improve work safety, productivity, and the health of workers.

WINPEPI updated: computer programs for epidemiologists, and their teaching potential

PubMed Central

2011-01-01

Background The WINPEPI computer programs for epidemiologists are designed for use in practice and research in the health field and as learning or teaching aids. The programs are free, and can be downloaded from the Internet. Numerous additions have been made in recent years. Implementation There are now seven WINPEPI programs: DESCRIBE, for use in descriptive epidemiology; COMPARE2, for use in comparisons of two independent groups or samples; PAIRSetc, for use in comparisons of paired and other matched observations; LOGISTIC, for logistic regression analysis; POISSON, for Poisson regression analysis; WHATIS, a "ready reckoner" utility program; and ETCETERA, for miscellaneous other procedures. The programs now contain 122 modules, each of which provides a number, sometimes a large number, of statistical procedures. The programs are accompanied by a Finder that indicates which modules are appropriate for different purposes. The manuals explain the uses, limitations and applicability of the procedures, and furnish formulae and references. Conclusions WINPEPI is a handy resource for a wide variety of statistical routines used by epidemiologists. Because of its ready availability, portability, ease of use, and versatility, WINPEPI has a considerable potential as a learning and teaching aid, both with respect to practical procedures in the planning and analysis of epidemiological studies, and with respect to important epidemiological concepts. It can also be used as an aid in the teaching of general basic statistics. PMID:21288353

Regression: The Apple Does Not Fall Far From the Tree.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-05-15

Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

The Role of Depressive Symptoms, Family Invalidation and Behavioral Impulsivity in the Occurrence and Repetition of Non-Suicidal Self-Injury in Chinese Adolescents: A 2-Year Follow-Up Study

ERIC Educational Resources Information Center

You, Jianing; Leung, Freedom

2012-01-01

This study used zero-inflated poisson regression analysis to examine the role of depressive symptoms, family invalidation, and behavioral impulsivity in the occurrence and repetition of non-suicidal self-injury among Chinese community adolescents over a 2-year period. Participants, 4782 high school students, were assessed twice during the…

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.

Climate variations and salmonellosis transmission in Adelaide, South Australia: a comparison between regression models

NASA Astrophysics Data System (ADS)

Zhang, Ying; Bi, Peng; Hiller, Janet

2008-01-01

This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.

A meta-model analysis of a finite element simulation for defining poroelastic properties of intervertebral discs.

PubMed

Nikkhoo, Mohammad; Hsu, Yu-Chun; Haghpanahi, Mohammad; Parnianpour, Mohamad; Wang, Jaw-Lin

2013-06-01

Finite element analysis is an effective tool to evaluate the material properties of living tissue. For an interactive optimization procedure, the finite element analysis usually needs many simulations to reach a reasonable solution. The meta-model analysis of finite element simulation can be used to reduce the computation of a structure with complex geometry or a material with composite constitutive equations. The intervertebral disc is a complex, heterogeneous, and hydrated porous structure. A poroelastic finite element model can be used to observe the fluid transferring, pressure deviation, and other properties within the disc. Defining reasonable poroelastic material properties of the anulus fibrosus and nucleus pulposus is critical for the quality of the simulation. We developed a material property updating protocol, which is basically a fitting algorithm consisted of finite element simulations and a quadratic response surface regression. This protocol was used to find the material properties, such as the hydraulic permeability, elastic modulus, and Poisson's ratio, of intact and degenerated porcine discs. The results showed that the in vitro disc experimental deformations were well fitted with limited finite element simulations and a quadratic response surface regression. The comparison of material properties of intact and degenerated discs showed that the hydraulic permeability significantly decreased but Poisson's ratio significantly increased for the degenerated discs. This study shows that the developed protocol is efficient and effective in defining material properties of a complex structure such as the intervertebral disc.

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.

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

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…

Nonlinear Poisson Equation for Heterogeneous Media

PubMed Central

Hu, Langhua; Wei, Guo-Wei

2012-01-01

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. PMID:22947937

Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung

NASA Astrophysics Data System (ADS)

Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani

2017-03-01

Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.

Nonlinear Poisson equation for heterogeneous media.

PubMed

Hu, Langhua; Wei, Guo-Wei

2012-08-22

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China

PubMed Central

Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao

2018-01-01

Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. PMID:29561835

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.

PubMed

Liu, Kangkang; Zhu, Yanshan; Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

2018-03-01

This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention.

Log-normal frailty models fitted as Poisson generalized linear mixed models.

PubMed

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Atmospheric pollutants and hospital admissions due to pneumonia in children

PubMed Central

Negrisoli, Juliana; Nascimento, Luiz Fernando C.

2013-01-01

OBJECTIVE: To analyze the relationship between exposure to air pollutants and hospitalizations due to pneumonia in children of Sorocaba, São Paulo, Brazil. METHODS: Time series ecological study, from 2007 to 2008. Daily data were obtained from the State Environmental Agency for Pollution Control for particulate matter, nitric oxide, nitrogen dioxide, ozone, besides air temperature and relative humidity. The data concerning pneumonia admissions were collected in the public health system of Sorocaba. Correlations between the variables of interest using Pearson cofficient were calculated. Models with lags from zero to five days after exposure to pollutants were performed to analyze the association between the exposure to environmental pollutants and hospital admissions. The analysis used the generalized linear model of Poisson regression, being significant p<0.05. RESULTS: There were 1,825 admissions for pneumonia, with a daily mean of 2.5±2.1. There was a strong correlation between pollutants and hospital admissions, except for ozone. Regarding the Poisson regression analysis with the multi-pollutant model, only nitrogen dioxide was statistically significant in the same day (relative risk - RR=1.016), as well as particulate matter with a lag of four days (RR=1.009) after exposure to pollutants. CONCLUSIONS: There was an acute effect of exposure to nitrogen dioxide and a later effect of exposure to particulate matter on children hospitalizations for pneumonia in Sorocaba. PMID:24473956

Marginalized zero-inflated negative binomial regression with application to dental caries

PubMed Central

Preisser, John S.; Das, Kalyan; Long, D. Leann; Divaris, Kimon

2015-01-01

The zero-inflated negative binomial regression model (ZINB) is often employed in diverse fields such as dentistry, health care utilization, highway safety, and medicine to examine relationships between exposures of interest and overdispersed count outcomes exhibiting many zeros. The regression coefficients of ZINB have latent class interpretations for a susceptible subpopulation at risk for the disease/condition under study with counts generated from a negative binomial distribution and for a non-susceptible subpopulation that provides only zero counts. The ZINB parameters, however, are not well-suited for estimating overall exposure effects, specifically, in quantifying the effect of an explanatory variable in the overall mixture population. In this paper, a marginalized zero-inflated negative binomial regression (MZINB) model for independent responses is proposed to model the population marginal mean count directly, providing straightforward inference for overall exposure effects based on maximum likelihood estimation. Through simulation studies, the finite sample performance of MZINB is compared to marginalized zero-inflated Poisson, Poisson, and negative binomial regression. The MZINB model is applied in the evaluation of a school-based fluoride mouthrinse program on dental caries in 677 children. PMID:26568034

Prediction of forest fires occurrences with area-level Poisson mixed models.

PubMed

Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo

2015-05-01

The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.

Utility of correlation techniques in gravity and magnetic interpretation

NASA Technical Reports Server (NTRS)

Chandler, V. W.; Koski, J. S.; Braice, L. W.; Hinze, W. J.

1977-01-01

Internal correspondence uses Poisson's Theorem in a moving-window linear regression analysis between the anomalous first vertical derivative of gravity and total magnetic field reduced to the pole. The regression parameters provide critical information on source characteristics. The correlation coefficient indicates the strength of the relation between magnetics and gravity. Slope value gives delta j/delta sigma estimates of the anomalous source. The intercept furnishes information on anomaly interference. Cluster analysis consists of the classification of subsets of data into groups of similarity based on correlation of selected characteristics of the anomalies. Model studies are used to illustrate implementation and interpretation procedures of these methods, particularly internal correspondence. Analysis of the results of applying these methods to data from the midcontinent and a transcontinental profile shows they can be useful in identifying crustal provinces, providing information on horizontal and vertical variations of physical properties over province size zones, validating long wavelength anomalies, and isolating geomagnetic field removal problems.

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.

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%.

Development and Validation of a Practical Instrument for Injury Prevention: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT).

PubMed

Sun, Yi; Arning, Martin; Bochmann, Frank; Börger, Jutta; Heitmann, Thomas

2018-06-01

The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.

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

Properties of the Bivariate Delayed Poisson Process

DTIC Science & Technology

1974-07-01

and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a

Pick Your Poisson: A Tutorial on Analyzing Counts of Student Victimization Data

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2012-01-01

School violence research is often concerned with infrequently occurring events such as counts of the number of bullying incidents or fights a student may experience. Analyzing count data using ordinary least squares regression may produce improbable predicted values, and as a result of regression assumption violations, result in higher Type I…

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

Modeling urban coastal flood severity from crowd-sourced flood reports using Poisson regression and Random Forest

NASA Astrophysics Data System (ADS)

Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2018-04-01

Sea level rise has already caused more frequent and severe coastal flooding and this trend will likely continue. Flood prediction is an essential part of a coastal city's capacity to adapt to and mitigate this growing problem. Complex coastal urban hydrological systems however, do not always lend themselves easily to physically-based flood prediction approaches. This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data. Two data-driven models, Poisson regression and Random Forest regression, are trained to predict the number of flood reports per storm event as a proxy for flood severity, given extensive environmental data (i.e., rainfall, tide, groundwater table level, and wind conditions) as input. The method is demonstrated using data from Norfolk, Virginia USA from September 2010 to October 2016. Quality-controlled, crowd-sourced street flooding reports ranging from 1 to 159 per storm event for 45 storm events are used to train and evaluate the models. Random Forest performed better than Poisson regression at predicting the number of flood reports and had a lower false negative rate. From the Random Forest model, total cumulative rainfall was by far the most dominant input variable in predicting flood severity, followed by low tide and lower low tide. These methods serve as a first step toward using data-driven methods for spatially and temporally detailed coastal urban flood prediction.

Use of ACE-inhibitors and falls in patients with Parkinson's disease.

PubMed

Laudisio, Alice; Lo Monaco, Maria Rita; Silveri, Maria Caterina; Bentivoglio, Anna Rita; Vetrano, Davide L; Pisciotta, Maria Stella; Brandi, Vincenzo; Bernabei, Roberto; Zuccalà, Giuseppe

2017-05-01

Falls represent a major concern in patients with Parkinson's disease (PD); however, currently acknowledged treatments for PD are not effective in reducing the risk of falling. The aim was to assess the association of use of ACE-inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) with falls among patients with PD. We analysed data of 194 elderly with PD attending a geriatric Day Hospital. Self-reported history of falls that occurred over the last year, as well as use of drugs, including ACEIs and angiotensin II receptor blockers (ARBs) were recorded. The association of the occurrence of any falls with use of ACEIs, and ARBs was assessed by logistic regression analysis. The association between the number of falls and use of ACEIs, and ARBs was assessed according to Poisson regression. In logistic regression, after adjusting for potential confounders, use of ACEIs was associated with a reduced probability of falling over the last year (OR=0.15, 95% CI=0.03-0.81; P=0.028). This association did not vary with blood pressure levels (P for the interaction term=0.528). Also, using Poisson regression, use of ACEIs predicted a reduced number of falls among participants who fell (PR=0.31; 95% CI=0.10-0.94; P=0.039). No association was found between use of ARBs and falls. Our results indicate that use of ACEIs might be independently associated with reduced probability, and a reduced number of falls among patients with PD. Dedicated studies are needed to define the single agents and dosages that might most effectively reduce the risk of falling in clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Trends in Mortality After Primary Cytoreductive Surgery for Ovarian Cancer: A Systematic Review and Metaregression of Randomized Clinical Trials and Observational Studies.

PubMed

Di Donato, Violante; Kontopantelis, Evangelos; Aletti, Giovanni; Casorelli, Assunta; Piacenti, Ilaria; Bogani, Giorgio; Lecce, Francesca; Benedetti Panici, Pierluigi

2017-06-01

Primary cytoreductive surgery (PDS) followed by platinum-based chemotherapy is the cornerstone of treatment and the absence of residual tumor after PDS is universally considered the most important prognostic factor. The aim of the present analysis was to evaluate trend and predictors of 30-day mortality in patients undergoing primary cytoreduction for ovarian cancer. Literature was searched for records reporting 30-day mortality after PDS. All cohorts were rated for quality. Simple and multiple Poisson regression models were used to quantify the association between 30-day mortality and the following: overall or severe complications, proportion of patients with stage IV disease, median age, year of publication, and weighted surgical complexity index. Using the multiple regression model, we calculated the risk of perioperative mortality at different levels for statistically significant covariates of interest. Simple regression identified median age and proportion of patients with stage IV disease as statistically significant predictors of 30-day mortality. When included in the multiple Poisson regression model, both remained statistically significant, with an incidence rate ratio of 1.087 for median age and 1.017 for stage IV disease. Disease stage was a strong predictor, with the risk estimated to increase from 2.8% (95% confidence interval 2.02-3.66) for stage III to 16.1% (95% confidence interval 6.18-25.93) for stage IV, for a cohort with a median age of 65 years. Metaregression demonstrated that increased age and advanced clinical stage were independently associated with an increased risk of mortality, and the combined effects of both factors greatly increased the risk.

Method selection and adaptation for distributed monitoring of infectious diseases for syndromic surveillance.

PubMed

Xing, Jian; Burkom, Howard; Tokars, Jerome

2011-12-01

Automated surveillance systems require statistical methods to recognize increases in visit counts that might indicate an outbreak. In prior work we presented methods to enhance the sensitivity of C2, a commonly used time series method. In this study, we compared the enhanced C2 method with five regression models. We used emergency department chief complaint data from US CDC BioSense surveillance system, aggregated by city (total of 206 hospitals, 16 cities) during 5/2008-4/2009. Data for six syndromes (asthma, gastrointestinal, nausea and vomiting, rash, respiratory, and influenza-like illness) was used and was stratified by mean count (1-19, 20-49, ≥50 per day) into 14 syndrome-count categories. We compared the sensitivity for detecting single-day artificially-added increases in syndrome counts. Four modifications of the C2 time series method, and five regression models (two linear and three Poisson), were tested. A constant alert rate of 1% was used for all methods. Among the regression models tested, we found that a Poisson model controlling for the logarithm of total visits (i.e., visits both meeting and not meeting a syndrome definition), day of week, and 14-day time period was best. Among 14 syndrome-count categories, time series and regression methods produced approximately the same sensitivity (<5% difference) in 6; in six categories, the regression method had higher sensitivity (range 6-14% improvement), and in two categories the time series method had higher sensitivity. When automated data are aggregated to the city level, a Poisson regression model that controls for total visits produces the best overall sensitivity for detecting artificially added visit counts. This improvement was achieved without increasing the alert rate, which was held constant at 1% for all methods. These findings will improve our ability to detect outbreaks in automated surveillance system data. Published by Elsevier Inc.

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.

A Critical Examination of Figure of Merit (FOM). Assessing the Goodness-of-Fit in Gamma/X-ray Peak Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croft, S.; Favalli, Andrea; Weaver, Brian Phillip

2015-10-06

In this paper we develop and investigate several criteria for assessing how well a proposed spectral form fits observed spectra. We consider the classical improved figure of merit (FOM) along with several modifications, as well as criteria motivated by Poisson regression from the statistical literature. We also develop a new FOM that is based on the statistical idea of the bootstrap. A spectral simulator has been developed to assess the performance of these different criteria under multiple data configurations.

Using multi-year national survey cohorts for period estimates: an application of weighted discrete Poisson regression for assessing annual national mortality in US adults with and without diabetes, 2000-2006.

PubMed

Cheng, Yiling J; Gregg, Edward W; Rolka, Deborah B; Thompson, Theodore J

2016-12-15

Monitoring national mortality among persons with a disease is important to guide and evaluate progress in disease control and prevention. However, a method to estimate nationally representative annual mortality among persons with and without diabetes in the United States does not currently exist. The aim of this study is to demonstrate use of weighted discrete Poisson regression on national survey mortality follow-up data to estimate annual mortality rates among adults with diabetes. To estimate mortality among US adults with diabetes, we applied a weighted discrete time-to-event Poisson regression approach with post-stratification adjustment to national survey data. Adult participants aged 18 or older with and without diabetes in the National Health Interview Survey 1997-2004 were followed up through 2006 for mortality status. We estimated mortality among all US adults, and by self-reported diabetes status at baseline. The time-varying covariates used were age and calendar year. Mortality among all US adults was validated using direct estimates from the National Vital Statistics System (NVSS). Using our approach, annual all-cause mortality among all US adults ranged from 8.8 deaths per 1,000 person-years (95% confidence interval [CI]: 8.0, 9.6) in year 2000 to 7.9 (95% CI: 7.6, 8.3) in year 2006. By comparison, the NVSS estimates ranged from 8.6 to 7.9 (correlation = 0.94). All-cause mortality among persons with diabetes decreased from 35.7 (95% CI: 28.4, 42.9) in 2000 to 31.8 (95% CI: 28.5, 35.1) in 2006. After adjusting for age, sex, and race/ethnicity, persons with diabetes had 2.1 (95% CI: 2.01, 2.26) times the risk of death of those without diabetes. Period-specific national mortality can be estimated for people with and without a chronic condition using national surveys with mortality follow-up and a discrete time-to-event Poisson regression approach with post-stratification adjustment.

Quantification of integrated HIV DNA by repetitive-sampling Alu-HIV PCR on the basis of poisson statistics.

PubMed

De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos

2014-06-01

Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

An Analysis of the Number of Medical Malpractice Claims and Their Amounts

PubMed Central

Bonetti, Marco; Cirillo, Pasquale; Musile Tanzi, Paola; Trinchero, Elisabetta

2016-01-01

Starting from an extensive database, pooling 9 years of data from the top three insurance brokers in Italy, and containing 38125 reported claims due to alleged cases of medical malpractice, we use an inhomogeneous Poisson process to model the number of medical malpractice claims in Italy. The intensity of the process is allowed to vary over time, and it depends on a set of covariates, like the size of the hospital, the medical department and the complexity of the medical operations performed. We choose the combination medical department by hospital as the unit of analysis. Together with the number of claims, we also model the associated amounts paid by insurance companies, using a two-stage regression model. In particular, we use logistic regression for the probability that a claim is closed with a zero payment, whereas, conditionally on the fact that an amount is strictly positive, we make use of lognormal regression to model it as a function of several covariates. The model produces estimates and forecasts that are relevant to both insurance companies and hospitals, for quality assurance, service improvement and cost reduction. PMID:27077661

Examining the spatially non-stationary associations between the second demographic transition and infant mortality: A Poisson GWR approach.

PubMed

Yang, Tse-Chuan; Shoff, Carla; Matthews, Stephen A

2013-01-01

Based on ecological studies, second demographic transition (SDT) theorists concluded that some areas in the US were in vanguard of the SDT compared to others, implying spatial nonstationarity may be inherent in the SDT process. Linking the SDT to the infant mortality literature, we sought out to answer two related questions: Are the main components of the SDT, specifically marriage postponement, cohabitation, and divorce, associated with infant mortality? If yes, do these associations vary across the US? We applied global Poisson and geographically weighted Poisson regression (GWPR) models, a place-specific analytic approach, to county-level data in the contiguous US. After accounting for the racial/ethnic and socioeconomic compositions of counties and prenatal care utilization, we found (1) marriage postponement was negatively related to infant mortality in the southwestern states, but positively associated with infant mortality in parts of Indiana, Kentucky, and Tennessee, (2) cohabitation rates were positively related to infant mortality, and this relationship was stronger in California, coastal Virginia, and the Carolinas than other areas, and (3) a positive association between divorce rates and infant mortality in southwestern and northeastern areas of the US. These spatial patterns suggested that the associations between the SDT and infant mortality were stronger in the areas in vanguard of the SDT than in others. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the SDT and infant mortality.

Occurrence of depressive tendency and associated social factors among elderly persons forced by the Great East Japan Earthquake and nuclear disaster to live as long-term evacuees: a prospective cohort study.

PubMed

Kuroda, Yujiro; Iwasa, Hajime; Goto, Aya; Yoshida, Kazuki; Matsuda, Kumiko; Iwamitsu, Yumi; Yasumura, Seiji

2017-09-03

This study examined the incidence of depression and associated factors among elderly persons from Iitate village after the March 2011 earthquake. This was a prospective cohort study. As a baseline survey, in May 2010 a self-assessment Basic Checklist (BCL) was distributed to 1611 elderly villagers, of which 1277 responded. Of these respondents, 885 without a tendency to depression (69.3%) were given a follow-up survey in May 2013. The BCL was used to assess depression tendency, instrumental activities of daily living (IADL), physical function, nutritional status, oral function, homeboundness, cognitive function and social activities. Univariate analysis was used to examine differences in risk between those with a presence of depression tendency (PDT) and those without (non-PDT) depending on demographic and BCL variables. Variables found to be significant were analysed by Poisson regression analysis. Of the 438 respondents in the second survey, 163 (37.2%) showed depression tendency. PDT risk was significantly increased by female gender, age, history of diabetes and cognitive disorder. It was significantly reduced by increased IADL. Engagement in social activities decreased PDT risk in rental accommodation. Renters faced a higher risk of PDT than persons evacuated in groups to purpose-built housing. The inclusion of social activities in the multivariate Poisson regression analysis weakened this effect. Female gender, a history of diabetes, reduced IADL and a tendency to cognitive disorder each independently affected PDT risk. These findings may inform future responses to earthquakes and the technical disasters that may accompany them. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Impact of hepatitis B vaccination on acute hepatitis B epidemiology in European Union/European Economic Area countries, 2006 to 2014

PubMed Central

Miglietta, Alessandro; Quinten, Chantal; Lopalco, Pier Luigi; Duffell, Erika

2018-01-01

Hepatitis B prevention in European Union/European Economic Area (EU/EEA) countries relies on vaccination programmes. We describe the epidemiology of acute hepatitis B virus (HBV) at country and EU/EEA level during 2006–2014. Using a multi-level mixed-effects Poisson regression model we assessed differences in the acute HBV infection notification rates between groups of countries that started universal HBV vaccination before/in vs after 1995; implemented or not a catch-up strategy; reached a vaccine coverage ≥ 95% vs < 95% and had a hepatitis B surface antigen prevalence ≥ 1% vs < 1%. Joinpoint regression analysis was used to assess trends by groups of countries, and additional Poisson regression models to evaluate the association between three-dose HBV vaccine coverage and acute HBV infection notification rates at country and EU/EEA level. The EU/EEA acute HBV infection notification rate decreased from 1.6 per 100,000 population in 2006 to 0.7 in 2014. No differences (p > 0.05) were found in the acute HBV infection notification rates between groups of countries, while as vaccine coverage increased, such rates decreased (p < 0.01). Countries with universal HBV vaccination before 1995, a catch-up strategy, and a vaccine coverage ≥ 95% had significant decreasing trends (p < 0.01). Ending HBV transmission in Europe by 2030 will require high vaccine coverage delivered through universal programmes, supported, where appropriate, by catch-up vaccination campaigns. PMID:29439751

Spatial variation of pneumonia hospitalization risk in Twin Cities metro area, Minnesota.

PubMed

Iroh Tam, P Y; Krzyzanowski, B; Oakes, J M; Kne, L; Manson, S

2017-11-01

Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.

[The short-term effects of air pollution on mortality. The results of the EMECAM project in the city of Vigo, 1991-94. Estudio Multicéntrico Español sobre la Relación entre la Contaminación Atmosférica y la Mortalidad].

PubMed

Taracido Trunk, M; Figueiras, A; Castro Lareo, I

1999-01-01

In the Autonomous Region of Galicia, no study has been made of the impacts of air pollution on human health, despite the fact that several of its major cities have moderate levels of pollution. Therefore, we have considered the need of making this study in the city of Vigo. The main objective of this analysis is that of analyzing the short-term impact of air pollution on the daily death rate for all reasons in the city of Vigo throughout the 1991-1994 period, by using the procedure for analysis set out as part of the EMECAM Project. The daily fluctuations in the number of deaths for all causes with the exception of the external ones are listed with the daily fluctuations of sulfur dioxide and particles using Poisson regression models. A non-parametric model is also used in order to better control the confusion variables. Using the Poisson regression model, no significant relationships have been found to exist between the pollutants and the death rate. In the non-parametric model, a relationship was found between the concentration of particles on the day immediately prior to the date of death and the death rate, an effect which remains unchanged on including the autoregressive terms. Particle-based air pollution is a health risk despite the average levels of this pollutant falling within the air quality guideline levels in the city of Vigo.

[Geographical distribution of mortality caused by stomach, trachea, bronchi and lung malignant tumors in Chile].

PubMed

Icaza N, M Gloria; Núñez F, M Loreto; Torres A, Francisco J; Díaz S, Nora L; Várela G, David E

2007-11-01

Maps have played a critical role in public health since 1855, when John Snow associated a cholera outbreak with contaminated water source in London. After cardiovascular diseases, cancer is the second leading cause of death in Chile. Cancer was responsible for 22.7% of all deaths in 1997-2004 period. To describe the geographical distribution of stomach, trachea, bronchi and lung cancer mortality. Mortality statistics for the years 1997-2004, published by the National Statistics Institute and Chilean Ministry of Health, were used. The standardized mortality ratio (SMR) for sex and age quinquennium was calculated for 341 counties in the country. A hierarchical Bayesian analysis of Poisson regression models for SMR was performed. The maps were developed using adjusted SMR (or smoothed) by the Poisson model. There is an excess mortality caused by stomach cancer in south central Chile, from Teno to Valdivia. There is an excess mortality caused by trachea, bronchi and lung cancer in northern Chile, from Copiapó to Iquique. The geographical analysis of mortality caused by cancer shows cluster of counties with an excess risk. These areas should be considered for health care decision making and resource allocation.

Epidemiology of occupational injury among cleaners in the healthcare sector.

PubMed

Alamgir, Hasanat; Yu, Shicheng

2008-09-01

The cleaning profession has been associated with multiple ergonomic and chemical hazards which elevate the risk for occupational injury. This study investigated the epidemiology of occupational injury among cleaners in healthcare work settings in the Canadian province of British Columbia. Incidents of occupational injury among cleaners, resulting in lost time from work or medical care, over a period of 1 year in two healthcare regions were extracted from a standardized operational database and with person-years obtained from payroll data. Detailed analysis was conducted using Poisson regression modeling. A total of 145 injuries were identified among cleaners, with an annual incidence rate of 32.1 per 100 person-years. After adjustment for age, gender, subsector, facility, experience and employment status, Poisson regression models demonstrated that a significantly higher relative risk (RR) of all injury, musculoskeletal injury and cuts was associated with cleaning work in acute care facilities, compared with long-term care facilities. Female cleaners were at a higher RR of all injuries and contusions than male cleaners. A lower risk of all injury and allergy and irritation incidents among part-time or casual workers was found. Cleaners with >10 years of experience were at significantly lower risk for all injury, contusion and allergy and irritation incidents. Cleaners were found to be at an elevated risk of all injury categories compared with healthcare workers in general.

Using perinatal morbidity scoring tools as a primary study outcome.

PubMed

Hutcheon, Jennifer A; Bodnar, Lisa M; Platt, Robert W

2017-11-01

Perinatal morbidity scores are tools that score or weight different adverse events according to their relative severity. Perinatal morbidity scores are appealing for maternal-infant health researchers because they provide a way to capture a broad range of adverse events to mother and newborn while recognising that some events are considered more serious than others. However, they have proved difficult to implement as a primary outcome in applied research studies because of challenges in testing if the scores are significantly different between two or more study groups. We outline these challenges and describe a solution, based on Poisson regression, that allows differences in perinatal morbidity scores to be formally evaluated. The approach is illustrated using an existing maternal-neonatal scoring tool, the Adverse Outcome Index, to evaluate the safety of labour and delivery before and after the closure of obstetrical services in small rural communities. Applying the proposed Poisson regression to the case study showed a protective risk ratio for adverse outcome following closures as compared with the original analysis, where no difference was found. This approach opens the door for considerably broader use of perinatal morbidity scoring tools as a primary outcome in applied population and clinical maternal-infant health research studies. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Treatment of singularities in cracked bodies

NASA Technical Reports Server (NTRS)

Shivakumar, K. N.; Raju, I. S.

1990-01-01

Three-dimensional finite-element analyses of middle-crack tension (M-T) and bend specimens subjected to mode I loadings were performed to study the stress singularity along the crack front. The specimen was modeled using 20-node isoparametric elements. The displacements and stresses from the analysis were used to estimate the power of singularities using a log-log regression analysis along the crack front. The analyses showed that finite-sized cracked bodies have two singular stress fields of the form rho = C sub o (theta, z) r to the -1/2 power + D sub o (theta, phi) R to the lambda rho power. The first term is the cylindrical singularity with the power -1/2 and is dominant over the middle 96 pct (for Poisson's ratio = 0.3) of the crack front and becomes nearly zero at the free surface. The second singularity is a vertex singularity with the vertex point located at the intersection of the crack front and the free surface. The second term is dominant at the free surface and becomes nearly zero away from the boundary layer. The thickness of the boundary layer depends on Poisson's ratio of the material and is independent of the specimen type. The thickness of the boundary layer varied from 0 pct to about 5 pct of the total specimen thickness as Poisson's ratio varied from 0.0 to 0.45. Because there are two singular stress fields near the free surface, the strain energy release rate (G) is an appropriate parameter to measure the severity of the crack.

Treatment of singularities in cracked bodies

NASA Technical Reports Server (NTRS)

Shivakumar, K. N.; Raju, I. S.

1989-01-01

Three-dimensional finite-element analyses of middle-crack tension (M-T) and bend specimens subjected to mode I loadings were performed to study the stress singularity along the crack front. The specimen was modeled using 20-node isoparametric elements. The displacements and stresses from the analysis were used to estimate the power of singularities using a log-log regression analysis along the crack front. The analyses showed that finite-sized cracked bodies have two singular stress fields of the form rho = C sub o (theta, z) r to the -1/2 power + D sub o (theta, phi) R to the lambda rho power. The first term is the cylindrical singularity with the power -1/2 and is dominant over the middle 96 pct (for Poisson's ratio = 0.3) of the crack front and becomes nearly zero at the free surface. The second singularity is a vertex singularity with the vertex point located at the intersection of the crack front and the free surface. The second term is dominant at the free surface and becomes nearly zero away from the the boundary layer. The thickness of the boundary layer depends on Poisson's ratio of the material and is independent of the specimen type. The thickness of the boundary layer varied from 0 pct to about 5 pct of the total specimen thickness as Poisson's ratio varied from 0.0 to 0.45. Because there are two singular stress fields near the free surface, the strain energy release rate (G) is an appropriate parameter to measure the severity of the crack.

Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea.

PubMed

Gómez-Barroso, Diana; García-Carrasco, Emely; Herrador, Zaida; Ncogo, Policarpo; Romay-Barja, María; Ondo Mangue, Martín Eka; Nseng, Gloria; Riloha, Matilde; Santana, Maria Angeles; Valladares, Basilio; Aparicio, Pilar; Benito, Agustín

2017-04-12

The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea. From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors. A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6-15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13-1.51 and IRR: 1.44; 95% CI 1.25-1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62-0.86). A significant cluster inland of the district, in rural areas has been found. This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.

Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.

PubMed

Renner, Ian W; Warton, David I

2013-03-01

Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.

Study of non-Hodgkin's lymphoma mortality associated with industrial pollution in Spain, using Poisson models

PubMed Central

Ramis, Rebeca; Vidal, Enrique; García-Pérez, Javier; Lope, Virginia; Aragonés, Nuria; Pérez-Gómez, Beatriz; Pollán, Marina; López-Abente, Gonzalo

2009-01-01

Background Non-Hodgkin's lymphomas (NHLs) have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER) is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs) associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model). Results Only proximity of paper industries to population centres (>2 km) could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27). Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of industrial pollution on the health of the population. PMID:19159450

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

Modeling laser velocimeter signals as triply stochastic Poisson processes

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1976-01-01

Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

PubMed Central

Chan, King-Pan; Chan, Kwok-Hung; Wong, Wilfred Hing-Sang; Peiris, J. S. Malik; Wong, Chit-Ming

2011-01-01

Background Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. Methods and Findings We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. Conclusion The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong. PMID:21412433

Disability rates for cardiovascular and psychological disorders among autoworkers by job category, facility type, and facility overtime hours.

PubMed

Landsbergis, Paul A; Janevic, Teresa; Rothenberg, Laura; Adamu, Mohammed T; Johnson, Sylvia; Mirer, Franklin E

2013-07-01

We examined the association between long work hours, assembly line work and stress-related diseases utilizing objective health and employment data from an employer's administrative databases. A North American automobile manufacturing company provided data for claims for sickness, accident and disability insurance (work absence of at least 4 days) for cardiovascular disease (CVD), hypertension and psychological disorders, employee demographics, and facility hours worked per year for 1996-2001. Age-adjusted claim rates and age-adjusted rate ratios were calculated using Poisson regression, except for comparisons between production and skilled trades workers owing to lack of age denominator data by job category. Associations between overtime hours and claim rates by facility were examined by Poisson regression and multi-level Poisson regression. Claims for hypertension, coronary heart disease, CVD, and psychological disorders were associated with facility overtime hours. We estimate that a facility with 10 more overtime hours per week than another facility would have 4.36 more claims for psychological disorders, 2.33 more claims for CVD, and 3.29 more claims for hypertension per 1,000 employees per year. Assembly plants had the highest rates of claims for most conditions. Production workers tended to have higher rates of claims than skilled trades workers. Data from an auto manufacturer's administrative databases suggest that autoworkers working long hours, and assembly-line workers relative to skilled trades workers or workers in non-assembly facilities, have a higher risk of hypertension, CVD, and psychological disorders. Occupational disease surveillance and disease prevention programs need to fully utilize such administrative data. Copyright © 2013 Wiley Periodicals, Inc.

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...

Added sugars and periodontal disease in young adults: an analysis of NHANES III data.

PubMed

Lula, Estevam C O; Ribeiro, Cecilia C C; Hugo, Fernando N; Alves, Cláudia M C; Silva, Antônio A M

2014-10-01

Added sugar consumption seems to trigger a hyperinflammatory state and may result in visceral adiposity, dyslipidemia, and insulin resistance. These conditions are risk factors for periodontal disease. However, the role of sugar intake in the cause of periodontal disease has not been adequately studied. We evaluated the association between the frequency of added sugar consumption and periodontal disease in young adults by using NHANES III data. Data from 2437 young adults (aged 18-25 y) who participated in NHANES III (1988-1994) were analyzed. We estimated the frequency of added sugar consumption by using food-frequency questionnaire responses. We considered periodontal disease to be present in teeth with bleeding on probing and a probing depth ≥3 mm at one or more sites. We evaluated this outcome as a discrete variable in Poisson regression models and as a categorical variable in multinomial logistic regression models adjusted for sex, age, race-ethnicity, education, poverty-income ratio, tobacco exposure, previous diagnosis of diabetes, and body mass index. A high consumption of added sugars was associated with a greater prevalence of periodontal disease in middle [prevalence ratio (PR): 1.39; 95% CI: 1.02, 1.89] and upper (PR: 1.42; 95% CI: 1.08, 1.85) tertiles of consumption in the adjusted Poisson regression model. The upper tertile of added sugar intake was associated with periodontal disease in ≥2 teeth (PR: 1.73; 95% CI: 1.19, 2.52) but not with periodontal disease in only one tooth (PR: 0.85; 95% CI: 0.54, 1.34) in the adjusted multinomial logistic regression model. A high frequency of consumption of added sugars is associated with periodontal disease, independent of traditional risk factors, suggesting that this consumption pattern may contribute to the systemic inflammation observed in periodontal disease and associated noncommunicable diseases. © 2014 American Society for Nutrition.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

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.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Complete synchronization of the global coupled dynamical network induced by Poisson noises.

PubMed

Guo, Qing; Wan, Fangyi

2017-01-01

The different Poisson noise-induced complete synchronization of the global coupled dynamical network is investigated. Based on the stability theory of stochastic differential equations driven by Poisson process, we can prove that Poisson noises can induce synchronization and sufficient conditions are established to achieve complete synchronization with probability 1. Furthermore, numerical examples are provided to show the agreement between theoretical and numerical analysis.

Impacts of floods on dysentery in Xinxiang city, China, during 2004-2010: a time-series Poisson analysis.

PubMed

Ni, Wei; Ding, Guoyong; Li, Yifei; Li, Hongkai; Jiang, Baofa

2014-01-01

Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42-1.670) and 1.74 (95% CI: 1.56-1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods.

Impacts of floods on dysentery in Xinxiang city, China, during 2004–2010: a time-series Poisson analysis

PubMed Central

Ni, Wei; Ding, Guoyong; Li, Yifei; Li, Hongkai; Jiang, Baofa

2014-01-01

Background Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. Objectives We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. Design A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. Results A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42–1.670) and 1.74 (95% CI: 1.56–1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. Conclusions This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods. PMID:25098726

Burn mortality in patients with preexisting cardiovascular disease.

PubMed

Knowlin, Laquanda; Reid, Trista; Williams, Felicia; Cairns, Bruce; Charles, Anthony

2017-08-01

Burn shock, a complex process, which develops following burn leads to severe and unique derangement of cardiovascular function. Patients with preexisting comorbidities such as cardiovascular diseases may be more susceptible. We therefore sought to examine the impact of preexisting cardiovascular disease on burn outcomes. A retrospective analysis of patients admitted to a regional burn center from 2002 to 2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, and length of ICU/hospital stay. Bivariate analysis was performed and Poisson regression modeling was utilized to estimate the incidence of being in the ICU and mortality. There were a total of 5332 adult patients admitted over the study period. 6% (n=428) had a preexisting cardiovascular disease. Cardiovascular disease patients had a higher mortality rate (16%) compared to those without cardiovascular disease (3%, p<0.001). The adjusted Poisson regression model to estimate incidence risk of being in intensive care unit in patients with cardiovascular disease was 33% higher compared to those without cardiovascular disease (IRR=1.33, 95% CI=1.22-1.47). The risk for mortality is 42% higher (IRR=1.42, 95% CI=1.10-1.84) for patients with pre-existing cardiovascular disease compared to those without cardiovascular disease after controlling for other covariates. Preexisting cardiovascular disease significantly increases the risk of intensive care unit admission and mortality in burn patients. Given the increasing number of Americans with cardiovascular diseases, there will likely be a greater number of individuals at risk for worse outcomes following burn. This knowledge can help with burn prognostication. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

Fertility is reduced in women and in men with type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium (T1DGC).

PubMed

Wiebe, Julia C; Santana, Angelo; Medina-Rodríguez, Nathan; Hernández, Marta; Nóvoa, Javier; Mauricio, Dídac; Wägner, Ana M

2014-12-01

A recent Finnish study described reduced fertility in patients with childhood-onset type 1 diabetes. The Type 1 Diabetes Genetics Consortium (T1DGC) is an international programme studying the genetics and pathogenesis of type 1 diabetes that includes families with the disease. Our aim was to assess fertility, defined as number of offspring, in the affected and unaffected siblings included in the T1DGC. Clinical information from participants aged ≥18 years at the time of examination was included in the present analysis. The number of offspring of affected and unaffected siblings was compared (in families including both) and the influence of birth year, disease duration and age of onset was assessed, the last in affected siblings only, using Poisson regression models. A total of 3010 affected and 801 unaffected adult siblings that belonged to 1761 families were assessed. The mean number of offspring was higher in the unaffected than in the affected individuals, and the difference between the two groups was more pronounced in women than men. Poisson regression analysis showed that both sex and birth cohort significantly affected the differences between groups. In the affected siblings, adult onset (≥18 years), female sex and older birth cohort were associated with higher fertility. Patients with type 1 diabetes have fewer children than their unaffected siblings. This effect is more evident in women and in older birth cohorts. Onset of type 1 diabetes as an adult rather than a child is associated with a higher number of offspring, even after accounting for birth cohort and disease duration.

Chronic arsenic exposure and risk of infant mortality in two areas of Chile.

PubMed Central

Hopenhayn-Rich, C; Browning, S R; Hertz-Picciotto, I; Ferreccio, C; Peralta, C; Gibb, H

2000-01-01

Chronic arsenic exposure has been associated with a range of neurologic, vascular, dermatologic, and carcinogenic effects. However, limited research has been directed at the association of arsenic exposure and human reproductive health outcomes. The principal aim of this study was to investigate the trends in infant mortality between two geographic locations in Chile: Antofagasta, which has a well-documented history of arsenic exposure from naturally contaminated water, and Valparaíso, a comparable low-exposure city. The arsenic concentration in Antofagasta's public drinking water supply rose substantially in 1958 with the introduction of a new water source, and remained elevated until 1970. We used a retrospective study design to examine time and location patterns in infant mortality between 1950 and 1996, using univariate statistics, graphical techniques, and Poisson regression analysis. Results of the study document the general declines in late fetal and infant mortality over the study period in both locations. The data also indicate an elevation of the late fetal, neonatal, and postneonatal mortality rates for Antofagasta, relative to Valparaíso, for specific time periods, which generally coincide with the period of highest arsenic concentration in the drinking water of Antofagasta. Poisson regression analysis yielded an elevated and significant association between arsenic exposure and late fetal mortality [rate ratio (RR) = 1.7; 95% confidence interval (CI), 1.5-1.9], neonatal mortality (RR = 1.53; CI, 1.4-1.7), and postneonatal mortality (RR = 1.26; CI, 1.2-1.3) after adjustment for location and calendar time. The findings from this investigation may support a role for arsenic exposure in increasing the risk of late fetal and infant mortality. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:10903622

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.

Finite element solution of torsion and other 2-D Poisson equations

NASA Technical Reports Server (NTRS)

Everstine, G. C.

1982-01-01

The NASTRAN structural analysis computer program may be used, without modification, to solve two dimensional Poisson equations such as arise in the classical Saint Venant torsion problem. The nonhomogeneous term (the right-hand side) in the Poisson equation can be handled conveniently by specifying a gravitational load in a "structural" analysis. The use of an analogy between the equations of elasticity and those of classical mathematical physics is summarized in detail.

Gingival enlargement in orthodontic patients: Effect of treatment duration.

PubMed

Pinto, Alice Souza; Alves, Luana Severo; Zenkner, Júlio Eduardo do Amaral; Zanatta, Fabrício Batistin; Maltz, Marisa

2017-10-01

In this study, we aimed to assess the effect of the duration of fixed orthodontic treatment on gingival enlargement (GE) in adolescents and young adults. The sample consisted of 260 subjects (ages, 10-30 years) divided into 4 groups: patients with no fixed orthodontic appliances (G0) and patients undergoing orthodontic treatment for 1 year (G1), 2 years (G2), or 3 years (G3). Participants completed a structured questionnaire on sociodemographic characteristics and oral hygiene habits. Clinical examinations were conducted by a calibrated examiner and included the plaque index, the gingival index, and the Seymour index. Poisson regression models were used to assess the association between group and GE. We observed increasing means of plaque, gingivitis, and GE in G0, G1, and G2. No significant differences were observed between G2 and G3. Adjusted Poisson regression analysis showed that patients undergoing orthodontic treatment had a 20 to 28-fold increased risk for GE than did those without orthodontic appliances (G1, rate ratio [RR] = 20.2, 95% CI = 9.0-45.3; G2, RR = 27.0, 95% CI = 12.1-60.3; G3 = 28.1; 95% CI = 12.6-62.5). The duration of orthodontic treatment significantly influenced the occurrence of GE. Oral hygiene instructions and motivational activities should target adolescents and young adults undergoing orthodontic treatment. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Analysis of the burns profile and the admission rate of severely burned adult patient to the National Burn Center of Chile after the 2010 earthquake.

PubMed

Albornoz, Claudia; Villegas, Jorge; Sylvester, Marilu; Peña, Veronica; Bravo, Iside

2011-06-01

Chile is located in the Ring of Fire, in South America. An earthquake 8.8° affected 80% of the population in February 27th, 2010. This study was conducted to assess any change in burns profile caused by the earthquake. This was an ecologic study. We compared the 4 months following the earthquake in 2009 and 2010. age, TBSA, deep TBSA, agent, specific mortality rate and rate of admissions to the National burn Center of Chile. Mann-Whitney test and a Poisson regression were performed. Age, agent, TBSA and deep TBSA percentages did not show any difference. Mortality rate was lower in 2010 (0.52 versus 1.22 per 1,000,000 habitants) but no meaningful difference was found (Poisson regression p = 0.06). Admission rate was lower in 2010, 4.6 versus 5.6 per 1,000,000 habitants, but no differences were found (p = 0.26). There was not any admissions directly related to the earthquake. As we do not have incidence registries in Chile, we propose to use the rate of admission to the National Burn Reference Center as an incidence estimator. There was not any significant difference in the burn profile, probably because of the time of the earthquake (3 am). We conclude the earthquake did not affect the way the Chilean people get burned. Copyright © 2011 Elsevier Ltd and ISBI. All rights reserved.

Higher mortality in areas of lower socioeconomic position measured by a single index of deprivation in Japan.

PubMed

Fukuda, Yoshiharu; Nakamura, Keiko; Takano, Takehito

2007-03-01

To formulate an index representing area deprivation and elucidate the relation between the index and mortality in Japan. Ecological study for prefectures (N=47) and municipalities (N=3366) across Japan. Based on socioeconomic indicators of seven domains of deprivation (i.e. unemployment, overcrowding, low social class and poverty, low education, no home ownership, low income and vulnerable group), an index was formulated using the z-scoring method. The relation between the index and mortality was examined by correlation analysis, hierarchical Poisson regression and comparison of standardized mortality ratio according to the index. The deprivation index ranged from -7.48 to 10.98 for prefectures and from -16.97 to 13.82 for municipalities. The index was significantly positively correlated with prefectural mortality, especially in the population aged under 74 years: r=0.65 for men and r=0.41 for women. At the municipal level, hierarchical Poisson regression showed a significant positive coefficient of the index to mortality for both men and women, and excess mortality in the most deprived fifth compared to the least deprived fifth was 26.4% in men and 11.8% in women. We formulated a deprivation index, which was substantially related to mortality at the prefectural and municipal levels. This study highlights the higher risk of dying among populations in socially disadvantaged areas and encourages the use of indices representing area socioeconomic conditions for further studies of area effects on health.

Saint-Venant end effects for materials with negative Poisson's ratios

NASA Technical Reports Server (NTRS)

Lakes, R. S.

1992-01-01

Results are presented from an analysis of Saint-Venant end effects for materials with negative Poisson's ratio. Examples are presented showing that slow decay of end stress occurs in circular cylinders of negative Poisson's ratio, whereas a sandwich panel containing rigid face sheets and a compliant core exhibits no anomalous effects for negative Poisson's ratio (but exhibits slow stress decay for core Poisson's ratios approaching 0.5). In sand panels with stiff but not perfectly rigid face sheets, a negative Poisson's ratio results in end stress decay, which is faster than it would be otherwise. It is suggested that the slow decay previously predicted for sandwich strips in plane deformation as a result of the geometry can be mitigated by the use of a negative Poisson's ratio material for the core.

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.

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

Geographical variation in the incidence of childhood leukaemia in Manitoba.

PubMed

Torabi, Mahmoud; Singh, Harminder; Galloway, Katie; Israels, Sara J

2015-11-01

Identification of geographical areas and ecological factors associated with higher incidence of childhood leukaemias can direct further study for preventable factors and location of health services to manage such individuals. The aim of this study was to describe the geographical variation and the socio-demographic factors associated with childhood leukaemia in Manitoba. Information on childhood leukaemia incidence between 1992 and 2008 was obtained from the Canadian Cancer Registry and the socio-demographic characteristics for the area of residence from the 2006 Canadian Census. Bayesian spatial Poisson mixed models were used to describe the geographical variation of childhood leukaemia and to determine the association between childhood leukaemia and socio-demographic factors. The south-eastern part of the province had a higher incidence of childhood leukaemia than other parts of the province. In the age and sex-adjusted Poisson regression models, areas with higher proportions of visible minorities and immigrant residents had higher childhood leukaemia incidence rate ratios. In the saturated Poisson regression model, the childhood leukaemia rates were higher in areas with higher proportions of immigrant residents. Unemployment rates were not a significant factor in leukaemia incidence. In Manitoba, areas with higher proportions of immigrants experience higher incidence rates of childhood leukaemia. We have identified geographical areas with higher incidence, which require further study and attention. © 2015 The Authors. Journal of Paediatrics and Child Health © 2015 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Impact of a prevention bundle on Clostridium difficile infection rates in a hospital in the Southeastern United States.

PubMed

Davis, Bionca M; Yin, Jingjing; Blomberg, Doug; Fung, Isaac Chun-Hai

2016-12-01

We sought to assess the impact of a multicomponent prevention program on hospital-acquired Clostridium difficile infections in a hospital in the Southeastern United States. We collected retrospective data of 140 patients from years 2009-2014 and applied the Poisson regression model for analysis. We did not find any significant associations of increased risk of Clostridium difficile infections for the preintervention group. Further studies are needed to test multifaceted bundles in hospitals with high infection rates. Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

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

The influence of climate variables on dengue in Singapore.

PubMed

Pinto, Edna; Coelho, Micheline; Oliver, Leuda; Massad, Eduardo

2011-12-01

In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC₁ (Principal component 1) is represented by temperature and rainfall and PC₂ (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10°C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.

Depression and HIV risk among men who have sex with men in Tanzania.

