Farmers' Participation in Extension Programs and Technology Adoption in Rural Nepal: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Suvedi, Murari; Ghimire, Raju; Kaplowitz, Michael

2017-01-01

Purpose: This paper examines the factors affecting farmers' participation in extension programs and adoption of improved seed varieties in the hills of rural Nepal. Methodology/approach: Cross-sectional farm-level data were collected during July and August 2014. A sample of 198 farm households was selected for interviewing by using a multistage,…

HIV-Related Risk Behaviors, Perceptions of Risk, HIV Testing, and Exposure to Prevention Messages and Methods among Urban American Indians and Alaska Natives

ERIC Educational Resources Information Center

Lapidus, Jodi A.; Bertolli, Jeanne; McGowan, Karen; Sullivan, Patrick

2006-01-01

The goal of this study was to describe HIV risk behaviors, perceptions, testing, and prevention exposure among urban American Indians and Alaska Natives (AI/AN). Interviewers administered a questionnaire to participants recruited through anonymous peer-referral sampling. Chi-square tests and multiple logistic regression were used to compare HIV…

Individual-Level Predictors of Nonparticipation and Dropout in a Life-Skills HIV Prevention Program for Adolescents in Foster Care

ERIC Educational Resources Information Center

Thompson, Ronald G., Jr.; Auslander, Wendy F.; Alonzo, Dana

2012-01-01

The purpose of this study is to identify individual-level characteristics of foster care adolescents who are more likely to not participate in, and drop out of, a life-skills HIV prevention program delivered over 8 months. Structured interviews were conducted with 320 foster care adolescents (15-18 years). Logistic regression and survival analyses…

Cancer prevalence and education by cancer site: logistic regression analysis.

PubMed

Johnson, Stephanie; Corsten, Martin J; McDonald, James T; Gupta, Michael

2010-10-01

Previously, using the American National Health Interview Survey (NHIS) and a logistic regression analysis, we found that upper aerodigestive tract (UADT) cancer is correlated with low socioeconomic status (SES). The objective of this study was to determine if this correlation between low SES and cancer prevalence exists for other cancers. We again used the NHIS and employed education level as our main measure of SES. We controlled for potentially confounding factors, including smoking status and alcohol consumption. We found that only two cancer subsites shared the pattern of increased prevalence with low education level and decreased prevalence with high education level: UADT cancer and cervical cancer. UADT cancer and cervical cancer were the only two cancers identified that had a link between prevalence and lower education level. This raises the possibility that an associated risk factor for the two cancers is causing the relationship between lower education level and prevalence.

[A cross-sectional survey on personality disorder in mental disorder outpatients in Shanghai].

PubMed

Zhang, Tian-Hong; Xiao, Ze-Ping; Wang, Lan-Lan; Dai, Yun-Fei; Zhang, Hai-Yin; Qiu, Jian-Yin; Tao, Ming-Yi; Wang, Zhen; Wang, Xiao; Yu, Jun-Han; Wu, Yan-Ru; Jiang, Wen-Hui

2010-08-01

To study the prevalence and risk factors for personality disorder (PD) outpatients attending in for psychiatric and psychological counseling in Shanghai. 3075 subjects were sampled by systematic sampling method from outpatients in psycho-counseling clinics and psychiatric clinics in Shanghai Mental Health Center. Based on DSM-IV criteria, personality disorders were assessed by both questionnaires (personality diagnostic questionnaire, PDQ-4+) and interviews (structured clinical interview for DSM-IV Axis II, SCID-II). Logistic regression analysis was performed to determine the significant independent contributor to PD. 71.3% of the outpatients were found having pathological personality by using questionnaire of self rating PD scale. 982 outpatients (31.9%) met criteria for at least one personality disorder by using structured clinical interview. Younger age (OR = 1.8, 95%CI: 1.5 - 2.1), single or divorced (OR = 1.6, 95%CI: 1.4 - 1.9), psychological counseling outpatients (OR = 1.2, 95%CI: 1.1 - 1.3), mood and outpatients with neurosis disorders (OR = 1.7, 95%CI: 1.4 - 2.0) were more frequently assigned as personality disorders. Data from logistic regression analysis showed that patients of tender age, not nurtured and raised by their parents, with introvert characters were related risk factors of PD. High prevalence rate of PD was found in this sample of Chinese outpatients, especially in those psychological counseling outpatients with mood or neurosis disorders. More attention should be paid to the recognition and intervention of PD in outpatients with mental disorders.

Sources of Interactional Problems in a Survey of Racial/Ethnic Discrimination

PubMed Central

Johnson, Timothy P.; Shariff-Marco, Salma; Willis, Gordon; Cho, Young Ik; Breen, Nancy; Gee, Gilbert C.; Krieger, Nancy; Grant, David; Alegria, Margarita; Mays, Vickie M.; Williams, David R.; Landrine, Hope; Liu, Benmei; Reeve, Bryce B.; Takeuchi, David; Ponce, Ninez A.

2014-01-01

Cross-cultural variability in respondent processing of survey questions may bias results from multiethnic samples. We analyzed behavior codes, which identify difficulties in the interactions of respondents and interviewers, from a discrimination module contained within a field test of the 2007 California Health Interview Survey. In all, 553 (English) telephone interviews yielded 13,999 interactions involving 22 items. Multilevel logistic regression modeling revealed that respondent age and several item characteristics (response format, customized questions, length, and first item with new response format), but not race/ethnicity, were associated with interactional problems. These findings suggest that item function within a multi-cultural, albeit English language, survey may be largely influenced by question features, as opposed to respondent characteristics such as race/ethnicity. PMID:26166949

Implementation of Motivational Interviewing in Substance Use Disorder Treatment: Research Network Participation and Organizational Compatibility.

PubMed

Rieckmann, Traci R; Abraham, Amanda J; Bride, Brian E

Despite considerable empirical evidence that psychosocial interventions improve addiction treatment outcomes across populations, implementation remains problematic. A small body of research points to the importance of research network participation as a facilitator of implementation; however, studies examined limited numbers of evidence-based practices. To address this gap, the present study examined factors impacting implementation of motivational interviewing (MI). This study used data from a national sample of privately funded treatment programs (n = 345) and programs participating in the National Drug Abuse Treatment Clinical Trials Network (CTN) (n = 156). Data were collected via face-to-face interviews with program administrators and clinical directors (2007-2009). Analysis included bivariate t tests and chi-square tests to compare private and CTN programs, and multivariable logistic regression of MI implementation. A majority (68.0%) of treatment programs reported use of MI. Treatment programs participating in the CTN (88.9%) were significantly more likely to report use of MI compared with non-CTN programs (58.5%; P < 0.01). CTN programs (82.1%) also were more likely to use trainers from the Motivational Interviewing Network of Trainers as compared with private programs (56.1%; P < 0.05). Multivariable logistic regression models reveal that CTN-affiliated programs and programs with a psychiatrist on staff were more likely to use MI. Programs that used the Stages of Change Readiness and Treatment Eagerness Scale assessment tool were more likely to use MI, whereas programs placing greater emphasis on confrontational group therapy were less likely to use MI. Findings suggest the critical role of research network participation, access to psychiatrists, and organizational compatibility in adoption and sustained use of MI.

The mental well-being of Central American transmigrant men in Mexico.

PubMed

Altman, Claire E; Gorman, Bridget K; Chávez, Sergio; Ramos, Federico; Fernández, Isaac

2018-04-01

To understand the mental health status of Central American migrant men travelling through Mexico to the U.S., we analysed the association between migration-related circumstances/stressors and psychological disorders. In-person interviews and a psychiatric assessment were conducted in 2010 and 2014 with 360 primarily Honduran transmigrant young adult males. The interviews were conducted at three Casas del Migrante (or migrant safe houses) in the migration-corridor cities of Monterrey, and Guadalupe, Nuevo Leon; and Saltillo, Coahuila. The results indicated high levels of migration-related stressors including abuse and a high prevalence of major depressive episodes (MDEs), alcohol dependency, and alcohol abuse. Nested logistic regression models were used to separately predict MDEs, alcohol dependency, and alcohol abuse, assessing their association with migration experiences and socio-demographic characteristics. Logistic regression models showed that characteristics surrounding migration (experiencing abuse, migration duration, and attempts) are predictive of depression. Alcohol dependency and abuse were both associated with marital status and having family/friends in the intended U.S. destination, while the number of migration attempts also predicted alcohol dependency. The results provide needed information on the association between transit migration through Mexico to the U.S. among unauthorised Central American men and major depressive disorder and alcohol abuse and dependency.

Impact of major depressive disorder, distinct subtypes, and symptom severity on lifestyle in the BiDirect Study.

PubMed

Rahe, Corinna; Khil, Laura; Wellmann, Jürgen; Baune, Bernhard T; Arolt, Volker; Berger, Klaus

2016-11-30

The aim of this study was to examine associations of major depressive disorder (MDD), its distinct subtypes, and symptom severity with the individual lifestyle factors smoking, diet quality, physical activity, and body mass index as well as with a combined lifestyle index measuring the co-occurrence of these lifestyle factors. A sample of 823 patients with MDD and 597 non-depressed controls was examined. The psychiatric assessment was based on a clinical interview including the Mini International Neuropsychiatric Interview and the Hamilton Depression Rating Scale. Each lifestyle factor was scored as either healthy or unhealthy, and the number of unhealthy lifestyle factors was added up in a combined lifestyle index. Cross-sectional analyses were performed using alternating logistic regression and ordinal logistic regression, adjusted for socio-demographic characteristics. After adjustment, MDD was significantly associated with smoking, low physical activity, and overweight. Likewise, MDD was significantly related to the overall lifestyle index. When stratifying for subtypes, all subtypes showed higher odds for an overall unhealthier lifestyle than controls, but the associations with the individual lifestyle factors were partly different. Symptom severity was associated with the lifestyle index in a dose-response manner. In conclusion, patients with MDD represent an important target group for lifestyle interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

What does theory-driven evaluation add to the analysis of self-reported outcomes of diabetes education? A comparative realist evaluation of a participatory patient education approach.

PubMed

Pals, Regitze A S; Olesen, Kasper; Willaing, Ingrid

2016-06-01

To explore the effects of the Next Education (NEED) patient education approach in diabetes education. We tested the use of the NEED approach at eight intervention sites (n=193). Six additional sites served as controls (n=58). Data were collected through questionnaires, interviews and observations. We analysed data using descriptive statistics, logistic regression and systematic text condensation. Results from logistic regression demonstrated better overall assessment of education program experiences and enhanced self-reported improvements in maintaining medications correctly among patients from intervention sites, as compared to control sites. Interviews and observations suggested that improvements in health behavior could be explained by mechanisms related to the education setting, including using person-centeredness and dialogue. However, similar mechanisms were observed at control sites. Observations suggested that the quality of group dynamics, patients' motivation and educators' ability to facilitate participation in education, supported by the NEED approach, contributed to better results at intervention sites. The use of participatory approaches and, in particular, the NEED patient education approach in group-based diabetes education improved self-management skills and health behavior outcomes among individuals with diabetes. The use of dialogue tools in diabetes education is advised for educators. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Methodologic considerations in the design and analysis of nested case-control studies: association between cytokines and postoperative delirium.

PubMed

Ngo, Long H; Inouye, Sharon K; Jones, Richard N; Travison, Thomas G; Libermann, Towia A; Dillon, Simon T; Kuchel, George A; Vasunilashorn, Sarinnapha M; Alsop, David C; Marcantonio, Edward R

2017-06-06

The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy-whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.

Mental illness in metropolitan, urban and rural Georgia populations

PubMed Central

2013-01-01

Background Mental illness represents an important public health problem. Local-level data concerning mental illness in different populations (e.g., socio-demographics and residence – metropolitan/urban/rural) provides the evidence-base for public health authorities to plan, implement and evaluate control programs. This paper describes prevalence and covariates of psychiatric conditions in Georgia populations in three defined geographic areas. Methods Data came from the Georgia population-based random-digit-dialing study investigating unwellness and chronic fatigue syndrome (CFS) in Georgia populations of three defined geographic areas (metropolitan, urban, and rural). Respondents were screened for symptoms of fatigue, sleep, cognition, and pain at household screening interviews, and a randomly selected sample completed detailed individual phone interviews. Based on the detailed phone interviews, we conducted one-day clinical evaluations of 292 detailed interview participants classified as unwell with a probable CFS (i.e. CFS-like; a functional somatic syndrome), 268 classified as other unwell, and 223 well (matched to CFS-like). Clinical evaluation included psychiatric classification by means of the Structured Clinical Interview for DSM (SCID). To derive prevalence estimates we used sample weighting to account for the complexity of the multistage sampling design. We used 2- and 3-way table analyses to examine socio-demographic and urbanicity specific associations and multiple logistic regression to calculate adjusted odds ratios. Results Anxiety and mood disorders were the most common psychiatric conditions. Nineteen percent of participants suffered a current anxiety disorder, 18% a mood disorder and 10% had two or more conditions. There was a significant linear trend in occurrence of anxiety or mood disorders from well to CFS-like. The most common anxiety disorders were post-traumatic stress disorder (PTSD) (6.6%) and generalized anxiety disorder (GAD) (5.8%). Logistic regression showed that lower education and female sex contributed significantly to risk for both PTSD and GAD. In addition, rural/urban residence and Hispanic ethnicity were associated with PTSD. We defined moderate to severe depression as Major Depressive Disorder or a Zung score >60 and logistic regression found lower education to be significantly associated but sex, age and urbanicity were not. Conclusions Overall occurrence of anxiety and mood disorders in Georgia mirrored national findings. However, PTSD and GAD occurred at twice the published national rates (3.6 and 2.7%, respectively). State and local prevalence and associations with education, sex and urbanicity comprise important considerations for developing control programs. The increased prevalence of anxiety and mood disorders in people with a functional somatic syndrome (or CFS-like illness) is important for primary care providers, who should consider additional psychiatric screening or referral of individuals presenting with somatoform symptoms. PMID:23631737

Early warnings for suicide attempt among Chinese rural population.

PubMed

Lyu, Juncheng; Wang, Yingying; Shi, Hong; Zhang, Jie

2018-06-05

This study was to explore the main influencing factors of attempted suicide and establish an early warning model, so as to put forward prevention strategies for attempted suicide. Data came from a large-scale case-control epidemiological survey. A sample of 659 serious suicide attempters was randomly recruited from 13 rural counties in China. Each case was matched by a community control for gender, age, and residence location. Face to face interviews were conducted for all the cases and controls with the same structured questionnaire. Univariate logistic regression was applied to screen the factors and multivariate logistic regression was used to excavate the predictors. There were no statistical differences between suicide attempters and the community controls in gender, age, and residence location. The Cronbach`s coefficients for all the scales used were above 0.675. The multivariate logistic regressions have revealed 12 statistically significant variables predicting attempted suicide, including less education, family history of suicide, poor health, mental problem, aspiration strain, hopelessness, impulsivity, depression, negative life events. On the other hand, social support, coping skills, and healthy community protected the rural residents from suicide attempt. The excavated warning predictors are significant clinical meaning for the clinical psychiatrist. Crisis intervention strategies in rural China should be informed by the findings from this research. Education, social support, healthy community, and strain reduction are all measures to decrease the likelihood of crises. Copyright © 2018. Published by Elsevier B.V.

Linking emotional distress to unhealthy sleep duration: analysis of the 2009 National Health Interview Survey.

PubMed

Seixas, Azizi A; Nunes, Joao V; Airhihenbuwa, Collins O; Williams, Natasha J; Pandi-Perumal, Seithikurippu Ratnas; James, Caryl C; Jean-Louis, Girardin

2015-01-01

The objective of the study was to examine the independent association of emotional distress with unhealthy sleep duration (defined as <7 or >8 hours). Data from the 2009 National Health Interview Survey (NHIS), a cross-sectional household survey, were analyzed to investigate the associations of emotional distress with unhealthy sleep durations, adjusting for sociodemographic factors, health risks, and chronic diseases through hierarchical multiple logistic regression analysis. A total of 27,731 participants (age range 18-85 years) from the NHIS 2009 dataset were interviewed. Unhealthy sleep duration is defined as sleep duration <7 or >8 hours, whereas healthy sleep is defined as sleep duration lasting for 7-8 hours. Emotional distress is based on the Kessler 6 Non-Specific Distress Battery, which assesses the frequency of feeling sad, nervous, restless, hopeless, worthless, and burdened, over a 30-day period. Of the sample, 51.7% were female; 83.1% were white and 16.9% were black. Eleven percent experienced emotional distress and 37.6% reported unhealthy sleep. Adjusted logistic regression analysis revealed that individuals with emotional distress had 55% greater odds of reporting unhealthy sleep (odds ratio [OR] =1.55, 95% confidence interval [CI] =1.42, 1.68, P<0.001). Emotional distress, an important proxy for poor psychological health, was a significant predictor of unhealthy sleep, independent of the influences of several factors including demographic (age, education, sex, race/ethnicity, and family income), health risks (alcohol consumption and smoking status), and chronic diseases/conditions (diabetes, obesity, hypertension, heart disease, cancer, and arthritis).

Self-mutilation and suicide attempts: relationships to bipolar disorder, borderline personality disorder, temperament and character.

PubMed

Joyce, Peter R; Light, Katrina J; Rowe, Sarah L; Cloninger, C Robert; Kennedy, Martin A

2010-03-01

Self-mutilation has traditionally been associated with borderline personality disorder, and seldom examined separately from suicide attempts. Clinical experience suggests that self-mutilation is common in bipolar disorder. A family study was conducted on the molecular genetics of depression and personality, in which the proband had been treated for depression. All probands and parents or siblings were interviewed with a structured interview and completed the Temperament and Character Inventory. Fourteen per cent of subjects interviewed reported a history of self-mutilation, mostly by wrist cutting. Self-mutilation was more common in bipolar I disorder subjects then in any other diagnostic groups. In multiple logistic regression self-mutilation was predicted by mood disorder diagnosis and harm avoidance, but not by borderline personality disorder. Furthermore, the relatives of non-bipolar depressed probands with self-mutilation had higher rates of bipolar I or II disorder and higher rates of self-mutilation. Sixteen per cent of subjects reported suicide attempts and these were most common in those with bipolar I disorder and in those with borderline personality disorder. On multiple logistic regression, however, only mood disorder diagnosis and harm avoidance predicted suicide attempts. Suicide attempts, unlike self-mutilation, were not familial. Self-mutilation and suicide attempts are only partially overlapping behaviours, although both are predicted by mood disorder diagnosis and harm avoidance. Self-mutilation has a particularly strong association with bipolar disorder. Clinicians need to think of bipolar disorder, not borderline personality disorder, when assessing an individual who has a history of self-mutilation.

Linking emotional distress to unhealthy sleep duration: analysis of the 2009 National Health Interview Survey

PubMed Central

Seixas, Azizi A; Nunes, Joao V; Airhihenbuwa, Collins O; Williams, Natasha J; Pandi-Perumal, Seithikurippu Ratnas; James, Caryl C; Jean-Louis, Girardin

2015-01-01

Objective The objective of the study was to examine the independent association of emotional distress with unhealthy sleep duration (defined as <7 or >8 hours). Methods Data from the 2009 National Health Interview Survey (NHIS), a cross-sectional household survey, were analyzed to investigate the associations of emotional distress with unhealthy sleep durations, adjusting for sociodemographic factors, health risks, and chronic diseases through hierarchical multiple logistic regression analysis. Participants A total of 27,731 participants (age range 18–85 years) from the NHIS 2009 dataset were interviewed. Measures Unhealthy sleep duration is defined as sleep duration <7 or >8 hours, whereas healthy sleep is defined as sleep duration lasting for 7–8 hours. Emotional distress is based on the Kessler 6 Non-Specific Distress Battery, which assesses the frequency of feeling sad, nervous, restless, hopeless, worthless, and burdened, over a 30-day period. Results Of the sample, 51.7% were female; 83.1% were white and 16.9% were black. Eleven percent experienced emotional distress and 37.6% reported unhealthy sleep. Adjusted logistic regression analysis revealed that individuals with emotional distress had 55% greater odds of reporting unhealthy sleep (odds ratio [OR] =1.55, 95% confidence interval [CI] =1.42, 1.68, P<0.001). Conclusion Emotional distress, an important proxy for poor psychological health, was a significant predictor of unhealthy sleep, independent of the influences of several factors including demographic (age, education, sex, race/ethnicity, and family income), health risks (alcohol consumption and smoking status), and chronic diseases/conditions (diabetes, obesity, hypertension, heart disease, cancer, and arthritis). PMID:26442563

Husband and Wife Perspectives on Farm Household Decision-making Authority and Evidence on Intra-household Accord in Rural Tanzania.

PubMed

Anderson, C Leigh; Reynolds, Travis W; Gugerty, Mary Kay

2017-02-01

We use OLS and logistic regression to investigate variation in husband and wife perspectives on the division of authority over agriculture-related decisions within households in rural Tanzania. Using original data from husbands and wives (interviewed separately) in 1,851 Tanzanian households, the analysis examines differences in the wife's authority over 13 household and farming decisions. The study finds that the level of decision-making authority allocated to wives by their husbands, and the authority allocated by wives to themselves, both vary significantly across households. In addition to commonly considered assets such as women's age and education, in rural agricultural households women's health and labor activities also appear to matter for perceptions of authority. We also find husbands and wives interviewed separately frequently disagree with each other over who holds authority over key farming, family, and livelihood decisions. Further, the results of OLS and logistic regression suggest that even after controlling for various individual, household, and regional characteristics, husband and wife claims to decision-making authority continue to vary systematically by decision-suggesting that decision characteristics themselves also matter. The absence of spousal agreement over the allocation of authority (i.e., a lack of "intra-household accord") over different farm and household decisions is problematic for interventions seeking to use survey data to develop and inform strategies for reducing gender inequalities or empowering women in rural agricultural households. Findings provide policy and program insights into when studies interviewing only a single spouse or considering only a single decision may inaccurately characterize intra-household decision-making dynamics.

Domains of psychosocial disability and mental disorders.

PubMed

Ro, Eunyoe; Watson, David; Clark, Lee Anna

2018-06-07

This study examined relations between comprehensive domains of psychosocial disability and mental disorders to determine (1) whether differential patterns of associations exist between psychosocial disability dimensions and commonly diagnosed mental disorders and (2) whether these relations differ between self-reported and interviewer-rated psychosocial disability domains. Self-reported and interviewer-rated psychosocial functioning measures and an interviewer-rated diagnostic assessment tool were administered to 181 psychiatric outpatients. Internalizing disorders showed the strongest and most pervasive associations with psychosocial impairment across both self-reported and interviewer-rated measures, followed by thought disorder; externalizing showed the weakest associations. More specifically, logistic regression analyses indicated that lower well-being factor score significantly increased the odds of distress-disorder diagnoses, and poor basic functioning increased the odds of PTSD. Results clearly showed differences in the magnitude of associations between three dimensions of psychosocial-disability and commonly diagnosed disorders, and that these differences were similar regardless of rater type. © 2018 Wiley Periodicals, Inc.

Brief Report: Vocational Outcomes for Young Adults with Autism Spectrum Disorders at Six Months After Virtual Reality Job Interview Training

PubMed Central

Fleming, Michael F.; Wright, Michael A.; Losh, Molly; Boteler Humm, Laura; Olsen, Dale; Bell, Morris D.

2016-01-01

Young adults with high-functioning autism spectrum disorder (ASD) have low employment rates and job interviewing presents a critical barrier to employment for them. Results from a prior randomized controlled efficacy trial suggested virtual reality job interview training (VR-JIT) improved interviewing skills among trainees with ASD, but not controls with ASD. We conducted a brief survey with 23 of 26 participants from this study to evaluate their vocational outcomes at 6-month follow-up with a focus on whether or not they attained a competitive position (employment or competitive volunteering). Logistic regression indicated VR-JIT trainees had greater odds of attaining a competitive position than controls (OR 7.82, p < 0.05). Initial evidence suggests VR-JIT is a promising intervention that enhances vocational outcomes among young adults with high-functioning ASD. PMID:25986176

Brief report: vocational outcomes for young adults with autism spectrum disorders at six months after virtual reality job interview training.

PubMed

Smith, Matthew J; Fleming, Michael F; Wright, Michael A; Losh, Molly; Humm, Laura Boteler; Olsen, Dale; Bell, Morris D

2015-10-01

Young adults with high-functioning autism spectrum disorder (ASD) have low employment rates and job interviewing presents a critical barrier to employment for them. Results from a prior randomized controlled efficacy trial suggested virtual reality job interview training (VR-JIT) improved interviewing skills among trainees with ASD, but not controls with ASD. We conducted a brief survey with 23 of 26 participants from this study to evaluate their vocational outcomes at 6-month follow-up with a focus on whether or not they attained a competitive position (employment or competitive volunteering). Logistic regression indicated VR-JIT trainees had greater odds of attaining a competitive position than controls (OR 7.82, p < 0.05). Initial evidence suggests VR-JIT is a promising intervention that enhances vocational outcomes among young adults with high-functioning ASD.

The effect of high leverage points on the logistic ridge regression estimator having multicollinearity

NASA Astrophysics Data System (ADS)

Ariffin, Syaiba Balqish; Midi, Habshah

2014-06-01

This article is concerned with the performance of logistic ridge regression estimation technique in the presence of multicollinearity and high leverage points. In logistic regression, multicollinearity exists among predictors and in the information matrix. The maximum likelihood estimator suffers a huge setback in the presence of multicollinearity which cause regression estimates to have unduly large standard errors. To remedy this problem, a logistic ridge regression estimator is put forward. It is evident that the logistic ridge regression estimator outperforms the maximum likelihood approach for handling multicollinearity. The effect of high leverage points are then investigated on the performance of the logistic ridge regression estimator through real data set and simulation study. The findings signify that logistic ridge regression estimator fails to provide better parameter estimates in the presence of both high leverage points and multicollinearity.

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Cross-sectional study on risk factors of HIV among female commercial sex workers in Cambodia.

PubMed Central

Ohshige, K.; Morio, S.; Mizushima, S.; Kitamura, K.; Tajima, K.; Ito, A.; Suyama, A.; Usuku, S.; Saphonn, V.; Heng, S.; Hor, L. B.; Tia, P.; Soda, K.

2000-01-01

To describe epidemiological features on HIV prevalence among female commercial sex workers (CSWs), a cross-sectional study on sexual behaviour and serological prevalence was carried out in Cambodia. The CSWs were interviewed on their demographic characters and behaviour and their blood samples were taken for testing on sexually transmitted diseases, including HIV, Chlamydia trachomatis, syphilis, and hepatitis B. Associations between risk factors and HIV seropositivity were analysed. High seroprevalence of HIV and Chlamydia trachomatis IgG antibody (CT-IgG-Ab) was shown among the CSWs (54 and 81.7%, respectively). Univariate logistic regression analyses showed an association between HIV seropositivity and age, duration of prostitution, the number of clients per day and CT-IgG-Ab. Especially, high-titre chlamydial seropositivity showed a strong significant association with HIV prevalence. In multiple logistic regression analyses, CT-IgG-Ab with higher titre was significantly independently related to HIV infection. These suggest that existence of Chlamydia trachomatis is highly related to HIV prevalence. PMID:10722142

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

PubMed

Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

PubMed

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

Impact of different approaches of primary care mental health on the prevalence of mental disorders.

PubMed

Moscovici, Leonardo; de Azevedo-Marques, Joao Mazzoncini; Bolsoni, Lívia Maria; Rodrigues-Junior, Antonio Luiz; Zuardi, Antonio Waldo

2018-05-01

AimTo compare the impact of three different approaches to primary care mental health on the prevalence of mental disorders. Millions of people suffer from mental disorders. As entry point into the health service, primary healthcare plays an important role in providing mental health prevention and treatment. Random sample of households in three different areas of the city of Ribeirão Preto (state of São Paulo, Brazil) were selected, and 20 trained medical students conducted interviews using a mental health screening instrument, the Mini-Screening of Mental Disorders, and a socio-demographic datasheet. Primary care mental health was provided in each area through a specific approach. The influence of the area of residence and the socio-demographic variables on the prevalence of mental disorder was explored and analyzed by univariate binary logistic regression and then by a multiple logistic regression model.FindingsA total of 1545 subjects were interviewed. Comparison between the three areas showed a significantly higher number of people with mental disorders in the area covered by the primary care team that did not have physicians with specific primary care mental health training, even when this association was adjusted for the influence of age, education, and socio-economic status.Our results suggest that residing in areas with family physicians with mental health training is associated with a lower prevalence of mental disorders.

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Assessing the oral health of an ageing population: methods, challenges and predictors of survey participation.

PubMed

Matthews, Debora C; Brillant, Martha G S; Clovis, Joanne B; McNally, Mary E; Filiaggi, Mark J; Kotzer, Robert D; Lawrence, Herenia P

2012-06-01

To examine predictors of participation and to describe the methodological considerations of conducting a two-stage population-based oral health survey. An observational, cross-sectional survey (telephone interview and clinical oral examination) of community-dwelling adults aged 45-64 and ≥65 living in Nova Scotia, Canada was conducted. The survey response rate was 21% for the interview and 13.5% for the examination. A total of 1141 participants completed one or both components of the survey. Both age groups had higher levels of education than the target population; the age 45-64 sample also had a higher proportion of females and lower levels of employment than the target population. Completers (participants who completed interview and examination) were compared with partial completers (who completed only the interview), and stepwise logistic regression was performed to examine predictors of completion. Identified predictors were as follows: not working, post-secondary education and frequent dental visits. Recruitment, communications and logistics present challenges in conducting a province-wide survey. Identification of employment, education and dental visit frequency as predictors of survey participation provide insight into possible non-response bias and suggest potential for underestimation of oral disease prevalence in this and similar surveys. This potential must be considered in analysis and in future recruitment strategies. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

Applying Kaplan-Meier to Item Response Data

ERIC Educational Resources Information Center

McNeish, Daniel

2018-01-01

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

Bias in assessment of health-related quality of life in a hemodialysis population: a comparison of self-administered and interviewer-administered surveys in the HEMO study.

PubMed

Unruh, Mark; Yan, Guofen; Radeva, Milena; Hays, Ron D; Benz, Robert; Athienites, Nicolaos V; Kusek, John; Levey, Andrew S; Meyer, Klemens B

2003-08-01

ABSTRACT. Examined is the relationship of patient-reported health-related quality of life (HRQOL) to the mode of survey administration in the Hemodialysis Study. In addition to self-administered surveys to assess HRQOL, interviewer-administered surveys were made available to include patients with poor vision, decreased manual dexterity, or strong preference. For examining the predictors of participation by self-administration of the survey, multiple logistic regression was performed. For examining the relationship of HRQOL results to mode of survey administration, adjusted differences between the self-administered and interviewer-administered groups were obtained from multiple linear regression models accounting for sociodemographic and case-mix factors. A total of 978 of the first 1000 subjects in the Hemodialysis Study completed the survey by interview (n = 427) or by self-administration (n = 551). The interviewer-administered group was older, was more likely black, had longer duration of ESRD, had a higher prevalence of diabetes, and had more severe comorbidity (all P < 0.01). After adjustment for these differences, patients in the interviewer-administered group had higher scores on scales that measured Role-Physical, Role-Emotional, and Effects of Kidney Disease (all P < 0.001). Dialysis studies that restrict HRQOL measurement to patients who are able to complete surveys without assistance will not accurately represent the health of the overall hemodialysis population. Clinical studies and clinical practices using HRQOL as an outcome should include interviewer administration or risk a selection bias against subjects with older age, minority status, and higher level of comorbidity. Future investigation should include research of survey modalities with a low response burden such as telephone interview, computer-assisted interview, and proxy administration.

Risk of suicide in male prison inmates.

PubMed

Saavedra, Javier; López, Marcelino

2015-01-01

Many studies have demonstrated that the risk of suicide in prison is higher than in the general population. This study has two aims. First, to explore the risk of suicide in men sentenced in Andalusian prisons. And second, to study the sociodemographic, criminal and, especially, psychopathological factors associated with this risk. An assessment was made of 472 sentenced inmates in two Andalusian prisons, and included a sociodemographic interview, the IPDE personality disorders questionnaire, the SCID-I diagnostic interview (DSMIV), and the Plutchick suicide risk questionnaire. The interviewers were experienced clinical psychologists with training in prison environments. Adjusted ORs were calculated using a logistic regression. A risk of committing suicide was detected in 33.5% of the sample. The diagnoses (lifetime prevalence) of affective disorder (adjusted OR 3329), substance dependence disorders (adjusted OR 2733), personality disorders (adjusted OR 3115) and anxiety disorder (adjusted OR 1650), as well as a family psychiatric history (adjusted OR 1650), were the predictors that remained as risk factors after the regression analysis. No socio-demographic risk factor was significant in the regression analysis. The psychopathological variables are essential and the most powerful factors to explain suicide risk in prisons. A correct and systematic diagnosis, and an appropriate treatment by mental health professionals during the imprisonment are essential to prevent the risk of suicide. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Is there a relationship between influenza vaccinations and risk of melanoma? A population-based case-control study.

PubMed

Mastrangelo, G; Rossi, C R; Pfahlberg, A; Marzia, V; Barba, A; Baldo, M; Fadda, E; Milan, G; Kölmel, K F

2000-01-01

The aim of the present case-control study was to ascertain whether, in adults, yearly repeated anti-influenza vaccinations (AIV) enhance protection against cutaneous melanoma (CM), as do repeated febrile infections. Ninety-nine new cases of histologically confirmed CM and 104 healthy controls (matched to cases for sex, age, and skin colour) selected from the general population were examined in order to ascertain their skin type, the number of nevi on both arms, and the intensity of freckles on the face and the arms; in these subjects, a structured questionnaire was used to obtain information on age, sex, education, social class, exposure and susceptibility to sunlight, history of febrile infectious diseases, and vaccinations. The odds ratio (OR) and the 95% confidence interval (CI) were estimated by commonly used methods and by fitting models of logistic regression. The risk of CM was reduced in subjects with a history of febrile (temperature above 38.5 degrees C) infections in the 5 years prior to CM surgery (cases) or interview (controls), but was increased in those with voluntary exposure to sunlight in tropical countries. By holding the above factors constant at logistic regression analysis, it was found that a history of repeated AIV (3-5 times in the last 5 years) halved the risk (OR: 0.43; CI: 0.19-1.00; p < 0.05). With the variable 'nevi on arms' included, the protective influence of repeated AIVs was observed in a similar magnitude. The inverse relationship found between melanoma and influenza vaccinations is unlikely to have depended on a bias, even if based on replies in a questionnaire, because neither the interviewers nor the interviewers were informed in advance of the working hypothesis.

Association Between Socioeconomic Status and Participation in Colonoscopy Screening Program in First Degree Relatives of Colorectal Cancer Patients.

PubMed

Chouhdari, Arezoo; Yavari, Parvin; Pourhoseingholi, Mohammad Amin; Sohrabi, Mohammad-Reza

2016-04-01

Approximately 15% to 25% of colorectal cancer (CRC) cases have positive family history for disease. Colonoscopy screening test is the best way for prevention and early diagnosis. Studies have found that first degree relatives (FDRs) with low socioeconomic status are less likely to participate in colonoscopy screening program. The aim of this study is to determine the association between socioeconomic status and participation in colonoscopy screening program in FDRs. This descriptive cross-sectional, study has been conducted on 200 FDRs who were consulted for undergoing colonoscopy screening program between 2007 and 2013 in research institute for gastroenterology and liver disease of Shahid Beheshti University of Medical Sciences, Tehran, Iran. They were interviewed via phone by a valid questionnaire about socioeconomic status. For data analysis, chi-square, exact fisher and multiple logistic regression were executed by SPSS 19. The results indicated 58.5% participants underwent colonoscopy screening test at least once to the time of the interview. There was not an association between participation in colonoscopy screening program and socioeconomic status to the time of the interview in binomial analysis. But statistical significance between intention to participate and educational and income level were found. We found, in logistic regression analysis, that high educational level (Diploma and University degree in this survey) was a predictor to participate in colonoscopy screening program in FDRs. According to this survey low socioeconomic status is an important factor to hinder participation of FDRs in colonoscopy screening program. Therefore, planned interventions for elevation knowledge and attitude in FDRs with low educational level are necessary. Also, reducing colonoscopy test costs should be a major priority for policy makers.

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

Risk factors for displaced abomasum or ketosis in Swedish dairy herds.

PubMed

Stengärde, L; Hultgren, J; Tråvén, M; Holtenius, K; Emanuelson, U

2012-03-01

Risk factors associated with high or low long-term incidence of displaced abomasum (DA) or clinical ketosis were studied in 60 Swedish dairy herds, using multivariable logistic regression modelling. Forty high-incidence herds were included as cases and 20 low-incidence herds as controls. Incidence rates were calculated based on veterinary records of clinical diagnoses. During the 3-year period preceding the herd classification, herds with a high incidence had a disease incidence of DA or clinical ketosis above the 3rd quartile in a national database for disease recordings. Control herds had no cows with DA or clinical ketosis. All herds were visited during the housing period and herdsmen were interviewed about management routines, housing, feeding, milk yield, and herd health. Target groups were heifers in late gestation, dry cows, and cows in early lactation. Univariable logistic regression was used to screen for factors associated with being a high-incidence herd. A multivariable logistic regression model was built using stepwise regression. A higher maximum daily milk yield in multiparous cows and a large herd size (p=0.054 and p=0.066, respectively) tended to be associated with being a high-incidence herd. Not cleaning the heifer feeding platform daily increased the odds of having a high-incidence herd twelvefold (p<0.01). Keeping cows in only one group in the dry period increased the odds of having a high incidence herd eightfold (p=0.03). Herd size was confounded with housing system. Housing system was therefore added to the final logistic regression model. In conclusion, a large herd size, a high maximum daily milk yield, keeping dry cows in one group, and not cleaning the feeding platform daily appear to be important risk factors for a high incidence of DA or clinical ketosis in Swedish dairy herds. These results confirm the importance of housing, management and feeding in the prevention of metabolic disorders in dairy cows around parturition and in early lactation. Copyright © 2011 Elsevier B.V. All rights reserved.

The role of extended family in diverse teens’ sexual health

PubMed Central

Grossman, Jennifer M.; Tracy, Allison; Richer, Amanda; Erkut, Sumru

2016-01-01

Despite increasing extended family involvement in childrearing, particularly in minority families, few studies investigate their role in talking with teens about sex or how this relates to teens’ sexual behavior. This mixed methods study assesses extended family sexuality communication through a survey of 1492 diverse middle school students and interviews with 32 students. Logistic regression shows that participants who report having had sex are more likely to report talking with extended family than those who report not having had sex. Interview themes explored reasons for and content of teen sexuality conversations with extended family. More sexually active teens’ reporting communication with extended family is interpreted as extended family members gaining importance in sexuality communication as teens become sexually active. PMID:27110060

Strategic Interviewing to Detect Deception: Cues to Deception across Repeated Interviews

PubMed Central

Masip, Jaume; Blandón-Gitlin, Iris; Martínez, Carmen; Herrero, Carmen; Ibabe, Izaskun

2016-01-01

Previous deception research on repeated interviews found that liars are not less consistent than truth tellers, presumably because liars use a “repeat strategy” to be consistent across interviews. The goal of this study was to design an interview procedure to overcome this strategy. Innocent participants (truth tellers) and guilty participants (liars) had to convince an interviewer that they had performed several innocent activities rather than committing a mock crime. The interview focused on the innocent activities (alibi), contained specific central and peripheral questions, and was repeated after 1 week without forewarning. Cognitive load was increased by asking participants to reply quickly. The liars’ answers in replying to both central and peripheral questions were significantly less accurate, less consistent, and more evasive than the truth tellers’ answers. Logistic regression analyses yielded classification rates ranging from around 70% (with consistency as the predictor variable), 85% (with evasive answers as the predictor variable), to over 90% (with an improved measure of consistency that incorporated evasive answers as the predictor variable, as well as with response accuracy as the predictor variable). These classification rates were higher than the interviewers’ accuracy rate (54%). PMID:27847493

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data.

PubMed

Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E

2013-06-01

Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework. © 2013, The International Biometric Society.

Factors Influencing Exclusive Breastfeeding in Tabuk, Saudi Arabia

PubMed Central

Alzaheb, Riyadh A

2017-01-01

Background: Breast milk contains all the nutrients infants need for their first 6 months of life. However, only a minority of Saudi Arabian mothers exclusively breastfeed, so the influencing factors must be examined to encourage more to do so. The study aimed to determine the prevalence of exclusive breastfeeding at 6 months and its associated factors in Tabuk, North West Saudi Arabia. Methods: A total of 589 mothers of healthy infants aged between 6 and 24 months were interviewed while attending Well-Baby Clinics within 5 primary health care centers. Interviews deployed a structured questionnaire to collect sociodemographic information and detailed data concerning breastfeeding practices. A logistic regression analysis was then performed on the data to identify the factors independently associated with exclusive breastfeeding practice for infants at 6 months. Results: Exclusive breastfeeding was practiced by 31.4% of mothers for the first 6 months of their infant’s life. The logistic regressions indicated that exclusive breastfeeding at 6 months was less likely to be practiced by working mothers, Saudi nationals, and for babies born via cesarean delivery or at low birth weights. Conversely, the mother’s awareness of the recommended exclusive breastfeeding duration was positively associated with exclusive breastfeeding. Conclusions: Programs promoting 6 months of exclusive breastfeeding should target high-risk groups. Two factors identified by this study are modifiable: working mothers and mothers’ awareness of the exclusive breastfeeding duration recommendation. Strategies to improve exclusive breastfeeding rates should therefore focus on workplace facilities and increasing awareness of the exclusive breastfeeding recommendation. PMID:28469519

Knowledge of stroke among stroke patients and their relatives in Northwest India.

PubMed

Pandian, Jeyaraj Durai; Kalra, Guneet; Jaison, Ashish; Deepak, Sukhbinder Singh; Shamsher, Shivali; Singh, Yashpal; Abraham, George

2006-06-01

The knowledge of warning symptoms and risk factors for stroke has not been studied among patients with stroke in developing countries. We aimed to assess the knowledge of stroke among patients with stroke and their relatives. Prospective tertiary referral hospital-based study in Northwest India. Trained nurses and medical interns interviewed patients with stroke and transient ischemic attack and their relatives about their knowledge of stroke symptoms and risk factors. Univariable and multivariable logistic regression were used. Of the 147 subjects interviewed, 102 (69%) were patients and 45 (31%) were relatives. There were 99 (67%) men and 48 (33%) women and the mean age was 59.7+/-14.1 years. Sixty-two percent of respondents recognized paralysis of one side as a warning symptom and 54% recognized hypertension as a risk factor for stroke. In the multivariable logistic regression analysis, higher education was associated with the knowledge of correct organ involvement in stroke (OR 2.6, CI 1.1- 6.1, P =0.02), whereas younger age (OR 2.7, CI 1.1-7.0, P =0.04) and higher education (OR 4.1, CI 1.5-10.9, P =0.005) correlated with a better knowledge regarding warning symptoms of stroke. In this study cohort, in general, there is lack of awareness of major warning symptoms, risk factors, organ involvement and self-recognition of stroke. However younger age and education status were associated with better knowledge. There is an urgent need for awareness programs about stroke in this study cohort.

Neighborhood Social Cohesion and Sleep Outcomes in the Native Hawaiian and Pacific Islander National Health Interview Survey.

PubMed

Young, Marielle C; Gerber, Monica W; Ash, Tayla; Horan, Christine M; Taveras, Elsie M

2018-05-16

Native Hawaiians and Pacific Islanders (NHPIs) have the lowest attainment of healthy sleep duration among all racial and ethnic groups in the United States. We examined associations of neighborhood social cohesion with sleep duration and quality. Cross-sectional analysis of 2,464 adults in the NHPI National Health Interview Survey (2014). Neighborhood social cohesion was categorized as a continuous and categorical variable into low (<12), medium (12-14) and high (>15) according to tertiles of the distribution of responses. We used multinomial logistic regression to examine the adjusted odds ratio of short and long sleep duration relative to intermediate sleep duration. We used binary logistic regression for dichotomous sleep quality outcomes. Sleep outcomes were modeled as categorical variables. 40% of the cohort reported short (<7 hours) sleep duration and only 4% reported long (>9 hours) duration. Mean (SE, range) social cohesion score was 12.4 units (0.11, 4-16) and 23% reported low social cohesion. In multivariable models, each 1 SD decrease in neighborhood social cohesion score was associated with higher odds of short sleep duration (OR: 1.14, 95% CI: 1.02, 1.29). Additionally, low social cohesion was associated with increased odds of short sleep duration (OR: 1.53, 95% CI: 1.10, 2.13). No associations between neighborhood social cohesion and having trouble falling or staying asleep and feeling well rested were found. Low neighborhood social cohesion is associated with short sleep duration in NHPIs.

Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

PubMed Central

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-01-01

Summary Objective Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this Review was to assess machine learning alternatives to logistic regression which may accomplish the same goals but with fewer assumptions or greater accuracy. Study Design and Setting We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. Results We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (CART), and meta-classifiers (in particular, boosting). Conclusion While the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and to a lesser extent decision trees (particularly CART) appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. PMID:20630332

Robust mislabel logistic regression without modeling mislabel probabilities.

PubMed

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Fungible weights in logistic regression.

PubMed

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cannabis, tobacco and domestic fumes intake are associated with nasopharyngeal carcinoma in North Africa.

PubMed

Feng, B-J; Khyatti, M; Ben-Ayoub, W; Dahmoul, S; Ayad, M; Maachi, F; Bedadra, W; Abdoun, M; Mesli, S; Bakkali, H; Jalbout, M; Hamdi-Cherif, M; Boualga, K; Bouaouina, N; Chouchane, L; Benider, A; Ben-Ayed, F; Goldgar, D E; Corbex, M

2009-10-06

The lifestyle risk factors for nasopharyngeal carcinoma (NPC) in North Africa are not known. From 2002 to 2005, we interviewed 636 patients and 615 controls from Algeria, Morocco and Tunisia, frequency-matched by centre, age, sex, and childhood household type (urban/rural). Conditional logistic regression was used to evaluate the association of lifestyles with NPC risk, controlling for socioeconomic status and dietary risk factors. Cigarette smoking and snuff (tobacco powder with additives) intake were significantly associated with differentiated NPC but not with undifferentiated carcinoma (UCNT), which is the major histological type of NPC in these populations. As demonstrated by a stratified permutation test and by conditional logistic regression, marijuana smoking significantly elevated NPC risk independently of cigarette smoking, suggesting dissimilar carcinogenic mechanisms between cannabis and tobacco. Domestic cooking fumes intake by using kanoun (compact charcoal oven) during childhood increased NPC risk, whereas exposure during adulthood had less effect. Neither alcohol nor shisha (water pipe) was associated with risk. Tobacco, cannabis and domestic cooking fumes intake are risk factors for NPC in western North Africa.

Cannabis, tobacco and domestic fumes intake are associated with nasopharyngeal carcinoma in North Africa

PubMed Central

Feng, B-J; Khyatti, M; Ben-Ayoub, W; Dahmoul, S; Ayad, M; Maachi, F; Bedadra, W; Abdoun, M; Mesli, S; Bakkali, H; Jalbout, M; Hamdi-Cherif, M; Boualga, K; Bouaouina, N; Chouchane, L; Benider, A; Ben-Ayed, F; Goldgar, D E; Corbex, M

2009-01-01

Background: The lifestyle risk factors for nasopharyngeal carcinoma (NPC) in North Africa are not known. Methods: From 2002 to 2005, we interviewed 636 patients and 615 controls from Algeria, Morocco and Tunisia, frequency-matched by centre, age, sex, and childhood household type (urban/rural). Conditional logistic regression was used to evaluate the association of lifestyles with NPC risk, controlling for socioeconomic status and dietary risk factors. Results: Cigarette smoking and snuff (tobacco powder with additives) intake were significantly associated with differentiated NPC but not with undifferentiated carcinoma (UCNT), which is the major histological type of NPC in these populations. As demonstrated by a stratified permutation test and by conditional logistic regression, marijuana smoking significantly elevated NPC risk independently of cigarette smoking, suggesting dissimilar carcinogenic mechanisms between cannabis and tobacco. Domestic cooking fumes intake by using kanoun (compact charcoal oven) during childhood increased NPC risk, whereas exposure during adulthood had less effect. Neither alcohol nor shisha (water pipe) was associated with risk. Conclusion: Tobacco, cannabis and domestic cooking fumes intake are risk factors for NPC in western North Africa. PMID:19724280

Comparison of patient centeredness of visits to emergency departments, physicians, and dentists for dental problems and injuries.

PubMed

Cohen, Leonard A; Bonito, Arthur J; Eicheldinger, Celia; Manski, Richard J; Macek, Mark D; Edwards, Robert R; Khanna, Niharika

2010-01-01

Patient-centered care has a positive impact on patient health status. This report compares patient assessments of patient centeredness during treatment in hospital emergency departments (EDs) and physician and dentist offices for dental problems and injuries. Participants included low-income White, Black, and Hispanic adults who had experienced a dental problem or injury during the previous 12 months and who visited an emergency department, physician, or dentist for treatment. A stratified random sample of Maryland households participated in a cross-sectional telephone survey. Interviews were completed with 94.8% (401/423) of eligible individuals. Multivariable logistic regression analyses were performed. The measure of predictive power, the pseudo-R2s, calculated for the logistic regression models ranged from 12% to 18% for the analyses of responses to the measures of patient centeredness (satisfaction with treatment, careful listening, thorough explaining, spending enough time, and treated with courtesy and respect). EDs were less likely than dentists to treat patients with great courtesy and respect. Further research is needed to identify factors that support patient-centered care.

Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

PubMed

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-08-01

Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Should metacognition be measured by logistic regression?

PubMed

Rausch, Manuel; Zehetleitner, Michael

2017-03-01

Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

Logistic models--an odd(s) kind of regression.

PubMed

Jupiter, Daniel C

2013-01-01

The logistic regression model bears some similarity to the multivariable linear regression with which we are familiar. However, the differences are great enough to warrant a discussion of the need for and interpretation of logistic regression. Copyright © 2013 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Oral Microbiota and Risk for Esophageal Squamous Cell Carcinoma in a High-Risk Area of China.

PubMed

Chen, Xingdong; Winckler, Björn; Lu, Ming; Cheng, Hongwei; Yuan, Ziyu; Yang, Yajun; Jin, Li; Ye, Weimin

2015-01-01

Poor oral health has been linked with an increased risk of esophageal squamous cell carcinoma (ESCC). We investigated whether alteration of oral microbiota is associated with ESCC risk. Fasting saliva samples were collected from 87 incident and histopathologicallly diagnosed ESCC cases, 63 subjects with dysplasia and 85 healthy controls. All subjects were also interviewed with a questionnaire. V3-V4 region of 16S rRNA was amplified and sequenced by 454-pyrosequencing platform. Carriage of each genus was compared by means of multivariate-adjusted odds ratios derived from logistic regression model. Relative abundance was compared using Metastats method. Beta diversity was estimated using Unifrac and weighted Unifrac distances. Principal coordinate analysis (PCoA) was applied to ordinate dissimilarity matrices. Multinomial logistic regression was used to compare the coordinates between different groups. ESCC subjects had an overall decreased microbial diversity compared to control and dysplasia subjects (P<0.001). Decreased carriage of genera Lautropia, Bulleidia, Catonella, Corynebacterium, Moryella, Peptococcus and Cardiobacterium were found in ESCC subjects compared to non-ESCC subjects. Multinomial logistic regression analyses on PCoA coordinates also revealed that ESCC subjects had significantly different levels for several coordinates compared to non-ESCC subjects. In conclusion, we observed a correlation between altered salivary bacterial microbiota and ESCC risk. The results of our study on the saliva microbiome are of particular interest as it reflects the shift in microbial communities. Further studies are warranted to verify this finding, and if being verified, to explore the underlying mechanisms.

Differentiating major depressive disorder in youths with attention deficit hyperactivity disorder.

