Central European journal of public health · 2022
Predictors of methamphetamine use in disadvantaged neighbourhoods in Czechia.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Petruželka Benjamin, Kupka Petr, Walach Václav
Аннотация
OBJECTIVE: This study aims to identify predictors of the lifetime prevalence of methamphetamine use in the population of Czech disadvantaged neighbourhoods.
METHODS: Using data from a face-to-face representative survey, two types of analysis were performed. A bivariate analysis (unadjusted odds ratios estimated with logistic regression) was conducted to determine the relationship with a dependent variable (lifetime prevalence of methamphetamine use). Subsequently, three multivariate binomial logistic regression models (socio-demographic and socioeconomic status, incarceration and victimization, mobility and space) were conducted to control for the influence of other variables.
RESULTS: In a series of multinomial logit models, we have found the following predictors to be significantly associated with lifetime prevalence of methamphetamine use: age, gender, Roma ethnicity, net monthly household income, unstable housing, lifetime experience with incarceration, lifetime experience with discrimination, urban-rural divide, and index of rural peripheralization.
CONCLUSIONS: The results suggest that methamphetamine users are multidimensionally disadvantaged and therefore constitute a vulnerable group with specific needs. This should be considered when designing services and policies targeting methamphetamine use in disadvantaged neighbourhoods.
METHODS: Using data from a face-to-face representative survey, two types of analysis were performed. A bivariate analysis (unadjusted odds ratios estimated with logistic regression) was conducted to determine the relationship with a dependent variable (lifetime prevalence of methamphetamine use). Subsequently, three multivariate binomial logistic regression models (socio-demographic and socioeconomic status, incarceration and victimization, mobility and space) were conducted to control for the influence of other variables.
RESULTS: In a series of multinomial logit models, we have found the following predictors to be significantly associated with lifetime prevalence of methamphetamine use: age, gender, Roma ethnicity, net monthly household income, unstable housing, lifetime experience with incarceration, lifetime experience with discrimination, urban-rural divide, and index of rural peripheralization.
CONCLUSIONS: The results suggest that methamphetamine users are multidimensionally disadvantaged and therefore constitute a vulnerable group with specific needs. This should be considered when designing services and policies targeting methamphetamine use in disadvantaged neighbourhoods.