PubMed

Ahaneku, Hycienth; Ross, Michael W; Nyoni, Joyce E; Selwyn, Beatrice; Troisi, Catherine; Mbwambo, Jessie; Adeboye, Adeniyi; McCurdy, Sheryl

2016-01-01

Studies have shown high rates of depression among men who have sex with men (MSM) in developed countries. Studies have also shown association between depression and HIV risk among MSM. However, very little research has been done on depression among African MSM. We assessed depression and HIV risk among a sample of MSM in Tanzania. We reviewed data on 205 MSM who were recruited from two Tanzanian cities using the respondent driven sampling method. Demographic and behavioral data were collected using a structured questionnaire. HIV and sexually transmitted infections data were determined from biological tests. Depression scores were assessed using the Patient Health Questionnaire (PHQ-9). For the analysis, depression scores were dichotomized as depressed (PHQ > 4) and not depressed (PHQ ≤ 4). Bivariate and multivariable Poisson regression analyses were conducted to assess factors associated with depression. The prevalence of depression in the sample was 46.3%. The mean (±SD) age of the sample was 25 (±5) years. In bivariate analysis, depression was associated with self-identifying as gay (p = .001), being HIV positive (p < .001: <8% of MSM knew they were HIV infected) and having a high number of sexual partners in the last 6 months (p = .001). Depression was also associated with sexual (p = .007), physical (p = .003) and verbal (p < .001) abuse. In the Poisson regression analysis, depression was associated with verbal abuse (APR = 1.91, CI = 1.30-2.81). Depression rates were high among MSM in Tanzania. It is also associated with abuse, HIV and HIV risk behaviors. Thus, reducing the risk of depression may be helpful in reducing the risk of HIV among MSM in Africa. We recommend the colocation of mental health and HIV preventive services as a cost-effective means of addressing both depression and HIV risk among MSM in Africa.

Investigation of the association between the test day milk fat-protein ratio and clinical mastitis using a Poisson regression approach for analysis of time-to-event data.

PubMed

Zoche-Golob, V; Heuwieser, W; Krömker, V

2015-09-01

The objective of the present study was to investigate the association between the milk fat-protein ratio and the incidence rate of clinical mastitis including repeated cases of clinical mastitis to determine the usefulness of this association to monitor metabolic disorders as risk factors for udder health. Herd records from 10 dairy herds of Holstein cows in Saxony, Germany, from September 2005-2011 (36,827 lactations of 17,657 cows) were used for statistical analysis. A mixed Poisson regression model with the weekly incidence rate of clinical mastitis as outcome variable was fitted. The model included repeated events of the outcome, time-varying covariates and multilevel clustering. Because the recording of clinical mastitis might have been imperfect, a probabilistic bias analysis was conducted to assess the impact of the misclassification of clinical mastitis on the conventional results. The lactational incidence of clinical mastitis was 38.2%. In 36.2% and 34.9% of the lactations, there was at least one dairy herd test day with a fat-protein ratio of <1.0 or >1.5, respectively. Misclassification of clinical mastitis was assumed to have resulted in bias towards the null. A clinical mastitis case increased the incidence rate of following cases of the same cow. Fat-protein ratios of <1.0 and >1.5 were associated with higher incidence rates of clinical mastitis depending on week in milk. The effect of a fat-protein ratio >1.5 on the incidence rate of clinical mastitis increased considerably over the course of lactation, whereas the effect of a fat-protein ratio <1.0 decreased. Fat-protein ratios <1.0 or >1.5 on the precedent test days of all cows irrespective of their time in milk seemed to be better predictors for clinical mastitis than the first test day results per lactation. Copyright © 2015 Elsevier B.V. All rights reserved.

Detecting isotopic ratio outliers

NASA Astrophysics Data System (ADS)

Bayne, C. K.; Smith, D. H.

An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers.

Minimum risk wavelet shrinkage operator for Poisson image denoising.

PubMed

Cheng, Wu; Hirakawa, Keigo

2015-05-01

The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

Generation of Plausible Hurricane Tracks for Preparedness Exercises

DTIC Science & Technology

2017-04-25

wind extents are simulated by Poisson regression and temporal filtering . The un-optimized MATLAB code runs in less than a minute and is integrated into...of real hurricanes. After wind radii have been simulated for the entire track, median filtering , attenuation over land, and smoothing clean up the wind

Inhalant Use among Indiana School Children, 1991-2004

ERIC Educational Resources Information Center

Ding, Kele; Torabi, Mohammad R.; Perera, Bilesha; Jun, Mi Kyung; Jones-McKyer, E. Lisako

2007-01-01

Objective: To examine the prevalence and trend of inhalant use among Indiana public school students. Methods: The Alcohol, Tobacco, and Other Drug Use among Indiana Children and Adolescents surveys conducted annually between 1991 and 2004 were reanalyzed using 2-way moving average, Poisson regression, and ANOVA tests. Results: The prevalence had…

Seasonally adjusted birth frequencies follow the Poisson distribution.

PubMed

Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A

2015-12-15

Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p < 0.01). The fundamental model with year and month as explanatory variables is significantly improved (p < 0.001) by adding day of the week as an explanatory variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.

Sight Impairment registration due to stroke-A small yet significant rise?

PubMed

Bunce, Catey; Zekite, Antra; Wormald, Richard; Rowe, Fiona

2017-12-01

In the United Kingdom, when an individual's sight falls to and remains at a certain threshold, they may be offered registration as sight impaired. Recent analysis of causes of registrable sight impairment in England/Wales indicated that visual impairment due to stroke had increased as a proportionate cause of sight loss. We aim to assess whether there is evidence of an increase in incidence of certification for sight impairment due to stroke in England/Wales between 2008 and 2014. The number of certifications with a main cause of sight impairment being stroke was obtained from the Certifications Office London. Directly standardized rates per 100,000 were computed with 95% confidence intervals and examined. Poisson regression was used to assess evidence of trend over time. In the year ending 31st March 2008, 992 people were newly certified with stroke with an estimated DSR of 2.1 (2.0 to 2.2) per 100,000 persons at risk. In the year ending March 31st 2014, there were 1310 certifications with a DSR of 2.5 (2.4 to 2.7). Figures were higher for men than women. Poisson regression indicated an estimated incidence rate ratio of 1.03 per year with 95% confidence intervals of 1.028 to 1.051, P  < .001. These data suggest a small but statistically significant increase in the incidence of certifiable visual impairment due to stroke between 2008 and 2014. Figures are, however, considerably lower than estimated, perhaps suggesting that more should be done to address the visual needs of those who have suffered stroke.

An evaluation of the Motion Picture Association of America's treatment of violence in PG-, PG-13-, and R-rated films.

PubMed

Jenkins, Lucille; Webb, Theresa; Browne, Nick; Afifi, A A; Kraus, Jess

2005-05-01

The purpose of this study was to determine whether the Motion Picture Association of America's ratings system distinguishes among the 3 primary rating categories (PG, PG-13, and R) with respect to violence based on a study of the 100 top-grossing films of 1994. The Motion Picture Association of America assigns age-based ratings for every film that is released in the United States accompanied by the reasons for the rating. A data abstraction instrument was designed to code each act of violence within the sample of 100 films. A series of Poisson regression models were used to examine the association among rating, seriousness of violence, and primary reason for the rating assignment. The total average number of violent acts within each film by rating category increased from PG (14) to PG-13 (20) to R (32). However, using results from the Poisson models, it is clear that the rating does not predict the frequency of violence in films. For all 3 rating categories, the predicted number of violent acts is almost identical for films with violence as a primary descriptor and films with the highest level of seriousness (R = 62.4 acts, PG-13 = 55.2 acts, and PG = 56.1 acts). The regression analysis shows that the rating does not predict the frequency of violence that occurs in films. Frequency of violence alone is not the most important criterion for the assignment of rating. The content descriptors and average seriousness of films are better measures of the violence than rating assignment.

Avoidable hospitalizations in Switzerland: a small area analysis on regional variation, density of physicians, hospital supply and rurality.

PubMed

Berlin, Claudia; Busato, André; Rosemann, Thomas; Djalali, Sima; Maessen, Maud

2014-07-03

Avoidable hospitalizations (AH) are hospital admissions for diseases and conditions that could have been prevented by appropriate ambulatory care. We examine regional variation of AH in Switzerland and the factors that determine AH. We used hospital service areas, and data from 2008-2010 hospital discharges in Switzerland to examine regional variation in AH. Age and sex standardized AH were the outcome variable, and year of admission, primary care physician density, medical specialist density, rurality, hospital bed density and type of hospital reimbursement system were explanatory variables in our multilevel poisson regression. Regional differences in AH were as high as 12-fold. Poisson regression showed significant increase of all AH over time. There was a significantly lower rate of all AH in areas with more primary care physicians. Rates increased in areas with more specialists. Rates of all AH also increased where the proportion of residences in rural communities increased. Regional hospital capacity and type of hospital reimbursement did not have significant associations. Inconsistent patterns of significant determinants were found for disease specific analyses. The identification of regions with high and low AH rates is a starting point for future studies on unwarranted medical procedures, and may help to reduce their incidence. AH have complex multifactorial origins and this study demonstrates that rurality and physician density are relevant determinants. The results are helpful to improve the performance of the outpatient sector with emphasis on local context. Rural and urban differences in health care delivery remain a cause of concern in Switzerland.

Marginal regression models for clustered count data based on zero-inflated Conway-Maxwell-Poisson distribution with applications.

PubMed

Choo-Wosoba, Hyoyoung; Levy, Steven M; Datta, Somnath

2016-06-01

Community water fluoridation is an important public health measure to prevent dental caries, but it continues to be somewhat controversial. The Iowa Fluoride Study (IFS) is a longitudinal study on a cohort of Iowa children that began in 1991. The main purposes of this study (http://www.dentistry.uiowa.edu/preventive-fluoride-study) were to quantify fluoride exposures from both dietary and nondietary sources and to associate longitudinal fluoride exposures with dental fluorosis (spots on teeth) and dental caries (cavities). We analyze a subset of the IFS data by a marginal regression model with a zero-inflated version of the Conway-Maxwell-Poisson distribution for count data exhibiting excessive zeros and a wide range of dispersion patterns. In general, we introduce two estimation methods for fitting a ZICMP marginal regression model. Finite sample behaviors of the estimators and the resulting confidence intervals are studied using extensive simulation studies. We apply our methodologies to the dental caries data. Our novel modeling incorporating zero inflation, clustering, and overdispersion sheds some new light on the effect of community water fluoridation and other factors. We also include a second application of our methodology to a genomic (next-generation sequencing) dataset that exhibits underdispersion. © 2015, The International Biometric Society.

Impact of previous ART and of ART initiation on outcome of HIV-associated tuberculosis.

PubMed

Girardi, Enrico; Palmieri, Fabrizio; Angeletti, Claudio; Vanacore, Paola; Matteelli, Alberto; Gori, Andrea; Carbonara, Sergio; Ippolito, Giuseppe

2012-01-01

Combination antiretroviral therapy (cART) has progressively decreased mortality of HIV-associated tuberculosis .To date, however, limited data on tuberculosis treatment outcomes among coinfected patients who are not ART-naive at the time of tuberculosis diagnosis are available. A multicenter, observational study enrolled 246 HIV-infected patients diagnosed with tuberculosis, in 96 Italian infectious diseases hospital units, who started tuberculosis treatment. A polytomous logistic regression model was used to identify baseline factors associated with the outcome. A Poisson regression model was used to explain the effect of ART during tuberculosis treatment on mortality, as a time-varying covariate, adjusting for baseline characteristics. Outcomes of tuberculosis treatment were as follows: 130 (52.8%) were successfully treated, 36 (14.6%) patients died in a median time of 2 months (range: 0-16), and 80 (32.6%) had an unsuccessful outcome. Being foreign born or injecting drug users was associated with unsuccessful outcomes. In multivariable Poisson regression, cART during tuberculosis treatment decreased the risk of death, while this risk increased for those who were not ART-naive at tuberculosis diagnosis. ART during tuberculosis treatment is associated with a substantial reduction of death rate among HIV-infected patients. However, patients who are not ART-naive when they develop tuberculosis remain at elevated risk of death.

Bayesian analysis of volcanic eruptions

NASA Astrophysics Data System (ADS)

Ho, Chih-Hsiang

1990-10-01

The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.

Elasticity of α-Cristobalite: A Silicon Dioxide with a Negative Poisson's Ratio

NASA Astrophysics Data System (ADS)

Yeganeh-Haeri, Amir; Weidner, Donald J.; Parise, John B.

1992-07-01

Laser Brillouin spectroscopy was used to determine the adiabatic single-crystal elastic stiffness coefficients of silicon dioxide (SiO_2) in the α-cristobalite structure. This SiO_2 polymorph, unlike other silicas and silicates, exhibits a negative Poisson's ratio; α-cristobalite contracts laterally when compressed and expands laterally when stretched. Tensorial analysis of the elastic coefficients shows that Poisson's ratio reaches a maximum value of -0.5 in some directions, whereas averaged values for the single-phased aggregate yield a Poisson's ratio of -0.16.

Response analysis of a class of quasi-linear systems with fractional derivative excited by Poisson white noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yongge; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Yang, Guidong

The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractionalmore » order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.« less

Impact of Homeland Security Alert level on calls to a law enforcement peer support hotline.

PubMed

Omer, Saad B; Barnett, Daniel J; Castellano, Cherie; Wierzba, Rachel K; Hiremath, Girish S; Balicer, Ran D; Everly, George S

2007-01-01

The Homeland Security Advisory System (HSAS) was established by the Department of Homeland Security to communicate the risk of a terrorist event. In order to explore the potential psychological impacts of HSAS we analyzed the effects of terror alerts on the law enforcement community. We used data from the New Jersey Cop 2 Cop crisis intervention hotline. Incidence Rate Ratios--interpreted as average relative increases in the daily number of calls to the Cop 2 Cop hotline during an increased alert period--were computed from Poisson models. The hotline received a total of 4,145 initial calls during the study period. The mean daily number of calls was higher during alert level elevation compared to prior 7 days (7.68 vs. 8.00). In the Poisson regression analysis, the Incidence Rate Ratios of number of calls received during elevated alert levels compared to the reference period of seven days preceding each change in alert were close to 1, with confidence intervals crossing 1 (i.e. not statistically significant) for all lag periods evaluated. This investigation, in the context of New Jersey law enforcement personnel, does not support the concern that elevating the alert status places undue stress upon alert recipients.

Questionable Validity of Poisson Assumptions in a Combined Loglinear/MDS Mapping Model.

ERIC Educational Resources Information Center

Gleason, John M.

1993-01-01

This response to an earlier article on a combined log-linear/MDS model for mapping journals by citation analysis discusses the underlying assumptions of the Poisson model with respect to characteristics of the citation process. The importance of empirical data analysis is also addressed. (nine references) (LRW)

Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial

NASA Astrophysics Data System (ADS)

Amaliana, Luthfatul; Sa'adah, Umu; Wayan Surya Wardhani, Ni

2017-12-01

Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation. Negative Binomial (NB) regression is an alternative method when over dispersion happens in Poisson regression. However, the data containing over dispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The purpose of this study are: (1) to model Tetanus Neonatorum cases in East Java Province with 71.05 percent proportion of zero-inflation by using NB and ZINB regression, (2) to obtain the best model. The result of this study indicates that ZINB is better than NB regression with smaller AIC.

[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

Evaluating for a geospatial relationship between radon levels and thyroid cancer in Pennsylvania.

PubMed

Goyal, Neerav; Camacho, Fabian; Mangano, Joseph; Goldenberg, David

2015-01-01

To determine whether there is an association between radon levels and the rise in incidence of thyroid cancer in Pennsylvania. Epidemiological study of the state of Pennsylvania. We used information from the Pennsylvania Cancer Registry and the Pennsylvania Department of Energy. From the registry, information regarding thyroid incidence by county and zip code was recorded. Information regarding radon levels per county was recorded from the state. Poisson regression models were fit predicting county-level thyroid incidence and change as a function of radon/lagged radon levels. To account for measurement error in the radon levels, a Bayesian Model extending the Poisson models was fit. Geospatial clustering analysis was also performed. No association was noted between cumulative radon levels and thyroid incidence. In the Poisson modeling, no significant association was noted between county radon level and thyroid cancer incidence (P = .23). Looking for a lag between the radon level and its effect, no significant effect was seen with a lag of 0 to 6 years between exposure and effect (P = .063 to P = .59). The Bayesian models also failed to show a statistically significant association. A cluster of high thyroid cancer incidence was found in western Pennsylvania. Through a variety of models, no association was elicited between annual radon levels recorded in Pennsylvania and the rising incidence of thyroid cancer. However, a cluster of thyroid cancer incidence was found in western Pennsylvania. Further studies may be helpful in looking for other exposures or associations. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Statistical modeling of dental unit water bacterial test kit performance.

PubMed

Cohen, Mark E; Harte, Jennifer A; Stone, Mark E; O'Connor, Karen H; Coen, Michael L; Cullum, Malford E

2007-01-01

While it is important to monitor dental water quality, it is unclear whether in-office test kits provide bacterial counts comparable to the gold standard method (R2A). Studies were conducted on specimens with known bacterial concentrations, and from dental units, to evaluate test kit accuracy across a range of bacterial types and loads. Colony forming units (CFU) were counted for samples from each source, using R2A and two types of test kits, and conformity to Poisson distribution expectations was evaluated. Poisson regression was used to test for effects of source and device, and to estimate rate ratios for kits relative to R2A. For all devices, distributions were Poisson for low CFU/mL when only beige-pigmented bacteria were considered. For higher counts, R2A remained Poisson, but kits exhibited over-dispersion. Both kits undercounted relative to R2A, but the degree of undercounting was reasonably stable. Kits did not grow pink-pigmented bacteria from dental-unit water identified as Methylobacterium rhodesianum. Only one of the test kits provided results with adequate reliability at higher bacterial concentrations. Undercount bias could be estimated for this device and used to adjust test kit results. Insensitivity to methylobacteria spp. is problematic.

[Study on influence of floods on bacillary dysentery incidence in Liaoning province, 2004 -2010].

PubMed

Xu, X; Liu, Z D; Han, D B; Xu, Y Q; Jiang, B F

2016-05-01

To understand the influence of floods on bacillary dysentery in Liaoning province. The monthly surveillance data of bacillary dysentery, floods, meteorological and demographic data in Liaoning from 2004 to 2010 were collected. Panel Poisson regression analysis was conducted to evaluate the influence of floods on the incidence of bacillary dysentery in Liaoning. The mean monthly morbidity of bacillary dysentery was 2.17 per 100 000 during the study period, the bacillary dysentery cases mainly occurred in during July-September. Spearman correlation analysis showed that no lagged effect was detected in the influence of floods on the incidence of bacillary dysentery. After adjusting the influence of meteorological factors, panel data analysis showed that the influence of floods on the incidence of bacillary dysentery existed and the incidence rate ratio was 1.439 4(95%CI: 1.408 1-1.471 4). Floods could significantly increase the risk of bacillary dysentery for population in Liaoning.

[The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city].

PubMed

Xiao, Hong; Tian, Huai-yu; Zhang, Xi-xing; Zhao, Jian; Zhu, Pei-juan; Liu, Ru-chun; Chen, Tian-mu; Dai, Xiang-yu; Lin, Xiao-ling

2011-10-01

To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.

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…

Modeling both of the number of pausibacillary and multibacillary leprosy patients by using bivariate poisson regression

NASA Astrophysics Data System (ADS)

Winahju, W. S.; Mukarromah, A.; Putri, S.

2015-03-01

Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.

Statistical guides to estimating the number of undiscovered mineral deposits: an example with porphyry copper deposits

USGS Publications Warehouse

Singer, Donald A.; Menzie, W.D.; Cheng, Qiuming; Bonham-Carter, G. F.

2005-01-01

Estimating numbers of undiscovered mineral deposits is a fundamental part of assessing mineral resources. Some statistical tools can act as guides to low variance, unbiased estimates of the number of deposits. The primary guide is that the estimates must be consistent with the grade and tonnage models. Another statistical guide is the deposit density (i.e., the number of deposits per unit area of permissive rock in well-explored control areas). Preliminary estimates and confidence limits of the number of undiscovered deposits in a tract of given area may be calculated using linear regression and refined using frequency distributions with appropriate parameters. A Poisson distribution leads to estimates having lower relative variances than the regression estimates and implies a random distribution of deposits. Coefficients of variation are used to compare uncertainties of negative binomial, Poisson, or MARK3 empirical distributions that have the same expected number of deposits as the deposit density. Statistical guides presented here allow simple yet robust estimation of the number of undiscovered deposits in permissive terranes. 

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment

PubMed Central

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso

2016-01-01

ABSTRACT Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. IMPORTANCE We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. PMID:27940547

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment.

PubMed

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu

2017-02-15

Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. Copyright © 2017 Koyama et al.

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

The Use of a Poisson Regression to Evaluate Antihistamines and Fatal Aircraft Mishaps in Instrument Meteorological Conditions.

PubMed

Gildea, Kevin M; Hileman, Christy R; Rogers, Paul; Salazar, Guillermo J; Paskoff, Lawrence N

2018-04-01

Research indicates that first-generation antihistamine usage may impair pilot performance by increasing the likelihood of vestibular illusions, spatial disorientation, and/or cognitive impairment. Second- and third-generation antihistamines generally have fewer impairing side effects and are approved for pilot use. We hypothesized that toxicological findings positive for second- and third-generation antihistamines are less likely to be associated with pilots involved in fatal mishaps than first-generation antihistamines. The evaluated population consisted of 1475 U.S. civil pilots fatally injured between September 30, 2008, and October 1, 2014. Mishap factors evaluated included year, weather conditions, airman rating, recent airman flight time, quarter of year, and time of day. Due to the low prevalence of positive antihistamine findings, a count-based model was selected, which can account for rare outcomes. The means and variances were close for both regression models supporting the assumption that the data follow a Poisson distribution; first-generation antihistamine mishap airmen (N = 582, M = 0.17, S2 = 0.17) with second- and third-generation antihistamine mishap airmen (N = 116, M = 0.20, S2 = 0.18). The data indicate fewer airmen with second- and third-generation antihistamines than first-generation antihistamines in their system are fatally injured while flying in IMC conditions. Whether the lower incidence is a factor of greater usage of first-generation antihistamines versus second- and third-generation antihistamines by the pilot population or fewer deleterious side effects with second- and third-generation antihistamines is unclear. These results engender cautious optimism, but additional research is necessary to determine why these differences exist.Gildea KM, Hileman CR, Rogers P, Salazar GJ, Paskoff LN. The use of a Poisson regression to evaluate antihistamines and fatal aircraft mishaps in instrument meteorological conditions. Aerosp Med Hum Perform. 2018; 89(4):389-395.

Fine particulate air pollution and all-cause mortality within the Harvard Six-Cities Study: variations in risk by period of exposure.

PubMed

Villeneuve, Paul J; Goldberg, Mark S; Krewski, Daniel; Burnett, Richard T; Chen, Yue

2002-11-01

We used Poisson regression methods to examine the relation between temporal changes in the levels of fine particulate air pollution (PM(2.5)) and the risk of mortality among participants of the Harvard Six Cities longitudinal study. Our analyses were based on 1430 deaths that occurred between 1974 and 1991 in a cohort that accumulated 105,714 person-years of follow-up. For each city, indices of PM(2.5) were derived using daily samples. Individual level data were collected on several risk factors including: smoking, education, body mass index (BMI), and occupational exposure to dusts. Time-dependent indices of PM(2.5) were created across 13 calendar periods (< 1979, 1979, 1980, em leader, 1989, >/= 1990) to explore whether recent or chronic exposures were more important predictors of mortality. The relative risk (RR) of mortality calculated using Poisson regression based on average city-specific exposures that remained constant during follow-up was 1.31 [95% confidence interval (CI) = 1.12-1.52] per 18.6 microg/m(3) of PM(2.5). This result was similar to the risk calculated using the Cox model (RR = 1.26, 95% CI = 1.08-1.46). The RR of mortality was attenuated when the Poisson regression model included a time-dependent estimate of exposure (RR = 1.19, 95% CI = 1.04-1.36). There was little variation in RR across time-dependent indices of PM(2.5). The attenuated risk of mortality that was observed with a time-dependent index of PM(2.5) is due to the combined influence of city-specific variations in mortality rates and decreasing levels of air pollution that occurred during follow-up. The RR of mortality associated with PM(2.5) did not depend on when exposure occurred in relation to death, possibly because of little variation between the time-dependent city-specific exposure indices.

Safety analysis of urban signalized intersections under mixed traffic.

PubMed

S, Anjana; M V L R, Anjaneyulu

2015-02-01

This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models. Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections. The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study. As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume. Copyright © 2014 Elsevier Ltd. All rights reserved.

Seropositivity for Anti-HCV Core Antigen is Independently Associated With Increased All-Cause, Cardiovascular, and Liver Disease-Related Mortality in Hemodialysis Patients

PubMed Central

Ohsawa, Masaki; Kato, Karen; Tanno, Kozo; Itai, Kazuyoshi; Fujishima, Yosuke; Okayama, Akira; Turin, Tanvir Chowdhury; Onoda, Toshiyuki; Suzuki, Kazuyuki; Nakamura, Motoyuki; Kawamura, Kazuko; Akiba, Takashi; Sakata, Kiyomi; Fujioka, Tomoaki

2011-01-01

Background It is not known whether chronic or past hepatitis C virus (HCV) infection contributes to the high mortality rate in hemodialysis patients. Methods This prospective study of 1077 adult hemodialysis patients without hepatitis B virus infection used Poisson regression analysis to estimate crude and sex- and age-adjusted rates (per 1000 patient-years) of all-cause, cardiovascular, infectious disease-related and liver disease-related mortality in patients negative for HCV antibody (group A), patients positive for HCV antibody and negative for anti-HCV core antigen (group B), and patients positive for anti-HCV core antigen (group C). The relative risks (RRs) for each cause of death in group B vs group C as compared with those in group A were also estimated by Poisson regression analysis after multivariate adjustment. Results A total of 407 patients died during the 5-year observation period. The sex- and age-adjusted mortality rate was 71.9 in group A, 80.4 in group B, and 156 in group C. The RRs (95% CI) for death in group B vs group C were 1.23 (0.72 to 2.12) vs 1.60 (1.13 to 2.28) for all-cause death, 0.75 (0.28 to 2.02) vs 1.64 (0.98 to 2.73) for cardiovascular death, 1.64 (0.65 to 4.15) vs 1.58 (0.81 to 3.07) for infectious disease-related death, and 15.3 (1.26 to 186) vs 28.8 (3.75 to 221) for liver disease-related death, respectively. Conclusions Anti-HCV core antigen seropositivity independently contributes to elevated risks of all-cause and cause-specific death. Chronic HCV infection, but not past HCV infection, is a risk for death among hemodialysis patients. PMID:22001541

Comparison of the Nernst-Planck model and the Poisson-Boltzmann model for electroosmotic flows in microchannels.

PubMed

Park, H M; Lee, J S; Kim, T W

2007-11-15

In the analysis of electroosmotic flows, the internal electric potential is usually modeled by the Poisson-Boltzmann equation. The Poisson-Boltzmann equation is derived from the assumption of thermodynamic equilibrium where the ionic distributions are not affected by fluid flows. Although this is a reasonable assumption for steady electroosmotic flows through straight microchannels, there are some important cases where convective transport of ions has nontrivial effects. In these cases, it is necessary to adopt the Nernst-Planck equation instead of the Poisson-Boltzmann equation to model the internal electric field. In the present work, the predictions of the Nernst-Planck equation are compared with those of the Poisson-Boltzmann equation for electroosmotic flows in various microchannels where the convective transport of ions is not negligible.

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

PubMed

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.

PubMed

Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique

2015-05-01

The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.

Occurrence of Conotruncal Heart Birth Defects in Texas: A Comparison of Urban/Rural Classifications

ERIC Educational Resources Information Center

Langlois, Peter H.; Jandle, Leigh; Scheuerle, Angela; Horel, Scott A.; Carozza, Susan E.

2010-01-01

Purpose: (1) Determine if there is an association between 3 conotruncal heart birth defects and urban/rural residence of mother. (2) Compare results using different methods of measuring urban/rural status. Methods: Data were taken from the Texas Birth Defects Registry, 1999-2003. Poisson regression was used to compare crude and adjusted birth…

Bidirectional relationship between renal function and periodontal disease in older Japanese women.

PubMed

Yoshihara, Akihiro; Iwasaki, Masanori; Miyazaki, Hideo; Nakamura, Kazutoshi

2016-09-01

The purpose of this study was to evaluate the reciprocal effects of chronic kidney disease (CKD) and periodontal disease. A total of 332 postmenopausal never smoking women were enrolled, and their serum high-sensitivity C-reactive protein, serum osteocalcin and serum cystatin C levels were measured. Poor renal function was defined as serum cystatin C > 0.91 mg/l. Periodontal disease markers, including clinical attachment level and the periodontal inflamed surface area (PISA), were also evaluated. Logistic regression analysis was conducted to evaluate the relationships between renal function and periodontal disease markers, serum osteocalcin level and hsCRP level. The prevalence-rate ratios (PRRs) on multiple Poisson regression analyses were determined to evaluate the relationships between periodontal disease markers and serum osteocalcin, serum cystatin C and serum hsCRP levels. On logistic regression analysis, PISA was significantly associated with serum cystatin C level. The odds ratio for serum cystatin C level was 2.44 (p = 0.011). The PRR between serum cystatin C level and periodontal disease markers such as number of sites with clinical attachment level ≥6 mm was significantly positive (3.12, p < 0.001). Similar tendencies were shown for serum osteocalcin level. This study suggests that CKD and periodontal disease can have reciprocal effects. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Intertime jump statistics of state-dependent Poisson processes.

PubMed

Daly, Edoardo; Porporato, Amilcare

2007-01-01

A method to obtain the probability distribution of the interarrival times of jump occurrences in systems driven by state-dependent Poisson noise is proposed. Such a method uses the survivor function obtained by a modified version of the master equation associated to the stochastic process under analysis. A model for the timing of human activities shows the capability of state-dependent Poisson noise to generate power-law distributions. The application of the method to a model for neuron dynamics and to a hydrological model accounting for land-atmosphere interaction elucidates the origin of characteristic recurrence intervals and possible persistence in state-dependent Poisson models.

Relationship among physical activity, smoking, drinking and clustering of the metabolic syndrome diagnostic components.

PubMed

Katano, Sayuri; Nakamura, Yasuyuki; Nakamura, Aki; Murakami, Yoshitaka; Tanaka, Taichiro; Nakagawa, Hideaki; Takebayashi, Toru; Yamato, Hiroshi; Okayama, Akira; Miura, Katsuyuki; Okamura, Tomonori; Ueshima, Hirotsugu

2010-06-30

To examine the relation between lifestyle and the number of metabolic syndrome (MetS) diagnostic components in a general population, and to find a means of preventing the development of MetS components. We examined baseline data from 3,365 participants (2,714 men and 651 women) aged 19 to 69 years who underwent a physical examination, lifestyle survey, and blood chemical examination. The physical activity of each participant was classified according to the International Physical Activity Questionnaire (IPAQ). We defined four components for MetS in this study as follows: 1) high BP: systolic BP > or = 130 mmHg or diastolic BP > or = 85 mmHg, or the use of antihypertensive drugs; 2) dyslipidemia: high-density lipoprotein-cholesterol concentration < 40 mg/dL, triglycerides concentration > or = 150 mg/dL, or on medication for dyslipidemia; 3) Impaired glucose tolerance: fasting blood sugar level > or = 110 mg/d, or if less than 8 hours after meals > or = 140 mg/dL), or on medication for diabetes mellitus; 4) obesity: body mass index > or = 25 kg/m(2). Those who had 0 to 4 MetS diagnostic components accounted for 1,726, 949, 484, 190, and 16 participants, respectively, in the Poisson distribution. Poisson regression analysis revealed that independent factors contributing to the number of MetS diagnostic components were being male (regression coefficient b=0.600, p < 0.01), age (b=0.027, p < 0.01), IPAQ class (b=-0.272, p= 0.03), and alcohol consumption (b=0.020, p=0.01). The contribution of current smoking was not statistically significant (b=-0.067, p=0.76). Moderate physical activity was inversely associated with the number of MetS diagnostic components, whereas smoking was not associated.

Association between quality of care and complications after abdominal surgery.

PubMed

Bergman, Simon; Deban, Melina; Martelli, Vanessa; Monette, Michèle; Sourial, Nadia; Hamadani, Fadi; Teasdale, Debby; Holcroft, Christina; Zakrzewski, Helena; Fraser, Shannon

2014-09-01

Measuring the quality of surgical care is essential to identifying areas of weakness in the delivery of effective surgical care and to improving patient outcomes. Our objectives were to (1) assess the quality of surgical care delivered to adult patients; and (2) determine the association between quality of surgical care and postoperative complications. This retrospective, pilot, cohort study was conducted at a single university-affiliated institution. Using the institution's National Surgical Quality Improvement Program database (2009-2010), 273 consecutive patients ≥18 years of age who underwent elective major abdominal operations were selected. Adherence to 10 process-based quality indicators (QIs) was measured and quantified by calculating a patient quality score (no. of QIs passed/no. of QIs eligible). A pass rate for each individual QI was also calculated. The association between quality of surgical care and postoperative complications was assessed using an incidence rate ratio, which was estimated from a Poisson regression. The mean overall patient quality score was 67.2 ± 14.4% (range, 25-100%). The mean QI pass rate was 65.9 ± 26.1%, which varied widely from 9.6% (oral intake documentation) to 95.6% (prophylactic antibiotics). Poisson regression revealed that as the quality score increased, the incidence of postoperative complications decreased (incidence rate ratio, 0.19; P = .011). A sensitivity analysis revealed that this association was likely driven by the postoperative ambulation QI. Higher quality scores, mainly driven by early ambulation, were associated with fewer postoperative complications. QIs with unacceptably low adherence were identified as targets for future quality improvement initiatives. Copyright © 2014 Mosby, Inc. All rights reserved.

Water quality, compliance, and health outcomes among utilities implementing Water Safety Plans in France and Spain.

PubMed

Setty, Karen E; Kayser, Georgia L; Bowling, Michael; Enault, Jerome; Loret, Jean-Francois; Serra, Claudia Puigdomenech; Alonso, Jordi Martin; Mateu, Arnau Pla; Bartram, Jamie

2017-05-01

Water Safety Plans (WSPs), recommended by the World Health Organization since 2004, seek to proactively identify potential risks to drinking water supplies and implement preventive barriers that improve safety. To evaluate the outcomes of WSP application in large drinking water systems in France and Spain, we undertook analysis of water quality and compliance indicators between 2003 and 2015, in conjunction with an observational retrospective cohort study of acute gastroenteritis incidence, before and after WSPs were implemented at five locations. Measured water quality indicators included bacteria (E. coli, fecal streptococci, total coliform, heterotrophic plate count), disinfectants (residual free and total chlorine), disinfection by-products (trihalomethanes, bromate), aluminum, pH, turbidity, and total organic carbon, comprising about 240K manual samples and 1.2M automated sensor readings. We used multiple, Poisson, or Tobit regression models to evaluate water quality before and after the WSP intervention. The compliance assessment analyzed exceedances of regulated, recommended, or operational water quality thresholds using chi-squared or Fisher's exact tests. Poisson regression was used to examine acute gastroenteritis incidence rates in WSP-affected drinking water service areas relative to a comparison area. Implementation of a WSP generally resulted in unchanged or improved water quality, while compliance improved at most locations. Evidence for reduced acute gastroenteritis incidence following WSP implementation was found at only one of the three locations examined. Outcomes of WSPs should be expected to vary across large water utilities in developed nations, as the intervention itself is adapted to the needs of each location. The approach may translate to diverse water quality, compliance, and health outcomes. Copyright © 2017 Elsevier GmbH. All rights reserved.

Access to Transportation and Health Care Visits for Medicaid Enrollees With Diabetes.

PubMed

Thomas, Leela V; Wedel, Kenneth R; Christopher, Jan E

2018-03-01

Diabetes is a chronic condition that requires frequent health care visits for its management. Individuals without nonemergency medical transportation often miss appointments and do not receive optimal care. This study aims to evaluate the association between Medicaid-provided nonemergency medical transportation and diabetes care visits. A retrospective analysis was conducted of demographic and claims data obtained from the Oklahoma Medicaid program. Participants consisted of Medicaid enrollees with diabetes who made at least 1 visit for diabetes care in a year. The sample was predominantly female and white, with an average age of 46.38 years. Two zero-truncated Poisson regression models were estimated to assess the independent effect of transportation use on number of diabetes care visits. Use of nonemergency medical transportation is a significant predictor of diabetes care visits. Zero-truncated Poisson regression coefficients showed a positive association between the use of transportation and number of visits (0.6563, P < .001). Age, gender, race/ethnicity, area of residence, and presence of additional chronic conditions had independent associations with number of visits. Older enrollees were likely to make more visits than younger enrollees with diabetes (0.02382); controlling for all other factors in the model, rural residents made more visits than urban; women made fewer visits than men (-0.09312; P < .001); and minorities made fewer visits than whites, with pronounced differences for Hispanics and Asians compared to whites. Findings underscore the importance of ensuring transportation to Medicaid populations with diabetes, particularly in the rural areas where the prevalence of diabetes and complications are higher and the availability of medical resources lower than in the urban areas. © 2017 National Rural Health Association.

Increased recurrence rates of hepatocellular carcinoma after DAA therapy in a hepatitis C-infected Egyptian cohort: A comparative analysis.

PubMed

El Kassas, M; Funk, A L; Salaheldin, M; Shimakawa, Y; Eltabbakh, M; Jean, K; El Tahan, A; Sweedy, A T; Afify, S; Youssef, N F; Esmat, G; Fontanet, A

2018-06-01

In Egypt, hepatocellular carcinoma (HCC) is the most common form of cancer and direct-acting antivirals (DAA) are administered on a large scale to patients with chronic HCV infection to reduce the risk. In this unique setting, we aimed to determine the association of DAA exposure with early-phase HCC recurrence in patients with a history of HCV-related liver cancer. This was a prospective cohort study of an HCV-infected population from one Egyptian specialized HCC management centre starting from the time of successful HCC intervention. The incidence rates of HCC recurrence between DAA-exposed and nonexposed patients were compared, starting from date of HCC complete radiological response and censoring after 2 years. DAA exposure was treated as time varying. Two Poisson regressions models were used to control for potential differences in the exposed and nonexposed group; multivariable adjustment and balancing using inverse probability of treatment weighting (IPTW). We included 116 patients: 53 treated with DAAs and 63 not treated with DAAs. There was 37.7% and 25.4% recurrence in each group after a median of 16.0 and 23.0 months of follow-up, respectively. Poisson regression using IPTW demonstrated an association between DAAs and HCC recurrence with an incidence rate ratio of 3.83 (95% CI: 2.02-7.25), which was similar in the multivariable-adjusted model and various sensitivity analyses. These results add important evidence towards the possible role of DAAs in HCC recurrence and stress the need for further mechanistic studies and clinical trials to accurately confirm this role and to identify patient characteristics that may be associated with this event. © 2017 John Wiley & Sons Ltd.

Impact of a New Law to Reduce the Legal Blood Alcohol Concentration Limit - A Poisson Regression Analysis and Descriptive Approach.

PubMed

Nistal-Nuño, Beatriz

2017-03-31

In Chile, a new law introduced in March 2012 lowered the blood alcohol concentration (BAC) limit for impaired drivers from 0.1% to 0.08% and the BAC limit for driving under the influence of alcohol from 0.05% to 0.03%, but its effectiveness remains uncertain. The goal of this investigation was to evaluate the effects of this enactment on road traffic injuries and fatalities in Chile. A retrospective cohort study. Data were analyzed using a descriptive and a Generalized Linear Models approach, type of Poisson regression, to analyze deaths and injuries in a series of additive Log-Linear Models accounting for the effects of law implementation, month influence, a linear time trend and population exposure. A review of national databases in Chile was conducted from 2003 to 2014 to evaluate the monthly rates of traffic fatalities and injuries associated to alcohol and in total. It was observed a decrease by 28.1 percent in the monthly rate of traffic fatalities related to alcohol as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 20.9 percent (P<0.001).There was a reduction in the monthly rate of traffic injuries related to alcohol by 10.5 percent as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 24.8 percent (P<0.001). Positive results followed from this new 'zero-tolerance' law implemented in 2012 in Chile. Chile experienced a significant reduction in alcohol-related traffic fatalities and injuries, being a successful public health intervention.

A two-arm cluster randomized control trial to determine the effectiveness of a pressure ulcer prevention bundle for critically ill patients.

PubMed

Tayyib, Nahla; Coyer, Fiona; Lewis, Peter A

2015-05-01

This study tested the effectiveness of a pressure ulcer (PU) prevention bundle in reducing the incidence of PUs in critically ill patients in two Saudi intensive care units (ICUs). A two-arm cluster randomized experimental control trial. Participants in the intervention group received the PU prevention bundle, while the control group received standard skin care as per the local ICU policies. Data collected included demographic variables (age, diagnosis, comorbidities, admission trajectory, length of stay) and clinical variables (Braden Scale score, severity of organ function score, mechanical ventilation, PU presence, and staging). All patients were followed every two days from admission through to discharge, death, or up to a maximum of 28 days. Data were analyzed with descriptive correlation statistics, Kaplan-Meier survival analysis, and Poisson regression. The total number of participants recruited was 140: 70 control participants (with a total of 728 days of observation) and 70 intervention participants (784 days of observation). PU cumulative incidence was significantly lower in the intervention group (7.14%) compared to the control group (32.86%). Poisson regression revealed the likelihood of PU development was 70% lower in the intervention group. The intervention group had significantly less Stage I (p = .002) and Stage II PU development (p = .026). Significant improvements were observed in PU-related outcomes with the implementation of the PU prevention bundle in the ICU; PU incidence, severity, and total number of PUs per patient were reduced. Utilizing a bundle approach and standardized nursing language through skin assessment and translation of the knowledge to practice has the potential to impact positively on the quality of care and patient outcome. © 2015 Sigma Theta Tau International.

Mortality among 24,865 workers exposed to polychlorinated biphenyls (PCBs) in three electrical capacitor manufacturing plants: a ten-year update.

PubMed

Ruder, Avima M; Hein, Misty J; Hopf, Nancy B; Waters, Martha A

2014-03-01

The objective of this analysis was to evaluate mortality among a cohort of 24,865 capacitor-manufacturing workers exposed to polychlorinated biphenyls (PCBs) at plants in Indiana, Massachusetts, and New York and followed for mortality through 2008. Cumulative PCB exposure was estimated using plant-specific job-exposure matrices. External comparisons to US and state-specific populations used standardized mortality ratios, adjusted for gender, race, age and calendar year. Among long-term workers employed 3 months or longer, within-cohort comparisons used standardized rate ratios and multivariable Poisson regression modeling. Through 2008, more than one million person-years at risk and 8749 deaths were accrued. Among long-term employees, all-cause and all-cancer mortality were not elevated; of the a priori outcomes assessed only melanoma mortality was elevated. Mortality was elevated for some outcomes of a priori interest among subgroups of long-term workers: all cancer, intestinal cancer and amyotrophic lateral sclerosis (women); melanoma (men); melanoma and brain and nervous system cancer (Indiana plant); and melanoma and multiple myeloma (New York plant). Standardized rates of stomach and uterine cancer and multiple myeloma mortality increased with estimated cumulative PCB exposure. Poisson regression modeling showed significant associations with estimated cumulative PCB exposure for prostate and stomach cancer mortality. For other outcomes of a priori interest--rectal, liver, ovarian, breast, and thyroid cancer, non-Hodgkin lymphoma, Alzheimer disease, and Parkinson disease--neither elevated mortality nor positive associations with PCB exposure were observed. Associations between estimated cumulative PCB exposure and stomach, uterine, and prostate cancer and myeloma mortality confirmed our previous positive findings. Published by Elsevier GmbH.

Mortality among 24,865 workers exposed to polychlorinated biphenyls (PCBs) in three electrical capacitor manufacturing plants: A ten-year update

PubMed Central

Ruder, Avima M.; Hein, Misty J.; Hopf, Nancy B.; Waters, Martha A.

2015-01-01

The objective of this analysis was to evaluate mortality among a cohort of 24,865 capacitor-manufacturing workers exposed to polychlorinated biphenyls (PCBs) at plants in Indiana, Massachusetts, and New York and followed for mortality through 2008. Cumulative PCB exposure was estimated using plant-specific job-exposure matrices. External comparisons to US and state-specific populations used standardized mortality ratios, adjusted for gender, race, age and calendar year. Among long-term workers employed 3 months or longer, within-cohort comparisons used standardized rate ratios and multivariable Poisson regression modeling. Through 2008, more than one million person-years at risk and 8749 deaths were accrued. Among long-term employees, all-cause and all-cancer mortality were not elevated; of the a priori outcomes assessed only melanoma mortality was elevated. Mortality was elevated for some outcomes of a priori interest among subgroups of long-term workers: all cancer, intestinal cancer and amyotrophic lateral sclerosis (women); melanoma (men); melanoma and brain and nervous system cancer (Indiana plant); and melanoma and multiple myeloma (New York plant). Standardized rates of stomach and uterine cancer and multiple myeloma mortality increased with estimated cumulative PCB exposure. Poisson regression modeling showed significant associations with estimated cumulative PCB exposure for prostate and stomach cancer mortality. For other outcomes of a priori interest – rectal, liver, ovarian, breast, and thyroid cancer, non-Hodgkin lymphoma, Alzheimer disease, and Parkinson disease – neither elevated mortality nor positive associations with PCB exposure were observed. Associations between estimated cumulative PCB exposure and stomach, uterine, and prostate cancer and myeloma mortality confirmed our previous positive findings. PMID:23707056

Pattern of oral-maxillofacial trauma from violence against women and its associated factors.

PubMed

da Nóbrega, Lorena Marques; Bernardino, Ítalo de Macedo; Barbosa, Kevan Guilherme Nóbrega; E Silva, Jéssica Antoniana Lira; Massoni, Andreza Cristina de Lima Targino; d'Avila, Sérgio

2017-06-01

Violence against women is a global public health problem. The aim of this study was to characterize the profile of women victims of violence and identify factors associated with maxillofacial injuries. A cross-sectional study was performed based on an evaluation of 884 medico-legal and social records of women victims of physical aggression treated at the Center of Forensic Medicine and Dentistry in Brazil. The variables investigated were related to the sociodemographic characteristics of victims, circumstances of aggressions, and patterns of trauma. Descriptive and multivariate statistics using decision tree analysis by the Chi-squared automatic interaction detector (CHAID) algorithm, as well as univariate and multivariate Poisson regression analyses were performed. The occurrence of maxillofacial trauma was 46.4%. The mean age of victims was 29.38 (SD=12.55 years). Based on decision tree, the profile of violence against women can be explained by the aggressor's gender (P<.001) and sociodemographic characteristics of victims, such as marital status (P=.001), place of residence (P=.019), and educational level (P=.014). Based on the final Poisson regression model, women living in suburban areas were more likely to suffer maxillofacial trauma (PR=1.752; CI 95%=1.153-2.662; P=.009) compared to those living in rural areas. Moreover, aggression using a weapon resulted in a lower occurrence of maxillofacial trauma (PR=0.476; CI 95%=0.284-0.799; P=.005) compared to cases of aggression using physical force. The prevalence of oral-maxillofacial trauma was high, and the main associated factors were place of residence and mechanism of aggression. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Revascularization Treatment of Emergency Patients with Acute ST-Segment Elevation Myocardial Infarction in Switzerland: Results from a Nationwide, Cross-Sectional Study in Switzerland for 2010-2011.

PubMed

Berlin, Claudia; Jüni, Peter; Endrich, Olga; Zwahlen, Marcel

2016-01-01

Cardiovascular diseases are the leading cause of death worldwide and in Switzerland. When applied, treatment guidelines for patients with acute ST-segment elevation myocardial infarction (STEMI) improve the clinical outcome and should eliminate treatment differences by sex and age for patients whose clinical situations are identical. In Switzerland, the rate at which STEMI patients receive revascularization may vary by patient and hospital characteristics. To examine all hospitalizations in Switzerland from 2010-2011 to determine if patient or hospital characteristics affected the rate of revascularization (receiving either a percutaneous coronary intervention or a coronary artery bypass grafting) in acute STEMI patients. We used national data sets on hospital stays, and on hospital infrastructure and operating characteristics, for the years 2010 and 2011, to identify all emergency patients admitted with the main diagnosis of acute STEMI. We then calculated the proportion of patients who were treated with revascularization. We used multivariable multilevel Poisson regression to determine if receipt of revascularization varied by patient and hospital characteristics. Of the 9,696 cases we identified, 71.6% received revascularization. Patients were less likely to receive revascularization if they were female, and 80 years or older. In the multivariable multilevel Poisson regression analysis, there was a trend for small-volume hospitals performing fewer revascularizations but this was not statistically significant while being female (Relative Proportion = 0.91, 95% CI: 0.86 to 0.97) and being older than 80 years was still associated with less frequent revascularization. Female and older patients were less likely to receive revascularization. Further research needs to clarify whether this reflects differential application of treatment guidelines or limitations in this kind of routine data.

Analysis strategies for longitudinal attachment loss data.

PubMed

Beck, J D; Elter, J R

2000-02-01

The purpose of this invited review is to describe and discuss methods currently in use to quantify the progression of attachment loss in epidemiological studies of periodontal disease, and to make recommendations for specific analytic methods based upon the particular design of the study and structure of the data. The review concentrates on the definition of incident attachment loss (ALOSS) and its component parts; measurement issues including thresholds and regression to the mean; methods of accounting for longitudinal change, including changes in means, changes in proportions of affected sites, incidence density, the effect of tooth loss and reversals, and repeated events; statistical models of longitudinal change, including the incorporation of the time element, use of linear, logistic or Poisson regression or survival analysis, and statistical tests; site vs person level of analysis, including statistical adjustment for correlated data; the strengths and limitations of ALOSS data. Examples from the Piedmont 65+ Dental Study are used to illustrate specific concepts. We conclude that incidence density is the preferred methodology to use for periodontal studies with more than one period of follow-up and that the use of studies not employing methods for dealing with complex samples, correlated data, and repeated measures does not take advantage of our current understanding of the site- and person-level variables important in periodontal disease and may generate biased results.

