BMJ open · 2026
Clustering socio-demographic of Indonesian adolescents and their associations with depression: a cross-sectional study.
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Murti Fadhaa Aditya Kautsar, Nursalam Nursalam, Kustanti Christina Yeni, McKenna Lisa, Sutrisno Sutrisno, Pradipta Rifky Octavia, Saleh Ariyanti, Efendi Ferry
Аннотация
OBJECTIVES: To identify socio-demographic subgroups of adolescents through cluster analysis and examine the extent to which these clusters are associated with depression.
DESIGN: This cross-sectional study used cluster analysis and logistic regression.
SETTING: The Indonesian Health Survey 2023 is a nationally representative survey of Indonesia.
PARTICIPANTS: A total of 89,866 adolescents aged 15-24 years were included.
PRIMARY AND SECONDARY OUTCOME MEASURES: Depression was assessed using the Mini International Neuropsychiatric Interview. Logistic regression models were applied to estimate the association between cluster membership and depression risk, adjusting for behavioural factors (smoking and alcohol use), and geographical distribution.
RESULTS: Five discrete socio-demographic clusters were identified in this study. Two clusters showed a significantly elevated risk of depression compared with the socioeconomically disadvantaged rural male cluster (Cluster 1). Cluster 2 (older, poor, rural females) had an OR 1.58 (95% CI 1.18 to 2.12), while Cluster 3 (younger, urban, affluent females) had an OR 2.60 (95% CI 1.92 to 3.52).
CONCLUSIONS: Adolescent depression risk factors are shaped by intersecting socio-demographic vulnerabilities, particularly among females in disadvantaged rural and socioeconomically privileged urban settings. Gender-responsive and context-specific mental health interventions are required.
DESIGN: This cross-sectional study used cluster analysis and logistic regression.
SETTING: The Indonesian Health Survey 2023 is a nationally representative survey of Indonesia.
PARTICIPANTS: A total of 89,866 adolescents aged 15-24 years were included.
PRIMARY AND SECONDARY OUTCOME MEASURES: Depression was assessed using the Mini International Neuropsychiatric Interview. Logistic regression models were applied to estimate the association between cluster membership and depression risk, adjusting for behavioural factors (smoking and alcohol use), and geographical distribution.
RESULTS: Five discrete socio-demographic clusters were identified in this study. Two clusters showed a significantly elevated risk of depression compared with the socioeconomically disadvantaged rural male cluster (Cluster 1). Cluster 2 (older, poor, rural females) had an OR 1.58 (95% CI 1.18 to 2.12), while Cluster 3 (younger, urban, affluent females) had an OR 2.60 (95% CI 1.92 to 3.52).
CONCLUSIONS: Adolescent depression risk factors are shaped by intersecting socio-demographic vulnerabilities, particularly among females in disadvantaged rural and socioeconomically privileged urban settings. Gender-responsive and context-specific mental health interventions are required.