Abstract
Chronic noncommunicable diseases (NCDs) are now prevalent in many low- and middle-income countries and confer a heightened risk of disability. It is unclear how public health programs can identify the older adults at highest risk of disability related to NCDs within diverse developing country populations. We studied nationally representative survey data from 7,150 Indian adults older than 50 years of age who participated in the World Health Organization Study on Global Aging and Adult Health (2007-2010) to identify population subgroups who are highly disabled. Using machine-learning algorithms, we identified sociodemographic correlates of disability. Although having 2 or more symptomatic NCDs was a key correlate of disability, the prevalence of symptomatic, undiagnosed NCDs was highest among the lowest 2 wealth quintiles of Indian adults, contrary to prior hypotheses of increased NCDs with wealth. Women and persons from rural populations were also disproportionately affected by nondiagnosed NCDs, with high out-of-pocket health care expenditures increasing the probability of remaining symptomatic from NCDs. These findings also indicate that NCD prevalence surveillance studies in low- and middle-income countries should expand beyond self-reported diagnoses to include more extensive symptom- and examination-based surveys, given the likely high rate of surveillance bias due to barriers to diagnosis among vulnerable populations.