PubMed

Diler, Rasim Somer; Daviss, W Burleson; Lopez, Adriana; Axelson, David; Iyengar, Satish; Birmaher, Boris

2007-09-01

Youths with attention deficit hyperactivity disorders (ADHD) frequently have comorbid major depressive disorders (MDD) sharing overlapping symptoms. Our objective was to examine which depressive symptoms best discriminate MDD among youths with ADHD. One-hundred-eleven youths with ADHD (5.2-17.8 years old) and their parents completed interviews with the K-SADS-PL and respective versions of the child or the parent Mood and Feelings Questionnaire (MFQ-C, MFQ-P). Controlling for group differences, logistic regression was used to calculate odds ratios reflecting the accuracy with which various depressive symptoms on the MFQ-C or MFQ-P discriminated MDD. Stepwise logistic regression then identified depressive symptoms that best discriminated the groups with and without MDD, using cross-validated misclassification rate as the criterion. Symptoms that discriminated youths with MDD (n=18) from those without MDD (n=93) were 4 of 6 mood/anhedonia symptoms, all 14 depressed cognition symptoms, and only 3 of 11 physical/vegetative symptoms. Mild irritability, miserable/unhappy moods, and symptoms related to sleep, appetite, energy levels and concentration did not discriminate MDD. A stepwise logistic regression correctly classified 89% of the comorbid MDD subjects, with only age, anhedonia at school, thoughts about killing self, thoughts that bad things would happen, and talking more slowly remaining in the final model. Results of this study may not generalize to community samples because subjects were drawn largely from a university-based outpatient psychiatric clinic. These findings stress the importance of social withdrawal, anhedonia, depressive cognitions, suicidal thoughts, and psychomotor retardation when trying to identify MDD among ADHD youths.

Improving completion rates for client intake forms through Audio Computer-Assisted Self-Interview (ACASI): results from a pilot study with the Avon Breast Health Outreach Program.

PubMed

Hallum-Montes, Rachel; Senter, Lindsay; D'Souza, Rohan; Gates-Ferris, Kathryn; Hurlbert, Marc; Anastario, Michael

2014-01-01

This study compares rates of completion of client intake forms (CIFs) collected via three interview modes: audio computer-assisted self-interview (ACASI), face-to-face interview (FFI), and self-administered paper-based interview (SAPI). A total of 303 clients served through the Avon Breast Health Outreach Program (BHOP) were sampled from three U.S. sites. Clients were randomly assigned to complete a standard CIF via one of the three interview modes. Logistic regression analyses demonstrated that clients were significantly more likely to complete the entire CIF via ACASI than either FFI or SAPI. The greatest observed differences were between ACASI and SAPI; clients were almost six times more likely to complete the CIF via ACASI as opposed to SAPI (AOR = 5.8, p < .001). We recommend that where feasible, ACASI be utilized as an effective means of collecting client-level data in healthcare settings. Adoption of ACASI in health centers may translate into higher completion rates of intake forms by clients, as well as reduced burden on clinic staff to enter data and review intake forms for completion. © 2013 National Association for Healthcare Quality.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

Pregnancy outcomes among female hairdressers who participated in the Danish National Birth Cohort.

PubMed

Zhu, Jin Liang; Vestergaard, Mogens; Hjollund, Niels Henrik; Olsen, Jørn

2006-02-01

The Danish National Birth Cohort (DNBC) was used to examine pregnancy outcomes among female hairdressers and neurodevelopment in their offspring. A population-based cohort study was conducted of 550 hairdressers and 3216 shop assistants (reference group) by using data from the Danish National Birth Cohort between 1997 and 2003. Information on job characteristics was reported by the women in the first interview (around 17 weeks of gestation). Pregnancy outcomes were obtained by linkage to the national registers. Developmental milestones were reported by the mother at the fourth interview, when the child was approximately 19 months old. Cox regression was applied to analyze fetal loss and congenital malformation. Logistic regression was used to analyze other pregnancy outcomes and developmental milestones. We found no significant differences in fetal loss, multiple births, gender ratio, preterm birth, small-for-gestational age, congenital malformations, or achievement of developmental milestones among the children of hairdressers and shop assistants. The results do not indicate that children of hairdressers in Denmark currently have a high risk of fetal impairment or delayed psychomotor development.

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

Predicting U.S. Army Reserve Unit Manning Using Market Demographics

DTIC Science & Technology

2015-06-01

develops linear regression , classification tree, and logistic regression models to determine the ability of the location to support manning requirements... logistic regression model delivers predictive results that allow decision-makers to identify locations with a high probability of meeting unit...manning requirements. The recommendation of this thesis is that the USAR implement the logistic regression model. 14. SUBJECT TERMS U.S

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

PubMed

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

NIDA-Drug Addiction Treatment Outcome Study (DATOS) Relapse as a Function of Spirituality/Religiosity

PubMed Central

Schoenthaler, Stephen J.; Blum, Kenneth; Braverman, Eric R.; Giordano, John; Thompson, Ben; Oscar-Berman, Marlene; Badgaiyan, Rajendra D.; Madigan, Margaret A.; Dushaj, Kristina; Li, Mona; Demotrovics, Zsolt; Waite, Roger L.; Gold, Mark S.

2015-01-01

Background The connection between religion/spirituality and deviance, like substance abuse, was first made by Durkheim who defined socially expected behaviors as norms. He explained that deviance is due in large part to their absence (called anomie), and concluded that spirituality lowers deviance by preserving norms and social bonds. Impairments in brain reward circuitry, as observed in Reward Deficiency Syndrome (RDS), may also result in deviance and as such we wondered if stronger belief in spirituality practice and religious belief could lower relapse from drugs of abuse. Methods The NIDA Drug Addiction Treatment Outcome Study data set was used to examine post hoc relapse rates among 2,947 clients who were interviewed at 12 months after intake broken down by five spirituality measures. Results Our main findings strongly indicate, that those with low spirituality have higher relapse rates and those with high spirituality have higher remission rates with crack use being the sole exception. We found significant differences in terms of cocaine, heroin, alcohol, and marijuana relapse as a function of strength of religious beliefs (x2 = 15.18, p = 0.028; logistic regression = 10.65, p = 0.006); frequency of attending religious services (x2 = 40.78, p < 0.0005; logistic regression = 30.45, p < 0.0005); frequency of reading religious books (x2 = 27.190, p < 0.0005; logistic regression = 17.31, p < 0.0005); frequency of watching religious programs (x2 = 19.02, p = 0.002; logistic regression = ns); and frequency of meditation/prayer (x2 = 11.33, p = 0.045; logistic regression = 9.650, p = 0.002). Across the five measures of spirituality, the spiritual participants reported between 7% and 21% less alcohol, cocaine, heroin, and marijuana use than the non-spiritual subjects. However, the crack users who reported that religion was not important reported significantly less crack use than the spiritual participants. The strongest association between remission and spirituality involves attending religious services weekly, the one marker of the five that involves the highest social interaction/social bonding consistent with Durkheim’s social bond theory. Conclusions Stronger spiritual/religious beliefs and practices are directly associated with remission from abused drugs except crack. Much like the value of having a sponsor, for clients who abuse drugs, regular spiritual practice, particularly weekly attendance at the religious services of their choice is associated with significantly higher remission. These results demonstrate the clinically significant role of spirituality and the social bonds it creates in drug treatment programs. PMID:26052556

NIDA-Drug Addiction Treatment Outcome Study (DATOS) Relapse as a Function of Spirituality/Religiosity.

PubMed

Schoenthaler, Stephen J; Blum, Kenneth; Braverman, Eric R; Giordano, John; Thompson, Ben; Oscar-Berman, Marlene; Badgaiyan, Rajendra D; Madigan, Margaret A; Dushaj, Kristina; Li, Mona; Demotrovics, Zsolt; Waite, Roger L; Gold, Mark S

The connection between religion/spirituality and deviance, like substance abuse, was first made by Durkheim who defined socially expected behaviors as norms. He explained that deviance is due in large part to their absence (called anomie), and concluded that spirituality lowers deviance by preserving norms and social bonds. Impairments in brain reward circuitry, as observed in Reward Deficiency Syndrome (RDS), may also result in deviance and as such we wondered if stronger belief in spirituality practice and religious belief could lower relapse from drugs of abuse. The NIDA Drug Addiction Treatment Outcome Study data set was used to examine post hoc relapse rates among 2,947 clients who were interviewed at 12 months after intake broken down by five spirituality measures. Our main findings strongly indicate, that those with low spirituality have higher relapse rates and those with high spirituality have higher remission rates with crack use being the sole exception. We found significant differences in terms of cocaine, heroin, alcohol, and marijuana relapse as a function of strength of religious beliefs (x 2 = 15.18, p = 0.028; logistic regression = 10.65, p = 0.006); frequency of attending religious services (x 2 = 40.78, p < 0.0005; logistic regression = 30.45, p < 0.0005); frequency of reading religious books (x 2 = 27.190, p < 0.0005; logistic regression = 17.31, p < 0.0005); frequency of watching religious programs (x 2 = 19.02, p = 0.002; logistic regression = ns); and frequency of meditation/prayer (x 2 = 11.33, p = 0.045; logistic regression = 9.650, p = 0.002). Across the five measures of spirituality, the spiritual participants reported between 7% and 21% less alcohol, cocaine, heroin, and marijuana use than the non-spiritual subjects. However, the crack users who reported that religion was not important reported significantly less crack use than the spiritual participants. The strongest association between remission and spirituality involves attending religious services weekly, the one marker of the five that involves the highest social interaction/social bonding consistent with Durkheim's social bond theory. Stronger spiritual/religious beliefs and practices are directly associated with remission from abused drugs except crack. Much like the value of having a sponsor, for clients who abuse drugs, regular spiritual practice, particularly weekly attendance at the religious services of their choice is associated with significantly higher remission. These results demonstrate the clinically significant role of spirituality and the social bonds it creates in drug treatment programs.

Logistic Regression: Concept and Application

ERIC Educational Resources Information Center

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Predictors of condom use and refusal among the population of Free State province in South Africa

PubMed Central

2012-01-01

Background This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. Methods Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. Results Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. Conclusions The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate interventions to reduce the shame associated with condoms and individual counselling of those likely to refuse condoms. PMID:22639964

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

PubMed Central

Weiss, Brandi A.; Dardick, William

2015-01-01

This article introduces an entropy-based measure of data–model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data–model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data–model fit to assess how well logistic regression models classify cases into observed categories. PMID:29795897

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Large unbalanced credit scoring using Lasso-logistic regression ensemble.

PubMed

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression.

PubMed

Weiss, Brandi A; Dardick, William

2016-12-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data-model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data-model fit to assess how well logistic regression models classify cases into observed categories.

Recent Findings on the Prevalence of E-Cigarette Use Among Adults in the U.S.

PubMed

Wilson, Fernando A; Wang, Yang

2017-03-01

This study uses a recent source of nationally representative data from in-person surveys to examine national estimates of e-cigarette use among adults and their relationship with demographic, socioeconomic, and health behavior measures. Data were provided by the National Health Interview Survey, conducted by the Centers for Disease Control and Prevention. A total of 34,356 respondents aged ≥18 years were examined for 2014, the most recent and only year in which the National Health Interview Survey included questions on e-cigarette use. E-cigarette information included ever and current use. Univariate and multivariable logistic regression analyses were performed, adjusting for age, sex, race/ethnicity, education level, marital status, poverty, and smoking status. Analyses were conducted in 2016. Compared with those who had never tried e-cigarettes, e-cigarette users were more likely to be younger, male, non-Hispanic white, non-married, poorer, and current smokers. Multivariable logistic regression suggested that respondents with high school or some college education had significantly higher adjusted odds of ever using e-cigarettes relative to those with less than high school education. However, the adjusted odds were not significantly different for college or graduate school education. The results suggest that, unlike tobacco use, ever using e-cigarettes is positively related to income. Interestingly, e-cigarette use exhibits a non-linear relationship with education. Reasons for the relationship of e-cigarettes with education are unclear and warrant further research. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

[Prevalence and characteristics of urinary incontinence in community-dwelling-elderly as determined by comprehensive health examination and interview for the prevention of geriatric syndrome and bed-ridden state].

PubMed

Yoshida, Yuko; Kim, Hunkyung; Iwasa, Hajime; Kwon, Jinhee; Sugiura, Miho; Furuna, Taketo; Yoshida, Hideyo; Suzuki, Takao

2007-01-01

We examined the prevalence and characteristics of urinary incontinence in community-dwelling elderly individuals. The participants were 1,783 individuals (768 men and 1,015 women) aged over 70 years who participated in a comprehensive health examination involving a medical examination and interview, plus physical performance tests. Differences in characteristics between individuals with and without urinary incontinence were examined, and multivariate logistic regression models were used to describe the characteristics associated with urinary incontinence. The prevalence of urinary incontinence was 13.4% in men and 23.3% in women. Urinary incontinence was significantly associated with a lower level of physical fitness. Multivariate logistic regression showed that urinary incontinence was significantly associated with a slower walking speed (Odds Ratio (OR) = 0.19, 95% Confidence Intervals (CI) 0.08-0.48) and lower serum albumin level (OR = 0.40, 95% CI 0.16-0.99) in men, and with a slower walking speed (OR = 0.29, 95% CI 0.15-0.56), a higher BMI (OR = 1.09, 95% CI 1.04-1.14), depression (OR = 3.06, 95% CI 1.40-6.69), and lack of physical activity (OR = 0.70, 95% CI 0.50-0.98) in women. The characteristics of urinary incontinence in this cohort of community-dwelling elderly individuals were a low level of physical fitness and poor nutritional state in men, and a low level of physical fitness, a tendency to be obese, a poor mental health state, and lack of physical activity in women.

Suicide attempt characteristics may orientate toward a bipolar disorder in attempters with recurrent depression.

PubMed

Guillaume, Sébastien; Jaussent, Isabelle; Jollant, Fabrice; Rihmer, Zoltán; Malafosse, Alain; Courtet, Philippe

2010-04-01

Identification of patients with a bipolar disorder (BPD) among those presenting a major depressive episode is often difficult, resulting in common misdiagnosis and mistreatment. Our aim was to identify clinical variables unrelated to current depressive episode and relevant to suicidal behavior that may help to improve the detection of BPD in suicide attempters presenting with recurrent major depressive disorder. 211 patients suffering from recurrent major depressive disorder or BPD, hospitalized after a suicide attempt (SA), were interviewed by semi-structured interview and validated questionnaires about DSM-IV axis I disorders, SA characteristics and a wide range of personality traits relevant to suicidal vulnerability. Multivariate logistic regression analysis was performed to determine differences between RMDD and BPD attempters. Logistic regression analysis showed that serious SA and family history of suicide are closely associated with a diagnosis of BPD [respectively OR=2.28, p=0.0195; OR=2.98, p=0.0081]. The presence of both characteristics increase the association with BDP [OR=4.78, p=0.005]. Conversely, when looking for the features associated with a serious SA, BPD was the only associated diagnosis [OR=2.03, p=0.004]. Lastly, affect intensity was higher in BPD samples [OR=2.08, p=0.041]. Retrospective nature of the study, lack of the separate analysis of bipolar subtypes. Serious suicide attempt and a familial history of completed suicide in patients with major depression seem to be a clinical marker of bipolarity. Facing suicide attempters with recurrent depression, clinician should be awareness to these characteristics to detect BPD. Copyright 2009 Elsevier B.V. All rights reserved.

Unintended pregnancy in the life-course perspective.

PubMed

Helfferich, Cornelia; Hessling, Angelika; Klindworth, Heike; Wlosnewski, Ines

2014-09-01

In this contribution unintended pregnancies are studied as a multidimensional concept from a life-course perspective. Standardized data on the prevalence of unwanted pregnancies in different stages of women's life course are combined with a qualitative analysis of the subjective meaning of "unwanted" and of subjective explanations of getting pregnant unintentionally. The study "frauen leben 3" on family planning in the life course of 20-44 year old women was conducted on behalf of the Federal Centre for Health Education (BZgA) from 2011 until 2014 in four federal states in Germany. A standardized questionnaire was used to collect retrospective information on 4794 pregnancies (including induced abortions), and biographical in-depth interviews provide qualitative information on 103 unwanted pregnancies. The standardized data were analyzed with bivariate methods and multivariate logistic regression models. The qualitative procedure to construct typologies of subjective meanings consisted of contrasting cases according to the generative approach of Grounded Theory. In contrast to unwanted pregnancies, mistimed pregnancies are characterized to a greater extent by negligence in the use of contraceptives, by a positive reaction to the pregnancy and by a more general desire to have a child. Four different subjective meanings of "unwanted" are constructed in qualitative analysis. The logistic regressions show that the selected factors that increase the likelihood of an unwanted pregnancy vary according to age and stage in the life course. The quantitative analysis reveals furthermore that relationship with a partner had a significant effect in all stages of the life course. The qualitative interviews specify the age- and life course-related aspects of these effects. Copyright © 2014 Elsevier Ltd. All rights reserved.

Does interview mode matter for food security measurement? Telephone versus in-person interviews in the Current Population Survey Food Security Supplement.

PubMed

Nord, Mark; Hopwood, Heather

2007-12-01

To assess whether interview mode (telephone vs. in-person) affects the results of surveys that measure food security. Responses given by households interviewed by telephone and in-person in recent US Current Population Survey Food Security Supplements (CPS-FSS) were compared. Statistical methods based on the Rasch measurement model were used to assess whether response patterns differed between the two interview modes. Multivariate logistic regression analysis was then used to gauge the effect of interview mode on the measured household prevalence rates of food insecurity and very low food security while controlling for income, employment, household structure, and other household characteristics that affect food security. Response patterns to the indicators that comprise the food security scale did not differ substantially between interview modes. Prevalence rates of food insecurity and very low food security estimated from the two interview modes differed by only small proportions after accounting for differences in the socio-economic characteristics of households. Findings suggest that effects of interview mode on food security measurement in the CPS-FSS are small, or at most modest. Prevalence estimates may be biased upwards somewhat for households interviewed in-person compared with those interviewed by telephone. The extent to which these results can be generalised may depend, to some extent, on survey characteristics other than interview mode, such as surveyor name recognition and respondents' trust and confidence in the surveyor.

[Dementia, depression and activity of daily living as risk factors for falls in elderly patients].

PubMed

Gostynski, M; Ajdacic-Gross, V; Heusser-Gretler, R; Gutzwiller, F; Michel, J P; Herrmann, F

2001-01-01

Falls among elderly are a well-recognised public health problem. The purpose of the present study was to explore the relation between dementia, number of depressive symptoms, activities of daily living, setting, and risk of falling. Data for the analysis came from a cross-sectional study about dementia, depression, and disabilities, carried out 1995/96 in Zurich and Geneva. The random sample stratified, by age and gender consisted of 921 subjects aged 65 and more. The interview was conducted by means of the Canberra interview for the Elderly, extended by short questionnaire. The subject was classified as a faller if the subject and/or the informant had reported a fall within the last 12 months prior to the interview. Logistic-regression analysis was used to determine the independent impact of dementia, depressive symptoms, and ADL-score on risk of falling. The stepwise logistic regression analysis has revealed a statistically significant association between dementia (OR 2.14, 95% CI 1.15-3.96), two resp. three depressive symptoms (OR 1.64, 95% CI 1.04-2.60) as well as four or more depressive symptoms (OR 2.64, 95% CI 1.39-5.02) and the risk of falling. There was no statistically significant relationship between studied risk factors and the risk of being one-time faller. However, we found a strong positive association between dementia (OR 3.92, 95% CI 1.75-8.79), four or more depressive symptoms (OR 3.90, 95% CI 1.55-9.83) and the risk of being recurrent faller. Moreover, residents of nursing homes (OR 8.50, 95% CI 2.18-33.22) and elderly aged 85 or more (OR 2.29, 95% CI 1.08-4.87) were under statistically significant higher risk of sustaining recurrent falls. The results of the present study confirm that dementia and depression substantially increase the risk of falling.

A mixed methods inquiry into the determinants of traditional food consumption among three Cree communities of Eeyou Istchee from an ecological perspective.

PubMed

Gaudin, Véronique Laberge; Receveur, Olivier; Walz, Leah; Girard, Félix; Potvin, Louise

2014-01-01

The Aboriginal nations of Canada have higher incidences of chronic diseases, coinciding with profound changes in their environment, lifestyle and diet. Traditional foods can protect against the risks of chronic disease. However, their consumption is in decline, and little is known about the complex mechanisms underlying this trend. To identify the factors involved in traditional food consumption by Cree Aboriginal people living in 3 communities in northern Quebec, Canada. Design. A mixed methods explanatory design, including focus group interviews to interpret the results of logistic regression. This study includes a secondary data analysis of a cross-sectional survey of 3 Cree communities (n=374) and 4 focus group interviews (n=23). In the first, quantitative phase of the study, data were collected using a food-frequency questionnaire along with a structured questionnaire. Subsequently, the focus group interviews helped explain and build on the results of logistic regressions. People who consume traditional food 3 days or more weekly were more likely to be 40 years old and over, to walk 30 minutes or more per day, not to have completed their schooling, to live in Mistissini and to be a hunter (p<0.05 for all comparisons). The focus group participants provided explanations for the quantitative analysis results or completed them. For example, although no statistical association was found, focus group participants believed that employment acts as both a facilitator and a barrier to traditional food consumption, rendering the effect undetectable. In addition, focus group participants suggested that traditional food consumption is the result of multiple interconnected influences, including individual, family, community and environmental influences, rather than a single factor. This study sheds light on a number of factors that are unique to traditional foods, factors that have been understudied to date. Efforts to promote and maintain traditional food consumption could improve the overall health and wellbeing of Cree communities.

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

ERIC Educational Resources Information Center

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

A Methodology for Generating Placement Rules that Utilizes Logistic Regression

ERIC Educational Resources Information Center

Wurtz, Keith

2008-01-01

The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

[Clinical experience and academic thoughts of Professor LIU Feng-bin on case series of gastroesophageal reflux disease based on data mining].

PubMed

Hou, Zheng-Kun; Li, Ji-Ping; Chen, Zhuo-Qun; Liu, Feng-Bin

2018-03-01

To analyze and summarize Professor LIU Feng-bin's clinical experience and academic thoughts on gastroesophageal reflux disease (GERD), the study group adopted the retrospective study for case series and expert interview, extracted the retrospective data, including the herbs, diseases, syndrome type, medical expense and quantity of herbs of GERD patients attended the First Affiliated Hospital of Guangzhou University of Chinese Medicine. Statistical description and binary Logistic regression were used for the identification and modification of syndrome type and initial core herbs. After expert interviews were performed for the syndrome type and herbs, the final scheme were formed. A total of 112 GERD patients ages（48.97±13.13）y; male: 35 (31.3%), female: 77(68.7%) were enrolled. The numbers of patients with liver and stomach incoordination syndrome, heat stagnation of liver and stomach syndrome, syndrome of dual deficiency of Qi and Yin, syndrome of spleen deficiency and dampness-heat, spleen-stomach disharmony syndrome were 40, 26, 19, 17 and 10, respectively. The patients used totally 80 herbs, and 26 of them had significant differences among different syndrome groups. According to the logistic regression analysis on the 23 herbs used by 112 patients, the herbs scheme was modified for the second time. After the expert interviews and modification, the final consensus was reached. The main causes for GERD were dietary irregularities, moodiness, and weak constitution. The basic mechanism of GERD was spleen deficiency with Qi adverseness. The spleen-stomach disharmony syndrome was deleted by expert interviews. The 10 core herbs for GERD treatment were Taizishen(Pseudostellariae Radix), Fuling(Poria), Baizhu(Atractylodismacrocephalae Rhizoma), Gancao(Glycyrrhizae Radix Et Rhizoma), Zhebeimu(Fritillariae Thunbergii Bulbus), Haipiaoxiao(Sepiae Endoconcha), Zhiqiao(Aurantii Fructus), Chenxiang(Alosewood), Pugongying(Taraxaci Herba), Zhizitan(Cape Jasmine Fruit). The modification and psychological and diet interventions were also identified. This study summarized Professor LIU Feng-bin's clinical experience and academic thoughts of chronic atrophic gastritis based on data mining of case series and expert interviews. The quality of methodologies and report were both well. The results provide a foundation and ideas for further study on the complex intervention for GERD, and can be directly applied in clinical practice. Copyright© by the Chinese Pharmaceutical Association.

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

PubMed Central

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988

The psychological impact of terrorism: an epidemiologic study of posttraumatic stress disorder and associated factors in victims of the 1995-1996 bombings in France.

PubMed

Verger, Pierre; Dab, William; Lamping, Donna L; Loze, Jean-Yves; Deschaseaux-Voinet, Céline; Abenhaim, Lucien; Rouillon, Frédéric

2004-08-01

A wave of bombings struck France in 1995 and 1996, killing 12 people and injuring more than 200. The authors conducted follow-up evaluations with the victims in 1998 to determine the prevalence of and factors associated with posttraumatic stress disorder (PTSD). Victims directly exposed to the bombings (N=228) were recruited into a retrospective, cross-sectional study. Computer-assisted telephone interviews were conducted to evaluate PTSD, per DSM-IV criteria, and to assess health status before the attack, initial injury severity and perceived threat at the time of attack, and psychological symptoms, cosmetic impairment, hearing problems, and health service use at the time of the follow-up evaluation. Factors associated with PTSD were investigated with univariate logistic regression followed by multiple logistic regression analyses. A total of 196 respondents (86%) participated in the study. Of these, 19% had severe initial physical injuries (hospitalization exceeding 1 week). Problems reported at the follow-up evaluation included attack-related hearing problems (51%), cosmetic impairment (33%), and PTSD (31%) (95% confidence interval=24.5%-37.5%). Results of logistic regression analyses indicated that the risk of PTSD was significantly higher among women (odds ratio=2.54), participants age 35-54 (odds ratio=2.83), and those who had severe initial injuries (odds ratio=2.79) or cosmetic impairment (odds ratio=2.74) or who perceived substantial threat during the attack (odds ratio=3.99). The high prevalence of PTSD 2.6 years on average after a terrorist attack emphasizes the need for improved health services to address the intermediate and long-term consequences of terrorism.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Prevalence of and Risk Factors for Intimate Partner Violence in China

PubMed Central

Xu, Xiao; Zhu, Fengchuan; O’Campo, Patricia; Koenig, Michael A.; Mock, Victoria; Campbell, Jacquelyn

2005-01-01

Objectives. We estimated the prevalence of and risk factors for intimate partner violence in China. Methods. Our cross-sectional, comparative prevalence study used a face-to-face survey of randomly selected women attending an urban outpatient gynecological clinic at a major teaching hospital in Fuzhou, China. Multiple logistic regression models were used to assess risk factors for intimate partner violence. Results. Of the 600 women interviewed, the prevalence of lifetime intimate partner violence and violence taking place within the year before the interview was 43% and 26%, respectively. For lifetime intimate partner violence, partners who had extramarital affairs and who refused to give respondents money were the strongest independent predictors. For intimate partner violence taking place within the year before the interview, frequent quarreling was the strongest predictor. Conclusions. Intimate partner violence is prevalent in China, with strong associations with male patriarchal values and conflict resolutions. Efforts to reduce intimate partner violence should be given high priority in health care settings where women can be reached. PMID:15623864

Factors associated with self-medication in Spain: a cross-sectional study in different age groups.

PubMed

Niclós, Gracia; Olivar, Teresa; Rodilla, Vicent

2018-06-01

The identification of factors which may influence a patient's decision to self-medicate. Descriptive, cross-sectional study of the adult population (at least 16 years old), using data from the 2009 European Health Interview Survey in Spain, which included 22 188 subjects. Logistic regression models enabled us to estimate the effect of each analysed variable on self-medication. In total, 14 863 (67%) individuals reported using medication (prescribed and non-prescribed) and 3274 (22.0%) of them self-medicated. Using logistic regression and stratifying by age, four different models have been constructed. Our results include different variables in each of the models to explain self-medication, but the one that appears on all four models is education level. Age is the other important factor which influences self-medication. Self-medication is strongly associated with factors related to socio-demographic, such as sex, educational level or age, as well as several health factors such as long-standing illness or physical activity. When our data are compared to those from previous Spanish surveys carried out in 2003 and 2006, we can conclude that self-medication is increasing in Spain. © 2017 Royal Pharmaceutical Society.

Nutrition knowledge, attitudes, behaviours and the influencing factors among non-parent caregivers of rural left-behind children under 7 years old in China.

PubMed

Tan, Cai; Luo, Jiayou; Zong, Rong; Fu, Chuhui; Zhang, Lingli; Mou, Jinsong; Duan, Danhui

2010-10-01

To explore and compare nutrition knowledge, attitudes and behaviours (KAB) between non-parent and parent caregivers of children under 7 years old in Chinese rural areas, and to identify the factors influencing their nutrition KAB. Face-to-face interviews were carried out with 1691 non-parent caregivers and 1670 parent caregivers in the selected study areas; multivariate logistic regression models were used to identify the factors influencing nutrition KAB in caregivers. The awareness rate of nutrition knowledge, the rate of positive attitudes and the rate of optimal behaviours in non-parent caregivers (52.2 %, 56.9 % and 37.7 %, respectively) were significantly lower than in the parent group (63.8 %, 62.1 % and 42.8 %, respectively). Multivariate logistic regression modelling showed that caregivers' family income and care will, and children's age and gender, were associated with caregivers' nutrition KAB after controlling the possible confounding variables (caregivers' age, gender, education and occupation). Non-parent caregivers had relatively poor nutrition KAB. Extra efforts and targeted education programmes aimed to improve rural non-parent caregivers' nutrition KAB are wanted and need to be emphasized.

Differences by Sexual Orientation in Expectations About Future Long-Term Care Needs Among Adults 40 to 65 Years Old.

PubMed

Henning-Smith, Carrie; Gonzales, Gilbert; Shippee, Tetyana P

2015-11-01

We examined whether and how lesbian, gay, and bisexual (LGB) adults between 40 and 65 years of age differ from heterosexual adults in long-term care (LTC) expectations. Our data were derived from the 2013 National Health Interview Survey. We used ordered logistic regression to compare the odds of expected future use of LTC among LGB (n = 297) and heterosexual (n = 13 120) adults. We also used logistic regression models to assess the odds of expecting to use specific sources of care. All models controlled for key socioeconomic characteristics. Although LGB adults had greater expectations of needing LTC in the future than their heterosexual counterparts, that association was largely explained by sociodemographic and health differences. After control for these differentials, LGB adults were less likely to expect care from family and more likely to expect to use institutional care in old age. LGB adults may rely more heavily than heterosexual adults on formal systems of care. As the older population continues to diversify, nursing homes and assisted living facilities should work to ensure safety and culturally sensitive best practices for older LGB groups.

Factors associated with heavy alcohol use among students in Brazilian capitals.

PubMed

Galduróz, José Carlos F; Sanchez, Zila van der Meer; Opaleye, Emérita Sátiro; Noto, Ana Regina; Fonseca, Arilton Martins; Gomes, Paulo Leonardo Sirimarco; Carlini, Elisaldo Araújo

2010-04-01

To evaluate the association between heavy use of alcohol among students and family, personal and social factors. Cross-sectional study including public school students aged ten to 18 from 27 Brazilian capital cities in 2004. Data was collected using an anonymous, self-report questionnaire that was adapted from a World Health Organization instrument. A representative sample comprising 48,155 students was stratified by census tracts and clusters (schools). The associations between heavy alcohol use and the factors studied were analyzed using logistic regression at a 5% significance level. Of all students, 4,286 (8.9%) reported heavy alcohol use in the month prior to the interview. The logistic regression analysis showed an association between fair or poor relationship with the father (OR = 1.46) and the mother (OR = 1.61) and heavy use of alcohol. Following a religion (OR = 0.83) was inversely associated with heavy alcohol consumption. Sports practice and mother perceived as a 'liberal' person had no significance in the model. However, a higher prevalence of heavy use of alcohol was seen among working students. Stronger family ties and religion may help preventing alcohol abuse among students.

Utilization of maternal health care services among indigenous women in Bangladesh: A study on the Mru tribe.

PubMed

Islam, Rakibul M

2017-01-01

Despite startling developments in maternal health care services, use of these services has been disproportionately distributed among different minority groups in Bangladesh. This study aimed to explore the factors associated with the use of these services among the Mru indigenous women in Bangladesh. A total of 374 currently married Mru women were interviewed using convenience sampling from three administrative sub-districts of the Bandarban district from June to August of 2009. Associations were assessed using Chi-square tests, and a binary logistic regression model was employed to explore factors associated with the use of maternal health care services. Among the women surveyed, 30% had ever visited maternal health care services in the Mru community, a very low proportion compared with mainstream society. Multivariable logistic regression analyses revealed that place of residence, religion, school attendance, place of service provided, distance to the service center, and exposure to mass media were factors significantly associated with the use of maternal health care services among Mru women. Considering indigenous socio-cultural beliefs and practices, comprehensive community-based outreach health programs are recommended in the community with a special emphasis on awareness through maternal health education and training packages for the Mru adolescents.

Prevalence and predictors of suicidal ideations and attempts among homeless children and adolescents in Ghana.

PubMed

Oppong Asante, Kwaku; Meyer-Weitz, Anna

2017-05-01

This study aimed to determine the prevalence and risk factors associated with suicidal ideations and attempts among a sample of homeless street children and adolescents found in Accra, Ghana. A cross-sectional survey of a convenience sample of 227 (122 male and 105 female) homeless youth was conducted in Ghana. An interviewer-administered questionnaire was used to collect data due to a low level of literacy among the study population. Bivariate and multivariate logistic regressions were fitted to analyse the data. The results indicated that 26.4% and 26.0% of the participants had attempted suicide and reported suicidal ideations respectively. The multivariate logistic regression showed that smoking, past and present use of alcohol, use of marijuana, and engagement in prostitution, were associated with suicidal ideations and suicide attempts. Suicidal ideations were associated with having been physically beaten, robbed, and assaulted with a weapon; while a suicide attempt was predicted by having been robbed and physically beaten. This study increased our understanding of the determinants of suicidal ideations and attempts among homeless youth. These findings suggest urgency to up-skill mental health workers to assess for risk factors and offer pathways to care for this vulnerable group.

Differences by Sexual Orientation in Expectations About Future Long-Term Care Needs Among Adults 40 to 65 Years Old

PubMed Central

Gonzales, Gilbert; Shippee, Tetyana P.

2015-01-01

Objectives. We examined whether and how lesbian, gay, and bisexual (LGB) adults between 40 and 65 years of age differ from heterosexual adults in long-term care (LTC) expectations. Methods. Our data were derived from the 2013 National Health Interview Survey. We used ordered logistic regression to compare the odds of expected future use of LTC among LGB (n = 297) and heterosexual (n = 13 120) adults. We also used logistic regression models to assess the odds of expecting to use specific sources of care. All models controlled for key socioeconomic characteristics. Results. Although LGB adults had greater expectations of needing LTC in the future than their heterosexual counterparts, that association was largely explained by sociodemographic and health differences. After control for these differentials, LGB adults were less likely to expect care from family and more likely to expect to use institutional care in old age. Conclusions. LGB adults may rely more heavily than heterosexual adults on formal systems of care. As the older population continues to diversify, nursing homes and assisted living facilities should work to ensure safety and culturally sensitive best practices for older LGB groups. PMID:26378822

Musculoskeletal disorders among workers in plastic manufacturing plants.

PubMed

Fernandes, Rita de Cássia Pereira; Assunção, Ada Avila; Silvany Neto, Annibal Muniz; Carvalho, Fernando Martins

2010-03-01

Epidemiological studies have indicated an association between musculoskeletal disorders (MSDs) and physical work demands. Psychosocial work demands have also been identified as possible risk factors, but findings have been inconsistent. To evaluate factors associated with upper back, neck and upper limb MSD among workers from 14 plastic manufacturing companies located in the city of Salvador, Brazil. A cross-sectional study design was used to survey a stratified proportional random sample of 577 workers. Data were collected by questionnaire interviews. Factor analysis was carried out on 11 physical demands variables. Psychosocial work demands were measured by demand, control and social support questions. The role of socio-demographic factors, lifestyle and household tasks was also examined. Multiple logistic regression was used to identify factors related to upper back, neck and upper limb MSDs. Results from multiple logistic regression showed that distal upper limb MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and gender. Neck, shoulder or upper back MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and physical unfitness. Reducing the prevalence of musculoskeletal disorders requires: improving the work environment, reducing biomechanical risk factors, and replanning work organization. Programs must also be aware of gender specificities related to MSDs.

Perception of tourists regarding the smoke-free policy at Suvarnabhumi International Airport, Bangkok, Thailand.

PubMed

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-08-30

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment.

Gender and literacy: factors related to diagnostic delay and unsuccessful treatment of tuberculosis in the mountainous area of Yemen.

PubMed

Date, J; Okita, K

2005-06-01

People in the mountainous area of Yemen, having maintained their traditional lifestyle, generally believe that uneducated women are unsuccessful in using modern medical care. Whether this belief applies to tuberculosis (TB) diagnosis and treatment has not been researched in Yemen. To examine how gender and literacy influence TB diagnosis and treatment. Individual interviews and data collection were conducted for 74 smear-positive pulmonary TB patients visiting the National Tuberculosis Institute in Sana'a from December 2001 to March 2002. The treatment outcome for each patient was checked from September 2002 to March 2003. Illiterate patients had a longer diagnostic delay than literate patients (P = 0.006, univariate logistic regression analysis). They also maintained their traditional view of illness, not the illness 'TB'. More females than males completed treatment (P = 0.046, univariate logistic regression analysis). Supervision by male relatives contributed to completion of treatment among female patients. Lack of education does not hinder women from receiving TB diagnosis and treatment. The concept of traditional illness, however, causes a longer diagnostic delay among illiterate patients, and the role of male relatives positively influences treatment outcomes for female patients.

Predicting Circulatory Diseases from Psychosocial Safety Climate: A Prospective Cohort Study from Australia

PubMed Central

Becher, Harry; Dollard, Maureen F.; Smith, Peter

2018-01-01

Circulatory diseases (CDs) (including myocardial infarction, angina, stroke or hypertension) are among the leading causes of death in the world. In this paper, we explore for the first time the impact of a specific aspect of organizational climate, Psychosocial Safety Climate (PSC), on CDs. We used two waves of interview data from Australia, with an average lag of 5 years (excluding baseline CDs, final n = 1223). Logistic regression was conducted to estimate the prospective associations between PSC at baseline on incident CDs at follow-up. It was found that participants in low PSC environments were 59% more likely to develop new CD than those in high PSC environments. Logistic regression showed that high PSC at baseline predicts lower CD risk at follow-up (OR = 0.98, 95% CI 0.96–1.00) and this risk remained unchanged even after additional adjustment for known job design risk factors (effort reward imbalance and job strain). These results suggest that PSC is an independent risk factor for CDs in Australia. Beyond job design this study implicates organizational climate and prevailing management values regarding worker psychological health as the genesis of CDs. PMID:29495533

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

ERIC Educational Resources Information Center

Weiss, Brandi A.; Dardick, William

2016-01-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…

What Are the Odds of that? A Primer on Understanding Logistic Regression

ERIC Educational Resources Information Center

Huang, Francis L.; Moon, Tonya R.

2013-01-01

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

PubMed

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.

PubMed

Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul

2015-11-04

Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.

Inability to access addiction treatment among street-involved youth in a Canadian setting.

PubMed

Phillips, Mark; DeBeck, Kora; Desjarlais, Timothy; Morrison, Tracey; Feng, Cindy; Kerr, Thomas; Wood, Evan

2014-08-01

From Sept 2005 to May 2012, 1015 street-involved youth were enrolled into the At-Risk Youth Study, a prospective cohort of youth aged 14-26 who use illicit drugs in Vancouver, Canada. Data were collected through semiannual interviewer administered questionnaires. Generalized estimating equation logistic regression was used to identify factors independently associated with being unable to access addiction treatment. The enclosed manuscript notes the implications and limitations of this study, as well as possible directions for future research. This study was funded by the US National Institutes of Health (NIH) and Canadian Institutes of Health (CIHR).

Logistic regression for risk factor modelling in stuttering research.

PubMed

Reed, Phil; Wu, Yaqionq

2013-06-01

To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

Dynamic Dimensionality Selection for Bayesian Classifier Ensembles

DTIC Science & Technology

2015-03-19

learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but much more...classifier, Generative learning, Discriminative learning, Naïve Bayes, Feature selection, Logistic regression , higher order attribute independence 16...discriminative learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

Preserving Institutional Privacy in Distributed binary Logistic Regression.

PubMed

Wu, Yuan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

Privacy is becoming a major concern when sharing biomedical data across institutions. Although methods for protecting privacy of individual patients have been proposed, it is not clear how to protect the institutional privacy, which is many times a critical concern of data custodians. Built upon our previous work, Grid Binary LOgistic REgression (GLORE)1, we developed an Institutional Privacy-preserving Distributed binary Logistic Regression model (IPDLR) that considers both individual and institutional privacy for building a logistic regression model in a distributed manner. We tested our method using both simulated and clinical data, showing how it is possible to protect the privacy of individuals and of institutions using a distributed strategy.

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

PubMed Central

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

2014-01-01

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

Differentially private distributed logistic regression using private and public data.

PubMed

Ji, Zhanglong; Jiang, Xiaoqian; Wang, Shuang; Xiong, Li; Ohno-Machado, Lucila

2014-01-01

Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee.

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules

PubMed Central

Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules’ 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively. PMID:29228030

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules.

PubMed

Pang, Tiantian; Huang, Leidan; Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Gong, Xuehao; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules' 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively.

Role of social support in adolescent suicidal ideation and suicide attempts.

PubMed

Miller, Adam Bryant; Esposito-Smythers, Christianne; Leichtweis, Richard N

2015-03-01

The present study examined the relative contributions of perceptions of social support from parents, close friends, and school on current suicidal ideation (SI) and suicide attempt (SA) history in a clinical sample of adolescents. Participants were 143 adolescents (64% female; 81% white; range, 12-18 years; M = 15.38; standard deviation = 1.43) admitted to a partial hospitalization program. Data were collected with well-validated assessments and a structured clinical interview. Main and interactive effects of perceptions of social support on SI were tested with linear regression. Main and interactive effects of social support on the odds of SA were tested with logistic regression. Results from the linear regression analysis revealed that perceptions of lower school support independently predicted greater severity of SI, accounting for parent and close friend support. Further, the relationship between lower perceived school support and SI was the strongest among those who perceived lower versus higher parental support. Results from the logistic regression analysis revealed that perceptions of lower parental support independently predicted SA history, accounting for school and close friend support. Further, those who perceived lower support from school and close friends reported the greatest odds of an SA history. Results address a significant gap in the social support and suicide literature by demonstrating that perceptions of parent and school support are relatively more important than peer support in understanding suicidal thoughts and history of suicidal behavior. Results suggest that improving social support across these domains may be important in suicide prevention efforts. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

An equivalence study of interview platform: Does videoconference technology impact medical school acceptance rates of different groups?

PubMed

Ballejos, Marlene P; Oglesbee, Scott; Hettema, Jennifer; Sapien, Robert

2018-02-14

Web-based interviewing may be an effective element of a medical school's larger approach to promotion of holistic review, as recommended by the Association of American Medical Colleges, by facilitating the feasibility of including rural and community physicians in the interview process. Only 10% of medical schools offer videoconference interviews to applicants and little is known about the impact of this interview modality on the admissions process. This study investigated the impact of overall acceptance rates using videoconference interviews and face-to-face interviews in the medical school selection process using an equivalence trial design. The University of New Mexico School of Medicine integrated a videoconferencing interview option for community and rural physician interviewers in a pseudo-random fashion during the 2014-2016 admissions cycles. Logistic regression was conducted to examine whether videoconference interviews impacted acceptance rates or the characteristics of accepted students. Demographic, admissions and diversity factors were analyzed that included applicant age, MCAT score, cumulative GPA, gender, underrepresented in medicine, socioeconomic status and geographic residency. Data from 752 interviews were analyzed. Adjusted rates of acceptance for face-to-face (37.0%; 95% CI 28.2, 46.7%) and videoconference (36.1%; 95% CI 17.8, 59.5%) interviews were within an a priori ± 5% margin of equivalence. Both interview conditions yielded highly diverse groups of admitted students. Having a higher medical college admission test score, grade point average, and self-identifying as disadvantaged increased odds of admission in both interview modalities. Integration of the videoconference interview did not impact the overall acceptance of a highly diverse and qualified group of applicants, and allowed rural and community physicians to participate in the medical school interview process as well as allowed campus faculty and medical student committee members to interview remotely.

Assessment of self-reported sexual behavior and condom use among female sex workers in India using a polling box approach: a preliminary report.

PubMed

Hanck, Sarah E; Blankenship, Kim M; Irwin, Kevin S; West, Brooke S; Kershaw, Trace

2008-05-01

The accuracy of behavioral data related to risk for HIV and other sexually transmitted infections is prone to misreporting because of social desirability effects. Because computer-assisted approaches are not always feasible, a noncomputerized interview method for reducing social desirability effects is needed. The previous performance of alternative methods has been limited to aggregate data or constrained by the simplicity of dichotomous-only responses. We designed and tested a "polling box" method for case-attributable, multiple-response survey items in a low literacy population. A cross-sectional survey was conducted with 812 female sex workers in Andhra Pradesh, India. For a subset of questions embedded in a face-to-face survey questionnaire, every third participant was provided graphical response cards upon which to mark their answer and place in a polling box outside the view of the interviewer. Multiple logistic regression analysis was used to test for response differences to questions about socially undesirable, socially desirable, or sensitivity-neutral behaviors in the 2 interview methods. Polling box participants demonstrated higher reporting of risky sexual behaviors and lower reporting of condom use, with no conclusive response patterns among sensitivity-neutral items. Our findings suggest that the polling box approach provides a promising technique for improving the accurate reporting of sensitive behaviors among a low-literacy population in a resource poor setting. Additional research is needed to test logistical adaptations of the polling box approach.

Minnesota Impulse Disorders Interview (MIDI): Validation of a structured diagnostic clinical interview for impulse control disorders in an enriched community sample.

PubMed

Chamberlain, Samuel R; Grant, Jon E

2018-07-01

Disorders of impulsivity are common, functionally impairing, and highly relevant across different clinical and research settings. Few structured clinical interviews for the identification and diagnosis of impulse control disorders exist, and none have been validated in a community sample in terms of psychometric properties. The Minnesota Impulse control disorders Interview (MIDI v2.0) was administered to an enriched sample of 293 non-treatment seeking adults aged 18-35 years, recruited using media advertisements in two large US cities. In addition to the MIDI, participants undertook extended clinical interview for other mental disorders, the Barratt impulsiveness questionnaire, and the Padua obsessive-compulsive inventory. The psychometric properties of the MIDI were characterized. In logistic regression, the MIDI showed good concurrent validity against the reference measures (versus gambling disorder interview, p < 0.001; Barratt impulsiveness attentional and non-planning scores p < 0.05), and good discriminant validity versus primarily non-impulsive symptoms, including against anxiety, depression, and obsessive-compulsive symptoms (all p > 0.05). Test re-test reliability was excellent (0.95). The MIDI has good psychometric properties and thus may be a valuable interview tool for clinical and research studies involving impulse control disorders. Further research is needed to better understanding the optimal diagnostic classification and neurobiology of these neglected disorders. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Determinants of children's use of and time spent in fast-food and full-service restaurants.

PubMed

McIntosh, Alex; Kubena, Karen S; Tolle, Glen; Dean, Wesley; Kim, Mi-Jeong; Jan, Jie-Sheng; Anding, Jenna

2011-01-01

Identify parental and children's determinants of children's use of and time spent in fast-food (FF) and full-service (FS) restaurants. Analysis of cross-sectional data. Parents were interviewed by phone; children were interviewed in their homes. Parents and children ages 9-11 or 13-15 from 312 families were obtained via random-digit dialing. Dependent variables were the use of and the time spent in FF and FS restaurants by children. Determinants included parental work schedules, parenting style, and family meal ritual perceptions. Logistic regression was used for multivariate analysis of use of restaurants. Least squares regression was used for multivariate analysis of time spent in restaurants. Significance set at P < .05. Factors related to use of and time spent in FF and FS restaurants included parental work schedules, fathers' use of such restaurants, and children's time spent in the family automobile. Parenting style, parental work, parental eating habits and perceptions of family meals, and children's other uses of their time influence children's use of and time spent in FF and FS restaurants. Copyright © 2011 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

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.

Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

PubMed

Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of more than 10% over the standard classification models, which can be translated to correct labeling of additional 400 - 500 readmissions for heart failure patients in the state of California over a year. Lastly, several key predictor identified from the HCUP data include the disposition location from discharge, the number of chronic conditions, and the number of acute procedures. It would be beneficial to apply simple decision rules obtained from the decision tree in an ad-hoc manner to guide the cohort stratification. It could be potentially beneficial to explore the effect of pairwise interactions between influential predictors when building the logistic regression models for different data strata. Judicious use of the ad-hoc CLR models developed offers insights into future development of prediction models for hospital readmissions, which can lead to better intuition in identifying high-risk patients and developing effective post-discharge care strategies. Lastly, this paper is expected to raise the awareness of collecting data on additional markers and developing necessary database infrastructure for larger-scale exploratory studies on readmission risk prediction.

Prevalence and risk factors of depressive disorder in caregivers of patients with head and neck cancer.

PubMed

Lee, Yu; Lin, Pao-Yen; Chien, Chih-Yen; Fang, Fu-Min

2015-02-01

The purpose of this study is to examine the prevalence and risk factors of depressive disorder in caregivers of patients with head and neck cancer. Study subjects were recruited from a multidisciplinary outpatient clinic for head and neck cancer in a medical center from February to July 2012. Caregivers of patients with head and neck cancer were enrolled and assessed using the Structured Clinical Interview for the DSM-IV, Clinician Version, the Short Form 36 Health Survey, and the Family APGAR index. The main aim of the study was to examine the difference in demographic data and clinical characteristics between the caregivers with and without depressive disorders. In addition, a stepwise forward model of logistic regression was used to test the possible risk factors. One hundred and forty-three caregivers were included in the study. The most prevalent psychiatric disorder was depressive disorder (14.7%), followed by adjustment disorder (13.3%). Nearly one-third of the caregivers had a psychiatric diagnosis. By using logistic regression analysis, it was found that unemployment (odds ratio (OR) = 3.16; 95% CI, 1.04-9.68), lower social functioning (OR = 1.43; 95% CI, 1.18-1.72), and lower educational level (OR = 1.16; 95% CI, 1.01-1.34) were significant risk factors for the depressive disorder. The clinical implication of our results is the value of using the standardized structured interview for early diagnosis of depressive disorder in caregivers of head and neck cancer patients. Early screening and management of depression in these caregivers will raise their quality of life and capability to care patients. Copyright © 2014 John Wiley & Sons, Ltd.

Etiological Risk Factors for Sibling Incest: Data From an Anonymous Computer-Assisted Self-Interview.

PubMed

Griffee, Karen; Swindell, Sam; O'Keefe, Stephen L; Stroebel, Sandra S; Beard, Keith W; Kuo, Shih-Ya; Stroupe, Walter

2016-10-01

Retrospective data from 1,821 women and 1,064 men with one or more siblings, provided anonymously using a computer-assisted self-interview, were used to identify risk factors for sibling incest (SI); 137 were participants in SI. In order of decreasing predictive power, the risk factors identified by the multiple logistic regression analysis included ever having shared a bed for sleeping with a sibling, parent-child incest (PCI), family nudity, low levels of maternal affection, and ever having shared a tub bath with a sibling. The results were consistent with the idea that SI in many families was the cumulative result of four types of parental behaviors: (a) factors that lower external barriers to sexual behavior (e.g., permitting co-sleeping or co-bathing of sibling dyads), (b) factors that encourage nudity of children within the nuclear family and permit children to see the parent's genitals, (c) factors that lead to the siblings relying on one another for affection (e.g., diminished maternal affection), and (d) factors that eroticize young children (e.g., child sexual abuse [CSA] by a parent). Thirty-eight of the 137 SI participants were participants in coerced sibling incest (CSI). In order of decreasing predictive power, risk factors for CSI identified by multiple logistic regression analysis included ever having shared a bed for sleeping with a brother, PCI, witnessing parental physical fighting, and family nudity. SI was more likely to have been reported as CSI if the sibling had touched the reporting sibling's genitals, and less likely to have been reported as CSI if the siblings had shared a bed. © The Author(s) 2014.

