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Bu sayfa, 26. Dünya Psikiyatri Kongresi'nde sunulan çalışmanın yapay zekâ desteğiyle hazırlanmış Türkçe özetidir. Çalışmanın sahibi sunan yazarlardır; atıf için orijinal kaynağa başvurun.

EV0658

What shapes substance use disorder across countries? An ecological analysis of socioeconomic, demographic, and health system factors

WHAT SHAPES DRUG USE DISORDER ACROSS COUNTRIES? AN ECOLOGICAL ANALYSIS OF SOCIOECONOMIC, DEMOGRAPHIC, AND HEALTH SYSTEM FACTORS

Country-level substance use disorder prevalence is positively associated with the education index, psychiatrist density, rurality, alcohol consumption, and unemployment, and negatively associated with the proportion of the population aged 0–14 years; the model explains 74.7% of the variance.

The study aimed to examine the relationship between cross-country differences in substance use disorder prevalence and socioeconomic, demographic, and health system factors. An ecological, cross-sectional country-level analysis was conducted using 2019 data from Our World in Data, with a sample of 123 countries and log-transformed substance use disorder prevalence as the outcome. Predictors were alcohol consumption, rurality, the proportion of the population aged 0–14 years, unemployment, the education index, and the number of psychiatrists per 100,000 people. Multiple linear regression, variance inflation factor (VIF) assessment, and residual diagnostics were used. The final model explained 74.7% of the variance (R²=0.747; adjusted R²=0.734; p<0.001). Based on standardized beta coefficients, the strongest positive association was observed for the education index and the strongest negative association for the proportion aged 0–14 years; B and p values were as follows: education index B=1.260, p<0.001; proportion aged 0–14 years B=-0.018, p=0.001; number of psychiatrists B=0.017, p=0.002; rural population percentage B=0.004, p=0.011; alcohol consumption B=0.019, p=0.034; unemployment B=0.011, p=0.028. The authors note that country-level prevalence is associated with structural indicators, that the findings may reflect both disease burden and epidemiological visibility (surveillance, diagnostic practices, data quality, and underreporting), that country-level associations do not imply individual-level or causal relationships, and that longitudinal and multilevel studies are needed.

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