International Institute for Population Sciences, 400088, Mumbai, India.
Department of Public Health & Mortality Studies, International Institute for Population Sciences, 400088, Mumbai, India.
BMC Psychiatry. 2024 Apr 30;24(1):330. doi: 10.1186/s12888-024-05684-5.
The study explored the levels and associated factors of undiagnosed depression among community-dwelling older Indian adults. It also identified the socio-demographic predictors of undiagnosed depression among the study population at national and state levels.
The study employed data from the Longitudinal Ageing Study in India wave-I, 2017-18. Based on the data on depression from interviewee's self-reporting and measurement on Composite International Diagnostic Interview- Short Form (CIDI-SF) and Centre for Epidemiological Studies- Depression scale (CES-D) scales, we estimated undiagnosed depression among older adults (age 60+). We estimated multivariable binary logistic regressions to examine the socio-demographic and health-related predictors of undiagnosed depression among older adults.
8% (95% CI: 7.8-8.4) of the total older adults had undiagnosed depression on CIDI-SF scale and 5% (95% CI: 4.8-5.3) on the combined CIDI-SF and CES-D. Undiagnosed depression was higher among those who were widowed, worked in the past and currently not working, scheduled castes, higher educated and the richest. Lack of health insurance coverage, presence of any other physical or mental impairment, family history of Alzheimer's/Parkinson's disease/ psychotic disorder, lower self-rated health and poor life satisfaction were significant predictors of undiagnosed depression on both CIDI-SF and combined scales.
To improve the health of older adults in India, targeted policy efforts integrating mental health screening, awareness campaigns and decentralization of mental healthcare to primary level is needed. Further research could explore the causal factors behind different levels of undiagnosed depression.
本研究旨在探讨印度社区居住的老年成年人中未确诊的抑郁症的水平及其相关因素。它还确定了在国家和州层面上,研究人群中未确诊的抑郁症的社会人口学预测因素。
本研究采用了 2017-18 年印度纵向老龄化研究的第一波数据。根据受访者自我报告的抑郁数据以及复合国际诊断访谈-短表(CIDI-SF)和流行病学研究中心抑郁量表(CES-D)的测量数据,我们估计了老年人中未确诊的抑郁症。我们估计了多变量二元逻辑回归模型,以检验老年人中未确诊的抑郁症的社会人口学和健康相关预测因素。
在 CIDI-SF 量表上,8%(95%CI:7.8-8.4)的老年人存在未确诊的抑郁症,在 CIDI-SF 和 CES-D 的综合量表上有 5%(95%CI:4.8-5.3)存在未确诊的抑郁症。在丧偶、过去和目前未工作、在册种姓、受过高等教育和最富裕的老年人中,未确诊的抑郁症更高。缺乏医疗保险、存在任何其他身体或精神障碍、阿尔茨海默病/帕金森病/精神病家族史、自我评估健康状况较差和生活满意度较差是 CIDI-SF 和综合量表上未确诊的抑郁症的显著预测因素。
为了改善印度老年人的健康,需要有针对性的政策努力,将心理健康筛查、宣传运动和精神卫生保健的权力下放整合到基层一级。进一步的研究可以探索未确诊的抑郁症不同水平背后的因果因素。