Racial Differences in Satisfaction with VA Health Care: A Mixed Methods Pilot Study.

PubMed

Zickmund, Susan L; Burkitt, Kelly H; Gao, Shasha; Stone, Roslyn A; Rodriguez, Keri L; Switzer, Galen E; Shea, Judy A; Bayliss, Nichole K; Meiksin, Rebecca; Walsh, Mary B; Fine, Michael J

2015-09-01

As satisfied patients are more adherent and play a more active role in their own care, a better understanding of factors associated with patient satisfaction is important. In response to a United States Veterans Administration (VA) Hospital Report Card that revealed lower levels of satisfaction with health care for African Americans compared to Whites, we conducted a mixed methods pilot study to obtain preliminary qualitative and quantitative information about possible underlying reasons for these racial differences. We conducted telephone interviews with 30 African American and 31 White veterans with recent inpatient and/or outpatient health care visits at three urban VA Medical Centers. We coded the qualitative interviews in terms of identified themes within defined domains. We summarized racial differences using ordinal logistic regression for Likert scale outcomes and used random effects logistic regression to assess racial differences at the domain level. Compared to Whites, African Americans were younger (p < 0.001) and better educated (p = 0.04). Qualitatively, African Americans reported less satisfaction with trust/confidence in their VA providers and healthcare system and less satisfaction with patient-provider communication. Quantitatively, African Americans reported less satisfaction with outpatient care (odds ratio = 0.28; 95 % confidence interval (CI) 0.10-0.82), but not inpatient care. At the domain level, African Americans were significantly less likely than Whites to express satisfaction themes in the domain of trust/confidence (odds ratio = 0.36; 95 % CI 0.18-0.73). The current pilot study demonstrates racial differences in satisfaction with outpatient care and identifies some specific sources of dissatisfaction. Future research will include a large national cohort, including Hispanic veterans, in order to gain further insight into the sources of racial and ethnic differences in satisfaction with VA care and inform future interventions.

Loss of social resources predicts incident posttraumatic stress disorder during ongoing political violence within the Palestinian Authority.

PubMed

Hall, Brian J; Murray, Sarah M; Galea, Sandro; Canetti, Daphna; Hobfoll, Stevan E

2015-04-01

Exposure to ongoing political violence and stressful conditions increases the risk of posttraumatic stress disorder (PTSD) in low-resource contexts. However, much of our understanding of the determinants of PTSD in these contexts comes from cross-sectional data. Longitudinal studies that examine factors associated with incident PTSD may be useful to the development of effective prevention interventions and the identification of those who may be most at-risk for the disorder. A 3-stage cluster random stratified sampling methodology was used to obtain a representative sample of 1,196 Palestinian adults living in Gaza, the West Bank and East Jerusalem. Face-to-face interviews were conducted at two time points 6-months apart. Logistic regression analyses were conducted on a restricted sample of 643 people who did not have PTSD at baseline and who completed both interviews. The incidence of PTSD was 15.0 % over a 6-month period. Results of adjusted logistic regression models demonstrated that talking to friends and family about political circumstances (aOR = 0.78, p = 0.01) was protective, and female sex (aOR = 1.76, p = 0.025), threat perception of future violence (aOR = 1.50, p = 0.002), poor general health (aOR = 1.39, p = 0.005), exposure to media (aOR = 1.37, p = 0.002), and loss of social resources (aOR = 1.71, p = 0.006) were predictive of incident cases of PTSD. A high incidence of PTSD was documented during a 6-month follow-up period among Palestinian residents of Gaza, the West Bank, and East Jerusalem. Interventions that promote health and increase and forestall loss to social resources could potentially reduce the onset of PTSD in communities affected by violence.

Prevalence and risk factors for intimate partner violence among Grade 8 learners in urban South Africa: baseline analysis from the Skhokho Supporting Success cluster randomised controlled trial.

PubMed

Shamu, Simukai; Gevers, Anik; Mahlangu, B Pinky; Jama Shai, P Nwabisa; Chirwa, Esnat D; Jewkes, Rachel K

2016-01-01

Intimate partner violence (IPV) is a serious public health problem among adolescents. This study investigated the prevalence of and factors associated with Grade 8 girls' experience and boys' perpetration of IPV in South Africa. Participants were interviewed using interviewer-administered questionnaires about IPV, childhood violence, bullying, gender attitudes, alcohol use and risky sexual behaviours. Multiple logistic regression analysis was conducted to assess factors associated with girls' experience and boys' perpetration of IPV. Structural equation modelling (SEM) was conducted to assess the pathways to IPV experience and perpetration. Results show dating relationships are common among girls (52.5%) and boys (70.7%) and high prevalence of sexual or physical IPV experience by girls (30.9%; 95% CI: 28.2-33.7) and perpetration by boys (39.5%; 95% CI: 36.6-42.3). The logistic regression model showed factors associated with girls' experience of IPV include childhood experience of violence, individual gender inequitable attitudes, corporal punishment at home and in school, alcohol use, wider communication with one's partner and being more negative about school. We found three pathways from childhood trauma to IPV experience and perpetration in both models and these are through inequitable gender attitudes and risky sex, bullying and alcohol use. Prevention of IPV in children needs to encompass prevention of exposure to trauma in childhood and addressing gender attitudes and social norms to encourage positive disciplining approaches. : The trial is registered on ClinicalTrials.gov as NCT02349321. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Factors related to tooth loss due to dental caries among workers in an industrial estates in Thailand.

PubMed

Chatrchaiwiwatana, Supaporn; Ratanasiri, Amornrat; Jaidee, Jeeratip; Soontorn, Surasak

2012-11-01

The present study aimed to evaluate the prevalence and factors related to tooth loss due to dental caries among workers in industrial estates in Pathumthani and Phranakhorn Si Ayutthaya provinces in central Thailand. The present study utilized quantitative and qualitative methodologies. A quantitative study was done using a cross-sectional analytic method with a sample group of 457 adults (283 males; 174 females) between 19 and 53 years. Data were obtained through an oral examination and oral health behavior questionnaire. Data analyses were done using descriptive, bivariate and multivariable logistic regression statistics. In-depth interviews were used to collect qualitative data from 11 subjects. Most (62.2%) participants had tooth loss due to caries and findings from the final multivariable logistic regression model revealed that such loss was associated with education, residency, use of social security welfare, decayed teeth and filled teeth. Relatedly, the in-depth interview confirmed that tooth loss due to dental caries was related to (1) lack of time to visit a dentist (2) have a negative attitude toward or a phobia regarding dental treatment (3) inability to afford the high cast of dental treatment (4) lack of knowledge in regarding dental caries prevention, root canal treatment and the harmful effects of losing teeth (5) choosing to get an extraction upon having caries exposed pulp and (6) lack of oral health promotion programs provided by either the government or private sectors. The government and non-government organizations should promote oral health in an industrial estates and provide services and welfare for dental health of workers in an industrial estate appropriate to their socio-economic needs.

[Behaviors on drug-abuse and prevalence of sexually transmitted diseases among drug users in Tianjin, China, from 2011 to 2015].

PubMed

Guo, Y; Zhou, N; Li, J; Ning, T L; Guo, W

2016-02-01

To understand the change of behavioral characteristics among drug users (DUS) in Tianjin and the prevalence rates of major sexually transmitted disease infections. A series of cross-sectional surveys were used. Between April and June, 2011 to 2015, a cross-sectional survey with face to face interview, was undertaken. Interview was conducted among DUS who entered the drug rehabilitation center and blood samples were drawn to test for HIV/syphilis/HCV infections. Multivariate logistic regression analysis was used to analyze the relationship between the infection of major sexually transmitted diseases and drug abuse or sexual behavior. 2 000 DUS were included during the 5-year study, with the average age of the DUS as 34.5 ± 8.7. Female accounted for 17.9% and club drug (new drugs) users accounted 45.4% of the participants, with its proportion increasing over the years. Comparing to traditional drug users, club drug users showed more sexual activities with partners, but lower proportion of condom use. Prevalence rates of HIV/Syphilis and HCV were 1.3%, 11.0%, 52.0%, respectively. The prevalence of syphilis among club drug users was significantly higher than those on traditional-drug use (χ(2)=67.778,P<0.001). Data from Binary logistic regression analysis showed that club drug use (adjusted OR=1.607, 95% CI:1.191-2.170) and females (adjusted OR=5.287, 95%CI: 3.824-7.311) were associated with syphilis infection among DUS. Drug abuse behavior changed among the drug abuse in Tianjin. Proportion of club drug use continued to increase so as the risk of infected sexually transmitted diseases.

Predictors of asthma control in children from different ethnic origins living in Amsterdam.

PubMed

van Dellen, Q M; Stronks, K; Bindels, P J E; Ory, F G; Bruil, J; van Aalderen, W M C

2007-04-01

To identify factors associated with asthma control in a multi-ethnic paediatric population. We interviewed 278 children with paediatrician diagnosed asthma (aged 7-17 years) and one of their parents. Asthma control was assessed with the Asthma Control Questionnaire (ACQ). Detailed information about sociodemographic variables, asthma medication, knowledge of asthma, inhalation technique and environmental factors were collected. Turkish and Moroccan parents were interviewed in their language of choice. Logistic regression analyses were used to identify correlates of asthma control. Of the 278 children, 85 (30.6%) were Dutch, 84 (30.2%) were Moroccan, 58 (20.9%) were Turkish and 51 (18.3%) were Surinamese. Overall, almost 60% had a status of well-controlled asthma, as indicated by the ACQ. Only 51 of the 142 (35.9%) Moroccan and Turkish parents had a good comprehension of the Dutch language. In logistic regression analyses the risk of having uncontrolled asthma was significantly higher among Surinamese children (OR 2.3; 95% CI 1.06-4.83), respondents with insufficient comprehension of the Dutch language (OR 2.3; 95% CI 1.08-4.78), children using woollen blankets (OR 9.8; 95% CI 1.52-63.42), and significantly lower among male (OR 0.5; 95% CI 0.31-0.91) and non-daily users of inhaled corticosteroids (OR 0.6; 95% CI 0.38-1.07). In conclusion, ethnicity as well as insufficient comprehension of the Dutch language appeared to be independent risk factors for uncontrolled asthma. Special attention should be given to children from immigrants groups for example by calling in an interpreter by physicians when comprehension is insufficient.

Personality disorders and health problems distinguish suicide attempters from completers in a direct comparison.

PubMed

Giner, Lucas; Blasco-Fontecilla, Hilario; Mercedes Perez-Rodriguez, M; Garcia-Nieto, Rebeca; Giner, Jose; Guija, Julio A; Rico, Antonio; Barrero, Enrique; Luna, Maria Angeles; de Leon, Jose; Oquendo, Maria A; Baca-Garcia, Enrique

2013-11-01

Whether suicide attempters and completers represent the same population evaluated at different points along a progression towards suicide death, overlapping populations, or completely different populations is a problem still unresolved. 446 Adult suicide attempters and knowledgeable collateral informants for 190 adult suicide probands were interviewed. Sociodemographic and clinical data was collected for both groups using semi-structured interviews and structured assessments. Univariate analyses and logistic regression models were conducted to explore the similarities and differences between suicide attempters and completers. Univariate analyses yielded significant differences in sociodemographics, recent life events, impulsivity, suicide intent, and distribution of Axis I and II disorders. A logistic regression model aimed at distinguishing suicide completers from attempters properly classified 90% of subjects. The most significant variables that distinguished suicide from attempted suicide were the presence of narcissistic personality disorder (OR=21.4; 95% CI=6.8-67.7), health problems (OR=20.6; 95% CI=5.6-75.9), male sex (OR=9.6; 95% CI=4.42-20.9), and alcohol abuse (OR=5.5; 95% CI=2.3-14.2). Our study shares the limitations of studies comparing suicide attempters and completers, namely that information from attempters can be obtained from the subject himself, whereas the assessment of completers depends on information from close family or friends. Furthermore, different semi-structured instruments assessed Axis I and Axis II disorders in suicide attempters and completers. Finally, we have no data on inter-rater reliability data. Suicide completers are more likely to be male and suffer from alcohol abuse, health problems (e.g. somatic illness), and narcissistic personality disorder. The findings emphasize the importance of implementing suicide prevention programs tailored to suicide attempters and completers. © 2013 Elsevier B.V. All rights reserved.

Prevalence of obsessive-compulsive disorder in Turkish university students and assessment of associated factors

PubMed Central

Yoldascan, Elcin; Ozenli, Yarkin; Kutlu, Oguz; Topal, Kenan; Bozkurt, Ali Ihsan

2009-01-01

Background Many students who begin university at risky periods for OCD development cannot meet the new challenges successfully. They often seek help and apply to the university health center for psychiatric distress. We aimed to determine the prevalence and associated factors of Obsessive Compulsive Disorder (OCD) at students of the Cukurova University in this cross sectional study. Methods This study was performed in the Cukurova University Faculty of Education with a population of 5500 students; the representative sample size for detecting the OCD prevalence was calculated to be 800. After collecting sociodemographic data, we questioned the students for associated factors of OCD. The General Health Questionnaire-12 (GHQ-12) and Composite International Diagnostic Interview (CIDI, Section K) were used for psychiatric evaluation. Logistic regression analysis was performed to evaluate the linkage between OCD and associated factors. Results A total of 804 university students were included in this study. The GHQ-12-positive students (241 students, 29.9%) were interviewed using Section K of the CIDI (222 students, 27.6%). OCD was diagnosed in 33 (4.2%) students. The Logistic regression analysis of the data showed significant associations between OCD and male gender (p:0.036), living on government dormitory (p: 0.003), living on students' house/parental house (p:0.006), having private room in the parental house (p:0.055) and verbal abuse in the family (p:0.006). Conclusion This study demonstrates a higher prevalence of OCD among a group of university students compared to other prevalence studies of OCD in Turkish society. Furthermore, our findings also suggest relationships between OCD and sociodemographic factors, as well as other environmental stress factors. PMID:19580658

Blended learning in situated contexts: 3-year evaluation of an online peer review project.

PubMed

Bridges, S; Chang, J W W; Chu, C H; Gardner, K

2014-08-01

Situated and sociocultural perspectives on learning indicate that the design of complex tasks supported by educational technologies holds potential for dental education in moving novices towards closer approximation of the clinical outcomes of their expert mentors. A cross-faculty-, student-centred, web-based project in operative dentistry was established within the Universitas 21 (U21) network of higher education institutions to support university goals for internationalisation in clinical learning by enabling distributed interactions across sites and institutions. This paper aims to present evaluation of one dental faculty's project experience of curriculum redesign for deeper student learning. A mixed-method case study approach was utilised. Three cohorts of second-year students from a 5-year bachelor of dental surgery (BDS) programme were invited to participate in annual surveys and focus group interviews on project completion. Survey data were analysed for differences between years using multivariate logistical regression analysis. Thematic analysis of questionnaire open responses and interview transcripts was conducted. Multivariate logistic regression analysis noted significant differences across items over time indicating learning improvements, attainment of university aims and the positive influence of redesign. Students perceived the enquiry-based project as stimulating and motivating, and building confidence in operative techniques. Institutional goals for greater understanding of others and lifelong learning showed improvement over time. Despite positive scores, students indicated global citizenship and intercultural understanding were conceptually challenging. Establishment of online student learning communities through a blended approach to learning stimulated motivation and intellectual engagement, thereby supporting a situated approach to cognition. Sociocultural perspectives indicate that novice-expert interactions supported student development of professional identities. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Motivational Interviewing Fidelity in a Community Corrections Setting: Treatment Initiation and Subsequent Drug Use.

PubMed

Spohr, Stephanie A; Taxman, Faye S; Rodriguez, Mayra; Walters, Scott T

2016-06-01

Although substance use is common among people in the U.S. criminal justice system, treatment initiation remains an ongoing problem. This study assessed the reliability and predictive validity of the Motivational Interviewing Treatment Integrity 3.1.1. (MITI) coding instrument in a community corrections sample. We used data from 80 substance-using clients who were participating in a clinical trial of MI in a probation setting. We analyzed 124 MI counseling sessions using the MITI, a coding system for documenting MI fidelity. Bivariate associations and logistic regression modeling were used to determine if MI-consistent behaviors predicted substance use or treatment initiation at a 2-month follow-up. We found a high level of agreement between coders on behavioral utterance counts. Counselors met at least beginning proficiency on most MITI summary scores. Probationers who initiated treatment at 2-month follow-up had significantly higher ratings of clinician empathy and MI spirit than clients who did not initiate treatment. Other MITI summary scores were not significantly different between clients who had initiated treatment and those who did not. MI spirit and empathy ratings were entered into a forward logistic regression in which MI spirit significantly predicted 2-month treatment initiation (χ(2) (1)=4.10, p<.05, R(2)=.05) but counselor empathy did not. MITI summary scores did not predict substance use at 2-month follow-up. Counselor MI-consistent relational skills were an important predictor of client treatment initiation. Counselor behaviors such as empathy and MI spirit may be important for developing client rapport with people in a probation setting. Copyright © 2015. Published by Elsevier Inc.

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Differentially private distributed logistic regression using private and public data

PubMed Central

2014-01-01

Background Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. Methodology In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. Experiments and results We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Conclusion Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee. PMID:25079786

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

PubMed

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

NASA Astrophysics Data System (ADS)

Mei, Zhixiong; Wu, Hao; Li, Shiyun

2018-06-01

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the simulated change sizes and locations of each land-use type under different scenarios. The results not only demonstrate the validity of the improved model but also provide a valuable reference for relevant policy-makers.

Factors Associated With Volunteering Among Racial/Ethnic Groups: Findings From the California Health Interview Survey.

PubMed

Johnson, Kimberly J; Lee, S Hannah

2017-06-01

The present study investigated how volunteering was influenced by individual resources and social capital among four racial/ethnic groups of adults aged 50 and older. The data came from the California Health Interview Survey, a statewide sample that includes non-Hispanic Whites ( n = 18,927), non-Hispanic Asians ( n = 2,428), non-Hispanic Blacks ( n = 1,265), and Hispanics ( n = 3,799). Logistic regression models of volunteering were estimated to explore the effects of human and social capital within and across the racial/ethnic groups. Compared to Whites, racial/ethnic minority adults volunteered less. Although education was a significant predictor of volunteering across all groups, the findings indicated group-specific factors related to human and social capital. Results showed similarities and differences associated with volunteer participation among diverse racial/ethnic groups. The findings underscore the importance of understanding ways of creating inclusive opportunities for civic engagement among an increasingly diverse population.

Activity-Limiting Musculoskeletal Conditions in US Veterans Compared to Non-Veterans: Results from the 2013 National Health Interview Survey

PubMed Central

Hinojosa, Ramon

2016-01-01

Past military service is associated with health outcomes, both positive and negative. In this study we use the 2013 National Health Interview Survey to examine the constellation of conditions referred to as musculoskeletal disorders (MSDs) for Veterans and non-veterans with health conditions that limit their daily activities. Multivariate logistic regression analysis reveal that Veterans are more likely to report MSDs like neck and back problems, fracture bone and joint problems as an activity limiting problem compared to non-veterans. The relationship between age and reports of activity limiting MSDs is moderated by Veteran status. Veterans in this sample report more activity limiting MSDs at younger ages compared to non-veterans and fewer MSDs at older ages. This research contributes to our understanding of potentially limiting health conditions at earlier ages for Veterans. PMID:28005905

Factors associated with the use of social workers for assistance with lifetime and 12-month behavioral health disorders.

PubMed

Woodward, Amanda Toler; Taylor, Robert Joseph

2018-04-01

This study examined the use of social workers for assistance with a behavioral health disorder. Data were from the Collaborative Psychiatric Epidemiology Surveys. The analytic sample included respondents who reported using professional services for assistance with a behavioral health disorder during their lifetime (n = 5,585). Logistic regression was used to examine the use of a social worker during the respondent's lifetime or 12 months prior to the interview. Ten percent of respondents visited a social worker for help with a behavioral health disorder during their lifetime and 3% did so in the 12 months prior to the interview. Women were less likely than men to report using a social worker. Those who visited a social worker tended to also use other professionals for a behavioral health disorder although overall respondents reported visiting social workers less frequently for this reason than other types of professionals.

Morbidity ranking of U.S. workers employed in 206 occupations: the National Health Interview Survey (NHIS) 1986-1994.

PubMed

Lee, David J; Fleming, Lora E; Gómez-Marín, Orlando; LeBlanc, William G; Arheart, Kristopher L; Caban, Alberto J; Christ, Sharon L; Chung-Bridges, Katherine; Pitman, Terry

2006-02-01

The objective of this study was to rank U.S. occupations by worker morbidity. From 1986 through 1994, morbidity information was collected on over 410,000 U.S. workers who participated in the National Health Interview Survey, an annual household survey representative of the U.S. civilian noninstitutionalized population. A multivariate adjusted logistic regression morbidity summary score was created for each worker group based on seven indicators: days of restricted activity, bedrest, and missed work in the previous 2 weeks; doctor visits and hospitalizations in the previous 12 months; reported health conditions; and health status. Worker groups reporting the greatest morbidity included social workers, inspectors, postal clerks, psychologists, and grinding machine operators; worker groups reporting the least morbidity included dentists, pilots, physicians, pharmacists, and dietitians. These findings aid in the identification of worker groups that require increased attention for morbidity research and prevention.

Does Timing of Internal Medicine Residency Interview Affect Likelihood of Matching?

PubMed

Heidemann, Danielle L; Thompson, Elizabeth; Drake, Sean M

2016-08-01

Applicants to our internal medicine (IM) residency program consistently have shared concerns about whether the interview date influences their ability to match via the National Residency Matching Program. We performed a retrospective study to assess whether interview timing was associated with successful matching at our IM program. We identified all of the applicants who interviewed for a first-year position with our IM residency program from 2010 to 2014. Each year's interview dates were totaled and divided equally into three categories: early, middle, or late. Baseline demographics, United States Medical Licensing Examination scores, and type of medical school (American or international) were compared among the interview date groups and between those who did and did not match at our program. Of 914 interviewees, 311 interviewed early (October/November), 299 interviewed in the middle (December), and 304 interviewed late (January). The proportion to match at our program was similar in each interview group (12.5%, 18.4%, 15.1%, respectively; P = 0.133). Logistic regression analysis showed that the middle interview group had increased odds to match compared with the early group (odds ratio 1.590; P = 0.044). The late-versus-early group showed no difference (P = 0.362). No significant differences were found with type of medical school or United States Medical Licensing Examination scores. Of all of the interviewees participating in the match, nearly all matched into a program somewhere, with no significant difference based on interview timing. When considering all of the interviewees, interview date showed no major influence on matching. Only the middle interview time period showed a slight increased chance of matching to our IM program, but the significance was marginal.

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Binary logistic regression-Instrument for assessing museum indoor air impact on exhibits.

PubMed

Bucur, Elena; Danet, Andrei Florin; Lehr, Carol Blaziu; Lehr, Elena; Nita-Lazar, Mihai

2017-04-01

This paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The prediction of the impact on the exhibits during certain pollution scenarios (environmental impact) was calculated by a mathematical model based on the binary logistic regression; it allows the identification of those environmental parameters from a multitude of possible parameters with a significant impact on exhibitions and ranks them according to their severity effect. Air quality (NO 2 , SO 2 , O 3 and PM 2.5 ) and microclimate parameters (temperature, humidity) monitoring data from a case study conducted within exhibition and storage spaces of the Romanian National Aviation Museum Bucharest have been used for developing and validating the binary logistic regression method and the mathematical model. The logistic regression analysis was used on 794 data combinations (715 to develop of the model and 79 to validate it) by a Statistical Package for Social Sciences (SPSS 20.0). The results from the binary logistic regression analysis demonstrated that from six parameters taken into consideration, four of them present a significant effect upon exhibits in the following order: O 3 >PM 2.5 >NO 2 >humidity followed at a significant distance by the effects of SO 2 and temperature. The mathematical model, developed in this study, correctly predicted 95.1 % of the cumulated effect of the environmental parameters upon the exhibits. Moreover, this model could also be used in the decisional process regarding the preventive preservation measures that should be implemented within the exhibition space. The paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The mathematical model developed on the environmental parameters analyzed by the binary logistic regression method could be useful in a decision-making process establishing the best measures for pollution reduction and preventive preservation of exhibits.

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

Content analysis of antiretroviral adherence enhancing interview reports.

PubMed

Kamal, Susan; Nulty, Paul; Bugnon, Olivier; Cavassini, Matthias; Schneider, Marie P

2018-05-17

To identify factors associated with low or high antiretroviral (ARV) adherence through computational text analysis of an adherence enhancing programme interview reports. Using text from 8428 interviews with 522 patients, we constructed a term-frequency matrix for each patient, retaining words that occurred at least ten times overall and used in at least six interviews with six different patients. The text included both the pharmacist's and the patient's verbalizations. We investigated their association with an adherence threshold (above or below 90%) using a regularized logistic regression model. In addition to this data-driven approach, we studied the contexts of words with a focus group. Analysis resulted in 7608 terms associated with low or high adherence. Terms associated with low adherence included disruption in daily schedule, side effects, socio-economic factors, stigma, cognitive factors and smoking. Terms associated with high adherence included fixed medication intake timing, no side effects and positive psychological state. Computational text analysis helps to analyze a large corpus of adherence enhancing interviews. It confirms main known themes affecting ARV adherence and sheds light on new emerging themes. Health care providers should be aware of factors that are associated with low or high adherence. This knowledge should reinforce the supporting factors and try to resolve the barriers together with the patient. Copyright © 2018 Elsevier B.V. All rights reserved.

Mixed conditional logistic regression for habitat selection studies.

PubMed

Duchesne, Thierry; Fortin, Daniel; Courbin, Nicolas

2010-05-01

1. Resource selection functions (RSFs) are becoming a dominant tool in habitat selection studies. RSF coefficients can be estimated with unconditional (standard) and conditional logistic regressions. While the advantage of mixed-effects models is recognized for standard logistic regression, mixed conditional logistic regression remains largely overlooked in ecological studies. 2. We demonstrate the significance of mixed conditional logistic regression for habitat selection studies. First, we use spatially explicit models to illustrate how mixed-effects RSFs can be useful in the presence of inter-individual heterogeneity in selection and when the assumption of independence from irrelevant alternatives (IIA) is violated. The IIA hypothesis states that the strength of preference for habitat type A over habitat type B does not depend on the other habitat types also available. Secondly, we demonstrate the significance of mixed-effects models to evaluate habitat selection of free-ranging bison Bison bison. 3. When movement rules were homogeneous among individuals and the IIA assumption was respected, fixed-effects RSFs adequately described habitat selection by simulated animals. In situations violating the inter-individual homogeneity and IIA assumptions, however, RSFs were best estimated with mixed-effects regressions, and fixed-effects models could even provide faulty conclusions. 4. Mixed-effects models indicate that bison did not select farmlands, but exhibited strong inter-individual variations in their response to farmlands. Less than half of the bison preferred farmlands over forests. Conversely, the fixed-effect model simply suggested an overall selection for farmlands. 5. Conditional logistic regression is recognized as a powerful approach to evaluate habitat selection when resource availability changes. This regression is increasingly used in ecological studies, but almost exclusively in the context of fixed-effects models. Fitness maximization can imply differences in trade-offs among individuals, which can yield inter-individual differences in selection and lead to departure from IIA. These situations are best modelled with mixed-effects models. Mixed-effects conditional logistic regression should become a valuable tool for ecological research.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

Risk factors of substance use among street children from Delhi.

PubMed

Pagare, Deepti; Meena, G S; Singh, M M; Sahu, Renuka

2004-03-01

To estimate the magnitude of and socio-demographic factors related to substance use among street children in Delhi. Observational study. 115 male street children aged 6 to 16 years were interviewed at the time of their admission to an observation home. More than half of the subjects had indulged in substance use before coming to the observation home. The agents consumed were nicotine,inhalants, alcohol and cannabis. On application of multiple logistic regression, maltreatment of the child by family members was found significant predictor of substance use in the study group. Substance use in street children is associated with unstable homes and maltreatment.

No higher risk of problem drinking or mental illness for women in male-dominated occupations.

PubMed

Savikko, Annukka; Lanne, Matilda; Spak, Fredrik; Hensing, Gunnel

2008-07-01

A sample of 562 women were drawn from the general population study "Women and alcohol in Goteborg" (N = 8335). An initial screening phase was followed by interviews regarding work, alcohol, and mental illness. Data from 1990 and 1995 were analyzed. Logistic regressions were used to calculate odds ratios. Contradictory to earlier studies we found no higher risk for alcohol problems/mental illness among women in male-dominated occupations. Selection and changes in cultural norms can be explanations. Study limitations included use of occupations at an aggregated level. The Swedish Council financially supported the study for Working Life and Social Research.

Why do they leave? Factors associated with job termination among personal assistant workers in home care.

PubMed

Butler, Sandra S; Simpson, Nan; Brennan, Mark; Turner, Winston

2010-11-01

Recruiting and retaining an adequate number of personal support workers in home care is both challenging and essential to allowing elders to age in place. A mixed-method, longitudinal study examined turnover in a sample of 261 personal support workers in Maine; 70 workers (26.8%) left their employment in the first year of the study. Logistic regression analysis indicated that younger age and lack of health insurance were significant predictors of turnover. Analysis of telephone interviews revealed three overarching themes related to termination: job not worthwhile, personal reasons, and burnout. Implications of study findings for gerontological social workers are outlined.

Parental History of Type 2 Diabetes in Patients with Nonaffective Psychosis

PubMed Central

Fernandez-Egea, Emilio; Miller, Brian; Bernardo, Miguel; Donner, Thomas; Kirkpatrick, Brian

2009-01-01

Introduction We attempted to replicate two previous studies which found an increased risk of diabetes in the relatives of schizophrenia probands. Methods N=34 patients with newly-diagnosed nonaffective psychosis and N=52 non-psychiatric controls were interviewed for parental history of Type 2 diabetes. Results In a logistic regression model that included multiple potential confounders, psychosis was a significant predictor of Type 2 diabetes in either parent (p<0.04). Discussion We found an increased prevalence of Type 2 diabetes in the parents of nonaffective psychosis subjects. This association may be due to shared environmental or genetic risk factors, or both. PMID:18031995

An Empirical Analysis of the Default Rate of Informal Lending—Evidence from Yiwu, China

NASA Astrophysics Data System (ADS)

Lu, Wei; Yu, Xiaobo; Du, Juan; Ji, Feng

This study empirically analyzes the underlying factors contributing to the default rate of informal lending. This paper adopts snowball sampling interview to collect data and uses the logistic regression model to explore the specific factors. The results of these analyses validate the explanation of how the informal lending differs from the commercial loan. Factors that contribute to the default rate have particular attributes, while sharing some similarities with commercial bank or FICO credit scoring Index. Finally, our concluding remarks draw some inferences from empirical analysis and speculate as to what this may imply for the role of formal and informal financial sectors.

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Socioeconomic and Cultural Correlates of Diet Quality in the Canadian Arctic: Results from the 2007-2008 Inuit Health Survey.

PubMed

Galloway, Tracey; Johnson-Down, Louise; Egeland, Grace M

2015-09-01

We examined the impact of socioeconomic and cultural factors on dietary quality in adult Inuit living in the Canadian Arctic. Interviews and a 24-h dietary recall were administered to 805 men and 1292 women from Inuit regions in the Canadian Arctic. We examined the effect of age, sex, education, income, employment, and cultural variables on respondents' energy, macronutrient intake, sodium/potassium ratio, and healthy eating index. Logistic regression was used to assess the impact of socioeconomic status (SES) on diet quality indicators. Age was positively associated with traditional food (TF) consumption and greater energy from protein but negatively associated with total energy and fibre intake. Associations between SES and diet quality differed considerably between men and women and there was considerable regional variability in diet quality measures. Age and cultural variables were significant predictors of diet quality in logistic regression. Increased age and use of the Inuit language in the home were the most significant predictors of TF consumption. Our findings are consistent with studies reporting a nutrition transition in circumpolar Inuit. We found considerable variability in diet quality and complex interaction between SES and cultural variables producing mixed effects that differ by age and gender.

Lower urinary tract symptoms and erectile dysfunction associated with depression among Japanese patients with late-onset hypogonadism symptoms.

PubMed

Takao, Tetsuya; Tsujimura, Akira; Okuda, Hidenobu; Yamamoto, Keisuke; Fukuhara, Shinichiro; Matsuoka, Yasuhiro; Miyagawa, Yasushi; Nonomura, Norio; Okuyama, Akihiko

2011-06-01

The aim of this study was to investigate the relation between lower urinary tract symptoms (LUTS), erectile dysfunction (ED) and depression in Japanese patients with late-onset hypogonadism (LOH) symptoms. The study comprised 87 Japanese patients with LOH symptoms (>27 points on the Aging Males Symptoms Scale). Thirty-four patients were diagnosed as having depression and the remaining 53 patients were diagnosed as not having depression by the Mini International Neuropsychiatric Interview. We compared the International Index of Erectile Function (IIEF) 5, International Prostate Symptom Score (IPSS), IPSS quality-of-life (QOL) index, King's Health Questionnaire (KHQ), endocrinological data, and free uroflow study between depression and non-depression patients and performed multiple logistic regression analysis. IIEF5 scores of depression patients were significantly lower than those of non-depression patients. In KHQ, only the category of general health perceptions was significantly higher in depression patients than non-depression patients. However, IPSS, QOL index, and endocrinological and uroflowmetric data showed no significant difference between the groups. Multiple logistic regression analysis revealed moderate and severe ED to be risk factors for depression. However, LUTS are not related to depression. Moderate and severe ED is correlated with depression, whereas LUTS are not related to depression in Japanese LOH patients.

Heart rate reactivity and current post-traumatic stress disorder when data are missing.

PubMed

Jeon-Slaughter, Haekyung; Tucker, Phebe; Pfefferbaum, Betty; North, Carol S; de Andrade, Bernardo Borba; Neas, Barbara

2011-08-01

This study demonstrates that auxiliary and exclusion criteria variables increase the effectiveness of missing imputation in correcting underestimation of physiologic reactivity in relation to post-traumatic stress disorder (PTSD) caused by deleting cases with missing physiologic data. This study used data from survivors of the 1995 Oklahoma City bombing and imputed missing heart rate data using auxiliary and exclusion criteria variables. Logistic regression was used to examine heart rate reactivity in relation to current PTSD. Of 113 survivors who participated in the bombing study's 7-year follow-up interview, 42 (37%) had missing data on heart rate reactivity due to exclusion criteria (medical illness or use of cardiovascular or psychotropic medications) or non-participation. Logistic regression results based on imputed heart rate data using exclusion criteria and auxiliary (the presence of any current PTSD arousal symptoms) variables showed that survivors with current bombing-related PTSD had significantly higher heart rates at baseline and recovered more slowly back to baseline heart rate during resting periods than survivors without current PTSD, while results based on complete cases failed to show significant correlations between current PTSD and heart rates at any assessment points. Suggested methods yielded an otherwise undetectable link between physiology and current PTSD. © 2011 The Authors. Psychiatry and Clinical Neurosciences © 2011 Japanese Society of Psychiatry and Neurology.

Correlates of Suicidality: Investigation of a Representative Sample of Manitoba First Nations Adolescents

PubMed Central

Mota, Natalie; Elias, Brenda; Tefft, Bruce; Medved, Maria; Munro, Garry

2012-01-01

Objectives. We examined individual, friend or family, and community or tribe correlates of suicidality in a representative on-reserve sample of First Nations adolescents. Methods. Data came from the 2002–2003 Manitoba First Nations Regional Longitudinal Health Survey of Youth. Interviews were conducted with adolescents aged 12 to 17 years (n = 1125) from 23 First Nations communities in Manitoba. We used bivariate logistic regression analyses to examine the relationships between a range of factors and lifetime suicidality. We conducted sex-by-correlate interactions for each significant correlate at the bivariate level. A multivariate logistic regression analysis identified those correlates most strongly related to suicidality. Results. We found several variables to be associated with an increased likelihood of suicidality in the multivariate model, including being female, depressed mood, abuse or fear of abuse, a hospital stay, and substance use (adjusted odds ratio range = 2.43–11.73). Perceived community caring was protective against suicidality (adjusted odds ratio = 0.93; 95% confidence interval = 0.88, 0.97) in the same model. Conclusions. Results of this study may be important in informing First Nations and government policy related to the implementation of suicide prevention strategies in First Nations communities. PMID:22676500

Medication adherence among patients in a chronic disease clinic.

PubMed

Tourkmani, Ayla M; Al Khashan, Hisham I; Albabtain, Monirah A; Al Harbi, Turki J; Al Qahatani, Hala B; Bakhiet, Ahmed H

2012-12-01

To assess motivation and knowledge domains of medication adherence intention, and to determine their predictors in an ambulatory setting. We conducted a cross-sectional survey study among patients attending a chronic disease clinic at the Family and Community Medicine Department, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia between June and September 2010. Adherence intention was assessed using Modified Morisky Scale. Predictors of low motivation and/or knowledge were determined using logistic regression models. A total of 347 patients were interviewed during the study duration. Most patients (75.5%) had 2 or more chronic diseases with an average of 6.3 +/- 2.3 medications, and 6.5 +/- 2.9 pills per prescription. The frequency of adherence intention was low (4.6%), variable (37.2%), and high (58.2%). In multivariate logistic regression analysis, younger age and having asthma were significantly associated with low motivation, while male gender, single status, and not having hypertension were significantly associated with low knowledge. Single status was the only independent predictor of low adherence intention. In a population with multiple chronic diseases and high illiteracy rate, more than 40% had low/variable intention to adhere to prescribed medications. Identifying predictors of this group may help in providing group-specific interventional programs.

Statistical Modelling for Dropped Out School Children (DOSC) in East Nusa Tenggara Province Indonesia

NASA Astrophysics Data System (ADS)

Guntur, R. D.; Lobo, M.

2017-02-01

A research has been carried out to investigate the characteristics of reasons for DOSC and to determine the statistical model explaining factors which influence on the DOSC in the age group 7 - 18 years in East Nusa Tenggara (ENT) Province. Primary data of out of school children had been collected throughout interviews using prepared questionnaires in three selected districts. Data was then analysed using descriptive and logistic regression method. The analysis shows that from the 341 samples, there were 194DOSC. The majority of them were males, lived in the countryside, had farmer parents, had family size of 5, and had mothers with only primary education level. The main reasons of children to drop out from the primary and junior education levels were the inabilities of paying the school fees and the willingness to work in the farms to help their parents. For senior education level, it was because of the unaffordable school tuitions and no desire of children in having good education. Both partial and simultaneous parameter tests in the logistic regression model show that children who lived in countryside, from poor families, males were the three factors that significantly affected the number of DOSC in the group age with odds ratio values 2.48; 2.37; 1.97 respectively.

The prevalence of postpartum depression: the relative significance of three social status indices.

PubMed

Segre, Lisa S; O'Hara, Michael W; Arndt, Stephan; Stuart, Scott

2007-04-01

Little is known about the prevalence of clinically significant postpartum depression in women of varying social status. The purpose of the present study was to examine the prevalence of postpartum depression as a function of three indices of social status: income, education and occupational prestige. A sample of 4,332 postpartum women completed a demographic interview and the Inventory to Diagnose Depression, a self-report scale developed to identify a major depressive episode in accordance with DSM diagnostic criteria. Logistic regression was used to assess the relative significance of the three social status variables as risk factors for postpartum depression controlling for the effects of correlated demographic variables. In the logistic regression, income, occupational prestige, marital status, and number of children were significant predictors of postpartum depression controlling for the effects of other related demographic characteristics. The Wald Chi Square value for each of these significant predictors indicates that income was the strongest predictor. The prevalence of postpartum depression was significantly higher in financially poor relative to financially affluent women. Maternal depression screening programs targeting women who are financially poor are well placed. Future research is needed to replicate the present findings in a more ethnically diverse sample that includes the full age range of teenage mothers.

Malaria treatment-seeking behaviour and related factors of Wa ethnic minority in Myanmar: a cross-sectional study

PubMed Central

2012-01-01

Background In Southeast Asia, data on malaria treatment-seeking behaviours and related affecting factors are rare. The population of the Wa ethnic in Myanmar has difficulty in accessing formal health care. To understand malaria treatment-seeking behaviour and household-affecting factors of the Wa people, a cross-sectional study carried out in Shan Special Region II, Myanmar. Methods The two methods, questionnaire-based household surveys to household heads and in-depth interviews to key informants, were carried out independently. The proportion of treatment-seeking patterns was calculated. Logistic regression was used to determine affecting factors of treatment-seeking. Qualitative data were analysed by using Text Analysis Markup System. Results Overall, 87.5% of the febrile population sought treatment, but only 32.0% did so within 24 hours. The proportion accessing the retail sector (79.6%) was statistically significant higher (P<0.0001) than accessing the public sector (10.6%). Multivariable logistic regression analysis identified family income, distances from a health facility, family decision and patient characteristics being independently associated with delayed malaria treatment. Conclusion Malaria treatment-seeking behaviour is not appropriate, and affecting factors include health service systems, social and cultural factors in Wa State of Myanmar. PMID:23237576

Perception of Tourists Regarding the Smoke-Free Policy at Suvarnabhumi International Airport, Bangkok, Thailand

PubMed Central

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-01-01

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment. PMID:23999549

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

PubMed

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

Optimizing Call Patterns for Landline and Cell Phone Surveys.

PubMed

Reimer, Becky; Roth, Veronica; Montgomery, Robert

2012-01-01

Cell phone surveys have become increasingly popular and researchers have noted major challenges in conducting cost-effective surveys while achieving high response rates. Previous work has shown that calling strategies that maximize both respondent contact and completed interviews for landline surveys may not be the most cost-effective for cell phone surveys. For example, Montgomery, et al. (2011) found important differences between landline and cell samples for best times to call and declines in contact rates after repeated dialing. Using paradata from the 2010 and 2011 National Flu Surveys (sponsored by the Centers for Disease Control and Prevention), we investigate differences in calling outcomes between landline and cell surveys. Specifically, we predict respondent contact and interview completion using logistic regression models that examine the impact of calling on particular days of the week, certain times of the day, number of previous calls, outcomes of previous calls and length of time between calls. We discuss how these differences can be used to increase the likelihood of contacting cooperative respondents and completing interviews for both sample types.

Modifiable risk factors of ecstasy use: risk perception, current dependence, perceived control, and depression

PubMed Central

Leung, Kit Sang; Ben Abdallah, Arbi; Cottler, Linda B.

2009-01-01

Risk perception, perceived behavioral control of obtaining ecstasy (PBC-obtaining), current ecstasy dependence, and recent depression have been associated with past ecstasy use, however, their utility in predicting ecstasy use has not been demonstrated. This study aimed to determine whether these four modifiable risk factors could predict ecstasy use after controlling for socio-demographic covariates and recent polydrug use. Data from 601 ecstasy users in the National Institute on Drug Abuse funded TriCity Study of Club Drug Use, Abuse and Dependence were analyzed using multivariate logistic regression. Participants were interviewed twice within a 2-week period using standardized instruments. Thirteen percent (n=80) of the participants reported using ecstasy between the two interviews. Low risk perception, high PBC-obtaining (an estimated ecstasy procurement time < 24 hours), and current ecstasy dependence were statistically associated with ecstasy use between the two interviews. Recent depression was not a significant predictor. Despite not being a target predictor, recent polydrug use was also statistically associated with ecstasy use. The present findings may inform the development of interventions targeting ecstasy users. PMID:19880258

Estimating the exceedance probability of rain rate by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.; Kedem, Benjamin

1990-01-01

Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

Comparison of naïve Bayes and logistic regression for computer-aided diagnosis of breast masses using ultrasound imaging

NASA Astrophysics Data System (ADS)

Cary, Theodore W.; Cwanger, Alyssa; Venkatesh, Santosh S.; Conant, Emily F.; Sehgal, Chandra M.

2012-03-01

This study compares the performance of two proven but very different machine learners, Naïve Bayes and logistic regression, for differentiating malignant and benign breast masses using ultrasound imaging. Ultrasound images of 266 masses were analyzed quantitatively for shape, echogenicity, margin characteristics, and texture features. These features along with patient age, race, and mammographic BI-RADS category were used to train Naïve Bayes and logistic regression classifiers to diagnose lesions as malignant or benign. ROC analysis was performed using all of the features and using only a subset that maximized information gain. Performance was determined by the area under the ROC curve, Az, obtained from leave-one-out cross validation. Naïve Bayes showed significant variation (Az 0.733 +/- 0.035 to 0.840 +/- 0.029, P < 0.002) with the choice of features, but the performance of logistic regression was relatively unchanged under feature selection (Az 0.839 +/- 0.029 to 0.859 +/- 0.028, P = 0.605). Out of 34 features, a subset of 6 gave the highest information gain: brightness difference, margin sharpness, depth-to-width, mammographic BI-RADs, age, and race. The probabilities of malignancy determined by Naïve Bayes and logistic regression after feature selection showed significant correlation (R2= 0.87, P < 0.0001). The diagnostic performance of Naïve Bayes and logistic regression can be comparable, but logistic regression is more robust. Since probability of malignancy cannot be measured directly, high correlation between the probabilities derived from two basic but dissimilar models increases confidence in the predictive power of machine learning models for characterizing solid breast masses on ultrasound.

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Social network and individual correlates of sexual risk behavior among homeless young men who have sex with men.

PubMed

Tucker, Joan S; Hu, Jianhui; Golinelli, Daniela; Kennedy, David P; Green, Harold D; Wenzel, Suzanne L

2012-10-01

There is growing interest in network-based interventions to reduce HIV sexual risk behavior among both homeless youth and men who have sex with men. The goal of this study was to better understand the social network and individual correlates of sexual risk behavior among homeless young men who have sex with men (YMSM) to inform these HIV prevention efforts. A multistage sampling design was used to recruit a probability sample of 121 homeless YMSM (ages: 16-24 years) from shelters, drop-in centers, and street venues in Los Angeles County. Face-to-face interviews were conducted. Because of the different distributions of the three outcome variables, three distinct regression models were needed: ordinal logistic regression for unprotected sex, zero-truncated Poisson regression for number of sex partners, and logistic regression for any sex trade. Homeless YMSM were less likely to engage in unprotected sex and had fewer sex partners if their networks included platonic ties to peers who regularly attended school, and had fewer sex partners if most of their network members were not heavy drinkers. Most other aspects of network composition were unrelated to sexual risk behavior. Individual predictors of sexual risk behavior included older age, Hispanic ethnicity, lower education, depressive symptoms, less positive condom attitudes, and sleeping outdoors because of nowhere else to stay. HIV prevention programs for homeless YMSM may warrant a multipronged approach that helps these youth strengthen their ties to prosocial peers, develop more positive condom attitudes, and access needed mental health and housing services. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Identification of patients with gout: elaboration of a questionnaire for epidemiological studies.

PubMed

Richette, P; Clerson, P; Bouée, S; Chalès, G; Doherty, M; Flipo, R M; Lambert, C; Lioté, F; Poiraud, T; Schaeverbeke, T; Bardin, T

2015-09-01

In France, the prevalence of gout is currently unknown. We aimed to design a questionnaire to detect gout that would be suitable for use in a telephone survey by non-physicians and assessed its performance. We designed a 62-item questionnaire covering comorbidities, clinical features and treatment of gout. In a case-control study, we enrolled patients with a history of arthritis who had undergone arthrocentesis for synovial fluid analysis and crystal detection. Cases were patients with crystal-proven gout and controls were patients who had arthritis and effusion with no monosodium urate crystals in synovial fluid. The questionnaire was administered by phone to cases and controls by non-physicians who were unaware of the patient diagnosis. Logistic regression analysis and classification and regression trees were used to select items discriminating cases and controls. We interviewed 246 patients (102 cases and 142 controls). Two logistic regression models (sensitivity 88.0% and 87.5%; specificity 93.0% and 89.8%, respectively) and one classification and regression tree model (sensitivity 81.4%, specificity 93.7%) revealed 11 informative items that allowed for classifying 90.0%, 88.8% and 88.5% of patients, respectively. We developed a questionnaire to detect gout containing 11 items that is fast and suitable for use in a telephone survey by non-physicians. The questionnaire demonstrated good properties for discriminating patients with and without gout. It will be administered in a large sample of the general population to estimate the prevalence of gout in France. 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.

Understanding logistic regression analysis.

PubMed

Sperandei, Sandro

2014-01-01

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

Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077

ERIC Educational Resources Information Center

Koon, Sharon; Petscher, Yaacov

2015-01-01

The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…

[Early prenatal interview knowledge in post-partum women: Cross-sectional study in 2011 in Lille (France)].

PubMed

Aernout, E M; Carpentier, S

2016-04-01

Early prenatal interview (EPI) is one of the flagship measures of the 2005-2007 perinatal strategy. It allows mothers to have a 45-minute interview, distinct from a medical consultation, promoting the expression of their expectations and medical, psychological or social difficulties. It should be routinely offered to all mothers in early pregnancy. The main objective of our study was to determine the proportion of women who had knowledge of Early prenatal interview and to profile women who knew it. Secondary objectives were to describe the EPI achievement rate and its terms of implementation. All women who gave birth between 16 and 20 January 2011 in one of the ten maternity hospitals of the Lille metropolis were interviewed during their stay in maternity. A mixed model logistic regression was made to draw the profile of women with knowledge of Early prenatal interview. Of 311 women who gave birth during the study period, 270 were included in the survey. 148 patients (54.8 %) knew Early prenatal interview and 79 (29.3 %) had it. Women who had a high level of education were significantly more aware of this interview than those with low level of study. Other factors studied were not significantly related to knowledge of the EPI. While the EPI should be routinely offered to all pregnant women, only half of the patients who give birth had heard about it during their pregnancy. Women of low educational level should be more targeted by professional performing this interview. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Learning to Detect Deception from Evasive Answers and Inconsistencies across Repeated Interviews: A Study with Lay Respondents and Police Officers

PubMed Central

Masip, Jaume; Martínez, Carmen; Blandón-Gitlin, Iris; Sánchez, Nuria; Herrero, Carmen; Ibabe, Izaskun

2018-01-01

Previous research has shown that inconsistencies across repeated interviews do not indicate deception because liars deliberately tend to repeat the same story. However, when a strategic interview approach that makes it difficult for liars to use the repeat strategy is used, both consistency and evasive answers differ significantly between truth tellers and liars, and statistical software (binary logistic regression analyses) can reach high classification rates (Masip et al., 2016b). Yet, if the interview procedure is to be used in applied settings the decision process will be made by humans, not statistical software. To address this issue, in the current study, 475 college students (Experiment 1) and 142 police officers (Experiment 2) were instructed to code and use consistency, evasive answers, or a combination or both before judging the veracity of Masip et al.'s (2016b) interview transcripts. Accuracy rates were high (60% to over 90%). Evasive answers yielded higher rates than consistency, and the combination of both these cues produced the highest accuracy rates in identifying both truthful and deceptive statements. Uninstructed participants performed fairly well (around 75% accuracy), apparently because they spontaneously used consistency and evasive answers. The pattern of results was the same among students, all officers, and veteran officers only, and shows that inconsistencies between interviews and evasive answers reveal deception when a strategic interview approach that hinders the repeat strategy is used. PMID:29354078

Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech.