Identifying Flood-Related Infectious Diseases in Anhui Province, China: A Spatial and Temporal Analysis

PubMed Central

Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Jiang, Baofa

2016-01-01

The aim of this study was to explore infectious diseases related to the 2007 Huai River flood in Anhui Province, China. The study was based on the notified incidences of infectious diseases between June 29 and July 25 from 2004 to 2011. Daily incidences of notified diseases in 2007 were compared with the corresponding daily incidences during the same period in the other years (from 2004 to 2011, except 2007) by Poisson regression analysis. Spatial autocorrelation analysis was used to test the distribution pattern of the diseases. Spatial regression models were then performed to examine the association between the incidence of each disease and flood, considering lag effects and other confounders. After controlling the other meteorological and socioeconomic factors, malaria (odds ratio [OR] = 3.67, 95% confidence interval [CI] = 1.77–7.61), diarrhea (OR = 2.16, 95% CI = 1.24–3.78), and hepatitis A virus (HAV) infection (OR = 6.11, 95% CI = 1.04–35.84) were significantly related to the 2007 Huai River flood both from the spatial and temporal analyses. Special attention should be given to develop public health preparation and interventions with a focus on malaria, diarrhea, and HAV infection, in the study region. PMID:26903612

Pseudo and conditional score approach to joint analysis of current count and current status data.

PubMed

Wen, Chi-Chung; Chen, Yi-Hau

2018-04-17

We develop a joint analysis approach for recurrent and nonrecurrent event processes subject to case I interval censorship, which are also known in literature as current count and current status data, respectively. We use a shared frailty to link the recurrent and nonrecurrent event processes, while leaving the distribution of the frailty fully unspecified. Conditional on the frailty, the recurrent event is assumed to follow a nonhomogeneous Poisson process, and the mean function of the recurrent event and the survival function of the nonrecurrent event are assumed to follow some general form of semiparametric transformation models. Estimation of the models is based on the pseudo-likelihood and the conditional score techniques. The resulting estimators for the regression parameters and the unspecified baseline functions are shown to be consistent with rates of square and cubic roots of the sample size, respectively. Asymptotic normality with closed-form asymptotic variance is derived for the estimator of the regression parameters. We apply the proposed method to a fracture-osteoporosis survey data to identify risk factors jointly for fracture and osteoporosis in elders, while accounting for association between the two events within a subject. © 2018, The International Biometric Society.

A flexible count data regression model for risk analysis.

PubMed

Guikema, Seth D; Coffelt, Jeremy P; Goffelt, Jeremy P

2008-02-01

In many cases, risk and reliability analyses involve estimating the probabilities of discrete events such as hardware failures and occurrences of disease or death. There is often additional information in the form of explanatory variables that can be used to help estimate the likelihood of different numbers of events in the future through the use of an appropriate regression model, such as a generalized linear model. However, existing generalized linear models (GLM) are limited in their ability to handle the types of variance structures often encountered in using count data in risk and reliability analysis. In particular, standard models cannot handle both underdispersed data (variance less than the mean) and overdispersed data (variance greater than the mean) in a single coherent modeling framework. This article presents a new GLM based on a reformulation of the Conway-Maxwell Poisson (COM) distribution that is useful for both underdispersed and overdispersed count data and demonstrates this model by applying it to the assessment of electric power system reliability. The results show that the proposed COM GLM can provide as good of fits to data as the commonly used existing models for overdispered data sets while outperforming these commonly used models for underdispersed data sets.

The influence of oral health conditions, socioeconomic status and home environment factors on schoolchildren's self-perception of quality of life.

PubMed

Paula, Janice S; Leite, Isabel Cg; Almeida, Anderso B; Ambrosano, Glaucia Mb; Pereira, Antônio C; Mialhe, Fábio L

2012-01-13

The objective this study was to investigate the influence of clinical conditions, socioeconomic status, home environment, subjective perceptions of parents and schoolchildren about general and oral health on schoolchildren's oral health-related quality of life (OHRQoL). A sample of 515 schoolchildren, aged 12 years was randomly selected by conglomerate analysis from public and private schools in the city of Juiz de Fora, Brazil. The schoolchildren were clinically examined for presence of caries lesions (DMFT and dmft index), dental trauma, enamel defects, periodontal status (presence/absence of bleeding), dental treatment and orthodontic treatment needs (DAI). The SiC index was calculated. The participants were asked to complete the Brazilian version of Child Perceptions Questionnaire (CPQ11-14) and a questionnaire about home environment. Questions were asked about the presence of general diseases and children's self-perception of their general and oral health status. In addition, a questionnaire was sent to their parents inquiring about their socioeconomic status (family income, parents' education level, home ownership) and perceptions about the general and oral health of their school-aged children. The chi-square test was used for comparisons between proportions. Poisson's regression was used for multivariate analysis with adjustment for variances. Univariate analysis revealed that school type, monthly family income, mother's education, family structure, number of siblings, use of cigarettes, alcohol and drugs in the family, parents' perception of oral health of schoolchildren, schoolchildren's self perception their general and oral health, orthodontic treatment needs were significantly associated with poor OHRQoL (p < 0.001). After adjusting for potential confounders, variables were included in a Multivariate Poisson regression. It was found that the variables children's self perception of their oral health status, monthly family income, gender, orthodontic treatment need, mother's education, number of siblings, and household overcrowding showed a strong negative effect on oral health-related quality of life. It was concluded that the clinical, socioeconomic and home environment factors evaluated exerted a negative impact on the oral health-related quality of life of schoolchildren, demonstrating the importance of health managers addressing all these factors when planning oral health promotion interventions for this population.

Impact of Saharan dust particles on hospital admissions in Madrid (Spain).

PubMed

Reyes, María; Díaz, Julio; Tobias, Aurelio; Montero, Juan Carlos; Linares, Cristina

2014-01-01

Saharan dust intrusions make a major contribution to levels of particulate matter (PM) present in the atmosphere of large cities. We analysed the impact of different PM fractions during periods with and without Saharan dust intrusions, using time-series analysis with Poisson regression models, based on: concentrations of coarse PM (PM10 and PM10-2.5) and fine PM (PM2.5); and daily all-, circulatory- and respiratory-cause hospital admissions. While periods without Saharan dust intrusions were marked by a statistically significant association between daily mean PM2.5 concentrations and all- and circulatory-cause hospital admissions, periods with such intrusions saw a significant increase in respiratory-cause admissions associated with fractions corresponding to PM10 and PM10-2.5.

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

Prevalence and factors associated with enamel defects among preschool children from a southeastern city in Brazil.

PubMed

Tourino, Luciana Fonseca Pádua; Zarzar, Patrícia Maria; Corrêa-Faria, Patrícia; Paiva, Saul Martins; Vale, Miriam Pimenta Parreira do

2018-05-01

This study sought to determine the prevalence of developmental defects of enamel (DDE) among preschool children and investigate associations with sociodemographic and socioeconomic factors and weight status. A cross-sectional study was conducted with 118 children aged 3 to 5 years. Data were collected via clinical examinations and a self-administered questionnaire completed by the parents. The diagnosis of DDE was performed using the modified DDE Index. Information on socioeconomic indicators (mother's schooling, monthly income per capita), child's sex and age, and age of mother at the birth of the child were obtained by questionnaire. The children's weight status was determined based on weight-for-age at the time of the exam. Statistical analysis involved the chi-squared test and Poisson regression with robust variance. The prevalence of DDE was 50.0%. DDE were more frequent in males (p = 0.025) and children whose families were classified as being at poverty line (p = 0.040). In the Poisson model controlled for child's sex and mother's schooling, children whose families were classified as being at the poverty line had a greater prevalence rate of DDE. In conclusion, the prevalence of DDE was high in the present sample and associated with lower household income. Weight status was not associated with DDE.

Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.

PubMed

Gao, Yi; Bouix, Sylvain

2016-05-01

Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.

High prevalence of suicide risk in people living with HIV: who is at higher risk?

PubMed

Passos, Susane Müller Klug; Souza, Luciano Dias de Mattos; Spessato, Bárbara Coiro

2014-01-01

A cross-sectional study was developed to evaluate suicide risk and associated factors in HIV/AIDS patients at a regional reference center for the treatment of HIV/AIDS in southern Brazil. We assessed 211 patients in regard to suicide risk, clinical and sociodemographic characteristics, drug use, depression, and anxiety. Suicide risk was assessed with Mini International Neuropsychiatric Interview, Module C. Multivariate analysis was performed using Poisson regression. Of the total sample, 34.1% were at risk of suicide. In the multivariate analysis, the following variables were independently associated with suicide risk: female gender; age up to 47 years; unemployment; indicative of anxiety; indicative of depression; and abuse or addiction on psychoactive substances. Suicide risk is high in this population. Psychosocial factors should be included in the physical and clinical evaluation, given their strong association with suicide risk.

Testing a Poisson Counter Model for Visual Identification of Briefly Presented, Mutually Confusable Single Stimuli in Pure Accuracy Tasks

ERIC Educational Resources Information Center

Kyllingsbaek, Soren; Markussen, Bo; Bundesen, Claus

2012-01-01

The authors propose and test a simple model of the time course of visual identification of briefly presented, mutually confusable single stimuli in pure accuracy tasks. The model implies that during stimulus analysis, tentative categorizations that stimulus i belongs to category j are made at a constant Poisson rate, v(i, j). The analysis is…

Evaluation of Shiryaev-Roberts procedure for on-line environmental radiation monitoring.

PubMed

Watson, Mara M; Seliman, Ayman F; Bliznyuk, Valery N; DeVol, Timothy A

2018-04-30

Water can become contaminated as a result of a leak from a nuclear facility, such as a waste facility, or from clandestine nuclear activity. Low-level on-line radiation monitoring is needed to detect these events in real time. A Bayesian control chart method, Shiryaev-Roberts (SR) procedure, was compared with classical methods, 3-σ and cumulative sum (CUSUM), for quantifying an accumulating signal from an extractive scintillating resin flow-cell detection system. Solutions containing 0.10-5.0 Bq/L of 99 Tc, as T99cO 4 - were pumped through a flow cell packed with extractive scintillating resin used in conjunction with a Beta-RAM Model 5 HPLC detector. While T99cO 4 - accumulated on the resin, time series data were collected. Control chart methods were applied to the data using statistical algorithms developed in MATLAB. SR charts were constructed using Poisson (Poisson SR) and Gaussian (Gaussian SR) probability distributions of count data to estimate the likelihood ratio. Poisson and Gaussian SR charts required less volume of radioactive solution at a fixed concentration to exceed the control limit in most cases than 3-σ and CUSUM control charts, particularly solutions with lower activity. SR is thus the ideal control chart for low-level on-line radiation monitoring. Once the control limit was exceeded, activity concentrations were estimated from the SR control chart using the control chart slope on a semi-logarithmic plot. A linear regression fit was applied to averaged slope data for five activity concentration groupings for Poisson and Gaussian SR control charts. A correlation coefficient (R 2 ) of 0.77 for Poisson SR and 0.90 for Gaussian SR suggest this method will adequately estimate activity concentration for an unknown solution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

PubMed

Hougaard, P; Lee, M L; Whitmore, G A

1997-12-01

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

Rates of Femicide in Women of Different Races, Ethnicities, and Places of Birth: Massachusetts, 1993-2007

ERIC Educational Resources Information Center

Azziz-Baumgartner, Eduardo; McKeown, Loreta; Melvin, Patrice; Dang, Quynh; Reed, Joan

2011-01-01

To describe the epidemiology of intimate partner violence (IPV) homicide in Massachusetts, an IPV mortality data set developed by the Massachusetts Department of Public Health was analyzed. The rates of death were estimated by dividing the number of decedents over the aged-matched population and Poisson regression was used to estimate the…

Growth Curve Models for Zero-Inflated Count Data: An Application to Smoking Behavior

ERIC Educational Resources Information Center

Liu, Hui; Powers, Daniel A.

2007-01-01

This article applies growth curve models to longitudinal count data characterized by an excess of zero counts. We discuss a zero-inflated Poisson regression model for longitudinal data in which the impact of covariates on the initial counts and the rate of change in counts over time is the focus of inference. Basic growth curve models using a…

Relations Between Residential Proximity to EPA-Designated Toxic Release Sites and Diffuse Large B-Cell Lymphoma Incidence.

PubMed

Bulka, Catherine; Nastoupil, Loretta J; Koff, Jean L; Bernal-Mizrachi, Leon; Ward, Kevin C; Williams, Jessica N; Bayakly, A Rana; Switchenko, Jeffrey M; Waller, Lance A; Flowers, Christopher R

2016-10-01

Examining the spatial patterns of diffuse large B-cell lymphoma (DLBCL) incidence and residential proximity to toxic release locations may provide insight regarding environmental and sociodemographic risk factors. We linked and geocoded cancer incidence data for the period 1999-2008 from the Georgia Comprehensive Cancer Registry with population data from the US Census and the Environmental Protection Agency's Toxics Release Inventory. We conducted cluster analyses and constructed Poisson regression models to assess DLBCL incidence as a function of mean distance to the toxic release sites. In total, 3851 incident DLBCL cases occurred among adults residing in Georgia between 1999 and 2008. Significant focal clustering was observed around 57% of ethylene oxide sites, 5% of benzene sites, 9% of tetrachloroethylene sites, 7% of styrene sites, 10% of formaldehyde sites, 5% of trichloroethylene sites, and 10% of all release sites. Mean distance to sites was significantly associated with DLBCL risk for all chemicals. Proximity to Toxics Release Inventory sites can be linked to increased DLBCL risk as assessed through focal clustering and Poisson regression, and confirmatory studies using geospatial mapping can aid in further specifying risk factors for DLBCL.

Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning.

PubMed

Wen, L; Bowen, C R; Hartman, G L

2017-10-01

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.

Predictors for the Number of Warning Information Sources During Tornadoes.

PubMed

Cong, Zhen; Luo, Jianjun; Liang, Daan; Nejat, Ali

2017-04-01

People may receive tornado warnings from multiple information sources, but little is known about factors that affect the number of warning information sources (WISs). This study examined predictors for the number of WISs with a telephone survey on randomly sampled residents in Tuscaloosa, Alabama, and Joplin, Missouri, approximately 1 year after both cities were struck by violent tornadoes (EF4 and EF5) in 2011. The survey included 1006 finished interviews and the working sample included 903 respondents. Poisson regression and Zero-Inflated Poisson regression showed that older age and having an emergency plan predicted more WISs in both cities. Education, marital status, and gender affected the possibilities of receiving warnings and the number of WISs either in Joplin or in Tuscaloosa. The findings suggest that social disparity affects the access to warnings not only with respect to the likelihood of receiving any warnings but also with respect to the number of WISs. In addition, historical and social contexts are important for examining predictors for the number of WISs. We recommend that the number of WISs should be regarded as an important measure to evaluate access to warnings in addition to the likelihood of receiving warnings. (Disaster Med Public Health Preparedness. 2017;11:168-172).

Association between large strongyle genera in larval cultures--using rare-event poisson regression.

PubMed

Cao, X; Vidyashankar, A N; Nielsen, M K

2013-09-01

Decades of intensive anthelmintic treatment has caused equine large strongyles to become quite rare, while the cyathostomins have developed resistance to several drug classes. The larval culture has been associated with low to moderate negative predictive values for detecting Strongylus vulgaris infection. It is unknown whether detection of other large strongyle species can be statistically associated with presence of S. vulgaris. This remains a statistical challenge because of the rare occurrence of large strongyle species. This study used a modified Poisson regression to analyse a dataset for associations between S. vulgaris infection and simultaneous occurrence of Strongylus edentatus and Triodontophorus spp. In 663 horses on 42 Danish farms, the individual prevalences of S. vulgaris, S. edentatus and Triodontophorus spp. were 12%, 3% and 12%, respectively. Both S. edentatus and Triodontophorus spp. were significantly associated with S. vulgaris infection with relative risks above 1. Further, S. edentatus was associated with use of selective therapy on the farms, as well as negatively associated with anthelmintic treatment carried out within 6 months prior to the study. The findings illustrate that occurrence of S. vulgaris in larval cultures can be interpreted as indicative of other large strongyles being likely to be present.

A Hands-on Activity for Teaching the Poisson Distribution Using the Stock Market

ERIC Educational Resources Information Center

Dunlap, Mickey; Studstill, Sharyn

2014-01-01

The number of increases a particular stock makes over a fixed period follows a Poisson distribution. This article discusses using this easily-found data as an opportunity to let students become involved in the data collection and analysis process.

General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.

PubMed

Reis, Matthias; Kromer, Justus A; Klipp, Edda

2018-01-20

Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.

Harnessing the theoretical foundations of the exponential and beta-Poisson dose-response models to quantify parameter uncertainty using Markov Chain Monte Carlo.

PubMed

Schmidt, Philip J; Pintar, Katarina D M; Fazil, Aamir M; Topp, Edward

2013-09-01

Dose-response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose-response model parameters are estimated using limited epidemiological data is rarely quantified. Second-order risk characterization approaches incorporating uncertainty in dose-response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta-Poisson dose-response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta-Poisson dose-response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta-Poisson dose-response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta-Poisson model are proposed, and simple algorithms to evaluate actual beta-Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta-Poisson dose-response model parameters is attributable to the absence of low-dose data. This region includes beta-Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility. © Her Majesty the Queen in Right of Canada 2013. Reproduced with the permission of the Minister of the Public Health Agency of Canada.

Are all quantitative postmarketing signal detection methods equal? Performance characteristics of logistic regression and Multi-item Gamma Poisson Shrinker.

PubMed

Berlin, Conny; Blanch, Carles; Lewis, David J; Maladorno, Dionigi D; Michel, Christiane; Petrin, Michael; Sarp, Severine; Close, Philippe

2012-06-01

The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR). A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied. There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity. Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis. Copyright © 2011 John Wiley & Sons, Ltd.

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.

Application of the Conway-Maxwell-Poisson generalized linear model for analyzing motor vehicle crashes.

PubMed

Lord, Dominique; Guikema, Seth D; Geedipally, Srinivas Reddy

2008-05-01

This paper documents the application of the Conway-Maxwell-Poisson (COM-Poisson) generalized linear model (GLM) for modeling motor vehicle crashes. The COM-Poisson distribution, originally developed in 1962, has recently been re-introduced by statisticians for analyzing count data subjected to over- and under-dispersion. This innovative distribution is an extension of the Poisson distribution. The objectives of this study were to evaluate the application of the COM-Poisson GLM for analyzing motor vehicle crashes and compare the results with the traditional negative binomial (NB) model. The comparison analysis was carried out using the most common functional forms employed by transportation safety analysts, which link crashes to the entering flows at intersections or on segments. To accomplish the objectives of the study, several NB and COM-Poisson GLMs were developed and compared using two datasets. The first dataset contained crash data collected at signalized four-legged intersections in Toronto, Ont. The second dataset included data collected for rural four-lane divided and undivided highways in Texas. Several methods were used to assess the statistical fit and predictive performance of the models. The results of this study show that COM-Poisson GLMs perform as well as NB models in terms of GOF statistics and predictive performance. Given the fact the COM-Poisson distribution can also handle under-dispersed data (while the NB distribution cannot or has difficulties converging), which have sometimes been observed in crash databases, the COM-Poisson GLM offers a better alternative over the NB model for modeling motor vehicle crashes, especially given the important limitations recently documented in the safety literature about the latter type of model.

Lognormal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of α-Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2010-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086

Mechanical properties investigation on single-wall ZrO2 nanotubes: A finite element method with equivalent Poisson's ratio for chemical bonds

NASA Astrophysics Data System (ADS)

Yang, Xiao; Li, Huijian; Hu, Minzheng; Liu, Zeliang; Wärnå, John; Cao, Yuying; Ahuja, Rajeev; Luo, Wei

2018-04-01

A method to obtain the equivalent Poisson's ratio in chemical bonds as classical beams with finite element method was proposed from experimental data. The UFF (Universal Force Field) method was employed to calculate the elastic force constants of Zrsbnd O bonds. By applying the equivalent Poisson's ratio, the mechanical properties of single-wall ZrNTs (ZrO2 nanotubes) were investigated by finite element analysis. The nanotubes' Young's modulus (Y), Poisson's ratio (ν) of ZrNTs as function of diameters, length and chirality have been discussed, respectively. We found that the Young's modulus of single-wall ZrNTs is calculated to be between 350 and 420 GPa.

Influenza vaccine coverage, influenza-associated morbidity and all-cause mortality in Catalonia (Spain).

PubMed

Muñoz, M Pilar; Soldevila, Núria; Martínez, Anna; Carmona, Glòria; Batalla, Joan; Acosta, Lesly M; Domínguez, Angela

2011-07-12

The objective of this work was to study the behaviour of influenza with respect to morbidity and all-cause mortality in Catalonia, and their association with influenza vaccination coverage. The study was carried out over 13 influenza seasons, from epidemiological week 40 of 1994 to week 20 of 2007, and included confirmed cases of influenza and all-cause mortality. Two generalized linear models were fitted: influenza-associated morbidity was modelled by Poisson regression and all-cause mortality by negative binomial regression. The seasonal component was modelled with the periodic function formed by the sum of the sinus and cosines. Expected influenza mortality during periods of influenza virus circulation was estimated by Poisson regression and its confidence intervals using the Bootstrap approach. Vaccination coverage was associated with a reduction in influenza-associated morbidity (p<0.001), but not with a reduction in all-cause mortality (p=0.149). In the case of influenza-associated morbidity, an increase of 5% in vaccination coverage represented a reduction of 3% in the incidence rate of influenza. There was a positive association between influenza-associated morbidity and all-cause mortality. Excess mortality attributable to influenza epidemics was estimated as 34.4 (95% CI: 28.4-40.8) weekly deaths. In conclusion, all-cause mortality is a good indicator of influenza surveillance and vaccination coverage is associated with a reduction in influenza-associated morbidity but not with all-cause mortality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Generic Schemes for Single-Molecule Kinetics. 2: Information Content of the Poisson Indicator.

PubMed

Avila, Thomas R; Piephoff, D Evan; Cao, Jianshu

2017-08-24

Recently, we described a pathway analysis technique (paper 1) for analyzing generic schemes for single-molecule kinetics based upon the first-passage time distribution. Here, we employ this method to derive expressions for the Poisson indicator, a normalized measure of stochastic variation (essentially equivalent to the Fano factor and Mandel's Q parameter), for various renewal (i.e., memoryless) enzymatic reactions. We examine its dependence on substrate concentration, without assuming all steps follow Poissonian kinetics. Based upon fitting to the functional forms of the first two waiting time moments, we show that, to second order, the non-Poissonian kinetics are generally underdetermined but can be specified in certain scenarios. For an enzymatic reaction with an arbitrary intermediate topology, we identify a generic minimum of the Poisson indicator as a function of substrate concentration, which can be used to tune substrate concentration to the stochastic fluctuations and to estimate the largest number of underlying consecutive links in a turnover cycle. We identify a local maximum of the Poisson indicator (with respect to substrate concentration) for a renewal process as a signature of competitive binding, either between a substrate and an inhibitor or between multiple substrates. Our analysis explores the rich connections between Poisson indicator measurements and microscopic kinetic mechanisms.

Piecewise exponential survival times and analysis of case-cohort data.

PubMed

Li, Yan; Gail, Mitchell H; Preston, Dale L; Graubard, Barry I; Lubin, Jay H

2012-06-15

Case-cohort designs select a random sample of a cohort to be used as control with cases arising from the follow-up of the cohort. Analyses of case-cohort studies with time-varying exposures that use Cox partial likelihood methods can be computer intensive. We propose a piecewise-exponential approach where Poisson regression model parameters are estimated from a pseudolikelihood and the corresponding variances are derived by applying Taylor linearization methods that are used in survey research. The proposed approach is evaluated using Monte Carlo simulations. An illustration is provided using data from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study of male smokers in Finland, where a case-cohort study of serum glucose level and pancreatic cancer was analyzed. Copyright © 2012 John Wiley & Sons, Ltd.

Factors associated with smoking cessation in Brazil.

PubMed

Tejada, Cesar Augusto Oviedo; Ewerling, Fernanda; Santos, Anderson Moreira Aristides dos; Bertoldi, Andréa Dâmaso; Menezes, Ana Maria

2013-08-01

Tobacco has been identified as the drug with the highest addiction rate and the leading cause of avoidable deaths. The current study thus aimed to identify the determinants of smoking cessation in a Brazilian population sample based on data from the National Household Sample Survey for 2008. The study analyzed socioeconomic, residential, and health-related data as well as individual habits. Data analysis used Poisson regression. The following factors were associated with smoking cessation: age 45 years or older, higher income, medical consultation in the previous 12 months, private health plan, physical exercise, believing that smoking is bad for one's health and that cigarette smoke is harmful to passive smokers, and Internet access in the household. Subjects with heart conditions, diabetes, and cancer were also more prone to quit smoking.

Multi-Parameter Linear Least-Squares Fitting to Poisson Data One Count at a Time

NASA Technical Reports Server (NTRS)

Wheaton, W.; Dunklee, A.; Jacobson, A.; Ling, J.; Mahoney, W.; Radocinski, R.

1993-01-01

A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multi-component linear model, with underlying physical count rates or fluxes which are to be estimated from the data.

Using a Modification of the Capture-Recapture Model To Estimate the Need for Substance Abuse Treatment.

ERIC Educational Resources Information Center

Maxwell, Jane Carlisle; Pullum, Thomas W.

2001-01-01

Applied the capture-recapture model, through a Poisson regression to a time series of data for admissions to treatment from 1987 to 1996 to estimate the number of heroin addicts in Texas who are "at-risk" for treatment. The entire data set produced estimates that were lower and more plausible than those produced by drawing samples,…

A Bayesian approach to parameter and reliability estimation in the Poisson distribution.

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1972-01-01

For life testing procedures, a Bayesian analysis is developed with respect to a random intensity parameter in the Poisson distribution. Bayes estimators are derived for the Poisson parameter and the reliability function based on uniform and gamma prior distributions of that parameter. A Monte Carlo procedure is implemented to make possible an empirical mean-squared error comparison between Bayes and existing minimum variance unbiased, as well as maximum likelihood, estimators. As expected, the Bayes estimators have mean-squared errors that are appreciably smaller than those of the other two.

Intraurban Differences in the Use of Ambulatory Health Services in a Large Brazilian City

PubMed Central

Lima-Costa, Maria Fernanda; Proietti, Fernando Augusto; Cesar, Cibele C.; Macinko, James

2010-01-01

A major goal of health systems is to reduce inequities in access to services, that is, to ensure that health care is provided based on health needs rather than social or economic factors. This study aims to identify the determinants of health services utilization among adults in a large Brazilian city and intraurban disparities in health care use. We combine household survey data with census-derived classification of social vulnerability of each household’s census tract. The dependent variable was utilization of physician services in the prior 12 months, and the independent variables included predisposing factors, health needs, enabling factors, and context. Prevalence ratios and 95% confidence intervals were estimated by the Hurdle regression model, which combined Poisson regression analysis of factors associated with any doctor visits (dichotomous variable) and zero-truncated negative binomial regression for the analysis of factors associated with the number of visits among those who had at least one. Results indicate that the use of health services was greater among women and increased with age, and was determined primarily by health needs and whether the individual had a regular doctor, even among those living in areas of the city with the worst socio-environmental indicators. The experience of Belo Horizonte may have implications for other world cities, particularly in the development and use of a comprehensive index to identify populations at risk and in order to guide expansion of primary health care services as a means of enhancing equity in health. PMID:21104332

Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter.

PubMed

Lord, Dominique

2006-07-01

There has been considerable research conducted on the development of statistical models for predicting crashes on highway facilities. Despite numerous advancements made for improving the estimation tools of statistical models, the most common probabilistic structure used for modeling motor vehicle crashes remains the traditional Poisson and Poisson-gamma (or Negative Binomial) distribution; when crash data exhibit over-dispersion, the Poisson-gamma model is usually the model of choice most favored by transportation safety modelers. Crash data collected for safety studies often have the unusual attributes of being characterized by low sample mean values. Studies have shown that the goodness-of-fit of statistical models produced from such datasets can be significantly affected. This issue has been defined as the "low mean problem" (LMP). Despite recent developments on methods to circumvent the LMP and test the goodness-of-fit of models developed using such datasets, no work has so far examined how the LMP affects the fixed dispersion parameter of Poisson-gamma models used for modeling motor vehicle crashes. The dispersion parameter plays an important role in many types of safety studies and should, therefore, be reliably estimated. The primary objective of this research project was to verify whether the LMP affects the estimation of the dispersion parameter and, if it is, to determine the magnitude of the problem. The secondary objective consisted of determining the effects of an unreliably estimated dispersion parameter on common analyses performed in highway safety studies. To accomplish the objectives of the study, a series of Poisson-gamma distributions were simulated using different values describing the mean, the dispersion parameter, and the sample size. Three estimators commonly used by transportation safety modelers for estimating the dispersion parameter of Poisson-gamma models were evaluated: the method of moments, the weighted regression, and the maximum likelihood method. In an attempt to complement the outcome of the simulation study, Poisson-gamma models were fitted to crash data collected in Toronto, Ont. characterized by a low sample mean and small sample size. The study shows that a low sample mean combined with a small sample size can seriously affect the estimation of the dispersion parameter, no matter which estimator is used within the estimation process. The probability the dispersion parameter becomes unreliably estimated increases significantly as the sample mean and sample size decrease. Consequently, the results show that an unreliably estimated dispersion parameter can significantly undermine empirical Bayes (EB) estimates as well as the estimation of confidence intervals for the gamma mean and predicted response. The paper ends with recommendations about minimizing the likelihood of producing Poisson-gamma models with an unreliable dispersion parameter for modeling motor vehicle crashes.

A prospective cohort study of postoperative complications in the management of perforated peptic ulcer.

PubMed

Sharma, Smita S; Mamtani, Manju R; Sharma, Mamta S; Kulkarni, Hemant

2006-06-16

With dwindling rates of postoperative mortality in perforated peptic ulcer that is attributable to H2-receptor blocker usage, there is a need to shift the focus towards the prevention of postoperative morbidity. Further, the simultaneous contribution of several putative clinical predictors to this postoperative morbidity is not fully appreciated. Our objective was to assess the predictors of the risk, rate and number of postoperative complications in surgically treated patients of perforated peptic ulcer. In a prospective cohort study of 96 subjects presenting as perforated peptic ulcer and treated using Graham's omentoplatsy patch or gastrojejunostomy (with total truncal vagotomy), we assessed the association of clinical predictors with three domains of postoperative complications: the risk of developing a complication, the rate of developing the first complication and the risk of developing higher number of complications. We used multiple regression methods - logistic regression, Cox proportional hazards regression and Poisson regression, respectively - to examine the association of the predictors with these three domains. We observed that the risk of developing a postoperative complication was significantly influenced by the presence of a concomitant medical illness [odds ratio (OR) = 8.9, p = 0.001], abdominal distension (3.8, 0.048) and a need of blood transfusion (OR = 8.2, p = 0.027). Using Poisson regression, it was observed that the risk for a higher number of complications was influenced by the same three factors [relative risk (RR) = 2.6, p = 0.015; RR = 4.6, p < 0.001; and RR = 2.4, p = 0.002; respectively]. However, the rate of development of complications was influenced by a history suggestive of shock [relative hazards (RH) = 3.4, p = 0.002] and A- blood group (RH = 4.7, p = 0.04). Abdominal distension, presence of a concomitant medical illness and a history suggestive of shock at the time of admission warrant a closer and alacritous postoperative management in patients of perforated peptic ulcer.

Association between educational level and access to safe abortion in a Brazilian population.

PubMed

Dias, Tábata Z; Passini, Renato; Duarte, Graciana A; Sousa, Maria H; Faúndes, Aníbal

2015-03-01

To evaluate sociodemographic factors associated with induced abortion. As part of a cross-sectional, descriptive study, 15 800 civil servants from Campinas, Brazil, were invited to complete a self-administered questionnaire about absolutely unwanted pregnancies in January 2010. Bivariate analysis and multivariate Poisson regression analysis were used to explore the associations between induced abortion and sociodemographic characteristics. Overall, 1660 questionnaires were returned. Unwanted pregnancy was reported by 296 (17.8%) respondents, of whom 165 (55.7%) resorted to abortion. Multiple regression analysis showed that college education was the only variable associated with an increased chance of abortion. Among 157 participants who answered questions about the abortion procedure, 97 (61.8%) reported that it had been performed by a physician. Following abortion, 35 (22.9%) of 153 reported that medical care was required and 26 (16.6%) of 157 reported hospitalization, principally those with a lower level of education and those whose abortion had been performed by a nonphysician. Compared with women with a college education, those with a lower education level were less likely to terminate an absolutely unwanted pregnancy and to have an abortion performed by a physician, and they were more likely to have complications. These findings confirm the social inequalities associated with abortion in Brazil. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Spirituality and Resilience Among Mexican American IPV Survivors.

PubMed

de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria

2016-12-01

Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.

Social stressors and alcohol use among immigrant sexual and gender minority Latinos in a nontraditional settlement state.

PubMed

Gilbert, Paul A; Perreira, Krista; Eng, Eugenia; Rhodes, Scott D

2014-09-01

We sought to quantify the association of social stressors with alcohol use among immigrant sexual and gender minority Latinos in North Carolina (n = 190). We modeled any drinking in past year using logistic regression and heavy episodic drinking in past 30 days using Poisson regression. Despite a large proportion of abstainers, there were indications of hazardous drinking. Among current drinkers, 63% reported at least one heavy drinking episode in past 30 days. Ethnic discrimination increased, and social support decreased, odds of any drinking in past year. Social support moderated the associations of English use and ethnic discrimination with heavy episodic drinking.

QMRA for Drinking Water: 2. The Effect of Pathogen Clustering in Single-Hit Dose-Response Models.

PubMed

Nilsen, Vegard; Wyller, John

2016-01-01

Spatial and/or temporal clustering of pathogens will invalidate the commonly used assumption of Poisson-distributed pathogen counts (doses) in quantitative microbial risk assessment. In this work, the theoretically predicted effect of spatial clustering in conventional "single-hit" dose-response models is investigated by employing the stuttering Poisson distribution, a very general family of count distributions that naturally models pathogen clustering and contains the Poisson and negative binomial distributions as special cases. The analysis is facilitated by formulating the dose-response models in terms of probability generating functions. It is shown formally that the theoretical single-hit risk obtained with a stuttering Poisson distribution is lower than that obtained with a Poisson distribution, assuming identical mean doses. A similar result holds for mixed Poisson distributions. Numerical examples indicate that the theoretical single-hit risk is fairly insensitive to moderate clustering, though the effect tends to be more pronounced for low mean doses. Furthermore, using Jensen's inequality, an upper bound on risk is derived that tends to better approximate the exact theoretical single-hit risk for highly overdispersed dose distributions. The bound holds with any dose distribution (characterized by its mean and zero inflation index) and any conditional dose-response model that is concave in the dose variable. Its application is exemplified with published data from Norovirus feeding trials, for which some of the administered doses were prepared from an inoculum of aggregated viruses. The potential implications of clustering for dose-response assessment as well as practical risk characterization are discussed. © 2016 Society for Risk Analysis.

Transient finite element analysis of electric double layer using Nernst-Planck-Poisson equations with a modified Stern layer.

PubMed

Lim, Jongil; Whitcomb, John; Boyd, James; Varghese, Julian

2007-01-01

A finite element implementation of the transient nonlinear Nernst-Planck-Poisson (NPP) and Nernst-Planck-Poisson-modified Stern (NPPMS) models is presented. The NPPMS model uses multipoint constraints to account for finite ion size, resulting in realistic ion concentrations even at high surface potential. The Poisson-Boltzmann equation is used to provide a limited check of the transient models for low surface potential and dilute bulk solutions. The effects of the surface potential and bulk molarity on the electric potential and ion concentrations as functions of space and time are studied. The ability of the models to predict realistic energy storage capacity is investigated. The predicted energy is much more sensitive to surface potential than to bulk solution molarity.

Investigating the relationship between jobs-housing balance and traffic safety.

PubMed

Xu, Chengcheng; Li, Haojie; Zhao, Jingya; Chen, Jun; Wang, Wei

2017-10-01

This study aimed to investigate the effects of jobs-housing balance on traffic safety. The crash, demographic characteristics, employment, road network, household characteristics and traffic data were collected from the Los Angeles in 2010. One-way ANOVA tests indicated that the jobs-housing ratio significantly affects traffic safety in terms of crash frequency at traffic analysis zone (TAZ). To quantify the safety impacts of jobs-housing balance, the semi-parametric geographically weighted Poisson regression (S-GWPR) was further used to link crash frequency at TAZ with jobs-housing ratio and other contributing factors. The S-GWPR provides better fitness to the data than do the generalized linear regression, as the S-GWPR accounts for the spatial heterogeneity. The S-GWPR results showed that the jobs-housing relationship has a significant association with crash frequency at TAZ when the factors of traffic, network, and household characteristics are controlled. Crash frequency at TAZ level increases with an increase in the jobs-housing ratio. To further investigate the interactive effects between jobs-housing ratio and other factors, a comparative analysis was conducted to compare the variable elasticities under different jobs-housing ratios. The results indicate considerable interactive effects that traffic conditions and road network characteristics have different effects on crash frequency under various jobs-housing ratios. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bacterial diversity in saliva and oral health-related conditions: the Hisayama Study

NASA Astrophysics Data System (ADS)

Takeshita, Toru; Kageyama, Shinya; Furuta, Michiko; Tsuboi, Hidenori; Takeuchi, Kenji; Shibata, Yukie; Shimazaki, Yoshihiro; Akifusa, Sumio; Ninomiya, Toshiharu; Kiyohara, Yutaka; Yamashita, Yoshihisa

2016-02-01

This population-based study determined the salivary microbiota composition of 2,343 adult residents of Hisayama town, Japan, using 16S rRNA gene next-generation high-throughput sequencing. Of 550 identified species-level operational taxonomic units (OTUs), 72 were common, in ≥75% of all individuals, as well as in ≥75% of the individuals in the lowest quintile of phylogenetic diversity (PD). These “core” OTUs constituted 90.9 ± 6.1% of each microbiome. The relative abundance profiles of 22 of the core OTUs with mean relative abundances ≥1% were stratified into community type I and community type II by partitioning around medoids clustering. Multiple regression analysis revealed that a lower PD was associated with better conditions for oral health, including a lower plaque index, absence of decayed teeth, less gingival bleeding, shallower periodontal pockets and not smoking, and was also associated with tooth loss. By contrast, multiple Poisson regression analysis demonstrated that community type II, as characterized by a higher ratio of the nine dominant core OTUs, including Neisseria flavescens, was implicated in younger age, lower body mass index, fewer teeth with caries experience, and not smoking. Our large-scale data analyses reveal variation in the salivary microbiome among Japanese adults and oral health-related conditions associated with the salivary microbiome.

Racial/Ethnic Differences in Cardiovascular Symptoms in Four Major Racial/Ethnic Groups of Midlife Women: A Secondary Analysis

PubMed Central

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2015-01-01

Ethnic minority midlife women frequently do not recognize cardiovascular symptoms that they experience during the menopausal transition. Racial/ethnic differences in cardiovascular symptoms are postulated as a plausible reason for their lack of knowledge and recognition of the symptoms. The purpose of this study was to explore racial/ethnic differences in midlife women’s cardiovascular symptoms and to determine the factors related to these symptoms in each racial/ethnic group. This was a secondary analysis of the data from a larger study among 466 participants, collected from 2006 to 2011. The instruments included questions on background characteristics, health and menopausal status and the Cardiovascular Symptom Index for Midlife Women. The data were analyzed using inferential statistics, including Poisson regression and logistic regression analyses. Significant racial/ethnic differences were observed in the total numbers and total severity scores of cardiovascular symptoms (p<0.01). Non-Hispanic Asians had significantly lower total numbers and total severity scores compared to other racial/ethnic groups (p<0.05). The demographic and health factors associated with cardiovascular symptoms were somewhat different in each racial/ethnic group. Further studies are needed about possible reasons for the racial/ethnic differences and the factors associated with cardiovascular symptoms in each racial/ethnic group. PMID:25826460

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary 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). PMID:29307954

Predictors of postoperative bleeding after vitrectomy for vitreous hemorrhage in patients with diabetic retinopathy.

PubMed

Motoda, Saori; Shiraki, Nobuhiko; Ishihara, Takuma; Sakaguchi, Hirokazu; Kabata, Daijiro; Takahara, Mitsuyoshi; Kimura, Takekazu; Kozawa, Junji; Imagawa, Akihisa; Nishida, Kohji; Shintani, Ayumi; Iwahashi, Hiromi; Shimomura, Iichiro

2017-12-19

To clarify the association between perioperative variables and postoperative bleeding in pars plana vitrectomy for vitreous hemorrhage in diabetic retinopathy. The present retrospective study enrolled 72 eyes of 64 patients who were admitted to Osaka University Hospital between April 2010 and March 2014, and underwent vitrectomy for vitreous hemorrhage as a result of diabetic retinopathy. Postoperative bleeding developed in 12 eyes. Using binomial logistic regression analysis, we found that the duration of operation was the only significant variable associated with postoperative bleeding within 12 weeks after vitrectomy. Furthermore, Poisson regression analysis identified fasting blood glucose just before vitrectomy, no treatment with antiplatelet drugs and treatment with antihypertensive drugs, as well as duration of operation, to be significantly associated with the frequency of bleeding within 52 weeks after vitrectomy. Long duration of operation can be used to predict bleeding within both 12 and 52 weeks after vitrectomy. In addition, fasting blood glucose just before vitrectomy, no treatment with antiplatelet drugs and treatment with antihypertensive drugs might be risk factors for postoperative bleeding up to 1 year after vitrectomy. © 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

High Incidence of Breast Cancer in Light-Polluted Areas with Spatial Effects in Korea.

PubMed

Kim, Yun Jeong; Park, Man Sik; Lee, Eunil; Choi, Jae Wook

2016-01-01

We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in R2 from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects.

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).

Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

PubMed

Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

2018-02-01

There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fractional poisson--a simple dose-response model for human norovirus.

PubMed

Messner, Michael J; Berger, Philip; Nappier, Sharon P

2014-10-01

This study utilizes old and new Norovirus (NoV) human challenge data to model the dose-response relationship for human NoV infection. The combined data set is used to update estimates from a previously published beta-Poisson dose-response model that includes parameters for virus aggregation and for a beta-distribution that describes variable susceptibility among hosts. The quality of the beta-Poisson model is examined and a simpler model is proposed. The new model (fractional Poisson) characterizes hosts as either perfectly susceptible or perfectly immune, requiring a single parameter (the fraction of perfectly susceptible hosts) in place of the two-parameter beta-distribution. A second parameter is included to account for virus aggregation in the same fashion as it is added to the beta-Poisson model. Infection probability is simply the product of the probability of nonzero exposure (at least one virus or aggregate is ingested) and the fraction of susceptible hosts. The model is computationally simple and appears to be well suited to the data from the NoV human challenge studies. The model's deviance is similar to that of the beta-Poisson, but with one parameter, rather than two. As a result, the Akaike information criterion favors the fractional Poisson over the beta-Poisson model. At low, environmentally relevant exposure levels (<100), estimation error is small for the fractional Poisson model; however, caution is advised because no subjects were challenged at such a low dose. New low-dose data would be of great value to further clarify the NoV dose-response relationship and to support improved risk assessment for environmentally relevant exposures. © 2014 Society for Risk Analysis Published 2014. This article is a U.S. Government work and is in the public domain for the U.S.A.

Angiogenic Signaling in Living Breast Tumor Models

DTIC Science & Technology

2007-06-01

Poisson distributed random noise is added in an amount relative to the desired signal to noise ratio. We fit the data using a regressive fitting...AD_________________ Award Number: W81XWH-05-1-0396 TITLE: Angiogenic Signaling in Living Breast...CONTRACT NUMBER Angiogenic Signaling in Living Breast Tumor Models 5b. GRANT NUMBER W81XWH-05-1-0396 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Long-term sickness absence during pregnancy and the gender balance of workplaces.

PubMed

Melsom, Anne M

2014-11-01

This study addresses how the gender composition of workplaces affects pregnant women's sickness absence. It also assesses whether an observed association may be explaine by differential selection to female- or male-dominated workplaces. The analyses are based on Norwegian registry data from 2003-2011. Using Poisson regressions with detailed control for occupational categories, I examine whether the number of absence days are associated with the proportion of females at the workplace. I address possible selection effects by Poisson regressions with fixed individual effects using only within-individual variation on women with two or more pregnancies during the time window. The analyses indicate a positive and significant relationship between the female proportion in workplaces and sickness absence rates during pregnancy. Analyses limited to within-individual variation also show positive and significant effects of similar strength, indicating that the observed relationship is not due to differential selection of absence-prone pregnant workers to female-dominated workplaces. The proportion of female individuals at workplaces is positively associated with sickness absence rates during pregnancy this association is not likely explained by occupational nor individual characteristics the results are consistent with absence culture theory and more lenient norms concerning sickness absence during pregnancy at female-dominated workplaces. © 2014 the Nordic Societies of Public Health.

Anonymous birth law saves babies--optimization, sustainability and public awareness.

PubMed

Grylli, Chryssa; Brockington, Ian; Fiala, Christian; Huscsava, Mercedes; Waldhoer, Thomas; Klier, Claudia M

2016-04-01

The aims of this study are to assess the impact of Austria's anonymous birth law from the time relevant statistical records are available and to evaluate the use of hatches versus anonymous hospital delivery. This study is a complete census of police-reported neonaticides (1975-2012) as well as anonymous births including baby hatches in Austria during 2002-2012. The time trends of neonaticide rates, anonymous births and baby hatches were analysed by means of Poisson and logistic regression model. Predicted and observed rates were derived and compared using a Bayesian Poisson regression model. Predicted numbers of neonaticides for the period of the active awareness campaign, 2002-2004, were more than three times larger than the observed number (p = 0.0067). Of the 365 women who benefitted from this legislation, only 11.5% chose to put their babies in a baby hatch. Since the law was introduced, a significant decreasing tendency of numbers of anonymous births (p = 047) was observed, while there was significant increase of neonaticide rates (p = 0.0001). The implementation of the anonymous delivery law is associated with a decrease in the number of police-reported neonaticides. The subsequent significantly decreasing numbers of anonymous births with an accompanying increase of neonaticides represents additional evidence for the effectiveness of the measure.

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.

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Composite laminates with negative through-the-thickness Poisson's ratios

NASA Technical Reports Server (NTRS)

Herakovich, C. T.

1984-01-01

A simple analysis using two dimensional lamination theory combined with the appropriate three dimensional anisotropic constitutive equation is presented to show some rather surprising results for the range of values of the through-the-thickness effective Poisson's ratio nu sub xz for angle ply laminates. Results for graphite-epoxy show that the through-the-thickness effective Poisson's ratio can range from a high of 0.49 for a 90 laminate to a low of -0.21 for a + or - 25s laminate. It is shown that negative values of nu sub xz are also possible for other laminates.

Composite laminates with negative through-the-thickness Poisson's ratios

NASA Technical Reports Server (NTRS)

Herakovich, C. T.

1984-01-01

A simple analysis using two-dimensional lamination theory combined with the appropriate three-dimensional anisotropic constitutive equation is presented to show some rather surprising results for the range of values of the through-the-thickness effective Poisson's ratio nu sub xz for angle ply laminates. Results for graphite-epoxy show that the through-the-thickness effective Poisson's ratio can range from a high of 0.49 for a 90 laminate to a low of -0.21 for a + or - 25s laminate. It is shown that negative values of nu sub xz are also possible for other laminates.

Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.

PubMed

Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha

2016-02-01

The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.

Probabilistic reasoning in data analysis.

PubMed

Sirovich, Lawrence

2011-09-20

This Teaching Resource provides lecture notes, slides, and a student assignment for a lecture on probabilistic reasoning in the analysis of biological data. General probabilistic frameworks are introduced, and a number of standard probability distributions are described using simple intuitive ideas. Particular attention is focused on random arrivals that are independent of prior history (Markovian events), with an emphasis on waiting times, Poisson processes, and Poisson probability distributions. The use of these various probability distributions is applied to biomedical problems, including several classic experimental studies.

Photon counting statistics analysis of biophotons from hands.

PubMed

Jung, Hyun-Hee; Woo, Won-Myung; Yang, Joon-Mo; Choi, Chunho; Lee, Jonghan; Yoon, Gilwon; Yang, Jong S; Soh, Kwang-Sup

2003-05-01

The photon counting statistics of biophotons emitted from hands is studied with a view to test its agreement with the Poisson distribution. The moments of observed probability up to seventh order have been evaluated. The moments of biophoton emission from hands are in good agreement while those of dark counts of photomultiplier tube show large deviations from the theoretical values of Poisson distribution. The present results are consistent with the conventional delta-value analysis of the second moment of probability.

A regularization corrected score method for nonlinear regression models with covariate error.

PubMed

Zucker, David M; Gorfine, Malka; Li, Yi; Tadesse, Mahlet G; Spiegelman, Donna

2013-03-01

Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and interval estimates of the regression coefficients. We present here a new general method for adjusting for covariate error. Our method consists of an approximate version of the Stefanski-Nakamura corrected score approach, using the method of regularization to obtain an approximate solution of the relevant integral equation. We develop the theory in the setting of classical likelihood models; this setting covers, for example, linear regression, nonlinear regression, logistic regression, and Poisson regression. The method is extremely general in terms of the types of measurement error models covered, and is a functional method in the sense of not involving assumptions on the distribution of the true covariate. We discuss the theoretical properties of the method and present simulation results in the logistic regression setting (univariate and multivariate). For illustration, we apply the method to data from the Harvard Nurses' Health Study concerning the relationship between physical activity and breast cancer mortality in the period following a diagnosis of breast cancer. Copyright © 2013, The International Biometric Society.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

PubMed

Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric

2015-12-30

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

[Travel time and participation in breast cancer screening in a region with high population dispersion].

