Dataset Information

Estimating mental health impacts of alcohol's harms from other drinkers: using propensity scoring methods with national cross-sectional data from the United States.

ABSTRACT: BACKGROUND AND AIMS:Alcohol's harms to others (AHTO) may cause substantial distress, particularly when harms are perpetrated by close others. One challenge to identifying causal impacts is that people harmed by drinkers differ in many ways from those not so harmed, so our aim was to assess mental health in relation to two serious types of AHTO, financial harm and assault by someone who had been drinking, using propensity score (PS) weighting to adjust for potentially confounding differences. DESIGN:Cross-sectional, nationally representative, random sample of adults. SETTING:United States. PARTICIPANTS:Seventy-six respondents reporting financial harm compared with 4625 with no past-year AHTO; 192 respondents reporting assault compared with 4623 with no past-year AHTO. MEASUREMENTS:Predictors were reported exposure to financial problems due to someone's drinking and assault by someone who had been drinking. Mental health outcomes were quality of life, distress and positive affect. Confounders included family history of alcohol problems, child physical/sexual abuse, substance use/dependence, impacts of recent economic recession, racial/ethnic discrimination, poverty and other demographics. RESULTS:In double-robust PS weighted models for financial harm, there were associations with reduced quality of life (B = -0.28, P = 0.02) and increased distress [adjusted odds ratio (aOR) = 4.69, P < 0.001], and for assault by a partner or family member, there were associations with increased distress (aOR = 2.23, P = 0.09). For assault by a friend or stranger, none of the associations are statistically significant after PS weighting (all P > 0.10). CONCLUSIONS:Financial troubles due to someone else's drinking and assaults perpetrated by drinking intimates (spouses, other partners or family members) are associated with reduced mental health.

SUBMITTER: Karriker-Jaffe KJ

PROVIDER: S-EPMC6158083 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Estimating mental health impacts of alcohol's harms from other drinkers: using propensity scoring methods with national cross-sectional data from the United States.

Karriker-Jaffe Katherine J KJ Li Libo L Greenfield Thomas K TK

Addiction (Abingdon, England) 20180625 10

<h4>Background and aims</h4>Alcohol's harms to others (AHTO) may cause substantial distress, particularly when harms are perpetrated by close others. One challenge to identifying causal impacts is that people harmed by drinkers differ in many ways from those not so harmed, so our aim was to assess mental health in relation to two serious types of AHTO, financial harm and assault by someone who had been drinking, using propensity score (PS) weighting to adjust for potentially confounding differen ...[more]

PMID: 29893009

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Project description:Existing methods for predicting protein crystallization obtain high accuracy using various types of complemented features and complex ensemble classifiers, such as support vector machine (SVM) and Random Forest classifiers. It is desirable to develop a simple and easily interpretable prediction method with informative sequence features to provide insights into protein crystallization. This study proposes an ensemble method, SCMCRYS, to predict protein crystallization, for which each classifier is built by using a scoring card method (SCM) with estimating propensity scores of p-collocated amino acid (AA) pairs (p=0 for a dipeptide). The SCM classifier determines the crystallization of a sequence according to a weighted-sum score. The weights are the composition of the p-collocated AA pairs, and the propensity scores of these AA pairs are estimated using a statistic with optimization approach. SCMCRYS predicts the crystallization using a simple voting method from a number of SCM classifiers. The experimental results show that the single SCM classifier utilizing dipeptide composition with accuracy of 73.90% is comparable to the best previously-developed SVM-based classifier, SVM_POLY (74.6%), and our proposed SVM-based classifier utilizing the same dipeptide composition (77.55%). The SCMCRYS method with accuracy of 76.1% is comparable to the state-of-the-art ensemble methods PPCpred (76.8%) and RFCRYS (80.0%), which used the SVM and Random Forest classifiers, respectively. This study also investigates mutagenesis analysis based on SCM and the result reveals the hypothesis that the mutagenesis of surface residues Ala and Cys has large and small probabilities of enhancing protein crystallizability considering the estimated scores of crystallizability and solubility, melting point, molecular weight and conformational entropy of amino acids in a generalized condition. The propensity scores of amino acids and dipeptides for estimating the protein crystallizability can aid biologists in designing mutation of surface residues to enhance protein crystallizability. The source code of SCMCRYS is available at http://iclab.life.nctu.edu.tw/SCMCRYS/.

Project description:Background and aimEvaluations of alcohol policy changes demonstrate that restriction of trading hours of both 'on'- and 'off'-licence venues can be an effective means of reducing rates of alcohol-related harm. Despite this, the effects of different trading hour policy options over time, accounting for different contexts and demographic characteristics, and the common co-occurrence of other harm reduction strategies in trading hour policy initiatives, are difficult to estimate. The aim of this study was to use dynamic simulation modelling to compare estimated impacts over time of a range of trading hour policy options on various indicators of acute alcohol-related harm.MethodsAn agent-based model of alcohol consumption in New South Wales, Australia was developed using existing research evidence, analysis of available data and a structured approach to incorporating expert opinion. Five policy scenarios were simulated, including restrictions to trading hours of on-licence venues and extensions to trading hours of bottle shops. The impact of the scenarios on four measures of alcohol-related harm were considered: total acute harms, alcohol-related violence, emergency department (ED) presentations and hospitalizations.ResultsSimulation of a 3 a.m. (rather than 5 a.m.) closing time resulted in an estimated 12.3 ± 2.4% reduction in total acute alcohol-related harms, a 7.9 ± 0.8% reduction in violence, an 11.9 ± 2.1% reduction in ED presentations and a 9.5 ± 1.8% reduction in hospitalizations. Further reductions were achieved simulating a 1 a.m. closing time, including a 17.5 ± 1.1% reduction in alcohol-related violence. Simulated extensions to bottle shop trading hours resulted in increases in rates of all four measures of harm, although most of the effects came from increasing operating hours from 10 p.m. to 11 p.m.ConclusionsAn agent-based simulation model suggests that restricting trading hours of licensed venues reduces rates of alcohol-related harm and extending trading hours of bottle shops increases rates of alcohol-related harm. The model can estimate the effects of a range of policy options.

Dataset Information

Estimating mental health impacts of alcohol's harms from other drinkers: using propensity scoring methods with national cross-sectional data from the United States.

Publications

Estimating mental health impacts of alcohol's harms from other drinkers: using propensity scoring methods with national cross-sectional data from the United States.

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