PubMed

Dodge, Hiroko H; Mattek, Nora; Gregor, Mattie; Bowman, Molly; Seelye, Adriana; Ybarra, Oscar; Asgari, Meysam; Kaye, Jeffrey A

2015-01-01

Detecting early signs of Alzheimer's disease (AD) and mild cognitive impairment (MCI) during the pre-symptomatic phase is becoming increasingly important for costeffective clinical trials and also for deriving maximum benefit from currently available treatment strategies. However, distinguishing early signs of MCI from normal cognitive aging is difficult. Biomarkers have been extensively examined as early indicators of the pathological process for AD, but assessing these biomarkers is expensive and challenging to apply widely among pre-symptomatic community dwelling older adults. Here we propose assessment of social markers, which could provide an alternative or complementary and ecologically valid strategy for identifying the pre-symptomatic phase leading to MCI and AD. The data came from a larger randomized controlled clinical trial (RCT), where we examined whether daily conversational interactions using remote video telecommunications software could improve cognitive functions of older adult participants. We assessed the proportion of words generated by participants out of total words produced by both participants and staff interviewers using transcribed conversations during the intervention trial as an indicator of how two people (participants and interviewers) interact with each other in one-on-one conversations. We examined whether the proportion differed between those with intact cognition and MCI, using first, generalized estimating equations with the proportion as outcome, and second, logistic regression models with cognitive status as outcome in order to estimate the area under ROC curve (ROC AUC). Compared to those with normal cognitive function, MCI participants generated a greater proportion of words out of the total number of words during the timed conversation sessions (p=0.01). This difference remained after controlling for participant age, gender, interviewer and time of assessment (p=0.03). The logistic regression models showed the ROC AUC of identifying MCI (vs. normals) was 0.71 (95% Confidence Interval: 0.54 - 0.89) when average proportion of word counts spoken by subjects was included univariately into the model. An ecologically valid social marker such as the proportion of spoken words produced during spontaneous conversations may be sensitive to transitions from normal cognition to MCI.

Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

DTIC Science & Technology

2017-03-23

PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and

Expression of Proteins Involved in Epithelial-Mesenchymal Transition as Predictors of Metastasis and Survival in Breast Cancer Patients

DTIC Science & Technology

2013-11-01

Ptrend 0.78 0.62 0.75 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of node...Ptrend 0.71 0.67 Unconditional logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for risk of high-grade tumors... logistic regression was used to estimate odds ratios (OR) and 95 % confidence intervals (CI) for the associations between each of the seven SNPs and

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

PubMed

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (P<0.05) to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD) and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD). However, it was inferior (P<0.05) to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD) and the AUC without CDD (0.785 vs. 0.844, P<0.001), but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

PubMed

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

Use and interpretation of logistic regression in habitat-selection studies

USGS Publications Warehouse

Keating, Kim A.; Cherry, Steve

2004-01-01

 Logistic regression is an important tool for wildlife habitat-selection studies, but the method frequently has been misapplied due to an inadequate understanding of the logistic model, its interpretation, and the influence of sampling design. To promote better use of this method, we review its application and interpretation under 3 sampling designs: random, case-control, and use-availability. Logistic regression is appropriate for habitat use-nonuse studies employing random sampling and can be used to directly model the conditional probability of use in such cases. Logistic regression also is appropriate for studies employing case-control sampling designs, but careful attention is required to interpret results correctly. Unless bias can be estimated or probability of use is small for all habitats, results of case-control studies should be interpreted as odds ratios, rather than probability of use or relative probability of use. When data are gathered under a use-availability design, logistic regression can be used to estimate approximate odds ratios if probability of use is small, at least on average. More generally, however, logistic regression is inappropriate for modeling habitat selection in use-availability studies. In particular, using logistic regression to fit the exponential model of Manly et al. (2002:100) does not guarantee maximum-likelihood estimates, valid probabilities, or valid likelihoods. We show that the resource selection function (RSF) commonly used for the exponential model is proportional to a logistic discriminant function. Thus, it may be used to rank habitats with respect to probability of use and to identify important habitat characteristics or their surrogates, but it is not guaranteed to be proportional to probability of use. Other problems associated with the exponential model also are discussed. We describe an alternative model based on Lancaster and Imbens (1996) that offers a method for estimating conditional probability of use in use-availability studies. Although promising, this model fails to converge to a unique solution in some important situations. Further work is needed to obtain a robust method that is broadly applicable to use-availability studies.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Determinants of postnatal care utilization in urban community among women in Debre Birhan Town, Northern Shewa, Ethiopia.

PubMed

Angore, Banchalem Nega; Tufa, Efrata Girma; Bisetegen, Fithamlak Solomon

2018-04-19

Reducing maternal mortality and improving maternal health care through increased utilization of postnatal care utilization is a global and local priority. However studies that have been carried out in Ethiopia regarding determinants are limited. So This study aims to assess the magnitude of postnatal care utilization and its determinants in Debre Birhan Town, North Ethiopia. A community-based cross-sectional study was conducted from March 1 to April 25, 2015, in Debre Birhan Town. Data were collected through face-to-face interviews using structured pre-tested questionnaires. The data were entered and cleaned in Epi Info version 3.5 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analyses were used. Variable with p value less than or equal to 0.2 at bivariate analysis were entered into multiple logistic regression. Significance was declared at 0.05 in multiple logistic regressions and considered to be an independent factor. From the total respondents, we found that 327 (83.3%) mothers utilized the postnatal care services. Single mothers were less likely to utilize postnatal care services than those mothers who are married and live together [adjusted odds ratio (AOR) = 0.06, 95% CI (0.01, 0.45)]. This study revealed that respondent's knowledge about postnatal care services is an important predictor of postnatal care utilization [AOR = 0.03, 95% CI (0.00, 0.44)] and mothers who delivered in a health care facility were more likely to receive PNC than mothers who did not deliver in a health care facility [AOR = 0.65, 95% CI (0.58, 0.94)]. The postnatal care utilization rate in Debre Birhan town was 83.3%. Marital status, maternal knowledge, and place of delivery were predictors of postnatal care service utilization. So specific attention should be directed towards the improvement of women's education since the perception of the need for PNC services were positively correlated with the mother's education.

Varicella infection is not associated with increasing prevalence of eczema: a U.S. population-based study.

PubMed

Li, J C; Silverberg, J I

2015-11-01

Chickenpox infection early in childhood has previously been shown to protect against the development of childhood eczema in line with the hygiene hypothesis. In 1995, the American Academy of Pediatrics recommended routine vaccination against varicella zoster virus in the United States. Subsequently, rates of chickenpox infection have dramatically decreased in childhood. We sought to understand the impact of declining rates of chickenpox infection on the prevalence of eczema. We analysed data from 207 007 children in the 1997-2013 National Health Interview Survey. One-year prevalence of eczema and 'ever had' history of chickenpox were analysed. Associations between chickenpox infection and eczema were tested using survey-weighted logistic regression. The impact of chickenpox on trends of eczema prevalence was tested using survey logistic regression and generalized linear models. Children with a history of chickenpox compared with those without chickenpox had a lower prevalence [survey-weighted logistic regression (95% confidence interval, CI)] of eczema [8·8% (8·5-9·0%) vs. 10·6% (10·4-10·8%)]. In pooled multivariate models controlling for age, sex, race/ethnicity, household income, highest level of household education, insurance coverage, U.S. birthplace and family size, eczema was inversely associated with chickenpox [adjusted odds ratio (95% CI), 0·90 (0·86-0·94), P < 0·001]. The prevalence of eczema significantly increased over time (Tukey post-hoc test, P < 0·001 for comparisons of survey years 2001-13 vs. 1997-2000, 2008-13 vs. 2001-04 and 2008-13 vs. 2005-07). In multivariate generalized linear models, the odds of eczema was not associated with chickenpox in 2001-13 (P ≥ 0·06). These findings suggest that lower rates of chickenpox infection secondary to widespread vaccination against varicella zoster virus are not contributing to higher rates of childhood eczema in the U.S. © 2015 British Association of Dermatologists.

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

Treesearch

T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Fuzzy multinomial logistic regression analysis: A multi-objective programming approach

NASA Astrophysics Data System (ADS)

Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan

2017-05-01

Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.

Predictors of Using a Microbicide-like Product Among Adolescent Girls

PubMed Central

Short, Mary B.; Succop, Paul A.; Ugueto, Ana M.; Rosenthal, Susan L.

2007-01-01

Purpose This study examined demographic, sexual history and weekly contextual variables, and perceptions about microbicides as predictors of microbicide-like product use. Methods Adolescent girls (N=208; 14-21 years) participated in a 6-month study in which they completed three face-to-face interviews and 24-weekly phone call interviews. Participants were given microbicide-like products (vaginal lubricants) and encouraged to use them with condoms when they had intercourse. Results Seventy-five percent of girls had a sexual opportunity to use the product. Using multi-variable logistic regression, the following variables independently predicted ever using the product: length of sexual experience, number of lifetime vaginal partners, and the Comparison to Condoms subscale on the Perceptions of Microbicides Scale. Using mixed model repeat measure linear regression, the following variables independently predicted frequency of use: week of the study, age, condom frequency prior to the study, and 3 subscales on the Perceptions of Microbicide Scale including the Comparison to Condoms subscale, the Negative Effects subscale, and the Pleasure subscale. Conclusion Most girls used the product, including those who were not protecting themselves with condoms. Girls’ initial perceptions regarding the product predicted initial use and frequency of use. Further research should evaluate the best methods for supporting the use of these products by young or sexually less experienced girls. PMID:17875461

Socioeconomic Differences in and Predictors of Home-Based Palliative Care Health Service Use in Ontario, Canada

PubMed Central

Cai, Jiaoli; Guerriere, Denise N.; Zhao, Hongzhong; Coyte, Peter C.

2017-01-01

The use of health services may vary across people with different socioeconomic statuses, and may be determined by many factors. The purposes of this study were (i) to examine the socioeconomic differences in the propensity and intensity of use for three main home-based health services, that is, home-based palliative care physician visits, nurse visits and personal support worker (PSW) hours; and (ii) to explore the determinants of the use of home-based palliative care services. A prospective cohort study was employed. A total of 181 caregivers were interviewed biweekly over the course of the palliative care trajectory, yielding a total of 994 interviews. The propensity and intensity of health service use were examined using logistic regression and negative binomial regression, respectively. The results demonstrated that both the propensity and intensity of home-based nurse and PSW visits fell with socioeconomic status. The use of home-based palliative care services was not concentrated in high socioeconomic status groups. The common predictors of health service use in the three service categories were patient age, the Palliative Performance Scale (PPS) score and place of death. These findings may assist health service planners in the appropriate allocation of resources and service packages to meet the complex needs of palliative care populations. PMID:28718797

Socioeconomic Differences in and Predictors of Home-Based Palliative Care Health Service Use in Ontario, Canada.

PubMed

Cai, Jiaoli; Guerriere, Denise N; Zhao, Hongzhong; Coyte, Peter C

2017-07-18

The use of health services may vary across people with different socioeconomic statuses, and may be determined by many factors. The purposes of this study were (i) to examine the socioeconomic differences in the propensity and intensity of use for three main home-based health services, that is, home-based palliative care physician visits, nurse visits and personal support worker (PSW) hours; and (ii) to explore the determinants of the use of home-based palliative care services. A prospective cohort study was employed. A total of 181 caregivers were interviewed biweekly over the course of the palliative care trajectory, yielding a total of 994 interviews. The propensity and intensity of health service use were examined using logistic regression and negative binomial regression, respectively. The results demonstrated that both the propensity and intensity of home-based nurse and PSW visits fell with socioeconomic status. The use of home-based palliative care services was not concentrated in high socioeconomic status groups. The common predictors of health service use in the three service categories were patient age, the Palliative Performance Scale (PPS) score and place of death. These findings may assist health service planners in the appropriate allocation of resources and service packages to meet the complex needs of palliative care populations.

A Primer on Logistic Regression.

ERIC Educational Resources Information Center

Woldbeck, Tanya

This paper introduces logistic regression as a viable alternative when the researcher is faced with variables that are not continuous. If one is to use simple regression, the dependent variable must be measured on a continuous scale. In the behavioral sciences, it may not always be appropriate or possible to have a measured dependent variable on a…

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

[Influences of environmental factors and interaction of several chemokines gene-environmental on systemic lupus erythematosus].

PubMed

Ye, Dong-qing; Hu, Yi-song; Li, Xiang-pei; Huang, Fen; Yang, Shi-gui; Hao, Jia-hu; Yin, Jing; Zhang, Guo-qing; Liu, Hui-hui

2004-11-01

To explore the impact of environmental factors, daily lifestyle, psycho-social factors and the interactions between environmental factors and chemokines genes on systemic lupus erythematosus (SLE). Case-control study was carried out and environmental factors for SLE were analyzed by univariate and multivariate unconditional logistic regression. Interactions between environmental factors and chemokines polymorphism contributing to systemic lupus erythematosus were also analyzed by logistic regression model. There were nineteen factors associated with SLE when univariate unconditional logistic regression was used. However, when multivariate unconditional logistic regression was used, only five factors showed having impacts on the disease, in which drinking well water (OR=0.099) was protective factor for SLE, and multiple drug allergy (OR=8.174), over-exposure to sunshine (OR=18.339), taking antibiotics (OR=9.630) and oral contraceptives were risk factors for SLE. When unconditional logistic regression model was used, results showed that there was interaction between eating irritable food and -2518MCP-1G/G genotype (OR=4.387). No interaction between environmental factors was found that contributing to SLE in this study. Many environmental factors were related to SLE, and there was an interaction between -2518MCP-1G/G genotype and eating irritable food.

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

PubMed

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

Controlling Type I Error Rates in Assessing DIF for Logistic Regression Method Combined with SIBTEST Regression Correction Procedure and DIF-Free-Then-DIF Strategy

ERIC Educational Resources Information Center

Shih, Ching-Lin; Liu, Tien-Hsiang; Wang, Wen-Chung

2014-01-01

The simultaneous item bias test (SIBTEST) method regression procedure and the differential item functioning (DIF)-free-then-DIF strategy are applied to the logistic regression (LR) method simultaneously in this study. These procedures are used to adjust the effects of matching true score on observed score and to better control the Type I error…

Understanding the Personality and Behavioral Mechanisms Defining Hypersexuality in Men Who Have Sex with Men

PubMed Central

Miner, Michael H.; Romine, Rebecca Swinburne; Raymond, Nancy; Janssen, Erick; MacDonald, Angus; Coleman, Eli

2016-01-01

Objective The purpose of this study was to investigate personality factors and behavioral mechanisms that are relevant to hypersexuality in men who have sex with men. Method A sample of 242 men who have sex with men were recruited from various sites in a moderate size mid-western city. Participants were assigned to hypersexuality or control group using a SCID-type interview. Self-report inventories were administered that measured the broad band personality constructs of positive emotionality, negative emotionality and constraint, and more narrow constructs related to sexual behavioral control, behavioral activation, behavioral inhibition, sexual excitation, sexual inhibition, impulsivity, ADHD, and sexual behavior. Hierarchical logistic regression was used to determine the relationship between these personality and behavioral variables and group membership. Results A hierarchical logistic regression, controlling for age, revealed a significant positive relationship between hypersexuality and negative emotionality and a negative relationship with constraint. None of the behavioral mechanism variables entered this equation. However, a hierarchical multiple regression predicting sexual behavioral control indicated that lack of such control was positively related to sexual excitation and sexual inhibition due to the threat of performance failure and negatively related to sexual inhibition due to the threat of performance consequences and general behavioral inhibition Conclusions Hypersexuality was found to be related to two broad personality factors that are characterized by emotional reactivity, risk-taking, and impulsivity. The associated lack of sexual behavior control is influenced by both sexual excitatory and inhibitory mechanisms, but not general behavioral activation and inhibitory mechanisms. PMID:27486137

How pharmacist-patient communication determines pharmacy loyalty? Modeling relevant factors.

PubMed

Patrícia Antunes, Liliana; Gomes, João José; Cavaco, Afonso Miguel

2015-01-01

Portuguese community pharmacies provide pharmaceutical services, such as therapeutic outcomes follow-up, supplemented by relevant point-of-care testing that require continuity of provision to be effective. To identify factors of technical and communication nature that during a patient interview contribute to patients' loyalty. A cross-sectional descriptive study, with a purposive sample of community pharmacies providing pharmaceutical care, was conducted. Patient interviews were taped and transcribed verbatim. Duration, segments and utterances were identified and time stamped, using a previously validated coding scheme. To identify predictors of loyalty, logistic regression analyses were performed. From 59 interviews, participants' average age was 65.7 years and 42 (71.2%) were female; 45 (76.3%) interviews were classified as outcomes measurements and 14 (23.7%) as pharmaceutical consultations, with 33.2% of the patients booking a following appointment. The significant items to explain loyalty were associated with lifestyle and psychosocial exchange, age of the patient, and the presence of all interview segments (i.e. a complete consultation). Contrary to common professional beliefs and practice orientation it would appear that pharmacists' technical skills are not the essential factors that promote patients' loyalty needed for continuity of care, at least in the same extent as the social and lifestyle-related content of the exchange. Pharmaceutical care education should focus on relational skills as much as on medication-related competencies. Copyright © 2015 Elsevier Inc. All rights reserved.

Access disparities to Magnet hospitals for patients undergoing neurosurgical operations

PubMed Central

Missios, Symeon; Bekelis, Kimon

2017-01-01

Background Centers of excellence focusing on quality improvement have demonstrated superior outcomes for a variety of surgical interventions. We investigated the presence of access disparities to hospitals recognized by the Magnet Recognition Program of the American Nurses Credentialing Center (ANCC) for patients undergoing neurosurgical operations. Methods We performed a cohort study of all neurosurgery patients who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2009–2013. We examined the association of African-American race and lack of insurance with Magnet status hospitalization for neurosurgical procedures. A mixed effects propensity adjusted multivariable regression analysis was used to control for confounding. Results During the study period, 190,535 neurosurgical patients met the inclusion criteria. Using a multivariable logistic regression, we demonstrate that African-Americans had lower admission rates to Magnet institutions (OR 0.62; 95% CI, 0.58–0.67). This persisted in a mixed effects logistic regression model (OR 0.77; 95% CI, 0.70–0.83) to adjust for clustering at the patient county level, and a propensity score adjusted logistic regression model (OR 0.75; 95% CI, 0.69–0.82). Additionally, lack of insurance was associated with lower admission rates to Magnet institutions (OR 0.71; 95% CI, 0.68–0.73), in a multivariable logistic regression model. This persisted in a mixed effects logistic regression model (OR 0.72; 95% CI, 0.69–0.74), and a propensity score adjusted logistic regression model (OR 0.72; 95% CI, 0.69–0.75). Conclusions Using a comprehensive all-payer cohort of neurosurgery patients in New York State we identified an association of African-American race and lack of insurance with lower rates of admission to Magnet hospitals. PMID:28684152

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

PubMed

Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

2016-01-01

Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Racial/ethnic variation in health care satisfaction: The role of acculturation.

PubMed

Han, Woojae; Lee, Sungkyu

2016-10-01

This study examined the role of acculturation and racial/ethnic variation in health care satisfaction among four different racial/ethnic groups. The study sample consisted of 41,560 adults from the 2011 California Health Interview Survey. Health care satisfaction was measured via two questions regarding doctors' listening and explanations. Guided by Andersen's behavioral model of health care use, multivariate logistic regressions were conducted. Hispanic and Asian respondents showed the lowest levels of satisfaction with their doctors' listening and explanations, respectively. Acculturation was found to be a significant predictor of health care satisfaction. Health care professionals should develop ways of expanding culturally competent health care professionals, who are aware of racial/ethnic variation in health care satisfaction.

Use of complementary and alternative medicine for physical performance, energy, immune function, and general health among older women and men in the United States.

PubMed

Tait, Elizabeth M; Laditka, Sarah B; Laditka, James N; Nies, Mary A; Racine, Elizabeth F

2012-01-01

We examined use of complementary and alternative medicine (CAM) for health and well-being by older women and men. Data were from the 2007 National Health Interview Survey, representing 89.5 million Americans ages 50+. Multivariate logistic regression accounted for the survey design. For general health, 52 million people used CAM. The numbers for immune function, physical performance, and energy were 21.6, 15.9, and 10.1 million respectively. In adjusted results, women were much more likely than men to use CAM for all four reasons, especially energy. Older adults, particularly women, could benefit from research on CAM benefits and risks.

Parent’s Socioeconomic Status, Adolescents’ Disposable Income, and Adolescents’ Smoking Status in Massachusetts

PubMed Central

Soteriades, Elpidoforos S.; DiFranza, Joseph R.

2003-01-01

Objectives. This study examined the association between parental socioeconomic status (SES) and adolescent smoking. Methods. We conducted telephone interviews with a probability sample of 1308 Massachusetts adolescents aged 12 to 17 years. We used multiple-variable-adjusted logistic regression models. Results. The risk of adolescent smoking increased by 28% with each step down in parental education and increased by 30% for each step down in parental household income. These associations persisted after adjustment for age, sex, race/ethnicity, and adolescent disposable income. Parental smoking status was a mediator of these associations. Conclusions. Parental SES is inversely associated with adolescent smoking. Parental smoking is a mediator but does not fully explain the association. PMID:12835202

Exploring Individual and Structural Factors Associated with Employment Among Young Transgender Women of Color Using a No-Cost Transgender Legal Resource Center.

PubMed

Hill, Brandon J; Rosentel, Kris; Bak, Trevor; Silverman, Michael; Crosby, Richard; Salazar, Laura; Kipke, Michele

2017-01-01

The purpose of this study was to explore individual and structural factors associated with employment among young transgender women (TW) of color. Sixty-five trans women of color were recruited from the Transgender Legal Defense and Education Fund to complete a 30-min interviewer-assisted survey assessing sociodemographics, housing, workplace discrimination, job-seeking self-efficacy, self-esteem, perceived public passability, and transactional sex work. Logistic regression models revealed that stable housing (structural factor) and job-seeking self-efficacy (individual factor) were significantly associated with currently being employed. Our findings underscore the need for multilevel approaches to assist TW of color gain employment.

Household participation in recycling programs: a case study from Turkey.

PubMed

Budak, Fuat; Oguz, Burcu

2008-11-01

This study investigates the underlining factors that motivate households to participate in a pilot source separation and recycling program in Turkey. The data of this research were collected from randomly selected households in the program area via face to face interviews based on an inclusive questionnaire. The results of logistic regression analysis show that having sufficient knowledge regarding recycling and the recycling program is the most statistically significant factor in determining whether a household will participate in recycling. The results also imply that some of the socio-economic and demographic characteristics of household hypothesized to affect the household decision to participate in recycling, in the research framework, are not significant.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Psychiatric comorbidity in autism spectrum disorder: Correspondence between mental health clinician report and structured parent interview.

PubMed

Stadnick, Nicole; Chlebowski, Colby; Baker-Ericzén, Mary; Dyson, Margaret; Garland, Ann; Brookman-Frazee, Lauren

2017-10-01

Publicly funded mental health services are critical in caring for children with autism spectrum disorder. Accurate identification of psychiatric comorbidity is necessary for effective mental health treatment. Little is known about psychiatric diagnosis for this population in routine mental health care. This study (1) examined correspondence between psychiatric diagnoses reported by mental health clinicians and those derived from a structured diagnostic interview and (2) identified predictors of agreement between clinician-reported and diagnostic interview-derived diagnoses in a sample of 197 children aged 4-14 years with autism spectrum disorder receiving mental health services. Data were drawn from a randomized effectiveness trial conducted in publicly funded mental health services. Non-autism spectrum disorder diagnoses were assessed using an adapted version of the Mini-International Neuropsychiatric Interview, parent version. Cohen's kappa was calculated to examine agreement between Mini-International Neuropsychiatric Interview, parent version and clinician-reported diagnoses of comorbid conditions. Children met criteria for an average of 2.83 (standard deviation = 1.92) Mini-International Neuropsychiatric Interview, parent version diagnoses. Agreement was poor across all diagnostic categories (κ values: 0.06-0.18). Logistic regression identified child gender and clinical characteristics as significant predictors of agreement for specific diagnoses. Results underscore the need for training mental health clinicians in targeted assessment of specific psychiatric disorders and prioritizing treatment development and testing for specific diagnoses to improve care for children with autism spectrum disorder served in publicly funded mental health settings.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

EPA Science Inventory

Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

Predisposition for Empathy, Intercultural Sensitivity, and Intentions for Using Motivational Interviewing in First Year Pharmacy Students

PubMed Central

Kavookjian, Jan; Hutchison, Amber

2017-01-01

Objective. To assess first-year pharmacy (P1) students’ predispositions (eg, perceptions for empathy, intercultural sensitivity, and motivational interviewing (MI) as a patient-centered communication skillset) and identify potential curricula content/communication skills training needs. Methods. A cross-sectional survey was used to collect students’ self-reported perceptions for empathy, intercultural sensitivity, counseling contexts, and projected future MI use. Relationships between variables were explored and logistic regression was used to evaluate intention for using MI in future patient encounters. Results. There were 134 students who participated. Higher predisposition for empathy and for intercultural sensitivity were significantly correlated. Significant predictors for applying MI in future patient encounters were sex, confidence with counseling skills, and current use of MI. Conclusion. Results suggest the need to incorporate innovative training strategies in communication skills curricula. Potential areas include empathy, intercultural sensitivity and significant predictor variables for future MI use. Further investigation in other schools is needed. PMID:29200452

Predisposition for Empathy, Intercultural Sensitivity, and Intentions for Using Motivational Interviewing in First Year Pharmacy Students.

PubMed

Ekong, Gladys; Kavookjian, Jan; Hutchison, Amber

2017-10-01

Objective. To assess first-year pharmacy (P1) students' predispositions (eg, perceptions for empathy, intercultural sensitivity, and motivational interviewing (MI) as a patient-centered communication skillset) and identify potential curricula content/communication skills training needs. Methods. A cross-sectional survey was used to collect students' self-reported perceptions for empathy, intercultural sensitivity, counseling contexts, and projected future MI use. Relationships between variables were explored and logistic regression was used to evaluate intention for using MI in future patient encounters. Results. There were 134 students who participated. Higher predisposition for empathy and for intercultural sensitivity were significantly correlated. Significant predictors for applying MI in future patient encounters were sex, confidence with counseling skills, and current use of MI. Conclusion. Results suggest the need to incorporate innovative training strategies in communication skills curricula. Potential areas include empathy, intercultural sensitivity and significant predictor variables for future MI use. Further investigation in other schools is needed.

Tracking Psychosocial Health in Adults with Epilepsy—Estimates from the 2010 National Health Interview Survey

PubMed Central

Kobau, R; Cui, W; Kadima, N; Zack, MM; Sajatovic, M; Kaiboriboon, K; Jobst, B

2015-01-01

Objective This study provides population-based estimates of psychosocial health among U.S. adults with epilepsy from the 2010 National Health Interview Survey. Methods Multinomial logistic regression was used to estimate the prevalence of the following measures of psychosocial health among adults with and those without epilepsy: 1) the Kessler-6 scale of Serious Psychological Distress; 2) cognitive limitation; the extent of impairments associated with psychological problems; and work limitation; 3) Social participation; and 4) the Patient Reported Outcome Measurement Information System Global Health scale. Results Compared with adults without epilepsy, adults with epilepsy, especially those with active epilepsy, reported significantly worse psychological health, more cognitive impairment, difficulty in participating in some social activities, and reduced health-related quality of life (HRQOL). Conclusions These disparities in psychosocial health in U.S. adults with epilepsy serve as baseline national estimates of their HRQOL, consistent with Healthy People 2020 national objectives on HRQOL. PMID:25305435

Smoking-related changes or brand switching? Smokers' anticipated responses to a large increase in Taiwan's Tobacco Health and Welfare Surcharge.

PubMed

Yeh, C-Y; Schafferer, C; Lee, J-M; Hsieh, C-J

2016-07-01

This study examines the impact on smokers' behaviour of a planned increase in the Health and Welfare Surcharge of Tobacco Products in Taiwan. This study used a structured questionnaire to perform telephone interviews. Stratified random sampling was applied to interview current smokers aged 18-65 years in Taiwan. Based on nationwide survey data of smokers' responses to future increases in cigarette prices, this study used multinomial logistic regression to perform its analyses. After the proposed increase in the Health and Welfare Surcharge of Tobacco Products, subsequent cigarette price increases would motivate nearly 30% of the smokers to adopt smoking-related changes and 10% to change to lower-priced brands. The study suggests that a large increase in the Health and Welfare Surcharge of Tobacco Products would lead to considerable changes in smoking behaviour, which in turn would increase cessation rate at the population level. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Suicidal Behavior and Associations with Quality of Life among HIV-Infected Patients in Ibadan, Nigeria.

PubMed

Oladeji, Bibilola Damilola; Taiwo, Babafemi; Mosuro, Olushola; Fayemiwo, Samuel A; Abiona, Taiwo; Fought, Angela J; Robertson, Kevin; Ogunniyi, Adesola; Adewole, Isaac F

Suicidality has rarely been studied in HIV-infected patients in sub-Saharan Africa. This study explored suicidal behavior in a clinic sample of people living with HIV, in Nigeria. Consecutive patients were interviewed using the Composite International Diagnostic Interview (CIDI-10.0) and the World Health Organization Quality of Life (WHO-QOL-HIV-BREF). Associations of suicidal behavior were explored using logistic regression models. In this sample of 828 patients (71% female, mean age 41.3 ± 10 years), prevalence of suicidal behaviors were 15.1%, 5.8%, and 3.9% for suicidal ideation, plans, and attempts, respectively. Women were more likely than men to report suicidal ideation (odds ratio 1.7; 95% confidence interval 1.05-2.64). Depression and/or anxiety disorder was associated with increased odds of all suicidal behaviors. Suicidal behavior was associated with significantly lower overall and domain scores on the WHO-QOL. Suicidal behaviors were common and significantly associated with the presence of mental disorders and lower quality of life.

Support, Inclusion, and Special Education Teachers' Attitudes toward the Education of Students with Autism Spectrum Disorders

PubMed Central

Rodríguez, Isabel R.; Saldaña, David; Moreno, F. Javier

2012-01-01

This study is aimed at assessing special education teachers' attitudes toward teaching pupils with autism spectrum disorders (ASDs) and at determining the role of variables associated with a positive attitude towards the children and their education. Sixty-nine special education teachers were interviewed. The interview included two multiple-choice Likert-type questionnaires, one about teachers' attitude, and another about teachers' perceived needs in relation to the specific education of the pupil with ASD. The study shows a positive view of teachers' expectations regarding the education of pupils with ASD. A direct logistic regression analysis was performed testing for experience with the child, school relationship with an ASD network and type of school (mainstream or special) as potential predictors. Although all three variables are useful in predicting special education teachers' attitudes, the most relevant was the relationship with an ASD network. Need for information and social support are the relatively highest needs expressed by teachers. PMID:22934171

Association between previous spontaneous abortion and pre-eclampsia during a subsequent pregnancy.

PubMed

Sepidarkish, Mahdi; Almasi-Hashiani, Amir; Maroufizadeh, Saman; Vesali, Samira; Pirjani, Reihaneh; Samani, Reza O

2017-01-01

To determine the impact of a history of spontaneous abortion on pre-eclampsia during a subsequent pregnancy. A cross-sectional study enrolled pregnant women admitted to obstetrics and gynecology wards at 103 hospitals in Tehran, Iran for delivery between July 6 and July 21, 2015. Consenting participants were interviewed by midwives; data were collected using a five-part questionnaire and patients' medical records were retrieved. Patient data were analyzed by multiple logistic regression to identify variables associated with increased odds of pre-eclampsia. In total, 5170 patients were interviewed and 252 had experienced pre-eclampsia. The number of previous spontaneous abortions was found to be associated with pre-eclampsia, and a higher number of previous spontaneous abortions was associated with increased odds of patients having experienced pre-eclampsia (adjusted odds ratio 1.28, 95% confidence interval 1.03-1.59; P=0.025). A history of spontaneous abortion was associated with increased odds of pre-eclampsia during a subsequent pregnancy. © 2016 International Federation of Gynecology and Obstetrics.

Association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent.

PubMed

Chung, Ming-Shun; Chiu, Hsien-Jane; Sun, Wen-Jung; Lin, Chieh-Nan; Kuo, Chien-Cheng; Huang, Wei-Che; Chen, Ying-Sheue; Cheng, Hui-Ping; Chou, Pesus

2014-09-01

The aim of this study is to investigate the association among depressive disorder, adjustment disorder, sleep disturbance, and suicidal ideation in Taiwanese adolescent. We recruited 607 students (grades 5-9) to fill out the investigation of basic data and sleep disturbance. Psychiatrists then used the Mini International Neuropsychiatric Interview-Kid to interview these students to assess their suicidal ideation and psychiatric diagnosis. Multiple logistic regression with forward conditionals was used to find the risk factors for multivariate analysis. Female, age, depressive disorder, adjustment disorder, and poor sleep all contributed to adolescent suicidal ideation in univariate analysis. However, poor sleep became non-significant under the control of depressive disorder and adjustment disorder. We found that both depressive disorder and adjustment disorder play important roles in sleep and adolescent suicidal ideation. After controlling both depressive disorder and adjustment disorder, sleep disturbance was no longer a risk of adolescent suicidal ideation. We also confirm the indirect influence of sleep on suicidal ideation in adolescent. © 2013 Wiley Publishing Asia Pty Ltd.

Outcry Consistency and Prosecutorial Decisions in Child Sexual Abuse Cases.

PubMed

Bracewell, Tammy E

2018-05-18

This study examines the correlation between the consistency in a child's sexual abuse outcry and the prosecutorial decision to accept or reject cases of child sexual abuse. Case-specific information was obtained from one Texas Children's Advocacy Center on all cases from 2010 to 2013. After the needed deletion, the total number of cases included in the analysis was 309. An outcry was defined as a sexual abuse disclosure. Consistency was measured at both the forensic interview and the sexual assault exam. Logistic regression was used to evaluate whether a correlation existed between disclosure and prosecutorial decisions. Disclosure was statistically significant. Partial disclosure (disclosure at one point in time and denial at another) versus full disclosure (disclosure at two points in time) had a statistically significant odds ratio of 4.801. Implications are discussed, specifically, how the different disciplines involved in child protection should take advantage of the expertise of both forensic interviewers and forensic nurses to inform their decisions.

The association between social stressors and drug use/hazardous drinking among former prison inmates.

PubMed

Calcaterra, Susan L; Beaty, Brenda; Mueller, Shane R; Min, Sung-Joon; Binswanger, Ingrid A

2014-07-01

Social stressors are associated with relapse to substance use among people receiving addiction treatment and people with substance use risk behaviors. The relationship between social stressors and drug use/hazardous drinking in former prisoners has not been studied. We interviewed former prisoners at baseline, 1 to 3 weeks post prison release, and follow up, between 2 and 9 months following the baseline interview. Social stressors were characterized by unemployment, homelessness, unstable housing, problems with family, friends, and/or significant others, being single, or major symptoms of depression. Associations between baseline social stressors and follow-up drug use and hazardous drinking were analyzed using multivariable logistic regression. Problems with family, friends, and/or significant others were associated with reported drug use (AOR 3.01, 95% CI 1.18-7.67) and hazardous drinking (AOR 2.69, 95% CI 1.05-6.87) post release. Further research may determine whether interventions and policies targeting social stressors can reduce relapse among former inmates. Copyright © 2014 Elsevier Inc. All rights reserved.

Tobacco and alcohol use in adolescents with unplanned pregnancies: relation with family structure, tobacco and alcohol use at home and by friends.

PubMed

Francisco, Vazquez-Nava; Carlos, Vazquez-Rodríguez; Eliza, Vazquez-Rodriguez; Octelina, Castillo-Ruiz; Maria, Iribar Ibabe

2016-03-01

Recent publications show that smoking and alcohol use among adolescents with unplanned pregnancy is increasing and the causes need to be further studied. To determine the association between living in a non-intact family household and the presence of smokers and consumers of alcoholic beverages in the adolescents' environment with smoking and consuming alcoholic beverages in adolescents with unplanned pregnancies. A cross-sectional study was carried out among 785 pregnant adolescents, aged 13-19 years. Data was collected by trained interviewers using a self-administered questionnaire. The association was determined using multivariate logistic regression analysis. In adolescents with unplanned pregnancies, the prevalence of active smoking was 21.2% and of alcohol consumption, 41.5%. The percentage of smoking at home was 57.4% and alcohol consumption, 77.5%. Approximately, 80.3% of adolescents with unplanned pregnancies had friends who smoked and 90.6% consumed alcoholic beverages. Multivariate logistic regression analysis shows that having friends who smoke or who consume alcoholic beverages is the most important risk factor for substance use in adolescents with unplanned pregnancies. Smoking and alcohol consumption at home are not associated with smoking in adolescents with unplanned pregnancies. Socializing with friends who smoke and/or consume alcoholic beverages constitutes the most important risk factor for substance use among adolescents with unplanned pregnancies.

Living near overhead high voltage transmission power lines as a risk factor for childhood acute lymphoblastic leukemia: a case-control study.

PubMed

Sohrabi, Mohammad-Reza; Tarjoman, Termeh; Abadi, Alireza; Yavari, Parvin

2010-01-01

This study aimed to investigate association of living near high voltage power lines with occurrence of childhood acute lymphoblastic leukemia (ALL). Through a case-control study 300 children aged 1-18 years with confirmed ALL were selected from all referral teaching centers for cancer. They interviewed for history of living near overhead high voltage power lines during at least past two years and compared with 300 controls which were individually matched for sex and approximate age. Logistic regression, chi square and paired t-tests were used for analysis when appropriate. The case group were living significantly closer to power lines (P<0.001). More than half of the cases were exposed to two or three types of power lines (P<0.02). Using logistic regression, odds ratio of 2.61 (95%CI: 1.73 to 3.94) calculated for less than 600 meters far from the nearest lines against more than 600 meters. This ratio estimated as 9.93 (95%CI: 3.47 to 28.5) for 123 KV, 10.78 (95%CI: 3.75 to 31) for 230 KV and 2.98 (95%CI: 0.93 to 9.54) for 400 KV lines. Odds of ALL decreased 0.61 for every 600 meters from the nearest power line. This study emphasizes that living close to high voltage power lines is a risk for ALL.

Risk factors for hospital readmission of elderly patients.

PubMed

Franchi, Carlotta; Nobili, Alessandro; Mari, Daniela; Tettamanti, Mauro; Djade, Codjo D; Pasina, Luca; Salerno, Francesco; Corrao, Salvatore; Marengoni, Alessandra; Iorio, Alfonso; Marcucci, Maura; Mannucci, Pier Mannuccio

2013-01-01

The aim of this study was to identify which factors were associated with a risk of hospital readmission within 3 months after discharge of a sample of elderly patients admitted to internal medicine and geriatric wards. Of the 1178 patients aged 65 years or more and discharged from one of the 66 wards of the 'Registry Politerapie SIMI (REPOSI)' during 2010, 766 were followed up by phone interview 3 months after discharge and were included in this analysis. Univariate and multivariate logistic regression models were used to evaluate the association of several variables with rehospitalization within 3 months from discharge. Nineteen percent of patients were readmitted at least once within 3 months after discharge. By univariate analysis in-hospital clinical adverse events (AEs), a previous hospital admission, number of diagnoses and drugs, comorbidity and severity index (according to Cumulative Illness Rating Scale-CIRS), vascular and liver diseases with a level of impairment at discharge of 3 or more at CIRS were significantly associated with risk of readmission. Multivariate logistic regression analysis showed that only AEs during hospitalization, previous hospital admission, and vascular and liver diseases were significantly associated with the likelihood of readmission. The results demonstrate the need for increased medical attention towards elderly patients discharged from hospital with characteristics such as AEs during the hospitalization, previous admission, vascular and liver diseases. Copyright © 2012 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Association between maternal smoking, gender, and cleft lip and palate.

PubMed

Martelli, Daniella Reis Barbosa; Coletta, Ricardo D; Oliveira, Eduardo A; Swerts, Mário Sérgio Oliveira; Rodrigues, Laíse A Mendes; Oliveira, Maria Christina; Martelli Júnior, Hercílio

2015-01-01

Cleft lip and/or palate (CL/P) represent the most common congenital anomalies of the face. To assess the relationship between maternal smoking, gender and CL/P. This is an epidemiological cross-sectional study. We interviewed 1519 mothers divided into two groups: mothers of children with CL/P (n=843) and mothers of children without CL/P (n=676). All mothers were classified as smoker or non-smoker subjects during the first trimester of pregnancy. To determine an association among maternal smoking, gender, and CL/P, odds ratios were calculated and the adjustment was made by a logistic regression model. An association between maternal smoking and the presence of cleft was observed. There was also a strong association between male gender and the presence of cleft (OR=3.51; 95% CI 2.83-4.37). By binary logistic regression analysis, it was demonstrated that both variables were independently associated with clefts. In a multivariate analysis, male gender and maternal smoking had a 2.5- and a 1.5-time greater chance of having a cleft, respectively. Our findings are consistent with a positive association between maternal smoking during pregnancy and CL/P in male gender. The results support the importance of smoking prevention and introduction of cessation programs among women with childbearing potential. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Screening for postpartum depression using Kurdish version of Edinburgh postnatal depression scale.

PubMed

Ahmed, Hamdia Mirkhan; Alalaf, Shahla Kareem; Al-Tawil, Namir Ghanim

2012-05-01

One of the important public health problems affecting maternal and child health is postpartum depression (PPD). It generally occurs within 6-8 weeks after childbirth. To determine the prevalence of postpartum depression (PPD) using a Kurdish version of Edinburgh postpartum depression scale (EPDS) and to analyze the risk factors for postpartum depression in a population of puerperal Kurdish women in Erbil city. A cross-sectional study was conducted between 20th of June and 30th of November 2010, in 14 antenatal care units of primary health centers, in Erbil city, Kurdistan region, Iraq. The sample of the study included 1,000 puerperal women (6-8 weeks postpartum), ranging in age from 14 to 48 years. Data were collected after interviewing the women using a questionnaire designed by the researchers, and the Kurdish version of the EPDS. Chi square test of association and the logistic regression tests were used in the analysis. The prevalence of postpartum depression was 28.4%. Logistic regression analysis showed that the factors found to be associated with PPD were: physical or sexual abuse, delivery by cesarean section, history of past psychiatric illness, and family history of past psychiatric illness; while marriage with no previous agreement, and high socio-economic level were associated with lower levels of PPD. The Kurdish version of the EPDS can be successfully used to screen depression in a Kurdish population of puerperal women.

Negative Life Events and Antenatal Depression among Pregnant Women in Rural China: The Role of Negative Automatic Thoughts.

PubMed

Wang, Yang; Wang, Xiaohua; Liu, Fangnan; Jiang, Xiaoning; Xiao, Yun; Dong, Xuehan; Kong, Xianglei; Yang, Xuemei; Tian, Donghua; Qu, Zhiyong

2016-01-01

Few studies have looked at the relationship between psychological and the mental health status of pregnant women in rural China. The current study aims to explore the potential mediating effect of negative automatic thoughts between negative life events and antenatal depression. Data were collected in June 2012 and October 2012. 495 rural pregnant women were interviewed. Depressive symptoms were measured by the Edinburgh postnatal depression scale, stresses of pregnancy were measured by the pregnancy pressure scale, negative automatic thoughts were measured by the automatic thoughts questionnaire, and negative life events were measured by the life events scale for pregnant women. We used logistic regression and path analysis to test the mediating effect. The prevalence of antenatal depression was 13.7%. In the logistic regression, the only socio-demographic and health behavior factor significantly related to antenatal depression was sleep quality. Negative life events were not associated with depression in the fully adjusted model. Path analysis showed that the eventual direct and general effects of negative automatic thoughts were 0.39 and 0.51, which were larger than the effects of negative life events. This study suggested that there was a potentially significant mediating effect of negative automatic thoughts. Pregnant women who had lower scores of negative automatic thoughts were more likely to suffer less from negative life events which might lead to antenatal depression.

[Epidemiological study on HIV/AIDS in Cambodia seroprevalence of HIV/STD among commercial sex workers].

PubMed

Ohshige, K; Morio, S; Mizushima, S; Kitamura, K; Tajima, K; Ito, A; Suyama, A; Usuku, S; Phalla, T; Leng, H B; Sopheab, H; Eab, B; Soda, K

1999-01-01

To describe epidemiological features of HIV prevalence among female commercial sex workers (CSWs) in Cambodia, a cross-sectional study using a questionnaire study and serological tests was carried out from December 1997 to January 1998. We report the main results of the analyses of serological tests in this article. Two hundred ninety six CSWs working in Sisophon and Poi Pet, located in northwest Cambodia, Bantey Mean Chey province, were recruited for interview based on a questionnaire on sexual behavior, and serological tests. The blood samples were examined for HIV antibody, Chlamydia trachomatis IgG antibody, TPHA, Hepatitis B surface antigen, and Hepatitis B surface antibody. The relationship between HIV and the other STD's was analyzed by using logistic regression analysis. The HIV seroprevalence rate was 43.9% (130 out of 296). The seropositive rate of Chlamydia trachomatis IgG antibody (C.T.-IgG-Ab) was 73.3% (217 out of 296). Logistic regression analysis showed a significant association between C.T.-IgG-Ab positive and HIV prevalence. (Odds Ratio: 5.33; 95% Confidence Interval, 2.82-10.07). This study suggests that the existence of Chlamydia trachomatis is closely related with HIV prevalence among CSWs in Cambodia. Other STDs may also increase susceptibility to male-to-female sexual transmission of HIV. This suggests that appropriate prevention against STDs will be needed for the control of HIV prevalence in Cambodia.

Predicting completion of treatment among foreign-born adolescents treated for latent tuberculosis infection in Los Angeles.

PubMed

Coly, A; Morisky, D

2004-06-01

Two health clinics in Los Angeles County, California. To identify factors associated with completion of care among foreign-born adolescents treated for latent tuberculosis infection (LTBI). A total of 766 low-income adolescents (79% participation rate), including 610 foreign-born, were recruited. In prospective face-to-face interviews, data were obtained on socio-demographic and lifestyle characteristics, psychosocial factors and clinic-related variables. Medical chart data were abstracted regarding clinic appointment keeping and completion of treatment. Univariate and multivariate logistic regression analyses were performed to identify factors associated with completion of care. Foreign-born adolescents were more likely to complete care than US-born adolescents, with 82% completion of care rate. In logistic regression analyses after controlling for age, medication taking behavior (OR 1.26, 95%CI 1.15-1.39), living with both parents (OR 1.74, 95%CI 1.02-2.97), sexual intercourse (OR 0.66, 95%CI 0.36-1.19) and speaking mostly or only English with parents (OR 0.39, 95%CI 0.15-1.03) were independently associated with completion of care. These findings contribute to our understanding of the factors that may explain why some adolescents complete care whereas others do not. They provide supportive evidence that tailored intervention programs should be developed to support the screening and completion of treatment of foreign-born adolescents.

Unhealthy lifestyle factors and depressive symptoms: A Japanese general adult population survey.

PubMed

Furihata, Ryuji; Konno, Chisato; Suzuki, Masahiro; Takahashi, Sakae; Kaneita, Yoshitaka; Ohida, Takashi; Uchiyama, Makoto

2018-07-01

To investigate the relationship between unhealthy lifestyles factors and depressive symptoms among the general adult population in Japan. Participants were randomly selected from the Japanese general adult population. Data from 2334 people aged 20 years or older were analyzed. This cross-sectional survey was conducted in August and September 2009. Participants completed a face-to-face interview about unhealthy lifestyle factors, including lack of exercise, skipping breakfast, a poorly balanced diet, snacking between meals, insufficient sleep, current smoking, alcohol drinking, and obesity. Presence of depressive symptoms was defined as a score of ≥ 16 on the Japanese version of the Center for Epidemiologic Studies Depression Scale (CES-D). Relationships between unhealthy lifestyle factors and depressive symptoms were evaluated by multivariate logistic regression analysis adjusting for sociodemographic variables and other unhealthy lifestyle factors. Multivariate logistic regression analysis revealed that insufficient sleep, a poorly balanced diet, snacking between meals and lack of exercise were significantly associated with the prevalence of depressive symptoms, with odds ratios ranging from 1.56 for lack of exercise to 3.98 for insufficient sleep. Since this study was a cross-sectional study, causal relationships could not be determined. These results suggest that promoting a healthy lifestyle focused on sleep, food intake and exercise may be important for individuals with depressive symptoms. Copyright © 2018 Elsevier B.V. All rights reserved.

[Suicidal Behavior and Attention Decifit Hyperactivity Disorder in Adolescents of Medellin (Colombia), 2011-2012].

PubMed

Restrepo-Bernal, Diana; Bonfante-Olivares, Laura; Torres de Galvis, Yolanda; Berbesi-Fernández, Dedsy; Sierra-Hincapié, Gloria

2014-01-01

Suicide is a public health problem. In Colombia, teenagers are considered a group at high risk for suicidal behavior. To explore the possible association between suicidal behavior and attention deficit hyperactivity disorder in adolescents of Medellin. Observational, cross-sectional, analytical study. The Composite International Diagnostic Interview was applied to a total of 447 adolescents and the sociodemographic, clinical, familiar, and life event variables of interest were analyzed. The descriptive analysis of qualitative variables are presented as absolute values and frequencies, and the age was described with median [interquartile range]. A logistic regression model was constructed with explanatory variables that showed statistical association. Data were analyzed with SPSS® software version 21.0. Of the total, 59.1% were female, and the median age was 16 [14-18] years. Suicidal behavior was presented in 31% of females and 23% of males. Attention deficit was present in 6.3% of adolescents. The logistic regression analysis showed that the variables that best explained the suicidal behavior of adolescents were: female sex, post-traumatic stress disorder, panic disorder, and cocaine use. The diagnosis and early intervention of attention deficit hyperactivity disorder in children may be a useful strategy in the prevention of suicidal behavior in adolescents. Copyright © 2014 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Knowledge, Attitudes, and Practices Related to Preoperative Chemoradiotherapy in Rectal Cancer Patients.

PubMed

Chen, Xingxing; Lin, Ruifang; Li, Huifang; Su, Meng; Zhang, Wenyi; Deng, Xia; Zhang, Ping; Zou, Changlin

2016-01-01

Background . The aim of this study is to assess the knowledge, attitudes, and practices related to pre-CRT in patients of stage II/III rectal cancer. Materials and Methods . Questionnaires regarding the knowledge, attitudes, and practices of pre-CRT were mailed to 145 rectal cancer patients in II/III stage between January 2012 and December 2014, and 111 agreed to participate and returned completed questionnaires to the researcher. Logistic regression model was used to compare sociodemographic characteristics, knowledge, and attitude with practice, respectively. Results . A total of 145 patients were approached for interview, of which 111 responded and 48.6% (54) had undergone pre-CRT. Only 31.5% of the participants knew that CRT is a treatment of rectal cancer and 39.6% were aware of the importance of CRT. However, the vast majority of participants (68.5%) expressed a positive attitude toward rectal cancer. Multivariate logistic regression analysis revealed that knowledge level ( p = 0.006) and attitudes ( p = 0.001) influence the actual practice significantly. Furthermore, age, gender, and income were potential predictors of practice (all p < 0.05). Conclusion . This study shows that, despite the fact that participants had suboptimal level of knowledge on rectal cancer, their attitude is favorable to pre-CRT. Strengthening the professional health knowledge and realizing the importance of attitudes may deepen patients' understanding of preoperative therapy.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Modification of the Mantel-Haenszel and Logistic Regression DIF Procedures to Incorporate the SIBTEST Regression Correction

ERIC Educational Resources Information Center

DeMars, Christine E.

2009-01-01

The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…

Major depressive disorder and suicide risk among adult outpatients at several general hospitals in a Chinese Han population.

PubMed

Li, Haiyan; Luo, Xinni; Ke, Xiaoyin; Dai, Qing; Zheng, Wei; Zhang, Chanjuan; Cassidy, Ryan M; Soares, Jair C; Zhang, XiangYang; Ning, Yuping

2017-01-01

Somatic complaints are often the presenting symptoms of major depressive disorder (MDD) in the outpatient context, because this may go unrecognized. It is well understood that MDD carries an increased risk of suicide. This study aimed to identify the risk factors and association with both MDD and suicidality among Han Chinese outpatients. A multicenter study was carried out in 5189 outpatient adults (≥18 years old) in four general hospitals in Guangzhou, China. The 1392 patients who had the Patient Health Questionnaire-9 (PHQ-9) score ≥ 5, indicating depressive symptoms were offered an interview with a psychiatrist by the Mini International Neuropsychiatric Interview (MINI); 819 patients consented and completed the MINI interview. MINI module B was used to assess suicidality. Stepwise binary logistic models were used to estimate the relationship between a significant risk factor and suicide or MDD. According to with or without MDD, the secondary analysis was performed using the logistic regression model for the risk of suicidility. The current prevalence of MDD and the one month prevalence of suicidality were 3.7% and 2.3% respectively. The odds ratio of suicidality in women was more than twice that in men (OR = 2.62; 95% CI 1.45-4.76). Other risk factors which were significantly associated with suicidality were: living alone, higher education, self-reported depression, getting psychiatric diagnoses (MDD, anxiety disorders, and bipolar disorders). Significant risk factors for MDD were also noticed, such as comorbid anxiety disorders, self-reported anxiety, insomnia, suicidal ideation. It's a cross-sectional study in outpatient clinics using self-report questionnaires. This study provides valuable data about the risk factors and association of MDD and suicide risk in adult outpatients in Han Chinese. Those factors allow better the employment of preventative measures.