PubMed

Borda, Alfredo; Sanz, Belén; Otero, Laura; Blasco, Teresa; García-Gómez, Francisco J; de Andrés, Fuencisla

2011-01-01

To analyze the association between travel time and participation in a breast cancer screening program adjusted for contextual variables in the province of Segovia (Spain). We performed an ecological study using the following data sources: the Breast Cancer Early Detection Program of the Primary Care Management of Segovia, the Population and Housing Census for 2001 and the municipal register for 2006-2007. The study period comprised January 2006 to December 2007. Dependent variables consisted of the municipal participation rate and the desired level of municipal participation (greater than or equal to 70%). The key independent variable was travel time from the municipality to the mammography unit. Covariables consisted of the municipalities' demographic and socioeconomic factors. We performed univariate and multivariate Poisson regression analyses of the participation rate, and logistic regression of the desired participation level. The sample was composed of 178 municipalities. The mean participation rate was 75.2%. The desired level of participation (≥ 70%) was achieved in 119 municipalities (67%). In the multivariate Poisson and logistic regression analyses, longer travel time was associated with a lower participation rate and with lower participation after adjustment was made for geographic density, age, socioeconomic status and dependency ratio, with a relative risk index of 0.88 (95% CI: 0.81-0.96) and an odds ratio of 0.22 (95% CI: 0.1-0.47), respectively. Travel time to the mammography unit may help to explain participation in breast cancer screening programs. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.

Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do

2015-01-01

The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system. Copyright © 2014 Elsevier B.V. All rights reserved.

[Prevalence of weapons possession and associated factors and involvement in physical aggression among adolescents 15 to 18 years of age: a population-based study].

PubMed

Silva, Ricardo Azevedo da; Jansen, Karen; Godoy, Russélia Vanila; Souza, Luciano Dias Mattos; Horta, Bernardo Lessa; Pinheiro, Ricardo Tavares

2009-12-01

This cross-sectional, population-based study aimed to evaluate the prevalence of weapons possession and associated factors and involvement in physical aggression among adolescents 15 to 18 years of age (n = 960) in the city of Pelotas, Rio Grande do Sul State, Brazil. Ninety of the city's 448 census tracts were selected, and 86 houses in each tract were visited. The statistical analysis used Poisson regression. Prevalence rates in the sample were 22.8% for involvement in fights with physical aggression and 9.6% for weapons possession in the previous 12 months. The study concluded that young males that use alcohol and/or illegal drugs and present minor psychiatric disorders show a higher probability of weapons possession and involvement in physical fights.

Individual and areal risk factors for road traffic injury deaths: nationwide study in South Korea.

PubMed

Park, Kunhee; Hwang, Seung-Sik; Lee, Jin-Seok; Kim, Yoon; Kwon, Soonman

2010-07-01

This study determines the individual and areal risk factors for road traffic injury deaths in South Korea. The risk factors that influence road traffic injury deaths are defined by multilevel Poisson regression analysis. It is seen that not only demographic factors but also individual educational level, which represents socioeconomic status, influences road traffic injury deaths. The material deprivation index, which represents areal socioeconomic status, and W statistics, as a measure of the quality of the emergency medical system in an area, also influence road traffic injury deaths. Based on this study, the most vulnerable group for road traffic injury deaths is elderly men with a low level of education who live in the most deprived areas.Therefore, preventive policies focusing on both these areas and this population demographic should be established.

Hospitalization for primary care susceptible conditions, health spending and Family Health Strategy: an analysis of trends.

PubMed

Morimoto, Tissiani; Costa, Juvenal Soares Dias da

2017-03-01

The goal of this study was to analyze the trend over time of hospitalizations due to conditions susceptible to primary healthcare (HCSPC), and how it relates to healthcare spending and Family Health Strategy (FHS) coverage in the city of São Leopoldo, Rio Grande do Sul State, Brazil, between 2003 and 2012. This is an ecological, time-trend study. We used secondary data available in the Unified Healthcare System Hospital Data System, the Primary Care Department and Public Health Budget Data System. The analysis compared HCSPC using three-year moving averages and Poisson regressions or negative binomials. We found no statistical significance in decreasing HCSPC indicators and primary care spending in the period analyzed. Healthcare spending, per-capita spending and FHS coverage increased significantly, but we found no correlation with HCSPC. The results show that, despite increases in the funds invested and population covered by FHS, they are still insufficient to deliver the level of care the population requires.

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

Factors associated with traditional Chinese medicine utilization among urban community health centers in Hubei Province of China.

PubMed

Cai, Yi; Mao, Zongfu; Xu, Bruce; Wu, Bei

2015-03-01

This study aims to examine resources and utilization of traditional Chinese medicine (TCM) and factors influencing TCM utilization in urban community health centers (CHCs) in Hubei Province of China. A cross-sectional survey including 234 government-owned CHCs was conducted in 2009. One-way analysis of variance analysis and a Poisson regression model were used to examine distribution of TCM resources and factors influencing TCM utilization. This study found unequal distribution of TCM resources among districts. TCM outpatient visits were positively associated with higher economic development districts, lower initial capital investment of the CHCs, health services covered by health insurance, higher qualification of TCM physicians, provision of TCM health records and rehabilitation, and greater availability of herbal medicine. To achieve equal access to TCM services, policy makers should consider the socioeconomic differences and income groups, provide training for TCM physicians, build pathway to recruit senior TCM physicians, and cover more TCM therapies by health insurance. © 2013 APJPH.

Housefly Population Density Correlates with Shigellosis among Children in Mirzapur, Bangladesh: A Time Series Analysis

PubMed Central

Farag, Tamer H.; Faruque, Abu S.; Wu, Yukun; Das, Sumon K.; Hossain, Anowar; Ahmed, Shahnawaz; Ahmed, Dilruba; Nasrin, Dilruba; Kotloff, Karen L.; Panchilangam, Sandra; Nataro, James P.; Cohen, Dani; Blackwelder, William C.; Levine, Myron M.

2013-01-01

Background Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD) among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. Methods Stool samples from 843 children presenting to Kumudini Hospital during 2009–2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization) were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs) were calculated using the Bruzzi method, with standard errors via jackknife procedure. Findings Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks) (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count), an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. Interpretation Houseflies may play an important role in the seasonal transmission of Shigella in some developing country ecologies. Interventions to control houseflies should be evaluated as possible additions to the public health arsenal to diminish Shigella (and perhaps other causes of) diarrheal infection. PMID:23818998

Housefly population density correlates with shigellosis among children in Mirzapur, Bangladesh: a time series analysis.

PubMed

Farag, Tamer H; Faruque, Abu S; Wu, Yukun; Das, Sumon K; Hossain, Anowar; Ahmed, Shahnawaz; Ahmed, Dilruba; Nasrin, Dilruba; Kotloff, Karen L; Panchilangam, Sandra; Nataro, James P; Cohen, Dani; Blackwelder, William C; Levine, Myron M

2013-01-01

Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD) among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. Stool samples from 843 children presenting to Kumudini Hospital during 2009-2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization) were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs) were calculated using the Bruzzi method, with standard errors via jackknife procedure. Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks) (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count), an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. Houseflies may play an important role in the seasonal transmission of Shigella in some developing country ecologies. Interventions to control houseflies should be evaluated as possible additions to the public health arsenal to diminish Shigella (and perhaps other causes of) diarrheal infection.

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment.

PubMed

Rice, F L; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust. Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death. Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m(3) for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000). There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.

Trends in stage-specific incidence of prostate cancer in Norway, 1980-2010: a population-based study.

PubMed

Møller, Mette H; Kristiansen, Ivar S; Beisland, Christian; Rørvik, Jarle; Støvring, Henrik

2016-10-01

To estimate changes in the stage distribution of prostate cancer during the time period where opportunistic prostate-specific antigen (PSA) testing was introduced. Cancer stage, age, and year of diagnosis were obtained for all men aged >50 years diagnosed with prostate cancer in Norway during the period 1980-2010. Three calendar-time periods (1980-1989, 1990-2000, and 2001-2010) and three age groups (50-65, 66-74, and ≥75 years) were defined. Birth cohorts were categorised into four intervals: ≤1915, 1916-1925, 1926-1940 and ≥1941. We used Poisson regressions to conduct both a time period and cohort-based analysis of trends in the incidence of localised, regional, and distant cancer for each combination of age groups and calendar-time periods or birth cohorts, respectively. Additionally, we explored the effect of cohorts on the stage-specific incidence graphically with a Poisson regression using 5-year age groups, and by estimating cumulative incidence rates for each birth cohort. The annual incidence of localised cancers among men aged 50-65 and 66-74 years rose from 41.4 and 255.2 per 100 000, respectively, before the introduction of PSA testing to 137.9 and 418.7 in 2001-2010 afterwards, corresponding to 3.3 [95% confidence interval (CI) 3.1-3.5] and 1.6 (95% CI 1.6-1.7) fold increases. The incidence of regional cancers increased by a factor seven among men aged <75 years. The incidence of distant cancers in men aged ≥75 years decreased by 29% (95% CI 25-33%). These findings were confirmed in the cohort-based approach. Opportunistic PSA testing substantially increased the incidence of localised and regional prostate cancers among men aged 50-74 years, which was not fully compensated by the 30% decrease in incidence of distant prostate cancers in older men. © 2015 The Authors BJU International © 2015 BJU International Published by John Wiley & Sons Ltd.

Burnout among Swedish school teachers - a cross-sectional analysis.

PubMed

Arvidsson, Inger; Håkansson, Carita; Karlson, Björn; Björk, Jonas; Persson, Roger

2016-08-18

Teachers are at high risk of stress-related disorders. This study aimed to examine the occurrence of burnout in a sample of Swedish school-teachers, to test a combined measure of three burnout dimensions on the individual level, to characterize associations between burnout and factors encountered during work and leisure time, and to explore any differences between the genders. A questionnaire of occupational, sociodemographic and life-style factors was answered by 490 teachers in school years 4-9. Outcome measures were (a) the single burnout dimensions of exhaustion, cynicism and professional efficacy (Maslach Burnout Inventory-General Survey), and (b) a combined measure based on high or low values in the three dimensions. The combined measure was used to stratify the study population into four levels (0-3) of burnout. Multivariable Poisson regression was applied on level 2 + 3 vs. level 0 + 1, for variables that we considered as relevant risk factors for burn out. Half of the teachers reported low values in all three dimensions (level 0), whereas 15 were classified as having high burnout in at least two out of the three dimensions (level 2 + 3), and 4 % in all three dimensions (level 3). Almost all psychosocial factors were incrementally more unfavourably reported through the rising levels of burnout, and so were dissatisfaction with the computer workstation, pain, sleep problems and lack of personal recovery. There was no association between gender and rising levels of overall burnout (p > 0.30). Low self-efficacy, poor leadership, high job demands and teaching in higher grades were the variables most clearly associated with burnout in multivariable Poisson regression. Even if circa 50 % of the teachers appear do well with respect to burnout, the results points to the need of implementing multifaceted countermeasures that may serve to reduce burnout.

Early-life factors affect risk of pain and fever in infants during teething periods.

PubMed

Un Lam, Carolina; Hsu, Chin-Ying Stephen; Yee, Robert; Koh, David; Lee, Yung Seng; Chong, Mary Foong-Fong; Cai, Meijin; Kwek, Kenneth; Saw, Seang Mei; Gluckman, Peter; Chong, Yap Seng

2016-11-01

This longitudinal study aimed to investigate the prevalence of teething-related pain and fever and the early-life factors that may affect the risk of experiencing these disturbances within the first 1.5 years of life. Participants were recruited (n = 1033) through the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort (n = 1237). Interviews were performed tri-monthly regarding the prevalence of teething pain and fever in children from 6 to 18 months of age. Crude and multivariable analyses were conducted using Poisson-log regression models. Prevalence rates for teething pain and fever were 35.5 and 49.9 % respectively. Multivariable Poisson regression analysis showed maternal second-hand tobacco smoke (SHS) exposure to increase the risk of both pain (mean ratio = 1.35; p = 0.006) and fever (mean ratio = 1.22; p = 0.025), whereas SHS exposure plus active smoking further increased risk of teething pain in the children (mean ratio = 1.89; p = 0.029). Delivery via Caesarean section increased risk of teething pain (mean ratio = 1.27; p = 0.033), while prenatal plasma vitamin D insufficiency lowered such a risk (mean ratio = 0.62; p = 0.012). Compared to Chinese infants, Indian babies exhibited lower risk of teething pain and fever (both p ≤ 0.001). Early-life factors such as tobacco smoke exposure and vitamin insufficiency during pregnancy, ethnicity and childbirth via Caesarean section may significantly affect the child's susceptibility to teething-related pain and fever. Knowledge of prevalence and risk factors of teething disturbances may better equip primary caregivers and healthcare professionals to accurately detect teething-related local and/or systemic signs/symptoms and effectively facilitate tobacco cessation among pregnant women.

Household air pollution and stillbirths in India: analysis of the DLHS-II National Survey.

PubMed

Lakshmi, P V M; Virdi, Navkiran Kaur; Sharma, Atul; Tripathy, Jaya Prasad; Smith, Kirk R; Bates, Michael N; Kumar, Rajesh

2013-02-01

Several studies have linked biomass cooking fuel with adverse pregnancy outcomes such as preterm births, low birth weight and post-neonatal infant mortality, but very few have studied the associations with cooking fuel independent of other factors associated with stillbirths. We analyzed the data from 188,917 ever-married women aged 15-49 included in India's 2003-2004 District Level Household Survey-II to investigate the association between household use of cooking fuels (liquid petroleum gas/electricity, kerosene, biomass) and risk of stillbirth. Prevalence ratios (PRs) were obtained using Poisson regression with robust standard errors after controlling for several potentially confounding factors (socio-demographic and maternal health characteristics). Risk factors significantly associated with occurrence of stillbirth in the Poisson regression with robust standard errors model were: literacy status of the mother and father, lighting fuel and cooking fuel used, gravida status, history of previous abortion, whether the woman had an antenatal check up, age at last pregnancy >35 years, labor complications, bleeding complications, fetal and other complications, prematurity and home delivery. After controlling the effect of these factors, women who cook with firewood (PR 1.24; 95% CI: 1.08-1.41, p=0.003) or kerosene (PR 1.36; 95% CI: 1.10-1.67, p=0.004) were more likely to have experienced a stillbirth than those who cook with LPG/electricity. Kerosene lamp use was also associated with stillbirths compared to electric lighting (PR 1.15; 95% CI: 1.06-1.25, p=0.001). The population attributable risk of firewood as cooking fuel for stillbirths in India was 11% and 1% for kerosene cooking. Biomass and kerosene cooking fuels are associated with stillbirth occurrence in this population sample. Assuming these associations are causal, about 12% of stillbirths in India could be prevented by providing access to cleaner cooking fuel. Copyright © 2012 Elsevier Inc. All rights reserved.

Reporting quality of randomised controlled trial abstracts on age-related macular degeneration health care: a cross-sectional quantification of the adherence to CONSORT abstract reporting recommendations.

PubMed

Baulig, Christine; Krummenauer, Frank; Geis, Berit; Tulka, Sabrina; Knippschild, Stephanie

2018-05-22

To assess the reporting quality of randomised controlled trial (RCT) abstracts on age-related macular degeneration (AMD) healthcare, to evaluate the adherence to the Consolidated Standards of Reporting Trials (CONSORT) statement's recommendations on minimum abstract information and to identify journal characteristics associated with abstract reporting quality. Cross-sectional evaluation of RCT abstracts on AMD healthcare. A PubMed search was implemented to identify RCT abstracts on AMD healthcare published in the English language between January 2004 and December 2013. Data extraction was performed by two parallel readers independently by means of a documentation format in accordance with the 16 items of the CONSORT checklist for abstracts. The total number of criteria fulfilled by an abstract was derived as primary endpoint of the investigation; incidence rate ratios (IRRs) with unadjusted 95% CI were estimated by means of multiple Poisson regression to identify journal and article characteristics (publication year, multicentre design, structured abstract recommendations, effective sample size, effective abstract word counts and journal impact factor) possibly associated with the total number of fulfilled items. 136 of 673 identified abstracts (published in 36 different journals) fulfilled all eligibility criteria. The median number of fulfilled items was 7 (95% CI 7 to 8). No abstract reported all 16 recommended items; the maximum total number was 14, the minimum 3 of 16 items. Multivariate analysis only demonstrated the abstracts' word counts as being significantly associated with a better reporting of abstracts (Poisson regression-based IRR 1.002, 95% CI 1.001 to 1.003). Reporting quality of RCT abstracts on AMD investigations showed a considerable potential for improvement to meet the CONSORT abstract reporting recommendations. Furthermore, word counts of abstracts were identified as significantly associated with the overall abstract reporting quality. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A novel method for the accurate evaluation of Poisson's ratio of soft polymer materials.

PubMed

Lee, Jae-Hoon; Lee, Sang-Soo; Chang, Jun-Dong; Thompson, Mark S; Kang, Dong-Joong; Park, Sungchan; Park, Seonghun

2013-01-01

A new method with a simple algorithm was developed to accurately measure Poisson's ratio of soft materials such as polyvinyl alcohol hydrogel (PVA-H) with a custom experimental apparatus consisting of a tension device, a micro X-Y stage, an optical microscope, and a charge-coupled device camera. In the proposed method, the initial positions of the four vertices of an arbitrarily selected quadrilateral from the sample surface were first measured to generate a 2D 1st-order 4-node quadrilateral element for finite element numerical analysis. Next, minimum and maximum principal strains were calculated from differences between the initial and deformed shapes of the quadrilateral under tension. Finally, Poisson's ratio of PVA-H was determined by the ratio of minimum principal strain to maximum principal strain. This novel method has an advantage in the accurate evaluation of Poisson's ratio despite misalignment between specimens and experimental devices. In this study, Poisson's ratio of PVA-H was 0.44 ± 0.025 (n = 6) for 2.6-47.0% elongations with a tendency to decrease with increasing elongation. The current evaluation method of Poisson's ratio with a simple measurement system can be employed to a real-time automated vision-tracking system which is used to accurately evaluate the material properties of various soft materials.

Analysis of overdispersed count data: application to the Human Papillomavirus Infection in Men (HIM) Study.

PubMed

Lee, J-H; Han, G; Fulp, W J; Giuliano, A R

2012-06-01

The Poisson model can be applied to the count of events occurring within a specific time period. The main feature of the Poisson model is the assumption that the mean and variance of the count data are equal. However, this equal mean-variance relationship rarely occurs in observational data. In most cases, the observed variance is larger than the assumed variance, which is called overdispersion. Further, when the observed data involve excessive zero counts, the problem of overdispersion results in underestimating the variance of the estimated parameter, and thus produces a misleading conclusion. We illustrated the use of four models for overdispersed count data that may be attributed to excessive zeros. These are Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial models. The example data in this article deal with the number of incidents involving human papillomavirus infection. The four models resulted in differing statistical inferences. The Poisson model, which is widely used in epidemiology research, underestimated the standard errors and overstated the significance of some covariates.

Log Normal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of Alpha Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2008-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log normal distribution function (J Nucl Med 47, 6 (2006) 1049-1058) with the aid of an autoradiographic approach. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analyses of these data. Methods The measured distributions of alpha particle tracks per cell were subjected to statistical tests with Poisson (P), log normal (LN), and Poisson – log normal (P – LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL 210Po-citrate. When cells were exposed to 67 kBq/mL, the P – LN distribution function gave a better fit, however, the underlying activity distribution remained log normal. Conclusions The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:16741316

Pattern analysis of community health center location in Surabaya using spatial Poisson point process

NASA Astrophysics Data System (ADS)

Kusumaningrum, Choriah Margareta; Iriawan, Nur; Winahju, Wiwiek Setya

2017-11-01

Community health center (puskesmas) is one of the closest health service facilities for the community, which provide healthcare for population on sub-district level as one of the government-mandated community health clinics located across Indonesia. The increasing number of this puskesmas does not directly comply the fulfillment of basic health services needed in such region. Ideally, a puskesmas has to cover up to maximum 30,000 people. The number of puskesmas in Surabaya indicates an unbalance spread in all of the area. This research aims to analyze the spread of puskesmas in Surabaya using spatial Poisson point process model in order to get the effective location of Surabaya's puskesmas which based on their location. The results of the analysis showed that the distribution pattern of puskesmas in Surabaya is non-homogeneous Poisson process and is approched by mixture Poisson model. Based on the estimated model obtained by using Bayesian mixture model couple with MCMC process, some characteristics of each puskesmas have no significant influence as factors to decide the addition of health center in such location. Some factors related to the areas of sub-districts have to be considered as covariate to make a decision adding the puskesmas in Surabaya.

Poisson-Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain.

PubMed

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-03-29

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson-Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson-Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods.

Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

PubMed

Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

2012-12-01

A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA.

Extended Poisson process modelling and analysis of grouped binary data.

PubMed

Faddy, Malcolm J; Smith, David M

2012-05-01

A simple extension of the Poisson process results in binomially distributed counts of events in a time interval. A further extension generalises this to probability distributions under- or over-dispersed relative to the binomial distribution. Substantial levels of under-dispersion are possible with this modelling, but only modest levels of over-dispersion - up to Poisson-like variation. Although simple analytical expressions for the moments of these probability distributions are not available, approximate expressions for the mean and variance are derived, and used to re-parameterise the models. The modelling is applied in the analysis of two published data sets, one showing under-dispersion and the other over-dispersion. More appropriate assessment of the precision of estimated parameters and reliable model checking diagnostics follow from this more general modelling of these data sets. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparison of different ways of including baseline counts in negative binomial models for data from falls prevention trials.

PubMed

Zheng, Han; Kimber, Alan; Goodwin, Victoria A; Pickering, Ruth M

2018-01-01

A common design for a falls prevention trial is to assess falling at baseline, randomize participants into an intervention or control group, and ask them to record the number of falls they experience during a follow-up period of time. This paper addresses how best to include the baseline count in the analysis of the follow-up count of falls in negative binomial (NB) regression. We examine the performance of various approaches in simulated datasets where both counts are generated from a mixed Poisson distribution with shared random subject effect. Including the baseline count after log-transformation as a regressor in NB regression (NB-logged) or as an offset (NB-offset) resulted in greater power than including the untransformed baseline count (NB-unlogged). Cook and Wei's conditional negative binomial (CNB) model replicates the underlying process generating the data. In our motivating dataset, a statistically significant intervention effect resulted from the NB-logged, NB-offset, and CNB models, but not from NB-unlogged, and large, outlying baseline counts were overly influential in NB-unlogged but not in NB-logged. We conclude that there is little to lose by including the log-transformed baseline count in standard NB regression compared to CNB for moderate to larger sized datasets. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crystalline nucleation in undercooled liquids: a Bayesian data-analysis approach for a nonhomogeneous Poisson process.

PubMed

Filipponi, A; Di Cicco, A; Principi, E

2012-12-01

A Bayesian data-analysis approach to data sets of maximum undercooling temperatures recorded in repeated melting-cooling cycles of high-purity samples is proposed. The crystallization phenomenon is described in terms of a nonhomogeneous Poisson process driven by a temperature-dependent sample nucleation rate J(T). The method was extensively tested by computer simulations and applied to real data for undercooled liquid Ge. It proved to be particularly useful in the case of scarce data sets where the usage of binned data would degrade the available experimental information.

Evolution of deep gray matter volume across the human lifespan.

PubMed

Narvacan, Karl; Treit, Sarah; Camicioli, Richard; Martin, Wayne; Beaulieu, Christian

2017-08-01

Magnetic resonance imaging of subcortical gray matter structures, which mediate behavior, cognition and the pathophysiology of several diseases, is crucial for establishing typical maturation patterns across the human lifespan. This single site study examines T1-weighted MPRAGE images of 3 healthy cohorts: (i) a cross-sectional cohort of 406 subjects aged 5-83 years; (ii) a longitudinal neurodevelopment cohort of 84 subjects scanned twice approximately 4 years apart, aged 5-27 years at first scan; and (iii) a longitudinal aging cohort of 55 subjects scanned twice approximately 3 years apart, aged 46-83 years at first scan. First scans from longitudinal subjects were included in the cross-sectional analysis. Age-dependent changes in thalamus, caudate, putamen, globus pallidus, nucleus accumbens, hippocampus, and amygdala volumes were tested with Poisson, quadratic, and linear models in the cross-sectional cohort, and quadratic and linear models in the longitudinal cohorts. Most deep gray matter structures best fit to Poisson regressions in the cross-sectional cohort and quadratic curves in the young longitudinal cohort, whereas the volume of all structures except the caudate and globus pallidus decreased linearly in the longitudinal aging cohort. Males had larger volumes than females for all subcortical structures, but sex differences in trajectories of change with age were not significant. Within subject analysis showed that 65%-80% of 13-17 year olds underwent a longitudinal decrease in volume between scans (∼4 years apart) for the putamen, globus pallidus, and hippocampus, suggesting unique developmental processes during adolescence. This lifespan study of healthy participants will form a basis for comparison to neurological and psychiatric disorders. Hum Brain Mapp 38:3771-3790, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Effects of greening and community reuse of vacant lots on crime

PubMed Central

Kondo, Michelle; Hohl, Bernadette; Han, SeungHoon; Branas, Charles

2016-01-01

The Youngstown Neighborhood Development Corporation initiated a ‘Lots of Green’ programme to reuse vacant land in 2010. We performed a difference-in-differences analysis of the effects of this programme on crime in and around newly treated lots, in comparison to crimes in and around randomly selected and matched, untreated vacant lot controls. The effects of two types of vacant lot treatments on crime were tested: a cleaning and greening ‘stabilisation’ treatment and a ‘community reuse’ treatment mostly involving community gardens. The combined effects of both types of vacant lot treatments were also tested. After adjustment for various sociodemographic factors, linear and Poisson regression models demonstrated statistically significant reductions in all crime classes for at least one lot treatment type. Regression models adjusted for spatial autocorrelation found the most consistent significant reductions in burglaries around stabilisation lots, and in assaults around community reuse lots. Spill-over crime reduction effects were found in contiguous areas around newly treated lots. Significant increases in motor vehicle thefts around both types of lots were also found after they had been greened. Community-initiated vacant lot greening may have a greater impact on reducing more serious, violent crimes. PMID:28529389

[Stages of behavioral change regarding physical activity in students from a Brazilian town].

PubMed

Silva, Diego A S; Smith-Menezes, Aldemir; Almeida-Gomes, Marciusde; de Sousa, Thiago Ferreira

2010-08-01

Verifying the association between stages of behavioural change (SBC) for physical activity (PA) and socio-demographic factors, behavioural factors and PA barriers in students from a small town in Brazil. This cross-sectional study's representative sample was formed by 281 high school students from Simão Dias, Sergipe State, in Brazil, having 17.4 (± 1.98) mean age. Socio-demographic information was collected via a self-administered instrument (gender, age, school grade, economic level (EL) and family-head's EL), SBC for PA, behavioural factors (smoking, alcohol and stress) and PA barriers. A hierarchical model was used, involving Poisson regression with respective confidence intervals; significance level was set at 5 % for all analysis. 65.8 % of the participating students were classified in stages referring to inactive physical behaviour. Being female had the probability of presenting 1.37 times higher inactive behaviour (1.14-1.65 95 %CI) when compared to being male in the final regression model; having a low EL remained a risk factor, compared to medium EL students (PR=1.41; 1.15-1.72 95 %CI). These findings may prove useful for developing health promotion programmes in school environments, paying special attention to female and low-EL students.

Social determinants of dental health services utilisation of Greek adults.

PubMed

Pavi, E; Karampli, E; Zavras, D; Dardavesis, T; Kyriopoulos, J

2010-09-01

To identify the determinants of dental care utilisation among Greek adults, with a particular emphasis on socio-economic determinants. Data were collected through a national survey on health and health care services utilisation of a sample of 4,003 Greek adults stratified by geographic region, age and gender. A purpose made questionnaire was used during face-to-face interviews. A 2-stage model was developed to assess the impact of independent variables on dental utilisation likelihood and frequency. 39.6% (1,562) of Greek adults reported having visited a dentist within the last year. Among dental attenders, 32.6% reported prevention as the reason for visit. Statistically significant differences in dental care utilisation were observed in relation to demographic, socioeconomic and lifestyle factors. Logistic regression analysis showed that gender, age, income, education, place of residence, private insurance coverage and self-rated oral health are important determinants of dental services utilisation. Mean number of dental visits within previous year was 1.6. Results from Poisson regression analysis indicated that lower income level correlates to lower number of dental visits, while having visited for treatment (rather than for prevention) correlated to higher number of dental visits. Greek adults do not exhibit satisfactory dental visiting behaviour. Extent of care sought is associated with need for treatment rather than preventive reasons. The findings confirm the existence of socioeconomic inequalities in dental services utilisation among Greek adults.

Risk factors for 2009 pandemic influenza A (H1N1)-related hospitalization and death among racial/ethnic groups in New Mexico.

PubMed

Thompson, Deborah L; Jungk, Jessica; Hancock, Emily; Smelser, Chad; Landen, Michael; Nichols, Megin; Selvage, David; Baumbach, Joan; Sewell, Mack

2011-09-01

We assessed risk factors for 2009 pandemic influenza A (H1N1)-related hospitalization, mechanical ventilation, and death among New Mexico residents. We calculated population rate ratios using Poisson regression to analyze risk factors for H1N1-related hospitalization. We performed a cross-sectional analysis of hospitalizations during September 14, 2009 through January 13, 2010, using logistic regression to assess risk factors for mechanical ventilation and death among those hospitalized. During the study period, 926 laboratory-confirmed H1N1-related hospitalizations were identified. H1N1-related hospitalization was significantly higher among American Indians (risk ratio [RR] = 2.6; 95% confidence interval [CI] = 2.2, 3.2), Blacks (RR = 1.7; 95% CI = 1.2, 2.4), and Hispanics (RR = 1.8; 95% CI = 1.5, 2.0) than it was among non-Hispanic Whites, and also was higher among persons of younger age and lower household income. Mechanical ventilation was significantly associated with age 25 years and older, obesity, and lack of or delayed antiviral treatment. Death was significantly associated with male gender, cancer during the previous 12 months, and liver disorder. This analysis supports recent national efforts to include American Indian/Alaska Native race as a group at high risk for complications of influenza with respect to vaccination and antiviral treatment recommendations.

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

PubMed Central

Reich, Steven

2014-01-01

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data. PMID:23354693

Age and the economics of an emergency medical admission-what factors determine costs?

PubMed

McCabe, J J; Cournane, S; Byrne, D; Conway, R; O'Riordan, D; Silke, B

2017-02-01

The ageing of the population may be anticipated to increase demand on hospital resources. We have investigated the relationship between hospital episode costs and age profile in a single centre. All Emergency Medical admissions (33 732 episodes) to an Irish hospital over a 6-year period, categorized into three age groups, were evaluated against total hospital episode costs. Univariate and adjusted incidence rate ratios (IRRs) were calculated using zero truncated Poisson regression. The total hospital episode cost increased with age ( P < 0.001). The multi-variable Poisson regression model demonstrated that the most important drivers of overall costs were Acute Illness Severity-IRR 1.36 (95% CI: 1.30, 1.41), Sepsis Status -1.46 (95% CI: 1.42, 1.51) and Chronic Disabling Disease Score -1.25 (95% CI: 1.22, 1.27) and the Age Group as exemplified for those 85 years IRR 1.23 (95% CI: 1.15, 1.32). Total hospital episode costs are a product of clinical complexity with contributions from the Acute Illness Severity, Co-Morbidity, Chronic Disabling Disease Score and Sepsis Status. However age is also an important contributor and an increasing patient age profile will have a predictable impact on total hospital episode costs. © The Author 2016. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Methods for analyzing matched designs with double controls: excess risk is easily estimated and misinterpreted when evaluating traffic deaths.

PubMed

Redelmeier, Donald A; Tibshirani, Robert J

2018-06-01

To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs. matched perspectives). We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls. Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155/d), and 2,593 individuals were in fatal crashes on the 20 control days (average = 130/d). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval: 1.12-1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval: 2.72-3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays. Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk. Copyright © 2018 Elsevier Inc. All rights reserved.

Effectiveness of preventive home visits in reducing the risk of falls in old age: a randomized controlled trial

PubMed Central

Luck, Tobias; Motzek, Tom; Luppa, Melanie; Matschinger, Herbert; Fleischer, Steffen; Sesselmann, Yves; Roling, Gudrun; Beutner, Katrin; König, Hans-Helmut; Behrens, Johann; Riedel-Heller, Steffi G

2013-01-01

Background Falls in older people are a major public health issue, but the underlying causes are complex. We sought to evaluate the effectiveness of preventive home visits as a multifactorial, individualized strategy to reduce falls in community-dwelling older people. Methods Data were derived from a prospective randomized controlled trial with follow-up examination after 18 months. Two hundred and thirty participants (≥80 years of age) with functional impairment were randomized to intervention and control groups. The intervention group received up to three preventive home visits including risk assessment, home counseling intervention, and a booster session. The control group received no preventive home visits. Structured interviews at baseline and follow-up provided information concerning falls in both study groups. Random-effects Poisson regression evaluated the effect of preventive home visits on the number of falls controlling for covariates. Results Random-effects Poisson regression showed a significant increase in the number of falls between baseline and follow-up in the control group (incidence rate ratio 1.96) and a significant decrease in the intervention group (incidence rate ratio 0.63) controlling for age, sex, family status, level of care, and impairment in activities of daily living. Conclusion Our results indicate that a preventive home visiting program can be effective in reducing falls in community-dwelling older people. PMID:23788832

Models for forecasting the flowering of Cornicabra olive groves.

PubMed

Rojo, Jesús; Pérez-Badia, Rosa

2015-11-01

This study examined the impact of weather-related variables on flowering phenology in the Cornicabra olive tree and constructed models based on linear and Poisson regression to forecast the onset and length of the pre-flowering and flowering phenophases. Spain is the world's leading olive oil producer, and the Cornicabra variety is the second largest Spanish variety in terms of surface area. However, there has been little phenological research into this variety. Phenological observations were made over a 5-year period (2009-2013) at four sampling sites in the province of Toledo (central Spain). Results showed that the onset of the pre-flowering phase is governed largely by temperature, which displayed a positive correlation with the temperature in the start of dormancy (November) and a negative correlation during the months prior to budburst (January, February and March). A similar relationship was recorded for the onset of flowering. Other weather-related variables, including solar radiation and rainfall, also influenced the succession of olive flowering phenophases. Linear models proved the most suitable for forecasting the onset and length of the pre-flowering period and the onset of flowering. The onset and length of pre-flowering can be predicted up to 1 or 2 months prior to budburst, whilst the onset of flowering can be forecast up to 3 months beforehand. By contrast, a nonlinear model using Poisson regression was best suited to predict the length of the flowering period.

Use of Segregation Indices, Townsend Index, and Air Toxics Data to Assess Lifetime Cancer Risk Disparities in Metropolitan Charleston, South Carolina, USA

PubMed Central

Rice, LaShanta J.; Jiang, Chengsheng; Wilson, Sacoby M.; Burwell-Naney, Kristen; Samantapudi, Ashok; Zhang, Hongmei

2014-01-01

Background: Studies have demonstrated a relationship between segregation and level of education, occupational opportunities, and risk behaviors, yet a paucity of research has elucidated the association between racial residential segregation, socioeconomic deprivation, and lifetime cancer risk. Objectives: We examined estimated lifetime cancer risk from air toxics by racial composition, segregation, and deprivation in census tracts in Metropolitan Charleston. Methods: Segregation indices were used to measure the distribution of groups of people from different races within neighborhoods. The Townsend Index was used to measure economic deprivation in the study area. Poisson multivariate regressions were applied to assess the association of lifetime cancer risk with segregation indices and Townsend Index along with several sociodemographic measures. Results: Lifetime cancer risk from all pollution sources was 28 persons/million for half of the census tracts in Metropolitan Charleston. Isolation Index and Townsend Index both showed significant correlation with lifetime cancer risk from different sources. This significance still holds after adjusting for other sociodemographic measures in a Poisson regression, and these two indices have stronger effect on lifetime cancer risk compared to the effects of sociodemographic measures. Conclusions: We found that material deprivation, measured by the Townsend Index and segregation measured by the Isolation index, introduced high impact on lifetime cancer risk by air toxics at the census tract level. PMID:24852759

Risk of thromboembolism in women taking ethinylestradiol/drospirenone and other oral contraceptives.

PubMed

Seeger, John D; Loughlin, Jeanne; Eng, P Mona; Clifford, C Robin; Cutone, Jennifer; Walker, Alexander M

2007-09-01

The oral contraceptive ethinylestradiol 0.03 mg/drospirenone 3 mg contains a progestin component that differs from other oral contraceptives. Case reports and prescription event monitoring suggested that ethinylestradiol/drospirenone might be associated with an elevated risk of thromboembolism. We sought to estimate the association between ethinylestradiol/drospirenone and risk of thromboembolism relative to the association among other oral contraceptives. We identified ethinylestradiol/drospirenone initiators and a twofold larger group of other oral contraceptive initiators between June 2001 and June 2004 within a U.S. health insurer database. The comparison group was selected to have demographic and health care characteristics preceding oral contraceptive initiation that were similar to ethinylestradiol/drospirenone initiators. Thromboembolism during the follow-up of the cohorts was identified through claims for medical services, and only medical record-confirmed cases were included in analyses. The primary (as-matched) analysis used proportional hazards regression, whereas a secondary (as-treated) analysis accounted for changes in oral contraceptives during follow-up using Poisson regression. The 22,429 ethinylestradiol/drospirenone initiators and 44,858 other oral contraceptive initiators were followed for an average of 7.6 months, and there were 18 cases of thromboembolism in ethinylestradiol/drospirenone initiators and 39 in the comparators (rate ratio 0.9, 95% confidence interval 0.5-1.6). More than 9,000 women would need to be prescribed oral contraceptives to observe a difference of one case of thromboembolism. Results of the as-treated analysis were similar to those of the as-matched analysis. Ethinylestradiol/drospirenone initiators and initiators of other oral contraceptives are similarly likely to experience thromboembolism. II.

Electronic health record analysis via deep poisson factor models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Proposing an Empirically Justified Reference Threshold for Blood Culture Sampling Rates in Intensive Care Units

PubMed Central

Castell, Stefanie; Schwab, Frank; Geffers, Christine; Bongartz, Hannah; Brunkhorst, Frank M.; Gastmeier, Petra; Mikolajczyk, Rafael T.

2014-01-01

Early and appropriate blood culture sampling is recommended as a standard of care for patients with suspected bloodstream infections (BSI) but is rarely taken into account when quality indicators for BSI are evaluated. To date, sampling of about 100 to 200 blood culture sets per 1,000 patient-days is recommended as the target range for blood culture rates. However, the empirical basis of this recommendation is not clear. The aim of the current study was to analyze the association between blood culture rates and observed BSI rates and to derive a reference threshold for blood culture rates in intensive care units (ICUs). This study is based on data from 223 ICUs taking part in the German hospital infection surveillance system. We applied locally weighted regression and segmented Poisson regression to assess the association between blood culture rates and BSI rates. Below 80 to 90 blood culture sets per 1,000 patient-days, observed BSI rates increased with increasing blood culture rates, while there was no further increase above this threshold. Segmented Poisson regression located the threshold at 87 (95% confidence interval, 54 to 120) blood culture sets per 1,000 patient-days. Only one-third of the investigated ICUs displayed blood culture rates above this threshold. We provided empirical justification for a blood culture target threshold in ICUs. In the majority of the studied ICUs, blood culture sampling rates were below this threshold. This suggests that a substantial fraction of BSI cases might remain undetected; reporting observed BSI rates as a quality indicator without sufficiently high blood culture rates might be misleading. PMID:25520442

Quality failures in residential aged care in Australia: The relationship between structural factors and regulation imposed sanctions.

PubMed

Baldwin, Richard; Chenoweth, Lynnette; Dela Rama, Marie; Liu, Zhixin

2015-12-01

To examine the relationship between structural factors and the imposition of sanctions on residential aged care services across Australia for regulatory compliance failure. Poisson Regression analysis was used to examine the association between the number of sanctions imposed and the structural characteristics of residential aged care services in Australia. Residential aged care services that have a greater likelihood of having government sanctions imposed on them are operated by for-profit providers and located in remote locations and in Victoria, Queensland, South Australia, Northern Territory and the Australian Capital Territory. The findings confirm the international literature on the relationship between residential aged care service location, ownership type and the likelihood of sanctions. In the light of the predicted expansion of residential aged care services, policy makers should give consideration to structural elements most likely to be associated with a failure to meet and maintain service standards. © 2014 ACOTA.

Geographical distribution of a seropositive myasthenia gravis population.

PubMed

Heldal, Anne Taraldsen; Eide, Geir Egil; Gilhus, Nils Erik; Romi, Fredrik

2012-06-01

To assess age- and sex-specific myasthenia gravis (MG) occurrence and incidence in the different geographical regions in Norway and thereby to identify factors that may contribute to the development of MG. Multiple Poisson regression analysis was used to assess variation in incidence dependent on year, gender and onset age in five geographically defined health regions. The study population comprised 419 individuals with first time seropositive tests from 1995 to 2007. Annual MG incidence ranged from < 1 to 14 per million, with an average of 7.04 per million for all five health regions combined. This is the first nation-wide epidemiological study of seropositive MG that elucidates the geographical differences within a country. The incidence of seropositive MG did not vary significantly between the regions. Mid-Norway tended to have a higher incidence, and North tended to have a lower incidence. Copyright © 2011 Wiley Periodicals, Inc.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals

NASA Astrophysics Data System (ADS)

Frejlich, Pedro; Mărcuț, Ioan

2018-03-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.

PubMed

Frejlich, Pedro; Mărcuț, Ioan

2018-01-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

PubMed

Peñagaricano, F; Urioste, J I; Naya, H; de los Campos, G; Gianola, D

2011-04-01

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep. © 2010 Blackwell Verlag GmbH.

Waiting-time distributions of magnetic discontinuities: clustering or Poisson process?

PubMed

Greco, A; Matthaeus, W H; Servidio, S; Dmitruk, P

2009-10-01

Using solar wind data from the Advanced Composition Explorer spacecraft, with the support of Hall magnetohydrodynamic simulations, the waiting-time distributions of magnetic discontinuities have been analyzed. A possible phenomenon of clusterization of these discontinuities is studied in detail. We perform a local Poisson's analysis in order to establish if these intermittent events are randomly distributed or not. Possible implications about the nature of solar wind discontinuities are discussed.

Waiting-time distributions of magnetic discontinuities: Clustering or Poisson process?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greco, A.; Matthaeus, W. H.; Servidio, S.

2009-10-15

Using solar wind data from the Advanced Composition Explorer spacecraft, with the support of Hall magnetohydrodynamic simulations, the waiting-time distributions of magnetic discontinuities have been analyzed. A possible phenomenon of clusterization of these discontinuities is studied in detail. We perform a local Poisson's analysis in order to establish if these intermittent events are randomly distributed or not. Possible implications about the nature of solar wind discontinuities are discussed.

Differential expression analysis for RNAseq using Poisson mixed models

PubMed Central

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny

2017-01-01

Abstract Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. PMID:28369632

What are hierarchical models and how do we analyze them?

USGS Publications Warehouse

Royle, Andy

2016-01-01

In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

PubMed

Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V

2014-11-30

We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.

Cracked rocks with positive and negative Poisson's ratio: real-crack properties extracted from pressure dependence of elastic-wave velocities

NASA Astrophysics Data System (ADS)

Zaitsev, Vladimir Y.; Radostin, Andrey V.; Dyskin, Arcady V.; Pasternak, Elena

2017-04-01

We report results of analysis of literature data on P- and S-wave velocities of rocks subjected to variable hydrostatic pressure. Out of about 90 examined samples, in more than 40% of the samples the reconstructed Poisson's ratios are negative for lowest confining pressure with gradual transition to the conventional positive values at higher pressure. The portion of rocks exhibiting negative Poisson's ratio appeared to be unexpectedly high. To understand the mechanism of negative Poisson's ratio, pressure dependences of P- and S-wave velocities were analyzed using the effective medium model in which the reduction in the elastic moduli due to cracks is described in terms of compliances with respect to shear and normal loading that are imparted to the rock by the presence of cracks. This is in contrast to widely used descriptions of effective cracked medium based on a specific crack model (e.g., penny-shape crack) in which the ratio between normal and shear compliances of such a crack is strictly predetermined. The analysis of pressure-dependences of the elastic wave velocities makes it possible to reveal the ratio between pure normal and shear compliances (called q-ratio below) for real defects and quantify their integral content in the rock. The examination performed demonstrates that a significant portion (over 50%) of cracks exhibit q-ratio several times higher than that assumed for the conventional penny-shape cracks. This leads to faster reduction of the Poisson's ratio with increasing the crack concentration. Samples with negative Poisson's ratio are characterized by elevated q-ratio and simultaneously crack concentration. Our results clearly indicate that the traditional crack model is not adequate for a significant portion of rocks and that the interaction between the opposite crack faces leading to domination of the normal compliance and reduced shear displacement discontinuity can play an important role in the mechanical behavior of rocks.

Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle

NASA Technical Reports Server (NTRS)

Coroneos, Rula; Pai, Shantaram, S.; Murthy, Pappu

2013-01-01

This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson??s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.

Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra

PubMed Central

Deepaisarn, S; Tar, P D; Thacker, N A; Seepujak, A; McMahon, A W

2018-01-01

Abstract Motivation Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI) facilitates the analysis of large organic molecules. However, the complexity of biological samples and MALDI data acquisition leads to high levels of variation, making reliable quantification of samples difficult. We present a new analysis approach that we believe is well-suited to the properties of MALDI mass spectra, based upon an Independent Component Analysis derived for Poisson sampled data. Simple analyses have been limited to studying small numbers of mass peaks, via peak ratios, which is known to be inefficient. Conventional PCA and ICA methods have also been applied, which extract correlations between any number of peaks, but we argue makes inappropriate assumptions regarding data noise, i.e. uniform and Gaussian. Results We provide evidence that the Gaussian assumption is incorrect, motivating the need for our Poisson approach. The method is demonstrated by making proportion measurements from lipid-rich binary mixtures of lamb brain and liver, and also goat and cow milk. These allow our measurements and error predictions to be compared to ground truth. Availability and implementation Software is available via the open source image analysis system TINA Vision, www.tina-vision.net. Contact paul.tar@manchester.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29091994

Independence of the effective dielectric constant of an electrolytic solution on the ionic distribution in the linear Poisson-Nernst-Planck model.

PubMed

Alexe-Ionescu, A L; Barbero, G; Lelidis, I

2014-08-28

We consider the influence of the spatial dependence of the ions distribution on the effective dielectric constant of an electrolytic solution. We show that in the linear version of the Poisson-Nernst-Planck model, the effective dielectric constant of the solution has to be considered independent of any ionic distribution induced by the external field. This result follows from the fact that, in the linear approximation of the Poisson-Nernst-Planck model, the redistribution of the ions in the solvent due to the external field gives rise to a variation of the dielectric constant that is of the first order in the effective potential, and therefore it has to be neglected in the Poisson's equation that relates the actual electric potential across the electrolytic cell to the bulk density of ions. The analysis is performed in the case where the electrodes are perfectly blocking and the adsorption at the electrodes is negligible, and in the absence of any ion dissociation-recombination effect.

Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds

NASA Astrophysics Data System (ADS)

Martínez-Torres, David; Miranda, Eva

2018-01-01

We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

PubMed

Sepúlveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain, Arnab; Clark, Taane G

2013-02-26

The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.

A Conway-Maxwell-Poisson (CMP) model to address data dispersion on positron emission tomography.

PubMed

Santarelli, Maria Filomena; Della Latta, Daniele; Scipioni, Michele; Positano, Vincenzo; Landini, Luigi

2016-10-01

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Association between air pollution and rhinitis incidence in two European cohorts.

PubMed

Burte, Emilie; Leynaert, Bénédicte; Bono, Roberto; Brunekreef, Bert; Bousquet, Jean; Carsin, Anne-Elie; De Hoogh, Kees; Forsberg, Bertil; Gormand, Frédéric; Heinrich, Joachim; Just, Jocelyne; Marcon, Alessandro; Künzli, Nino; Nieuwenhuijsen, Mark; Pin, Isabelle; Stempfelet, Morgane; Sunyer, Jordi; Villani, Simona; Siroux, Valérie; Jarvis, Deborah; Nadif, Rachel; Jacquemin, Bénédicte

2018-06-01

The association between air pollution and rhinitis is not well established. The aim of this longitudinal analysis was to study the association between modeled air pollution at the subjects' home addresses and self-reported incidence of rhinitis. We used data from 1533 adults from two multicentre cohorts' studies (EGEA and ECRHS). Rhinitis incidence was defined as reporting rhinitis at the second follow-up (2011 to 2013) but not at the first follow-up (2000 to 2007). Annual exposure to NO 2 , PM 10 and PM 2.5 at the participants' home addresses was estimated using land-use regression models developed by the ESCAPE project for the 2009-2010 period. Incidence rate ratios (IRR) were computed using Poisson regression. Pooled analysis, analyses by city and meta-regression testing for heterogeneity were carried out. No association between long-term air pollution exposure and incidence of rhinitis was found (adjusted IRR (aIRR) for an increase of 10 μg·m -3 of NO 2: 1.00 [0.91-1.09], for an increase of 5 μg·m -3 of PM 2.5 : 0.88 [0.73-1.04]). Similar results were found in the two-pollutant model (aIRR for an increase of 10 μg·m -3 of NO 2: 1.01 [0.87-1.17], for an increase of 5 μg·m -3 of PM 2.5 : 0.87 [0.68-1.08]). Results differed depending on the city, but no regional pattern emerged for any of the pollutants. This study did not find any consistent evidence of an association between long-term air pollution and incident rhinitis. Copyright © 2018. Published by Elsevier Ltd.

