Gender Disparities in Depressive Symptoms and Cognitive Impairment Among Older Adults in India

Purpose:  In 2010, persons aged 60+ numbered 765 million (11% of the global population). By 2050, more than 2 billion (20%) people will be in this age sector. The most rapid, extensive aging will be in less developed, resource-constrained settings, where older adults are projected to increase more than 250% between 2010 and 2050, compared to 71% in more developed countries. Further, non-communicative diseases (NCD), including mental, neurological and substance use (MNS) disorders, are now the chief health concern worldwide. Lifetime prevalence of MNS disorders is estimated at 12.2% - 48.6%. In the 2011 WHO rankings of DALYs for 291 conditions, mental and behavioral disorders ranked 6;neurological disorders, 7. The association of depression and dementia has been sparsely examined, but both will rise with population aging; and both disproportionately affect women. We use data from 7,150 persons aged 50+ in India to examine: 1) prevalence of depressive symptoms, cognitive impairment, and their co-occurrence; 2) socio-demographic, health, and psychosocial correlates of each condition; and 3) gender-based disparities and shared and unique correlates for men and women.

Methods: Data are from Wave 1 (2007-2010) of the WHO-SAGE survey on aging, using a multi-stage, stratified clustered sample design that reflects the India Census. There are three main outcomes: 1) self-reported depressive symptoms (none or mild = 0 and moderate, severe or extreme=1); 2) cognitive impairment (sum of memory (immediate and delayed recall); executive functions (verbal fluency) and attention (forward and backward digit span), parsed at the median into good = 0 and poor = 1; and 3) presence of both conditions (yes = 1; no = 0).  We used logistic regression models that included theoretical and empirical correlates of these conditions, i.e., sociodemographics, self-rated health, BMI, 7 NCDs, WHO-DAS (α =.88); level of work/ leisure /transport activities; WHO-QOL (α =.86); and Social Cohesion Scale (α = .75). We first examined the association of these variables with the three binary outcomes, then explored gender-specific correlates for each outcome.

Results:  The weighted sample was 51.3% male; mean age 61.9 ± 9.0 years; 51% had no schooling; 77% were married and 71% lived in rural areas. Fully 26%  reported moderate to severe depressive symptoms; 49% had poor cognitive functioning; and 52% experienced both conditions.  Models for depressive symptoms (R² =.30; gender NS); 2); cognitive impairment (R² =. 27; gender β = -.38, p <.001); and 3) both disorders (R²=.25, gender β =.27, p <.001) were significant at p<.001.  R²values for gender-specific models ranged from .23 to .29 for women (p <.001) and.25 to .33 for men (p <.001).  Women fared worse in all instances except the model for depressive symptoms. Gender-specific models revealed key unique and shared correlates of outcomes.

Implications:  Results show gender disparities in prevalence of depressive symptoms, cognitive decline and both conditions among older adults in India, and in logistic models of cognitive impairment with and without depressive symptoms. Correlates of outcomes in gender-specific models point to key shared and gender-specific health and psychosocial factors for prevention and intervention.