Satellite rainfall retrieval by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.

1986-01-01

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

Confidential donation confirmation as an alternative to confidential unit exclusion: 15 months experience of the HEMOMINAS foundation.

PubMed

Loureiro, Flávia Cristine Martineli; Oliveira, Cláudia Di Lorenzo; Proietti, Anna Bárbara F Carneiro; Proietti, Fernando Augusto

2011-01-01

Confidential unit exclusion remains a controversial strategy to reduce the residual risk of transfusion-transmitted infections. This study aimed to analyze confidential unit exclusion from its development in a large institution in light of confidential donation confirmation. Data of individuals who donated from October 1, 2008 to December 31, 2009 were analyzed in a case-control study. The serological results and sociodemographic characteristics of donors who did not confirm their donations were compared to those who did. Variables with p-values < 0.20 in univariate analysis were included in a logistic multivariate analysis. In the univariate analysis there was a statically significant association between positive serological results and response to confidential donation confirmation of "No". Donation type, (firsttime or return donor - OR 1.69, CI 1.37-2.09), gender (OR 1.66, CI 1.35-2.04), education level (OR 2.82, CI 2.30-3.47) and ethnic background (OR 0.67, CI 0.55-0.82) were included in the final logistic regression model. In all logistic regression models analyzed, the serological suitability and confidential donation confirmation were not found to be statistically associated. The adoption of new measures of clinical classification such as audiovisual touch-screen computer-assisted self-administered interviews might be more effective than confidential unit exclusion in the identification of donor risk behavior. The requirement that transfusion services continue to use confidential unit exclusion needs to be debated in countries where more specific and sensitive clinical and serological screening methods are available. Our findings suggest that there are not enough benefits to justify continued use of confidential donation confirmation in the analyzed institution.

Confidential donation confirmation as an alternative to confidential unit exclusion: 15 months experience of the HEMOMINAS foundation

PubMed Central

Loureiro, Flávia Cristine Martineli; Oliveira, Cláudia Di Lorenzo; Proietti, Anna Bárbara F. Carneiro; Proietti, Fernando Augusto

2011-01-01

Background Confidential unit exclusion remains a controversial strategy to reduce the residual risk of transfusion-transmitted infections. Objective This study aimed to analyze confidential unit exclusion from its development in a large institution in light of confidential donation confirmation. Methods Data of individuals who donated from October 1, 2008 to December 31, 2009 were analyzed in a case-control study. The serological results and sociodemographic characteristics of donors who did not confirm their donations were compared to those who did. Variables with p-values < 0.20 in univariate analysis were included in a logistic multivariate analysis. Results In the univariate analysis there was a statically significant association between positive serological results and response to confidential donation confirmation of "No". Donation type, (firsttime or return donor - OR 1.69, CI 1.37-2.09), gender (OR 1.66, CI 1.35-2.04), education level (OR 2.82, CI 2.30-3.47) and ethnic background (OR 0.67, CI 0.55-0.82) were included in the final logistic regression model. In all logistic regression models analyzed, the serological suitability and confidential donation confirmation were not found to be statistically associated. The adoption of new measures of clinical classification such as audiovisual touch-screen computer-assisted self-administered interviews might be more effective than confidential unit exclusion in the identification of donor risk behavior. The requirement that transfusion services continue to use confidential unit exclusion needs to be debated in countries where more specific and sensitive clinical and serological screening methods are available. Conclusion Our findings suggest that there are not enough benefits to justify continued use of confidential donation confirmation in the analyzed institution. PMID:23049316

Practical Session: Logistic Regression

NASA Astrophysics Data System (ADS)

Clausel, M.; Grégoire, G.

2014-12-01

An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Using effort-reward imbalance theory to understand high rates of depression and anxiety among clergy.

PubMed

Proeschold-Bell, Rae Jean; Miles, Andrew; Toth, Matthew; Adams, Christopher; Smith, Bruce W; Toole, David

2013-12-01

The clergy occupation is unique in its combination of role strains and higher calling, putting clergy mental health at risk. We surveyed all United Methodist clergy in North Carolina, and 95% (n = 1,726) responded, with 38% responding via phone interview. We compared clergy phone interview depression rates, assessed using the Patient Health Questionnaire (PHQ-9), to those of in-person interviews in a representative United States sample that also used the PHQ-9. The clergy depression prevalence was 8.7%, significantly higher than the 5.5% rate of the national sample. We used logistic regression to explain depression, and also anxiety, assessed using the Hospital Anxiety and Depression Scale. As hypothesized by effort-reward imbalance theory, several extrinsic demands (job stress, life unpredictability) and intrinsic demands (guilt about not doing enough work, doubting one's call to ministry) significantly predicted depression and anxiety, as did rewards such as ministry satisfaction and lack of financial stress. The high rate of clergy depression signals the need for preventive policies and programs for clergy. The extrinsic and intrinsic demands and rewards suggest specific actions to improve clergy mental health.

Household food insecurity as a determinant of overweight and obesity among low-income Hispanic subgroups: Data from the 2011-2012 California Health Interview Survey.

PubMed

Smith, Teresa M; Colón-Ramos, Uriyoán; Pinard, Courtney A; Yaroch, Amy L

2016-02-01

An estimated 78% of Hispanics in the United States (US) are overweight or obese. Household food insecurity, a condition of limited or uncertain access to adequate food, has been associated with obesity rates among Hispanic adults in the US. However, the Hispanic group is multi-ethnic and therefore associations between obesity and food insecurity may not be constant across Hispanic country of origin subgroups. This study sought to determine if the association between obesity and food insecurity among Hispanics is modified by Hispanic ancestry across low-income (≤200% of poverty level) adults living in California. Data are from the cross-sectional 2011-12 California Health Interview Survey (n = 5498). Rates of overweight or obesity (BMI ≥ 25), Calfresh receipt (California's Supplemental Nutrition Assistance Program), and acculturation were examined for differences across subgroups. Weighted multiple logistic regressions examined if household food insecurity was significantly associated with overweight or obesity and modified by country of origin after controlling for age, education, marital status, country of birth (US vs. outside of US), language spoken at home, and Calfresh receipt (P < .05). Significant differences across subgroups existed for prevalence of overweight or obesity, food security, Calfresh receipt, country of birth, and language spoken at home. Results from the adjusted logistic regression models found that food insecurity was significantly associated with overweight or obesity among Mexican-American women (β (SE) = 0.22 (0.09), p = .014), but not Mexican-American men or Non-Mexican groups, suggesting Hispanic subgroups behave differently in their association between food insecurity and obesity. By highlighting these factors, we can promote targeted obesity prevention interventions, which may contribute to more effective behavior change and reduced chronic disease risk in this population. Copyright © 2015 Elsevier Ltd. All rights reserved.

Social Determinants of Domestic Violence Among Saudi Married Women in Riyadh, Kingdom of Saudi Arabia.

PubMed

Alquaiz, ALJohara M; Almuneef, Maha; Kazi, Ambreen; Almeneessier, Aljohara

2017-12-01

Intimate partner violence is a worldwide public health problem. The objectives of this study were to measure the prevalence and types of domestic violence, and to explore the association between social determinants (sociodemographic factors, husband-related factors, and social support) and violence against women by their intimate partner (husband). We conducted a cross-sectional survey in 18 randomly selected primary health care centers and 13 private institutions (teaching institutes, government offices, social welfare organizations) in Riyadh, Saudi Arabia. Female data collectors took interview from 1,883 married Saudi females aged 30 to 75 years. Interviews included sociodemographic information, reproductive health variables, and social support questionnaire. Violence was measured using modified Intimate Partner Violence Against Women questionnaire developed by the World Health Organization. Multivariate logistic regression analysis was conducted. The lifetime prevalence for any type of violence was 43.0% ( n = 810). The most frequent type was controlling behavior (36.8%), followed by emotional violence (22%), sexual violence (12.7%), and physical violence (9.0%). Multivariate logistic regression analysis revealed that the following were associated with greater odds of reporting domestic violence: younger age 30 to 40 years (adjusted odds ratio [aOR] = 1.9, 95% confidence interval [CI] = [1.3, 3.0]), 41 to 50 years (aOR = 1.6, 95% CI = [1.1, 2.5]); lack of emotional support (aOR = 1.7, 95% CI = [1.2, 2.5]); lack of tangible support (aOR = 1.4, 95% CI = [1.1, 1.9]); and perceived poor self-health (aOR = 1.7, 95% CI = [1.0, 3.0]), husbands' poor health (aOR = 1.9, 95% CI = [1.2, 2.0]), and polygamy (aOR = 1.6, 95% CI = [1.5, 2.6]). Domestic violence occurs frequently in Saudi Arabia. Both social conditions and social relations are significantly associated with domestic violence against Saudi women. Furthermore, improvement in implementation of the local policies and multisectoral protection services can prevent women from domestic violence.

Parental perspectives of vaccine safety and experience of adverse events following immunisation.

PubMed

Parrella, Adriana; Gold, Michael; Marshall, Helen; Braunack-Mayer, Annette; Baghurst, Peter

2013-04-12

We aimed to determine demographic predictors of parental vaccine safety and risk perceptions, and assess the relationship between the occurrence of children's perceived adverse events following immunisation (AEFI) on parents' opinions. Computer-assisted telephone interviews (CATI) were conducted in 2011 with a cross-sectional, random general population sample of rural and metropolitan residents in South Australia. Multivariate ordinal logistic regression analyses examined associations between parental vaccine safety attitudes and socio-demographic factors, adjusting for whether children had ever experienced a previous suspected AEFI. Of 469 parents interviewed, 95% were confident in vaccine safety in general, but almost half expressed concern for pre-licensure testing of vaccines. Of all parents, 41% responded that at least one of their children had experienced an AEFI. Almost one third of the AEFI parent group indicated they reported their children's symptoms to either a healthcare professional or the Department of Health. Parental acceptability of the risks of febrile convulsion and anaphylaxis were 73% and 76% respectively. Ordinal logistic regression analyses showed parents of children who had experienced a suspected AEFI were associated with greater concern for vaccine safety (OR:0.53, p≤0.01) and more were likely to expect either a mild or a serious AEFI. After adjusting for demographics, parental confidence in vaccine safety was significantly associated with higher levels of education (OR:2.58, p=0.01) and being born in Australia OR:2.30, p=0.004. Mothers, when compared with fathers, were less accepting of the two vaccine risks presented: febrile convulsion (OR:0.57, p=0.04) and anaphylaxis, (OR:0.55, p=0.04). Parents commonly perceive and report that their child has experienced an AEFI. In this group of parents the subsequent expectation of an AEFI and vaccine safety concerns may be heightened. Further research should investigate parental understandings of differentiating an expected event from an adverse event as this could inform immunization risk communication and consumer AEFI reporting strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Racial and Ethnic Differences in Dietary Intake, Physical Activity, and Body Mass Index (BMI) Among Cancer Survivors: 2005 and 2010 National Health Interview Surveys (NHIS).

PubMed

Byrd, Doratha A; Agurs-Collins, Tanya; Berrigan, David; Lee, Richard; Thompson, Frances E

2017-12-01

This paper reports racial/ethnic differences in mean dietary and alcohol intake, physical activity, and body mass index (BMI) among cancer survivors and examines adherence to the American Cancer Society and the US Dietary Guidelines for Americans. Data are from the cross-sectional 2005 and 2010 National Health Interview Surveys (NHIS). The total sample of cancer survivors (N = 3367) included non-Hispanic Whites (NHW; N = 2698), non-Hispanic Blacks (NHBs; N = 379), and Hispanics (N = 290). We compared mean reported dietary intake, moderate/vigorous physical activity, and BMI among racial/ethnic groups. Predicted marginals and multivariate logistic regression analysis were used to compare prevalence of non-adherence with recommendations among groups. Among the three racial/ethnic groups, Hispanics had the highest mean intake of vegetables, fiber, and calcium (p = 0.0003; p < 0.0001; p = 0.001). In the logistic regression model adjusting for sociodemographic covariates, smoking and BMI, Hispanics had lower non-adherence to fiber guidelines (OR = 0.38; CI = 0.24-0.58) than NHWs. NHBs had significantly higher non-adherence to vegetable guidelines (OR = 1.63; CI = 1.07-2.47). NHBs and Hispanics had lower non-adherence with alcohol guidelines than NHWs (OR = 0.35 and 0.38; CI = 0.18-0.69 and 0.19-0.76, respectively). NHBs and Hispanics were more likely to be overweight/obese (OR = 1.66 and 1.57; CI = 1.24-2.23 and CI = 1.11-2.21, respectively). There are racial/ethnic differences in certain health behaviors of cancer survivors. However, non-adherence to guidelines is high in all three racial/ethnic groups. Achieving the recommended guidelines for diet, physical activity, and a healthy BMI is a concern for all cancer survivors, indicating the need for intervention among this growing group of at-risk individuals.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Shared Decision-Making among Caregivers and Health Care Providers of Youth with Type 1 Diabetes

PubMed Central

Valenzuela, Jessica M.; Smith, Laura B.; Stafford, Jeanette M.; Andrews, S.; D’Agostino, Ralph B.; Lawrence, Jean M.; Yi-Frazier, Joyce P.; Seid, Michael; Dolan, Lawrence M.

2014-01-01

The present study aimed to examine perceptions of shared decision-making (SDM) in caregivers of youth with type 1 diabetes (T1D). Interview, survey data, and HbA1c assays were gathered from caregivers of 439 youth with T1D aged 3–18 years. Caregiver-report indicated high perceived SDM during medical visits. Multivariable linear regression indicated that greater SDM is associated with lower HbA1c, older child age, and having a pediatric endocrinologist provider. Multiple logistic regression found that caregivers who did not perceive having made any healthcare decisions in the past year were more likely to identify a non-pediatric endocrinologist provider and to report less optimal diabetes self-care. Findings suggest that youth whose caregivers report greater SDM may show benefits in terms of self-care and glycemic control. Future research should examine the role of youth in SDM and how best to identify youth and families with low SDM in order to improve care. PMID:24952739

Contextual predictive factors of child sexual abuse: the role of parent-child interaction.

PubMed

Ramírez, Clemencia; Pinzón-Rondón, Angela María; Botero, Juan Carlos

2011-12-01

To determine the prevalence of child sexual abuse in the Colombian coasts, as well as to assess the role of parent-child interactions on its occurrence and to identify factors from different environmental levels that predict it. This cross-sectional study explores the results of 1,089 household interviews responded by mothers. Descriptive analyses and multivariate logistic regressions were conducted, with child sexual abuse regressed on parent-child interactions, children's characteristics, maternal characteristics, family characteristics, and community characteristics. 1.2% of the mothers reported that their children had been sexually abused. Families that communicated with their children were less likely to report child sexual abuse, each additional standard deviation of communication reduced child sexual abuse 3.5 times. Affection and negative treatment to the children were not associated with child sexual abuse. Families who experienced intimate partner violence and violent communities were more likely to experience child sexual abuse. Interventions are needed to address the problem of child sexual abuse. Copyright © 2011 Elsevier Ltd. All rights reserved.

Women's work stress and cortisol levels: a longitudinal study of the association between the psychosocial work environment and serum cortisol.

PubMed

Evolahti, Annika; Hultcrantz, Malou; Collins, Aila

2006-11-01

The aim of the present study was to investigate whether there is an association between serum cortisol and work-related stress, as defined by the demand-control model in a longitudinal design. One hundred ten women aged 47-53 years completed a health questionnaire, including the Swedish version of the Job Content Scale, and participated in a psychological interview at baseline and in a follow-up session 2 years later. Morning blood samples were drawn for analyses of cortisol. Multiple stepwise regression analyses and logistic regression analyses showed that work demands and lack of social support were significantly associated with cortisol. The results of this study showed that negative work characteristics in terms of high demands and low social support contributed significantly to the biological stress levels in middle-aged women. Participation in the study may have served as an intervention, increasing the women's awareness and thus improving their health profiles on follow-up.

Stress and psychiatric disorder in healthcare professionals and hospital staff.

PubMed

Weinberg, A; Creed, F

2000-02-12

Previous studies of stress in healthcare staff have indicated a probable high prevalence of distress. Whether this distress can be attributed to the stressful nature of the work situation is not clear. No previous study has used a detailed interview method to ascertain the link between stress in and outside of work and anxiety and depressive disorders. Doctors, nurses, and administrative and ancillary staff were screened using the general health questionnaire (GHQ). High scorers (GHQ>4) and matched individuals with low GHQ scores were interviewed by means of the clinical interview schedule to ascertain definite anxiety and depressive disorders (cases). Cases and controls, matched for age, sex, and occupational group were interviewed with the life events and difficulties schedule classification and an objective measure of work stress to find out the amount of stress at work and outside of work. Sociodemographic and stress variables were entered into a logistic-regression analysis to find out the variables associated with anxiety and depressive disorders. 64 cases and 64 controls were matched. Cases and controls did not differ on demographic variables but cases were less likely to have a confidant (odds ratio 0.09 [95% CI 0.01-0.79]) and more likely to have had a previous episode of psychiatric disorder (3.07 [1.10-8.57]). Cases and controls worked similar hours and had similar responsibility but cases had a greater number of objective stressful situations both in and out of work (severe event or substantial difficulty in and out of work-45 cases vs 18 controls 6.05 [2.81-13.00], p<0.001; severe chronic difficulty outside of work-27 vs 8, 5.12 [2.09-12.46], p<0.001). Cases had significantly more objective work problems than controls (median 6 vs 4, z=3.81, p<0.001). The logistic-regression analyses indicated that even after the effects of personal vulnerability to psychiatric disorder and ongoing social stress outside of work had been taken into account, stressful situations at work contributed to anxiety and depressive disorders. Both stress at work and outside of work contribute to the anxiety and depressive disorders experienced by healthcare staff. Our findings suggest that the best way to decrease the prevalence of these disorders is individual treatment, which may focus on personal difficulties outside of work, combined with organisational attempts to reduce work stress. The latter may involve more assistance for staff who have a conflict between their managerial role and clinical role.

Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

PubMed

Kesselmeier, Miriam; Lorenzo Bermejo, Justo

2017-11-01

Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

CUSUM-Logistic Regression analysis for the rapid detection of errors in clinical laboratory test results.

PubMed

Sampson, Maureen L; Gounden, Verena; van Deventer, Hendrik E; Remaley, Alan T

2016-02-01

The main drawback of the periodic analysis of quality control (QC) material is that test performance is not monitored in time periods between QC analyses, potentially leading to the reporting of faulty test results. The objective of this study was to develop a patient based QC procedure for the more timely detection of test errors. Results from a Chem-14 panel measured on the Beckman LX20 analyzer were used to develop the model. Each test result was predicted from the other 13 members of the panel by multiple regression, which resulted in correlation coefficients between the predicted and measured result of >0.7 for 8 of the 14 tests. A logistic regression model, which utilized the measured test result, the predicted test result, the day of the week and time of day, was then developed for predicting test errors. The output of the logistic regression was tallied by a daily CUSUM approach and used to predict test errors, with a fixed specificity of 90%. The mean average run length (ARL) before error detection by CUSUM-Logistic Regression (CSLR) was 20 with a mean sensitivity of 97%, which was considerably shorter than the mean ARL of 53 (sensitivity 87.5%) for a simple prediction model that only used the measured result for error detection. A CUSUM-Logistic Regression analysis of patient laboratory data can be an effective approach for the rapid and sensitive detection of clinical laboratory errors. Published by Elsevier Inc.

Nonconvex Sparse Logistic Regression With Weakly Convex Regularization

NASA Astrophysics Data System (ADS)

Shen, Xinyue; Gu, Yuantao

2018-06-01

In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the $\\ell_0$ pseudo norm is able to better induce sparsity than the commonly used $\\ell_1$ norm. For a class of weakly convex sparsity inducing functions, we prove the nonconvexity of the corresponding sparse logistic regression problem, and study its local optimality conditions and the choice of the regularization parameter to exclude trivial solutions. Despite the nonconvexity, a method based on proximal gradient descent is used to solve the general weakly convex sparse logistic regression, and its convergence behavior is studied theoretically. Then the general framework is applied to a specific weakly convex function, and a necessary and sufficient local optimality condition is provided. The solution method is instantiated in this case as an iterative firm-shrinkage algorithm, and its effectiveness is demonstrated in numerical experiments by both randomly generated and real datasets.

A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

PubMed

López Puga, Jorge; García García, Juan

2012-11-01

Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research.

Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

PubMed

Campos-Filho, N; Franco, E L

1989-02-01

A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

Comparison of cranial sex determination by discriminant analysis and logistic regression.

PubMed

Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis

PubMed Central

Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B.; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain

2017-01-01

Abstract Background: The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Results: Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Conclusions: Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics. PMID:28327993

Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis.

PubMed

Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain; Jelinsky, Scott A

2017-05-01

The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics. © The Author 2017. Published by Oxford University Press.

Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

PubMed

Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

2010-03-01

Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

PubMed

Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

2016-06-01

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Association of internet use and depression among the spinal cord injury population.

PubMed

Tsai, I-Hsuan; Graves, Daniel E; Lai, Ching-Huang; Hwang, Lu-Yu; Pompeii, Lisa A

2014-02-01

To examine the relation between the frequency of Internet use and depression among people with spinal cord injury (SCI). Cross-sectional survey. SCI Model Systems. People with SCI (N=4618) who were interviewed between 2004 and 2010. Not applicable. The frequency of Internet use and the severity of depressive symptoms were measured simultaneously by interview. Internet use was reported as daily, weekly, monthly, or none. The depressive symptoms were measured by the Patient Health Questionnaire-9 (PHQ-9), with 2 published criteria being used to screen for depressive disorder. The diagnostic method places more weight on nonsomatic items (ie, items 1, 2, and 9), and the cut-off method that determines depression by a (PHQ-9) score ≥10 places more weight on somatic factors. The average scores of somatic and nonsomatic items represented the severity of somatic and nonsomatic symptoms, respectively. Our multivariate logistic regression model indicated that daily Internet users were less likely to have depressive symptoms (odds ratio=.77; 95% confidence interval, .64-.93), if the diagnostic method was used. The linear multivariate regression analysis indicated that daily and weekly Internet usage were associated with fewer nonsomatic symptoms; no significant association was observed between daily or weekly Internet usage and somatic symptoms. People with SCI who used the Internet daily were less likely to have depressive symptoms. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Urinary Incontinence of Women in a Nationwide Study in Sri Lanka: Prevalence and Risk Factors.

PubMed

Pathiraja, Ramya; Prathapan, Shamini; Goonawardena, Sampatha

2017-05-23

Urinary incontinence, be stress incontinence or urge incontinence or a mixed type incontinence affects women of all ages. The aim of this study was to describe the prevalence and risk factors of urinary incontinence in Sri Lanka. A community based cross-sectional study was performed in Sri Lanka. The age group of the women in Sri Lanka was categorized into 3 age groups: Less than or equal to 35 years, 36 to 50 years of age and more than or equal to 51 years of age. A sample size of 675 women was obtained from each age category obtaining a total sample of 2025 from Sri Lanka. An interviewer-administered questionnaire consisting of two parts; Socio demographic factors, Medical and Obstetric History, and the King's Health Questionnaire (KHQ), was used for data collection. Stepwise logistic regression analysis was performed. The Prevalence of women with only stress incontinence was 10%, with urge incontinence was 15.6% and with stress and urge incontinence was 29.9%. Stepwise logistic regression analysis showed that the age groups of 36 - 50 years (OR = 2.03; 95% CI = 1.56 - 2.63) and 51 years and above (OR = 2.61; 95% CI= 1.95 - 3.48), Living in one of the districts in Sri Lanka (OR = 4.58; 95% CI = 3.35 - 6.27) and having given birth to multiple children (OR = 1.1; 95% CI = 1.02 - 1.21), diabetes mellitus (OR = 1.97; 95% CI = 1.19 - 3.23), and respiratory diseases (OR = 2.17; 95% CI = 1.48 - 3.19 ) showed a significant risk in the regression analysis. The risk factor, mostly modifiable, if prevented early, could help to reduce the symptoms of urinary incontinence.

The Relationship Between Developmental Assets and Food Security In Adolescents From A Low-Income Community

PubMed Central

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2014-01-01

Purpose To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income, urban community. Methods This mixed methods study occurred in two phases. In Phase 1, using a census approach, 2350 6-12th graders from the public school district completed an anonymous survey that included the Development Assets Profile (DAP), youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In Phase 2, 20 adult key informant interviews and four semi-structured student focus groups were performed to explain findings from Phase 1. Results On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (OR=.96, 95% CI=.95-.97); family assets drove this association(OR=.93, 95% CI=.91-.95). In multinomial regression modeling, these associations persisted and, paradoxically, higher community assets were also associated with VLFS (ORVLFS=1.08, 95% CI=1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Conclusion Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. That community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. PMID:25620305

The relationship between developmental assets and food security in adolescents from a low-income community.

PubMed

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2015-02-01

To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income urban community. This mixed-methods study occurred in two phases. In phase 1, using a census approach, 2,350 6th to 12th graders from the public school district completed an anonymous survey that included the developmental assets profile (DAP), the youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In phase 2, 20 adult key informant interviews and four semistructured student focus groups were performed to explain findings from phase 1. On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (odds ratio [OR], .96; 95% confidence interval [CI], .95-.97); family assets drove this association (OR, .93; 95% CI, .91-.95). In multinomial regression modeling, these associations persisted, and paradoxically, higher community assets were also associated with VLFS (ORVLFS, 1.08; 95% CI, 1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. The fact that community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

ERIC Educational Resources Information Center

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

Male circumcision and HIV status among Latino immigrant MSM in New York City.

PubMed

Reisen, Carol A; Zea, Maria Cecilia; Poppen, Paul J; Bianchi, Fernanda T

2007-01-01

This study investigated protective effects of circumcision in a sample of immigrant Latino men who have sex with men (MSM). A survey in Portuguese, Spanish, or English was administered with computer-assisted self-interview technology with audio enhancement (A-CASI) to 482 MSM from Brazil (n=146), Colombia (n=169), and the Dominican Republic (n=167), living in the New York metropolitan area. Logistic regression revealed that after controlling for age, income, education, having had syphilis, having done sex work, and preferring the receptive role in anal intercourse, uncircumcised men were almost twice as likely to be HIV-positive as circumcised men. Follow-up analyses revealed, however, that the protective effects occurred only among the group of Colombian men.

Losing a loved one to homicide: prevalence and mental health correlates in a national sample of young adults.

PubMed

Zinzow, Heidi M; Rheingold, Alyssa A; Hawkins, Alesia O; Saunders, Benjamin E; Kilpatrick, Dean G

2009-02-01

The present study examined the prevalence, demographic distribution, and mental health correlates of losing a loved one to homicide. A national sample of 1,753 young adults completed structured telephone interviews measuring violence exposure, mental health diagnoses, and loss of a family member or close friend to a drunk driving accident (vehicular homicide) or murder (criminal homicide). The prevalence of homicide survivorship was 15%. African Americans were more highly represented among criminal homicide survivors. Logistic regression analyses found that homicide survivors were at risk for past year posttraumatic stress disorder (OR = 1.88), major depressive episode (OR = 1.64), and drug abuse/dependence (OR = 1.77). These findings highlight the significant mental health needs of homicide survivors.

Factors Associated with Research Wrongdoing in Nigeria

PubMed Central

Adeleye, Omokhoa A.; Adebamowo, Clement A.

2013-01-01

Concerns about research wrongdoing in biomedical research are growing in developing countries, where research ethics training and research regulatory systems are just emerging. In a first-time study in Africa, medical/dental researchers (N = 132) in two states in Nigeria were interviewed on a wide range of research wrongdoings and potential predictors. Using multivariate logistic regression, significant predictors of research wrongdoing were identified. Some 22.0% admitted to at least one of fabrication, falsification, and plagiarism, the predictors of which were knowledge gaps in research ethics and pressure to publish enough papers for promotion. Acknowledging inadequate knowledge of research ethics was a predictor of admitting a wrongdoing. Systems that support ethical research, including skilled training and funding, are recommended. PMID:23324199

Male transvestite prostitutes and HIV risk.

PubMed Central

Elifson, K W; Boles, J; Posey, E; Sweat, M; Darrow, W; Elsea, W

1993-01-01

Human immunodeficiency virus (HIV)-1, syphilis, and hepatitis B prevalence and associated risk factors were assessed among male transvestite prostitutes. Structured street-level interviews were conducted with 53 respondents in Atlanta, Ga, from July 1990 through July 1991. Test results from serum samples revealed that 68% were seropositive for HIV-1, 81% had seromarkers for syphilis, and 80% had seromarkers for hepatitis B. Univariate logistic regression analysis indicated that seromarkers for syphilis and Black race were the primary factors associated with HIV-1 infection. The results show that transvestite prostitutes are a heterogenous population and distinct from nontransvestite prostitutes; specific outreach is thus needed. Targeted interventions should address the sexual and drug-use-related HIV risk behaviors of transvestite prostitutes. PMID:8427336

[Complete immunization coverage and reasons for non-vaccination in a periurban area of Abidjan].

PubMed

Sackou, K J; Oga, A S S; Desquith, A A; Houenou, Y; Kouadio, K L

2012-10-01

An immunization coverage survey was conducted among children aged 12-59 months in a suburban neighbourhood in Abidjan. The objective was to determine the complete immunization coverage, the reasons for non-vaccination and factors influencing the immunization status of children. The method of exhaustive sampling enabled us to interview the mothers of 669 children using a questionnaire. Overall vaccination coverage was 68.6% with 1.2%, with 1.2% of children never having received vaccine. The logistic regression analysis showed that the level of education, knowledge of the immunization schedule and the marital status of mothers, as well as the type of habitat, were associated with full immunization of children. These determinants must be taken into account to improve vaccination coverage.

Exploring Individual and Structural Factors Associated with Employment Among Young Transgender Women of Color Using a No-Cost Transgender Legal Resource Center

PubMed Central

Hill, Brandon J.; Rosentel, Kris; Bak, Trevor; Silverman, Michael; Crosby, Richard; Salazar, Laura; Kipke, Michele

2017-01-01

Abstract Purpose: The purpose of this study was to explore individual and structural factors associated with employment among young transgender women (TW) of color. Methods: Sixty-five trans women of color were recruited from the Transgender Legal Defense and Education Fund to complete a 30-min interviewer-assisted survey assessing sociodemographics, housing, workplace discrimination, job-seeking self-efficacy, self-esteem, perceived public passability, and transactional sex work. Results: Logistic regression models revealed that stable housing (structural factor) and job-seeking self-efficacy (individual factor) were significantly associated with currently being employed. Conclusion: Our findings underscore the need for multilevel approaches to assist TW of color gain employment. PMID:28795154

Short Sleep Duration is Associated with Obesity in Hispanic Manufacturing Workers.

PubMed

Benham, Grant; Ghaddar, Suad F; Talavera-Garza, Liza

2017-01-01

The present study examined the relationship between obesity and sleep duration among Hispanic manufacturing workers. Two hundred and twenty eight Hispanic workers from eight manufacturing plants completed an in-person interview that included measures of demographics, health literacy, and sleep duration. Height and weight were directly assessed. A logistic regression, controlling for gender, education, age, income, physical activity levels, self-reported health status, and health literacy, indicated that workers who slept six hours or less were significantly more likely to be obese than those sleeping seven to nine hours (OR: 1.90, 95% CI: 1.04-3.47). Our results extend previous research on the association between sleep duration and obesity to an understudied population of Hispanic workers.

Toward a model for improved targeting of aged at risk of institutionalization.

PubMed Central

Weissert, W G; Cready, C M

1989-01-01

A national sample of institutionalized and noninstitutionalized aged was created by merging the 1977 National Nursing Home Survey and its counterpart, the National Health Interview Survey for the same year. A weighted logistic regression analysis was conducted to identify factors that might be useful in calculating home- and community-based long-term care clients' risk of institutionalization. A model containing patient characteristics, nursing home bed supply, and a climate variable correctly classified 98.2 percent of cases residing in nursing homes or the community. Physical dependency, mental disorder and degenerative disease, lack of spouse, being white, poverty, old age, unoccupied nursing home beds, and climate all appear to be determinants of institutional residency among the aged. PMID:2807934

[Women's opinion on abortion legalization in a middle size county in southern Brazil].

PubMed

César, J A; Gomes, G; Horta, B L; de Oliveira, A K; Saraiva, A K; Pardo, D O; Silva, L M; Rodghiero, C L; Gross, M R

1997-12-01

Induced abortion is the main cause of maternal death in Brazil. Question of its legalization has been the subject of frequent discussion. In order to assess the influence of the variables affecting the opinion of women of reproductive age, a population-based systematic sample in the county of Rio Grande (Southern Brazil) was examined. Of a total of 1,456 interviews 30% endorsed the legalization, whatever the circumstances; this percentage was directly associated with age, schooling, family income and previous induced abortion (p < 0.01). Adjusted analysis using logistic regression showed a significant effect of schooling and previous induced abortion on favourable opinion. Schooling and previous induced abortion were the main determinants of women's favorable opinions regarding abortion legalization.

Adolescent judgments and reasoning about the failure to include peers with social disabilities.

PubMed

Bottema-Beutel, Kristen; Li, Zhushan

2015-06-01

Adolescents with autism spectrum disorder often do not have access to crucial peer social activities. This study examines how typically developing adolescents evaluate decisions not to include a peer based on disability status, and the justifications they apply to these decisions. A clinical interview methodology was used to elicit judgments and justifications across four contexts. We found adolescents are more likely to judge the failure to include as acceptable in personal as compared to public contexts. Using logistic regression, we found that adolescents are more likely to provide moral justifications as to why failure to include is acceptable in a classroom as compared to home, lab group, and soccer practice contexts. Implications for intervention are also discussed.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Knowledge, Attitude, and Practices Regarding Vector-borne Diseases in Western Jamaica.

PubMed

Alobuia, Wilson M; Missikpode, Celestin; Aung, Maung; Jolly, Pauline E

2015-01-01

Outbreaks of vector-borne diseases (VBDs) such as dengue and malaria can overwhelm health systems in resource-poor countries. Environmental management strategies that reduce or eliminate vector breeding sites combined with improved personal prevention strategies can help to significantly reduce transmission of these infections. The aim of this study was to assess the knowledge, attitudes, and practices (KAPs) of residents in western Jamaica regarding control of mosquito vectors and protection from mosquito bites. A cross-sectional study was conducted between May and August 2010 among patients or family members of patients waiting to be seen at hospitals in western Jamaica. Participants completed an interviewer-administered questionnaire on sociodemographic factors and KAPs regarding VBDs. KAP scores were calculated and categorized as high or low based on the number of correct or positive responses. Logistic regression analyses were conducted to identify predictors of KAP and linear regression analysis conducted to determine if knowledge and attitude scores predicted practice scores. In all, 361 (85 men and 276 women) people participated in the study. Most participants (87%) scored low on knowledge and practice items (78%). Conversely, 78% scored high on attitude items. By multivariate logistic regression, housewives were 82% less likely than laborers to have high attitude scores; homeowners were 65% less likely than renters to have high attitude scores. Participants from households with 1 to 2 children were 3.4 times more likely to have high attitude scores compared with those from households with no children. Participants from households with at least 5 people were 65% less likely than those from households with fewer than 5 people to have high practice scores. By multivariable linear regression knowledge and attitude scores were significant predictors of practice score. The study revealed poor knowledge of VBDs and poor prevention practices among participants. It identified specific groups that can be targeted with vector control and personal protection interventions to decrease transmission of the infections. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

Effect of folic acid on appetite in children: ordinal logistic and fuzzy logistic regressions.

PubMed

Namdari, Mahshid; Abadi, Alireza; Taheri, S Mahmoud; Rezaei, Mansour; Kalantari, Naser; Omidvar, Nasrin

2014-03-01

Reduced appetite and low food intake are often a concern in preschool children, since it can lead to malnutrition, a leading cause of impaired growth and mortality in childhood. It is occasionally considered that folic acid has a positive effect on appetite enhancement and consequently growth in children. The aim of this study was to assess the effect of folic acid on the appetite of preschool children 3 to 6 y old. The study sample included 127 children ages 3 to 6 who were randomly selected from 20 preschools in the city of Tehran in 2011. Since appetite was measured by linguistic terms, a fuzzy logistic regression was applied for modeling. The obtained results were compared with a statistical ordinal logistic model. After controlling for the potential confounders, in a statistical ordinal logistic model, serum folate showed a significantly positive effect on appetite. A small but positive effect of folate was detected by fuzzy logistic regression. Based on fuzzy regression, the risk for poor appetite in preschool children was related to the employment status of their mothers. In this study, a positive association was detected between the levels of serum folate and improved appetite. For further investigation, a randomized controlled, double-blind clinical trial could be helpful to address causality. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictors of early breastfeeding initiation among mothers of children under 24 months of age in rural part of West Ethiopia.

PubMed

Hailemariam, Tsedeke Wolde; Adeba, Emiru; Sufa, Alem

2015-10-21

The World Health Organization recommends initiation of breastfeeding within the first hour after childbirth. In developing countries alone, early initiation of breastfeeding could save as many as 1.45 million lives each year by reducing deaths mainly due to diarrheal disorders and lower respiratory tract infections in children. The current study aimed to determine the rate and the predictors of breastfeeding initiation in East Wollega Zones of West Ethiopia. A community-based, cross-sectional study was conducted from April to May 2014 among 594 mothers who had children less than 24 months. Multi stage cluster sampling method was used to select the study population. Eligible mothers were invited to interview using pretested questionnaires to gather data regarding sociodemographics, health-related variables, breastfeeding initiation, and current breastfeeding practices. A multivariable logistic regression analysis was used to identify independent predictors of early initiation of breastfeeding after controlling for confounding variables. A sample of 593 mothers was included in the study. Breastfeeding was initiated by 83.1 % of mothers within the first hour of childbirth. Being a housewife (AOR (95 % CI) = 2.48 (1.54- 3.99)) and infant received colostrum (AOR (95 % CI) =2.22 (1.08-4.55)) were significant positive predictors for early breastfeeding initiation as revealed by logistic regression. The multivariable logistic regression analysis showed that the mothers who had no radio and/or TV in the household (AOR (95 % CI = 0.55 (0.35-0.88)), were not exposure to health information (AOR (95 % CI) = 0.44 (0.25-0.75)), and infants were provided with prelacteal feeds (AOR (95 % CI)=0.30 (0.14-0.65)) were less likely to initiate breastfeeding. The rate of timely initiation of breastfeeding was high. Breastfeeding promotion program is essential to encourage the practice of timely initiation of breastfeeding, and reduce the practice of providing prelacteal feeds within three days of life. Thus appropriate health information is vital to boost early initiation of breastfeeding.

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People's Republic of China.

PubMed

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People's Republic of China. Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11-20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population.

Barriers and benefits of a healthy diet in spain: comparison with other European member states.

PubMed

Holgado, B; de Irala-Estévez, J; Martínez-González, M A; Gibney, M; Kearney, J; Martínez, J A

2000-06-01

Our purpose was to identify the main barriers and benefits perceived by the European citizens in regard to following a healthy diet and to assess the differences in expected benefits and difficulties between Spain and the remaining countries of the European Union. A cross-sectional study in which quota-controlled, nationally representative samples of approximately 1000 adults from each country completed a questionnaire. The survey was carried out between October 1995 and February 1996 in the 15 member states of the European Union. Participants (aged 15 y and older) were selected and interviewed in their homes about their attitudes towards healthy diets. They were asked to select two options from a list of 22 potential barriers to achieve a healthy diet and the benefits derived from a healthy diet. The associations of the perceived benefits of barriers with the sociodemographic variables within Spain and the rest of the European Union were compared with the Pearson chi-squared test and the chi-squared linear trend test. Two multivariate logistic regression models were also fitted to assess the characteristics independently related to the selection of 'Resistance to change' among the main barriers and to the selection of 'Prevent disease/stay healthy' as the main perceived benefits. The barrier most frequently mentioned in Spain was 'Irregular work hours' (29.7%) in contrast with the rest of the European Union where 'Giving up foods that I like' was the barrier most often chosen (26.2%). In the multivariate logistic regression model studying resistance to change, Spaniards were less resistant to change than the rest of the European Union. The benefit more frequently mentioned across Europe was 'Prevent disease/stay healthy'. In the multivariate logistic regression model women, older individuals, and people with a higher educational level were more likely to choose this benefit. It is apparent that there are many barriers to achieve healthy eating, mostly lack of time. For this reason a higher availability of food in line with the nutrition guidelines could be helpful. The population could have a better knowledge of the benefits derived from a healthy diet.

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People’s Republic of China

PubMed Central

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

Objective To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People’s Republic of China. Methods Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Results Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11–20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. Conclusion The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population. PMID:26664107

Correlates of historical suicide attempt in rapid-cycling bipolar disorder: a cross-sectional assessment.

PubMed

Gao, Keming; Tolliver, Bryan K; Kemp, David E; Ganocy, Stephen J; Bilali, Sarah; Brady, Kathleen L; Findling, Robert L; Calabrese, Joseph R

2009-07-01

A rapid-cycling course in bipolar disorder has previously been identified as a risk factor for attempted suicide. This study investigated factors associated with suicide attempts in patients with rapid-cycling bipolar I or II disorder. Cross-sectional data at the initial assessment of patients who were enrolled into 4 clinical trials were used to study the factors associated with suicide attempt. An extensive clinical interview and the Mini-International Neuropsychiatric Interview were used to ascertain DSM-IV diagnoses of rapid-cycling bipolar disorder, substance use disorders, anxiety disorders, psychosis, and other clinical variables. Chi-square, t test, and logistic regression or Poisson regression were used to analyze the data where appropriate, with odds ratios (ORs) for relative risk estimate. The data were collected from September 1995 to June 2005. In a univariate analysis, 41% of 561 patients had at least 1 lifetime suicide attempt. Earlier age of depression onset, bipolar I subtype, female sex, unmarried status, and a history of drug use disorder, panic disorder, sexual abuse, and psychosis were associated with significantly higher rates of attempted suicide (all p < .05). After considering 31 potential confounding factors in the stepwise logistic regression model (n = 387), any Axis I comorbidity (OR = 2.68, p = .0219), female sex (OR = 2.11, p = .0005), psychosis during depression (OR = 1.84, p = .0167), bipolar I subtype (OR = 1.83, p = .0074), and history of drug abuse (OR = 1.62, p = .0317) were independent predictors for increased risk of attempted suicide. However, white race was associated with a lower risk for suicide attempt (OR = 0.47, p = .0160). Psychosis during depression (p = .0003), bipolar I subtype (p = .0302), and physical abuse (p = .0195) were associated with increased numbers of suicide attempts by 248%, 166%, and 162%, respectively; white race was associated with a 60% decrease in the number of suicide attempts (p = .0320). In this highly comorbid group of patients with rapid-cycling bipolar disorder, 41% had at least 1 suicide attempt. Among the demographics, female sex was positively associated, but white race was negatively associated, with the risk for suicide attempt. Independent clinical variables for increased risk and/or number of attempted suicides were any Axis I comorbidity, psychosis during depression, bipolar I subtype, a history of drug abuse, and physical abuse. ©Copyright 2009 Physicians Postgraduate Press, Inc.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

The emotional cost of distance: Geographic social network dispersion and post-traumatic stress among survivors of Hurricane Katrina.

PubMed

Morris, Katherine Ann; Deterding, Nicole M

2016-09-01

Social networks offer important emotional and instrumental support following natural disasters. However, displacement may geographically disperse network members, making it difficult to provide and receive support necessary for psychological recovery after trauma. We examine the association between distance to network members and post-traumatic stress using survey data, and identify potential mechanisms underlying this association using in-depth qualitative interviews. We use longitudinal, mixed-methods data from the Resilience in Survivors of Katrina (RISK) Project to capture the long-term effects of Hurricane Katrina on low-income mothers from New Orleans. Baseline surveys occurred approximately one year before the storm and follow-up surveys and in-depth interviews were conducted five years later. We use a sequential explanatory analytic design. With logistic regression, we estimate the association of geographic network dispersion with the likelihood of post-traumatic stress. With linear regressions, we estimate the association of network dispersion with the three post-traumatic stress sub-scales. Using maximal variation sampling, we use qualitative interview data to elaborate identified statistical associations. We find network dispersion is positively associated with the likelihood of post-traumatic stress, controlling for individual-level socio-demographic characteristics, exposure to hurricane-related trauma, perceived social support, and New Orleans residency. We identify two social-psychological mechanisms present in qualitative data: respondents with distant network members report a lack of deep belonging and a lack of mattering as they are unable to fulfill obligations to important distant ties. Results indicate the importance of physical proximity to emotionally-intimate network ties for long-term psychological recovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cigarette smoking trends among U.S. working adult by industry and occupation: findings from the 2004-2012 National Health Interview Survey.

PubMed

Syamlal, Girija; Mazurek, Jacek M; Hendricks, Scott A; Jamal, Ahmed

2015-05-01

To examine trends in age-adjusted cigarette smoking prevalence among working adults by industry and occupation during 2004-2012, and to project those prevalences and compare them to the 2020 Healthy People objective (TU-1) to reduce cigarette smoking prevalence to ≤12%. We analyzed the 2004-2012 National Health Interview Survey (NHIS) data. Respondents were aged ≥18 years working in the week prior to the interview. Temporal changes in cigarette smoking prevalence were assessed using logistic regression. We used the regression model to extrapolate to the period 2013-2020. Overall, an estimated 19.0% of working adults smoked cigarettes: 22.4% in 2004 to 18.1% in 2012. The largest declines were among workers in the education services (6.5%) industry and in the life, physical, and social science (9.7%) occupations. The smallest declines were among workers in the real estate and rental and leasing (0.9%) industry and the legal (0.4%) occupations. The 2020 projected smoking prevalences in 15 of 21 industry groups and 13 of the 23 occupation groups were greater than the 2020 Healthy People goal. During 2004-2012, smoking prevalence declined in the majority of industry and occupation groups. The decline rate varied by industry and occupation groups. Projections suggest that certain groups may not reach the 2020 Healthy People goal. Consequently, smoking cessation, prevention, and intervention efforts may need to be revised and strengthened, particularly in specific occupational groups. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco [2014]. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A Facebook Follow-Up Strategy for Rural Drug-Using Women.

PubMed

Dickson, Megan F; Staton-Tindall, Michele; Smith, Kirsten E; Leukefeld, Carl; Webster, J Matthew; Oser, Carrie B

2017-06-01

Facebook (FB) use has grown exponentially over the past decade, including in rural areas. Despite its popularity, FB has been underutilized as a research follow-up approach to maintain contact with research participants and may have advantages in less densely populated areas and among more hard-to-reach, at-risk groups. The overall goal of this study was to examine FB as a supplemental follow-up approach to other follow-up strategies with rural drug-using women. Face-to-face interviews were conducted with randomly selected women who completed baseline interviews in 3 rural jails in 1 state. Analyses focus on participants who were released from jail and were eligible for 3-month follow-up (n = 284). Bivariate analyses were used to examine differences between FB users and nonusers, and multivariate logistic regression models examined predictors of 3-month follow-up participation and being located for follow-up using FB. About two-thirds (64.4%) of participants were regular FB users. Bivariate analyses indicated that FB users were younger, more educated, and more likely to have used alcohol in the 30 days before incarceration but less likely to have a chronic health problem. Regression analyses indicated that rural FB users had more than 5 times the odds of being located for the 3-month follow-up interview, even after controlling for other variables. There were no significant predictors of being followed up using FB. Findings suggest that FB is widely used and well accepted among rural drug-using women. Among hard-to-reach populations, including those in rural, geographically isolated regions, FB serves as a method to improve participant follow-up. © 2016 National Rural Health Association.

Racial/ethnic and educational differences in the estimated odds of recent nitrite use among adult household residents in the United States: an illustration of matching and conditional logistic regression.

PubMed

Delva, J; Spencer, M S; Lin, J K

2000-01-01

This article compares estimates of the relative odds of nitrite use obtained from weighted unconditional logistic regression with estimates obtained from conditional logistic regression after post-stratification and matching of cases with controls by neighborhood of residence. We illustrate these methods by comparing the odds associated with nitrite use among adults of four racial/ethnic groups, with and without a high school education. We used aggregated data from the 1994-B through 1996 National Household Survey on Drug Abuse (NHSDA). Difference between the methods and implications for analysis and inference are discussed.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

History of spontaneous miscarriage and the risk of diabetes mellitus among middle-aged and older Chinese women.

PubMed

Liu, Bingqing; Song, Lulu; Li, Hui; Zheng, Xiaoxuan; Yuan, Jing; Liang, Yuan; Wang, Youjie

2018-06-01

Epidemiological studies of the long-term maternal health outcomes of spontaneous miscarriages have been sparse and inconsistent. The objective of our study is to examine the association between spontaneous miscarriages and diabetes among middle-aged and older Chinese women. A total of 19,539 women from the Dongfeng-Tongji cohort study who completed a questionnaire and had medical examinations performed on were included in the analysis. History of spontaneous miscarriage was obtained by self-reporting in the first follow-up questionnaire interview. The presence of diabetes was determined by a fasting plasma glucose level, self-reported physician diagnosis and use of antidiabetic medication. A series of multivariate logistic regression models were used to calculate the odds ratios and 95% CI across spontaneous miscarriage categories (0, 1, 2, ≥ 3) after adjustment for potential confounding factors. The prevalence rate of diabetes was 18.8% among the participants. In the fully adjusted logistic regression model, women who had 1, 2 or ≥ 3 spontaneous miscarriages had 0.86 times (95% CI 0.68, 1.08), 1.30 times (95% CI 0.82, 2.04) and 2.11 times (95% CI 1.08, 4.11) higher risk of diabetes, respectively, compared with women who had no history of spontaneous miscarriage. There is an increased risk of diabetes among women with a history of a higher number of spontaneous miscarriages. History of multiple spontaneous miscarriages should be taken into consideration when assessing the risk of diabetes.

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

PubMed

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

2016-11-01

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

Influenza vaccination among chiropractic patients and other users of complementary and alternative medicine: are chiropractic patients really different?

PubMed

Davis, Matthew A; Smith, Monica; Weeks, William B

2012-01-01

Previous studies suggest a possible association between using chiropractic care and lower influenza vaccination rates. We examined adult influenza vaccination rates for chiropractic patients to determine if they are different than those for users of other complementary and alternative medicine (CAM). We used the 2007 National Health Interview Survey to examine influenza vaccination rates among adult respondents who were considered high priority for the influenza vaccine (n=12,164). We separated respondents into clinically meaningful categories according to age and whether or not they had recently used chiropractic care, some other type of CAM, or neither. We used adjusted logistic regression to determine whether user status predicted influenza vaccination. Only 33% of younger and 64% of older high priority Chiropractic Users were vaccinated in 2007; these rates approximated those of Non-CAM Users. However, younger Non-Chiropractic CAM Users were more likely than Non-CAM Users to have been vaccinated (p-value=0.05). In adjusted logistic regressions, we found statistically insignificant differences when comparing Chiropractic Users to Non-CAM Users for younger adults (OR=0.93(95% CI:0.76-1.13), or for older adults OR=0.90 (95% CI:0.64-1.20). Chiropractic Users appear no less likely to be vaccinated for influenza; whereas, younger Non-chiropractic CAM Users are more likely than Non-CAM Users to be vaccinated. Copyright © 2011 Elsevier Inc. All rights reserved.

Adult correlates of early behavioral maladjustment: a study of injured drivers.