Public health vulnerability to wintertime weather: time-series regression and episode analyses of national mortality and morbidity databases to inform the Cold Weather Plan for England.

PubMed

Hajat, S; Chalabi, Z; Wilkinson, P; Erens, B; Jones, L; Mays, N

2016-08-01

To inform development of Public Health England's Cold Weather Plan (CWP) by characterizing pre-existing relationships between wintertime weather and mortality and morbidity outcomes, and identification of groups most at risk. Time-series regression analysis and episode analysis of daily mortality, emergency hospital admissions, and accident and emergency visits for each region of England. Seasonally-adjusted Poisson regression models estimating the percent change in daily health events per 1 °C fall in temperature or during individual episodes of extreme weather. Adverse cold effects were observed in all regions, with the North East, North West and London having the greatest risk of cold-related mortality. Nationally, there was a 3.44% (95% CI: 3.01, 3.87) increase in all-cause deaths and 0.78% (95% CI: 0.53, 1.04) increase in all-cause emergency admissions for every 1 °C drop in temperature below identified thresholds. The very elderly and people with COPD were most at risk from low temperatures. A&E visits for fractures were elevated during heavy snowfall periods, with adults (16-64 years) being the most sensitive age-group. Since even moderately cold days are associated with adverse health effects, by far the greatest health burdens of cold weather fell outside of the alert periods currently used in the CWP. Our findings indicate that levels 0 ('year round planning') and 1 ('winter preparedness and action') are crucial components of the CWP in comparison to the alerts. Those most vulnerable during winter may vary depending on the type of weather conditions being experienced. Recommendations are made for the CWP. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Relation between increased numbers of safe playing areas and decreased vehicle related child mortality rates in Japan from 1970 to 1985: a trend analysis

PubMed Central

Nakahara, S.; Nakamura, Y.; Ichikawa, M.; Wakai, S.

2004-01-01

Objectives: To examine vehicle related mortality trends of children in Japan; and to investigate how environmental modifications such as the installation of public parks and pavements are associated with these trends. Design: Poisson regression was used for trend analysis, and multiple regression modelling was used to investigate the associations between trends in environmental modifications and trends in motor vehicle related child mortality rates. Setting: Mortality data of Japan from 1970 to 1994, defined as E-code 810–23 from 1970 to 1978 and E810–25 from 1979 to 1994, were obtained from vital statistics. Multiple regression modelling was confined to the 1970–1985 data. Data concerning public parks and other facilities were obtained from the Ministry of Land, Infrastructure, and Transport. Subjects: Children aged 0–14 years old were examined in this study and divided into two groups: 0–4 and 5–14 years. Main results: An increased number of public parks was associated with decreased vehicle related mortality rates among children aged 0–4 years, but not among children aged 5–14. In contrast, there was no association between trends in pavements and mortality rates. Conclusions: An increased number of public parks might reduce vehicle related preschooler deaths, in particular those involving pedestrians. Safe play areas in residential areas might reduce the risk of vehicle related child death by lessening the journey both to and from such areas as well as reducing the number of children playing on the street. However, such measures might not be effective in reducing the vehicle related mortalities of school age children who have an expanded range of activities and walk longer distances. PMID:15547055

Formulation of the Multi-Hit Model With a Non-Poisson Distribution of Hits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vassiliev, Oleg N., E-mail: Oleg.Vassiliev@albertahealthservices.ca

2012-07-15

Purpose: We proposed a formulation of the multi-hit single-target model in which the Poisson distribution of hits was replaced by a combination of two distributions: one for the number of particles entering the target and one for the number of hits a particle entering the target produces. Such an approach reflects the fact that radiation damage is a result of two different random processes: particle emission by a radiation source and interaction of particles with matter inside the target. Methods and Materials: Poisson distribution is well justified for the first of the two processes. The second distribution depends on howmore » a hit is defined. To test our approach, we assumed that the second distribution was also a Poisson distribution. The two distributions combined resulted in a non-Poisson distribution. We tested the proposed model by comparing it with previously reported data for DNA single- and double-strand breaks induced by protons and electrons, for survival of a range of cell lines, and variation of the initial slopes of survival curves with radiation quality for heavy-ion beams. Results: Analysis of cell survival equations for this new model showed that they had realistic properties overall, such as the initial and high-dose slopes of survival curves, the shoulder, and relative biological effectiveness (RBE) In most cases tested, a better fit of survival curves was achieved with the new model than with the linear-quadratic model. The results also suggested that the proposed approach may extend the multi-hit model beyond its traditional role in analysis of survival curves to predicting effects of radiation quality and analysis of DNA strand breaks. Conclusions: Our model, although conceptually simple, performed well in all tests. The model was able to consistently fit data for both cell survival and DNA single- and double-strand breaks. It correctly predicted the dependence of radiation effects on parameters of radiation quality.« less

The Effect of the "Zero Tolerance for Head Contact" Rule Change on the Risk of Concussions in Youth Ice Hockey Players.

PubMed

Krolikowski, Maciej P; Black, Amanda M; Palacios-Derflingher, Luz; Blake, Tracy A; Schneider, Kathryn J; Emery, Carolyn A

2017-02-01

Ice hockey is a popular winter sport in Canada. Concussions account for the greatest proportion of all injuries in youth ice hockey. In 2011, a policy change enforcing "zero tolerance for head contact" was implemented in all leagues in Canada. To determine if the risk of game-related concussions and more severe concussions (ie, resulting in >10 days of time loss) and the mechanisms of a concussion differed for Pee Wee class (ages 11-12 years) and Bantam class (ages 13-14 years) players after the 2011 "zero tolerance for head contact" policy change compared with players in similar divisions before the policy change. Cohort study; Level of evidence, 3. The retrospective cohort included Pee Wee (most elite 70%, 2007-2008; n = 891) and Bantam (most elite 30%, 2008-2009; n = 378) players before the rule change and Pee Wee (2011-2012; n = 588) and Bantam (2011-2012; n = 242) players in the same levels of play after the policy change. Suspected concussions were identified by a team designate and referred to a sport medicine physician for diagnosis. Incidence rate ratios (IRRs) were estimated based on multiple Poisson regression analysis, controlling for clustering by team and other important covariates and offset by game-exposure hours. Incidence rates based on the mechanisms of a concussion were estimated based on univariate Poisson regression analysis. The risk of game-related concussions increased after the head contact rule in Pee Wee (IRR, 1.85; 95% CI, 1.20-2.86) and Bantam (IRR, 2.48; 95% CI, 1.17-5.24) players. The risk of more severe concussions increased after the head contact rule in Pee Wee (IRR, 4.12; 95% CI, 2.00-8.50) and Bantam (IRR, 7.91; 95% CI, 3.13-19.94) players. The rates of concussions due to body checking and direct head contact increased after the rule change. The "zero tolerance for head contact" policy change did not reduce the risk of game-related concussions in Pee Wee or Bantam class ice hockey players. Increased concussion awareness and education after the policy change may have contributed to the increased risk of concussions found after the policy change.

Poisson-event-based analysis of cell proliferation.

PubMed

Summers, Huw D; Wills, John W; Brown, M Rowan; Rees, Paul

2015-05-01

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry.

Guidelines for Use of the Approximate Beta-Poisson Dose-Response Model.

PubMed

Xie, Gang; Roiko, Anne; Stratton, Helen; Lemckert, Charles; Dunn, Peter K; Mengersen, Kerrie

2017-07-01

For dose-response analysis in quantitative microbial risk assessment (QMRA), the exact beta-Poisson model is a two-parameter mechanistic dose-response model with parameters α>0 and β>0, which involves the Kummer confluent hypergeometric function. Evaluation of a hypergeometric function is a computational challenge. Denoting PI(d) as the probability of infection at a given mean dose d, the widely used dose-response model PI(d)=1-(1+dβ)-α is an approximate formula for the exact beta-Poisson model. Notwithstanding the required conditions α<β and β>1, issues related to the validity and approximation accuracy of this approximate formula have remained largely ignored in practice, partly because these conditions are too general to provide clear guidance. Consequently, this study proposes a probability measure Pr(0 < r < 1 | α̂, β̂) as a validity measure (r is a random variable that follows a gamma distribution; α̂ and β̂ are the maximum likelihood estimates of α and β in the approximate model); and the constraint conditions β̂>(22α̂)0.50 for 0.02<α̂<2 as a rule of thumb to ensure an accurate approximation (e.g., Pr(0 < r < 1 | α̂, β̂) >0.99) . This validity measure and rule of thumb were validated by application to all the completed beta-Poisson models (related to 85 data sets) from the QMRA community portal (QMRA Wiki). The results showed that the higher the probability Pr(0 < r < 1 | α̂, β̂), the better the approximation. The results further showed that, among the total 85 models examined, 68 models were identified as valid approximate model applications, which all had a near perfect match to the corresponding exact beta-Poisson model dose-response curve. © 2016 Society for Risk Analysis.

Evolving Epidemiology of Staphylococcus aureus Bacteremia.

PubMed

Rhee, Yoona; Aroutcheva, Alla; Hota, Bala; Weinstein, Robert A; Popovich, Kyle J

2015-12-01

Methicillin-resistant Staphylococcus aureus (MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type. To examine the epidemiology of S. aureus BSIs, including USA300 and non-USA300 MRSA strains. Retrospective observational study with molecular analysis. Large urban public hospital. Individuals with S. aureus BSIs from January 1, 2007 through December 31, 2013. We used electronic surveillance data to identify cases of S. aureus BSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors. A total of 1,015 cases of S. aureus BSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO- and HO- methicillin-susceptible S. aureus infections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains. USA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.

[Temporal analysis of mortality due to intimate partner violence in Spain].

PubMed

Vives, Carmen; Caballero, Pablo; Álvarez-Dardet, Carlos

2004-01-01

To analyze the temporal distribution of mortality due to violence by intimate partners (VIP) and to identify possible temporal clusters in women deaths by VIP in Spain. We performed a descriptive epidemiological study based on the VIP deaths included in the database of the Federation of Divorced and Separated Women (1998-2003). The epidemic index (EI) was calculated as the ratio between the actual number of VIP deaths in a given month from January to July 2003 and the median number in the same month in the five preceding years. A Poisson model was used to analyze the distribution by years (1998-2002), seasons, months, and days. Simple regression analysis was performed with three-monthly means. A temporal cluster analysis was also carried out. In 2003, the EI of VIP mortality was high in January (EI = 1.6), March (EI = 1.2), May (EI = 1.5), June (EI = 2), and July (EI = 2.5). Compared with 1998 and Sundays, respectively, mortality due to VIP was significantly increased in 2001 (relative risk, RR = 1.52; 95% confidence interval [CI], 1.05-2.20) and on Mondays (RR = 1.77; 95%CI, 1.13-2.76). The regression analyses confirmed an increase between the first three-month period of 1998 and the last three-month period of 2001. There were no differences between seasons and months. No temporal clusters of deaths were detected. VIP is currently an increasing epidemic in Spain with no clear temporal pattern. Political and legal efforts to reduce this problem do not seem to be successful.

Understanding prescription adherence: Pharmacy claims data from the Contraceptive CHOICE Project

PubMed Central

Pittman, Meredith E.; Secura, Gina M.; Allsworth, Jenifer E.; Homco, Juell B.; Madden, Tessa; Peipert, Jeffrey F.

2010-01-01

BACKGROUND We examined prescription adherence rates by contraceptive method among women who used oral contraceptive pills (OCP), transdermal patch, or vaginal ring. STUDY DESIGN Women in the St. Louis area were provided their choice of OCP, patch, or ring at no cost and followed for 18 months. Time between monthly refills was obtained from pharmacy data and analyzed as a marker of adherence. Risk factors for initial nonadherence were estimated using Cox proportional hazards; predictors for repeated nonadherence were analyzed using Poisson regression with robust error variance. RESULTS Overall, 619 participants filled 6,435 contraceptive prescriptions with a median of 10 refills per participant. Only 30% of women (n=187) obtained all refills on time. In the time-to-failure analysis, use of vaginal ring and increased parity were predictors of early nonadherence (p<0.05). In the multivariable analysis, use of the vaginal ring and history of abortion were risk factors for repeated nonadherence (p<0.01). CONCLUSIONS Even with financial barriers removed, pharmacy data show that many women inconsistently refill their contraception and may be at risk for unintended pregnancy. PMID:21397092

Back pain prevalence and associated factors in children and adolescents: an epidemiological population study

PubMed Central

Noll, Matias; Candotti, Cláudia Tarragô; da Rosa, Bruna Nichele; Loss, Jefferson Fagundes

2016-01-01

ABSTRACT OBJECTIVE To identify the prevalence of back pain among Brazilian school children and the factors associated with this pain. METHODS All 1,720 schoolchildren from the fifth to the eight grade attending schools from the city of Teutonia, RS, Southern Brazil, were invited to participate in the study. From these, 1,597 children participated. We applied the Back Pain and Body Posture Evaluation Instrument. The dependent variable was back pain, while the independent one were demographic, socioeconomic, behavior and heredity data. The prevalence ratio was estimated by multivariate analysis using the Poisson regression model (α = 0.05). RESULTS The prevalence of back pain in the last three months was 55.7% (n = 802). The multivariate analysis showed that back pain is associated with the variables: sex, parents with back pain, weekly frequency of physical activity, daily time spent watching television, studying in bed, sitting posture to write and use the computer, and way of carrying the backpack. CONCLUSIONS The prevalence of back pain in schoolchildren is high and it is associated with demographic, behavior and heredity aspects. PMID:27305406

Relative Deprivation, Poverty, and Subjective Health: JAGES Cross-Sectional Study

PubMed Central

Saito, Masashige; Kondo, Katsunori; Kondo, Naoki; Abe, Aya; Ojima, Toshiyuki; Suzuki, Kayo

2014-01-01

To evaluate the association between relative deprivation (lacking daily necessities) and subjective health in older Japanese adults, we performed a cross-sectional analysis using data from the Japan Gerontological Evaluation Study (JAGES). The data were obtained from functionally independent residents aged ≥65 years from 24 municipalities in Japan (n = 24,742). Thirteen items in three dimensions were used to evaluate relative deprivation of material conditions. Approximately 28% of older Japanese people indicated that they lacked some daily necessities (non-monetary poverty). A two-level Poisson regression analysis revealed that relative deprivation was associated with poor self-rated health (PR = 1.3–1.5) and depressive symptoms (PR = 1.5–1.8) in both men and women, and these relationships were stronger than those observed in people living in relative poverty (monetary poverty). The interaction effect between relative deprivation and relative poverty was not associated with poor health. As a dimension of the social determinants of health, poverty should be evaluated from a multidimensional approach, capturing not only monetary conditions but also material-based, non-monetary conditions. PMID:25350284

Relative deprivation, poverty, and subjective health: JAGES cross-sectional study.

PubMed

Saito, Masashige; Kondo, Katsunori; Kondo, Naoki; Abe, Aya; Ojima, Toshiyuki; Suzuki, Kayo

2014-01-01

To evaluate the association between relative deprivation (lacking daily necessities) and subjective health in older Japanese adults, we performed a cross-sectional analysis using data from the Japan Gerontological Evaluation Study (JAGES). The data were obtained from functionally independent residents aged ≥65 years from 24 municipalities in Japan (n = 24,742). Thirteen items in three dimensions were used to evaluate relative deprivation of material conditions. Approximately 28% of older Japanese people indicated that they lacked some daily necessities (non-monetary poverty). A two-level Poisson regression analysis revealed that relative deprivation was associated with poor self-rated health (PR = 1.3-1.5) and depressive symptoms (PR = 1.5-1.8) in both men and women, and these relationships were stronger than those observed in people living in relative poverty (monetary poverty). The interaction effect between relative deprivation and relative poverty was not associated with poor health. As a dimension of the social determinants of health, poverty should be evaluated from a multidimensional approach, capturing not only monetary conditions but also material-based, non-monetary conditions.

Traffic effects on bird counts on North American Breeding Bird Survey routes

USGS Publications Warehouse

Griffith, Emily H.; Sauer, John R.; Royle, J. Andrew

2010-01-01

The North American Breeding Bird Survey (BBS) is an annual roadside survey used to estimate population change in >420 species of birds that breed in North America. Roadside sampling has been criticized, in part because traffic noise can interfere with bird counts. Since 1997, data have been collected on the numbers of vehicles that pass during counts at each stop. We assessed the effect of traffic by modeling total vehicles as a covariate of counts in hierarchical Poisson regression models used to estimate population change. We selected species for analysis that represent birds detected at low and high abundance and birds with songs of low and high frequencies. Increases in vehicle counts were associated with decreases in bird counts in most of the species examined. The size and direction of these effects remained relatively constant between two alternative models that we analyzed. Although this analysis indicated only a small effect of incorporating traffic effects when modeling roadside counts of birds, we suggest that continued evaluation of changes in traffic at BBS stops should be a component of future BBS analyses.

Differential expression analysis for RNAseq using Poisson mixed models.

PubMed

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.

DTIC Science & Technology

A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the

A Poisson process approximation for generalized K-5 confidence regions

NASA Technical Reports Server (NTRS)

Arsham, H.; Miller, D. R.

1982-01-01

One-sided confidence regions for continuous cumulative distribution functions are constructed using empirical cumulative distribution functions and the generalized Kolmogorov-Smirnov distance. The band width of such regions becomes narrower in the right or left tail of the distribution. To avoid tedious computation of confidence levels and critical values, an approximation based on the Poisson process is introduced. This aproximation provides a conservative confidence region; moreover, the approximation error decreases monotonically to 0 as sample size increases. Critical values necessary for implementation are given. Applications are made to the areas of risk analysis, investment modeling, reliability assessment, and analysis of fault tolerant systems.

Longitudinal Poisson Regression To Evaluate the Epidemiology of Cryptosporidium, Giardia, and Fecal Indicator Bacteria in Coastal California Wetlands

PubMed Central

Hogan, Jennifer N.; Daniels, Miles E.; Watson, Fred G.; Conrad, Patricia A.; Oates, Stori C.; Miller, Melissa A.; Hardin, Dane; Byrne, Barbara A.; Dominik, Clare; Melli, Ann; Jessup, David A.

2012-01-01

Fecal pathogen contamination of watersheds worldwide is increasingly recognized, and natural wetlands may have an important role in mitigating fecal pathogen pollution flowing downstream. Given that waterborne protozoa, such as Cryptosporidium and Giardia, are transported within surface waters, this study evaluated associations between fecal protozoa and various wetland-specific and environmental risk factors. This study focused on three distinct coastal California wetlands: (i) a tidally influenced slough bordered by urban and agricultural areas, (ii) a seasonal wetland adjacent to a dairy, and (iii) a constructed wetland that receives agricultural runoff. Wetland type, seasonality, rainfall, and various water quality parameters were evaluated using longitudinal Poisson regression to model effects on concentrations of protozoa and indicator bacteria (Escherichia coli and total coliform). Among wetland types, the dairy wetland exhibited the highest protozoal and bacterial concentrations, and despite significant reductions in microbe concentrations, the wetland could still be seen to influence water quality in the downstream tidal wetland. Additionally, recent rainfall events were associated with higher protozoal and bacterial counts in wetland water samples across all wetland types. Notably, detection of E. coli concentrations greater than a 400 most probable number (MPN) per 100 ml was associated with higher Cryptosporidium oocyst and Giardia cyst concentrations. These findings show that natural wetlands draining agricultural and livestock operation runoff into human-utilized waterways should be considered potential sources of pathogens and that wetlands can be instrumental in reducing pathogen loads to downstream waters. PMID:22427504

Analysis of single-molecule fluorescence spectroscopic data with a Markov-modulated Poisson process.

PubMed

Jäger, Mark; Kiel, Alexander; Herten, Dirk-Peter; Hamprecht, Fred A

2009-10-05

We present a photon-by-photon analysis framework for the evaluation of data from single-molecule fluorescence spectroscopy (SMFS) experiments using a Markov-modulated Poisson process (MMPP). A MMPP combines a discrete (and hidden) Markov process with an additional Poisson process reflecting the observation of individual photons. The algorithmic framework is used to automatically analyze the dynamics of the complex formation and dissociation of Cu2+ ions with the bidentate ligand 2,2'-bipyridine-4,4'dicarboxylic acid in aqueous media. The process of association and dissociation of Cu2+ ions is monitored with SMFS. The dcbpy-DNA conjugate can exist in two or more distinct states which influence the photon emission rates. The advantage of a photon-by-photon analysis is that no information is lost in preprocessing steps. Different model complexities are investigated in order to best describe the recorded data and to determine transition rates on a photon-by-photon basis. The main strength of the method is that it allows to detect intermittent phenomena which are masked by binning and that are difficult to find using correlation techniques when they are short-lived.

Flood return level analysis of Peaks over Threshold series under changing climate

NASA Astrophysics Data System (ADS)

Li, L.; Xiong, L.; Hu, T.; Xu, C. Y.; Guo, S.

2016-12-01

Obtaining insights into future flood estimation is of great significance for water planning and management. Traditional flood return level analysis with the stationarity assumption has been challenged by changing environments. A method that takes into consideration the nonstationarity context has been extended to derive flood return levels for Peaks over Threshold (POT) series. With application to POT series, a Poisson distribution is normally assumed to describe the arrival rate of exceedance events, but this distribution assumption has at times been reported as invalid. The Negative Binomial (NB) distribution is therefore proposed as an alternative to the Poisson distribution assumption. Flood return levels were extrapolated in nonstationarity context for the POT series of the Weihe basin, China under future climate scenarios. The results show that the flood return levels estimated under nonstationarity can be different with an assumption of Poisson and NB distribution, respectively. The difference is found to be related to the threshold value of POT series. The study indicates the importance of distribution selection in flood return level analysis under nonstationarity and provides a reference on the impact of climate change on flood estimation in the Weihe basin for the future.

An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies.

PubMed

Remontet, L; Bossard, N; Belot, A; Estève, J

2007-05-10

Relative survival provides a measure of the proportion of patients dying from the disease under study without requiring the knowledge of the cause of death. We propose an overall strategy based on regression models to estimate the relative survival and model the effects of potential prognostic factors. The baseline hazard was modelled until 10 years follow-up using parametric continuous functions. Six models including cubic regression splines were considered and the Akaike Information Criterion was used to select the final model. This approach yielded smooth and reliable estimates of mortality hazard and allowed us to deal with sparse data taking into account all the available information. Splines were also used to model simultaneously non-linear effects of continuous covariates and time-dependent hazard ratios. This led to a graphical representation of the hazard ratio that can be useful for clinical interpretation. Estimates of these models were obtained by likelihood maximization. We showed that these estimates could be also obtained using standard algorithms for Poisson regression. Copyright 2006 John Wiley & Sons, Ltd.

Survival analysis of clinical mastitis data using a nested frailty Cox model fit as a mixed-effects Poisson model.

PubMed

Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik

2014-12-01

Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation approach for frailty Cox models based on the penalized partial likelihood. The simulation study showed good performance for the Poisson maximum likelihood approach with Gaussian quadrature and biased variance component estimates for both the Poisson maximum likelihood with Laplace approximation and penalized partial likelihood approaches. Copyright © 2014. Published by Elsevier B.V.

Violent behaviour in a forensic psychiatric hospital in Finland: an analysis of violence incident reports.

PubMed

Kuivalainen, S; Vehviläinen-Julkunen, K; Putkonen, A; Louheranta, O; Tiihonen, J

2014-04-01

The aim of this paper was to explore the frequency and provocation of physically violent incidents in a Finnish forensic psychiatric hospital. Three years (2007-2009) of violent incident reports were analysed retrospectively. The data were analysed by content analysis, and statistically by Poisson regression analysis. During the study period a total of 840 incidents of physical violence occurred. Six main categories were found to describe the provocation of violence where three of these categories seemed to be without a specified reason (61%), and three represented a reaction to something (36%). The risk for violent behaviour was highest for the civil patients (RR = 11.96; CI 95% 9.43-15.18; P < 0.001), compared to criminal patients (RR = 1). The civil patients represented 36.7% of the patients, and in 43.6% of the studied patient days, they caused 89.8% of the reported violence incidents. Patients undergoing a forensic mental examination did not frequently behave aggressively (RR = 1.97; CI 95% 0.91-4.28). These results can be used in the reorganization of health-care practices and the allocation of resources. © 2013 John Wiley & Sons Ltd.

Predicting spatio-temporal failure in large scale observational and micro scale experimental systems

NASA Astrophysics Data System (ADS)

de las Heras, Alejandro; Hu, Yong

2006-10-01

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

Caribou distribution during the post-calving period in relation to infrastructure in the Prudhoe Bay oil field, Alaska

USGS Publications Warehouse

Cronin, Matthew A.; Amstrup, Steven C.; Durner, George M.; Noel, Lynn E.; McDonald, Trent L.; Ballard, Warren B.

1998-01-01

There is concern that caribou (Rangifer tarandus) may avoid roads and facilities (i.e., infrastructure) in the Prudhoe Bay oil field (PBOF) in northern Alaska, and that this avoidance can have negative effects on the animals. We quantified the relationship between caribou distribution and PBOF infrastructure during the post-calving period (mid-June to mid-August) with aerial surveys from 1990 to 1995. We conducted four to eight surveys per year with complete coverage of the PBOF. We identified active oil field infrastructure and used a geographic information system (GIS) to construct ten 1 km wide concentric intervals surrounding the infrastructure. We tested whether caribou distribution is related to distance from infrastructure with a chi-squared habitat utilization-availability analysis and log-linear regression. We considered bulls, calves, and total caribou of all sex/age classes separately. The habitat utilization-availability analysis indicated there was no consistent trend of attraction to or avoidance of infrastructure. Caribou frequently were more abundant than expected in the intervals close to infrastructure, and this trend was more pronounced for bulls and for total caribou of all sex/age classes than for calves. Log-linear regression (with Poisson error structure) of numbers of caribou and distance from infrastructure were also done, with and without combining data into the 1 km distance intervals. The analysis without intervals revealed no relationship between caribou distribution and distance from oil field infrastructure, or between caribou distribution and Julian date, year, or distance from the Beaufort Sea coast. The log-linear regression with caribou combined into distance intervals showed the density of bulls and total caribou of all sex/age classes declined with distance from infrastructure. Our results indicate that during the post-calving period: 1) caribou distribution is largely unrelated to distance from infrastructure; 2) caribou regularly use habitats in the PBOF; 3) caribou often occur close to infrastructure; and 4) caribou do not appear to avoid oil field infrastructure.

Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

NASA Astrophysics Data System (ADS)

Frahm, Klaus M.; Shepelyansky, Dima L.

2014-04-01

We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

Impact of sociodemographic attributes and dental caries on quality of life of intellectual disabled children using ECOHIS

PubMed Central

Aggarwal, Vikram Pal; Mathur, Anmol; Dileep, C.L; Batra, Manu; Makkar, Diljot Kaur

2016-01-01

Objectives To assess the impact of oral health outcomes on Oral Health-Related Quality of Life (OHRQoL) among intellectual disabled children and their families. Methodology OHRQoL based study was conducted among 150 intellectual disabled children students in the North West part of the country, Rajasthan, India. Guardians were asked to complete questionnaire on socioeconomic status and the Early Childhood Oral Health Impact Scale (ECOHIS) on their perception of the children’s OHRQoL. Clinical assessment included dental caries and OHI-S INDEX. Univariate regression analysis was fitted to assess covariates for the prevalence of impacts on OHRQoL. Results 54% of the caregivers reported that their child had an impact on at least one ECOHIS item. Negative impacts were more prevalent on items related to difficulty in eating some foods, difficulty in pronouncing any words and missed preschool, day-care or school. The univariate Poisson regression analysis showed that dental caries was significantly associated with the outcome. The prevalence of any impact on OHRQoL was approximately 1.32 and 2.84 times higher for children with low and higher severity of dental caries respectively when compared with those who were free of caries. Conclusion Patient-oriented outcomes like OHRQoL will enhance our understanding of the relationship between oral health and general health and demonstrate to clinical researchers and practitioners that improving the quality of patient’s well-being go beyond simply treating dental disease and disorders. PMID:27833512

Risk Factors for 2009 Pandemic Influenza A (H1N1)–Related Hospitalization and Death Among Racial/Ethnic Groups in New Mexico

PubMed Central

Jungk, Jessica; Hancock, Emily; Smelser, Chad; Landen, Michael; Nichols, Megin; Selvage, David; Baumbach, Joan; Sewell, Mack

2011-01-01

Objectives. We assessed risk factors for 2009 pandemic influenza A (H1N1)–related hospitalization, mechanical ventilation, and death among New Mexico residents. Methods. We calculated population rate ratios using Poisson regression to analyze risk factors for H1N1-related hospitalization. We performed a cross-sectional analysis of hospitalizations during September 14, 2009 through January 13, 2010, using logistic regression to assess risk factors for mechanical ventilation and death among those hospitalized. Results. During the study period, 926 laboratory-confirmed H1N1-related hospitalizations were identified. H1N1-related hospitalization was significantly higher among American Indians (risk ratio [RR] = 2.6; 95% confidence interval [CI] = 2.2, 3.2), Blacks (RR = 1.7; 95% CI = 1.2, 2.4), and Hispanics (RR = 1.8; 95% CI = 1.5, 2.0) than it was among non-Hispanic Whites, and also was higher among persons of younger age and lower household income. Mechanical ventilation was significantly associated with age 25 years and older, obesity, and lack of or delayed antiviral treatment. Death was significantly associated with male gender, cancer during the previous 12 months, and liver disorder. Conclusions. This analysis supports recent national efforts to include American Indian/Alaska Native race as a group at high risk for complications of influenza with respect to vaccination and antiviral treatment recommendations. PMID:21778495

The impact of land ownership, firefighting, and reserve status on fire probability in California

NASA Astrophysics Data System (ADS)

Starrs, Carlin Frances; Butsic, Van; Stephens, Connor; Stewart, William

2018-03-01

The extent of wildfires in the western United States is increasing, but how land ownership, firefighting, and reserve status influence fire probability is unclear. California serves as a unique natural experiment to estimate the impact of these factors, as ownership is split equally between federal and non-federal landowners; there is a relatively large proportion of reserved lands where extractive uses are prohibited and fire suppression is limited; and land ownership and firefighting responsibility are purposefully not always aligned. Panel Poisson regression techniques and pre-regression matching were used to model changes in annual fire probability from 1950-2015 on reserve and non-reserve lands on federal and non-federal ownerships across four vegetation types: forests, rangelands, shrublands, and forests without commercial species. Fire probability was found to have increased over time across all 32 categories. A marginal effects analysis showed that federal ownership and firefighting was associated with increased fire probability, and that the difference in fire probability on federal versus non-federal lands is increasing over time. Ownership, firefighting, and reserve status, played roughly equal roles in determining fire probability, and were found to have much greater influence than average maximum temperature (°C) during summer months (June, July, August), average annual precipitation (cm), and average annual topsoil moisture content by volume, demonstrating the critical role these factors play in western fire regimes and the importance of including them in future analysis focused on understanding and predicting wildfire in the Western United States.

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.

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.

Method for resonant measurement

DOEpatents

Rhodes, G.W.; Migliori, A.; Dixon, R.D.

1996-03-05

A method of measurement of objects to determine object flaws, Poisson`s ratio ({sigma}) and shear modulus ({mu}) is shown and described. First, the frequency for expected degenerate responses is determined for one or more input frequencies and then splitting of degenerate resonant modes are observed to identify the presence of flaws in the object. Poisson`s ratio and the shear modulus can be determined by identification of resonances dependent only on the shear modulus, and then using that shear modulus to find Poisson`s ratio using other modes dependent on both the shear modulus and Poisson`s ratio. 1 fig.

High Prevalence of Cardiovascular Disease in End-Stage Kidney Disease Patients Ongoing Hemodialysis in Peru: Why Should We Care About It?

PubMed

Bravo-Jaimes, Katia; Whittembury, Alvaro; Santivañez, Vilma

2015-01-01

Purpose. To determine clinical, biochemical, and pharmacological characteristics as well as cardiovascular disease prevalence and its associated factors among end-stage kidney disease patients receiving hemodialysis in the main hemodialysis center in Lima, Peru. Methods. This cross-sectional study included 103 patients. Clinical charts were reviewed and an echocardiogram was performed to determine prevalence of cardiovascular disease, defined as the presence of systolic/diastolic dysfunction, coronary heart disease, ventricular dysrhythmias, cerebrovascular disease, and/or peripheral vascular disease. Associations between cardiovascular disease and clinical, biochemical, and dialysis factors were sought using prevalence ratio. A robust Poisson regression model was used to quantify possible associations. Results. Cardiovascular disease prevalence was 81.6%, mainly due to diastolic dysfunction. It was significantly associated with age older than 50 years, metabolic syndrome, C-reactive protein levels, effective blood flow ≤ 300 mL/min, severe anemia, and absence of mild anemia. However, in the regression analysis only age older than 50 years, effective blood flow ≤ 300 mL/min, and absence of mild anemia were associated. Conclusions. Cardiovascular disease prevalence is high in patients receiving hemodialysis in the main center in Lima. Diastolic dysfunction, age, specific hemoglobin levels, and effective blood flow may play an important role.

Trends in the incidence of dementia: design and methods in the Alzheimer Cohorts Consortium.

PubMed

Chibnik, Lori B; Wolters, Frank J; Bäckman, Kristoffer; Beiser, Alexa; Berr, Claudine; Bis, Joshua C; Boerwinkle, Eric; Bos, Daniel; Brayne, Carol; Dartigues, Jean-Francois; Darweesh, Sirwan K L; Debette, Stephanie; Davis-Plourde, Kendra L; Dufouil, Carole; Fornage, Myriam; Grasset, Leslie; Gudnason, Vilmundur; Hadjichrysanthou, Christoforos; Helmer, Catherine; Ikram, M Arfan; Ikram, M Kamran; Kern, Silke; Kuller, Lewis H; Launer, Lenore; Lopez, Oscar L; Matthews, Fiona; Meirelles, Osorio; Mosley, Thomas; Ower, Alison; Psaty, Bruce M; Satizabal, Claudia L; Seshadri, Sudha; Skoog, Ingmar; Stephan, Blossom C M; Tzourio, Christophe; Waziry, Reem; Wong, Mei Mei; Zettergren, Anna; Hofman, Albert

2017-10-01

Several studies have reported a decline in incidence of dementia which may have large implications for the projected burden of disease, and provide important guidance to preventive efforts. However, reports are conflicting or inconclusive with regard to the impact of gender and education with underlying causes of a presumed declining trend remaining largely unidentified. The Alzheimer Cohorts Consortium aggregates data from nine international population-based cohorts to determine changes in the incidence of dementia since 1990. We will employ Poisson regression models to calculate incidence rates in each cohort and Cox proportional hazard regression to compare 5-year cumulative hazards across study-specific epochs. Finally, we will meta-analyse changes per decade across cohorts, and repeat all analysis stratified by sex, education and APOE genotype. In all cohorts combined, there are data on almost 69,000 people at risk of dementia with the range of follow-up years between 2 and 27. The average age at baseline is similar across cohorts ranging between 72 and 77. Uniting a wide range of disease-specific and methodological expertise in research teams, the first analyses within the Alzheimer Cohorts Consortium are underway to tackle outstanding challenges in the assessment of time-trends in dementia occurrence.

Exploration of diarrhoea seasonality and its drivers in China.

PubMed

Xu, Zhiwei; Hu, Wenbiao; Zhang, Yewu; Wang, Xiaofeng; Zhou, Maigeng; Su, Hong; Huang, Cunrui; Tong, Shilu; Guo, Qing

2015-02-04

This study investigated the diarrhoea seasonality and its potential drivers as well as potential opportunities for future diarrhoea control and prevention in China. Data on weekly infectious diarrhoea cases in 31 provinces of China from 2005 to 2012, and data on demographic and geographic characteristics, as well as climatic factors, were complied. A cosinor function combined with a Poisson regression was used to calculate the three seasonal parameters of diarrhoea in different provinces. Regression tree analysis was used to identify the predictors of diarrhoea seasonality. Diarrhoea cases in China showed a bimodal distribution. Diarrhoea in children <5 years was more likely to peak in fall-winter seasons, while diarrhoea in persons > = 5 years peaked in summer. Latitude was significantly associated with spatial pattern of diarrhoea seasonality, with peak and trough times occurring earlier at high latitudes (northern areas), and later at low latitudes (southern areas). The annual amplitudes of diarrhoea in persons > = 5 years increased with latitude (r = 0.62, P<0.001). Latitude 27.8° N and 38.65° N were the latitudinal thresholds for diarrhoea seasonality in China. Regional-specific diarrhoea control and prevention strategies may be optimal for China. More attention should be paid to diarrhoea in children <5 years during fall-winter seasons.

Impact of the 1990 Hong Kong legislation for restriction on sulfur content in fuel.

PubMed

Wong, Chit-Ming; Rabl, Ari; Thach, Thuan Q; Chau, Yuen Kwan; Chan, King Pan; Cowling, Benjamin J; Lai, Hak Kan; Lam, Tai Hing; McGhee, Sarah M; Anderson, H Ross; Hedley, Anthony J

2012-08-01

After the implementation of a regulation restricting sulfur to 0.5% by weight in fuel on July 1, 1990, in Hong Kong, sulfur dioxide (SO2*) levels fell by 45% on average and as much as 80% in the most polluted districts (Hedley et al. 2002). In addition, a reduction of respiratory symptoms and an improvement in bronchial hyperresponsiveness in children were observed (Peters et al. 1996; Wong et al. 1998). A recent time-series study (Hedley et al. 2002) found an immediate reduction in mortality during the cool season at six months after the intervention, followed by an increase in cool-season mortality in the second and third years, suggesting that the reduction in pollution was associated with a delay in mortality. Proportional changes in mortality trends between the 5-year periods before and after the intervention were measured as relative risks and used to assess gains in life expectancy using the life table method (Hedley et al. 2002). To further explore the relation between changes in pollution-related mortality before and after the intervention, our study had three objectives: (1) to evaluate the short-term effects on mortality of changes in the pollutant mix after the Hong Kong sulfur intervention, particularly with changes in the particulate matter (PM) chemical species; (2) to improve the methodology for assessment of the health impact in terms of changes in life expectancy using linear regression models; and (3) to develop an approach for analyzing changes in life expectancy from Poisson regression models. A fourth overarching objective was to determine the relation between short- and long-term benefits due to an improvement in air quality. For an assessment of the short-term effects on mortality due to changes in the pollutant mix, we developed Poisson regression Core Models with natural spline smoothers to control for long-term and seasonal confounding variations in the mortality counts and with covariates to adjust for temperature (T) and relative humidity (RH). We assessed the adequacy of the Core Models by evaluating the results against the Akaike Information Criterion, which stipulates that, at a minimum, partial autocorrelation plots should be between -0.1 and 0.1, and by examining the residual plots to make sure they were free from patterns. We assessed the effects for gaseous pollutants (NO2, SO2, and O3), PM with an aerodynamic diameter < or = 10 microm (PM10), and its chemical species (aluminum [Al], iron [Fe], manganese [Mn], nickel [Ni], vanadium [V], lead [Pb], and zinc [Zn]) using the Core Models, which were developed for the periods 5 years (or 2 years in the case of the sensitivity analysis) before and 5 years after the intervention, as well as in the10-year (or 7-year in the case of the sensitivity analysis) period pre- and post-intervention. We also included an indicator to separate the pre- and post-intervention periods, as well as the product of the indicator with an air pollution concentration variable. The health outcomes were mortality for all natural causes and for cardiovascular and respiratory causes, at all ages and in the 65 years or older age group. To assess the short- and long-term effects, we developed two methods: one using linear regression models reflecting the age-standardized mortality rate D(j) at day j, divided by a reference D(ref); and the other using Poisson regression models with daily mortality counts as the outcome variables. We also used both models to evaluate the relation between outcome variables and daily air pollution concentrations in the current day up to all previous days in the past 3 to 4 years. In the linear regression approach, we adjusted the data for temperature and relative humidity. We then removed season as a potential confounder, or deseasonalized them, by calculating a standard seasonal mortality rate profile, normalized to an annual average of unity, and dividing the mortality rates by this profile. Finally, to correct for long-term trends, we calculated a reference mortality rate D(ref)(j) as a moving average of the corrected and deseasonalized D(j) over the observation window. Then we regressed the outcome variable D(j)/D(ref) on an entire exposure sequence {c(i)} with lags up to 4 years in order to obtain impact coefficient f(i) from the regression model shown below: deltaD(j)/D (ref) = i(max)sigma f(i) c(j - i)(i = 0). The change in life expectancy (LE) for a change of units (deltac) in the concentration of pollutants on T(day)--representing the short interval (i.e., a day)--was calculated from the following equation (deltaL(pop) = average loss in life expectancy of an entire population): deltaL(pop) = -deltac T(day) infinity sigma (j = 0) infinity sigma f(i) (i = 0). In the Poisson regression approach, we fitted a distributed-lag model for exposure to previous days of up to 4 years in order to obtain the cumulative lag effect sigma beta(i). We fit the linear regression model of log(LE*/LE) = gamma(SMR - 1) + alpha to estimate the parameter gamma by gamma, where LE* and LE are life expectancy for an exposed and an unexposed population, respectively, and SMR represents the standardized mortality ratio. The life expectancy change per Ac increase in concentration is LE {exp[gamma delta c(sigma beta(i))]-1}. In our assessment of the changes in pollutant levels, the mean levels of SO2, Ni, and V showed a statistically significant decline, particularly in industrial areas. Ni and V showed the greatest impact on mortality, especially for respiratory diseases in the 5-year pre-intervention period for both the all-ages and 65+ groups among all chemical species. There were decreases in excess risks associated with Ni and V after the intervention, but they were nonsignificant. Using the linear regression approach, with a window of 1095 days (3 years), the losses in life expectancy with a 10-microg/m3 increase in concentrations, using two methods of estimation (one with adjustment for temperature and RH before the regression against pollutants, the other with adjustment for temperature and RH within the regression against pollutants), were 19.2 days (95% CI, 12.5 to 25.9) and 31.4 days (95% CI, 25.6 to 37.2) for PM10; and 19.7 days (95% CI, 15.2 to 24.2) and 12.8 days (95% CI, 8.9 to 16.8) for SO2. The losses in life expectancy in the current study were smaller than the ones implied by Elliott and colleagues (2007) and Pope and colleagues (2002) as expected since the observation window in our study was only 3 years whereas these other studies had windows of 16 years. In particular, the coefficients used by Elliott and colleagues (2007) for windows of 12 and 16 years were non-zero, which suggests that our window of at most 3 years cannot capture the full life expectancy loss and the effects were most likely underestimated. Using the Poisson regression approach, with a window of 1461 days (4 years), we found that a 10-microg/m3 increase in concentration of PM10 was associated with a change in life expectancy of -69 days (95% CI, -140 to 1) and a change of -133 days (95% CI, -172 to -94) for the same increase in SO2. The effect estimates varied as expected according to most variations in the sensitivity analysis model, specifically in terms of the Core Model definition, exposure windows, constraint of the lag effect pattern, and adjustment for smoking prevalence or socioeconomic status. Our results on the excess risks of mortality showed exposure to chemical species to be a health hazard. However, the statistical power was not sufficient to detect the differences between the pre- and post-intervention periods in Hong Kong due to the data limitations (specifically, the chemical species data were available only once every 6 days, and data were not available from some monitoring stations). Further work is needed to develop methods for maximizing the information from the data in order to assess any changes in effects due to the intervention. With complete daily air pollution and mortality data over a long period, time-series analysis methods can be applied to assess the short- and long-term effects of air pollution, in terms of changes in life expectancy. Further work is warranted to assess the duration and pattern of the health effects from an air pollution pulse (i.e., an episode of a rapid rise in air pollution) so as to determine an appropriate length and constraint on the distributed-lag assessment model.

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.

Collisional effects on the numerical recurrence in Vlasov-Poisson simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pezzi, Oreste; Valentini, Francesco; Camporeale, Enrico

The initial state recurrence in numerical simulations of the Vlasov-Poisson system is a well-known phenomenon. Here, we study the effect on recurrence of artificial collisions modeled through the Lenard-Bernstein operator [A. Lenard and I. B. Bernstein, Phys. Rev. 112, 1456–1459 (1958)]. By decomposing the linear Vlasov-Poisson system in the Fourier-Hermite space, the recurrence problem is investigated in the linear regime of the damping of a Langmuir wave and of the onset of the bump-on-tail instability. The analysis is then confirmed and extended to the nonlinear regime through an Eulerian collisional Vlasov-Poisson code. It is found that, despite being routinely used,more » an artificial collisionality is not a viable way of preventing recurrence in numerical simulations without compromising the kinetic nature of the solution. Moreover, it is shown how numerical effects associated to the generation of fine velocity scales can modify the physical features of the system evolution even in nonlinear regime. This means that filamentation-like phenomena, usually associated with low amplitude fluctuations contexts, can play a role even in nonlinear regime.« less

Determination of oral mucosal Poisson's ratio and coefficient of friction from in-vivo contact pressure measurements.

PubMed

Chen, Junning; Suenaga, Hanako; Hogg, Michael; Li, Wei; Swain, Michael; Li, Qing

2016-01-01

Despite their considerable importance to biomechanics, there are no existing methods available to directly measure apparent Poisson's ratio and friction coefficient of oral mucosa. This study aimed to develop an inverse procedure to determine these two biomechanical parameters by utilizing in vivo experiment of contact pressure between partial denture and beneath mucosa through nonlinear finite element (FE) analysis and surrogate response surface (RS) modelling technique. First, the in vivo denture-mucosa contact pressure was measured by a tactile electronic sensing sheet. Second, a 3D FE model was constructed based on the patient CT images. Third, a range of apparent Poisson's ratios and the coefficients of friction from literature was considered as the design variables in a series of FE runs for constructing a RS surrogate model. Finally, the discrepancy between computed in silico and measured in vivo results was minimized to identify the best matching Poisson's ratio and coefficient of friction. The established non-invasive methodology was demonstrated effective to identify such biomechanical parameters of oral mucosa and can be potentially used for determining the biomaterial properties of other soft biological tissues.

Oral Health-Related Quality of Life in institutionalized elderly in Barcelona (Spain)

PubMed Central

Pérez, Glòria; de Lima, Kenio C.; Casals-Peidro, Elías; Borrell, Carme

2013-01-01

Objective: The objective of this study is to describe the oral health status and the factors associated with oral health-related quality of life (OHRQoL) in people aged 65 and older institutionalized in Barcelona in 2009. Study Design: Cross sectional study in 194 elderly. The dependent variable was poor OHRQoL, according to the Geriatric Oral Health Assessment Index (GOHAI). The independent variables were socio-demographic data, last dental visit, subjective and objective oral health status. Robust Poisson regression analysis was used to determine the factors associated with OHRQoL as well as the strengths of association (Prevalence Ratios with respective confidence intervals at 95%). Results: According to GOHAI, 94 women (68.1%) and 36 men (64.3%) had poor OHRQoL. The average DMFT index (number of decayed, missing and filled teeth) was 22.8, with mean 10.2 remaining teeth. According to the Community Periodontal Index only 1.9% were healthy. 33.8% of the sample (35.5% of women and 30.4% of men) presented edentulism, 54.2% needed upper dental prostheses (51.1% of women and 60.7% of men) and 64.7% needed lower ones (61.6% of women and 71.4% of men). Only 7.2% had visited a dentist in the past year (8.8% of women and 3.6% of men). After fitting several multivariate adjusted robust Poisson regression models, poor OHRQoL was found to be associated to self-reporting problems with teeth or gums, self-reporting poor opinion about teeth/gums/denture and also associated to functional edentulism, needing upper denture, but not to socio-demographic factors or time since last dental visit. Conclusions: The study population has poor objective oral health. A high percentage has poor OHRQoL associated to subjective and objective oral health conditions. Dental care is required and these services should be included in the Spanish National Health System. Key words:Oral health, homes for the aged, elderly, self-assessment, quality of life, geriatric oral health assessment index (GOHAI). PMID:23385501

Migration pattern and mortality of ethnic German migrants from the former Soviet Union: a cohort study in Germany

PubMed Central

Kaucher, Simone; Deckert, Andreas; Becher, Heiko; Winkler, Volker

2017-01-01

Objective We aimed to investigate all-cause and cause-specific mortality among ethnic German migrants from the former Soviet Union by different immigration periods to describe associations with migration pattern and mortality. Design We used pooled data from three retrospective cohort studies in Germany. Participants Ethnic German migrants from the former Soviet Union (called resettlers), who immigrated to Germany since 1990 to the federal states North Rhine-Westphalia and Saarland and to the region of Augsburg (n=59 390). Outcome All-cause and cause-specific mortality among resettlers in comparison to the general German population, separated by immigration period. Methods Immigration periods were defined following legislative changes in German immigration policy (1990–1992, 1993–1995, 1996+). Resettlers’ characteristics were described accordingly. To investigate mortality differences by immigration period, we calculated age-standardised mortality rates (ASRs) and standardised mortality ratios (SMRs) of resettlers in comparison to the general German population. Additionally, we modelled sex-specific ASRs with Poisson regression, using age, year and immigration period as independent variables. Results The composition of resettlers differed by immigration period. Since 1993, the percentage of resettlers from the Russian Federation and non-German spouses increased. Higher all-cause mortality was found among resettlers who immigrated in 1996 and after (ASR 628.1, 95% CI 595.3 to 660.8), compared with resettlers who immigrated before 1993 (ASR 561.8, 95% CI 537.2 to 586.4). SMR analysis showed higher all-cause mortality among resettler men from the last immigration period compared with German men (SMR 1.11, 95% CI 1.04 to 1.19), whereas resettlers who immigrated earlier showed lower all-cause mortality. Results from Poisson regression, adjusted for age and year, corroborated those findings. Conclusions Mortality differences by immigration period suggest different risk-factor patterns and possibly deteriorated integration opportunities. Health policy should guard the consequences of immigration law alterations with respect to changing compositions of migrant groups and their health status. PMID:29259065

Factors associated with poor balance ability in older adults of nine high-altitude communities.

