Maternal age and husband’s income as predictors of postpartum depression among Indonesian mothers

Afinia Sandhya Rini Rini

Abstract


This study examined the relationship between maternal age and husband’s income with postpartum depression among mothers in Indonesia. Postpartum depression is a serious mental health condition that varies in prevalence and significantly affects both maternal well-being and child development. Identifying demographic risk factors is essential for early detection and effective intervention. A total of 142 mothers with infants were recruited through purposive sampling from six community health centers. Postpartum depression was measured using the Edinburgh Postnatal Depression Scale (EPDS), and data were analyzed using multiple linear regression. The results indicated that the regression model significantly predicted postpartum depression levels (F(2,139) = 3.439, p = 0.035). Maternal age was a significant predictor (β = 0.217, p = 0.010), indicating that older mothers tended to experience higher levels of postpartum depression. In contrast, husband’s income was not a significant predictor (β = −0.00036, p = 0.997). Although the model was statistically significant, the predictors explained only 3.3% of the variance in postpartum depression levels (Adjusted R² = 0.033). These findings highlight the importance of incorporating maternal age into postpartum mental health screening and support programs, while emphasizing the need for further research to explore additional factors that may more strongly influence postpartum depression.

Keywords: postpartum depression; mother's age; husband's income; Indonesian; EPDS

 Copyright ©2025. The Authors. Published by Psikoislamika: Jurnal Psikologi dan Psikologi Islam. This is an open access article under the CC BY NO SA. Link: Creative Commons — Attribution-NonCommercial-ShareAlike 4.0 International — CC BY-NC-SA 4.0  


Keywords


Postpartum depression; Mother's age; Husband's income; Tulungagung; EPDS

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DOI: https://doi.org/10.18860/psikoislamika.v22i2.37301

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