Addictive behaviors reports · 2026
Association between latent classes of tobacco, e-cigarette, alcohol, and illicit drug use patterns and depression among Thai adolescents.
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.
Sagayanathan Renarebecca, Wichaidit Wit, Stafström Martin
Аннотация
BACKGROUND: Adolescent substance use behaviors often co-occur and are associated with poorer mental health. While latent class analysis (LCA) has identified adolescent substance use patterns in high-income countries, evidence from Southeast Asia remains limited.
AIM: To identify gender-stratified substance use patterns among Thai adolescents aged 16-17 years and examine their associations with elevated depressive symptoms.
METHODS: We conducted a cross-sectional analysis of 9188 Thai adolescents aged 16-17 years using data from the 5th Thai National School Survey on Alcohol Consumption, Substance Use and Other Health-Risk Behaviors. Fourteen indicators of lifetime and recent tobacco, e-cigarette, alcohol, and illicit substance use were included in gender-stratified LCA models. Elevated depressive symptoms were assessed using the Patient Health Questionnaire-2 (PHQ-2; score ≥ 2). Logistic regression estimated associations between latent class membership and elevated depressive symptoms after adjustment for sociodemographic, academic, and lifestyle covariates.
RESULTS: Four latent classes were identified among males and three among females and gender-diverse adolescents. Compared with the minimal/non-use class, all substance-using classes showed higher odds of elevated depressive symptoms. The highest odds were generally observed in the high polysubstance-use classes. Among males, the experimental cannabis/kratom and tobacco-related use class showed odds comparable to the high polysubstance-use class.
CONCLUSIONS: Distinct gender-stratified substance use patterns were associated with elevated depressive symptoms among Thai adolescents. These findings extend evidence on adolescent substance use heterogeneity in Southeast Asia and support the use of latent class analysis to identify adolescents at greater mental health risk. Longitudinal studies are needed to clarify temporal relationships.
AIM: To identify gender-stratified substance use patterns among Thai adolescents aged 16-17 years and examine their associations with elevated depressive symptoms.
METHODS: We conducted a cross-sectional analysis of 9188 Thai adolescents aged 16-17 years using data from the 5th Thai National School Survey on Alcohol Consumption, Substance Use and Other Health-Risk Behaviors. Fourteen indicators of lifetime and recent tobacco, e-cigarette, alcohol, and illicit substance use were included in gender-stratified LCA models. Elevated depressive symptoms were assessed using the Patient Health Questionnaire-2 (PHQ-2; score ≥ 2). Logistic regression estimated associations between latent class membership and elevated depressive symptoms after adjustment for sociodemographic, academic, and lifestyle covariates.
RESULTS: Four latent classes were identified among males and three among females and gender-diverse adolescents. Compared with the minimal/non-use class, all substance-using classes showed higher odds of elevated depressive symptoms. The highest odds were generally observed in the high polysubstance-use classes. Among males, the experimental cannabis/kratom and tobacco-related use class showed odds comparable to the high polysubstance-use class.
CONCLUSIONS: Distinct gender-stratified substance use patterns were associated with elevated depressive symptoms among Thai adolescents. These findings extend evidence on adolescent substance use heterogeneity in Southeast Asia and support the use of latent class analysis to identify adolescents at greater mental health risk. Longitudinal studies are needed to clarify temporal relationships.