PubMed

Ryb, Gabriel; Dischinger, Patricia; Smith, Gordon; Soderstrom, Carl

2008-10-01

To establish whether a history of school suspension (HSS) predicts adult driver behavior. 323 injured drivers were interviewed as part of a study of psychoactive substance use disorders (PSUD) and injury. Drivers with a HSS were compared to those without HSS in relation to demographics, SES, PSUD, risky behaviors, trauma history and driving history using student's t test and chi-square. Multiple logistic regression models were constructed to adjust for demographics, SES and PSUD. HSS drivers represented 31% of the population and were younger, more likely to be male and had higher rates of alcohol and drug dependence than drivers without HSS. Educational achievement was worse for drivers with HSS. Drivers with HSS were more likely to have a history of prior vehicular trauma and assault. Seat-belt non-use, drinking and driving, riding with drunk driver, binge drinking, driving fast for the thrill, license suspension and drinking and driving convictions were more common among drivers with HSS. In multiple logistic regression models adjusting for demographics and SES, HSS revealed higher odds ratios for the same outcomes. After adding PSUD to the models HSS remained significant only for seat belt non use, binge drinking and previous assault history. HSS is associated with risky behaviors, repeated vehicular injury, and poor driver history. The association with driver history, however, disappears when PSUD are included in the models. The association of HSS (a marker of early behavioral maladjustment) with behavioral risks suggests that undiagnosed psychopathology may be linked to injury recidivism.

Television Viewing and Its Association with Sedentary Behaviors, Self-Rated Heath and Academic Performance among Secondary School Students in Peru.

PubMed

Sharma, Bimala; Cosme Chavez, Rosemary; Jeong, Ae Suk; Nam, Eun Woo

2017-04-05

The study assessed television viewing >2 h a day and its association with sedentary behaviors, self-rated health, and academic performance among secondary school adolescents. A cross-sectional survey was conducted among randomly selected students in Lima in 2015. We measured self-reported responses of students using a standard questionnaire, and conducted in-depth interviews with 10 parents and 10 teachers. Chi-square test, correlation and multivariate logistic regression analysis were performed among 1234 students, and thematic analysis technique was used for qualitative information. A total of 23.1% adolescents reported watching television >2 h a day. Qualitative findings also show that adolescents spend most of their leisure time watching television, playing video games or using the Internet. Television viewing had a significant positive correlation with video game use in males and older adolescents, with Internet use in both sexes, and a negative correlation with self-rated health and academic performance in females. Multivariate logistic regression analysis shows that television viewing >2 h a day, independent of physical activity was associated with video games use >2 h a day, Internet use >2 h a day, poor/fair self-rated health and poor self-reported academic performance. Television viewing time and sex had a significant interaction effect on both video game use >2 h a day and Internet use >2 h a day. Reducing television viewing time may be an effective strategy for improving health and academic performance in adolescents.

Girls and Weapons: An International Study of the Perpetration of Violence

PubMed Central

Butters, Jennifer E.; Cousineau, Marie-Marthe; Harrison, Lana; Korf, Dirk

2006-01-01

The purpose of this study was to describe delinquent girls' weapons preferences where and how often they carried weapons and to identify the most important factors that explained four different weapon-related violent outcomes. A large, high-risk sample of female adolescents consisting of 510 girls aged 14–17 in four cities were interviewed using the same questionnaire and methods. Tabular and logistic regression analyses were applied. Knives emerged as the most frequently reported weapon in all cities. Rates of both lifetime victimization and perpetration of violence with weapons were high in all sites. Starting to carry a weapon as a result of violence was reported by 40% of the girls in Toronto, 28% in Philadelphia, 25% in Amsterdam, and 16% in Montreal. The major predictors of weapon perpetrated violent behaviours included ethnic origin, early onset of delinquent activities, participation in delinquent acts in the past 12 months, gang fighting and carrying a weapon as a result of violence. Site, age and heavy alcohol consumption had a minor impact, and drug use, drug selling, and neighborhood features, none. Despite numerous differences in weapons' prevalence across cities, the logistic regression found that site was only significant in use of an object (Toronto) and not significant in threatening or hurting someone with either a knife or a gun or actually hurting others with a weapon. These findings suggest commonality in serious female violence that extends beyond borders and cultures. PMID:16937086

Cell phone exposures and hearing loss in children in the Danish National Birth Cohort.

PubMed

Sudan, Madhuri; Kheifets, Leeka; Arah, Onyebuchi A; Olsen, Jorn

2013-05-01

Children today are exposed to cell phones early in life, and may be the most vulnerable if exposure is harmful to health. We investigated the association between cell phone use and hearing loss in children. The Danish National Birth Cohort (DNBC) enrolled pregnant women between 1996 and 2002. Detailed interviews were conducted during gestation, and when the children were 6 months, 18 months and 7 years of age. We used multivariable-adjusted logistic regression, marginal structural models (MSM) with inverse-probability weighting, and doubly robust estimation (DRE) to relate hearing loss at age 18 months to cell phone use at age 7 years, and to investigate cell phone use reported at age 7 in relation to hearing loss at age 7. Our analyses included data from 52 680 children. We observed weak associations between cell phone use and hearing loss at age 7, with odds ratios and 95% confidence intervals from the traditional logistic regression, MSM and DRE models being 1.21 [95% confidence interval [CI] 0.99, 1.46], 1.23 [95% CI 1.01, 1.49] and 1.22 [95% CI 1.00, 1.49], respectively. Our findings could have been affected by various biases and are not sufficient to conclude that cell phone exposures have an effect on hearing. This is the first large-scale epidemiologic study to investigate this potentially important association among children, and replication of these findings is needed. © 2013 Blackwell Publishing Ltd.

Camelus dromedarius brucellosis and its public health associated risks in the Afar National Regional State in northeastern Ethiopia

PubMed Central

2013-01-01

Background A cross-sectional study was carried out in four districts of the Afar region in Ethiopia to determine the prevalence of brucellosis in camels, and to identify risky practices that would facilitate the transmission of zoonoses to humans. This study involved testing 461 camels and interviewing 120 livestock owners. The modified Rose Bengal plate test (mRBPT) and complement fixation test (CFT) were used as screening and confirmatory tests, respectively. SPSS 16 was used to analyze the overall prevalence and potential risk factors for seropositivity, using a multivariable logistic regression analysis. Results In the camel herds tested, 5.4% had antibodies against Brucella species, and the district level seroprevalence ranged from 11.7% to 15.5% in camels. The logistic regression model for camels in a herd size > 20 animals (OR = 2.8; 95% CI: 1.16-6.62) and greater than four years of age (OR = 4.9; 95% CI: 1.45-16.82) showed a higher risk of infection when compared to small herds and those ≤ 4 years old. The questionnaire survey revealed that most respondents did not know about the transmission of zoonotic diseases, and that their practices could potentially facilitate the transmission of zoonotic pathogens. Conclusions The results of this study revealed that camel brucellosis is prevalent in the study areas. Therefore, there is a need for implementing control measures and increasing public awareness in the prevention methods of brucellosis. PMID:24344729

[Research on etiological aspects of dual pathology].

PubMed

Barea, Juan; Benito, Ana; Mateu, César; Martín, Eva; López, Nuria; Haro, Gonzalo

2010-01-01

It is important to assess the interaction between family psychopathologic history (FH), family dynamics (FD), behavior disorders, substance-use disorders and personality disorders (PD). Cross-sectional design. The sample was made up of 350 subjects with substance-use disorders who were assessed for FH including alcoholism and substance-use disorders through an interview; for substance use via a questionnaire; for FD; for PD using the International Personality Disorder Examination (IPDE); for behavior problems in adolescence; and for disocial disorder. Correlated variables were included in logistic regression models. Early age of onset for substance use is related to FH of substance use disorders and poorer FD. FH of alcoholism, substance-use disorders and psychiatric disorders are related to poorer FD. Early age of onset for substance use, FH and a disruptive FD are related to behavior problems and disocial disorder. Early age of onset for substance use, FH, disruptive FD, behavior problems and disocial disorder are related to presence of PD. Logistic regression predicted the presence of PD by age of onset for use of methadone (CI(95):1.005/3.222; p=0.048) and of other opiates (CI(95):0.864/0.992;p=0.028). FH score in alcoholism predicted Borderline Personality Disorder (CI(95):1.137- 2.942; p=0.013), and age of onset of cocaine use predicted Antisocial Personality Disorder (CI(95):0.864/0.992; p=0.028). FH of substance use and own use predict the presence of some PDs.

Cell Phone Exposures and Hearing Loss in Children in the Danish National Birth Cohort

PubMed Central

Sudan, Madhuri; Kheifets, Leeka; Arah, Onyebuchi A.; Olsen, Jorn

2013-01-01

Background Children today are exposed to cell phones early in life, and may be the most vulnerable if exposure is harmful to health. We investigated the association between cell phone use and hearing loss in children. Methods The Danish National Birth Cohort (DNBC) enrolled pregnant women between 1996 and 2002. Detailed interviews were conducted during gestation, and when the children were 6 months, 18 months, and 7 years of age. We used multivariable-adjusted logistic regression, marginal structural models (MSM) with inverse-probability weighting, and doubly-robust estimation (DRE) to relate hearing loss at age 18 months to cell phone use at age seven years, and to investigate cell phone use reported at age seven in relation to hearing loss at age seven. Results Our analyses included data from 52,680 children. We observed weak associations between cell phone use and hearing loss at age seven, with odds ratios and 95% confidence intervals from the traditional logistic regression, MSM, and DRE models being 1.21 [0.99–1.46], 1.23 [1.01–1.49], and 1.22 [1.00–1.49], respectively. Conclusions Our findings could have been affected by various biases and are not sufficient to conclude that cell phone exposures have an effect on hearing. This is the first large-scale epidemiologic study to investigate this potentially important association among children, and replication of these findings is needed. PMID:23574412

Sleep Bruxism and Anxiety Impacts in Quality of Life Related to Oral Health of Brazilian Children and their Families.

PubMed

de Alencar, Nashalie Andrade; Leão, Cecília Sued; Leão, Anna Thereza Thomé; Luiz, Ronir Raggio; Fonseca-Gonçalves, Andréa; Maia, Lucianne Cople

This study aimed to assess the impact of parent reported sleep bruxism, trait anxiety and sociodemographic/socioeconomic features on quality of life related to oral health (OHRQoL) of children and their families. Healthy children aged 3-7 years, with (n=34) and without (n=32) bruxism were select for this study. Data was collected by applying the following instruments: The Early Childhood Oral Health Scale (B-ECOHIS) and Trait-anxiety Scale (TAS). The sociodemographic/socioeconomic characteristics were obtained by interviews with parents. Multiple logistic regression tests were performed to observe the influence of sociodemographic/socioeconomic characteristics, bruxism and trait-anxiety on the children's OHRQoL. No association between sleep bruxism and all evaluated sociodemographic/socioeconomic conditions, with exception of being the only child (p=0.029), were observed. Mean B-ECOHIS and TAS scores were different (p<0.05) between children with (3.41 ± 4.87; 45.09 ± 15.46, respectively) and without (0.63 ± 1.28; 29.53 ± 11.82, respectively) bruxism. Although an association between bruxism and OHRQoL (p=0.015) was observed, it was dropped (p=0.336; OR=1.77) in the logistic regression model. Trait anxiety was the variable responsible for the impact on the OHRQoL of children (p=0.012; OR=1.05). Our results indicated anxiety as the main factor that interfered in the OHRQoL of children with sleep bruxism.

Infant otitis media and the use of secondary heating sources.

PubMed

Pettigrew, Melinda M; Gent, Janneane F; Triche, Elizabeth W; Belanger, Kathleen D; Bracken, Michael B; Leaderer, Brian P

2004-01-01

This prospective study investigated the association of exposure to indoor secondary heating sources with otitis media and recurrent otitis media risk in infants. We enrolled mothers living in nonsmoking households and delivering babies between 1993 and 1996 in 12 Connecticut and Virginia hospitals. Biweekly telephone interviews during the first year of life assessed diagnoses from doctors' office visits and use of secondary home heating sources, air conditioner use, and day care. Otitis media episodes separated by more than 21 days were considered to be unique episodes. Recurrent otitis media was defined as 4 or more episodes of otitis media. Repeated-measures logistic regression modeling evaluated the association of kerosene heater, fireplace, or wood stove use with otitis media episodes while controlling for potential confounders. Logistic regression evaluated the relation of these secondary heating sources with recurrent otitis media. None of the secondary heating sources were associated with otitis media or with recurrent otitis media. Otitis media was associated with day care, the winter heating season, birth in the fall, white race, additional children in the home, and a maternal history of allergies in multivariate models. Recurrent otitis media was associated with day care, birth in the fall, white race, and a maternal history of allergies or asthma. We found no evidence that the intermittent use of secondary home heating sources increases the risk of otitis media or recurrent otitis media. This study confirms earlier findings regarding the importance of day care with respect to otitis media risk.

Predicting Future Suicide Attempts among Depressed Suicide Ideators: A 10-year Longitudinal Study

PubMed Central

May, Alexis M.; Klonsky, E. David; Klein, Daniel N.

2012-01-01

Suicidal ideation and attempts are a major public health problem. Research has identified many risk factors for suicidality; however, most fail to identify which suicide ideators are at greatest risk of progressing to a suicide attempt. Thus, the present study identified predictors of future suicide attempts in a sample of psychiatric patients reporting suicidal ideation. The sample comprised 49 individuals who met full DSM-IV criteria for major depressive disorder and/or dysthymic disorder and reported suicidal ideation at baseline. Participants were followed for 10 years. Demographic, psychological, personality, and psychosocial risk factors were assessed using validated questionnaires and structured interviews. Phi coefficients and point-biserial correlations were used to identify prospective predictors of attempts, and logistic regressions were used to identify which variables predicted future attempts over and above past suicide attempts. Six significant predictors of future suicide attempts were identified – cluster A personality disorder, cluster B personality disorder, lifetime substance abuse, baseline anxiety disorder, poor maternal relationship, and poor social adjustment. Finally, exploratory logistic regressions were used to examine the unique contribution of each significant predictor controlling for the others. Co-morbid cluster B personality disorder emerged as the only robust, unique predictor of future suicide attempts among depressed suicide ideators. Future research should continue to identify variables that predict transition from suicidal thoughts to suicide attempts, as such work will enhance clinical assessment of suicide risk as well as theoretical models of suicide. PMID:22575331

Resilience and risk for alcohol use disorders: A Swedish twin study

PubMed Central

Long, E.C.; Lönn, S.L.; Ji, J.; Lichtenstein, P.; Sundquist, J.; Sundquist, K.; Kendler, K.S.

2016-01-01

Background Resilience has been shown to be protective against alcohol use disorders (AUD), but the magnitude and nature of the relationship between these two phenotypes is not clear. The aim of this study is to examine the strength of this relationship and the degree to which it results from common genetic or common environmental influences. Methods Resilience was assessed on a nine-point scale during a personal interview in 1,653,721 Swedish men aged 17–25 years. AUD was identified based on Swedish medical, legal, and pharmacy registries. The magnitude of the relationship between resilience and AUD was examined using logistic regression. The extent to which the relationship arises from common genetic or common environmental factors was examined using a bivariate Cholesky decomposition model. Results The five single items that comprised the resilience assessment (social maturity, interest, psychological energy, home environment, and emotional control) all reduced risk for subsequent AUD, with social maturity showing the strongest effect. The linear effect by logistic regression showed that a one-point increase on the resilience scale was associated with a 29% decrease in odds of AUD. The Cholesky decomposition model demonstrated that the resilience-AUD relationship was largely attributable to overlapping genetic and shared environmental factors (57% and 36%, respectively). Conclusion Resilience is strongly associated with a reduction in risk for AUD. This relationship appears to be the result of overlapping genetic and shared environmental influences that impact resilience and risk of AUD, rather than a directly causal relationship. PMID:27918840

Surrogate screening models for the low physical activity criterion of frailty.

PubMed

Eckel, Sandrah P; Bandeen-Roche, Karen; Chaves, Paulo H M; Fried, Linda P; Louis, Thomas A

2011-06-01

Low physical activity, one of five criteria in a validated clinical phenotype of frailty, is assessed by a standardized, semiquantitative questionnaire on up to 20 leisure time activities. Because of the time demanded to collect the interview data, it has been challenging to translate to studies other than the Cardiovascular Health Study (CHS), for which it was developed. Considering subsets of activities, we identified and evaluated streamlined surrogate assessment methods and compared them to one implemented in the Women's Health and Aging Study (WHAS). Using data on men and women ages 65 and older from the CHS, we applied logistic regression models to rank activities by "relative influence" in predicting low physical activity.We considered subsets of the most influential activities as inputs to potential surrogate models (logistic regressions). We evaluated predictive accuracy and predictive validity using the area under receiver operating characteristic curves and assessed criterion validity using proportional hazards models relating frailty status (defined using the surrogate) to mortality. Walking for exercise and moderately strenuous household chores were highly influential for both genders. Women required fewer activities than men for accurate classification. The WHAS model (8 CHS activities) was an effective surrogate, but a surrogate using 6 activities (walking, chores, gardening, general exercise, mowing and golfing) was also highly predictive. We recommend a 6 activity questionnaire to assess physical activity for men and women. If efficiency is essential and the study involves only women, fewer activities can be included.

Television Viewing and Its Association with Sedentary Behaviors, Self-Rated Health and Academic Performance among Secondary School Students in Peru

PubMed Central

Sharma, Bimala; Cosme Chavez, Rosemary; Jeong, Ae Suk; Nam, Eun Woo

2017-01-01

The study assessed television viewing >2 h a day and its association with sedentary behaviors, self-rated health, and academic performance among secondary school adolescents. A cross-sectional survey was conducted among randomly selected students in Lima in 2015. We measured self-reported responses of students using a standard questionnaire, and conducted in-depth interviews with 10 parents and 10 teachers. Chi-square test, correlation and multivariate logistic regression analysis were performed among 1234 students, and thematic analysis technique was used for qualitative information. A total of 23.1% adolescents reported watching television >2 h a day. Qualitative findings also show that adolescents spend most of their leisure time watching television, playing video games or using the Internet. Television viewing had a significant positive correlation with video game use in males and older adolescents, with Internet use in both sexes, and a negative correlation with self-rated health and academic performance in females. Multivariate logistic regression analysis shows that television viewing >2 h a day, independent of physical activity was associated with video games use >2 h a day, Internet use >2 h a day, poor/fair self-rated health and poor self-reported academic performance. Television viewing time and sex had a significant interaction effect on both video game use >2 h a day and Internet use >2 h a day. Reducing television viewing time may be an effective strategy for improving health and academic performance in adolescents. PMID:28379202

Is frequency of family meals associated with fruit and vegetable intake among preschoolers? A logistic regression analysis.

PubMed

Caldwell, A R; Terhorst, L; Skidmore, E R; Bendixen, R M

2018-01-23

The present study aimed to examine the associations between frequency of family meals and low fruit and vegetable intake in preschool children. Promoting healthy nutrition early in life is recommended for combating childhood obesity. Frequency of family meals is associated with fruit and vegetable intake in school-age children and adolescents; the relationship in young children is less clear. We completed a secondary analysis using data from the Early Childhood Longitudinal Study-Birth Cohort. Participants included children, born in the year 2001, to mothers who were >15 years old (n = 8 950). Data were extracted from structured parent interviews during the year prior to kindergarten. We used hierarchical logistic regression to describe the relationships between frequency of family meals and low fruit and vegetable intake. Frequency of family meals was associated with low fruit and vegetable intake. The odds of low fruit and vegetable intake were greater for preschoolers who shared less than three evening family meals per week (odds ratio = 1.5, β = 0.376, P < 0.001) than preschoolers who shared the evening meal with family every night. Fruit and vegetable intake is related to frequency of family meals in preschool-age children. Educating parents about the potential benefits of frequent shared meals may lead to a higher fruit and vegetable consumption among preschoolers. Future studies should address other factors that likely contribute to eating patterns during the preschool years. © 2018 The British Dietetic Association Ltd.

The relationship of gender and trauma characteristics to posttraumatic stress disorder in a community sample of traumatized northern plains American Indian adolescents and young adults.

PubMed

Gnanadesikan, Mukund; Novins, Douglas K; Beals, Janette

2005-09-01

Previous studies have identified a high prevalence (25%-80%) of trauma among American Indian and non-American Indian adolescents and adults. However, only a fraction of traumatized individuals develop posttraumatic stress disorder (PTSD). This article examines the relationships of gender and trauma characteristics to a diagnosis of PTSD among a community sample of traumatized American Indian adolescents and young adults. Complete data were collected from 349 American Indians aged 15 to 24 years who participated in a cross-sectional community-based study from July 1997 to December 1999 and reported experiencing at least 1 traumatic event. Traumatic events and PTSD were assessed using a version of the Composite International Diagnostic Interview. Logistic regression determined the relationships of gender, trauma type, age at first trauma, and number of traumas to the development of PTSD. Forty-two participants (12.0% of those who experienced a traumatic event) met criteria for lifetime PTSD. While all 4 of the independent variables noted above demonstrated univariate associations with PTSD, multivariate logistic regression analyses indicated that only experiencing a sexual trauma (odds ratio [OR] = 4.45, 95% confidence interval [CI] = 1.76 to 11.28) and having experienced 6 or more traumas (OR = 2.53, 95% CI = 1.06 to 6.04) were independent predictors of meeting criteria for PTSD. American Indian children and adolescents who experience sexual trauma and multiple traumatic experiences may be at particularly high risk for developing PTSD.

Corporal punishment and physical maltreatment against children: a community study on Chinese parents in Hong Kong.

PubMed

Tang, Catherine So-kum

2006-08-01

This study aimed to examine rates and associated factors of parent-to-child corporal punishment and physical maltreatment in Hong Kong Chinese families. Cross-sectional and randomized household interviews were conducted with 1,662 Chinese parents to collect information on demographic characteristics of parents and children, marital satisfaction, perceived social support, evaluation of child problem behaviors, and reactions to conflicts with children. Descriptive statistics, analyses of variances, and logistic regression analyses were conducted. The rates of parent-to-child physical aggression were 57.5% for corporal punishment and 4.5% for physical maltreatment. Mothers as compared to fathers reported higher rates and more frequent use of corporal punishment on their children, but this parental gender effect was insignificant among older parents and those with adolescent children. Boys as compared to girls were more likely to experience higher rates and more frequent parental corporal punishment, especially in middle childhood at aged 5-12. Furthermore, parents perpetrated more frequent physical maltreatment on younger as compared to older children. Results from logistic regression analyses indicated that significant correlates of parental corporal punishment were: children's young age, male gender, and externalizing behaviors as well as parents' young age, non-employment, and marital dissatisfaction. For parent-to-child physical maltreatment, significant correlates were externalizing behaviors of children and parental marital dissatisfaction. Hong Kong Chinese parents commonly used corporal punishment on their children, which was associated with characteristics of children, parents, and family.

Factors Associated With Risky Alcohol Consumption Among Male Street Laborers in Urban Vietnam.

PubMed

Mylona, Lamprini; Huy, Nguyen Van; Ha, Pham Nguyen; Riggi, Emilia; Marrone, Gaetano

2017-07-29

Alcohol consumption is of global concern. However, drinking patterns and associated factors remain under-investigated, especially among low socioeconomic groups such as street laborers. Using the social cognitive model as a framework for the study we aimed to identify factors associated with risky alcohol consumption. In a cross-sectional study using structured questionnaires, 450 male street laborers searching for casual works in Hanoi, Vietnam were interviewed. A logistic regression was applied in order to detect predictors of risky alcohol drinking. During the last month, 45% of the participants reported daily consumption while the other 55% consumed weekly or less. Among the drinkers (416 out of 450, 92%), 27% were identified as high-risk drinkers who reported more than 14 standard drinks per week, while only 8% were lifetime abstainers. The multivariable logistic regression showed that older age, higher income were positively associated with a higher likelihood of drinking alcohol, while high school level negatively. The environmental predictor was the higher level of peer connection. The association between drinking and risky behavior was found positive with regards to the number of sexual partners. The study suggests that male street laborers are vulnerable to health risks. Decision makers should note that a significant proportion of this target group exceeds the guidelines for alcohol use and this should be included in future interventions or further research. A multisectoral approach together with an important strategy of education is needed to control alcohol use.

Gender Inequality: Is the National Population Policy's Objective of Two Child Norm Heading the Correct Way?

PubMed

Patrikar, S R; Bhalwar, R; Datta, A; Basannar, D R

2008-07-01

Male Preference is well known phenomena world wide from ancient ages. A descriptive study was carried out to assess the attitude of women towards birth of son, use of contraception methods and sex determination methods in rural village Kasurdi in Pune district. Univariate analysis was carried out by considering each factor determining sex preference separately as well as using a Logistic Regression Model. Adequacy of fit of the model has also been tested. Out of 110 respondents interviewed, 62.7% felt that male child is necessary in the family. Univariate analysis revealed that sex of first child, concern undergone for second pregnancy with regards to sex of the child, number of children in family and type of family were significant factors contributing to the son preference. The analysis under the logistic regression model revealed that sex of the first child and concern undergone in second pregnancy with respect to the sex of the second child are the most dominating and significant factors in the causation of son preference. The difference between family sizes when compared with the sex of first child was statistically significant signifying that if the first child is a male then it hardly matters whether the second child is male or female, but if the sex of first child is female then the families land up with bigger family size. On an average most of the respondents favour two children with an equal share of male and female children.

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

Iterative Purification and Effect Size Use with Logistic Regression for Differential Item Functioning Detection

ERIC Educational Resources Information Center

French, Brian F.; Maller, Susan J.

2007-01-01

Two unresolved implementation issues with logistic regression (LR) for differential item functioning (DIF) detection include ability purification and effect size use. Purification is suggested to control inaccuracies in DIF detection as a result of DIF items in the ability estimate. Additionally, effect size use may be beneficial in controlling…

A Note on Three Statistical Tests in the Logistic Regression DIF Procedure

ERIC Educational Resources Information Center

Paek, Insu

2012-01-01

Although logistic regression became one of the well-known methods in detecting differential item functioning (DIF), its three statistical tests, the Wald, likelihood ratio (LR), and score tests, which are readily available under the maximum likelihood, do not seem to be consistently distinguished in DIF literature. This paper provides a clarifying…

"Let Me Count the Ways:" Fostering Reasons for Living among Low-Income, Suicidal, African American Women

ERIC Educational Resources Information Center

West, Lindsey M.; Davis, Telsie A.; Thompson, Martie P.; Kaslow, Nadine J.

2011-01-01

Protective factors for fostering reasons for living were examined among low-income, suicidal, African American women. Bivariate logistic regressions revealed that higher levels of optimism, spiritual well-being, and family social support predicted reasons for living. Multivariate logistic regressions indicated that spiritual well-being showed…

Comparison of Two Approaches for Handling Missing Covariates in Logistic Regression

ERIC Educational Resources Information Center

Peng, Chao-Ying Joanne; Zhu, Jin

2008-01-01

For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…

Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

ERIC Educational Resources Information Center

Atar, Burcu; Kamata, Akihito

2011-01-01

The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

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

2010-01-01

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

Propensity Score Estimation with Data Mining Techniques: Alternatives to Logistic Regression

ERIC Educational Resources Information Center

Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M.

2013-01-01

Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…

Two-factor logistic regression in pediatric liver transplantation

NASA Astrophysics Data System (ADS)

Uzunova, Yordanka; Prodanova, Krasimira; Spasov, Lyubomir

2017-12-01

Using a two-factor logistic regression analysis an estimate is derived for the probability of absence of infections in the early postoperative period after pediatric liver transplantation. The influence of both the bilirubin level and the international normalized ratio of prothrombin time of blood coagulation at the 5th postoperative day is studied.

Predictors of Placement Stability at the State Level: The Use of Logistic Regression to Inform Practice

ERIC Educational Resources Information Center

Courtney, Jon R.; Prophet, Retta

2011-01-01

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors…

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Matched samples logistic regression in case-control studies with missing values: when to break the matches.

PubMed

Hansson, Lisbeth; Khamis, Harry J

2008-12-01

Simulated data sets are used to evaluate conditional and unconditional maximum likelihood estimation in an individual case-control design with continuous covariates when there are different rates of excluded cases and different levels of other design parameters. The effectiveness of the estimation procedures is measured by method bias, variance of the estimators, root mean square error (RMSE) for logistic regression and the percentage of explained variation. Conditional estimation leads to higher RMSE than unconditional estimation in the presence of missing observations, especially for 1:1 matching. The RMSE is higher for the smaller stratum size, especially for the 1:1 matching. The percentage of explained variation appears to be insensitive to missing data, but is generally higher for the conditional estimation than for the unconditional estimation. It is particularly good for the 1:2 matching design. For minimizing RMSE, a high matching ratio is recommended; in this case, conditional and unconditional logistic regression models yield comparable levels of effectiveness. For maximizing the percentage of explained variation, the 1:2 matching design with the conditional logistic regression model is recommended.

Label-noise resistant logistic regression for functional data classification with an application to Alzheimer's disease study.

PubMed

Lee, Seokho; Shin, Hyejin; Lee, Sang Han

2016-12-01

Alzheimer's disease (AD) is usually diagnosed by clinicians through cognitive and functional performance test with a potential risk of misdiagnosis. Since the progression of AD is known to cause structural changes in the corpus callosum (CC), the CC thickness can be used as a functional covariate in AD classification problem for a diagnosis. However, misclassified class labels negatively impact the classification performance. Motivated by AD-CC association studies, we propose a logistic regression for functional data classification that is robust to misdiagnosis or label noise. Specifically, our logistic regression model is constructed by adopting individual intercepts to functional logistic regression model. This approach enables to indicate which observations are possibly mislabeled and also lead to a robust and efficient classifier. An effective algorithm using MM algorithm provides simple closed-form update formulas. We test our method using synthetic datasets to demonstrate its superiority over an existing method, and apply it to differentiating patients with AD from healthy normals based on CC from MRI. © 2016, The International Biometric Society.

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

Naval Research Logistics Quarterly. Volume 28. Number 3,

DTIC Science & Technology

1981-09-01

denotes component-wise maximum. f has antone (isotone) differences on C x D if for cl < c2 and d, < d2, NAVAL RESEARCH LOGISTICS QUARTERLY VOL. 28...or negative correlations and linear or nonlinear regressions. Given are the mo- ments to order two and, for special cases, (he regression function and...data sets. We designate this bnb distribution as G - B - N(a, 0, v). The distribution admits only of positive correlation and linear regressions

Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

PubMed

Bond, H S; Sullivan, S G; Cowling, B J

2016-06-01

Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

PubMed

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

Prenatal and infant exposure to thimerosal from vaccines and immunoglobulins and risk of autism.

PubMed

Price, Cristofer S; Thompson, William W; Goodson, Barbara; Weintraub, Eric S; Croen, Lisa A; Hinrichsen, Virginia L; Marcy, Michael; Robertson, Anne; Eriksen, Eileen; Lewis, Edwin; Bernal, Pilar; Shay, David; Davis, Robert L; DeStefano, Frank

2010-10-01

Exposure to thimerosal, a mercury-containing preservative that is used in vaccines and immunoglobulin preparations, has been hypothesized to be associated with increased risk of autism spectrum disorder (ASD). This study was designed to examine relationships between prenatal and infant ethylmercury exposure from thimerosal-containing vaccines and/or immunoglobulin preparations and ASD and 2 ASD subcategories: autistic disorder (AD) and ASD with regression. A case-control study was conducted in 3 managed care organizations (MCOs) of 256 children with ASD and 752 controls matched by birth year, gender, and MCO. ASD diagnoses were validated through standardized in-person evaluations. Exposure to thimerosal in vaccines and immunoglobulin preparations was determined from electronic immunization registries, medical charts, and parent interviews. Information on potential confounding factors was obtained from the interviews and medical charts. We used conditional logistic regression to assess associations between ASD, AD, and ASD with regression and exposure to ethylmercury during prenatal, birth-to-1 month, birth-to-7-month, and birth-to-20-month periods. There were no findings of increased risk for any of the 3 ASD outcomes. The adjusted odds ratios (95% confidence intervals) for ASD associated with a 2-SD increase in ethylmercury exposure were 1.12 (0.83-1.51) for prenatal exposure, 0.88 (0.62-1.26) for exposure from birth to 1 month, 0.60 (0.36-0.99) for exposure from birth to 7 months, and 0.60 (0.32-0.97) for exposure from birth to 20 months. In our study of MCO members, prenatal and early-life exposure to ethylmercury from thimerosal-containing vaccines and immunoglobulin preparations was not related to increased risk of ASDs.

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

PubMed

Fei, Y; Hu, J; Li, W-Q; Wang, W; Zong, G-Q

2017-03-01

Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicting PSMVT. Additional predictive factors may be incorporated into artificial neural networks. Objective To construct and validate artificial neural networks (ANNs) for predicting the occurrence of portosplenomesenteric venous thrombosis (PSMVT) and compare the predictive ability of the ANNs with that of logistic regression. Methods The ANNs and logistic regression modeling were constructed using simple clinical and laboratory data of 72 acute pancreatitis (AP) patients. The ANNs and logistic modeling were first trained on 48 randomly chosen patients and validated on the remaining 24 patients. The accuracy and the performance characteristics were compared between these two approaches by SPSS17.0 software. Results The training set and validation set did not differ on any of the 11 variables. After training, the back propagation network training error converged to 1 × 10 -20 , and it retained excellent pattern recognition ability. When the ANNs model was applied to the validation set, it revealed a sensitivity of 80%, specificity of 85.7%, a positive predictive value of 77.6% and negative predictive value of 90.7%. The accuracy was 83.3%. Differences could be found between ANNs modeling and logistic regression modeling in these parameters (10.0% [95% CI, -14.3 to 34.3%], 14.3% [95% CI, -8.6 to 37.2%], 15.7% [95% CI, -9.9 to 41.3%], 11.8% [95% CI, -8.2 to 31.8%], 22.6% [95% CI, -1.9 to 47.1%], respectively). When ANNs modeling was used to identify PSMVT, the area under receiver operating characteristic curve was 0.849 (95% CI, 0.807-0.901), which demonstrated better overall properties than logistic regression modeling (AUC = 0.716) (95% CI, 0.679-0.761). Conclusions ANNs modeling was a more accurate tool than logistic regression in predicting the occurrence of PSMVT following AP. More clinical factors or biomarkers may be incorporated into ANNs modeling to improve its predictive ability. © 2016 International Society on Thrombosis and Haemostasis.

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

PubMed

Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

2013-03-01

Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

Rise in needle sharing among injection drug users in Pakistan during the Afghanistan war.

PubMed

Strathdee, Steffanie A; Zafar, Tariq; Brahmbhatt, Heena; Baksh, Ahmed; ul Hassan, Salman

2003-07-20

The war in Afghanistan in 2001 may have had direct or indirect effects on drug users' behaviors in nearby Pakistan. We studied drug use patterns and correlates of needle sharing among injection drug users (IDUs) in Lahore, Pakistan, before and after the beginning of the Afghanistan war. Between August and October 2001, 244 drug users registering for needle exchange and other services underwent an interviewer-administered survey on sociodemographics, drug use and HIV/AIDS awareness. chi(2)-tests were used to compare drug use behaviors among subjects interviewed before and after October 6th, 2001, coinciding with the start of the Afghanistan war. Correlates of needle sharing among IDUs were identified using logistic regression. Comparing IDUs interviewed before and after October 6th, 2001, levels of needle sharing were significantly higher after the war (56% versus 76%, respectively; P=0.02). Factors independently associated with needle sharing included registering after the war began (adjusted odds ratio, AOR=3.76 (95% CI: 1.23-11.48)), being married (AOR=0.36), being homeless (AOR=3.91), having been arrested (AOR=6.00), and re-using syringes (AOR=6.19). Expansion of needle exchange, drug treatment and supportive services is urgently needed to avoid an explosive HIV epidemic in Pakistan.

Prevalence of Chronic Pain, Treatments, Perception, and Interference on Life Activities: Brazilian Population-Based Survey

PubMed Central

Perissinotti, Dirce Maria Navas; de Oliveira Junior, Jose Oswaldo; da Fonseca, Paulo Renato Barreiros; Posso, Irimar de Paula

2017-01-01

Background and Objectives Chronic pain affects between 30% and 50% of the world population. Our objective was to estimate the prevalence of chronic pain in Brazil, describe and compare differences between pain types and characteristics, and identify the types of therapies adopted and the impact of pain on daily life. Methods Cross-sectional study of a population-based survey with randomized sample from a private database. The interviews were conducted by phone. 78% of the respondents aged 18 years or more agreed to be interviewed, for a total of 723 respondents distributed throughout the country. Independent variables were demographic data, pain and treatment characteristics, and impact of pain on daily life. Comparative and associative statistical analyses were conducted to select variables for nonhierarchical logistic regression. Results Chronic pain prevalence was 39% and mean age was 41 years with predominance of females (56%). We found higher prevalence of chronic pain in the Southern and Southeastern regions. Pain treatment was not specific to gender. Dissatisfaction with chronic pain management was reported by 49% of participants. Conclusion 39% of interviewed participants reported chronic pain, with prevalence of females. Gender-associated differences were found in intensity perception and interference of pain on daily life activities. PMID:29081680

Maternal support for human papillomavirus vaccination in Honduras.

PubMed

Perkins, Rebecca B; Langrish, Sarah M; Cotton, Deborah J; Simon, Carol J

2011-01-01

Cervical cancer is a leading cause of cancer death for women in Latin America, and vaccinating against human papillomavirus (HPV) has the potential to limit this disease. We sought to determine Honduran women's awareness of HPV vaccination and interest in vaccinating their daughters against HPV. We interviewed mothers aged ≥17 at primary care clinics in Honduras. First, we collected demographic information and assessed knowledge related to cervical cancer prevention and awareness of HPV and HPV vaccination. Because most participants were not familiar with HPV, education about the relationships among HPV, sexual activity, and cervical cancer was provided before we asked participants if they would accept HPV vaccination for a 9-year-old daughter. We used multivariable logistic regression to determine predictors of vaccine acceptance. We interviewed 632 mothers. Only 13% had heard of HPV vaccination before the interview. After education, 91% would accept HPV vaccination for a 9-year-old daughter. Mothers who intended to vaccinate knew more at baseline about cervical cancer prevention than did those who did not endorse vaccination. Demographic characteristics did not predict vaccine acceptance. Few Honduran mothers were aware of HPV or HPV vaccination. However, most Honduran mothers would accept HPV vaccination for their daughters after receiving education about the relationship between HPV infection and cervical cancer. Baseline cervical cancer knowledge was associated with vaccine acceptance.

Rank-Optimized Logistic Matrix Regression toward Improved Matrix Data Classification.

PubMed

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

While existing logistic regression suffers from overfitting and often fails in considering structural information, we propose a novel matrix-based logistic regression to overcome the weakness. In the proposed method, 2D matrices are directly used to learn two groups of parameter vectors along each dimension without vectorization, which allows the proposed method to fully exploit the underlying structural information embedded inside the 2D matrices. Further, we add a joint [Formula: see text]-norm on two parameter matrices, which are organized by aligning each group of parameter vectors in columns. This added co-regularization term has two roles-enhancing the effect of regularization and optimizing the rank during the learning process. With our proposed fast iterative solution, we carried out extensive experiments. The results show that in comparison to both the traditional tensor-based methods and the vector-based regression methods, our proposed solution achieves better performance for matrix data classifications.

Correlation between traumatic events and posttraumatic stress disorder among North Korean defectors in South Korea.

PubMed

Jeon, WooTaek; Hong, ChangHyung; Lee, ChangHo; Kim, Dong Kee; Han, Mooyoung; Min, SungKil

2005-04-01

The number of North Korean defectors entering South Korea has been increasing rapidly since 1994. Two hundred North Korean defectors in South Korea were studied to identify their experiences of traumatic events in North Korea and during defection, and the correlation with Posttraumatic Stress Disorder (PTSD). Researchers conducted face-to-face interviews and assisted defectors in performing a self-report assessment of this survey. The study questionnaire consisted of demographic characteristics, the Traumatic Experiences Scale for North Korean Defectors, and the PTSD part of the Structured Clinical Interview for DSM-III-R Korean version. Prevalence rate of PTSD in defectors was 29.5%, with a higher rate for women. In factor analysis, the 25 items of traumatic events experienced in North Korea were divided into three factors: Physical Trauma, Political-Ideological Trauma, and Family-Related Trauma. In addition, the 19 items of traumatic events during defection were grouped into four factors: Physical Trauma, Detection and Capture-Related Trauma, Family-Related Trauma, and Betrayal-Related Trauma. In multifactorial logistic regression analysis, Family-Related Trauma in North Korea had a significant odds ratio.

Factors associated with suicidal risk among a French cohort of problem gamblers seeking treatment.

PubMed

Guillou-Landreat, Morgane; Guilleux, Alice; Sauvaget, Anne; Brisson, Lucille; Leboucher, Juliette; Remaud, Manon; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2016-06-30

Compared to general population, pathological gamblers are 3.4 times more likely to attempt suicide. Our objective was to identify specific profiles of problem gamblers (PGs) with suicidal risk according to sociodemographic, clinical and gambling characteristics. The PGs cohort, called "EVALJEU" , consists in the inclusion of any new PG seeking treatment in our Department. Patients underwent a semi-structured clinical interview and completed self-report questionnaires. The "suicidal risk module" of the Mini International Psychiatric interview (MINI) allowed to constitute two groups of patients that were compared, according to the presence of a suicidal risk. A logistic regression was performed to identify factors related to suicidal risk in PGs. In our sample (N=194), 40.21% presented a suicidal risk. A history of major depression and anxiety disorders were predictors of suicidal risk as well as the perceived inability to stop gambling. Suicidality is a significant clinical concern in PGs. Therefore, three specific predictors, identified by our study, must be assessed. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Linking educational leadership styles to the HR architecture for new teachers in primary education.

PubMed

Vekeman, Eva; Devos, Geert; Valcke, Martin

2016-01-01

This study aims to gain insight in the relationship between principals' leadership styles and the configuration of different HR practices for new teachers in primary education. Besides the longstanding interest in educational leadership as a key element in teacher and student performance, there is a growing interest in strategic human resource management (SHRM) in the educational sector. However, few educational studies link educational leadership to SHRM. In particular, this study examines the relationship between principals' instructional and transformational leadership style and principals' strategic and HR orientation in configuring HR practices for new teachers. Data were gathered using a mixed methods approach, including interviews with 75 principals as well as an online survey of 1058 teachers in Flemish primary education. Qualitative interview data were transformed and analysed together with the quantitative survey data using logistic regression and ANOVA analyses. The results indicate that both instructional and transformational leadership is associated with the strategic orientation of principals. The HR orientation, on the other hand, is not reflected in the principals' leadership style. Recommendations for further research in this area are discussed.

Detecting DIF in Polytomous Items Using MACS, IRT and Ordinal Logistic Regression

ERIC Educational Resources Information Center

Elosua, Paula; Wells, Craig

2013-01-01

The purpose of the present study was to compare the Type I error rate and power of two model-based procedures, the mean and covariance structure model (MACS) and the item response theory (IRT), and an observed-score based procedure, ordinal logistic regression, for detecting differential item functioning (DIF) in polytomous items. A simulation…

Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

ERIC Educational Resources Information Center

Rudner, Lawrence

2016-01-01

In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?

ERIC Educational Resources Information Center

Ford, Michael

2011-01-01

This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…

Hierarchical Bayesian Logistic Regression to forecast metabolic control in type 2 DM patients.

PubMed

Dagliati, Arianna; Malovini, Alberto; Decata, Pasquale; Cogni, Giulia; Teliti, Marsida; Sacchi, Lucia; Cerra, Carlo; Chiovato, Luca; Bellazzi, Riccardo

2016-01-01

In this work we present our efforts in building a model able to forecast patients' changes in clinical conditions when repeated measurements are available. In this case the available risk calculators are typically not applicable. We propose a Hierarchical Bayesian Logistic Regression model, which allows taking into account individual and population variability in model parameters estimate. The model is used to predict metabolic control and its variation in type 2 diabetes mellitus. In particular we have analyzed a population of more than 1000 Italian type 2 diabetic patients, collected within the European project Mosaic. The results obtained in terms of Matthews Correlation Coefficient are significantly better than the ones gathered with standard logistic regression model, based on data pooling.

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

USGS Publications Warehouse

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

2008-01-01

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

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

Same-Sex Behavior and its Relationship with Sexual and Health-Related Practices Among a Population-Based Sample of Women in Puerto Rico: Implications for Cancer Prevention and Control.

PubMed

Soto-Salgado, Marievelisse; Colón-López, Vivian; Perez, Cynthia; Muñoz-Masso, Cristina; Marrero, Edmir; Suárez, Erick; Ortiz, Ana P

2016-01-01

This secondary data analysis aimed to estimate the prevalence of same-sex behavior and sexual and health-related practices of a population-based sample (n=560) of women aged 16-64 years in Puerto Rico (PR). Data collection included interviews and biologic samples. Seven percent of the sample had had sex with other women (WSW). Age-adjusted logistic regression models indicated that WSW had higher odds of history of cancer, having ≥ 7 lifetime sexual partners, using sex toys and sharing them, and use of tobacco and illicit drugs. Future research is needed to address the health needs of WSW, including cancer-related risk factors and sexual practices.

A case-control study of Nocardia mastitis in Nova Scotia dairy herds

PubMed Central

Ferns, Lyn; Dohoo, Ian; Donald, Alan

1991-01-01

A case-control study was conducted to identify herd production, housing, and hygienic and therapeutic factors associated with a diagnosis of Nocardia mastitis in dairy herds in Nova Scotia. The data were collected by on-farm interviews with owners of 54 case and 54 control herds. Logistic regression was used to study risk factors. The use of dry cow products containing neomycin, including two specific dry cow products, was strongly associated with a diagnosis of Nocardia mastitis in a herd. Other factors which increased the risk of Nocardia mastitis were higher levels of production, larger herd size, and a large percentage of cows treated with dry cow products. These results are compared to results from a similar study carried out in Ontario. PMID:17423896

Are bald men more virile than their well thatched contemporaries?

PubMed

Sinclair, Rodney D; English, Dallas R; Giles, Graham G

2013-12-16

To test the popular assertion that bald men are more virile than their well thatched contemporaries Secondary analysis of data from a case-control study in a community setting between 1994 and 1997 among men below the age of 70 years, using in-person interviews and categorisation of baldness, with subsequent completion of a questionnaire by the participant. We analysed risk factors for baldness using unconditional logistic regression. Baldness; history of ejaculations between the ages of 20 and 49 years; total number of sexual partners. There was no significant association between baldness and the frequency of ejaculations, but bald men were significantly less likely to have had more than four female sexual partners. In the population studied, bald men appear to be no more virile than their well thatched contemporaries.

Smoking, alcohol consumption and betal-quid chewing among young adult Myanmar laborers in Thailand.

PubMed

Htin, Kyaw; Howteerakull, Nopporn; Suwannapong, Nawarat; TipayamongkholgulI, Mathuros

2014-07-01

Health-risk behaviors among young adults are a serious public health problem. This cross sectional study aimed to estimate the prevalence of single and concurrent multiple health-risk behaviors: smoking tobacco, consuming alcohol, and chewing betel quid among young adult Myanmar laborers in Mae Sot District, Tak Province, Thailand. Three hundred Myanmar laborers, aged 18-24 years, were interviewed using a structured questionnaire. About 33.6% reported no risk behaviors, 24.7% had one, and 41.7% had two or three risk behaviors. Multinomial logistic regression analysis showed six variables were significantly associated with health-risk behaviors: male gender, high/moderate custom/traditional influences, friends who smoked/consumed alcohol/chewed betel quid, and exposure to betel-quid chewing by other family members.

Losing a Loved One to Homicide: Prevalence and Mental Health Correlates in a National Sample of Young Adults

PubMed Central

Zinzow, Heidi; Rheingold, Alyssa A.; Hawkins, Alesia; Saunders, Benjamin E.; Kilpatrick, Dean G.

2010-01-01

The present study examined the prevalence, demographic distribution, and mental health correlates of losing a loved one to homicide. A national sample of 1753 young adults completed structured telephone interviews measuring violence exposure, mental health diagnoses, and loss of a family member or close friend to a drunk driving accident (vehicular homicide) or murder (criminal homicide). The prevalence of homicide survivorship was 15.2%. African Americans were more highly represented among criminal homicide survivors. Logistic regression analyses found that homicide survivors were at risk for past year posttraumatic stress disorder (OR = 1.88), major depressive episode (OR = 1.64), and drug abuse/dependence (OR = 1.77). These findings highlight the significant mental health needs of homicide survivors. PMID:19230006

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Immigration, health care access, and recent cancer tests among Mexican-Americans in California.

PubMed

Breen, Nancy; Rao, Sowmya R; Meissner, Helen I

2010-08-01

Immigrants' lower rates of cancer testing may be due to lack of fluency in English and other skills and knowledge about navigating US health care markets, lack of access to health services, or both. We analyzed 9,079 Mexican-American respondents to the 2001 California Health Interview Survey (CHIS) grouped as born in the US, living in the US 10 or more years, or living in the US less than 10 years. The CHIS provides the largest Mexican-American sample in a US survey. Access to care meant having health insurance coverage and a usual source of care. English proficiency meant the respondent took the interview in English. Multivariate logistic regression was used to predict outcomes. Respondents reporting more time in the US were more likely to report access to medical care and to report getting a cancer screening exam. Regardless of time in the US, respondents reporting access had similar test rates. Regression results indicate that time in the US and primary language were not significant relative to use of cancer screening tests, but access to care was. Cancer screening tests that are covered by Every Woman Counts, California's breast and cervical cancer early detection program, had smaller gaps among groups than colorectal cancer screening which is not covered by a program. California is the only state with a survey able to monitor changes in small population groups. Understanding barriers specific to subgroups is key to developing appropriate policy and interventions to increase use of cancer screening exams.

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

ERIC Educational Resources Information Center

Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

2010-01-01

The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Odds Ratio, Delta, ETS Classification, and Standardization Measures of DIF Magnitude for Binary Logistic Regression

ERIC Educational Resources Information Center

Monahan, Patrick O.; McHorney, Colleen A.; Stump, Timothy E.; Perkins, Anthony J.

2007-01-01

Previous methodological and applied studies that used binary logistic regression (LR) for detection of differential item functioning (DIF) in dichotomously scored items either did not report an effect size or did not employ several useful measures of DIF magnitude derived from the LR model. Equations are provided for these effect size indices.…

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

ERIC Educational Resources Information Center

Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

2012-01-01

Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

Estimation of Logistic Regression Models in Small Samples. A Simulation Study Using a Weakly Informative Default Prior Distribution

ERIC Educational Resources Information Center

Gordovil-Merino, Amalia; Guardia-Olmos, Joan; Pero-Cebollero, Maribel

2012-01-01

In this paper, we used simulations to compare the performance of classical and Bayesian estimations in logistic regression models using small samples. In the performed simulations, conditions were varied, including the type of relationship between independent and dependent variable values (i.e., unrelated and related values), the type of variable…

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

USGS Publications Warehouse

Ohlmacher, G.C.; Davis, J.C.

2003-01-01

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

PubMed

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (P<0.05). In addition, a comparison of the area under receiver operating characteristic curves of the two models showed a statistically significant difference (P<0.05). The RBF ANNs model is more likely to predict the occurrence of PVT induced by AP than logistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

A multinational case-control study on childhood brain tumours, anthropogenic factors, birth characteristics and prenatal exposures: A validation of interview data.

PubMed

Vienneau, Danielle; Infanger, Denis; Feychting, Maria; Schüz, Joachim; Schmidt, Lisbeth Samsø; Poulsen, Aslak Harbo; Tettamanti, Giorgio; Klæboe, Lars; Kuehni, Claudia E; Tynes, Tore; Von der Weid, Nicolas; Lannering, Birgitta; Röösli, Martin

2016-02-01

Little is known about the aetiology of childhood brain tumours. We investigated anthropometric factors (birth weight, length, maternal age), birth characteristics (e.g. vacuum extraction, preterm delivery, birth order) and exposures during pregnancy (e.g. maternal: smoking, working, dietary supplement intake) in relation to risk of brain tumour diagnosis among 7-19 year olds. The multinational case-control study in Denmark, Sweden, Norway and Switzerland (CEFALO) included interviews with 352 (participation rate=83.2%) eligible cases and 646 (71.1%) population-based controls. Interview data were complemented with data from birth registries and validated by assessing agreement (Cohen's Kappa). We used conditional logistic regression models matched on age, sex and geographical region (adjusted for maternal age and parental education) to explore associations between birth factors and childhood brain tumour risk. Agreement between interview and birth registry data ranged from moderate (Kappa=0.54; worked during pregnancy) to almost perfect (Kappa=0.98; birth weight). Neither anthropogenic factors nor birth characteristics were associated with childhood brain tumour risk. Maternal vitamin intake during pregnancy was indicative of a protective effect (OR 0.75, 95%-CI: 0.56-1.01). No association was seen for maternal smoking during pregnancy or working during pregnancy. We found little evidence that the considered birth factors were related to brain tumour risk among children and adolescents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Agreement between patient interview data on prescription medication use and pharmacy records in those aged older than 50 years varied by therapeutic group and reporting of indicated health conditions.