PubMed

Urrunaga-Pastor, Diego; Moncada-Mapelli, Enrique; Runzer-Colmenares, Fernando M; Bailon-Valdez, Zaira; Samper-Ternent, Rafael; Rodriguez-Mañas, Leocadio; Parodi, Jose F

Poor balance ability in older adults result in multiple complications. Poor balance ability has not been studied among older adults living at high altitudes. In this study, we analysed factors associated with poor balance ability by using the Functional Reach (FR) among older adults living in nine high-altitude communities. Analytical cross-sectional study, carried out in inhabitants aged 60 or over from nine high-altitude Andean communities of Peru during 2013-2016. FR was divided according to the cut-off point of 8 inches (20.32 cm) and two groups were generated: poor balance ability (FR less or equal than 20.32 cm) and good balance ability (greater than 20.32 cm). Additionally, we collected socio-demographic, medical, functional and cognitive assessment information. Poisson regression models were constructed to identify factors associated with poor balance ability. Prevalence ratio (PR) with 95% confidence intervals (95CI%) are presented. A total of 365 older adults were studied. The average age was 73.0 ± 6.9 years (range: 60-91 years), and 180 (49.3%) participants had poor balance ability. In the adjusted Poisson regression analysis, the factors associated with poor balance ability were: alcohol consumption (PR = 1.35; 95%CI: 1.05-1.73), exhaustion (PR = 2.22; 95%CI: 1.49-3.31), gait speed (PR = 0.67; 95%CI: 0.50-0.90), having had at least one fall in the last year (PR = 2.03; 95%CI: 1.19-3.46), having at least one comorbidity (PR = 1.60; 95%CI: 1.10-2.35) and having two or more comorbidities (PR = 1.61; 95%CI: 1.07-2.42) compared to none. Approximately a half of the older adults from these high-altitude communities had poor balance ability. Interventions need to be designed to target these balance issues and prevent adverse events from concurring to these individuals. Copyright © 2018 Elsevier B.V. All rights reserved.

Migration pattern and mortality of ethnic German migrants from the former Soviet Union: a cohort study in Germany.

PubMed

Kaucher, Simone; Deckert, Andreas; Becher, Heiko; Winkler, Volker

2017-12-19

We aimed to investigate all-cause and cause-specific mortality among ethnic German migrants from the former Soviet Union by different immigration periods to describe associations with migration pattern and mortality. We used pooled data from three retrospective cohort studies in Germany. Ethnic German migrants from the former Soviet Union (called resettlers), who immigrated to Germany since 1990 to the federal states North Rhine-Westphalia and Saarland and to the region of Augsburg (n=59 390). All-cause and cause-specific mortality among resettlers in comparison to the general German population, separated by immigration period. Immigration periods were defined following legislative changes in German immigration policy (1990-1992, 1993-1995, 1996+). Resettlers' characteristics were described accordingly. To investigate mortality differences by immigration period, we calculated age-standardised mortality rates (ASRs) and standardised mortality ratios (SMRs) of resettlers in comparison to the general German population. Additionally, we modelled sex-specific ASRs with Poisson regression, using age, year and immigration period as independent variables. The composition of resettlers differed by immigration period. Since 1993, the percentage of resettlers from the Russian Federation and non-German spouses increased. Higher all-cause mortality was found among resettlers who immigrated in 1996 and after (ASR 628.1, 95% CI 595.3 to 660.8), compared with resettlers who immigrated before 1993 (ASR 561.8, 95% CI 537.2 to 586.4). SMR analysis showed higher all-cause mortality among resettler men from the last immigration period compared with German men (SMR 1.11, 95% CI 1.04 to 1.19), whereas resettlers who immigrated earlier showed lower all-cause mortality. Results from Poisson regression, adjusted for age and year, corroborated those findings. Mortality differences by immigration period suggest different risk-factor patterns and possibly deteriorated integration opportunities. Health policy should guard the consequences of immigration law alterations with respect to changing compositions of migrant groups and their health status. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Geographical factors affecting bed net ownership, a tool for the elimination of Anopheles-transmitted lymphatic filariasis in hard-to-reach communities.

PubMed

Stanton, Michelle C; Bockarie, Moses J; Kelly-Hope, Louise A

2013-01-01

Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = -0.28, -0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67-7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy.

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment

PubMed Central

Rice, F; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

OBJECTIVE—To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust.
METHODS—Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death.
RESULTS—Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m3 for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000).
CONCLUSIONS—There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.


Keywords: crystalline silica; cristobalite; lung cancer PMID:11119633

Latent Profiles of Macronutrient Density and their Association with Mobility Limitations in an Observational Longitudinal Study of Older U.S. Adults.

PubMed

Bishop, N J; Zuniga, K E; Lucht, A L

2018-01-01

Our first objective was to estimate empirically-derived subgroups (latent profiles) of observed carbohydrate, protein, and fat intake density in a nationally representative sample of older U.S. adults. Our second objective was to determine whether membership in these groups was associated with levels of, and short term change in, physical mobility limitations. Measures of macronutrient density were taken from the 2013 Health Care and Nutrition Study, an off-year supplement to the Health and Retirement Study, which provided indicators of physical mobility limitations and sociodemographic and health-related covariates. 3,914 community-dwelling adults age 65 years and older. Percent of daily calories from carbohydrate, protein, and fat were calculated based on responses to a modified Harvard food frequency questionnaire. Latent profile analysis was used to describe unobserved heterogeneity in measures of carbohydrate, protein, and fat density. Mobility limitation counts were based on responses to 11 items indicating physical limitations. Poisson regression models with autoregressive controls were used to identify associations between macronutrient density profile membership and mobility limitations. Sociodemographic and health-related covariates were included in all Poisson regression models. Four latent subgroups of macronutrient density were identified: "High Carbohydrate", "Moderate with Fat", "Moderate", and "Low Carbohydrate/High Fat". Older adults with the lowest percentage of daily calories coming from carbohydrate and the greatest percentage coming from fat ("Low Carbohydrate/High Fat") were found to have greater reported mobility limitations in 2014 than those identified as having moderate macronutrient density, and more rapid two-year increases in mobility limitations than those identified as "Moderate with Fat" or "Moderate". Older adults identified as having the lowest carbohydrate and highest fat energy density were more likely to report a greater number of mobility limitations and experience greater increases in these limitations than those identified as having moderate macronutrient density. These results suggest that the interrelation of macronutrients must be considered by those seeking to reduce functional limitations among older adults through dietary interventions.

Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of Anopheles-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities

PubMed Central

Stanton, Michelle C.; Bockarie, Moses J.; Kelly-Hope, Louise A.

2013-01-01

Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = −0.28, −0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67–7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy. PMID:23308281

BFV-BRST analysis of equivalence between noncommutative and ordinary gauge theories

NASA Astrophysics Data System (ADS)

Dayi, O. F.

2000-05-01

Constrained hamiltonian structure of noncommutative gauge theory for the gauge group /U(1) is discussed. Constraints are shown to be first class, although, they do not give an Abelian algebra in terms of Poisson brackets. The related BFV-BRST charge gives a vanishing generalized Poisson bracket by itself due to the associativity of /*-product. Equivalence of noncommutative and ordinary gauge theories is formulated in generalized phase space by using BFV-BRST charge and a solution is obtained. Gauge fixing is discussed.

The transverse Poisson's ratio of composites.

NASA Technical Reports Server (NTRS)

Foye, R. L.

1972-01-01

An expression is developed that makes possible the prediction of Poisson's ratio for unidirectional composites with reference to any pair of orthogonal axes that are normal to the direction of the reinforcing fibers. This prediction appears to be a reasonable one in that it follows the trends of the finite element analysis and the bounding estimates, and has the correct limiting value for zero fiber content. It can only be expected to apply to composites containing stiff, circular, isotropic fibers bonded to a soft matrix material.

The Spot of Arago and Its Role in Aberration Analysis.

DTIC Science & Technology

1983-12-01

Finally, my family and in- laws were always there with patience, love and support. This thesis would have been impossible were it not for my wife...five was chosen to judge the entries. The panel members were Laplace, Biot, Arago, Sime6n Denis Poisson and Joseph - Louis Gay- Lussac . Laplace, Biot and...Poisson were staunch adherents of P the particle theory of light while Arago advocated Fresnel’s view. P - *..*. ..-. 9 Gay- Lussac , a chemist, was

A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs.

PubMed

Jones, Andrew M; Lomas, James; Moore, Peter T; Rice, Nigel

2016-10-01

We conduct a quasi-Monte-Carlo comparison of the recent developments in parametric and semiparametric regression methods for healthcare costs, both against each other and against standard practice. The population of English National Health Service hospital in-patient episodes for the financial year 2007-2008 (summed for each patient) is randomly divided into two equally sized subpopulations to form an estimation set and a validation set. Evaluating out-of-sample using the validation set, a conditional density approximation estimator shows considerable promise in forecasting conditional means, performing best for accuracy of forecasting and among the best four for bias and goodness of fit. The best performing model for bias is linear regression with square-root-transformed dependent variables, whereas a generalized linear model with square-root link function and Poisson distribution performs best in terms of goodness of fit. Commonly used models utilizing a log-link are shown to perform badly relative to other models considered in our comparison.

Poisson Approximation-Based Score Test for Detecting Association of Rare Variants.

PubMed

Fang, Hongyan; Zhang, Hong; Yang, Yaning

2016-07-01

Genome-wide association study (GWAS) has achieved great success in identifying genetic variants, but the nature of GWAS has determined its inherent limitations. Under the common disease rare variants (CDRV) hypothesis, the traditional association analysis methods commonly used in GWAS for common variants do not have enough power for detecting rare variants with a limited sample size. As a solution to this problem, pooling rare variants by their functions provides an efficient way for identifying susceptible genes. Rare variant typically have low frequencies of minor alleles, and the distribution of the total number of minor alleles of the rare variants can be approximated by a Poisson distribution. Based on this fact, we propose a new test method, the Poisson Approximation-based Score Test (PAST), for association analysis of rare variants. Two testing methods, namely, ePAST and mPAST, are proposed based on different strategies of pooling rare variants. Simulation results and application to the CRESCENDO cohort data show that our methods are more powerful than the existing methods. © 2016 John Wiley & Sons Ltd/University College London.

Information transmission in hippocampal CA1 neuron models in the presence of poisson shot noise: the case of periodic sub-threshold spike trains.

PubMed

Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M

2006-01-01

This article presents an analysis of the information transmission of periodic sub-threshold spike trains in a hippocampal CA1 neuron model in the presence of a homogeneous Poisson shot noise. In the computer simulation, periodic sub-threshold spike trains were presented repeatedly to the midpoint of the main apical branch, while the homogeneous Poisson shot noise was applied to the mid-point of a basal dendrite in the CA1 neuron model consisting of the soma with one sodium, one calcium, and five potassium channels. From spike firing times recorded at the soma, the inter spike intervals were generated and then the probability, p(T), of the inter-spike interval histogram corresponding to the spike interval, r, of the periodic input spike trains was estimated to obtain an index of information transmission. In the present article, it is shown that at a specific amplitude of the homogeneous Poisson shot noise, p(T) was found to be maximized, as well as the possibility to encode the periodic sub-threshold spike trains became greater. It was implied that setting the amplitude of the homogeneous Poisson shot noise to the specific values which maximize the information transmission might contribute to efficiently encoding the periodic sub-threshold spike trains by utilizing the stochastic resonance.

Competitive Swimming and Racial Disparities in Drowning

PubMed Central

Myers, Samuel L.; Cuesta, Ana M.; Lai, Yufeng

2018-01-01

This paper provides compelling evidence of an inverse relationship between competitive swimming rates and drowning rates using Centers for Disease Control and Prevention (CDC) data on fatal drowning rates and membership rates from USA Swimming, the governing organization of competitive swimming in the United States. Tobit and Poisson regression models are estimated using panel data by state from 1999–2007 separately for males, females, African Americans and whites. The strong inverse relationship between competitive swimming rates and unintentional deaths through fatal drowning is most pronounced among African Americans males.

A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

PubMed Central

2013-01-01

Background The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Results Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. Conclusions In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. PMID:23442253

Convergence of Spectral Discretizations of the Vlasov--Poisson System

DOE PAGES

Manzini, G.; Funaro, D.; Delzanno, G. L.

2017-09-26

Here we prove the convergence of a spectral discretization of the Vlasov-Poisson system. The velocity term of the Vlasov equation is discretized using either Hermite functions on the infinite domain or Legendre polynomials on a bounded domain. The spatial term of the Vlasov and Poisson equations is discretized using periodic Fourier expansions. Boundary conditions are treated in weak form through a penalty type term that can be applied also in the Hermite case. As a matter of fact, stability properties of the approximated scheme descend from this added term. The convergence analysis is carried out in detail for the 1D-1Vmore » case, but results can be generalized to multidimensional domains, obtained as Cartesian product, in both space and velocity. The error estimates show the spectral convergence under suitable regularity assumptions on the exact solution.« less

Does the U.S. exercise contagion on Italy? A theoretical model and empirical evidence

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Fenga, Livio; Ventura, Marco

2018-06-01

This paper deals with the theme of contagion in financial markets. At this aim, we develop a model based on Mixed Poisson Processes to describe the abnormal returns of financial markets of two considered countries. In so doing, the article defines the theoretical conditions to be satisfied in order to state that one of them - the so-called leader - exercises contagion on the others - the followers. Specifically, we employ an invariant probabilistic result stating that a suitable transformation of a Mixed Poisson Process is still a Mixed Poisson Process. The theoretical claim is validated by implementing an extensive simulation analysis grounded on empirical data. The countries considered are the U.S. (as the leader) and Italy (as the follower) and the period under scrutiny is very large, ranging from 1970 to 2014.

Brain, music, and non-Poisson renewal processes

NASA Astrophysics Data System (ADS)

Bianco, Simone; Ignaccolo, Massimiliano; Rider, Mark S.; Ross, Mary J.; Winsor, Phil; Grigolini, Paolo

2007-06-01

In this paper we show that both music composition and brain function, as revealed by the electroencephalogram (EEG) analysis, are renewal non-Poisson processes living in the nonergodic dominion. To reach this important conclusion we process the data with the minimum spanning tree method, so as to detect significant events, thereby building a sequence of times, which is the time series to analyze. Then we show that in both cases, EEG and music composition, these significant events are the signature of a non-Poisson renewal process. This conclusion is reached using a technique of statistical analysis recently developed by our group, the aging experiment (AE). First, we find that in both cases the distances between two consecutive events are described by nonexponential histograms, thereby proving the non-Poisson nature of these processes. The corresponding survival probabilities Ψ(t) are well fitted by stretched exponentials [ Ψ(t)∝exp (-(γt)α) , with 0.5<α<1 .] The second step rests on the adoption of AE, which shows that these are renewal processes. We show that the stretched exponential, due to its renewal character, is the emerging tip of an iceberg, whose underwater part has slow tails with an inverse power law structure with power index μ=1+α . Adopting the AE procedure we find that both EEG and music composition yield μ<2 . On the basis of the recently discovered complexity matching effect, according to which a complex system S with μS<2 responds only to a complex driving signal P with μP⩽μS , we conclude that the results of our analysis may explain the influence of music on the human brain.

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

PubMed Central

Inouye, David I.; Ravikumar, Pradeep; Dhillon, Inderjit S.

2016-01-01

We develop Square Root Graphical Models (SQR), a novel class of parametric graphical models that provides multivariate generalizations of univariate exponential family distributions. Previous multivariate graphical models (Yang et al., 2015) did not allow positive dependencies for the exponential and Poisson generalizations. However, in many real-world datasets, variables clearly have positive dependencies. For example, the airport delay time in New York—modeled as an exponential distribution—is positively related to the delay time in Boston. With this motivation, we give an example of our model class derived from the univariate exponential distribution that allows for almost arbitrary positive and negative dependencies with only a mild condition on the parameter matrix—a condition akin to the positive definiteness of the Gaussian covariance matrix. Our Poisson generalization allows for both positive and negative dependencies without any constraints on the parameter values. We also develop parameter estimation methods using node-wise regressions with ℓ1 regularization and likelihood approximation methods using sampling. Finally, we demonstrate our exponential generalization on a synthetic dataset and a real-world dataset of airport delay times. PMID:27563373

Large Occurrence Patterns of New Zealand Deep Earthquakes: Characterization by Use of a Switching Poisson Model

NASA Astrophysics Data System (ADS)

Shaochuan, Lu; Vere-Jones, David

2011-10-01

The paper studies the statistical properties of deep earthquakes around North Island, New Zealand. We first evaluate the catalogue coverage and completeness of deep events according to cusum (cumulative sum) statistics and earlier literature. The epicentral, depth, and magnitude distributions of deep earthquakes are then discussed. It is worth noting that strong grouping effects are observed in the epicentral distribution of these deep earthquakes. Also, although the spatial distribution of deep earthquakes does not change, their occurrence frequencies vary from time to time, active in one period, relatively quiescent in another. The depth distribution of deep earthquakes also hardly changes except for events with focal depth less than 100 km. On the basis of spatial concentration we partition deep earthquakes into several groups—the Taupo-Bay of Plenty group, the Taranaki group, and the Cook Strait group. Second-order moment analysis via the two-point correlation function reveals only very small-scale clustering of deep earthquakes, presumably limited to some hot spots only. We also suggest that some models usually used for shallow earthquakes fit deep earthquakes unsatisfactorily. Instead, we propose a switching Poisson model for the occurrence patterns of deep earthquakes. The goodness-of-fit test suggests that the time-varying activity is well characterized by a switching Poisson model. Furthermore, detailed analysis carried out on each deep group by use of switching Poisson models reveals similar time-varying behavior in occurrence frequencies in each group.

Impact of traffic congestion on road accidents: a spatial analysis of the M25 motorway in England.

PubMed

Wang, Chao; Quddus, Mohammed A; Ison, Stephen G

2009-07-01

Traffic congestion and road accidents are two external costs of transport and the reduction of their impacts is often one of the primary objectives for transport policy makers. The relationship between traffic congestion and road accidents however is not apparent and less studied. It is speculated that there may be an inverse relationship between traffic congestion and road accidents, and as such this poses a potential dilemma for transport policy makers. This study aims to explore the impact of traffic congestion on the frequency of road accidents using a spatial analysis approach, while controlling for other relevant factors that may affect road accidents. The M25 London orbital motorway, divided into 70 segments, was chosen to conduct this study and relevant data on road accidents, traffic and road characteristics were collected. A robust technique has been developed to map M25 accidents onto its segments. Since existing studies have often used a proxy to measure the level of congestion, this study has employed a precise congestion measurement. A series of Poisson based non-spatial (such as Poisson-lognormal and Poisson-gamma) and spatial (Poisson-lognormal with conditional autoregressive priors) models have been used to account for the effects of both heterogeneity and spatial correlation. The results suggest that traffic congestion has little or no impact on the frequency of road accidents on the M25 motorway. All other relevant factors have provided results consistent with existing studies.

Orientational analysis of planar fibre systems observed as a Poisson shot-noise process.

PubMed

Kärkkäinen, Salme; Lantuéjoul, Christian

2007-10-01

We consider two-dimensional fibrous materials observed as a digital greyscale image. The problem addressed is to estimate the orientation distribution of unobservable thin fibres from a greyscale image modelled by a planar Poisson shot-noise process. The classical stereological approach is not straightforward, because the point intensities of thin fibres along sampling lines may not be observable. For such cases, Kärkkäinen et al. (2001) suggested the use of scaled variograms determined from grey values along sampling lines in several directions. Their method is based on the assumption that the proportion between the scaled variograms and point intensities in all directions of sampling lines is constant. This assumption is proved to be valid asymptotically for Boolean models and dead leaves models, under some regularity conditions. In this work, we derive the scaled variogram and its approximations for a planar Poisson shot-noise process using the modified Bessel function. In the case of reasonable high resolution of the observed image, the scaled variogram has an approximate functional relation to the point intensity, and in the case of high resolution the relation is proportional. As the obtained relations are approximative, they are tested on simulations. The existing orientation analysis method based on the proportional relation is further experimented on images with different resolutions. The new result, the asymptotic proportionality between the scaled variograms and the point intensities for a Poisson shot-noise process, completes the earlier results for the Boolean models and for the dead leaves models.

The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants--An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots.

PubMed

Kauhl, Boris; Heil, Jeanne; Hoebe, Christian J P A; Schweikart, Jürgen; Krafft, Thomas; Dukers-Muijrers, Nicole H T M

2015-01-01

Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002-2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants.

Assessing model uncertainty using hexavalent chromium and ...

EPA Pesticide Factsheets

Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective of this analysis is to characterize model uncertainty by evaluating the variance in estimates across several epidemiologic analyses.Methods: This analysis compared 7 publications analyzing two different chromate production sites in Ohio and Maryland. The Ohio cohort consisted of 482 workers employed from 1940-72, while the Maryland site employed 2,357 workers from 1950-74. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability in estimates across and within model forms. A total of 7 similarly parameterized analyses were considered across model forms, and 23 analyses with alternative parameterizations were considered within model form (14 Cox; 9 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients for 7 similar analyses ranged from 2.47

Developing descriptors to predict mechanical properties of nanotubes.

PubMed

Borders, Tammie L; Fonseca, Alexandre F; Zhang, Hengji; Cho, Kyeongjae; Rusinko, Andrew

2013-04-22

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.

Malocclusion and socioeconomic indicators in primary dentition.

PubMed

Sousa, Raulison Vieira de; Pinto-Monteiro, Ana Karla de Almeida; Martins, Carolina Castro; Granville-Garcia, Ana Flávia; Paiva, Saul Martins

2014-01-01

The aim of the present study was to determine the prevalence of malocclusion and associations with socioeconomic indicators among preschoolers. A cross-sectional study was conducted with 732 children 3 to 5 years of age in the city of Campina Grande, Brazil. Three dentists underwent a calibration exercise (K = 0.85–0.90) and diagnosed malocclusion based on the criteria proposed by Foster & Hamilton and Grabowski et al. Parents/guardians answered a questionnaire addressing sociodemographic aspects. Data analysis involved descriptive statistics and bivariate Poisson regression (PR; α = 5%). The prevalence of malocclusion was 62.4%. The most frequent types were increased overjet (42.6%), anterior open bite (21%) and deep overbite (19.3%). An association was found between malocclusion and age: the prevalence of malocclusion was greater among younger children, with the highest prevalence among 3-year-olds (PR = 1.116; 95%CI = 1.049–1.187). The prevalence of malocclusion was high. Mother's schooling and household income were not associated with malocclusion. Socioeconomic factors were also not associated with the occurrence of malocclusion.

Early determinants of attention and hyperactivity problems in adolescents: the 11-year follow-up of the 1993 Pelotas (Brazil) birth cohort study.

PubMed

Anselmi, Luciana; Menezes, Ana M B; Barros, Fernando C; Hallal, Pedro C; Araújo, Cora Luiza; Domingues, Marlos R; Rohde, Luis A

2010-10-01

The aim of this study was to assess early determinants of attention and hyperactivity problems in adolescents. In 1993, all hospital births in the city of Pelotas, Rio Grande do Sul State, Brazil, were monitored and mothers were interviewed (N = 5,249). At 11 years of age, 4,423 mothers answered the Strengths and Difficulties Questionnaire (SDQ) in order to evaluate attention and hyperactivity problems in the adolescents. Crude and adjusted prevalence ratios were calculated using Poisson regression. Prevalence of attention and hyperactivity problems was 19.9%. Factors associated with the outcome in the adjusted analysis were: male gender, low family income, smoking during pregnancy, minor psychiatric disorders in the mother, and history of child's behavioral/emotional problems at four years of age. Early life events impacted attention and hyperactivity problems in adolescence. Risk factors for attention and hyperactivity problems found in this study were similar to those reported in other cultures.

An interdisciplinary perspective on social and physical determinants of seismic risk

NASA Astrophysics Data System (ADS)

Lin, K.-H.; Chang, Y.-C.; Liu, G.-Y.; Chan, C.-H.; Lin, T.-H.; Yeh, C.-H.

2015-01-01

While disaster studies researchers usually view risk as a function of hazard, exposure, and vulnerability, few studies have systematically examined the relationships among the various physical and socioeconomic determinants underlying disasters, and fewer have done so through seismic risk analysis. In the context of the 1999 Chi-Chi earthquake in Taiwan, this study constructs five hypothetical models to test different determinants that affect disaster fatality at the village level, namely seismic hazard intensity, population, building fragility, demographics and socioeconomics. The Poisson Regression Model is used to estimate the impact of natural hazards and social factors on fatality. Results indicate that although all of the determinants have an impact on the specific dimension of seismic fatality, some indicators of social inequality, such as gender ratio, dependency ratio, income and its SD, are the driving determinants deteriorating vulnerability to seismic risk. These findings have strong social implications for policy interventions to mitigate such disasters. This study presents an interdisciplinary investigation into social and physical determinants in seismic risk.

[Alcohol consumption by university students].

PubMed

Pedrosa, Adriano Antonio da Silva; Camacho, Luiz Antonio Bastos; Passos, Sônia Regina Lambert; Oliveira, Raquel de Vasconcellos Carvalhaes de

2011-08-01

Consumption of alcoholic beverages is widely encouraged by the mass media, despite the related health risks. Today's students in the health fields are the professionals of tomorrow who will be providing advice and serving as role models for patients. The aim of this study was to analyze alcohol consumption and related factors among these students. A total of 608 male and female university students from Maceió, the capital of Alagoas State, Brazil, completed a self-administered questionnaire. Data analysis included Poisson regression and multinomial logistic models. Prevalence of lifetime use of alcohol was 90.4%. Prevalence of alcohol abuse was 18.3% in men and 6.1% in women. Heavier alcohol consumption and alcohol abuse were observed in males, older students, non-natives of Maceió, smokers, and those exposed to alcohol advertising. The results emphasized the vulnerability of these young people to risky health behaviors. Their future social role highlights distinct needs in their university education to enable them to act professionally in this area.

Association between perception of maternal bonding styles and social anxiety disorder among young women.

PubMed

Castelli, Rochele D; Quevedo, Luciana de Á; Coelho, Fábio M; Lopez, Mariane A; da Silva, Ricardo A; Böhm, Denise M; Souza, Luciano D; de Matos, Mariana B; Pinheiro, Karen A; Pinheiro, Ricardo T

2015-01-01

To evaluate the association between social anxiety disorder (SAD) and perceived maternal bonding styles among young women during pregnancy and 30 months after childbirth. A cohort of young women from the city of Pelotas, Brazil was followed up from pregnancy to 30 months postpartum. The Mini Neuropsychiatric Interview Plus was used to assess SAD and the Parental Bonding Instrument was administered to measure maternal bonding styles. Poisson regression with robust variance was used for multivariable analysis. After adjusting for potential confounding factors, SAD prevalence was 6.39 times higher among young women who perceived their mothers as neglectful (prevalence ratio [PR] 6.39; 95% confidence interval [95%CI] 1.2-32.0), and 5.57 times higher in women who perceived their mothers as affectionless controlling (PR = 5.57; 95%CI 1.5-19.7) when compared with those who received optimal care. Maternal bonding style may have an influence on the development of SAD. Therefore, support and early prevention strategies should be offered to the family.

Religious Affiliation and Fertility in a Sub-Saharan Context: Dynamic and Lifetime Perspectives.

PubMed

Agadjanian, Victor; Yabiku, Scott T

2014-10-01

We use uniquely detailed data from a predominantly Christian high-fertility area in Mozambique to examine denominational differentials in fertility from two complementary perspectives-dynamic and cumulative. First, we use event-history analysis to predict yearly risks of birth from denominational affiliation. Then, we employ Poisson regression to model the association between the number of children ever born and share of reproductive life spent in particular denominations or outside organized religion. Both approaches detect a significant increase in fertility associated with membership in a particular type of African-initiated churches which is characterized by strong organizational identity, rigid hierarchy, and insular corporate culture. Membership in the Catholic Church is also associated with elevated completed fertility. We relate these results to extant theoretical perspectives on the relationship between religion and fertility by stressing the interplay between ideological, social, and organizational characteristics of different types of churches and situate our findings within the context of fertility transition and religious demographics in Mozambique and elsewhere in sub-Saharan Africa.

Gender Differences in Factors Associated With Anal Intercourse Among Heterosexual Adolescents in Singapore.

PubMed

Ng, Junice Y S; Wong, Mee-Lian; Chan, Roy K W; Sen, Priya; Chio, Martin T W; Koh, David

2015-08-01

Using a cross-sectional survey, we examined the gender differences in prevalence of and factors associated with anal sex among adolescents attending the only public STI clinic in Singapore. Data were collected from 1035 sexually active adolescents aged 14 to 19 and analyzed using Poisson regression. Prevalence of anal intercourse was 28%, with significantly more females (32%) than males (23%) ever engaged in it. On multivariate analysis, the factors associated with anal intercourse for both genders were oral sex and the nonuse of contraception at last sex. For males, anal intercourse was associated with younger age of sexual debut and greater perceived external control. Among females, it was associated with higher rebellious scores and lack of confidence to resist peer pressure to engage in sex. Consistent condom use for anal sex was 22% and 8% for males and females, respectively. STI prevention programs for adolescents should address anal sex, be gender-specific, and take into consideration individual personality characteristics.

Radon in Drinking Water and Cancer Mortality: An Ecological Study in Japan

NASA Astrophysics Data System (ADS)

Yoshinaga, Shinji; Ishikawa, Tetsuo; Tokonami, Shinji; Mizoue, Tetsuya; Narazaki, Yukinori; Mizuno, Shoichi; Akiba, Suminori

2008-08-01

There is limited information on the health effects of radon in drinking water in spite of their potential exposures. We conducted an ecological study in a small town in Japan where the groundwater with high concentrations of radon is supplied as utilities. A total of 607 cancer deaths were ascertained by vital statistics in that town from 1972 to 1997. Standardized mortality ratios on the basis of national rates were 1.01 (95% confidence interval; 0.93-1.09) for all cancers, 1.10 (0.95-1.28) for stomach cancer, 0.88 (0.70-1.10) for lung cancer, and 1.14 (0.87-1.48) for liver cancer. Mortality from liver cancer was significantly higher than that of two surrounding control cities combined, with a relative risk of 1.40 (1.04-1.89) based on Poisson regression analysis. Lack of information on possible confounders including diet, alcohol drinking, smoking and hepatitis virus infection, is the main limitation of the study, which precludes the evaluation of causal associations.

Immunological response to quadrivalent HPV vaccine in treatment of recurrent respiratory papillomatosis.

PubMed

Tjon Pian Gi, Robin E A; San Giorgi, Michel R M; Pawlita, Michael; Michel, Angelika; van Hemel, Bettien M; Schuuring, Ed M D; van den Heuvel, Edwin R; van der Laan, Bernard F A M; Dikkers, Frederik G

2016-10-01

Aim of this study was to explore influence of the quadrivalent HPV vaccine (Gardasil(®)) on the immune status of recurrent respiratory papillomatosis (RRP) patients. In retrospective observational study, six RRP patients who received the quadrivalent HPV vaccine and whose HPV seroreactivity was measured were included. Multiplex HPV Serology was used to determine HPV-specific antibodies pre- and post-vaccination. Surgical interventions and patient records were analyzed. Five HPV6 and 1 HPV11 infected patient were included. Mean antibody reactivity against the associated HPV type rose from 1125 median fluorescence intensity (MFI) pre-vaccination to 4690 MFI post-vaccination (p < 0.001). Median post-vaccination follow-up was 4 years. Poisson regression analysis showed that the quadrivalent HPV vaccine decreased the incidence rate of surgeries. The immune system of RRP patients is able to increase antibody reactivity against the associated HPV type. A double blind randomized controlled trial is needed to determine whether this immunological increase can cause decrease in number of surgeries.

Contributing influences of work environment on sleep quantity and quality of nursing assistants in long-term care facilities: A cross-sectional study

PubMed Central

Zhang, Yuan; Punnett, Laura; McEnany, Geoffry Phillips; Gore, Rebecca

2018-01-01

The effect of shift work on nurses’ sleep is well-studied, but there are other challenging aspects of health care work that might also affect the sleep of direct caregivers. This study examined the influence of the long-term care work environment on sleep quantity and quality of nursing assistants. A cross-sectional survey collected data from 650 nursing assistants in 15 long-term care facilities; 46% reported short sleep duration and 23% reported poor sleep quality. A simple additive index of the number of beneficial work features (up to 7) was constructed for analysis with Poisson regression. With each unit increase of beneficial work features, nursing assistants were 7% less likely to report short sleep duration and 17% less likely to report poor sleep quality. These results suggest that effective workplace interventions should address a variety of work stressors, not only work schedule arrangements, in order to improve nursing assistants’ sleep health. PMID:26384714

Fractional Poisson Fields and Martingales

NASA Astrophysics Data System (ADS)

Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely

2018-02-01

We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.

On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action

NASA Astrophysics Data System (ADS)

Chekhov, L. O.; Mazzocco, M.

2017-12-01

Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.

On the association between outdoor PM2.5 concentration and the seasonality of tuberculosis for Beijing and Hong Kong.

PubMed

You, Siming; Tong, Yen Wah; Neoh, Koon Gee; Dai, Yanjun; Wang, Chi-Hwa

2016-11-01

Tuberculosis (TB) is still a serious public health problem in various countries. One of the long-elusive but critical questions about TB is what the risk factors are and how they contribute for its seasonality. An ecologic study was conducted to examine the association between the variation of outdoor PM 2.5 concentration and the TB seasonality based on the monthly TB notification and PM 2.5 concentration data of Hong Kong and Beijing. Both descriptive analysis and Poisson regression analysis suggested that the outdoor PM 2.5 concentration could be a potential risk factor for the seasonality of TB disease. The significant relationship between the number of TB cases and PM 2.5 concentration was not changed when regression models were adjusted by sunshine duration, a potential confounder. The regression analysis showed that a 10 μg/m 3 increase in PM 2.5 concentrations during winter is significantly associated with a 3% (i.e. 18 and 14 cases for Beijing and Hong Kong, respectively) increase in the number of TB cases notified during the coming spring or summer for both Beijing and Hong Kong. Three potential mechanisms were proposed to explain the significant relationship: (1) increased PM 2.5 exposure increases host's susceptibility to TB disease by impairing or modifying the immunology of the human respiratory system; (2) increased indoor activities during high outdoor PM 2.5 episodes leads to an increase in human contact and thus the risk of TB transmission; (3) the seasonal change of PM 2.5 concentration is correlated with the variation of other potential risk factors of TB seasonality. Preliminary evidence from the analysis of this work favors the first mechanism about the PM 2.5 exposure-induced immunity impairment. This work adds new horizons to the explanation of the TB seasonality and improves our understanding of the potential mechanisms affecting TB incidence, which benefits the prevention and control of TB disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design and statistical problems in prevention.

PubMed

Gullberg, B

1996-01-01

Clinical and epidemiological research in osteoporosis can benefit from using the methods and techniques established in the area of chronic disease epidemiology. However, attention has to be given to the special characteristics such as the multifactorial nature and the fact that the subjects usually are of high ages. In order to evaluate prevention it is of course first necessary to detect and confirm reversible risk factors. The advantage and disadvantage of different design (cross-sectional, cohort and case-control) are well known. The effects of avoidable biases, e.g. selection, observation and confounding have to be balanced against practical conveniences like time, expenses, recruitment etc. The translation of relative risks into population attributable risks (etiologic fractions, prevented fractions) are complex and are usually performed under unrealistic, simplified assumptions. The consequences of interactions (synergy) between risk factors are often neglected. The multifactorial structure requires application of more advanced multi-level statistical techniques. The common strategy in prevention to target a cluster of risk factors in order to avoid the multifactorial nature implies that in the end it is impossible to separate each unique factor. Experimental designs for evaluating prevention like clinical trials and intervention have to take into account the distinction between explanatory and pragmatic studies. An explanatory approach is similar to an idealized laboratory trial while the pragmatic design is more realistic, practical and has a general public health perspective. The statistical techniques to be used in osteoporosis research are implemented in easy available computer-packages like SAS, SPSS, BMDP and GLIM. In addition to the traditional logistic regression methods like Cox analysis and Poisson regression also analysis of repeated measurement and cluster analysis are relevant.

High prolactin levels are independently associated with damage accrual in systemic lupus erythematosus patients.

PubMed

Ugarte-Gil, M F; Gamboa-Cárdenas, R V; Zevallos, F; Medina, M; Cucho-Venegas, J M; Perich-Campos, R A; Alfaro-Lozano, J L; Rodriguez-Bellido, Z; Alarcón, G S; Pastor-Asurza, C A

2014-09-01

to determine whether prolactin levels are independently associated with disease damage in systemic lupus erythematosus (SLE) patients. these cross-sectional analyses were conducted in SLE patient members of the Almenara Lupus Cohort who were seen between January 2012 and June 2013. Disease damage was ascertained with the System Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) damage index (SDI). Prolactin was measured in ng/ml. The association between prolactin levels and the SDI (total and its domains) was evaluated using Spearman's correlation. Subsequently, adjusted Poisson regression models were performed to evaluate these associations. 160 patients were included. 147 (91.9%) were female; their median age at diagnosis was 33.4 (interquartile range (IQR): 26.0-44.3) years; their disease duration was 5.5 (IQR: 2.6-9.7) years. The median prolactin value was 16.8 (IQR: 11.8-24.5) ng/ml. After adjusting for confounders in the Poisson regression model the estimated rate ratios (RR) and 95% confidence interval (CI) for each 10 ng/ml increment of prolactin were 1.13 (95% CI 1.60-1.20, p<0.001) for the total SDI score, 1.15 (1.03-1.28, p=0.003) for the renal domain and 1.41 (1.11-1.79, p=0.003) for the cardiac/peripheral vascular domains. there was a positive association between prolactin levels and the SDI (overall and its renal and cardiac/peripheral vascular domains), independently of other well-known risk factors. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Datamining approaches for modeling tumor control probability.

PubMed

Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D

2010-11-01

Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

Seasonal prediction of the typhoon genesis frequency over the Western North Pacific with a Poisson regression model

NASA Astrophysics Data System (ADS)

Zhang, Xinchang; Zhong, Shanshan; Wu, Zhiwei; Li, Yun

2017-06-01

This study investigates the typhoon genesis frequency (TGF) in the dominant season (July to October) in Western North Pacific (WNP) using observed data in 1965-2015. Of particular interest is the predictability of the TGF and associated preseason sea surface temperature (SST) in the Pacific. It is found that, the TGF is positively related to a tri-polar pattern of April SST anomalies in North Pacific (NP{T}_{Apr}), while it is negatively related to SST anomalies over the Coral Sea (CSS{T}_{Apr}) off east coast of Australia. The NP{T}_{Apr} leads to large anomalous cyclonic circulation over North Pacific. The anomalous southwesterly weakens the northeast trade wind, decreases evaporation, and induces warm water in central tropical North Pacific. As such, the warming effect amplifies the temperature gradient in central tropical North Pacific, which in turn maintains the cyclonic wind anomaly in the west tropical Pacific, which favors the typhoon genesis in WNP. In the South Pacific, the CSS{T}_{Apr} supports the typhoon formation over the WNP by (a) strengthening the cross-equatorial flows and enhancing the Inter-tropical Convergence Zone; (b) weakening southeast and northeast trade wind, and keeping continuous warming in the center of tropical Pacific. The influence of both NP{T}_{Apr} and CSS{T}_{Apr} can persistently affect the zonal wind in the tropical Pacific and induce conditions favorable for the typhoon genesis in the typhoon season. A Poisson regression model using NP{T}_{Apr} and CSS}{T}_{Apr} is developed to predict the TGF and a promising skill is achieved.

Bayesian random-effect model for predicting outcome fraught with heterogeneity--an illustration with episodes of 44 patients with intractable epilepsy.

PubMed

Yen, A M-F; Liou, H-H; Lin, H-L; Chen, T H-H

2006-01-01

The study aimed to develop a predictive model to deal with data fraught with heterogeneity that cannot be explained by sampling variation or measured covariates. The random-effect Poisson regression model was first proposed to deal with over-dispersion for data fraught with heterogeneity after making allowance for measured covariates. Bayesian acyclic graphic model in conjunction with Markov Chain Monte Carlo (MCMC) technique was then applied to estimate the parameters of both relevant covariates and random effect. Predictive distribution was then generated to compare the predicted with the observed for the Bayesian model with and without random effect. Data from repeated measurement of episodes among 44 patients with intractable epilepsy were used as an illustration. The application of Poisson regression without taking heterogeneity into account to epilepsy data yielded a large value of heterogeneity (heterogeneity factor = 17.90, deviance = 1485, degree of freedom (df) = 83). After taking the random effect into account, the value of heterogeneity factor was greatly reduced (heterogeneity factor = 0.52, deviance = 42.5, df = 81). The Pearson chi2 for the comparison between the expected seizure frequencies and the observed ones at two and three months of the model with and without random effect were 34.27 (p = 1.00) and 1799.90 (p < 0.0001), respectively. The Bayesian acyclic model using the MCMC method was demonstrated to have great potential for disease prediction while data show over-dispersion attributed either to correlated property or to subject-to-subject variability.

A comprehensive review of prehospital and in-hospital delay times in acute stroke care.

PubMed

Evenson, K R; Foraker, R E; Morris, D L; Rosamond, W D

2009-06-01

The purpose of this study was to systematically review and summarize prehospital and in-hospital stroke evaluation and treatment delay times. We identified 123 unique peer-reviewed studies published from 1981 to 2007 of prehospital and in-hospital delay time for evaluation and treatment of patients with stroke, transient ischemic attack, or stroke-like symptoms. Based on studies of 65 different population groups, the weighted Poisson regression indicated a 6.0% annual decline (P<0.001) in hours/year for prehospital delay, defined from symptom onset to emergency department arrival. For in-hospital delay, the weighted Poisson regression models indicated no meaningful changes in delay time from emergency department arrival to emergency department evaluation (3.1%, P=0.49 based on 12 population groups). There was a 10.2% annual decline in hours/year from emergency department arrival to neurology evaluation or notification (P=0.23 based on 16 population groups) and a 10.7% annual decline in hours/year for delay time from emergency department arrival to initiation of computed tomography (P=0.11 based on 23 population groups). Only one study reported on times from arrival to computed tomography scan interpretation, two studies on arrival to drug administration, and no studies on arrival to transfer to an in-patient setting, precluding generalizations. Prehospital delay continues to contribute the largest proportion of delay time. The next decade provides opportunities to establish more effective community-based interventions worldwide. It will be crucial to have effective stroke surveillance systems in place to better understand and improve both prehospital and in-hospital delays for acute stroke care.

Potential impact of macroclimatic variability on the epidemiology of giardiasis in three provinces of Cuba, 2010-2012.

PubMed

Escobedo, Angel A; Almirall, Pedro; Rumbaut, Raisa; Rodríguez-Morales, Alfonso J

2015-01-01

Climate change and variability are common phenomena affecting various infectious diseases. Many studies have been performed on vector-borne diseases; however, few studies have addressed such influences on intestinal parasitic diseases (e.g., giardiasis). In this study, using nonlinear Poisson regression models, we assessed the potential associations between macroclimatic variation and giardiasis cases in children and school workers from three provinces of Cuba in the context of large sampling and parasitological assessment. Between 2010 and 2012, 293,019 subjects were assessed, resulting in 6357 positive for Giardia (216.95 cases/10,000 pop.; 95%CI 211.7-222.2). The variation in time for those giardiasis rates ranged from 35.8 to 525.8 cases/10,000 pop. Nonlinear Poisson regression models between the ONI index and the giardiasis incidence indicated a significant association (p<0.01). With lower values of ONI, lower incidence of giardiasis was observed at Havana (pseudo r(2)=0.0576; p<0.001) and Guantánamo (pseudo r(2)=0.0376; p<0.001). Although these results are preliminary and the magnitude of association is not higher, the results were of statistical significance. This result indicates the need to assess in detail in further studies the impact of additional macroclimatic and microclimatic variables on the epidemiology of this still important intestinal parasitic disease, not only in Cuba but also in other countries of the Caribbean and Latin American region. Copyright © 2014 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Reprint of "Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression".

PubMed

Shimaponda-Mataa, Nzooma M; Tembo-Mwase, Enala; Gebreslasie, Michael; Achia, Thomas N O; Mukaratirwa, Samson

2017-11-01

Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role. Copyright © 2017 Elsevier B.V. All rights reserved.

A decline in the prevalence of injecting drug users in Estonia, 2005–2009

PubMed Central

Uusküla, A; Rajaleid, K; Talu, A; Abel-Ollo, K; Des Jarlais, DC

2013-01-01

Aims and setting Descriptions of behavioural epidemics have received little attention compared with infectious disease epidemics in Eastern Europe. Here we report a study aimed at estimating trends in the prevalence of injection drug use between 2005 and 2009 in Estonia. Design and methods The number of injection drug users (IDUs) aged 15–44 each year between 2005 and 2009 was estimated using capture-recapture methodology based on 4 data sources (2 treatment data bases: drug abuse and non-fatal overdose treatment; criminal justice (drug related offences) and mortality (injection drug use related deaths) data). Poisson log-linear regression models were applied to the matched data, with interactions between data sources fitted to replicate the dependencies between the data sources. Linear regression was used to estimate average change over time. Findings there were 24305, 12292, 238, 545 records and 8100, 1655, 155, 545 individual IDUs identified in the four capture sources (Police, drug treatment, overdose, and death registry, accordingly) over the period 2005 – 2009. The estimated prevalence of IDUs among the population aged 15–44 declined from 2.7% (1.8–7.9%) in 2005 to 2.0% (1.4–5.0%) in 2008, and 0.9% (0.7–1.7%) in 2009. Regression analysis indicated an average reduction of over 1700 injectors per year. Conclusion While the capture-recapture method has known limitations, the results are consistent with other data from Estonia. Identifying the drivers of change in the prevalence of injection drug use warrants further research. PMID:23290632

On the Singularity of the Vlasov-Poisson System

DOE Office of Scientific and Technical Information (OSTI.GOV)

and Hong Qin, Jian Zheng

2013-04-26

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker- Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency v approaches zero. However, we show that the colllisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the approaching zero from the positive side.

On the singularity of the Vlasov-Poisson system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Jian; Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08550

2013-09-15

The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker-Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency ν approaches zero. However, we show that the collisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the ν approaches zero from the positive side.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

NASA Astrophysics Data System (ADS)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Effect of non-Poisson samples on turbulence spectra from laser velocimetry

NASA Technical Reports Server (NTRS)

Sree, Dave; Kjelgaard, Scott O.; Sellers, William L., III

1994-01-01

Spectral analysis of laser velocimetry (LV) data plays an important role in characterizing a turbulent flow and in estimating the associated turbulence scales, which can be helpful in validating theoretical and numerical turbulence models. The determination of turbulence scales is critically dependent on the accuracy of the spectral estimates. Spectral estimations from 'individual realization' laser velocimetry data are typically based on the assumption of a Poisson sampling process. What this Note has demonstrated is that the sampling distribution must be considered before spectral estimates are used to infer turbulence scales.

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

On the fractal characterization of Paretian Poisson processes

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Sokolov, Igor M.

2012-06-01

Paretian Poisson processes are Poisson processes which are defined on the positive half-line, have maximal points, and are quantified by power-law intensities. Paretian Poisson processes are elemental in statistical physics, and are the bedrock of a host of power-law statistics ranging from Pareto's law to anomalous diffusion. In this paper we establish evenness-based fractal characterizations of Paretian Poisson processes. Considering an array of socioeconomic evenness-based measures of statistical heterogeneity, we show that: amongst the realm of Poisson processes which are defined on the positive half-line, and have maximal points, Paretian Poisson processes are the unique class of 'fractal processes' exhibiting scale-invariance. The results established in this paper are diametric to previous results asserting that the scale-invariance of Poisson processes-with respect to physical randomness-based measures of statistical heterogeneity-is characterized by exponential Poissonian intensities.

Nambu-Poisson gauge theory

NASA Astrophysics Data System (ADS)

Jurčo, Branislav; Schupp, Peter; Vysoký, Jan

2014-06-01

We generalize noncommutative gauge theory using Nambu-Poisson structures to obtain a new type of gauge theory with higher brackets and gauge fields. The approach is based on covariant coordinates and higher versions of the Seiberg-Witten map. We construct a covariant Nambu-Poisson gauge theory action, give its first order expansion in the Nambu-Poisson tensor and relate it to a Nambu-Poisson matrix model.

