Background:
A key aim of Universal Health Coverage (UHC) is to protect individuals and households against the financial risk of illness. Large-scale health insurance expansions are therefore a central focus of the UHC agenda. Importantly, however, health insurance does not protect against a key dimension of financial risk associated with illness: forgone wage income (due to short-term disability). In this paper, we quantify the economic burden of illness in India attributable--separately--to wage loss and to medical care spending, as well as differences in them across the socio-economic distribution.
Methods:
We use data from two Indian longitudinal household surveys: (i) the Village Dynamics in South Asia (VDSA) survey (1,350 households surveyed every month for 60 months between 2010 and 2015) and (ii) the Indian Human Development Survey (IHDS) (more than 40,000 households surveyed in 2005 and again in 2011). The VDSA allows us to study the economic dynamics of illness using high-frequency observations, and the IHDS allows us to confirm our findings in a nationally-representative sample. Both contain individual- and household-level information about illness, wage income, and medical spending over time. We use longitudinal variation in illness to estimate regression models of economic burden separately for wage loss and medical care spending across the socio-economic distribution. Our regression models include a series of fixed effects that control for differences in time-invariant household (or individual) characteristics and time-varying factors common across households.
Findings:
1,184 households (88%) in the VDSA sample reported an episode of illness over 60 months, and 15770 households (40%) in the IHDS reported an illness in the preceding year. In the VDSA sample, on average, a day of illness was associated with a reduction in monthly per capita wage income of Rs 77 [95% CI -99 to -57] and an increase in monthly per capita medical spending of Rs 126 [95% CI 110-142]. Variation across the socio-economic distribution was substantial. Among the poorest households, wage loss due to illness is roughly 15% of total household spending--nearly three times greater than medical spending. Alternatively, among the most affluent households, wage loss is less than 5% of total household spending--and only one-third of medical spending. Put differently, wage loss accounts for more than 80% of the total economic burden of illness among the poorest households, but only about 20% of the economic burden of illness among the most affluent. Estimates from the IHDS sample show that this socio-economic gradient is present in the Indian population generally.
Interpretation:
Wage loss accounts for a substantial share of the total economic burden of illness in India--and disproportionately so among the poorest households. If Universal Health Coverage truly aims to protect households against the financial risk of illness--particularly poor households, the inclusion of wage loss insurance or another illness-related income replacement benefit is needed.