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Predictors of methamphetamine use in disadvantaged neighbourhoods in Czechia

B. Petruželka, P. Kupka, V. Walach

. 2022 ; 30 (4) : 253-260. [pub] 20221231

Language English Country Czech Republic

Document type Journal Article

Digital library NLK
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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.

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$a 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.
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