PubMed

Richardson, Kathryn; Kenny, Rose Anne; Peklar, Jure; Bennett, Kathleen

2013-11-01

To estimate the agreement between interview-ascertained medication use and pharmacy records among the population aged older than 50 years, and to identify patient-level predictors of discordance. The Irish Longitudinal study on Ageing is representative of community-dwelling adults aged 50 years and older in Ireland. Interview-ascertained medication data from 2,621 participants were linked to pharmacy dispensing records. The kappa statistics measured the agreement between the two sources for 19 therapeutic classes. Logistic regression assessed the effect of patient-level characteristics on survey under- and overreporting of regularly dispensed medications. Agreement was good or very good (κ=0.64-0.86) for 15 medication classes, and moderate or poor for antiinflammatory and antirheumatic products (κ=0.54), analgesics (κ=0.50), psycholeptics (κ=0.59), and ophthalmologicals (κ=0.37). Not reporting an indicated health condition, less frequent dispensing, older age, and more medications regularly dispensed were associated with survey underreporting, but results varied by therapeutic class. Memory and cognition were not associated with discordance. Ascertaining medication use via patient interview seems a valid method for most medication classes and also captures nonprescription and supplement use. However, medications applied topically and as needed may be underreported. The source of medication data should be carefully considered when performing pharmacoepidemiological studies. Copyright © 2013 Elsevier Inc. All rights reserved.

EXpectation Propagation LOgistic REgRession (EXPLORER): Distributed Privacy-Preserving Online Model Learning

PubMed Central

Wang, Shuang; Jiang, Xiaoqian; Wu, Yuan; Cui, Lijuan; Cheng, Samuel; Ohno-Machado, Lucila

2013-01-01

We developed an EXpectation Propagation LOgistic REgRession (EXPLORER) model for distributed privacy-preserving online learning. The proposed framework provides a high level guarantee for protecting sensitive information, since the information exchanged between the server and the client is the encrypted posterior distribution of coefficients. Through experimental results, EXPLORER shows the same performance (e.g., discrimination, calibration, feature selection etc.) as the traditional frequentist Logistic Regression model, but provides more flexibility in model updating. That is, EXPLORER can be updated one point at a time rather than having to retrain the entire data set when new observations are recorded. The proposed EXPLORER supports asynchronized communication, which relieves the participants from coordinating with one another, and prevents service breakdown from the absence of participants or interrupted communications. PMID:23562651

Correlates of cognitive function scores in elderly outpatients.

PubMed

Mangione, C M; Seddon, J M; Cook, E F; Krug, J H; Sahagian, C R; Campion, E W; Glynn, R J

1993-05-01

To determine medical, ophthalmologic, and demographic predictors of cognitive function scores as measured by the Telephone Interview for Cognitive Status (TICS), an adaptation of the Folstein Mini-Mental Status Exam. A secondary objective was to perform an item-by-item analysis of the TICS scores to determine which items correlated most highly with the overall scores. Cross-sectional cohort study. The Glaucoma Consultation Service of the Massachusetts Eye and Ear Infirmary. 472 of 565 consecutive patients age 65 and older who were seen at the Glaucoma Consultation Service between November 1, 1987 and October 31, 1988. Each subject had a standard visual examination and review of medical history at entry, followed by a telephone interview that collected information on demographic characteristics, cognitive status, health status, accidents, falls, symptoms of depression, and alcohol intake. A multivariate linear regression model of correlates of TICS score found the strongest correlates to be education, age, occupation, and the presence of depressive symptoms. The only significant ocular condition that correlated with lower TICS score was the presence of surgical aphakia (model R2 = .46). Forty-six percent (216/472) of patients fell below the established definition of normal on the mental status scale. In a logistic regression analysis, the strongest correlates of an abnormal cognitive function score were age, diabetes, educational status, and occupational status. An item analysis using step-wise linear regression showed that 85 percent of the variance in the TICS score was explained by the ability to perform serial sevens and to repeat 10 items immediately after hearing them. Educational status correlated most highly with both of these items (Kendall Tau R = .43 and Kendall Tau R = .30, respectively). Education, occupation, depression, and age were the strongest correlates of the score on this new screening test for assessing cognitive status. These factors were stronger correlates of the TICS score than chronic medical conditions, visual loss, or medications. The Telephone Interview for Cognitive Status is a useful instrument, but it may overestimate the prevalence of dementia in studies with a high prevalence of persons with less than a high school education.

Social, economic and environmental risk factors for acute lower respiratory infections among children under five years of age in Rwanda.

PubMed

Harerimana, Jean-Modeste; Nyirazinyoye, Leatitia; Thomson, Dana R; Ntaganira, Joseph

2016-01-01

In low and middle-income countries, acute lower respiratory illness is responsible for roughly 1 in every 5 child deaths. Rwanda has made major health system improvements including its community health worker systems, and it is one of the few countries in Africa to meet the 2015 Millennium Development Goals, although prevalence of acute lower respiratory infections (4 %) is similar to other countries in sub-Saharan Africa. This study aims to assess social, economic, and environmental factors associated with acute lower respiratory infections among children under five to inform potential further improvements in the health system. This is a cross-sectional study using data collected from women interviewed in the 2010 DHS about 8,484 surviving children under five. Based on a literature review, we defined 19 health, social, economic, and environmental potential risk factors, tested bivariate associations with acute lower respiratory infections, and advanced variables significant at the 0.1 confidence level to logistic regression modelling. We used manual backward stepwise regression to arrive at a final model. All analyses were performed in Stata v13 and adjusted for complex sample design. The following factors were independently associated with acute lower respiratory infections: child's age, anemia level, and receipt of Vitamin A; household toilet type and residence, and season of interview. In multivariate regression, being in the bottom ten percent of households (OR: 1.27, 95 % CI: 0.85-1.87) or being interviewed during the rainy season (OR: 1.61, 95 % CI: 1.24-2.09) was positively associated with acute lower respiratory infections, while urban residence (OR: 0.58, 95 % CI: 0.38-0.88) and being age 24-59 months versus 0-11 months (OR: 0.53, 95 % CI: 0.40-0.69) was negatively associated with acute lower respiratory infections. Potential areas for intervention including community campaigns about acute lower respiratory infections symptoms and treatment, and continued poverty reduction through rural electrification and modern stove distribution which may reduce use of dirty cooking fuel, improve living conditions, and reduce barriers to health care.

Survey on Tuberculosis Patients in Rural Areas in China: Tracing the Role of Stigma in Psychological Distress.

PubMed

Xu, Minlan; Markström, Urban; Lyu, Juncheng; Xu, Lingzhong

2017-10-04

Depressed patients had risks of non-adherence to medication, which brought a big challenge for the control of tuberculosis (TB). The stigma associated with TB may be the reason for distress. This study aimed to assess the psychological distress among TB patients living in rural areas in China and to further explore the relation of experienced stigma to distress. This study was a cross-sectional study with multi-stage randomized sampling for recruiting TB patients. Data was collected by the use of interviewer-led questionnaires. A total of 342 eligible and accessible TB patients being treated at home were included in the survey. Psychological distress was measured using the Kessler Psychological Distress Scale (K10). Experienced stigma was measured using a developed nine-item stigma questionnaire. Univariate analysis and multiple logistic regression were used to analyze the variables related to distress, respectively. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to present the strength of the associations. Finally, the prediction of logistic model was assessed in form of the Receiver Operating Characteristic (ROC) curve and the area under the ROC curve (AUC). According to the referred cut-off point from K10, this study revealed that 65.2% (223/342) of the participants were categorized as having psychological distress. Both the stigma questionnaire and the K10 were proven to be reliable and valid in measurement. Further analysis found that experienced stigma and illness severity were significant variables to psychological distress in the model of logistic regression. The model was assessed well in predicting distress by use of experienced stigma and illness severity in form of ROC and AUC. Rural TB patients had a high prevalence of psychological distress. Experience of stigma played a significant role in psychological distress. To move the barrier of stigma from the surroundings could be a good strategy in reducing distress for the patients and TB controlling for public health management.

Major depressive disorder and suicide risk among adult outpatients at several general hospitals in a Chinese Han population

PubMed Central

Li, Haiyan; Luo, Xinni; Ke, Xiaoyin; Dai, Qing; Zheng, Wei; Zhang, Chanjuan; Cassidy, Ryan M.; Soares, Jair C.; Zhang, XiangYang

2017-01-01

Background Somatic complaints are often the presenting symptoms of major depressive disorder (MDD) in the outpatient context, because this may go unrecognized. It is well understood that MDD carries an increased risk of suicide. This study aimed to identify the risk factors and association with both MDD and suicidality among Han Chinese outpatients. Methods A multicenter study was carried out in 5189 outpatient adults (≥18 years old) in four general hospitals in Guangzhou, China. The 1392 patients who had the Patient Health Questionnaire-9 (PHQ-9) score ≥ 5, indicating depressive symptoms were offered an interview with a psychiatrist by the Mini International Neuropsychiatric Interview (MINI); 819 patients consented and completed the MINI interview. MINI module B was used to assess suicidality. Stepwise binary logistic models were used to estimate the relationship between a significant risk factor and suicide or MDD. According to with or without MDD, the secondary analysis was performed using the logistic regression model for the risk of suicidility. Results The current prevalence of MDD and the one month prevalence of suicidality were 3.7% and 2.3% respectively. The odds ratio of suicidality in women was more than twice that in men (OR = 2.62; 95% CI 1.45–4.76). Other risk factors which were significantly associated with suicidality were: living alone, higher education, self-reported depression, getting psychiatric diagnoses (MDD, anxiety disorders, and bipolar disorders). Significant risk factors for MDD were also noticed, such as comorbid anxiety disorders, self-reported anxiety, insomnia, suicidal ideation. Limitation It’s a cross-sectional study in outpatient clinics using self-report questionnaires. Conclusion This study provides valuable data about the risk factors and association of MDD and suicide risk in adult outpatients in Han Chinese. Those factors allow better the employment of preventative measures. PMID:29016669

Dietary consumption patterns and laryngeal cancer risk.

PubMed

Vlastarakos, Petros V; Vassileiou, Andrianna; Delicha, Evie; Kikidis, Dimitrios; Protopapas, Dimosthenis; Nikolopoulos, Thomas P

2016-06-01

We conducted a case-control study to investigate the effect of diet on laryngeal carcinogenesis. Our study population was made up of 140 participants-70 patients with laryngeal cancer (LC) and 70 controls with a non-neoplastic condition that was unrelated to diet, smoking, or alcohol. A food-frequency questionnaire determined the mean consumption of 113 different items during the 3 years prior to symptom onset. Total energy intake and cooking mode were also noted. The relative risk, odds ratio (OR), and 95% confidence interval (CI) were estimated by multiple logistic regression analysis. We found that the total energy intake was significantly higher in the LC group (p < 0.001), and that the difference remained statistically significant after logistic regression analysis (p < 0.001; OR: 118.70). Notably, meat consumption was higher in the LC group (p < 0.001), and the difference remained significant after logistic regression analysis (p = 0.029; OR: 1.16). LC patients also consumed significantly more fried food (p = 0.036); this difference also remained significant in the logistic regression model (p = 0.026; OR: 5.45). The LC group also consumed significantly more seafood (p = 0.012); the difference persisted after logistic regression analysis (p = 0.009; OR: 2.48), with the consumption of shrimp proving detrimental (p = 0.049; OR: 2.18). Finally, the intake of zinc was significantly higher in the LC group before and after logistic regression analysis (p = 0.034 and p = 0.011; OR: 30.15, respectively). Cereal consumption (including pastas) was also higher among the LC patients (p = 0.043), with logistic regression analysis showing that their negative effect was possibly associated with the sauces and dressings that traditionally accompany pasta dishes (p = 0.006; OR: 4.78). Conversely, a higher consumption of dairy products was found in controls (p < 0.05); logistic regression analysis showed that calcium appeared to be protective at the micronutrient level (p < 0.001; OR: 0.27). We found no difference in the overall consumption of fruits and vegetables between the LC patients and controls; however, the LC patients did have a greater consumption of cooked tomatoes and cooked root vegetables (p = 0.039 for both), and the controls had more consumption of leeks (p = 0.042) and, among controls younger than 65 years, cooked beans (p = 0.037). Lemon (p = 0.037), squeezed fruit juice (p = 0.032), and watermelon (p = 0.018) were also more frequently consumed by the controls. Other differences at the micronutrient level included greater consumption by the LC patients of retinol (p = 0.044), polyunsaturated fats (p = 0.041), and linoleic acid (p = 0.008); LC patients younger than 65 years also had greater intake of riboflavin (p = 0.045). We conclude that the differences in dietary consumption patterns between LC patients and controls indicate a possible role for lifestyle modifications involving nutritional factors as a means of decreasing the risk of laryngeal cancer.

Village health volunteers’ social capital related to their performance in Lao People’s Democratic Republic: a cross-sectional study

PubMed Central

2014-01-01

Background Improving the performance of community health workers (CHWs) is a global issue. The relationship between CHWs and their community may impact their performance. In Lao People’s Democratic Republic (Lao PDR), CHW are called village health volunteers (VHV). Lao PDR has a problem with VHV inactivity, especially in rural areas. This study focused on which aspects of social capital are related to VHV performance. Methods This research represents a cross-sectional study with a quantitative survey based primarily on interviews using a semi-structured questionnaire. Interviews were conducted with 149 VHVs living and working in the Sepon District. VHV performance evaluation was measured with scores on a 5-point scale, and the cutoff point for designating performance as good or poor was set at the median score. This evaluation of VHV performance was conducted as a self-evaluation by VHVs and by health center staff who were supervisors of the VHVs. Measurement of social capital was accomplished using the short version of the Adapted Social Capital Assessment Tool (SASCAT). For statistical analyses, logistic regression was used to calculate adjusted odds ratios (OR) and 95% confidence intervals (CI). Results The results of multiple logistic regression adjusted by moderator variables showed that citizenship activities in the structural social capital component of SASCAT were significantly related to performance in self-evaluation by VHVs (adjusted OR: 2.10, 95% CI: 1.19-3.71) and the evaluations by health center staff (adjusted OR: 1.67, 95% CI: 1.01-2.77). Support from groups (adjusted OR: 1.87, 95% CI: 1.27-2.76) and cognitive social capital (adjusted OR: 7.48, 95% CI: 2.14-26.10) were found to be significantly associated but only for VHV self-evaluation. Conclusions The results suggest that individuals who interact with important figures in the community and who cooperate with other villagers whenever problems arise, i.e., have social capital, exhibit good performance as VHVs. These findings suggest that increasing citizenship activities could increase the retention rate of CHWs and help improve their performance. Citizenship activities could also be used as a predictive indicator when selecting new CHWs. PMID:24620729

Risk factors associated with default among new smear positive TB patients treated under DOTS in India.

PubMed

Vijay, Sophia; Kumar, Prahlad; Chauhan, Lakbir Singh; Vollepore, Balasangameshwara Hanumanthappa; Kizhakkethil, Unnikrishnan Pallikkara; Rao, Sumathi Govinda

2010-04-06

Poor treatment adherence leading to risk of drug resistance, treatment failure, relapse, death and persistent infectiousness remains an impediment to the tuberculosis control programmes. The objective of the study was to identify predictors of default among new smear positive TB patients registered for treatment to suggest possible interventions to set right the problems to sustain and enhance the programme performance. Twenty districts selected from six states were assigned to six strata formed, considering the geographic, socio-cultural and demographic setup of the area. New smear positive patients registered for treatment in two consecutive quarters during III quarter 2004 to III quarter 2005 formed the retrospective study cohort. Case control analysis was done including defaulted patients as "cases" and equal number of age and sex matched patients completing treatment as "controls". The presence and degree of association between default and determinant factors was computed through univariate and multivariate logistic regression analysis. Data collection was through patient interviews using pre-tested semi structured questionnaire and review of treatment related records. Information on a wide range of socio demographic and patient related factors was obtained. Among the 687 defaulted and equal numbers of patients in completed group, 389 and 540 patients respectively were satisfactorily interviewed. In the logistic regression analysis, factors independently associated with default were alcoholism [AOR-1.72 (1.23-2.44)], illiteracy [AOR-1.40 (1.03-1.92)], having other commitments during treatment [AOR-3.22 (1.1-9.09)], inadequate knowledge of TB [AOR-1.88(1.35-2.63)], poor patient provider interaction [AOR-1.72(1.23-2.44)], lack of support from health staff [AOR-1.93(1.41-2.64)], having instances of missed doses [AOR-2.56(1.82-3.57)], side effects to anti TB drugs [AOR-2.55 (1.87-3.47)] and dissatisfaction with services provided [AOR-1.73 (1.14-2.6)]. Majority of risk factors for default were treatment and provider oriented and rectifiable with appropriate interventions, which would help in sustaining the good programme performance.

Ethnic and sex differences in E-cigarette use and relation to alcohol use in California adolescents: the California Health Interview Survey.

PubMed

Wong, D N; Fan, W

2018-04-01

E-cigarette use is not only prevalent among adolescents but is growing at an alarming rate. This study sought to determine e-cigarette use prevalence and its relation to alcohol use as a potential gateway drug, and how this may differ by sex and ethnicity in a multi-ethnic sample of California adolescents. Cross-sectional survey. We included data from 1806 adolescents (weighted to 3.0 million) aged 12-17 in the 2014 and 2015 California Health Interview Survey (CHIS) cycles. The prevalence of e-cigarette use was calculated within sex and ethnic groups and the prevalence of alcohol use according to e-cigarette use was also examined with sample weighting providing population estimates. Multiple logistic regression models were built to predict the odds of using alcohol from e-cigarette use status adjusted for sociodemographic and other characteristics. The prevalence of e-cigarette use was 9.1% (projected to 0.3 million) overall in California adolescents but highest in boys among non-Hispanic Whites (15.1%) and in Asian girls (13.3%). Among e-cigarette users, 61.3% of boys and 71.0% of girls reported using alcohol as well. The logistic regression odds of alcohol use, adjusted for age, ethnicity, body mass index, cigarette smoking status, socioeconomic status, parents' education level, and insurance status among e-cigarettes users (compared with non-users) was 9.2 in girls and 3.1 in boys (both P < 0.01). Asians/others, non-Hispanic whites and Hispanics were similarly at increased odds: 17.8, 5.4, and 3.0, respectively (P < 0.01 for Asians/others and for whites) of using alcohol compared with their non-e-cigarette using counterparts, respectively. Attention needs to be paid to the high prevalence of e-cigarette smoking as well as its potential as a gateway drug for alcohol drinking in adolescents, especially among girls and Asians. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

A Comparison of the Logistic Regression and Contingency Table Methods for Simultaneous Detection of Uniform and Nonuniform DIF

ERIC Educational Resources Information Center

Guler, Nese; Penfield, Randall D.

2009-01-01

In this study, we investigate the logistic regression (LR), Mantel-Haenszel (MH), and Breslow-Day (BD) procedures for the simultaneous detection of both uniform and nonuniform differential item functioning (DIF). A simulation study was used to assess and compare the Type I error rate and power of a combined decision rule (CDR), which assesses DIF…

The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

ERIC Educational Resources Information Center

Le, Huy; Marcus, Justin

2012-01-01

This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

2012-01-01

Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

Using ROC curves to compare neural networks and logistic regression for modeling individual noncatastrophic tree mortality

Treesearch

Susan L. King

2003-01-01

The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...

Logistic regression trees for initial selection of interesting loci in case-control studies

PubMed Central

Nickolov, Radoslav Z; Milanov, Valentin B

2007-01-01

Modern genetic epidemiology faces the challenge of dealing with hundreds of thousands of genetic markers. The selection of a small initial subset of interesting markers for further investigation can greatly facilitate genetic studies. In this contribution we suggest the use of a logistic regression tree algorithm known as logistic tree with unbiased selection. Using the simulated data provided for Genetic Analysis Workshop 15, we show how this algorithm, with incorporation of multifactor dimensionality reduction method, can reduce an initial large pool of markers to a small set that includes the interesting markers with high probability. PMID:18466557

Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

Polymorphism Thr160Thr in SRD5A1, involved in the progesterone metabolism, modifies postmenopausal breast cancer risk associated with menopausal hormone therapy.

PubMed

Hein, R; Abbas, S; Seibold, P; Salazar, R; Flesch-Janys, D; Chang-Claude, J

2012-01-01

Menopausal hormone therapy (MHT) is associated with an increased breast cancer risk in postmenopausal women, with combined estrogen-progestagen therapy posing a greater risk than estrogen monotherapy. However, few studies focused on potential effect modification of MHT-associated breast cancer risk by genetic polymorphisms in the progesterone metabolism. We assessed effect modification of MHT use by five coding single nucleotide polymorphisms (SNPs) in the progesterone metabolizing enzymes AKR1C3 (rs7741), AKR1C4 (rs3829125, rs17134592), and SRD5A1 (rs248793, rs3736316) using a two-center population-based case-control study from Germany with 2,502 postmenopausal breast cancer patients and 4,833 matched controls. An empirical-Bayes procedure that tests for interaction using a weighted combination of the prospective and the retrospective case-control estimators as well as standard prospective logistic regression were applied to assess multiplicative statistical interaction between polymorphisms and duration of MHT use with regard to breast cancer risk assuming a log-additive mode of inheritance. No genetic marginal effects were observed. Breast cancer risk associated with duration of combined therapy was significantly modified by SRD5A1_rs3736316, showing a reduced risk elevation in carriers of the minor allele (p (interaction,empirical-Bayes) = 0.006 using the empirical-Bayes method, p (interaction,logistic regression) = 0.013 using logistic regression). The risk associated with duration of use of monotherapy was increased by AKR1C3_rs7741 in minor allele carriers (p (interaction,empirical-Bayes) = 0.083, p (interaction,logistic regression) = 0.029) and decreased in minor allele carriers of two SNPs in AKR1C4 (rs3829125: p (interaction,empirical-Bayes) = 0.07, p (interaction,logistic regression) = 0.021; rs17134592: p (interaction,empirical-Bayes) = 0.101, p (interaction,logistic regression) = 0.038). After Bonferroni correction for multiple testing only SRD5A1_rs3736316 assessed using the empirical-Bayes method remained significant. Postmenopausal breast cancer risk associated with combined therapy may be modified by genetic variation in SRD5A1. Further well-powered studies are, however, required to replicate our finding.

Distress and depression in men who have sex with men: the Urban Men's Health Study.

PubMed

Mills, Thomas C; Paul, Jay; Stall, Ron; Pollack, Lance; Canchola, Jesse; Chang, Y Jason; Moskowitz, Judith T; Catania, Joseph A

2004-02-01

This study estimates the prevalence of depression and describes the correlates and independent associations of distress and depression among U.S. men who have sex with men. A household-based probability sample of men who have sex with men (N=2,881) was interviewed between 1996 and 1998 in four large American cities. With cutoff points of 15 and 22 for the Center for Epidemiological Studies Depression Scale, individual correlates and predictors of distress and depression were examined, and multinomial logistic regression was performed. The 7-day prevalence of depression in men who have sex with men was 17.2%, higher than in adult U.S. men in general. Both distress and depression were associated with lack of a domestic partner; not identifying as gay, queer, or homosexual; experiencing multiple episodes of antigay violence in the previous 5 years; and very high levels of community alienation. Distress was also associated with being of other than Asian/Pacific Islander ethnicity and experiencing early antigay harassment. Depression was also associated with histories of attempted suicide, child abuse, and recent sexual dysfunction. Being HIV positive was correlated with distress and depression but not significantly when demographic characteristics, developmental history, substance use, sexual behavior, and current social context were controlled by logistic regression. Rates of distress and depression are high in men who have sex with men. These high rates have important public health ramifications. The predictors of distress and depression suggest prevention efforts that might be effective when aimed at men who have sex with men.

Substance use disorder comorbidity with schizophrenia in families of Mexican and Central American Ancestry

PubMed Central

Jiménez-Castro, Lorena; Hare, Elizabeth; Medina, Rolando; Raventos, Henriette; Nicolini, Humberto; Mendoza, Ricardo; Ontiveros, Alfonso; Jerez, Alvaro; Muñoz, Rodrigo; Dassori, Albana; Escamilla, Michael

2010-01-01

Objectives The aims of this study were to estimate the frequency and course of substances use disorders in Latino patients with schizophrenia and to ascertain risk factors associated with substance use disorders in this population. Method We studied 518 subjects with schizophrenia recruited for a genetic study from the Southwest United States, Mexico, and Central America (Costa Rica and Guatemala). Subjects were assessed using structured interviews and a best estimate consensus process. Logistic regression, χ2, t- test, Fisher’s exact test, and Yates’ correction, as appropriate, were performed to assess the sociodemographic variables associated with dual diagnosis. We defined substance use disorder as either alcohol or substance abuse or dependence. Results Out of 518 patients with schizophrenia, 121 (23.4%) had substance use disorders. Comorbid substance use disorders were associated with male gender, residence in the United States, immigration of Mexican men to the United State, history of depressive syndrome or episode, and being unemployed. The most frequent substance use disorder was alcohol abuse/dependence, followed by marijuana abuse/dependence, and solvent abuse/dependence. Conclusion This study provides data suggesting that depressive episode or syndrome, unemployment, male gender, and immigration of Mexican men to the United States were factors associated with substance use disorder comorbidity in schizophrenia. Binary logistic regression showed that country of residence was associated with substance use disorder in schizophrenic patients. The percentage of subjects with comorbid substance use disorders was higher in the Latinos living in the United States compared with subjects living in Central America and Mexico. PMID:20303714

The predictors and consequences of adolescent amphetamine use: findings from the Victoria Adolescent Health Cohort Study.

PubMed

Degenhardt, Louisa; Coffey, Carolyn; Moran, Paul; Carlin, John B; Patton, George C

2007-07-01

Previous work has highlighted the adverse consequences of early-onset cannabis use. However, little is known about the predictors and effects of early-onset amphetamine use. We set out to examine these issues using a representative cohort of young people followed-up over 11 years in Victoria, Australia. A stratified, random sample of 1943 adolescents was recruited from secondary schools across Victoria at age 14-15 years. This cohort was interviewed on eight occasions until the age of 24-25 years (78% follow-up at that age). Cross-sectional associations were assessed using logistic regression with allowance for repeated measures. Both proportional hazards models and logistic regression models were used to assess prospective associations. Approximately 7% of the sample had used amphetamines by the age of 17 years. Amphetamine use by this age was associated with poorer mental health and other drug use. The incidence of amphetamine use during the teenage years was predicted by heavier drug use and by mental health problems. By young adulthood (age 24-25 years), adolescent amphetamine users were more likely to meet criteria for dependence upon a range of drugs, to have greater psychological morbidity and to have some limitations in educational attainment. Most of these associations were not sustained after adjustment for early-onset cannabis use. Young people in Australia who begin amphetamine use by age 17 years are at increased risk for a range of mental health, substance use and psychosocial problems in young adulthood. However, these problems are largely accounted for by their even earlier-onset cannabis use.

Prevalence of cognitive and functional impairment in a community sample in Ribeirão Preto, Brazil.

PubMed

Lopes, Marcos A; Hototian, Sergio R; Bustamante, Sonia E Z; Azevedo, Dionísio; Tatsch, Mariana; Bazzarella, Mário C; Litvoc, Júlio; Bottino, Cássio M C

2007-08-01

This study aimed at estimating the prevalence of cognitive and functional impairment (CFI) in a community sample in Ribeirão Preto, Brazil, evaluating its distribution in relation to various socio-demographic and clinical factors. The population was a representative sample aged 60 and older, from three different socio-economic classes. Cluster sampling was applied. Instruments used to select CFI (a syndromic category that does not exclude dementia): 'Mini Mental State Examination' (MMSE), 'Fuld Object Memory Evaluation' (FOME), 'Informant Questionnaire on Cognitive Decline in the Elderly' (IQCODE), 'Bayer Activities of Daily Living Scale' (B-ADL) and clinical interviews. The data obtained were submitted to bivariate and logistic regression analysis. A sample of 1.145 elderly persons was evaluated, with a mean age of 70.9 years (60-100; DP: 7.7); 63.4% were female, and 52.8% had up to 4 years of schooling. CFI prevalence was 18.9% (n = 217). Following logistic regression analysis, higher age, low education, stroke, epilepsy and depression were associated with CFI. Female sex, widowhood, low social class and head trauma were associated with CFI only on bivariate analysis. CFI prevalence results were similar to those found by studies in Brazil, Puerto Rico and Malaysia. Cognitive and functional impairment is a rather heterogeneous condition which may be associated with various clinical conditions found in the elderly population. Due to its high prevalence and association with higher mortality and disability rates, this clinical syndrome should receive more attention on public health intervention planning.

Rural-urban difference in the use of annual physical examination among seniors in Shandong, China: a cross-sectional study.

PubMed

Ge, Dandan; Chu, Jie; Zhou, Chengchao; Qian, Yangyang; Zhang, Li; Sun, Long

2017-05-23

Regular physical examination contributes to early detection and timely treatment, which is helpful in promoting healthy behaviors and preventing diseases. The objective of this study is to compare the annual physical examination (APE) use between rural and urban elderly in China. A total of 3,922 participants (60+) were randomly selected from three urban districts and three rural counties in Shandong Province, China, and were interviewed using a standardized questionnaire. We performed unadjusted and adjusted logistic regression models to examine the difference in the utilization of APE between rural and urban elderly. Two adjusted logistic regression models were employed to identify the factors associated with APE use in rural and urban seniors respectively. The utilization rates of APE in rural and urban elderly are 37.4% and 76.2% respectively. Factors including education level, exercise, watching TV, and number of non-communicable chronic conditions, are associated with APE use both in rural and urban elderly. Hospitalization, self-reported economic status, and health insurance are found to be significant (p < 0.05) predictors for APE use in rural elderly. Elderly covered by Urban Resident Basic Medical Insurance (URBMI) (p < 0.05, OR = 1.874) are more likely to use APE in urban areas. There is a big difference in APE utilization between rural and urban elderly. Interventions targeting identified at-risk subgroups, especially for those rural elderly, are essential to reduce such a gap. To improve health literacy might be helpful to increase the utilization rate of APE among the elderly.

A cross-sectional evaluation of the prevalence and detection of predictors of polypharmacy amongst adult in Spain.

PubMed

Niclós, Gracia; Olivar, Teresa; Rodilla, Vicent

2018-06-01

To investigate the association between polypharmacy and sociodemographic factors as well as health status, determinants of health and healthcare use, illness and use of prescribed medicines amongst adults in Spain. Data from the 2009 European Health Interview Survey in Spain which included 22 188 subjects were used. Polypharmacy was defined as the use of five or more prescribed medicines. The association between polypharmacy and several variables was assessed by means of bivariate analysis and logistic regression analysis (adjusted by age and gender). Amongst study participants, 15.8% were on prescribed polypharmacy (19.3%, women; 10.3%, men (P < 0.001)). A number of sociodemographic factors (e.g. age, gender, educational level), health status factors (e.g. limitation in daily activities, self-perception of health, presence of chronic disease) and other health-related factors (e.g. smoking, alcohol drinking, physical activity) have been studied and have been found to play a role in polypharmacy. Logistic regression analysis provided three variables which together with age could be used to predict polypharmacy. In Spain, approximately 16% of people who take medicines are on polypharmacy and this is more frequent in women and amongst older adults. From our study, we can conclude that the variables which can predict a higher likelihood of polypharmacy are, together with age, prescribed antidepressants, and prescribed medicines for back/neck pain and joint pain. This may provide a tool for health professionals to readily assess polypharmacy appropriateness in polymedicated patients. © 2017 Royal Pharmaceutical Society.

Can You Ride a Bicycle? The Ability to Ride a Bicycle Prevents Reduced Social Function in Older Adults With Mobility Limitation

PubMed Central

Sakurai, Ryota; Kawai, Hisashi; Yoshida, Hideyo; Fukaya, Taro; Suzuki, Hiroyuki; Kim, Hunkyung; Hirano, Hirohiko; Ihara, Kazushige; Obuchi, Shuichi; Fujiwara, Yoshinori

2016-01-01

Background The health benefits of bicycling in older adults with mobility limitation (ML) are unclear. We investigated ML and functional capacity of older cyclists by evaluating their instrumental activities of daily living (IADL), intellectual activity, and social function. Methods On the basis of interviews, 614 community-dwelling older adults (after excluding 63 participants who never cycled) were classified as cyclists with ML, cyclists without ML, non-cyclists with ML (who ceased bicycling due to physical difficulties), or non-cyclists without ML (who ceased bicycling for other reasons). A cyclist was defined as a person who cycled at least a few times per month, and ML was defined as difficulty walking 1 km or climbing stairs without using a handrail. Functional capacity and physical ability were evaluated by standardized tests. Results Regular cycling was documented in 399 participants, and 74 of them (18.5%) had ML; among non-cyclists, 49 had ML, and 166 did not. Logistic regression analysis for evaluating the relationship between bicycling and functional capacity revealed that non-cyclists with ML were more likely to have reduced IADL and social function compared to cyclists with ML. However, logistic regression analysis also revealed that the risk of bicycle-related falls was significantly associated with ML among older cyclists. Conclusions The ability and opportunity to bicycle may prevent reduced IADL and social function in older adults with ML, although older adults with ML have a higher risk of falls during bicycling. It is important to develop a safe environment for bicycling for older adults. PMID:26902165

Association between polycystic ovary syndrome and hot flash presentation during the midlife period.

PubMed

Yin, Ophelia; Zacur, Howard A; Flaws, Jodi A; Christianson, Mindy S

2018-06-01

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in reproductive-aged women; however, the impact of PCOS on menopausal symptoms remains poorly understood. This study aims to determine the influence of PCOS on hot flash presentation in midlife women. Participants were recruited from the Midlife Women's Health Study involving 780 women aged 45 to 54 years. All women completed detailed questionnaires on hot flash symptoms. Between June 2014 and March 2015, participants were screened for history of PCOS based on the Rotterdam criteria. Fisher's exact tests and Wilcoxon rank-sum tests were used for analysis. Multivariate logistic regression was performed to identify factors associated with hot flashes at midlife. In all, 453 women (69%) consented to the telephone interview and 9.3% (n = 42) met diagnostic criteria for PCOS; 411 were included as controls. Mean age was 48.0 and body mass index was 27.3 for women with PCOS. The majority of participants were white (72%). There was no difference between PCOS and control women for levels of follicle-stimulating hormone, testosterone, progesterone, or estradiol. Multivariate logistic regression demonstrated that PCOS was not associated with increased odds of hot flash incidence. Smoking was the only variable associated with experiencing hot flashes (odds ratio 2.0, 95% confidence interval 1.05-3.98). A history of PCOS was not associated with increased hot flash symptoms during the midlife period. Additional research should continue to investigate the health and quality of life associated with a history of PCOS in the aging population.

Social cohesion and the smoking behaviors of adults living with children.

PubMed

Alcalá, Héctor E; Sharif, Mienah Z; Albert, Stephanie L

2016-02-01

The smoking behavior of adults can negatively impact children through exposure to environmental tobacco smoke and by modeling this unhealthy behavior. Little research has examined the role of the social environment in smoking behaviors of adults living with children. The present study specifically analyzed the relationship between social cohesion and smoking behaviors of adults living with children. Data from the 2009 California Health Interview Survey, a random-digit dial cross-sectional survey of California Adults, were used. Adults living with children reported their levels of social cohesion and smoking behaviors (N=13,978). Logistic regression models were used to predict odds of being a current smoker or living in a household in which smoking was allowed, from social cohesion. Overall, 13% of the sample was current smokers and 3.74% lived in households in which smoking was allowed. Logistic regression models showed that each one-unit increase in social cohesion is associated with reduced odds of being a current smoker (AOR=0.92; 95% CI=0.85-0.99) and reduced odds of living in a household in which smoking is allowed (AOR=0.84; 95% CI=0.75-0.93), after controlling for sociodemographic characteristics. Among adults living with children, higher social cohesion is associated with a lower likelihood of both being and smoker and living in a home where smoking is allowed. Thus, future research is needed to better understand mechanisms that explain the relationship between social cohesion and smoking-related behavior in order to prevent smoking-related health consequences and smoking initiation among children and adults. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unstimulated whole salivary flow rate and anxiolytics intake are independently associated with oral Candida infection in patients with oral lichen planus.

PubMed

Bokor-Bratic, Marija; Cankovic, Milos; Dragnic, Natasa

2013-10-01

Many factors have been proposed to influence oral infection with yeast. The aim of this study was to determine the prevalence of oral yeasts in oral lichen planus (OLP) patients and control subjects, and to perform a multiple logistic regression analysis to identify factors that influence oral Candida infection in OLP patients. In this cross-sectional study, 90 new patients with OLP and 90 sex- and age-matched control subjects with no mucosal lesions were interviewed about their health status, use of medication, and smoking and alcohol habits. Swab and unstimulated whole saliva samples were collected and salivary pH was measured. A positive Candida culture was more prevalent among OLP patients (48.9%) than among control subjects (26.7%). Candida albicans was the most frequently isolated species in both groups. By logistic regression analysis, unstimulated whole salivary flow rates of 0.11-0.24 ml min(-1) (OR = 5.90) and 0.25-0.32 ml min(-1) (OR = 3.51) and benzodiazepine anxiolytics intake (OR = 8.30) were independently associated with the presence of Candida among OLP patients. Age, denture wearing, levels of dentition, decreased salivary pH, antihypertensive drugs, and alcohol consumption were not associated with oral Candida infection in OLP patients. The results indicate that data on benzodiazepine anxiolytics intake and evaluation of unstimulated whole salivary flow rate should be considered as part of the clinical evaluation to identify OLP patients at risk for Candida infection. © 2013 Eur J Oral Sci.

Association Between Inpatient Sleep Loss and Hyperglycemia of Hospitalization

PubMed Central

DePietro, Regina H.; Knutson, Kristen L.; Spampinato, Lisa; Anderson, Samantha L.; Meltzer, David O.; Van Cauter, Eve

2017-01-01

OBJECTIVE To determine whether inpatient sleep duration and efficiency are associated with a greater risk of hyperglycemia in hospitalized patients with and without diabetes. RESEARCH DESIGN AND METHODS In this retrospective analysis of a prospective cohort study, medical inpatients ≥50 years of age were interviewed, and their charts were reviewed to obtain demographic data and diagnosis. Using World Health Organization criteria, patients were categorized as having normal blood glucose, impaired fasting blood glucose, or hyperglycemia based on morning glucose from the electronic health record. Wrist actigraphy measured sleep. Multivariable ordinal logistic regression models, controlling for subject random effects, tested the association between inpatient sleep duration and proportional odds of hyperglycemia versus impaired fasting blood glucose or impaired fasting blood glucose versus normal blood glucose in hospitalized adults. RESULTS A total of 212 patients (60% female and 74% African American) were enrolled. Roughly one-third (73, 34%) had diabetes. Objective inpatient sleep measures did not differ between patients with or without diabetes. In ordinal logistic regression models, each additional hour of in-hospital sleep was associated with an 11% (odds ratio 0.89 [95% CI 0.80, 0.99]; P = 0.043) lower proportional odds of a higher glucose category the next morning (hyperglycemia vs. elevated and elevated vs. normal). Every 10% increase in sleep efficiency was associated with an 18% lower proportional odds of a higher glucose category (odds ratio 0.82 [95% CI 0.74, 0.89]; P < 0.001). CONCLUSIONS Among medical inpatients, both shorter sleep duration and worse sleep efficiency were independently associated with greater proportional odds of hyperglycemia and impaired fasting glucose. PMID:27903614

Uncontrolled diabetes mellitus: prevalence and risk factors among people with type 2 diabetes mellitus in an Urban District of Karachi, Pakistan.

PubMed

Siddiqui, Fahad Javaid; Avan, Bilal Iqbal; Mahmud, Sadia; Nanan, Debra J; Jabbar, Abdul; Assam, Pryseley Nkouibert

2015-01-01

This study aimed to explore the prevalence of, and factors associated with, uncontrolled diabetes mellitus (UDM) in a community setting in Pakistan. A single-center, cross-sectional study, conducted in a community-based specialized care center (SCC) for diabetes in District Central Karachi, in 2003, registered 452 type 2 DM participants, tested for HbA1c and interviewed face-to-face for other information. Logistic regression analysis was conducted to identify factors associated with UDM. Prevalence of UDM among diabetes patients was found to be 38.9% (95% CI: 34.4-43.4%). Multivariable logistic regression model analysis indicated that age <50 years (OR: 1.9; 95% CI: 1.2-2.9), being diagnosed in a hospital (vs. a clinic) (OR: 1.8; 95% CI: 1.1-2.8), diabetes information from a doctor or nurse only (vs. multiple sources) (OR: 1.8; 95% CI: 1.2-2.9), higher monthly treatment cost (OR: 1.3; 95% CI: 1.1-1.6; for every extra 500 PKR), and higher consumption of tea (OR: 1.5; 95% CI: 1.0-2.2; for every 2 extra cups) were independently associated with UDM. The prevalence of UDM was approximately 39% among persons with type 2 diabetes visiting a community based SCC for diabetes. Modifiable risk factors such as sources of diabetes information and black tea consumption can be considered as potential targets of interventions in Karachi. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Potential serum biomarkers from a metabolomics study of autism

PubMed Central

Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

2016-01-01

Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

Narcissistic Personality Disorder and suicidal behavior in mood disorders.

PubMed

Coleman, Daniel; Lawrence, Ryan; Parekh, Amrita; Galfalvy, Hanga; Blasco-Fontecilla, Hilario; Brent, David A; Mann, J John; Baca-Garcia, Enrique; Oquendo, Maria A

2017-02-01

The relationship of Narcissistic Personality Disorder (NPD) to suicidal behavior is understudied. The modest body of existing research suggests that NPD is protective against low-lethality suicide attempts, but is associated with high lethality attempts. Mood-disordered patients (N = 657) received structured interviews including Axis I and II diagnosis and standardized clinical measures. Following chi-square and t-tests, a logistical regression model was constructed to identify predictors of suicide attempt. While there was no bivariate relationship of NPD on suicide attempt, in the logistic regression patients with NPD were 2.4 times less likely to make a suicide attempt (OR = 0.41; 95% CI = 0.19 - 0.88; p < 0.05), compared with non-NPD patients and controlling for possible confounding variables. NPD was not associated with attempt lethality. NPD patients were more likely to be male, to have a substance use disorder, and to have high aggression and hostility scores. Limitations include that the sample consists of only mood-disordered patients, a modest sample size of NPD, and the data are cross-sectional. The multivariate protective effect of NPD on suicide attempt is consistent with most previous research. The lower impulsivity of NPD patients and less severe personality pathology relative to other personality disorders may contribute to this effect. No relationship of NPD to attempt lethality was found, contradicting other research, but perhaps reflecting differences between study samples. Future studies should oversample NPD patients and include suicide death as an outcome. Clinical implications include discussion of individualized suicide risk assessment with NPD patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Anxiety and Depression among Breast Cancer Patients in an Urban Setting in Malaysia.

PubMed

Hassan, Mohd Rohaizat; Shah, Shamsul Azhar; Ghazi, Hasanain Faisal; Mohd Mujar, Noor Mastura; Samsuri, Mohd Fadhli; Baharom, Nizam

2015-01-01

Breast cancer is one of the most feared diseases among women and it could induce the development of psychological disorders like anxiety and depression. An assessment was here performed of the status and to determine contributory factors. A cross-sectional study was conducted among breast cancer patients at University Kebangsaan Malaysia Medical Center (UKMMC), Kuala Lumpur. A total of 205 patients who were diagnosed between 2007 until 2010 were interviewed using the questionnaires of Hospital Anxiety and Depression (HADS). The associated factors investigated concerned socio-demographics, socio economic background and the cancer status. Descriptive analysis, chi-squared tests and logistic regression were used for the statistical test analysis. The prevalence of anxiety was 31.7% (n=65 ) and of depression was 22.0% (n=45) among the breast cancer patients. Age group (p= 0.032), monthly income (p=0.015) and number of visits per month (p=0.007) were significantly associated with anxiety. For depression, marital status (p=0.012), accompanying person (p=0.041), financial support (p-0.007) and felt burden (p=0.038) were significantly associated. In binary logistic regression, those in the younger age group were low monthly income were 2 times more likely to be associated with anxiety. Having less financial support and being single were 3 and 4 times more likely to be associated with depression. In management of breast cancer patients, more care or support should be given to the young and low socio economic status as they are at high risk of anxiety and depression.

Association of Sociodemographic Factors, Smoking-Related Beliefs, and Smoking Restrictions With Intention to Quit Smoking in Korean Adults: Findings From the ITC Korea Survey

PubMed Central

Myung, Seung-Kwon; Seo, Hong Gwan; Cheong, Yoo-Seock; Park, Sohee; Lee, Wonkyong B; Fong, Geoffrey T

2012-01-01

Background Few studies have reported the factors associated with intention to quit smoking among Korean adult smokers. This study aimed to examine sociodemographic characteristics, smoking-related beliefs, and smoking-restriction variables associated with intention to quit smoking among Korean adult smokers. Methods We used data from the International Tobacco Control Korea Survey, which was conducted from November through December 2005 by using random-digit dialing and computer-assisted telephone interviewing of male and female smokers aged 19 years or older in 16 metropolitan areas and provinces of Korea. We performed univariate analysis and multiple logistic regression analysis to identify predictors of intention to quit. Results A total of 995 respondents were included in the final analysis. Of those, 74.9% (n = 745) intended to quit smoking. In univariate analyses, smokers with an intention to quit were younger, smoked fewer cigarettes per day, had a higher annual income, were more educated, were more likely to have a religious affiliation, drank less alcohol per week, were less likely to have self-exempting beliefs, and were more likely to have self-efficacy beliefs regarding quitting, to believe that smoking had damaged their health, and to report that smoking was never allowed anywhere in their home. In multiple logistic regression analysis, higher education level, having a religious affiliation, and a higher self-efficacy regarding quitting were significantly associated with intention to quit. Conclusions Sociodemographic factors, smoking-related beliefs, and smoking restrictions at home were associated with intention to quit smoking among Korean adults. PMID:22186157

Self-report of gingival problems and periodontitis in indigenous and non-indigenous populations in Chiapas, Mexico.

PubMed

García-Pérez, Álvaro; Borges-Yáñez, Socorro Aída; Jiménez-Corona, Aida; Jiménez-Corona, María Eugenia; Ponce-de-León, Samuel

2016-04-01

To estimate the prevalence of self-reported gingival and periodontal conditions and their association with smoking, oral hygiene, indigenous origin, diabetes and location (urban or rural) in indigenous and non-indigenous adults in Chiapas, Mexico. A cross-sectional study of 1,749 persons, ≥20 years of age, living in four rural and four urban marginal localities in Comitán (Chiapas, México). The variables investigated were: age; sex; indigenous origin; oral hygiene; halitosis; chewing ability; gingival conditions; periodontitis; smoking; alcoholism; diabetes; and location. Bivariate analysis and a logistic regression model were used to identify the association of periodontitis with the independent variables. In total, 762 (43.6%) indigenous and 987 (56.4%) non-indigenous persons were interviewed. Their mean age was 41 ± 14 years, 66.7% were women and 43.8% lived in rural locations. Gingival problems were reported by 68.5% and periodontitis by 8.7%. In total, 17.9% had used dental services during the previous year, 28.7% wore a removable partial or a complete dental prosthesis, 63.7% had lost at least one tooth, the prevalence of diabetes was 9.2% and the prevalence of smoking was 12.2%. The logistic regression model showed that age, diabetes and the interaction between rural location and indigenous origin were associated with the presence of periodontitis. Indigenous people living in rural areas are more likely to have periodontitis. It is necessary to promote oral health practices in indigenous and marginalised populations with a focus on community-oriented primary care. © 2016 FDI World Dental Federation.

The relationship between quality of work life and location of cross-training among obstetric nurses in urban northeastern Ontario, Canada: A population-based cross sectional study.

PubMed

Nowrouzi, Behdin; Lightfoot, Nancy; Carter, Lorraine; Larivière, Michel; Rukholm, Ellen; Schinke, Robert; Belanger-Gardner, Diane

2015-01-01

The purpose of this mixed methods study was to examine the quality of work life of registered nurses working in obstetrics at 4 hospitals in northeastern Ontario and explore demographic and occupational factors related to nurses' quality of work life (QWL). A stratified random sample of registered nurses (N = 111) selected from the 138 eligible registered nurses (80.4%) of staff in the labor, delivery, recovery, and postpartum areas at the 4 hospitals participated. Logistic regression analyses were used to consider QWL in relation to the following: 1) demographic factors, and 2) stress, employment status and educational attainment. In the logistic regression model, the odds of a higher quality of work life for nurses who were cross trained (nurses who can work across all areas of obstetrical care) were estimated to be 3.82 (odds ratio = 3.82, 95% confidence interval: 1.01-14.5) times the odds of a higher quality of work life for nurses who were not cross trained. This study highlights a relationship between quality of work life and associated factors including location of cross-training among obstetrical nurses in northeastern Ontario. These findings are supported by the qualitative interviews that examine in depth their relationship to QWL. Given the limited number of employment opportunities in the rural and remote regions, it is paramount that employers and employees work closely together in creating positive environments that promote nurses' QWL. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Social Cohesion and the Smoking Behaviors of Adults Living with Children

PubMed Central

Sharif, Mienah Z.; Albert, Stephanie L.

2015-01-01

Introduction The smoking behavior of adults can negatively impact children through exposure to environmental tobacco smoke and by modeling this unhealthy behavior. Little research has examined the role of the social environment in smoking behaviors of adults living with children. The present study specifically analyzed the relationship between social cohesion and smoking behaviors of adults living with children. Methods Data from the 2009 California Health Interview Survey, a random-digit dial cross-sectional survey of California Adults, were used. Adults living with children reported their levels of social cohesion and smoking behaviors (N=13,978). Logistic regression models were used to predict odds of being a current smoker or living in a household in which smoking was allowed, from social cohesion. Results Overall, 13% of the sample was current smokers and 3.74% lived in households in which smoking was allowed. Logistic regression models showed that each one-unit increase in social cohesion is associated with reduced odds of being a current smoker (AOR= 0.92; 95% CI= 0.85–0.99) and reduced odds of living in a household in which smoking is allowed (AOR= 0.84; 95% CI= 0.75–0.93), after controlling for sociodemographic characteristics. Conclusions Among adults living with children, higher social cohesion is associated with a lower likelihood of both being and smoker and living in a home where smoking is allowed. Thus, future research is needed to better understand mechanisms that explain the relationship between social cohesion and smoking-related behavior in order to prevent smoking-related health consequences and smoking initiation among children and adults. PMID:26562680

Association of sociodemographic factors, smoking-related beliefs, and smoking restrictions with intention to quit smoking in Korean adults: findings from the ITC Korea Survey.