RECURRENT STROKE IN THE WARFARIN VERSUS ASPIRIN IN REDUCED EJECTION FRACTION (WARCEF) TRIAL

PubMed Central

Pullicino, Patrick M.; Qian, Min; Sacco, Ralph L.; Freudenberger, Ron; Graham, Susan; Teerlink, John R.; Mann, Douglas; Di Tullio, Marco R.; Ponikowski, Piotr; Lok, Dirk J.; Anker, Stefan D.; Lip, Gregory Y.H.; Estol, Conrado J.; Levin, Bruce; Mohr, J.P.; Thompson, John L. P.; Homma, Shunichi

2014-01-01

Background and Purpose WARCEF randomized 2305 patients in sinus rhythm with ejection fraction (EF) ≤35% to warfarin (INR 2.0–3.5) or aspirin 325 mg. Warfarin reduced the incident ischemic stroke (IIS) hazard rate by 48% over aspirin in a secondary analysis. The IIS rate in heart failure (HF) is too low to warrant routine anticoagulation but epidemiologic studies show that prior stroke increases the stroke risk in HF. We here explore IIS rates in WARCEF patients with and without baseline stroke to look for risk factors for IIS and determine if a subgroup with an IIS rate high enough to give a clinically relevant stroke risk reduction can be identified. Methods We compared potential stroke risk factors between patients with baseline stroke and those without using the exact conditional score test for Poisson variables. We looked for risk factors for IIS, by comparing IIS rates between different risk factors. For EF we tried cutoff points of 10%, 15% and 20%. 15% was used as it was the highest EF that was associated with a significant increase in IIS rate. IIS and EF strata were balanced as to warfarin/aspirin assignment by the stratified randomized design. A multiple Poisson regression examined the simultaneous effects of all risk factors on IIS rate. IIS rates per hundred patient years (/100PY) were calculated in patient groups with significant risk factors. Missing values were assigned the modal value. Results Twenty of 248 (8.1%) patients with baseline stroke and 64 of 2048 (3.1%) without had IIS. IIS rate in patients with baseline stroke (2.37/100PY) was greater than patients without (0.89/100PY)(rate ratio 2.68, p<0.001). Fourteen of 219 (6.4%) patients with ejection fraction (EF)<15% and 70 of 2079 (3.4%) with EF ≥15% had IIS. In the multiple regression analysis stroke at baseline (p<0.001) and EF<15% vs. ≥15% (p=.005) remained significant predictors of IIS. IIS rate was 2.04/100PY in patients with EF<15% and 0.95/100PY in patients with EF ≥15% (p=0.009). IIS rate in patients with baseline stroke and reduced EF was 5.88/100PY with EF<15% decreasing to 2.62/100PY with EF<30%. Conclusions In a WARCEF exploratory analysis, prior stroke and EF<15% were risk factors for IIS. Further research is needed to determine if a clinically relevant stroke risk reduction is obtainable with warfarin in HF patients with prior stroke and reduced EF. PMID:25300706

Pregnancy Intentions and Safer Pregnancy Knowledge Among Female Sex Workers in Port Elizabeth, South Africa.

PubMed

Rao, Amrita; Baral, Stefan; Phaswana-Mafuya, Nancy; Lambert, Andrew; Kose, Zamakayise; Mcingana, Mfezi; Holland, Claire; Ketende, Sosthenes; Schwartz, Sheree

2016-07-01

To assess the association between human immunodeficiency virus (HIV) and pregnancy intentions and safer conception knowledge among female sex workers in Port Elizabeth, South Africa. This cross-sectional study recruited female sex workers in Port Elizabeth using respondent-driven sampling and completed an interviewer-administered questionnaire alongside HIV testing and counseling. In this secondary analysis, robust Poisson regression was used to model prevalence ratios for positive fertility intentions in this cross-sectional study. Knowledge of safer conception methods by HIV status was compared using Fisher exact tests. Overall 391 women were represented in the analyses. More than 50% had a prior HIV diagnosis, and an additional 12% were diagnosed with HIV during the study. Approximately half (n=185) of the women reported future pregnancy intentions. In univariate analysis, a prior HIV diagnosis was negatively associated with pregnancy intentions as compared with HIV-negative women (prevalence ratio 0.68, 95% confidence interval 0.55-0.85). Only parity remained independently associated with future pregnancy intentions in multivariate regression after controlling for HIV status, age, race, relationship status, and years selling sex. Knowledge of safer conception methods such as timed sex without a condom, preexposure prophylaxis, or self-insemination was low and similar between those with and without future pregnancy plans. Pregnancy intentions did not significantly vary according to HIV status. Fertility intentions were high, however, and knowledge of safer conception methods low, suggesting a need to provide female sex workers with advice around options to conceive safely in the context of high HIV prevalence.

Chronic Exposure to Fine Particles and Mortality: An Extended Follow-up of the Harvard Six Cities Study from 1974 to 2009

PubMed Central

Laden, Francine; Dockery, Douglas; Schwartz, Joel

2012-01-01

Background: Epidemiologic studies have reported associations between fine particles (aerodynamic diameter ≤ 2.5 µm; PM2.5) and mortality. However, concerns have been raised regarding the sensitivity of the results to model specifications, lower exposures, and averaging time. Objective: We addressed these issues using 11 additional years of follow-up of the Harvard Six Cities study, incorporating recent lower exposures. Methods: We replicated the previously applied Cox regression, and examined different time lags, the shape of the concentration–response relationship using penalized splines, and changes in the slope of the relation over time. We then conducted Poisson survival analysis with time-varying effects for smoking, sex, and education. Results: Since 2001, average PM2.5 levels, for all six cities, were < 18 µg/m3. Each increase in PM2.5 (10 µg/m3) was associated with an adjusted increased risk of all-cause mortality (PM2.5 average on previous year) of 14% [95% confidence interval (CI): 7, 22], and with 26% (95% CI: 14, 40) and 37% (95% CI: 7, 75) increases in cardiovascular and lung-cancer mortality (PM2.5 average of three previous years), respectively. The concentration–response relationship was linear down to PM2.5 concentrations of 8 µg/m3. Mortality rate ratios for PM2.5 fluctuated over time, but without clear trends despite a substantial drop in the sulfate fraction. Poisson models produced similar results. Conclusions: These results suggest that further public policy efforts that reduce fine particulate matter air pollution are likely to have continuing public health benefits. PMID:22456598

Model-independent constraints on modified gravity from current data and from the Euclid and SKA future surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taddei, Laura; Martinelli, Matteo; Amendola, Luca, E-mail: taddei@thphys.uni-heidelberg.de, E-mail: martinelli@lorentz.leidenuniv.nl, E-mail: amendola@thphys.uni-heidelberg.de

2016-12-01

The aim of this paper is to constrain modified gravity with redshift space distortion observations and supernovae measurements. Compared with a standard ΛCDM analysis, we include three additional free parameters, namely the initial conditions of the matter perturbations, the overall perturbation normalization, and a scale-dependent modified gravity parameter modifying the Poisson equation, in an attempt to perform a more model-independent analysis. First, we constrain the Poisson parameter Y (also called G {sub eff}) by using currently available f σ{sub 8} data and the recent SN catalog JLA. We find that the inclusion of the additional free parameters makes the constraintsmore » significantly weaker than when fixing them to the standard cosmological value. Second, we forecast future constraints on Y by using the predicted growth-rate data for Euclid and SKA missions. Here again we point out the weakening of the constraints when the additional parameters are included. Finally, we adopt as modified gravity Poisson parameter the specific Horndeski form, and use scale-dependent forecasts to build an exclusion plot for the Yukawa potential akin to the ones realized in laboratory experiments, both for the Euclid and the SKA surveys.« less

Long-wavelength Magnetic and Gravity Anomaly Correlations of Africa and Europe

NASA Technical Reports Server (NTRS)

Vonfrese, R. R. B.; Hinze, W. J. (Principal Investigator); Olivier, R.

1984-01-01

Preliminary MAGSAT scalar magnetic anomaly data were compiled for comparison with long-wavelength-pass filtered free-air gravity anomalies and regional heat-flow and tectonic data. To facilitate the correlation analysis at satellite elevations over a spherical-Earth, equivalent point source inversion was used to differentially reduce the magnetic satellite anomalies to the radial pole at 350 km elevation, and to upward continue the first radial derivative of the free-air gravity anomalies. Correlation patterns between these regional geopotential anomaly fields are quantitatively established by moving window linear regression based on Poisson's theorem. Prominent correlations include direct correspondences for the Baltic Shield, where both anomalies are negative, and the central Mediterranean and Zaire Basin where both anomalies are positive. Inverse relationships are generally common over the Precambrian Shield in northwest Africa, the Basins and Shields in southern Africa, and the Alpine Orogenic Belt. Inverse correlations also presist over the North Sea Rifts, the Benue Rift, and more generally over the East African Rifts. The results of this quantitative correlation analysis support the general inverse relationships of gravity and magnetic anomalies observed for North American continental terrain which may be broadly related to magnetic crustal thickness variations.

Long-wavelength magnetic and gravity anomaly correlations on Africa and Europe

NASA Technical Reports Server (NTRS)

Vonfrese, R. R. B.; Olivier, R.; Hinze, W. J.

1985-01-01

Preliminary MAGSAT scalar magnetic anomaly data were compiled for comparison with long-wavelength-pass filtered free-air gravity anomalies and regional heat-flow and tectonic data. To facilitate the correlation analysis at satellite elevations over a spherical-Earth, equivalent point source inversion was used to differentially reduce the magnetic satellite anomalies to the radial pole at 350 km elevation, and to upward continue the first radial derivative of the free-air gravity anomalies. Correlation patterns between these regional geopotential anomaly fields are quantitatively established by moving window linear regression based on Poisson's theorem. Prominent correlations include direct correspondences for the Baltic shield, where both anomalies are negative, and the central Mediterranean and Zaire Basin where both anomalies are positive. Inverse relationships are generally common over the Precambrian Shield in northwest Africa, the Basins and Shields in southern Africa, and the Alpine Orogenic Belt. Inverse correlations also presist over the North Sea Rifts, the Benue Rift, and more generally over the East African Rifts. The results of this quantitative correlation analysis support the general inverse relationships of gravity and magnetic anomalies observed for North American continental terrain which may be broadly related to magnetic crustal thickness variations.

Association between Periodontal Condition and Nutritional Status of Brazilian Adolescents: A Population-based Study.

PubMed

Cavalcanti, Alessandro L; Ramos, Ianny A; Cardoso, Andreia M R; Fernandes, Liege Helena F; Aragão, Amanda S; Santos, Fábio G; Aguiar, Yêska P C; Carvalho, Danielle F; Medeiros, Carla C M; De S C Soares, Renata; Castro, Ricardo D

2016-12-01

Obesity is a serious problem of public health and affects all socio-economic groups, irrespective of age, sex or ethnicity. The aim of this study was to evaluate the association between periodontal condition and nutritional status of adolescents. This was a cross-sectional study using a probability cluster sampling, and the sample was defined by statistical criterion, consisting of 559 students aged 15-19 yr enrolled in public schools of adolescents of Campina Grande, PB, Brazil in 2012. Socioeconomic characteristics were analyzed, as well as self-reported general and oral health, anthropometric data and periodontal condition (CPI and OHI-S). Descriptive and analytical analysis from bivariate and multivariate Poisson regression analysis with 5% significance level was performed. Of the 559 adolescents, 18.6% were overweight and 98.4% had some form of periodontal changes such as: bleeding (34.3%), calculus (38.8%), shallow pocket (22.9%) and deep pocket (2.3%). There was association between presence of periodontal changes with obesity ( P <0.05; CI 95%: 0.99 [0.98 - 0.99]). The association between presence of periodontal changes and obesity status in adolescents was indicated.

Association between Periodontal Condition and Nutritional Status of Brazilian Adolescents: A Population-based Study

PubMed Central

CAVALCANTI, Alessandro L.; RAMOS, Ianny A.; CARDOSO, Andreia M. R.; FERNANDES, Liege Helena F.; ARAGÃO, Amanda S.; SANTOS, Fábio G.; AGUIAR, Yêska P. C.; CARVALHO, Danielle F.; MEDEIROS, Carla C. M.; De S. C. SOARES, Renata; CASTRO, Ricardo D.

2016-01-01

Background: Obesity is a serious problem of public health and affects all socio-economic groups, irrespective of age, sex or ethnicity. The aim of this study was to evaluate the association between periodontal condition and nutritional status of adolescents. Methods: This was a cross-sectional study using a probability cluster sampling, and the sample was defined by statistical criterion, consisting of 559 students aged 15–19 yr enrolled in public schools of adolescents of Campina Grande, PB, Brazil in 2012. Socioeconomic characteristics were analyzed, as well as self-reported general and oral health, anthropometric data and periodontal condition (CPI and OHI-S). Descriptive and analytical analysis from bivariate and multivariate Poisson regression analysis with 5% significance level was performed. Results: Of the 559 adolescents, 18.6% were overweight and 98.4% had some form of periodontal changes such as: bleeding (34.3%), calculus (38.8%), shallow pocket (22.9%) and deep pocket (2.3%). There was association between presence of periodontal changes with obesity (P<0.05; CI 95%: 0.99 [0.98 – 0.99]). Conclusion: The association between presence of periodontal changes and obesity status in adolescents was indicated. PMID:28053924

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Silicosis prevalence and risk factors in semi-precious stone mining in Brazil.

PubMed

Souza, Tamires P; Watte, Guilherme; Gusso, Alaíde M; Souza, Rafaela; Moreira, José da S; Knorst, Marli M

2017-06-01

Underground mining generates large amounts of dust and exposes workers to silica. This study aims to determine the prevalence and predictor factors for the development of silicosis among semi-precious-stone mineworkers in southern Brazil working in a self-administered cooperative. In a cross-sectional study of 348 current workers and retirees, demographic data, medical, and occupational history were collected through an interview performed by a nurse and medical record review. Risk factor associations were studied by Poisson multivariate regression. The overall prevalence of silicosis was 37%, while in current miners it was 28%. Several risk factors for silicosis were identified in the univariate analysis. Inadequate ventilation in the underground galleries combined with dry drilling, duration of silica exposure, and (inversely) education remained significant in the multivariate analysis (P < 0.05). This study is unusual in studying semi-precious stone mineworkers in a self-administered worker cooperative with limited resources. The prevalence of silicosis was very high. A number of recommendations are made-including technical support for worker cooperatives, surveillance of silica exposure and silicosis, exposure reduction measures, and benefits allowing impaired miners to leave the industry. © 2017 Wiley Periodicals, Inc.

Hyperspectral cytometry.

PubMed

Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J

2014-01-01

Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

Heterogeneity of Rotavirus Vaccine Efficacy Among Infants in Developing Countries.

PubMed

Gruber, Joann F; Hille, Darcy A; Liu, G Frank; Kaplan, Susan S; Nelson, Micki; Goveia, Michelle G; Mast, T Christopher

2017-01-01

Rotavirus is the leading cause of severe diarrhea worldwide in young children. Although rotavirus vaccine efficacy is high in developed countries, efficacy is lower in developing countries. Here, we investigated heterogeneity of rotavirus vaccine efficacy by infant characteristics in developing countries. An exploratory, post hoc analysis was conducted using randomized controlled trial data of the pentavalent rotavirus vaccine (RV5) conducted in Africa and Asia (NCT00362648). Infants received either 3 doses of vaccine/placebo and were followed for up to 2 years. Within subgroups, vaccine efficacies and 95% confidence intervals (CIs) against rotavirus gastroenteritis (RVGE) were estimated using Poisson regression. We assessed heterogeneity of efficacy by age at first dose, gender, breastfeeding status and nutrition status. African children receiving the first dose at <8 weeks had lower efficacy (23.7%; 95% CI: -8.2%-46.3%) than those vaccinated at ≥8 weeks (59.1%; 95% CI: 34.0%-74.6%). Marginally statistically significant differences were observed by age at first dose, gender and underweight status in Ghana and gender in Asian countries. Heterogeneity of efficacy was observed for age at first dose in African countries. This was an exploratory analysis; additional studies are needed to validate these results.

Impact of temperature on mortality in Hubei, China: a multi-county time series analysis

NASA Astrophysics Data System (ADS)

Zhang, Yunquan; Yu, Chuanhua; Bao, Junzhe; Li, Xudong

2017-03-01

We examined the impact of extreme temperatures on mortality in 12 counties across Hubei Province, central China, during 2009-2012. Quasi-Poisson generalized linear regression combined with distributed lag non-linear model was first applied to estimate county-specific relationship between temperature and mortality. A multivariable meta-analysis was then used to pool the estimates of county-specific mortality effects of extreme cold temperature (1st percentile) and hot temperature (99th percentile). An inverse J-shaped relationship was observed between temperature and mortality at the provincial level. Heat effect occurred immediately and persisted for 2-3 days, whereas cold effect was 1-2 days delayed and much longer lasting. Higher mortality risks were observed among females, the elderly aged over 75 years, persons dying outside the hospital and those with high education attainment, especially for cold effects. Our data revealed some slight differences in heat- and cold- related mortality effects on urban and rural residents. These findings may have important implications for developing locally-based preventive and intervention strategies to reduce temperature-related mortality, especially for those susceptible subpopulations. Also, urbanization should be considered as a potential influence factor when evaluating temperature-mortality association in future researches.

Predictive models of safety based on audit findings: Part 2: Measurement of model validity.

PubMed

Hsiao, Yu-Lin; Drury, Colin; Wu, Changxu; Paquet, Victor

2013-07-01

Part 1 of this study sequence developed a human factors/ergonomics (HF/E) based classification system (termed HFACS-MA) for safety audit findings and proved its measurement reliability. In Part 2, we used the human error categories of HFACS-MA as predictors of future safety performance. Audit records and monthly safety incident reports from two airlines submitted to their regulatory authority were available for analysis, covering over 6.5 years. Two participants derived consensus results of HF/E errors from the audit reports using HFACS-MA. We adopted Neural Network and Poisson regression methods to establish nonlinear and linear prediction models respectively. These models were tested for the validity of prediction of the safety data, and only Neural Network method resulted in substantially significant predictive ability for each airline. Alternative predictions from counting of audit findings and from time sequence of safety data produced some significant results, but of much smaller magnitude than HFACS-MA. The use of HF/E analysis of audit findings provided proactive predictors of future safety performance in the aviation maintenance field. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Platelet-rich plasma versus autologous blood versus steroid injection in lateral epicondylitis: systematic review and network meta-analysis.

PubMed

Arirachakaran, Alisara; Sukthuayat, Amnat; Sisayanarane, Thaworn; Laoratanavoraphong, Sorawut; Kanchanatawan, Wichan; Kongtharvonskul, Jatupon

2016-06-01

Clinical outcomes between the use of platelet-rich plasma (PRP), autologous blood (AB) and corticosteroid (CS) injection in lateral epicondylitis are still controversial. A systematic review and network meta-analysis of randomized controlled trials was conducted with the aim of comparing relevant clinical outcomes between the use of PRP, AB and CS injection. Medline and Scopus databases were searched from inception to January 2015. A network meta-analysis was performed by applying weight regression for continuous outcomes and a mixed-effect Poisson regression for dichotomous outcomes. Ten of 374 identified studies were eligible. When compared to CS, AB injection showed significantly improved effects with unstandardized mean differences (UMD) in pain visual analog scale (VAS), Disabilities of Arm Shoulder and Hand (DASH), Patient-Related Tennis Elbow Evaluation (PRTEE) score and pressure pain threshold (PPT) of -2.5 (95 % confidence interval, -3.5, -1.5), -25.5 (-33.8, -17.2), -5.3 (-9.1, -1.6) and 9.9 (5.6, 14.2), respectively. PRP injections also showed significantly improved VAS and DASH scores when compared with CS. PRP showed significantly better VAS with UMD when compared to AB injection. AB injection has a higher risk of adverse effects, with a relative risk of 1.78 (1.00, 3.17), when compared to CS. The network meta-analysis suggested no statistically significant difference in multiple active treatment comparisons of VAS, DASH and PRTEE when comparing PRP and AB injections. However, AB injection had improved DASH score and PPT when compared with PRP injection. In terms of adverse effects, AB injection had a higher risk than PRP injection. This network meta-analysis provided additional information that PRP injection can improve pain and lower the risk of complications, whereas AB injection can improve pain, disabilities scores and pressure pain threshold but has a higher risk of complications. Level I evidence.

Probabilistic structural analysis methods for improving Space Shuttle engine reliability

NASA Technical Reports Server (NTRS)

Boyce, L.

1989-01-01

Probabilistic structural analysis methods are particularly useful in the design and analysis of critical structural components and systems that operate in very severe and uncertain environments. These methods have recently found application in space propulsion systems to improve the structural reliability of Space Shuttle Main Engine (SSME) components. A computer program, NESSUS, based on a deterministic finite-element program and a method of probabilistic analysis (fast probability integration) provides probabilistic structural analysis for selected SSME components. While computationally efficient, it considers both correlated and nonnormal random variables as well as an implicit functional relationship between independent and dependent variables. The program is used to determine the response of a nickel-based superalloy SSME turbopump blade. Results include blade tip displacement statistics due to the variability in blade thickness, modulus of elasticity, Poisson's ratio or density. Modulus of elasticity significantly contributed to blade tip variability while Poisson's ratio did not. Thus, a rational method for choosing parameters to be modeled as random is provided.

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.

PubMed

Carrasco-Escobar, Gabriel; Gamboa, Dionicia; Castro, Marcia C; Bangdiwala, Shrikant I; Rodriguez, Hugo; Contreras-Mancilla, Juan; Alava, Freddy; Speybroeck, Niko; Lescano, Andres G; Vinetz, Joseph M; Rosas-Aguirre, Angel; Llanos-Cuentas, Alejandro

2017-08-14

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.

A Three-dimensional Polymer Scaffolding Material Exhibiting a Zero Poisson's Ratio.

PubMed

Soman, Pranav; Fozdar, David Y; Lee, Jin Woo; Phadke, Ameya; Varghese, Shyni; Chen, Shaochen

2012-05-14

Poisson's ratio describes the degree to which a material contracts (expands) transversally when axially strained. A material with a zero Poisson's ratio does not transversally deform in response to an axial strain (stretching). In tissue engineering applications, scaffolding having a zero Poisson's ratio (ZPR) may be more suitable for emulating the behavior of native tissues and accommodating and transmitting forces to the host tissue site during wound healing (or tissue regrowth). For example, scaffolding with a zero Poisson's ratio may be beneficial in the engineering of cartilage, ligament, corneal, and brain tissues, which are known to possess Poisson's ratios of nearly zero. Here, we report a 3D biomaterial constructed from polyethylene glycol (PEG) exhibiting in-plane Poisson's ratios of zero for large values of axial strain. We use digital micro-mirror device projection printing (DMD-PP) to create single- and double-layer scaffolds composed of semi re-entrant pores whose arrangement and deformation mechanisms contribute the zero Poisson's ratio. Strain experiments prove the zero Poisson's behavior of the scaffolds and that the addition of layers does not change the Poisson's ratio. Human mesenchymal stem cells (hMSCs) cultured on biomaterials with zero Poisson's ratio demonstrate the feasibility of utilizing these novel materials for biological applications which require little to no transverse deformations resulting from axial strains. Techniques used in this work allow Poisson's ratio to be both scale-independent and independent of the choice of strut material for strains in the elastic regime, and therefore ZPR behavior can be imparted to a variety of photocurable biomaterial.

From Loss of Memory to Poisson.

ERIC Educational Resources Information Center

Johnson, Bruce R.

1983-01-01

A way of presenting the Poisson process and deriving the Poisson distribution for upper-division courses in probability or mathematical statistics is presented. The main feature of the approach lies in the formulation of Poisson postulates with immediate intuitive appeal. (MNS)

Economic Adversity Transitions From Childhood to Older Adulthood Are Differentially Associated With Later-Life Physical Performance Measures in Men and Women in Middle and High-Income Sites.

PubMed

Hwang, Phoebe W; Dos Santos Gomes, Cristiano; Auais, Mohammad; Braun, Kathryn L; Guralnik, Jack M; Pirkle, Catherine M

2017-10-01

This study examines the relationship between economic adversity transitions from childhood to older adulthood and older adulthood physical performance among 1,998 community-dwelling older adults from five demographically diverse sites from middle and high-income countries. The principal exposure variable was economic adversity transition. No adversity encompassed not experiencing poverty in both childhood and older adulthood, improved described having only experienced poverty in childhood, worsened captured having experienced poverty in older adulthood, and severe is having experienced poverty in both childhood and older adulthood. The short physical performance battery (SPPB) was used for outcome measures. Analyses of the continuous SPPB score used linear regression, while analysis of a binary outcome (SPPB < 8 vs. ≥8) used Poisson regression models with robust error variance, both adjusting for sex, education, and site location. In sex-stratified models, the SPPB < 8 prevalence rate ratio (PRR) was higher for the severe (PRR: 2.80, 95% confidence interval [CI] = [1.70, 4.61]), worsened (PRR: 2.40, 95% CI = [1.41, 4.09]), and improved (PRR: 1.82, 95% CI = [1.11, 3.01]) groups, compared with those with no adversity in childhood or as adults, but only for females. Findings from this study indicate that persistent economic adversity has a negative effect on older adult physical performance, especially among women.

Nonlocal Poisson-Fermi model for ionic solvent.

PubMed

Xie, Dexuan; Liu, Jinn-Liang; Eisenberg, Bob

2016-07-01

We propose a nonlocal Poisson-Fermi model for ionic solvent that includes ion size effects and polarization correlations among water molecules in the calculation of electrostatic potential. It includes the previous Poisson-Fermi models as special cases, and its solution is the convolution of a solution of the corresponding nonlocal Poisson dielectric model with a Yukawa-like kernel function. The Fermi distribution is shown to be a set of optimal ionic concentration functions in the sense of minimizing an electrostatic potential free energy. Numerical results are reported to show the difference between a Poisson-Fermi solution and a corresponding Poisson solution.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

PubMed

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-06-14

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

PubMed Central

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-01-01

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably. PMID:27314369

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.

Low-Dose N,N-Dimethylformamide Exposure and Liver Injuries in a Cohort of Chinese Leather Industry Workers.

PubMed

Qi, Cong; Gu, Yiyang; Sun, Qing; Gu, Hongliang; Xu, Bo; Gu, Qing; Xiao, Jing; Lian, Yulong

2017-05-01

We assessed the risk of liver injuries following low doses of N,N-dimethylformamide (DMF) below threshold limit values (20 mg/m) among leather industry workers and comparison groups. A cohort of 429 workers from a leather factory and 466 non-exposed subjects in China were followed for 4 years. Poisson regression and piece-wise linear regression were used to examine the relationship between DMF and liver injury. Workers exposed to a cumulative dose of DMF were significantly more likely than non-exposed workers to develop liver injury. A nonlinear relationship between DMF and liver injury was observed, and a threshold of the cumulative DMF dose for liver injury was 7.30 (mg/m) year. The findings indicate the importance of taking action to reduce DMF occupational exposure limits for promoting worker health.

Poisson's ratio of fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Christiansson, Henrik; Helsing, Johan

1996-05-01

Poisson's ratio flow diagrams, that is, the Poisson's ratio versus the fiber fraction, are obtained numerically for hexagonal arrays of elastic circular fibers in an elastic matrix. High numerical accuracy is achieved through the use of an interface integral equation method. Questions concerning fixed point theorems and the validity of existing asymptotic relations are investigated and partially resolved. Our findings for the transverse effective Poisson's ratio, together with earlier results for random systems by other authors, make it possible to formulate a general statement for Poisson's ratio flow diagrams: For composites with circular fibers and where the phase Poisson's ratios are equal to 1/3, the system with the lowest stiffness ratio has the highest Poisson's ratio. For other choices of the elastic moduli for the phases, no simple statement can be made.

Statistical analysis of excitation energies in actinide and rare-earth nuclei

NASA Astrophysics Data System (ADS)

Levon, A. I.; Magner, A. G.; Radionov, S. V.

2018-04-01

Statistical analysis of distributions of the collective states in actinide and rare-earth nuclei is performed in terms of the nearest-neighbor spacing distribution (NNSD). Several approximations, such as the linear approach to the level repulsion density and that suggested by Brody to the NNSDs were applied for the analysis. We found an intermediate character of the experimental spectra between the order and the chaos for a number of rare-earth and actinide nuclei. The spectra are closer to the Wigner distribution for energies limited by 3 MeV, and to the Poisson distribution for data including higher excitation energies and higher spins. The latter result is in agreement with the theoretical calculations. These features are confirmed by the cumulative distributions, where the Wigner contribution dominates at smaller spacings while the Poisson one is more important at larger spacings, and our linear approach improves the comparison with experimental data at all desired spacings.

A Liouville Problem for the Stationary Fractional Navier-Stokes-Poisson System

NASA Astrophysics Data System (ADS)

Wang, Y.; Xiao, J.

2017-06-01

This paper deals with a Liouville problem for the stationary fractional Navier-Stokes-Poisson system whose special case k=0 covers the compressible and incompressible time-independent fractional Navier-Stokes systems in R^{N≥2} . An essential difficulty raises from the fractional Laplacian, which is a non-local operator and thus makes the local analysis unsuitable. To overcome the difficulty, we utilize a recently-introduced extension-method in Wang and Xiao (Commun Contemp Math 18(6):1650019, 2016) which develops Caffarelli-Silvestre's technique in Caffarelli and Silvestre (Commun Partial Diff Equ 32:1245-1260, 2007).

Nonlinear Finite Element Analysis of Metals and Metal Matrix Composites: A Local-Global Investigation

DTIC Science & Technology

1992-10-01

and SiC/Al [47] possess good chemical bonding and experience mechanical clamping due to the differences in thermal expansion coefficients between...Coefficient of Thermal 2.70 x 10.6 *F-1 4.09 x 10-6 *C-1 Expansion (ca) Poisson’s Ratio (v) 0.25 0.25 Fiber Diameter (d) 0.0056 in 0.014224 cm...Properties of the matrix (as fabricated) Coefficient of Thermal 5.4 x 10-6 "F1 9.72 x 10-6 "C-1 Expansion (a) Poisson’s Ratio (v) 0.351 0.351 Longitudinal

A Liouville Problem for the Stationary Fractional Navier-Stokes-Poisson System

NASA Astrophysics Data System (ADS)

Wang, Y.; Xiao, J.

2018-06-01

This paper deals with a Liouville problem for the stationary fractional Navier-Stokes-Poisson system whose special case k=0 covers the compressible and incompressible time-independent fractional Navier-Stokes systems in R^{N≥2}. An essential difficulty raises from the fractional Laplacian, which is a non-local operator and thus makes the local analysis unsuitable. To overcome the difficulty, we utilize a recently-introduced extension-method in Wang and Xiao (Commun Contemp Math 18(6):1650019, 2016) which develops Caffarelli-Silvestre's technique in Caffarelli and Silvestre (Commun Partial Diff Equ 32:1245-1260, 2007).

Characterization of Nonhomogeneous Poisson Processes Via Moment Conditions.

DTIC Science & Technology

1986-08-01

Poisson processes play an important role in many fields. The Poisson process is one of the simplest counting processes and is a building block for...place of independent increments. This provides a somewhat different viewpoint for examining Poisson processes . In addition, new characterizations for

Constructions and classifications of projective Poisson varieties.

PubMed

Pym, Brent

2018-01-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Constructions and classifications of projective Poisson varieties

NASA Astrophysics Data System (ADS)

Pym, Brent

2018-03-01

This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

Time distributions of solar energetic particle events: Are SEPEs really random?

NASA Astrophysics Data System (ADS)

Jiggens, P. T. A.; Gabriel, S. B.

2009-10-01

Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.

Hurdle models for multilevel zero-inflated data via h-likelihood.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2010-12-30

Count data often exhibit overdispersion. One type of overdispersion arises when there is an excess of zeros in comparison with the standard Poisson distribution. Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros. Further, data often arise in clustered, longitudinal or multiple-membership settings. The proper analysis needs to reflect the design of a study. Typically random effects are used to account for dependencies in the data. We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures to fit hurdle models, thereby extending h-likelihood to truncated distributions. Two applications of the methodology are presented. Copyright © 2010 John Wiley & Sons, Ltd.

Effect of collisions on photoelectron sheath in a gas

NASA Astrophysics Data System (ADS)

Sodha, Mahendra Singh; Mishra, S. K.

2016-02-01

This paper presents a study of the effect of the collision of electrons with atoms/molecules on the structure of a photoelectron sheath. Considering the half Fermi-Dirac distribution of photo-emitted electrons, an expression for the electron density in the sheath has been derived in terms of the electric potential and the structure of the sheath has been investigated by incorporating Poisson's equation in the analysis. The method of successive approximations has been used to solve Poisson's equation with the solution for the electric potential in the case of vacuum, obtained earlier [Sodha and Mishra, Phys. Plasmas 21, 093704 (2014)], being used as the zeroth order solution for the present analysis. The inclusion of collisions influences the photoelectron sheath structure significantly; a reduction in the sheath width with increasing collisions is obtained.

Monitoring Poisson observations using combined applications of Shewhart and EWMA charts

NASA Astrophysics Data System (ADS)

Abujiya, Mu'azu Ramat

2017-11-01

The Shewhart and exponentially weighted moving average (EWMA) charts for nonconformities are the most widely used procedures of choice for monitoring Poisson observations in modern industries. Individually, the Shewhart EWMA charts are only sensitive to large and small shifts, respectively. To enhance the detection abilities of the two schemes in monitoring all kinds of shifts in Poisson count data, this study examines the performance of combined applications of the Shewhart, and EWMA Poisson control charts. Furthermore, the study proposes modifications based on well-structured statistical data collection technique, ranked set sampling (RSS), to detect shifts in the mean of a Poisson process more quickly. The relative performance of the proposed Shewhart-EWMA Poisson location charts is evaluated in terms of the average run length (ARL), standard deviation of the run length (SDRL), median run length (MRL), average ratio ARL (ARARL), average extra quadratic loss (AEQL) and performance comparison index (PCI). Consequently, all the new Poisson control charts based on RSS method are generally more superior than most of the existing schemes for monitoring Poisson processes. The use of these combined Shewhart-EWMA Poisson charts is illustrated with an example to demonstrate the practical implementation of the design procedure.

Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.

PubMed

de Nijs, Robin

2015-07-21

In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.

[Statistical (Poisson) motor unit number estimation. Methodological aspects and normal results in the extensor digitorum brevis muscle of healthy subjects].

PubMed

Murga Oporto, L; Menéndez-de León, C; Bauzano Poley, E; Núñez-Castaín, M J

Among the differents techniques for motor unit number estimation (MUNE) there is the statistical one (Poisson), in which the activation of motor units is carried out by electrical stimulation and the estimation performed by means of a statistical analysis based on the Poisson s distribution. The study was undertaken in order to realize an approximation to the MUNE Poisson technique showing a coprehensible view of its methodology and also to obtain normal results in the extensor digitorum brevis muscle (EDB) from a healthy population. One hundred fourteen normal volunteers with age ranging from 10 to 88 years were studied using the MUNE software contained in a Viking IV system. The normal subjects were divided into two age groups (10 59 and 60 88 years). The EDB MUNE from all them was 184 49. Both, the MUNE and the amplitude of the compound muscle action potential (CMAP) were significantly lower in the older age group (p< 0.0001), showing the MUNE a better correlation with age than CMAP amplitude ( 0.5002 and 0.4142, respectively p< 0.0001). Statistical MUNE method is an important way for the assessment to the phisiology of the motor unit. The value of MUNE correlates better with the neuromuscular aging process than CMAP amplitude does.

Negative Binomial Process Count and Mixture Modeling.

PubMed

Zhou, Mingyuan; Carin, Lawrence

2015-02-01

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number of data samples. We reveal relationships between various count- and mixture-modeling distributions and construct a Poisson-logarithmic bivariate distribution that connects the NB and Chinese restaurant table distributions. Fundamental properties of the models are developed, and we derive efficient Bayesian inference. It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively. These relationships highlight theoretical, structural, and computational advantages of the NB process. A variety of NB processes, including the beta-geometric, beta-NB, marked-beta-NB, marked-gamma-NB and zero-inflated-NB processes, with distinct sharing mechanisms, are also constructed. These models are applied to topic modeling, with connections made to existing algorithms under Poisson factor analysis. Example results show the importance of inferring both the NB dispersion and probability parameters.

Assessment of Linear Finite-Difference Poisson-Boltzmann Solvers

PubMed Central

Wang, Jun; Luo, Ray

2009-01-01

CPU time and memory usage are two vital issues that any numerical solvers for the Poisson-Boltzmann equation have to face in biomolecular applications. In this study we systematically analyzed the CPU time and memory usage of five commonly used finite-difference solvers with a large and diversified set of biomolecular structures. Our comparative analysis shows that modified incomplete Cholesky conjugate gradient and geometric multigrid are the most efficient in the diversified test set. For the two efficient solvers, our test shows that their CPU times increase approximately linearly with the numbers of grids. Their CPU times also increase almost linearly with the negative logarithm of the convergence criterion at very similar rate. Our comparison further shows that geometric multigrid performs better in the large set of tested biomolecules. However, modified incomplete Cholesky conjugate gradient is superior to geometric multigrid in molecular dynamics simulations of tested molecules. We also investigated other significant components in numerical solutions of the Poisson-Boltzmann equation. It turns out that the time-limiting step is the free boundary condition setup for the linear systems for the selected proteins if the electrostatic focusing is not used. Thus, development of future numerical solvers for the Poisson-Boltzmann equation should balance all aspects of the numerical procedures in realistic biomolecular applications. PMID:20063271

A poisson process model for hip fracture risk.

PubMed

Schechner, Zvi; Luo, Gangming; Kaufman, Jonathan J; Siffert, Robert S

2010-08-01

The primary method for assessing fracture risk in osteoporosis relies primarily on measurement of bone mass. Estimation of fracture risk is most often evaluated using logistic or proportional hazards models. Notwithstanding the success of these models, there is still much uncertainty as to who will or will not suffer a fracture. This has led to a search for other components besides mass that affect bone strength. The purpose of this paper is to introduce a new mechanistic stochastic model that characterizes the risk of hip fracture in an individual. A Poisson process is used to model the occurrence of falls, which are assumed to occur at a rate, lambda. The load induced by a fall is assumed to be a random variable that has a Weibull probability distribution. The combination of falls together with loads leads to a compound Poisson process. By retaining only those occurrences of the compound Poisson process that result in a hip fracture, a thinned Poisson process is defined that itself is a Poisson process. The fall rate is modeled as an affine function of age, and hip strength is modeled as a power law function of bone mineral density (BMD). The risk of hip fracture can then be computed as a function of age and BMD. By extending the analysis to a Bayesian framework, the conditional densities of BMD given a prior fracture and no prior fracture can be computed and shown to be consistent with clinical observations. In addition, the conditional probabilities of fracture given a prior fracture and no prior fracture can also be computed, and also demonstrate results similar to clinical data. The model elucidates the fact that the hip fracture process is inherently random and improvements in hip strength estimation over and above that provided by BMD operate in a highly "noisy" environment and may therefore have little ability to impact clinical practice.

Systematic design of 3D auxetic lattice materials with programmable Poisson's ratio for finite strains

NASA Astrophysics Data System (ADS)

Wang, Fengwen

2018-05-01

This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.

Crash data modeling with a generalized estimator.

PubMed

Ye, Zhirui; Xu, Yueru; Lord, Dominique

2018-08-01

The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Classifying next-generation sequencing data using a zero-inflated Poisson model.

PubMed

Zhou, Yan; Wan, Xiang; Zhang, Baoxue; Tong, Tiejun

2018-04-15

With the development of high-throughput techniques, RNA-sequencing (RNA-seq) is becoming increasingly popular as an alternative for gene expression analysis, such as RNAs profiling and classification. Identifying which type of diseases a new patient belongs to with RNA-seq data has been recognized as a vital problem in medical research. As RNA-seq data are discrete, statistical methods developed for classifying microarray data cannot be readily applied for RNA-seq data classification. Witten proposed a Poisson linear discriminant analysis (PLDA) to classify the RNA-seq data in 2011. Note, however, that the count datasets are frequently characterized by excess zeros in real RNA-seq or microRNA sequence data (i.e. when the sequence depth is not enough or small RNAs with the length of 18-30 nucleotides). Therefore, it is desired to develop a new model to analyze RNA-seq data with an excess of zeros. In this paper, we propose a Zero-Inflated Poisson Logistic Discriminant Analysis (ZIPLDA) for RNA-seq data with an excess of zeros. The new method assumes that the data are from a mixture of two distributions: one is a point mass at zero, and the other follows a Poisson distribution. We then consider a logistic relation between the probability of observing zeros and the mean of the genes and the sequencing depth in the model. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. Two real datasets including a breast cancer RNA-seq dataset and a microRNA-seq dataset are also analyzed, and they coincide with the simulation results that our proposed method outperforms the existing competitors. The software is available at http://www.math.hkbu.edu.hk/∼tongt. xwan@comp.hkbu.edu.hk or tongt@hkbu.edu.hk. Supplementary data are available at Bioinformatics online.

Patient experience of general practice and use of emergency hospital services in England: regression analysis of national cross-sectional time series data.

PubMed

Cowling, Thomas E; Majeed, Azeem; Harris, Matthew J

2018-01-22

The UK Government has introduced several national policies to improve access to primary care. We examined associations between patient experience of general practice and rates of visits to accident and emergency (A&E) departments and emergency hospital admissions in England. The study included 8124 general practices between 2011-2012 and 2013-2014. Outcome measures were annual rates of A&E visits and emergency admissions by general practice population, according to administrative hospital records. Explanatory variables included three patient experience measures from the General Practice Patient Survey: practice-level means of experience of making an appointment, satisfaction with opening hours and overall experience (on 0-100 scales). The main analysis used random-effects Poisson regression for cross-sectional time series. Five sensitivity analyses examined changes in model specification. Mean practice-level rates of A&E visits and emergency admissions increased from 2011-2012 to 2013-2014 (310.3-324.4 and 98.8-102.9 per 1000 patients). Each patient experience measure decreased; for example, mean satisfaction with opening hours was 79.4 in 2011-2012 and 76.6 in 2013-2014. In the adjusted regression analysis, an SD increase in experience of making appointments (equal to 9 points) predicted decreases of 1.8% (95% CI -2.4% to -1.2%) in A&E visit rates and 1.4% (95% CI -1.9% to -0.9%) in admission rates. This equalled 301 174 fewer A&E visits and 74 610 fewer admissions nationally per year. Satisfaction with opening hours and overall experience were not consistently associated with either outcome measure across the main and sensitivity analyses. Associations between patient experience of general practice and use of emergency hospital services were small or inconsistent. In England, realistic short-term improvements in patient experience of general practice may only have modest effects on A&E visits and emergency admissions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study.

PubMed

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-06-19

In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study

PubMed Central

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-01-01

Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386

Incidence and predictors of single drug discontinuation according to the presence of HCV coinfection in HIV patients from the ICONA Foundation Cohort Study.

PubMed

Leone, Sebastiano; Shanyinde, Milensu; Cozzi Lepri, Alessandro; Lampe, Fiona C; Caramello, Pietro; Costantini, Andrea; Giacometti, Andrea; De Luca, Andrea; Cingolani, Antonella; Ceccherini Silberstein, Francesca; Puoti, Massimo; Gori, Andrea; d'Arminio Monforte, Antonella

2018-05-01

To evaluate incidence rates of and predictors for any antiretroviral (ART) drug discontinuation by HCV infection status in a large Italian cohort of HIV infected patients. All patients enrolled in ICONA who started combination antiretroviral therapy (cART) containing abacavir or tenofovir or emtricitabine or lamivudine plus efavirenz or rilpivirine or atazanavir/r or darunavir/r (DRV/r) or lopinavir/r or dolutegravir or elvitegravir or raltegravir were included. Multivariate Poisson regression models were used to determine factors independently associated with single ART drug discontinuation. Inverse probability weighting method to control for potential informative censoring was applied. Data from 10,637 patients were analyzed and 1,030 (9.7%) were HCV-Ab positive. Overall, there were 15,464 ART discontinuations due to any reason in 82,415.9 person-years of follow-up (PYFU) for an incidence rate (IR) of 18.8 (95% confidence interval [95%CI] 18.5-19.1) per 100 PYFU. No difference in IR of ART discontinuation due to any reason between HCV-infected and -uninfected patients was found. In a multivariable Poisson regression model, HCV-infected participants were at higher risk of darunavir/r discontinuation due to any reason (adjusted incidence rate ratio = 1.5, 95%CI 1.01-2.22, p value = 0.045) independently of demographics, HIV-related, ART and life-style factors. Among DRV/r treated patients, we found that HCV-viremic patients had twice the risk of ART discontinuation due to any reason than HCV-aviremic patients. In conclusion, HIV/HCV coinfected patients had a marginal risk increase of DRV/r discontinuation due to any reason compared with those without coinfection.

Severe edentulism is a major risk factor influencing stroke incidence in rural Ecuador (The Atahualpa Project).

PubMed

Del Brutto, Oscar H; Mera, Robertino M; Zambrano, Mauricio; Del Brutto, Victor J

2017-02-01

Background There is no information on stroke incidence in rural areas of Latin America, where living conditions and cardiovascular risk factors are different from urban centers. Aim Using a population-based prospective cohort study design, we aimed to assess risk factors influencing stroke incidence in community-dwelling adults living in rural Ecuador. Methods First-ever strokes occurring from 1 June 2012 to 31 May 2016, in Atahualpa residents aged ≥40 years, were identified from yearly door-to-door surveys and other overlapping sources. Poisson regression models adjusted for demographics, cardiovascular risk factors, edentulism and the length of observation time per subject were used to estimate stroke incidence rate ratio as well as factors influencing such incidence. Results Of 807 stroke-free individuals prospectively enrolled in the Atahualpa Project, follow-up was achieved in 718 (89%), contributing 2,499 years of follow-up (average 3.48 ± 0.95 years). Overall stroke incidence rate was 2.97 per 100 person-years of follow-up (95% CI: 1.73-4.2), which increased to 4.77 (95% CI: 1.61-14.1) when only persons aged ≥57 years were considered. Poisson regression models, adjusted for relevant confounders, showed that high blood pressure (IRR: 5.24; 95% CI: 2.55-7.93) and severe edentulism (IRR: 5.06; 95% CI: 2.28-7.85) were the factors independently increasing stroke incidence. Conclusions Stroke incidence in this rural setting is comparable to that reported from the developed world. Besides age and high blood pressure, severe edentulism is a major factor independently predicting incident strokes. Public awareness of the consequences of poor dental care might reduce stroke incidence in rural settings.

Linked versus unlinked estimates of mortality and length of life by education and marital status: evidence from the first record linkage study in Lithuania.

PubMed

Shkolnikov, Vladimir M; Jasilionis, Domantas; Andreev, Evgeny M; Jdanov, Dmitri A; Stankuniene, Vladislava; Ambrozaitiene, Dalia

2007-04-01

Earlier studies have found large and increasing with time differences in mortality by education and marital status in post-Soviet countries. Their results are based on independent tabulations of population and deaths counts (unlinked data). The present study provides the first census-linked estimates of group-specific mortality and the first comparison between census-linked and unlinked mortality estimates for a post-Soviet country. The study is based on a data set linking 140,000 deaths occurring in 2001-2004 in Lithuania with the population census of 2001. The same socio-demographic information about the deceased is available from both the census and death records. Cross-tabulations and Poisson regressions are used to compare linked and unlinked data. Linked and unlinked estimates of life expectancies and mortality rate ratios are calculated with standard life table techniques and Poisson regressions. For the two socio-demographic variables under study, the values from the death records partly differ from those from the census records. The deviations are especially significant for education, with 72-73%, 66-67%, and 82-84% matching for higher education, secondary education, and lower education, respectively. For marital status, deviations are less frequent. For education and marital status, unlinked estimates tend to overstate mortality in disadvantaged groups and they understate mortality in advantaged groups. The differences in inter-group life expectancy and the mortality rate ratios thus are significantly overestimated in the unlinked data. Socio-demographic differences in mortality previously observed in Lithuania and possibly other post-Soviet countries are overestimated. The growth in inequalities over the 1990s is real but might be overstated. The results of this study confirm the existence of large and widening health inequalities but call for better data.

Suicide Attempts and Completions among Mothers Whose Children Were Taken into Care by Child Protection Services: A Cohort Study Using Linkable Administrative Data.

PubMed

Wall-Wieler, Elizabeth; Roos, Leslie L; Brownell, Marni; Nickel, Nathan; Chateau, Dan; Singal, Deepa

2018-03-01

The objective of this study is to examine suicide attempts and completions among mothers who had a child taken into care by child protection services (CPS). These mothers were compared with their biological sisters who did not have a child taken into care and with mothers who received services from CPS but did not have a child taken into care. A retrospective cohort of mothers whose first child was born in Manitoba, Canada, between April 1, 1992, and March 31, 2015, is used. Rates among discordant biological sisters (1872 families) were compared using fixed-effects Poisson regression models, and mothers involved with CPS (children in care [ n = 1872] and received services [ n = 9590]) were compared using a Poisson regression model. Compared with their biological sisters and mothers who received services, the adjusted incidence rate ratio (aIRR) of death by suicide was greater among mothers whose child was taken into care by CPS (aIRR = 4.46 [95% confidence interval (CI), 1.39-14.33] and ARR = 3.45 [95% CI, 1.61-7.40], respectively). Incidence rates of suicide attempts were higher among mothers with a child taken into care compared with their sisters (aIRR = 2.15; 95% CI, 1.40-3.30) and mothers receiving services (aIRR = 2.82; 95% CI, 2.03-3.92). Mothers who had a child taken into care had significantly higher rates of suicide attempts and completions. When children are taken into care, physician and social workers should inquire about maternal suicidal behaviour and provide appropriate mental health.

Assessment of inappropriate antibiotic prescribing among a large cohort of general dentists in the United States.

PubMed

Durkin, Michael J; Feng, Qianxi; Warren, Kyle; Lockhart, Peter B; Thornhill, Martin H; Munshi, Kiraat D; Henderson, Rochelle R; Hsueh, Kevin; Fraser, Victoria J

2018-05-01

The purpose of this study was to assess dental antibiotic prescribing trends over time, to quantify the number and types of antibiotics dentists prescribe inappropriately, and to estimate the excess health care costs of inappropriate antibiotic prescribing with the use of a large cohort of general dentists in the United States. We used a quasi-Poisson regression model to analyze antibiotic prescriptions trends by general dentists between January 1, 2013, and December 31, 2015, with the use of data from Express Scripts Holding Company, a large pharmacy benefits manager. We evaluated antibiotic duration and appropriateness for general dentists. Appropriateness was evaluated by reviewing the antibiotic prescribed and the duration of the prescription. Overall, the number and rate of antibiotic prescriptions prescribed by general dentists remained stable in our cohort. During the 3-year study period, approximately 14% of antibiotic prescriptions were deemed inappropriate, based on the antibiotic prescribed, antibiotic treatment duration, or both indicators. The quasi-Poisson regression model, which adjusted for number of beneficiaries covered, revealed a small but statistically significant decrease in the monthly rate of inappropriate antibiotic prescriptions by 0.32% (95% confidence interval, 0.14% to 0.50%; P = .001). Overall antibiotic prescribing practices among general dentists in this cohort remained stable over time. The rate of inappropriate antibiotic prescriptions by general dentists decreased slightly over time. From these authors' definition of appropriate antibiotic prescription choice and duration, inappropriate antibiotic prescriptions are common (14% of all antibiotic prescriptions) among general dentists. Further analyses with the use of chart review, administrative data sets, or other approaches are needed to better evaluate antibiotic prescribing practices among dentists. Copyright © 2018 American Dental Association. Published by Elsevier Inc. All rights reserved.

