South Asian Journal of Social Studies and Economics

Objectives: This study derives a composite frailty index for adults aged 50 and above in India, examines the distribution of frailty conditions across socioeconomic and demographic strata, and estimates the independent effects of background characteristics on frailty using multivariate analysis.

Study Design: Cross-sectional secondary analysis of a nationally representative household survey. The cross-sectional design provides a baseline prevalence estimate but does not permit causal inference; findings should be interpreted accordingly.

Place and Duration of Study: Six states of India (Assam, Karnataka, Maharashtra, Rajasthan, Uttar Pradesh, and West Bengal), using WHO Study on Global Ageing and Adult Health (SAGE) India Wave 1, 2007. These six states were selected by WHO-SAGE to represent India's geographic, linguistic, and socioeconomic diversity, though they do not constitute a nationally representative sample in the strict probability sense.

Methodology: Data from 6,560 respondents aged 50 and above were analysed. A modified frailty index comprising seven deficit indicators — low grip strength, slowness, low body mass index, low physical activity, cognitive limitation, psychological limitation, and exhaustion — was constructed. This index adapts the Fried phenotype to SAGE India's measurement instruments; key differences from the standard Fried criteria are explicitly acknowledged in the methodology. Participants were classified as robust (0 deficits), pre-frail (1–2), intermediate frail (3–4), or frail (5–7). Multinomial logistic regression was used to estimate socioeconomic determinants of frailty.

Results: Frailty prevalence was 15.5% overall, rising sharply with age from 7.1% in the 50–59 group to 50.8% in those aged 80 and above. Female sex, no formal education, low wealth, rural residence, and scheduled caste/tribe status were consistently associated with higher frailty burden. Multinomial logistic regression confirmed that advanced age, low education, and low wealth quintile were the strongest predictors of frailty, with statistically significant odds ratios at p < 0.01.

Conclusion: Frailty is prevalent and strongly socially patterned among older Indians. These findings call for the integration of frailty screening into India's primary healthcare infrastructure, and for targeted nutritional and physical rehabilitation programmes directed at low-income, low-education older adults in rural settings. Targeted preventive strategies addressing nutritional deficiency, physical deconditioning, and socioeconomic disadvantage are urgently needed to mitigate the growing burden of frailty in India's ageing population.