PubMed

Myung, Seung-Kwon; Seo, Hong Gwan; Cheong, Yoo-Seock; Park, Sohee; Lee, Wonkyong B; Fong, Geoffrey T

2012-01-01

Few studies have reported the factors associated with intention to quit smoking among Korean adult smokers. This study aimed to examine sociodemographic characteristics, smoking-related beliefs, and smoking-restriction variables associated with intention to quit smoking among Korean adult smokers. We used data from the International Tobacco Control Korea Survey, which was conducted from November through December 2005 by using random-digit dialing and computer-assisted telephone interviewing of male and female smokers aged 19 years or older in 16 metropolitan areas and provinces of Korea. We performed univariate analysis and multiple logistic regression analysis to identify predictors of intention to quit. A total of 995 respondents were included in the final analysis. Of those, 74.9% (n = 745) intended to quit smoking. In univariate analyses, smokers with an intention to quit were younger, smoked fewer cigarettes per day, had a higher annual income, were more educated, were more likely to have a religious affiliation, drank less alcohol per week, were less likely to have self-exempting beliefs, and were more likely to have self-efficacy beliefs regarding quitting, to believe that smoking had damaged their health, and to report that smoking was never allowed anywhere in their home. In multiple logistic regression analysis, higher education level, having a religious affiliation, and a higher self-efficacy regarding quitting were significantly associated with intention to quit. Sociodemographic factors, smoking-related beliefs, and smoking restrictions at home were associated with intention to quit smoking among Korean adults.

Developing a Referral Protocol for Community-Based Occupational Therapy Services in Taiwan: A Logistic Regression Analysis

PubMed Central

Chang, Ling-Hui; Tsai, Athena Yi-Jung; Huang, Wen-Ni

2016-01-01

Because resources for long-term care services are limited, timely and appropriate referral for rehabilitation services is critical for optimizing clients’ functions and successfully integrating them into the community. We investigated which client characteristics are most relevant in predicting Taiwan’s community-based occupational therapy (OT) service referral based on experts’ beliefs. Data were collected in face-to-face interviews using the Multidimensional Assessment Instrument (MDAI). Community-dwelling participants (n = 221) ≥ 18 years old who reported disabilities in the previous National Survey of Long-term Care Needs in Taiwan were enrolled. The standard for referral was the judgment and agreement of two experienced occupational therapists who reviewed the results of the MDAI. Logistic regressions and Generalized Additive Models were used for analysis. Two predictive models were proposed, one using basic activities of daily living (BADLs) and one using instrumental ADLs (IADLs). Dementia, psychiatric disorders, cognitive impairment, joint range-of-motion limitations, fear of falling, behavioral or emotional problems, expressive deficits (in the BADL-based model), and limitations in IADLs or BADLs were significantly correlated with the need for referral. Both models showed high area under the curve (AUC) values on receiver operating curve testing (AUC = 0.977 and 0.972, respectively). The probability of being referred for community OT services was calculated using the referral algorithm. The referral protocol facilitated communication between healthcare professionals to make appropriate decisions for OT referrals. The methods and findings should be useful for developing referral protocols for other long-term care services. PMID:26863544

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

Developing a Referral Protocol for Community-Based Occupational Therapy Services in Taiwan: A Logistic Regression Analysis.

PubMed

Mao, Hui-Fen; Chang, Ling-Hui; Tsai, Athena Yi-Jung; Huang, Wen-Ni; Wang, Jye

2016-01-01

Because resources for long-term care services are limited, timely and appropriate referral for rehabilitation services is critical for optimizing clients' functions and successfully integrating them into the community. We investigated which client characteristics are most relevant in predicting Taiwan's community-based occupational therapy (OT) service referral based on experts' beliefs. Data were collected in face-to-face interviews using the Multidimensional Assessment Instrument (MDAI). Community-dwelling participants (n = 221) ≥ 18 years old who reported disabilities in the previous National Survey of Long-term Care Needs in Taiwan were enrolled. The standard for referral was the judgment and agreement of two experienced occupational therapists who reviewed the results of the MDAI. Logistic regressions and Generalized Additive Models were used for analysis. Two predictive models were proposed, one using basic activities of daily living (BADLs) and one using instrumental ADLs (IADLs). Dementia, psychiatric disorders, cognitive impairment, joint range-of-motion limitations, fear of falling, behavioral or emotional problems, expressive deficits (in the BADL-based model), and limitations in IADLs or BADLs were significantly correlated with the need for referral. Both models showed high area under the curve (AUC) values on receiver operating curve testing (AUC = 0.977 and 0.972, respectively). The probability of being referred for community OT services was calculated using the referral algorithm. The referral protocol facilitated communication between healthcare professionals to make appropriate decisions for OT referrals. The methods and findings should be useful for developing referral protocols for other long-term care services.

The Association of Low Parental Monitoring With Early Substance Use in European American and African American Adolescent Girls

PubMed Central

Blustein, Erica C.; Munn-Chernoff, Melissa A.; Grant, Julia D.; Sartor, Carolyn E.; Waldron, Mary; Bucholz, Kathleen K.; Madden, Pamela A. F.; Heath, Andrew C.

2015-01-01

Objective: Research indicates that low parental monitoring increases the risk for early substance use. Because low parental monitoring tends to co-occur with other familial and neighborhood factors, the specificity of the association is challenging to establish. Using logistic regression and propensity score analyses, we examined associations between low parental monitoring and early substance use in European American (EA) and African American (AA) girls, controlling for risk factors associated with low parental monitoring. Method: Participants were 3,133 EA and 523 AA girls from the Missouri Adolescent Female Twin Study with data on parental monitoring assessed via self-report questionnaire, and with ages at first use of alcohol, tobacco, and cannabis queried in at least one of three diagnostic interviews (median ages = 15, 22, and 24 years). Results: The rate of early alcohol use was greater in EA than AA girls, whereas the proportion of AA girls reporting low parental monitoring was higher than in EA girls. EA girls who experienced low parental monitoring were at elevated risk for early alcohol, tobacco, and cannabis use, findings supported in both logistic regression and propensity score analyses. Evidence regarding associations between low parental monitoring and risk for early substance use was less definitive forAA girls. Conclusions: Findings highlight the role of parental monitoring in modifying risk for early substance use in EA girls. However, we know little regarding the unique effects, if any, of low parental monitoring on the timing of first substance use in AA girls. PMID:26562593

Inequality in the hepatitis B awareness level in rural residents from 7 provinces in China.

PubMed

Zheng, Juan; Li, Quan; Wang, Jian; Zhang, Guojie; Wangen, Knut R

2017-05-04

The hepatitis B (HB) awareness level is an important factor affecting the rates of HB virus vaccination. To better understand income-related inequalities in the HB awareness level, it is imperative to identify the sources of inequalities and assess the contribution rates of these influential factors. This study analyzed the unequal distribution of the HB awareness level and the contributions of various influential factors. We performed a cross-sectional household survey with questionnaire-based, face-to-face interviews in 7 Chinese provinces. Responses from 7271 respondents were used in this analysis. Multinomial logistic regression was used for the analysis of contributing factors, and the concentration index was used as a measure of HB awareness inequalities. The HB awareness level varied across participants with different characteristics. Multinomial logistic regression of the explanatory factors of the HB awareness level showed that several estimated coefficients and relative risk ratios were statistically significant for middle- and high-level awareness, except for sex, occupation, and household income. The concentration index of the HB knowledge score was 0.140, indicating inequality gradients disadvantageous to the poor. The contribution rate of socioeconomic factors was the largest (60.8%), followed by demographic characteristics (29.0%) and geographic factors (4.3%). Demographic, socioeconomic, and geographic factors are associated with the HB awareness inequality. Therefore, to reduce inequality, HB-related health education targeting individuals with low socioeconomic status should be performed. Less-developed provinces, especially with high proportions of poor residents, warrant particular attention. Our findings may be beneficial to improve the HB virus vaccination rate for individuals with low socioeconomic status.

Determinants of use of health facility for childbirth in rural Hadiya zone, Southern Ethiopia.

PubMed

Asseffa, Netsanet Abera; Bukola, Fawole; Ayodele, Arowojolu

2016-11-16

Maternal mortality remains a major global public health concern despite many international efforts. Facility-based childbirth increases access to appropriate skilled attendance and emergency obstetric care services as the vast majority of obstetric complications occur during delivery. The purpose of the study was to determine the proportion of facility delivery and assess factors influencing utilization of health facility for childbirth. A cross-sectional study was conducted in two rural districts of Hadiya zone, southern Ethiopia. Participants who delivered within three years of the survey were selected by stratified random sampling. Trained interviewers administered a pre-tested semi-structured questionnaire. We employed bivariate analysis and logistic regression to identify determinants of facility-based delivery. Data from 751 participants showed that 26.9% of deliveries were attended in health facilities. In bivariate analysis, maternal age, education, husband's level of education, possession of radio, antenatal care, place of recent ANC attended, planned pregnancy, wealth quintile, parity, birth preparedness and complication readiness, being a model family and distance from the nearest health facility were associated with facility delivery. On multiple logistic regression, age, educational status, antenatal care, distance from the nearest health facility, wealth quintile, being a model family, planned pregnancy and place of recent ANC attended were the determinants of facility-based childbirth. Efforts to improve institutional deliveries in the region must strengthen initiatives that promote female education, opportunities for wealth creation, female empowerment and increased uptake of family planning among others. Service related barriers and cultural influences on the use of health facility for childbirth require further evaluation.

Difficulties Reported by Hiv-Infected Patients Using Antiretroviral Therapy in Brazil

PubMed Central

Guimarães, Mark Drew Crosland; Rocha, Gustavo Machado; Campos, Lorenza Nogueira; de Freitas, Felipe Melo Teixeira; Gualberto, Felipe Augusto Souza; Teixeira, Ramiro d’Ávila Rivelli; de Castilho, Fábio Morato

2008-01-01

OBJECTIVE To describe the degree of difficulty that HIV-infected patients have with therapy treatment. INTRODUCTION Patients’ perceptions about their treatment are a determinant factor for improved adherence and a better quality of life. METHODS Two cross-sectional analyses were conducted in public AIDS referral centers in Brazil among patients initiating treatment. Patients interviewed at baseline, after one month, and after seven months following the beginning of treatment were asked to classify and justify the degree of difficulty with treatment. Logistic regression was used for analysis. RESULTS Among 406 patients initiating treatment, 350 (86.2%) and 209 (51.5%) returned for their first and third visits, respectively. Treatment perceptions ranged from medium to very difficult for 51.4% and 37.3% on the first and third visits, respectively. The main difficulties reported were adverse reactions to the medication and scheduling. A separate logistic regression indicated that the HIV-seropositive status disclosure, symptoms of anxiety, absence of psychotherapy, higher CD4+ cell count (> 200/mm3) and high (> 4) adverse reaction count reported were independently associated with the degree of difficulty in the first visit, while CDC clinical category A, pill burden (> 7 pills), use of other medications, high (> 4) adverse reaction count reported and low understanding of medical orientation showed independent association for the third visit. CONCLUSIONS A significant level of difficulty was observed with treatment. Our analyses suggest the need for early assessment of difficulties with treatment, highlighting the importance of modifiable factors that may contribute to better adherence to the treatment protocol. PMID:18438569

Applications of statistics to medical science, III. Correlation and regression.

PubMed

Watanabe, Hiroshi

2012-01-01

In this third part of a series surveying medical statistics, the concepts of correlation and regression are reviewed. In particular, methods of linear regression and logistic regression are discussed. Arguments related to survival analysis will be made in a subsequent paper.

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Stein, Joshua D; Musch, David C

2013-12-21

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification. Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation. The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression. A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

Computing group cardinality constraint solutions for logistic regression problems.

PubMed

Zhang, Yong; Kwon, Dongjin; Pohl, Kilian M

2017-01-01

We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints. Copyright © 2016 Elsevier B.V. All rights reserved.

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

PubMed

Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

2016-10-01

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery.

PubMed

Engoren, Milo; Habib, Robert H; Dooner, John J; Schwann, Thomas A

2013-08-01

As many as 14 % of patients undergoing coronary artery bypass surgery are readmitted within 30 days. Readmission is usually the result of morbidity and may lead to death. The purpose of this study is to develop and compare statistical and genetic programming models to predict readmission. Patients were divided into separate Construction and Validation populations. Using 88 variables, logistic regression, genetic programs, and artificial neural nets were used to develop predictive models. Models were first constructed and tested on the Construction populations, then validated on the Validation population. Areas under the receiver operator characteristic curves (AU ROC) were used to compare the models. Two hundred and two patients (7.6 %) in the 2,644 patient Construction group and 216 (8.0 %) of the 2,711 patient Validation group were re-admitted within 30 days of CABG surgery. Logistic regression predicted readmission with AU ROC = .675 ± .021 in the Construction group. Genetic programs significantly improved the accuracy, AU ROC = .767 ± .001, p < .001). Artificial neural nets were less accurate with AU ROC = 0.597 ± .001 in the Construction group. Predictive accuracy of all three techniques fell in the Validation group. However, the accuracy of genetic programming (AU ROC = .654 ± .001) was still trivially but statistically non-significantly better than that of the logistic regression (AU ROC = .644 ± .020, p = .61). Genetic programming and logistic regression provide alternative methods to predict readmission that are similarly accurate.

Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings.

PubMed

Eken, Cenker; Bilge, Ugur; Kartal, Mutlu; Eray, Oktay

2009-06-03

Logistic regression is the most common statistical model for processing multivariate data in the medical literature. Artificial intelligence models like an artificial neural network (ANN) and genetic algorithm (GA) may also be useful to interpret medical data. The purpose of this study was to perform artificial intelligence models on a medical data sheet and compare to logistic regression. ANN, GA, and logistic regression analysis were carried out on a data sheet of a previously published article regarding patients presenting to an emergency department with flank pain suspicious for renal colic. The study population was composed of 227 patients: 176 patients had a diagnosis of urinary stone, while 51 ultimately had no calculus. The GA found two decision rules in predicting urinary stones. Rule 1 consisted of being male, pain not spreading to back, and no fever. In rule 2, pelvicaliceal dilatation on bedside ultrasonography replaced no fever. ANN, GA rule 1, GA rule 2, and logistic regression had a sensitivity of 94.9, 67.6, 56.8, and 95.5%, a specificity of 78.4, 76.47, 86.3, and 47.1%, a positive likelihood ratio of 4.4, 2.9, 4.1, and 1.8, and a negative likelihood ratio of 0.06, 0.42, 0.5, and 0.09, respectively. The area under the curve was found to be 0.867, 0.720, 0.715, and 0.713 for all applications, respectively. Data mining techniques such as ANN and GA can be used for predicting renal colic in emergency settings and to constitute clinical decision rules. They may be an alternative to conventional multivariate analysis applications used in biostatistics.

Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

NASA Astrophysics Data System (ADS)

Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

2006-11-01

As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

[Mining analysis and experience summary for chronic atrophic gastritis cases treated by Professor LIU Feng-bin].

PubMed

Hou, Zheng-kun; Liu, Feng-bin; Li, Pei-wu; Zhuang, Kun-hai

2015-06-01

To summarize Professor LIU Feng-bin's clinical experience and theoretical thoughts on chronic atrophic gastritis (CAG), the study group designed a retrospective study on his case series and expert interview. First of all, the data of CAG patients treated in the First Affiliated Hospital of Guangzhou University of Chinese Medicine between 2009 and 2013, e. g. herbs, diseases, syndrome type, prescription amount and number of herbs, was collected and processed. The statistical description and binary logistic regression were used to determined the syndrome type, initial basic remedy and modification. During the statistics, a complete and sub-group analysis was performed simultaneously. After the expert interview, the syndrome type and medication were finalized. As a result, a total of 228 CAG patients aged at (50.30 ± 10.18) were collected, including 151 males (66.23%). Of them, the TCM diagnosis and syndrome type were extracted from the information of 157 patients, including 115 cases with gastric stuffiness, 23 cases with gastric pain, 19 missing cases, 2 cases with spleen-stomach weakness syndrome, 57 cases with spleen deficiency and dampness-heat syndrome, 18 cases with spleen-stomach disharmony syndrome, 23 cases with syndrome of liver depression syndrome, 21 cases with liver qi invading stomach syndrome and 26 qi and yin deficiency syndrome, respectively. All of the 228 patients used totally 104 herbs, while the subgroups with 157 patients used 94 herbs. The most frequently used 15 herbs used in each groups were analyzed to determine the initial basic remedy and modification. Subsequently, based on the information of the sub-groups with 157 patients, with the syndrome type as the dependent variable, the logistic regression analysis was made on the most frequently used 32 herbs, in order to determined the modification in herbs for different syndrome types. After experts reviewed and modified, they believed the main causes of CAG were dietary irregularities, moodiness and weak constitution; the pathogenesis of CAG was spleen deficiency with qi stagnation, heat depression and blood stasis in the stomach meridian. The above six syndrome types and 12 herbs were determined, including Pseudostellariae Radix, Poria, Atractylodismacrocephalae Rhizoma, Glycyrrhizae Radix et Rhizoma, Fritillariae Thunbergii Bulbus, Sepiae Endoconcha, Arecae Pericarpium, Aurantii Fructus, Perillae Caulis, Herba Hedyotis Diffusae, Scutellariae Barbatae Herba, Curcumae Rhizoma. This study summarized Professor LIU Feng-bin's clinical experience and theoretical thoughts of chronic atrophic gastritis based on clinical practice data and expert interview, with a rigorous design and good scientificity and practicability.

New robust statistical procedures for the polytomous logistic regression models.

PubMed

Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

2018-05-17

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.

Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States

USGS Publications Warehouse

Staley, Dennis M.; Negri, Jacquelyn A.; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2016-06-30

Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

EXpectation Propagation LOgistic REgRession (EXPLORER): distributed privacy-preserving online model learning.

PubMed

Wang, Shuang; Jiang, Xiaoqian; Wu, Yuan; Cui, Lijuan; Cheng, Samuel; Ohno-Machado, Lucila

2013-06-01

We developed an EXpectation Propagation LOgistic REgRession (EXPLORER) model for distributed privacy-preserving online learning. The proposed framework provides a high level guarantee for protecting sensitive information, since the information exchanged between the server and the client is the encrypted posterior distribution of coefficients. Through experimental results, EXPLORER shows the same performance (e.g., discrimination, calibration, feature selection, etc.) as the traditional frequentist logistic regression model, but provides more flexibility in model updating. That is, EXPLORER can be updated one point at a time rather than having to retrain the entire data set when new observations are recorded. The proposed EXPLORER supports asynchronized communication, which relieves the participants from coordinating with one another, and prevents service breakdown from the absence of participants or interrupted communications. Copyright © 2013 Elsevier Inc. All rights reserved.

A computational approach to compare regression modelling strategies in prediction research.

PubMed

Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

2016-08-25

It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Medical Logistics in a New Threater of Operations: An Operation Iraqi Freedom Case Study

DTIC Science & Technology

2006-05-25

Illinois Press, 2001. Fry, William , Colonel, Interview by author on 23 January 2006. Fort Detrick, MD. Fuson, Jack C . Transportation and Logistics...PERSON ABSTRACT OF PAGES REPORT b. ABSTRACT c . THIS PAGE 19B. TELEPHONE. NUMBER (Include area code) (U) 72 (913) 758-3300 (U) (U) (U) Standard...Colonel George C . Thorpe wrote in 1917 in his groundbreaking study of logistics, Pure Logistics: The Science of War Preparation, “history repeats

Science of Test Research Consortium: Year Two Final Report

DTIC Science & Technology

2012-10-02

July 2012. Analysis of an Intervention for Small Unmanned Aerial System ( SUAS ) Accidents, submitted to Quality Engineering, LQEN-2012-0056. Stone... Systems Engineering. Wolf, S. E., R. R. Hill, and J. J. Pignatiello. June 2012. Using Neural Networks and Logistic Regression to Model Small Unmanned ...Human Retina. 6. Wolf, S. E. March 2012. Modeling Small Unmanned Aerial System Mishaps using Logistic Regression and Artificial Neural Networks. 7

Binary Logistic Regression Analysis for Detecting Differential Item Functioning: Effectiveness of R[superscript 2] and Delta Log Odds Ratio Effect Size Measures

ERIC Educational Resources Information Center

Hidalgo, Mª Dolores; Gómez-Benito, Juana; Zumbo, Bruno D.

2014-01-01

The authors analyze the effectiveness of the R[superscript 2] and delta log odds ratio effect size measures when using logistic regression analysis to detect differential item functioning (DIF) in dichotomous items. A simulation study was carried out, and the Type I error rate and power estimates under conditions in which only statistical testing…

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...

Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model.

PubMed

Mohammed, Mohammed A; Manktelow, Bradley N; Hofer, Timothy P

2016-04-01

There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable. © The Author(s) 2012.

Three methods to construct predictive models using logistic regression and likelihood ratios to facilitate adjustment for pretest probability give similar results.

PubMed

Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les

2008-01-01

To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.

A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: ordinal logistic regression, Rasch analysis and the Mantel chi-square procedure.

PubMed

Cameron, Isobel M; Scott, Neil W; Adler, Mats; Reid, Ian C

2014-12-01

It is important for clinical practice and research that measurement scales of well-being and quality of life exhibit only minimal differential item functioning (DIF). DIF occurs where different groups of people endorse items in a scale to different extents after being matched by the intended scale attribute. We investigate the equivalence or otherwise of common methods of assessing DIF. Three methods of measuring age- and sex-related DIF (ordinal logistic regression, Rasch analysis and Mantel χ(2) procedure) were applied to Hospital Anxiety Depression Scale (HADS) data pertaining to a sample of 1,068 patients consulting primary care practitioners. Three items were flagged by all three approaches as having either age- or sex-related DIF with a consistent direction of effect; a further three items identified did not meet stricter criteria for important DIF using at least one method. When applying strict criteria for significant DIF, ordinal logistic regression was slightly less sensitive. Ordinal logistic regression, Rasch analysis and contingency table methods yielded consistent results when identifying DIF in the HADS depression and HADS anxiety scales. Regardless of methods applied, investigators should use a combination of statistical significance, magnitude of the DIF effect and investigator judgement when interpreting the results.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Factors Affecting Employment Among Informal Caregivers Assisting People with Multiple Sclerosis

PubMed Central

Huang, Chunfeng; Zheng, Zhida

2013-01-01

The objective of this study was to identify characteristics of informal caregivers, caregiving, and the people with multiple sclerosis (MS) receiving assistance that are associated with reduced caregiver employment. Data were collected during telephone interviews with 530 MS caregivers, including 215 employed caregivers, with these survey data analyzed using logistic regression. Poorer cognitive ability by the care recipient to make decisions about daily tasks and more caregiving hours per week predicted reduced caregiver employment. Better physical health domains of caregiver quality of life were associated with significantly lower odds of reduced employment. Health professionals treating informal caregivers, as well as those treating people with MS, need to be aware of respite, support, and intervention programs available to MS caregivers and refer them to these programs, which could reduce the negative impact of caregiving on employment. PMID:24453784

Lay Consultations in Heart Failure Symptom Evaluation.

PubMed

Reeder, Katherine M; Sims, Jessica L; Ercole, Patrick M; Shetty, Shivan S; Wallendorf, Michael

2017-01-01

Lay consultations can facilitate or impede healthcare. However, little is known about how lay consultations for symptom evaluation affect treatment decision-making. The purpose of this study was to explore the role of lay consultations in symptom evaluation prior to hospitalization among patients with heart failure. Semi-structured interviews were conducted with 60 patients hospitalized for acute decompensated heart failure. Chi-square and Fisher's exact tests, along with logistic regression were used to characterize lay consultations in this sample. A large proportion of patients engaged in lay consultations for symptom evaluation and decision-making before hospitalization. Lay consultants provided attributions and advice and helped make the decision to seek medical care. Men consulted more often with their spouse than women, while women more often consulted with adult children. Findings have implications for optimizing heart failure self-management interventions, improving outcomes, and reducing hospital readmissions.

In hindsight: urban exposure explains the association between prior migration and current health of older adults in Mexico.

PubMed

Wheaton, Felicia V; Crimmins, Eileen M

2013-04-01

This study examines sex differences in the association between migration and exposure to an urban environment and overweight, hypertension and diabetes in later life. Interviews were conducted with 3,604 adults aged 50 and older in the Mexican Family Life Survey (MxFLS). Logistic regression analyses were used to examine the association between previous migration, urban exposure, and risk of overweight, hypertension, and diabetes. Migration itself was not associated with health outcomes after controlling for urban exposure. The risk of overweight and diabetes associated with urban exposure appeared to be greater for men. Sex differences were found in the covariates that helped explain differences in health between those with high and low urban exposure. These findings underscore the need to consider heterogeneity in health by urban exposure and by sex.

Factors influencing nanotechnology commercialization: an empirical analysis of nanotechnology firms in South Korea

NASA Astrophysics Data System (ADS)

Lee, Cheol-Ju; Lee, SuKap; Jhon, Myung S.; Shin, Juneseuk

2013-02-01

Nanotechnology is a representative emerging technology in an embryonic stage. Due to the continuous support provided by both the public and private sectors of many countries, nanotechnologies have increasingly been commercialized in a wide array of industries, but also produce many commercialization failures. Tackling this problem, we investigate key factors affecting the commercialization of nanotechnologies. Identifying key factors of nanotechnology commercialization through literature review and interview with CEOs, we collected data of 206 Korean nanotechnology-based companies, and analyzed the causal relationship between key factors and financial performance. Logistic and Tobit regression models are used. Overall, companies achieving successful commercialization hold some common characteristics including consistent exploratory R&D, governmental funding, and nano-instrument/energy/environment-related products. Also, the use of potentially toxic materials makes commercialization difficult even if the products are not toxic.

The Cycle of Social Exclusion for Urban, Young Men of Color in the United States: What is the Role of Incarceration?

PubMed Central

RAMASWAMY, MEGHA; FREUDENBERG, NICHOLAS

2013-01-01

This article explores how incarceration amplifies the disconnection from school and work experienced by urban, young men of color in the United States and ultimately leads to their social exclusion. The authors draw on longitudinal data collected in interviews with 397 men age 16 to 18 in a New York City jail and then again one year after their release. Using logistic regression analysis, the authors found that though incarceration did not appear to exacerbate disconnectedness directly, it was associated with unstable housing, which in turn may contribute to several negative outcomes related to social exclusion. These findings may inform advocates, policy makers, and researchers in their efforts to meet the needs of socially excluded youth, in particular those with criminal justice histories. PMID:24431927

Caregiver Burden in Frontotemporal Degeneration and Corticobasal Syndrome

PubMed Central

Armstrong, Nicole; Schupf, Nicole; Grafman, Jordan; Huey, Edward D.

2015-01-01

Background and Aims Caregiver stress is often a serious problem when caring for a patient with frontal lobe dysfunction. Methods A total of 102 caregivers of both patients with frontotemporal degeneration and corticobasal syndrome completed the Frontal Systems Behavior Scale (FrSBe) and the Zarit Burden Interview (ZBI). To analyze the association between apathy or disinhibition (or both) and caregiver burden, the effects of the total FrSBe and the apathy and disinhibition subscales of the FrSBE on the total ZBI score were assessed with logistic regressions and t tests. Results Total FrSBE score and the apathy FrSBE subscore predicted caregiver burden. Apathy occurred without disinhibition, and the two occurred together, but disinhibition without apathy was very rare. Conclusions Disinhibition without apathy occurred very rarely. Apathy was more associated with caregiver burden than disinhibition. PMID:24022248

From Attitudes to Actions: Predictors of Lion Killing by Maasai Warriors.

PubMed

Hazzah, Leela; Bath, Alistair; Dolrenry, Stephanie; Dickman, Amy; Frank, Laurence

2017-01-01

Despite legal protection, deliberate killing by local people is one of the major threats to the conservation of lions and other large carnivores in Africa. Addressing this problem poses particular challenges, mainly because it is difficult to uncover illicit behavior. This article examined two groups of Maasai warriors: individuals who have killed African lions (Panthera leo) and those who have not. We conducted interviews to explore the relationship between attitudes, intentions and known lion killing behavior. Factor analysis and logistic regression revealed that lion killing was mainly determined by: (a) general attitudes toward lions, (b) engagement in traditional customs, (c) lion killing intentions to defend property, and (d) socio-cultural killing intentions. Our results indicated that general attitudes toward lions were the strongest predictor of lion killing behavior. Influencing attitudes to encourage pro-conservation behavior may help reduce killing.

Racial/ethnic disparities in obesity among US-born and foreign-born adults by sex and education.

PubMed

Barrington, Debbie S; Baquero, Maria C; Borrell, Luisa N; Crawford, Natalie D

2010-02-01

This study examines sex and education variations in obesity among US- and foreign-born whites, blacks, and Hispanics utilizing 1997-2005 data from the National Health Interview Survey on 267,585 adults aged > or =18 years. After adjusting for various demographic, health, and socioeconomic factors via logistic regression, foreign-born black men had the lowest odds for obesity relative to US-born white men. The largest racial/ethnic disparity in obesity was between US-born black and white women. High educational attainment diminished the US-born black-white and Hispanic-white disparities among women, increased these disparities among men, and had minimal effect on foreign-born Hispanic-white disparities among women and men. Comprehension of these relationships is vital for conducting effective obesity research and interventions within an increasingly diverse United States.

Psychotropic substance abuse among adolescents: a structural equation model on risk and protective factors.

PubMed

Rumpold, Gerhard; Klingseis, Michael; Dornauer, Kurt; Kopp, Martin; Doering, Stephan; Höfer, Stefan; Mumelter, Birgit; Schüssler, Gerhard

2006-01-01

The use of psychotropic substances in adolescents represents a serious public health problem. In this study a representative sample of 485 Austrian students between 14 and 18 years of age were investigated with a semistructured interview about substance-related issues and completed the general health questionnaire. The following rates of regular psychotropic substance use were found: cigarettes 41.4%, alcohol 44.5%, cannabis 10.1%, and other illicit substances 3%. Logistic regression analyses and structural equation modeling revealed the following major risk factors for substance use: peer pressure, negative family atmosphere, school difficulties, and psychopathology. Knowledge about substance use acted as a protective factor. Prevention of adolescent substance use and misuse should aim at these different targets. Information about coping with peer pressure may be a particularly promising route of intervention.

Toward an understanding of the context of anal sex behavior in ethnic minority adolescent women.

PubMed

Dimmitt Champion, Jane; Roye, Carol F

2014-07-01

Understanding the context of anal sex behavior among ethnic minority adolescent women has public health implications for behavioral sexual health promotion and risk reduction interventions. African-American (n = 94) and Mexican-American (n = 465) women (14-18 years of age) enrolled in a clinical trial completed semi-structured interviews to assess psychosocial and situational factors and relationships to sexual risk behavior, substance use, sexually transmitted infection/HIV acquisition, and violence. Bivariate analyses with comparisons by anal sex experiences identified differences by ethnicity and higher self-reported histories of sexual risk behaviors, substance use, violence, and stressful psychosocial and situational factors among adolescent women experiencing anal sex. Predictors of anal sex identified through logistic regression included Mexican-American ethnicity, ecstasy use, methamphetamine use, childhood sexual molestation, oral sex, and sex with friends for benefits.

Condom use at last sexual relationship among adolescents of Santiago Island, Cape Verde, - West Africa

PubMed Central

2012-01-01

Objective To estimate factors associated with condom use at last sexual intercourse among adolescents. Methods Cross-sectional study of a representative sample of 368 sexually active adolescents aged 13–17 years from eight public high schools on Santiago Island, Cape Verde, 2007. The level of significance was 5.0% obtained from logistic regression, considering the association between condom use and socio-demographic, sexual and reproductive variables. Results The prevalence of condom use at last sexual intercourse was 94.9%. Factors associated with condom use at last sexual relationship were: non-Catholic religion (OR=0.68, 95%CI: 0.52; 0.88) and affective-sexual partnership before the interview (OR=5.15, 95%CI: 1.79; 14.80). Conclusions There was a high prevalence of condom use at last sexual intercourse of adolescents. PMID:23153259

Employment Barriers Among Welfare Recipients and Applicants With Chronically Ill Children

PubMed Central

Smith, Lauren A.; Romero, Diana; Wood, Pamela R.; Wampler, Nina S.; Chavkin, Wendy; Wise, Paul H.

2002-01-01

Objectives. This study evaluated the association of chronic child illness with parental employment among individuals who have had contact with the welfare system. Methods. Parents of children with chronic illnesses were interviewed. Results. Current and former welfare recipients and welfare applicants were more likely than those with no contact with the welfare system to report that their children’s illnesses adversely affected their employment. Logistic regression analyses showed that current and former receipt of welfare, pending welfare application, and high rates of child health care use were predictors of unemployment. Conclusions. Welfare recipients and applicants with chronically ill children face substantial barriers to employment, including high child health care use rates and missed work. The welfare reform reauthorization scheduled to occur later in 2002 should address the implications of chronic child illness for parental employment. PMID:12197972

Family functionality: a study of Brazilian institutionalized elderly individuals.

PubMed

de Oliveira, Simone Camargo; Pavarini, Sofia Cristina Iost; Orlandi, Fabiana de Souza; de Mendiondo, Marisa Silvana Zazzeta

2014-01-01

This study presents an analysis of a potential association between family functionality and the variables of gender, length of institutionalization, family composition, depressive symptoms, and cognitive disorders in elderly individuals living in Long-Term Care Facilities (LTCF) in a city in the interior of São Paulo, Brazil. This is a quantitative, cross-sectional study with a descriptive-correlational design. A total of 107 institutionalized elderly individuals were interviewed. Data were analyzed through raw and adjusted Logistic Regression. The results indicate that most elderly individuals experience family dysfunction, 57% present a high level of family dysfunction, 21% present moderate family dysfunction and 22% present good family functionality. There was a statistical association between the Family APGAR and the variables of length of institutionalization, depressive symptoms, family composition and cognitive disorders. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Difficulties of care-work reconciliation: employed and nonemployed mothers of children with intellectual disability.

PubMed

Chou, Yueh-Ching; Fu, Li-Yeh; Pu, Cheng-Yun; Chang, Heng-Hao

2012-09-01

Whether employed and nonemployed mothers of children with intellectual disability (ID) have different experiences with reconciliation between care and work has rarely been explored. A survey was conducted in a county in Taiwan and 487 mothers aged younger than 65 and having a child with ID were interviewed face to face at their homes to explore whether there are different factors related to the reconciliation between care and work among employed and nonemployed mothers. Except for the common ground of mothers' health and care demands, logistic regression revealed work flexibility and care support were important for employed mothers. In contrast, the success of reconciliation for nonemployed mothers was determined by their individual characteristics (i.e., age, marital status, family income). Reconciliation policies for mothers with different employment statuses need to use different strategies.

History of falls, gait, balance, and fall risks in older cancer survivors living in the community.

PubMed

Huang, Min H; Shilling, Tracy; Miller, Kara A; Smith, Kristin; LaVictoire, Kayle

2015-01-01

Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A "faller" was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher's exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling.

History of falls, gait, balance, and fall risks in older cancer survivors living in the community

PubMed Central

Huang, Min H; Shilling, Tracy; Miller, Kara A; Smith, Kristin; LaVictoire, Kayle

2015-01-01

Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A “faller” was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher’s exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594–29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling. PMID:26425079

Risk Factors Associated With Antidepressant Exposure and History of Antidepressant-Induced Mania in Bipolar Disorder.

PubMed

Williams, Aislinn J; Lai, Zongshan; Knight, Seth; Kamali, Masoud; Assari, Shervin; McInnis, Melvin G

2018-05-15

Despite their widespread use in bipolar disorder, there is controversy surrounding the inclusion of antidepressant medications in the disorder's management. We sought to identify which demographic, socioeconomic, and clinical factors are associated with antidepressant exposure in bipolar disorder and which bipolar disorder patients are most likely to report a history of antidepressant-induced mania (AIM) when exposed to antidepressants. Our study included subjects with bipolar I disorder (n = 309), bipolar II disorder (n = 66), and bipolar disorder not otherwise specified (n = 27) and schizoaffective disorder, bipolar type (n = 14), from a longitudinal, community-based study. Subjects were evaluated using the Diagnostic Interview for Genetic Studies, modified for DSM-IV criteria. We applied multivariate logistical regression modeling to investigate which factors contribute to antidepressant exposure in bipolar disorder patients. We also used a logistic regression modeling approach to determine which clinical factors in bipolar disorder patients are associated with a history of AIM. Data were gathered from February 2006 through December 2010. Our results suggest that the risk factors most strongly associated with antidepressant exposure are female sex (OR = 2.73, P = .005), older age (OR = 1.03, P = .04), greater chronicity of illness (OR = 2.29, P = .04), and, to a lesser extent, white race (OR = 0.44, P = .051). Factors associated with reduced antidepressant exposure include history of affective psychosis (OR = 0.36, P = .01) and a greater number of previous manic episodes (OR = 0.98, P = .03). In subjects who reported a history of AIM, regression analysis revealed that the only statistically significant factor associated with AIM history was female sex (OR = 3.74, P = .02). These data suggest that there are certain identifiable factors associated with antidepressant exposure in bipolar disorder patients, and some of these, specifically female sex, are also associated with a history of AIM. These data may be useful in designing prospective trials to identify interventions that can reduce the risk of this adverse outcome. © Copyright 2018 Physicians Postgraduate Press, Inc.

Maternal Support for Human Papillomavirus Vaccination in Honduras

PubMed Central

Langrish, Sarah M.; Cotton, Deborah J.; Simon, Carol J.

2011-01-01

Abstract Background Cervical cancer is a leading cause of cancer death for women in Latin America, and vaccinating against human papillomavirus (HPV) has the potential to limit this disease. We sought to determine Honduran women's awareness of HPV vaccination and interest in vaccinating their daughters against HPV. Methods We interviewed mothers aged ≥17 at primary care clinics in Honduras. First, we collected demographic information and assessed knowledge related to cervical cancer prevention and awareness of HPV and HPV vaccination. Because most participants were not familiar with HPV, education about the relationships among HPV, sexual activity, and cervical cancer was provided before we asked participants if they would accept HPV vaccination for a 9-year-old daughter. We used multivariable logistic regression to determine predictors of vaccine acceptance. Results We interviewed 632 mothers. Only 13% had heard of HPV vaccination before the interview. After education, 91% would accept HPV vaccination for a 9-year-old daughter. Mothers who intended to vaccinate knew more at baseline about cervical cancer prevention than did those who did not endorse vaccination. Demographic characteristics did not predict vaccine acceptance. Conclusions Few Honduran mothers were aware of HPV or HPV vaccination. However, most Honduran mothers would accept HPV vaccination for their daughters after receiving education about the relationship between HPV infection and cervical cancer. Baseline cervical cancer knowledge was associated with vaccine acceptance. PMID:21091226

Prenatal predictors of postpartum depression and postpartum depressive symptoms in Mexican mothers: a longitudinal study.

PubMed

Lara, María Asunción; Navarrete, Laura; Nieto, Lourdes

2016-10-01

Prospective studies on the predictors of postpartum depression (PPD) in Latin America are scarce, which is a matter of importance, since the significance of PPD risk factors may vary according to the level of development of a country, the types of measurement and the time periods assessed. This study identifies the prenatal predictors for PPD (diagnostic interview) and postpartum depressive symptoms (PPDS) (self-report scale) in Mexican mothers at 6 weeks and 6 months postpartum. Two hundred and ten women were interviewed using the Structured Clinical Interview (SCID-I), Patient Health Questionnaire (PHQ-9) and various risk factor scales. Univariate logistic regressions showed that social support, marital satisfaction, life events, a history of psychopathology, anxiety symptoms, depressive symptoms, the traditional female role, previous miscarriages/termination of pregnancy and unplanned/unwanted pregnancy were significant predictors for both PPD and PPDS at both assessment times in the postpartum. Education, age, marital status, income, occupation, parity, C-section and resilience were significant for only one of the measurements and/or at just one assessment time. General findings replicate a high- and low-income country observed psychosocial risk profile and confirm a sociodemographic and obstetric profile of vulnerability that is more prevalent in resource-constrained countries. PPD constitutes a high burden for new mothers, particularly for those living in low-middle-income countries who face social disadvantages (such as low educational attainment and income).

Factors affecting maternal participation in the genetic component of the National Birth Defects Prevention Study-United States, 1997-2007.

PubMed

Glidewell, Jill; Reefhuis, Jennita; Rasmussen, Sonja A; Woomert, Alison; Hobbs, Charlotte; Romitti, Paul A; Crider, Krista S

2014-04-01

As epidemiological studies expand to examine gene-environment interaction effects, it is important to identify factors associated with participation in genetic studies. The National Birth Defects Prevention Study is a multisite case-control study designed to investigate environmental and genetic risk factors for major birth defects. The National Birth Defects Prevention Study includes maternal telephone interviews and mailed buccal cell self-collection kits. Because subjects can participate in the interview, independent of buccal cell collection, detailed analysis of factors associated with participation in buccal cell collection was possible. Multivariable logistic regression models were used to identify the factors associated with participation in the genetic component of the study. Buccal cell participation rates varied by race/ethnicity (non-Hispanic whites, 66.9%; Hispanics, 60.4%; and non-Hispanic blacks, 47.3%) and study site (50.2-74.2%). Additional monetary incentive following return of buccal cell kit and shorter interval between infant's estimated date of delivery and interview were associated with increased participation across all racial/ethnic groups. Higher education and delivering an infant with a birth defect were associated with increased participation among non-Hispanic whites and Hispanics. Factors associated with participation varied by race/ethnicity. Improved understanding of factors associated with participation may facilitate strategies to increase participation, thereby improving generalizability of study findings.

The consequences of task delegation for the process of care: Female patients seem to benefit more.

PubMed

Noordman, Janneke; van Dulmen, Sandra

2016-01-01

The shift of tasks from primary care physicians to practice nurses and the continuing incease in the numbers of women involved in medical care may have consequences for the provision of health care and communication. The aim of the present study was to examine potential differences in female practice nurses' application of communication skills, practice guidelines, and motivational interviewing skills during consultations with female and male patients. Nineteen female practice nurses and their patients (n = 181) agreed to have their consultations videotaped (during 2010-2011). The videotaped consultations were rated using two validated instruments: the Maas-Global (to assess generic communication skills and practice guidelines) and the Behaviour Change Counselling Index (to assess motivational interviewing skills). Multilevel linear and logistic regression analyses were performed. Female practice nurses provided significantly more comprehensive information during consultations with female patients (p = .03) and talked more about management with male patients (p = .04). Furthermore, nurses applied motivational interviewing skills more clearly during consultations with female than with male patients (p < .01). The shift in tasks from primary care physicians toward practice nurses may have implications for clinical and patient outcomes as patients will no longer be counseled by male professionals. Conceivably, female patients are motivated more by nurses to change their behavior, while male patients receive more concrete management information or advice.

Problem parental care and teenage deliberate self-harm in young community adults.

PubMed

Bifulco, Antonia; Schimmenti, Adriano; Moran, Patricia; Jacobs, Catherine; Bunn, Amanda; Rusu, Adina Carmen

2014-01-01

Deliberate self-harm (DSH) in young people is a clinical and social problem related to early maltreatment but with little specificity in type of care or abuse determined. A community sample of 160 high-risk young people (aged 16-30) were the offspring of mothers' previously interviewed as vulnerable to major depression. The youth were interviewed to determine DSH (both suicidal and nonsuicidal), childhood maltreatment (using the Childhood Experience of Care and Abuse interview) and major depression (using SCID for DSMIV) before age 17. Around one fifth reported DSH; equal proportions were suicidal and nonsuicidal with a fourth of these with both. DSH was highly related to family context (single mother upbringing and family discord) and poor parental care (including antipathy, neglect, inadequate supervision, and role reversal). Highest odds ratios were for role reversal (OR = 17) and neglect (OR = 11). DSH was unrelated to any type of abuse. Logistic regression showed that role reversal, inadequate supervision, and teenage depression all modeled DSH. There was some specificity, with single mother upbringing, role reversal, and inadequate supervision predicting nonsuicidal DSH, and neglect and role reversal alone predicting suicidal DSH. Role reversal remained a key predictor for both types of DSH when controls were applied. Poor childhood care, which has implications for problematic emotion regulation and empoverished social development, needs to be understood to improve interventions and treatment for DSH in young people.

Clinical characteristics and diagnostic confirmation of Internet addiction in secondary school students in Wuhan, China.

PubMed

Tang, Jun; Zhang, Yao; Li, Yi; Liu, Lianzhong; Liu, Xiujun; Zeng, Hongling; Xiang, Dongfang; Li, Chiang-Shan Ray; Lee, Tony Szu-Hsien

2014-06-01

This study investigated the clinical characteristics of internet addiction using a cross-sectional survey and psychiatric interview. A structured questionnaire consisted of demographics, Symptom Checklist 90, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and Young's Internet Addiction Test (YIAT) was administered to students of two secondary schools in Wuhan, China. Students with a score of 5 or higher on the YIAT were classified as having Internet Addiction Disorder (IAD). Two psychiatrists interviewed students with IAD to confirm the diagnosis and evaluate their clinical characteristics. Of a total of 1076 respondents (mean age 15.4 ± 1.7 years; 54.1% boys), 12.6% (n = 136) met the YIAT criteria for IAD. Clinical interviews ascertained the Internet addiction of 136 pupils and also identified 20 students (14.7% of IAD group) with comorbid psychiatric disorders. Results from multinomial logistic regression indicated that being male, in grade 7-9, poor relationship between parents and higher self-reported depression scores were significantly associated with the diagnosis of IAD. These results advance our understanding of the clinical characteristics of Internet addiction in Chinese secondary school students and may help clinicians, teachers, and other stakeholders better manage this increasingly serious mental condition. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

Reproductive factors, nutritional status and serum 25(OH)D levels in women with breast cancer: A case control study.

PubMed

Sofi, Nighat Y; Jain, Monika; Kapil, Umesh; Seenu, Vuthaluru; R, Lakshmy; Yadav, Chander P; Pandey, Ravindra M; Sareen, Neha

2018-01-01

The study was conducted with an objective to investigate the association between reproductive factors, nutritional status and serum 25(OH)D levels among women diagnosed with breast cancer (BC). A total of 200 women with BC attending a tertiary healthcare institute of Delhi, India matched with 200 healthy women for age (±2years) and socio economic status were included in the study. Data was collected on socio-demographic profile, reproductive factors, physical activity and dietary intake (24h dietary recall and food frequency questionnaire) using interviewer administered structured questionnaires and standard tools. Non fasting blood samples (5ml) were collected for the biochemical estimation of serum 25(OH)D and calcium levels by chemiluminescent immunoassay and colorimetric assay technique. Data was analyzed by univariable conditional logistic regression and significant variables with (p<0.05), were analyzed in final model by conditional multivariable logistic regression analysis. The mean age of patients at diagnosis of BC was 45±10years. Results of multivariable conditional logistic regression analysis revealed significantly higher odds of BC for reproductive factors like age at marriage (more than 23 years), number of abortions, history or current use of oral contraceptive pills (OCP), with [OR (95% CI)] of [2.4 (1.2-4.9)], [4.0 (1.6-12.6)], [2.4 (1.2-5.0)]. Women with physically light activities and occasional consumption of eggs were found to have higher odds of BC [4.6 (1.6-13.0)] and [3.2 (1.6-6.3)]. Women with serum 25(OH)D levels less than 20ng/ml and calcium levels less than 10.5mg/dl had higher odds of having BC [2.4 (1.2-5.1)] and [3.7 (1.5-8.8)]. A protective effect of urban areas as place of residence and energy intake greater than 50% of Recommended Dietary Allowance (RDA) per day against BC was observed (p<0.05). The findings of the present study revealed a significant association of reproductive and dietary factors in addition to sedentary physical activity and low serum 25(OH)D levels in women diagnosed with BC. Copyright © 2017 Elsevier Ltd. All rights reserved.

An artificial neural network prediction model of congenital heart disease based on risk factors: A hospital-based case-control study.

PubMed

Li, Huixia; Luo, Miyang; Zheng, Jianfei; Luo, Jiayou; Zeng, Rong; Feng, Na; Du, Qiyun; Fang, Junqun

2017-02-01

An artificial neural network (ANN) model was developed to predict the risks of congenital heart disease (CHD) in pregnant women.This hospital-based case-control study involved 119 CHD cases and 239 controls all recruited from birth defect surveillance hospitals in Hunan Province between July 2013 and June 2014. All subjects were interviewed face-to-face to fill in a questionnaire that covered 36 CHD-related variables. The 358 subjects were randomly divided into a training set and a testing set at the ratio of 85:15. The training set was used to identify the significant predictors of CHD by univariate logistic regression analyses and develop a standard feed-forward back-propagation neural network (BPNN) model for the prediction of CHD. The testing set was used to test and evaluate the performance of the ANN model. Univariate logistic regression analyses were performed on SPSS 18.0. The ANN models were developed on Matlab 7.1.The univariate logistic regression identified 15 predictors that were significantly associated with CHD, including education level (odds ratio  = 0.55), gravidity (1.95), parity (2.01), history of abnormal reproduction (2.49), family history of CHD (5.23), maternal chronic disease (4.19), maternal upper respiratory tract infection (2.08), environmental pollution around maternal dwelling place (3.63), maternal exposure to occupational hazards (3.53), maternal mental stress (2.48), paternal chronic disease (4.87), paternal exposure to occupational hazards (2.51), intake of vegetable/fruit (0.45), intake of fish/shrimp/meat/egg (0.59), and intake of milk/soymilk (0.55). After many trials, we selected a 3-layer BPNN model with 15, 12, and 1 neuron in the input, hidden, and output layers, respectively, as the best prediction model. The prediction model has accuracies of 0.91 and 0.86 on the training and testing sets, respectively. The sensitivity, specificity, and Yuden Index on the testing set (training set) are 0.78 (0.83), 0.90 (0.95), and 0.68 (0.78), respectively. The areas under the receiver operating curve on the testing and training sets are 0.87 and 0.97, respectively.This study suggests that the BPNN model could be used to predict the risk of CHD in individuals. This model should be further improved by large-sample-size research.

Applicant Characteristics Associated With Selection for Ranking at Independent Surgery Residency Programs.

PubMed

Dort, Jonathan M; Trickey, Amber W; Kallies, Kara J; Joshi, Amit R T; Sidwell, Richard A; Jarman, Benjamin T

2015-01-01

This study evaluated characteristics of applicants selected for interview and ranked by independent general surgery residency programs and assessed independent program application volumes, interview selection, rank list formation, and match success. Demographic and academic information was analyzed for 2014-2015 applicants. Applicant characteristics were compared by ranking status using univariate and multivariable statistical techniques. Characteristics independently associated with whether or not an applicant was ranked were identified using multivariable logistic regression modeling with backward stepwise variable selection and cluster-correlated robust variance estimates to account for correlations among individuals who applied to multiple programs. The Electronic Residency Application Service was used to obtain applicant data and program match outcomes at 33 independent surgery programs. All applicants selected to interview at 33 participating independent general surgery residency programs were included in the study. Applicants were 60% male with median age of 26 years. Birthplace was well distributed. Most applicants (73%) had ≥1 academic publication. Median United States Medical Licensing Exams (USMLE) Step 1 score was 228 (interquartile range: 218-240), and median USMLE Step 2 clinical knowledge score was 241 (interquartile range: 231-250). Residency programs in some regions more often ranked applicants who attended medical school within the same region. On multivariable analysis, significant predictors of ranking by an independent residency program were: USMLE scores, medical school region, and birth region. Independent programs received an average of 764 applications (range: 307-1704). On average, 12% interviews, and 81% of interviewed applicants were ranked. Most programs (84%) matched at least 1 applicant ranked in their top 10. Participating independent programs attract a large volume of applicants and have high standards in the selection process. This information can be used by surgery residency applicants to gauge their candidacy at independent programs. Independent programs offer a select number of interviews, rank most applicants that they interview, and successfully match competitive applicants. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders.

PubMed

Kupek, Emil

2006-03-15

Structural equation modelling (SEM) has been increasingly used in medical statistics for solving a system of related regression equations. However, a great obstacle for its wider use has been its difficulty in handling categorical variables within the framework of generalised linear models. A large data set with a known structure among two related outcomes and three independent variables was generated to investigate the use of Yule's transformation of odds ratio (OR) into Q-metric by (OR-1)/(OR+1) to approximate Pearson's correlation coefficients between binary variables whose covariance structure can be further analysed by SEM. Percent of correctly classified events and non-events was compared with the classification obtained by logistic regression. The performance of SEM based on Q-metric was also checked on a small (N = 100) random sample of the data generated and on a real data set. SEM successfully recovered the generated model structure. SEM of real data suggested a significant influence of a latent confounding variable which would have not been detectable by standard logistic regression. SEM classification performance was broadly similar to that of the logistic regression. The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM. The interpretation of results is aided by expressing them as odds ratios which are the most frequently used measure of effect in medical statistics.