Do school crossing guards make crossing roads safer? A quasi-experimental study of pedestrian-motor vehicle collisions in Toronto, Canada.

PubMed

Rothman, Linda; Perry, Daniel; Buliung, Ron; Macarthur, Colin; To, Teresa; Macpherson, Alison; Larsen, Kristian; Howard, Andrew

2015-07-31

The presence of school crossing guards has been associated with more walking and more pedestrian-motor vehicle collisions (PMVCs) in area-level cross-sectional analyses. The objectives of the study were to (1) Determine the effect on PMVC rates of newly implemented crossing guards in Toronto, Canada (2) Determine where collisions were located in relation to crossing guards throughout the city, and whether they occurred during school travel times. School crossing guards with 50 m buffers were mapped along with police-reported child PMVCs from 2000-2011. (1) A quasi-experimental study identified all age collision counts near newly implemented guards before and after implementation, modeled using repeated measures Poisson regression adjusted for season and built environment variables. (2) A retrospective cohort study of all child PMVCS throughout the city to determine the proportions of child PMVCs which occurred during school travel times and at guard locations. There were 27,827 PMVCs, with 260 PMVCs at the locations of 58 newly implemented guards. Repeated measures adjusted Poisson regression found PMVCs rates remained unchanged at guard locations after implementation (IRR 1.02, 95 % CI 0.74, 1.39). There were 568 guards citywide with 1850 child PMVCs that occurred at guard locations. The majority of child PMVCs occurred outside school travel times (n = 1155, 62 %) and of those that occurred during school travel times, only 95 (13.7 %) were at a guard location. School crossing guards are a simple roadway modification to increase walking to school without apparent detrimental safety effects. Other more permanent interventions are necessary to address the frequency of child PMVCs occurring away from the location of crossing guards, and outside of school travel times.

Changes in alcohol consumption in the 50- to 64-year-old European economically active population during an economic crisis.

PubMed

Bosque-Prous, Marina; Kunst, Anton E; Brugal, M Teresa; Espelt, Albert

2017-08-01

The aim was to compare alcohol drinking patterns in economically active people aged 50-64 years before the last economic crisis (2006) and during the crisis (2013). Cross-sectional study with data from 25 479 economically active people aged 50-64 years resident in 11 European countries who participated in wave 2 or wave 5 of the SHARE project (2006 and 2013). The outcome variables were hazardous drinking, abstention in previous 3 months and the weekly average number of drinks per drinker. The prevalence ratios of hazardous drinking and abstention, comparing the prevalence in 2013 vs. 2006, were estimated with Poisson regression models with robust variance, and the changes in the number of drinks per week with Poisson regression models. The prevalence of hazardous drinking decreased among both men (PR = 0.75; 95%CI = 0.63-0.92) and women (PR = 0.91; 95%CI = 0.72-1.15), although the latter decrease was smaller and not statistically significant. The proportion of abstainers increased among both men (PR = 1.11; 95%CI = 0.99-1.29) and women (PR = 1.18; 95%CI = 1.07-1.30), although the former increase was smaller and not statistically significant. The weekly average number of drinks per drinker decreased in men and women. The decreases in consumption were larger in Italy and Spain. From 2006 to 2013, the amount of alcohol consumed by late working age drinkers decreased in Europe, with more pronounced declines in the countries hardest hit by the economic crisis. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Update on Neonatal Herpes Simplex Epidemiology in the Netherlands: A Health Problem of Increasing Concern?

PubMed

van Oeffelen, Louise; Biekram, Manisha; Poeran, Jashvant; Hukkelhoven, Chantal; Galjaard, Sander; van der Meijden, Wim; Op de Coul, Eline

2018-01-18

This paper provides an update on the incidence of neonatal herpes, guideline adherence by health care professionals (HCP), and trends in genital herpes simplex virus (HSV) infection during pregnancy in the Netherlands. Questionnaires were sent to all hospitals inquiring about numbers and characteristics of neonatal and maternal HSV infections, and guideline adherence between 2012 and 2015. Longitudinal trends were investigated from 1999 onwards using survey data and Perinatal Registry of the Netherlands data (Perined). Trends were smoothed with Poisson regression splines. Risk indicators for neonatal and maternal HSV infections were examined with Poisson regression analyses. Neonatal herpes incidence was 4.8/100,000 live births based on survey data (2012-2015) and 3.4/100,000 based on Perined (2012-2014). Mortality rate was 23% (7/30). Neonatal herpes incidence increased slightly over time as did the prevalence of genital HSV infection among pregnant women. Non-Western ethnicity (RR 1.9, 95%CI 1.5-2.5) and age <20 years (RR 2.3, 95%CI 1.2-4.7) were associated with genital herpes during pregnancy. In Perined, none of the neonatal herpes cases had a mother diagnosed with an active genital herpes infection during pregnancy. Preventive measures to reduce vertical herpes transmission (such as caesarean section) were less commonly reported by HCP in 2012-2015 compared to 2006-2011. Neonatal herpes incidence in the Netherlands slowly increased over the last 15 years. An increased genital HSV prevalence during pregnancy or, to lower extent, the decreased guideline adherence by HCP may be responsible. A rise in asymptomatic maternal HSV shedding is also plausible, emphasizing the challenges in preventing neonatal herpes.

Inequalities in financial risk protection in Bangladesh: an assessment of universal health coverage.

PubMed

Islam, Md Rashedul; Rahman, Md Shafiur; Islam, Zobida; Nurs, Cherri Zhang B; Sultana, Papia; Rahman, Md Mizanur

2017-04-04

Financial risk protection and equity are major components of universal health coverage (UHC), which is defined as ensuring access to health services for all citizens without any undue financial burden. We investigated progress towards UHC financial risk indicators and assessed variability of inequalities in financial risk protection indicators by wealth quintile. We further examined the determinants of different financial hardship indicators related to healthcare costs. A cross-sectional, three-stage probability survey was conducted in Bangladesh, which collected information from 1600 households from August to November 2011. Catastrophic health payments, impoverishment, and distress financing (borrowing or selling assets) were treated as financial hardship indicators in UHC. Poisson regression models were used to identify the determinants of catastrophic payment, impoverishment and distress financing separately. Slope, relative and concentration indices of inequalities were used to assess wealth-based inequalities in financial hardship indicators. The study found that around 9% of households incurred catastrophic payments, 7% faced distress financing, and 6% experienced impoverishing health payments in Bangladesh. Slope index of inequality indicated that the incidence of catastrophic health payment and distress financing among the richest households were 12 and 9 percentage points lower than the poorest households respectively. Multivariable Poisson regression models revealed that all UHC financial hardship indicators were significantly higher among household that had members who received inpatient care or were in the poorest quintile. The presence of a member with chronic illness in a household increased the risk of impoverishment by nearly double. This study identified a greater inequality in UHC financial hardship indicators. Rich households in Bangladesh were facing disproportionately less financial hardship than the poor ones. Households can be protected from financial hardship associated with healthcare costs by implementing risk pooling mechanism, increasing GDP spending on health, and properly monitoring subsidized programs in public health facilities.

Effect of smoke-free legislation on the incidence of sudden circulatory arrest in the Netherlands.

PubMed

de Korte-de Boer, Dianne; Kotz, Daniel; Viechtbauer, Wolfgang; van Haren, Emiel; Grommen, Devina; de Munter, Michelle; Coenen, Harry; Gorgels, Anton P M; van Schayck, Onno C P

2012-07-01

To investigate whether smoke-free legislation in the Netherlands led to a decreased incidence of out-of-hospital sudden circulatory arrest (SCA). Smoke-free legislation was implemented in two phases: a workplace ban in 2004 and an extension of this ban to the hospitality sector on 1 July 2008. Weekly incidence data on SCA were obtained from the ambulance registry of South Limburg, the Netherlands. Three time periods were distinguished: the pre-ban period (1 January 2002-1 January 2004), the first post-ban period (1 January 2004-1 July 2008) and the second post-ban period (1 July 2008-1 May 2010). Trends in absolute SCA incidence were analysed using Poisson regression, adjusted for population size, ambient temperature, air pollution and influenza rates. A total of 2305 SCA cases were observed (mean weekly incidence 5.3±2.3 SD). The adjusted Poisson regression model showed a small but significant increase in SCA incidence during the pre-ban period (+0.20% cases per week, p=0.044). This trend changed significantly after implementation of the first ban (with -0.24% cases per week, p=0.043), translating into a 6.8% (22 cases) reduction in the number of SCA cases after 1 year of smoke-free legislation. No further decrease was seen after the second smoking ban. After introduction of a nationwide workplace smoking ban in 2004, a significant decrease in the incidence of out-of-hospital SCA was seen in South Limburg. Poor enforcement of the 2008 hospitality sector ban may account for the fact that no further decrease in the incidence of SCA was seen at this time.

Blood and body fluid exposure risks among health care workers: results from the Duke Health and Safety Surveillance System.

PubMed

Dement, John M; Epling, Carol; Ostbye, Truls; Pompeii, Lisa A; Hunt, Debra L

2004-12-01

Health care workers (HCWs) are at risk of exposures to human blood and body fluids (BBF). Needlestick injuries and splashes place HCWs at risk for numerous blood-borne infections including human immunodeficiency virus (HIV), hepatitis B (HBV), and hepatitis C (HCV). Utilizing a new comprehensive occupational health surveillance system, the objective of this research was to better define the BBF exposure risk and risk factors among employees of a large tertiary medical center. A population of 24,425 HCWs employed in jobs with potential BBF exposures was followed for BBF exposure events from 1998 to 2002. BBF exposure rates were calculated for strata defined by age, race, gender, occupation, work location, and duration of employment. Poisson regression was used for detailed analyses of risk factors for BBF exposure. The study population reported 2,730 BBF exposures during the study period, resulting in an overall annual rate of 5.5 events/100 FTEs and a rate of 3.9 for percutaneous exposures. Higher rates were observed for males, persons employed less than 4 years, Hispanic employees, and persons less than 45 years of age. Much higher rates were observed for house staff, nurse anesthetists, inpatient nurses, phlebotomists, and surgical/operating room technicians. Poisson regression results strengthened and extended results from stratified analyses. Rates of percutaneous exposures from hollow needles were found to decrease over the study period; however, exposure rates from suture needles appear to be increasing. While continued training efforts need to be directed toward new HCWs, our data also suggest that employees who have been in their job 1-4 years continue to be at higher risk of BBF exposures. This research also points to the need for better safety devices/products and work practices to reduce suture-related injuries.

Exposures to road traffic, noise, and air pollution as risk factors for type 2 diabetes: A feasibility study in Bulgaria

PubMed Central

Dzhambov, Angel M; Dimitrova, Donka D

2016-01-01

Type 2 diabetes mellitus (T2DM) is a growing public health problem in Bulgaria. While individual and lifestyle determinants have been researched; till date there has been no study on environmental risks such as road traffic, noise, and air pollution. As a first step toward designing a large-scale population-based survey, we aimed at exploring the overall associations of prevalent T2DM with exposures to road traffic, noise, and air pollution. A total of 513 residents of Plovdiv city, Bulgaria were recruited. Individual data on self-reported doctor-diagnosed T2DM and confounding factors were linked to objective and self-rated exposure indicators. Logistic and log-link Poisson regressions were conducted. In the fully adjusted logistic models, T2DM was positively associated with exposures to Lden 71-80 dB (odds ratio (OR) = 4.49, 95% confidence interval (CI): 1.38, 14.68), fine particulate matter (PM)2.5 25.0-66.8 μg/m3 (OR = 1.32, 95% CI: 0.28, 6.24), benzo alpha pyrene 6.0-14.02 ng/m3 (OR = 1.76, 95% CI: 0.52, 5.98) and high road traffic (OR = 1.40, 95% CI: 0.48, 4.07). Lden remained a significant risk factor in the: Poisson regression model. Other covariates with consistently high multivariate effects were age, gender, body mass index, family history of T2DM, subjective sleep disturbance, and especially bedroom location. We concluded that residential noise exposure might be associated with elevated risk of prevalent T2DM. The inferences made by this research and the lessons learned from its limitations could guide the designing of a longitudinal epidemiological survey in Bulgaria. PMID:27157686

Age at First Concussion Influences the Number of Subsequent Concussions.

PubMed

Schmidt, Julianne D; Rizzone, Katherine; Hoffman, Nicole L; Weber, Michelle L; Jones, Courtney; Bazarian, Jeff; Broglio, Steven P; McCrea, Michael; McAllister, Thomas W

2018-04-01

Individuals who sustain their first concussion during childhood may be at greater risk of sustaining multiple concussions throughout their lifetime because of a longer window of vulnerability. This article aims to estimate the association between age at first concussion and number of subsequent concussions. A total of 23,582 collegiate athletes from 26 universities and military cadets from three military academies completed a concussion history questionnaire (65% males, age 19.9 ± 1.4 years). Participants self-reported concussions and age at time of each injury. Participants with a history of concussion (n = 3,647, 15.5%) were categorized as having sustained their first concussion during childhood (less than ten years old) or adolescence (≥10 and ≤18 years old). Poisson regression was used to model age group (childhood, adolescence) predicting the number of subsequent concussions (0, 1, 2+). A second Poisson regression was developed to determine whether age at first concussion predicted the number of subsequent concussions. Participants self-reporting their first concussion during childhood had an increased risk of subsequent concussions (rate ratio = 2.19, 95% confidence interval: 1.82, 2.64) compared with participants self-reporting their first concussion during adolescence. For every one-year increase in age at first concussion, we observed a 16% reduction in the risk of subsequent concussion (rate ratio = 0.84, 95% confidence interval: 0.82, 0.86). Individuals self-reporting a concussion at a young age sustained a higher number of concussions before age 18. Concussion prevention, recognition, and reporting strategies are of particular need at the youth level. Copyright © 2018 Elsevier Inc. All rights reserved.

Relationship between Tasks Performed, Personality Traits, and Sleep Bruxism in Brazilian School Children - A Population-Based Cross-Sectional Study

PubMed Central

Serra-Negra, Junia Maria; Paiva, Saul Martins; Abreu, Mauro Henrique; Flores-Mendoza, Carmen Elvira; Pordeus, Isabela Almeida

2013-01-01

Background Tasks can be instruments of stress and may affect the health of children. Sleep bruxism is a multifactorial sleep-related movement disorder that affects children and adults. The aim of the present study was to analyze the association between children’s tasks, personality traits and sleep bruxism. Methods And Findings A cross-sectional, population-based study of 652 randomly selected Brazilian schoolchildren (52% of whom were female), aged from 7 to 10 years was conducted in the city of Belo Horizonte, Brazil. A questionnaire based on criteria proposed by the American Academy of Sleep Medicine (AASM) was completed by parents. In addition, the Neuroticism and Responsibility sub-scales of the Big Five Questionnaire for Children (BFQ-C) were administered to the children. Psychological tests were administered and evaluated by psychologists. The Social Vulnerability Index from the city council database was used to determine the social classification of the families. Chi-square and Poisson regression statistical tests were used with a 95% confidence interval. The majority of families were classified as having low social vulnerability (61.3%), whereas, 38.7% were classified as having high social vulnerability. Regarding extracurricular activities, the majority of girls performed household work (56.4%) and some artistic activity (51.3%) while sporting activities were most common among boys (61%). The results of the Poisson regression model indicated that sleep bruxism was most prevalent in children who scored highly in the Neuroticism sub-scale, and who frequently performed household tasks. Conclusion Children whose personality domain has a high level of Neuroticism and who perform household chores imposed by the family are more vulnerable to sleep bruxism. PMID:24244614

Does more education mean less disability in people with dementia? A large cross-sectional study in Taiwan

PubMed Central

Huang, Shih-Wei; Chi, Wen-Chou; Yen, Chia-Feng; Chang, Kwang-Hwa; Liao, Hua-Fang; Escorpizo, Reuben; Chang, Feng-Hang; Liou, Tsan-Hon

2017-01-01

Background WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) is a feasible tool for assessing functional disability and analysing the risk of institutionalisation among elderly patients with dementia. However, the data for the effect of education on disability status in patients with dementia is lacking. The aim of this large-scale, population-based study was to analyse the effect of education on the disability status of elderly Taiwanese patients with dementia by using WHODAS 2.0. Methods From the Taiwan Data Bank of Persons with Disability, we enrolled 7698 disabled elderly (older than 65 years) patients diagnosed with dementia between July 2012 and January 2014. According to their education status, we categorised these patients with and without formal education (3849 patients each). We controlled for the demographic variables through propensity score matching. The standardised scores of these patients in the six domains of WHODAS 2.0 were evaluated by certified interviewers. Student’s t-test was used for comparing the WHODAS 2.0 scores of patients with dementia in the two aforementioned groups. Poisson regression was applied for analysing the association among all the investigated variables. Results Patients with formal education had low disability status in the domains of getting along and social participation than did patients without formal education. Poisson regression revealed that standardised scores in all domains of WHODAS 2.0—except self-care—were associated with education status. Conclusions This study revealed lower disability status in the WHODAS 2.0 domains of getting along and social participation for patients with dementia with formal education compared with those without formal education. For patients with disability and dementia without formal education, community intervention of social participation should be implemented to maintain better social interaction ability. PMID:28473510

Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model.

PubMed

Wei, Wang; Yuan-Yuan, Jin; Ci, Yan; Ahan, Alayi; Ming-Qin, Cao

2016-10-06

The spatial interplay between socioeconomic factors and tuberculosis (TB) cases contributes to the understanding of regional tuberculosis burdens. Historically, local Poisson Geographically Weighted Regression (GWR) has allowed for the identification of the geographic disparities of TB cases and their relevant socioeconomic determinants, thereby forecasting local regression coefficients for the relations between the incidence of TB and its socioeconomic determinants. Therefore, the aims of this study were to: (1) identify the socioeconomic determinants of geographic disparities of smear positive TB in Xinjiang, China (2) confirm if the incidence of smear positive TB and its associated socioeconomic determinants demonstrate spatial variability (3) compare the performance of two main models: one is Ordinary Least Square Regression (OLS), and the other local GWR model. Reported smear-positive TB cases in Xinjiang were extracted from the TB surveillance system database during 2004-2010. The average number of smear-positive TB cases notified in Xinjiang was collected from 98 districts/counties. The population density (POPden), proportion of minorities (PROmin), number of infectious disease network reporting agencies (NUMagen), proportion of agricultural population (PROagr), and per capita annual gross domestic product (per capita GDP) were gathered from the Xinjiang Statistical Yearbook covering a period from 2004 to 2010. The OLS model and GWR model were then utilized to investigate socioeconomic determinants of smear-positive TB cases. Geoda 1.6.7, and GWR 4.0 software were used for data analysis. Our findings indicate that the relations between the average number of smear-positive TB cases notified in Xinjiang and their socioeconomic determinants (POPden, PROmin, NUMagen, PROagr, and per capita GDP) were significantly spatially non-stationary. This means that in some areas more smear-positive TB cases could be related to higher socioeconomic determinant regression coefficients, but in some areas more smear-positive TB cases were found to do with lower socioeconomic determinant regression coefficients. We also found out that the GWR model could be better exploited to geographically differentiate the relationships between the average number of smear-positive TB cases and their socioeconomic determinants, which could interpret the dataset better (adjusted R 2  = 0.912, AICc = 1107.22) than the OLS model (adjusted R 2  = 0.768, AICc = 1196.74). POPden, PROmin, NUMagen, PROagr, and per capita GDP are socioeconomic determinants of smear-positive TB cases. Comprehending the spatial heterogeneity of POPden, PROmin, NUMagen, PROagr, per capita GDP, and smear-positive TB cases could provide valuable information for TB precaution and control strategies.

Data mining of tree-based models to analyze freeway accident frequency.

PubMed

Chang, Li-Yen; Chen, Wen-Chieh

2005-01-01

Statistical models, such as Poisson or negative binomial regression models, have been employed to analyze vehicle accident frequency for many years. However, these models have their own model assumptions and pre-defined underlying relationship between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimation of accident likelihood. Classification and Regression Tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. This study collected the 2001-2002 accident data of National Freeway 1 in Taiwan. A CART model and a negative binomial regression model were developed to establish the empirical relationship between traffic accidents and highway geometric variables, traffic characteristics, and environmental factors. The CART findings indicated that the average daily traffic volume and precipitation variables were the key determinants for freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies.

A cross-sectional analysis of HIV and hepatitis C clinical trials 2007 to 2010: the relationship between industry sponsorship and randomized study design.

PubMed

Goswami, Neela D; Tsalik, Ephraim L; Naggie, Susanna; Miller, William C; Horton, John R; Pfeiffer, Christopher D; Hicks, Charles B

2014-01-22

The proportion of clinical research sponsored by industry will likely continue to expand as federal funds for academic research decreases, particularly in the fields of HIV/AIDS and hepatitis C (HCV). While HIV and HCV continue to burden the US population, insufficient data exists as to how industry sponsorship affects clinical trials involving these infectious diseases. Debate exists about whether pharmaceutical companies undertake more market-driven research practices to promote therapeutics, or instead conduct more rigorous trials than their non-industry counterparts because of increased resources and scrutiny. The ClinicalTrials.gov registry, which allows investigators to fulfill a federal mandate for public trial registration, provides an opportunity for critical evaluation of study designs for industry-sponsored trials, independent of publication status. As part of a large public policy effort, the Clinical Trials Transformation Initiative (CTTI) recently transformed the ClinicalTrials.gov registry into a searchable dataset to facilitate research on clinical trials themselves. We conducted a cross-sectional analysis of 477 HIV and HCV drug treatment trials, registered with ClinicalTrials.gov from 1 October 2007 to 27 September 2010, to study the relationship of study sponsorship with randomized study design. The likelihood of using randomization given industry (versus non-industry) sponsorship was reported with prevalence ratios (PR). PRs were estimated using crude and stratified tabular analysis and Poisson regression adjusting for presence of a data monitoring committee, enrollment size, study phase, number of study sites, inclusion of foreign study sites, exclusion of persons older than age 65, and disease condition. The crude PR was 1.17 (95% CI 0.94, 1.45). Adjusted Poisson models produced a PR of 1.13 (95% CI 0.82, 1.56). There was a trend toward mild effect measure modification by study phase, but this was not statistically significant. In stratified tabular analysis the adjusted PR was 1.14 (95% CI 0.78, 1.68) among phase 2/3 trials and 1.06 (95% CI 0.50, 2.22) among phase 4 trials. No significant relationship was found between industry sponsorship and use of randomization in trial design in this cross-sectional study. Prospective studies evaluating other aspects of trial design may shed further light on the relationship between industry sponsorship and appropriate trial methodology.

A cross-sectional analysis of HIV and hepatitis C clinical trials 2007 to 2010: the relationship between industry sponsorship and randomized study design

PubMed Central

2014-01-01

Background The proportion of clinical research sponsored by industry will likely continue to expand as federal funds for academic research decreases, particularly in the fields of HIV/AIDS and hepatitis C (HCV). While HIV and HCV continue to burden the US population, insufficient data exists as to how industry sponsorship affects clinical trials involving these infectious diseases. Debate exists about whether pharmaceutical companies undertake more market-driven research practices to promote therapeutics, or instead conduct more rigorous trials than their non-industry counterparts because of increased resources and scrutiny. The ClinicalTrials.gov registry, which allows investigators to fulfill a federal mandate for public trial registration, provides an opportunity for critical evaluation of study designs for industry-sponsored trials, independent of publication status. As part of a large public policy effort, the Clinical Trials Transformation Initiative (CTTI) recently transformed the ClinicalTrials.gov registry into a searchable dataset to facilitate research on clinical trials themselves. Methods We conducted a cross-sectional analysis of 477 HIV and HCV drug treatment trials, registered with ClinicalTrials.gov from 1 October 2007 to 27 September 2010, to study the relationship of study sponsorship with randomized study design. The likelihood of using randomization given industry (versus non-industry) sponsorship was reported with prevalence ratios (PR). PRs were estimated using crude and stratified tabular analysis and Poisson regression adjusting for presence of a data monitoring committee, enrollment size, study phase, number of study sites, inclusion of foreign study sites, exclusion of persons older than age 65, and disease condition. Results The crude PR was 1.17 (95% CI 0.94, 1.45). Adjusted Poisson models produced a PR of 1.13 (95% CI 0.82, 1.56). There was a trend toward mild effect measure modification by study phase, but this was not statistically significant. In stratified tabular analysis the adjusted PR was 1.14 (95% CI 0.78, 1.68) among phase 2/3 trials and 1.06 (95% CI 0.50, 2.22) among phase 4 trials. Conclusions No significant relationship was found between industry sponsorship and use of randomization in trial design in this cross-sectional study. Prospective studies evaluating other aspects of trial design may shed further light on the relationship between industry sponsorship and appropriate trial methodology. PMID:24450313

Unimodularity criteria for Poisson structures on foliated manifolds

NASA Astrophysics Data System (ADS)

Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury

2018-03-01

We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.

surrosurv: An R package for the evaluation of failure time surrogate endpoints in individual patient data meta-analyses of randomized clinical trials.

PubMed

Rotolo, Federico; Paoletti, Xavier; Michiels, Stefan

2018-03-01

Surrogate endpoints are attractive for use in clinical trials instead of well-established endpoints because of practical convenience. To validate a surrogate endpoint, two important measures can be estimated in a meta-analytic context when individual patient data are available: the R indiv 2 or the Kendall's τ at the individual level, and the R trial 2 at the trial level. We aimed at providing an R implementation of classical and well-established as well as more recent statistical methods for surrogacy assessment with failure time endpoints. We also intended incorporating utilities for model checking and visualization and data generating methods described in the literature to date. In the case of failure time endpoints, the classical approach is based on two steps. First, a Kendall's τ is estimated as measure of individual level surrogacy using a copula model. Then, the R trial 2 is computed via a linear regression of the estimated treatment effects; at this second step, the estimation uncertainty can be accounted for via measurement-error model or via weights. In addition to the classical approach, we recently developed an approach based on bivariate auxiliary Poisson models with individual random effects to measure the Kendall's τ and treatment-by-trial interactions to measure the R trial 2 . The most common data simulation models described in the literature are based on: copula models, mixed proportional hazard models, and mixture of half-normal and exponential random variables. The R package surrosurv implements the classical two-step method with Clayton, Plackett, and Hougaard copulas. It also allows to optionally adjusting the second-step linear regression for measurement-error. The mixed Poisson approach is implemented with different reduced models in addition to the full model. We present the package functions for estimating the surrogacy models, for checking their convergence, for performing leave-one-trial-out cross-validation, and for plotting the results. We illustrate their use in practice on individual patient data from a meta-analysis of 4069 patients with advanced gastric cancer from 20 trials of chemotherapy. The surrosurv package provides an R implementation of classical and recent statistical methods for surrogacy assessment of failure time endpoints. Flexible simulation functions are available to generate data according to the methods described in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Brand name and generic proton pump inhibitor prescriptions in the United States: insights from the national ambulatory medical care survey (2006-2010).

PubMed

Gawron, Andrew J; Feinglass, Joseph; Pandolfino, John E; Tan, Bruce K; Bove, Michiel J; Shintani-Smith, Stephanie

2015-01-01

Introduction. Proton pump inhibitors (PPI) are one of the most commonly prescribed medication classes with similar efficacy between brand name and generic PPI formulations. Aims. We determined demographic, clinical, and practice characteristics associated with brand name PPI prescriptions at ambulatory care visits in the United States. Methods. Observational cross sectional analysis using the National Ambulatory Medical Care Survey (NAMCS) of all adult (≥18 yrs of age) ambulatory care visits from 2006 to 2010. PPI prescriptions were identified by using the drug entry code as brand name only or generic available formulations. Descriptive statistics were reported in terms of unweighted patient visits and proportions of encounters with brand name PPI prescriptions. Global chi-square tests were used to compare visits with brand name PPI prescriptions versus generic PPI prescriptions for each measure. Poisson regression was used to determine the incidence rate ratio (IRR) for generic versus brand PPI prescribing. Results. A PPI was prescribed at 269.7 million adult ambulatory visits, based on 9,677 unweighted visits, of which 53% were brand name only prescriptions. In 2006, 76.0% of all PPI prescriptions had a brand name only formulation compared to 31.6% of PPI prescriptions in 2010. Visits by patients aged 25-44 years had the greatest proportion of brand name PPI formulations (57.9%). Academic medical centers and physician-owned practices had the greatest proportion of visits with brand name PPI prescriptions (58.9% and 55.6% of visits with a PPI prescription, resp.). There were no significant differences in terms of median income, patient insurance type, or metropolitan status when comparing the proportion of visits with brand name versus generic PPI prescriptions. Poisson regression results showed that practice ownership type was most strongly associated with the likelihood of receiving a brand name PPI over the entire study period. Compared to HMO visits, patient visits at academic medical centers (IRR 4.2, 95% CI 2.2-8.0), physician-owned practices (IRR 3.9, 95% CI 2.1-7.1), and community health centers (IRR 3.6, 95% CI 1.9-6.6) were all more likely to have brand name PPIs. Conclusion. PPI prescriptions with brand name only formulations are most strongly associated with physician practice type.

[Epidemiological features and risk factors of spontaneous abortion among rural Tibetan women at childbearing age].

PubMed

Fan, Xiaojing; Wang, Weihua; Liu, Ruru; Dang, Shaonong; Kang, Yijun

2014-04-01

To study the current status and risk factors of spontaneous abortion of women with Tibetan ethnicity at reproductive age in rural areas. Pregnant women who lived in Tibet were interviewed on their former reproductive history and being followed on the outcomes of pregnant from 2006 to 2012. Generalized Poisson regression model was used to explore the influencing factors of spontaneous abortion. OR value of the research factors was estimated and its 95% confidence interval counted. There were 1 557 pregnant women under this study, with a total number of 2 687 pregnancies and 2 382 productions. 171 women underwent spontaneous abortion, with a total number of 204 times, 93 women had histories of abortion, with a total number of 101 times. Among all the Tibetan pregnant women, the ratio between spontaneous abortion and pregnant women was 7.6% while the rate of spontaneous abortion was 7.9% . Ratio between the number of women who had experienced spontaneous abortion and the total number of women under survey was 11.0% . Pregnancy appeared the important reason on spontaneous abortion. The risk of having spontaneous abortion would increase among women who had more than 3 pregnancies. Results from Poisson regression analysis revealed that the odds ratio (OR) value before the adjustment was 3.921 (95% CI:2.553-6.021) but after the adjustment, it increased to 4.722 (95% CI:2.834-7.866). The increase of production time could reduce the risk of spontaneous abortion in women of childbearing age. Risks related to spontaneous abortion were associated with the number of pregnancies. Women seemed to have lower risk for spontaneous abortion after 2009, with OR value as 0.419 (95%CI:0.285-0.616) before, compared to aOR value as 0.580 (95%CI:0.380-0.885) after the adjustment Social-demographic characteristics was not found to be particularly associated with the occurrence of spontaneous abortion. Rate of spontaneous abortion among Tibetan women at childbearing age was not particularly high when comparing to those women living in the plain area such as Shanxi. However, in order to further reduce the incidence of spontaneous abortion among Tibetan women, approaches should include the following items:strengthening maternal health care, extending the spacing of pregnancy and reducing the frequency of pregnancy.

Tackle-related injury rates and nature of injuries in South African Youth Week tournament rugby union players (under-13 to under-18): an observational cohort study.

PubMed

Burger, Nicholas; Lambert, Mike I; Viljoen, Wayne; Brown, James C; Readhead, Clint; Hendricks, Sharief

2014-08-12

The tackle situation is most often associated with the high injury rates in rugby union. Tackle injury epidemiology in rugby union has previously been focused on senior cohorts but less is known about younger cohorts. The aim of this study was to report on the nature and rates of tackle-related injuries in South African youth rugby union players representing their provinces at national tournaments. Observational cohort study. Four South African Youth Week tournaments (under-13 Craven Week, under-16 Grant Khomo Week, under-18 Academy Week, under-18 Craven Week). Injury data were collected from 3652 youth rugby union players (population at risk) in 2011 and 2012. Tackle-related injury severity ('time-loss' and 'medical attention'), type and location, injury rate per 1000 h (including 95% CIs). Injury rate ratios (IRR) were calculated and modelled using a Poisson regression. A χ(2) analysis was used to detect linear trends between injuries and increasing match quarters. The 2012 under-13 Craven Week had a significantly greater 'time-loss' injury rate when compared with the 2012 under-18 Academy Week (IRR=4.43; 95% CI 2.13 to 9.21, p<0.05) and under-18 Craven Week (IRR=3.52; 95% CI 1.54 to 8.00, p<0.05). The Poisson regression also revealed a higher probability of 'overall' ('time-loss' and 'medical attention' combined) and 'time-loss' tackle-related injuries occurring at the under-13 Craven Week. The proportion of 'overall' and 'time-loss' injuries increased significantly with each quarter of the match when all four tournaments were combined (p<0.05). There was a difference in the tackle-related injury rate between the under-13 tournament and the two under-18 tournaments, and the tackle-related injury rate was higher in the final quarter of matches. Ongoing injury surveillance is required to better interpret these findings. Injury prevention strategies targeting the tackle may only be effective once the rate and nature of injuries have been accurately determined. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Tackle-related injury rates and nature of injuries in South African Youth Week tournament rugby union players (under-13 to under-18): an observational cohort study

PubMed Central

Burger, Nicholas; Lambert, Mike I; Viljoen, Wayne; Brown, James C; Readhead, Clint; Hendricks, Sharief

2014-01-01

Objectives The tackle situation is most often associated with the high injury rates in rugby union. Tackle injury epidemiology in rugby union has previously been focused on senior cohorts but less is known about younger cohorts. The aim of this study was to report on the nature and rates of tackle-related injuries in South African youth rugby union players representing their provinces at national tournaments. Design Observational cohort study. Setting Four South African Youth Week tournaments (under-13 Craven Week, under-16 Grant Khomo Week, under-18 Academy Week, under-18 Craven Week). Participants Injury data were collected from 3652 youth rugby union players (population at risk) in 2011 and 2012. Outcome measures Tackle-related injury severity (‘time-loss’ and ‘medical attention’), type and location, injury rate per 1000 h (including 95% CIs). Injury rate ratios (IRR) were calculated and modelled using a Poisson regression. A χ2 analysis was used to detect linear trends between injuries and increasing match quarters. Results The 2012 under-13 Craven Week had a significantly greater ‘time-loss’ injury rate when compared with the 2012 under-18 Academy Week (IRR=4.43; 95% CI 2.13 to 9.21, p<0.05) and under-18 Craven Week (IRR=3.52; 95% CI 1.54 to 8.00, p<0.05). The Poisson regression also revealed a higher probability of ‘overall’ (‘time-loss’ and ‘medical attention’ combined) and ‘time-loss’ tackle-related injuries occurring at the under-13 Craven Week. The proportion of ‘overall’ and ‘time-loss’ injuries increased significantly with each quarter of the match when all four tournaments were combined (p<0.05). Conclusions There was a difference in the tackle-related injury rate between the under-13 tournament and the two under-18 tournaments, and the tackle-related injury rate was higher in the final quarter of matches. Ongoing injury surveillance is required to better interpret these findings. Injury prevention strategies targeting the tackle may only be effective once the rate and nature of injuries have been accurately determined. PMID:25116454

Association Between Dabigatran vs Warfarin and Risk of Osteoporotic Fractures Among Patients With Nonvalvular Atrial Fibrillation.

PubMed

Lau, Wallis C Y; Chan, Esther W; Cheung, Ching-Lung; Sing, Chor Wing; Man, Kenneth K C; Lip, Gregory Y H; Siu, Chung-Wah; Lam, Joanne K Y; Lee, Alan C H; Wong, Ian C K

2017-03-21

The risk of osteoporotic fracture with dabigatran use in patients with nonvalvular atrial fibrillation (NVAF) is unknown. To investigate the risk of osteoporotic fracture with dabigatran vs warfarin in patients with NVAF. Retrospective cohort study using a population-wide database managed by the Hong Kong Hospital Authority. Patients newly diagnosed with NVAF from 2010 through 2014 and prescribed dabigatran or warfarin were matched by propensity score at a 1:2 ratio with follow-up until July 31, 2016. Dabigatran or warfarin use during the study period. Risk of osteoporotic hip fracture and vertebral fracture was compared between dabigatran and warfarin users using Poisson regression. The corresponding incidence rate ratio (IRR) and absolute risk difference (ARD) with 95% CIs were calculated. Among 51 496 patients newly diagnosed with NVAF, 8152 new users of dabigatran (n = 3268) and warfarin (n = 4884) were matched by propensity score (50% women; mean [SD] age, 74 [11] years). Osteoporotic fracture developed in 104 (1.3%) patients during follow-up (32 dabigatran users [1.0%]; 72 warfarin users [1.5%]). Results of Poisson regression analysis showed that dabigatran use was associated with a significantly lower risk of osteoporotic fracture compared with warfarin (0.7 vs 1.1 per 100 person-years; ARD per 100 person-years, -0.68 [95% CI, -0.38 to -0.86]; IRR, 0.38 [95% CI, 0.22 to 0.66]). The association with lower risk was statistically significant in patients with a history of falls, fractures, or both (dabigatran vs warfarin, 1.6 vs 3.6 per 100 person-years; ARD per 100 person-years, -3.15 [95% CI, -2.40 to -3.45]; IRR, 0.12 [95% CI, 0.04 to 0.33]), but not in those without a history (0.6 vs 0.7 per 100 person-years; ARD per 100 person-years, -0.04 [95% CI, 0.67 to -0.39]; IRR, 0.95 [95% CI, 0.45 to 1.96]) (P value for interaction, <.001). Among adults with NVAF receiving anticoagulation, the use of dabigatran compared with warfarin was associated with a lower risk of osteoporotic fracture. Additional study, perhaps including randomized clinical trials, may be warranted to further understand the relationship between use of dabigatran vs warfarin and risk of fracture.

Time Trends and Educational Inequalities in Out-of-Hospital Coronary Deaths in Norway 1995-2009: A Cardiovascular Disease in Norway (CVDNOR) Project.

PubMed

Sulo, Enxhela; Nygård, Ottar; Vollset, Stein Emil; Igland, Jannicke; Ebbing, Marta; Østbye, Truls; Jørgensen, Torben; Sulo, Gerhard; Tell, Grethe S

2017-02-20

Recent time trends and educational gradients characterizing out-of-hospital coronary deaths (OHCD) are poorly described. We identified all deaths from coronary heart disease occurring outside the hospital in Norway during 1995 to 2009. Time trends were explored using Poisson regression analysis with year as the independent, continuous variable. Information on the highest achieved education was obtained from The National Education Database and classified as primary (up to 10 years of compulsory education), secondary (high school or vocational school), or tertiary (college/university). Educational gradients in OHCD were explored using Poisson regression, stratified by sex and age (<70 and ≥70 years), and results were expressed as incidence rate ratios (IRRs) and 95%CIs. Of 100 783 coronary heart disease deaths, 58.8% were OHCDs. From 1995 to 2009, age-adjusted OHCD rates declined across all education categories (primary, secondary, and tertiary) in younger men (IRR=0.35; 95%CI 0.32-0.38; IRR=0.38; 95%CI 0.35-0.42; IRR=0.33; 95%CI 0.28-0.40), younger women (IRR=0.47; 95% CI 0.40-0.56; IRR=0.55; 95%CI 0.45-0.67; IRR=0.28; 95% CI 0.16-0.47), older men (IRR=0.20; 95%CI 0.19-0.22; IRR=0.20; 95%CI 0.18-0.22; IRR=0.20; 95%CI 0.17-0.23), and older women (IRR=0.26; 95%CI 0.24-0.28; IRR=0.25; 95%CI 0.23-0.28; IRR=0.28; 95%CI 0.22-0.34). Tertiary education was associated with lower risk of OHCD compared to primary education (IRR=0.37; 95%CI 0.35-0.40 in younger men, IRR=0.26; 95%CI 0.22-0.30 in younger women, IRR=0.52; 95%CI 0.49-0.55 in older men, and IRR=0.61; 95%CI 0.57-0.66 in older women). These gradients did not change over time ( P interaction=0.25). Although OHCD rates declined substantially during 1995 to 2009, they displayed educational gradients that remained constant over time. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data.

PubMed

Rodrigues, Josemar; Cancho, Vicente G; de Castro, Mário; Balakrishnan, N

2012-12-01

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis--latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de São Carlos, São Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de São Carlos, São Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Eruption patterns of the chilean volcanoes Villarrica, Llaima, and Tupungatito

NASA Astrophysics Data System (ADS)

Muñoz, Miguel

1983-09-01

The historical eruption records of three Chilean volcanoes have been subjected to many statistical tests, and none have been found to differ significantly from random, or Poissonian, behaviour. The statistical analysis shows rough conformity with the descriptions determined from the eruption rate functions. It is possible that a constant eruption rate describes the activity of Villarrica; Llaima and Tupungatito present complex eruption rate patterns that appear, however, to have no statistical significance. Questions related to loading and extinction processes and to the existence of shallow secondary magma chambers to which magma is supplied from a deeper system are also addressed. The analysis and the computation of the serial correlation coefficients indicate that the three series may be regarded as stationary renewal processes. None of the test statistics indicates rejection of the Poisson hypothesis at a level less than 5%, but the coefficient of variation for the eruption series at Llaima is significantly different from the value expected for a Poisson process. Also, the estimates of the normalized spectrum of the counting process for the three series suggest a departure from the random model, but the deviations are not found to be significant at the 5% level. Kolmogorov-Smirnov and chi-squared test statistics, applied directly to ascertaining to which probability P the random Poisson model fits the data, indicate that there is significant agreement in the case of Villarrica ( P=0.59) and Tupungatito ( P=0.3). Even though the P-value for Llaima is a marginally significant 0.1 (which is equivalent to rejecting the Poisson model at the 90% confidence level), the series suggests that nonrandom features are possibly present in the eruptive activity of this volcano.

Stationary and non-stationary occurrences of miniature end plate potentials are well described as stationary and non-stationary Poisson processes in the mollusc Navanax inermis.

PubMed

Cappell, M S; Spray, D C; Bennett, M V

1988-06-28

Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.

Spacelab system analysis: The modified free access protocol: An access protocol for communication systems with periodic and Poisson traffic

NASA Technical Reports Server (NTRS)

Ingels, Frank; Owens, John; Daniel, Steven

1989-01-01

The protocol definition and terminal hardware for the modified free access protocol, a communications protocol similar to Ethernet, are developed. A MFA protocol simulator and a CSMA/CD math model are also developed. The protocol is tailored to communication systems where the total traffic may be divided into scheduled traffic and Poisson traffic. The scheduled traffic should occur on a periodic basis but may occur after a given event such as a request for data from a large number of stations. The Poisson traffic will include alarms and other random traffic. The purpose of the protocol is to guarantee that scheduled packets will be delivered without collision. This is required in many control and data collection systems. The protocol uses standard Ethernet hardware and software requiring minimum modifications to an existing system. The modification to the protocol only affects the Ethernet transmission privileges and does not effect the Ethernet receiver.

Weber's law implies neural discharge more regular than a Poisson process.

PubMed

Kang, Jing; Wu, Jianhua; Smerieri, Anteo; Feng, Jianfeng

2010-03-01

Weber's law is one of the basic laws in psychophysics, but the link between this psychophysical behavior and the neuronal response has not yet been established. In this paper, we carried out an analysis on the spike train statistics when Weber's law holds, and found that the efferent spike train of a single neuron is less variable than a Poisson process. For population neurons, Weber's law is satisfied only when the population size is small (< 10 neurons). However, if the population neurons share a weak correlation in their discharges and individual neuronal spike train is more regular than a Poisson process, Weber's law is true without any restriction on the population size. Biased competition attractor network also demonstrates that the coefficient of variation of interspike interval in the winning pool should be less than one for the validity of Weber's law. Our work links Weber's law with neural firing property quantitatively, shedding light on the relation between psychophysical behavior and neuronal responses.

Calculation of the Poisson cumulative distribution function

NASA Technical Reports Server (NTRS)

Bowerman, Paul N.; Nolty, Robert G.; Scheuer, Ernest M.

1990-01-01

A method for calculating the Poisson cdf (cumulative distribution function) is presented. The method avoids computer underflow and overflow during the process. The computer program uses this technique to calculate the Poisson cdf for arbitrary inputs. An algorithm that determines the Poisson parameter required to yield a specified value of the cdf is presented.

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE PAGES

Sanborn, Brett; Song, Bo

2018-06-03

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanborn, Brett; Song, Bo

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less

Crustal structure in Ethiopia and Kenya from receiver function analysis: Implications for rift development in eastern Africa

NASA Astrophysics Data System (ADS)

Dugda, Mulugeta T.; Nyblade, Andrew A.; Julia, Jordi; Langston, Charles A.; Ammon, Charles J.; Simiyu, Silas

2005-01-01

Crustal structure in Kenya and Ethiopia has been investigated using receiver function analysis of broadband seismic data to determine the extent to which the Cenozoic rifting and magmatism has modified the thickness and composition of the Proterozoic crust in which the East African rift system developed. Data for this study come from broadband seismic experiments conducted in Ethiopia between 2000 and 2002 and in Kenya between 2001 and 2002. Two methods have been used to analyze the receiver functions, the H-κ method, and direct stacks of the waveforms, yielding consistent results. Crustal thickness to the east of the Kenya rift varies between 39 and 42 km, and Poisson's ratios for the crust vary between 0.24 and 0.27. To the west of the Kenya rift, Moho depths vary between 37 and 38 km, and Poisson's ratios vary between 0.24 and 0.27. These findings support previous studies showing that crust away from the Kenya rift has not been modified extensively by Cenozoic rifting and magmatism. Beneath the Ethiopian Plateau on either side of the Main Ethiopian Rift, crustal thickness ranges from 33 to 44 km, and Poisson's ratios vary from 0.23 to 0.28. Within the Main Ethiopian Rift, Moho depths vary from 27 to 38 km, and Poisson's ratios range from 0.27 to 0.35. A crustal thickness of 25 km and a Poisson's ratio of 0.36 were obtained for a single station in the Afar Depression. These results indicate that the crust beneath the Ethiopian Plateau has not been modified significantly by the Cenozoic rifting and magmatism, even though up to a few kilometers of flood basalts have been added, and that the crust beneath the rifted regions in Ethiopia has been thinned in many places and extensively modified by the addition of mafic rock. The latter finding is consistent with models for rift evolution, suggesting that magmatic segments with the Main Ethiopian Rift, characterized by dike intrusion and Quaternary volcanism, act now as the locus of extension rather than the rift border faults.

A modified Poisson-Boltzmann equation applied to protein adsorption.

PubMed

Gama, Marlon de Souza; Santos, Mirella Simões; Lima, Eduardo Rocha de Almeida; Tavares, Frederico Wanderley; Barreto, Amaro Gomes Barreto

2018-01-05

Ion-exchange chromatography has been widely used as a standard process in purification and analysis of protein, based on the electrostatic interaction between the protein and the stationary phase. Through the years, several approaches are used to improve the thermodynamic description of colloidal particle-surface interaction systems, however there are still a lot of gaps specifically when describing the behavior of protein adsorption. Here, we present an improved methodology for predicting the adsorption equilibrium constant by solving the modified Poisson-Boltzmann (PB) equation in bispherical coordinates. By including dispersion interactions between ions and protein, and between ions and surface, the modified PB equation used can describe the Hofmeister effects. We solve the modified Poisson-Boltzmann equation to calculate the protein-surface potential of mean force, treated as spherical colloid-plate system, as a function of process variables. From the potential of mean force, the Henry constants of adsorption, for different proteins and surfaces, are calculated as a function of pH, salt concentration, salt type, and temperature. The obtained Henry constants are compared with experimental data for several isotherms showing excellent agreement. We have also performed a sensitivity analysis to verify the behavior of different kind of salts and the Hofmeister effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

PubMed

Chatzis, Sotirios P; Andreou, Andreas S

2015-11-01

Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.

A Martingale Characterization of Mixed Poisson Processes.

DTIC Science & Technology

1985-10-01

03LA A 11. TITLE (Inciuae Security Clanafication, ",A martingale characterization of mixed Poisson processes " ________________ 12. PERSONAL AUTHOR... POISSON PROCESSES Jostification .......... . ... . . Di.;t ib,,jtion by Availability Codes Dietmar Pfeifer* Technical University Aachen Dist Special and...Mixed Poisson processes play an important role in many branches of applied probability, for instance in insurance mathematics and physics (see Albrecht

Generation of Non-Homogeneous Poisson Processes by Thinning: Programming Considerations and Comparision with Competing Algorithms.

DTIC Science & Technology

1978-12-01

Poisson processes . The method is valid for Poisson processes with any given intensity function. The basic thinning algorithm is modified to exploit several refinements which reduce computer execution time by approximately one-third. The basic and modified thinning programs are compared with the Poisson decomposition and gap-statistics algorithm, which is easily implemented for Poisson processes with intensity functions of the form exp(a sub 0 + a sub 1t + a sub 2 t-squared. The thinning programs are competitive in both execution