| Multilevel population and socioeconomic variation in health insurance coverage in India |
| Authors: |
Pijush Kanti Khan, Jessica M. Perkins, Rockli Kim, Sanjay K. Mohanty, Sankaran V. Subramanian |
| Source: |
Tropical Medicine and International Health, 26(10); DOI: 10.1111/tmi.13645 |
| Topic(s): |
Health equity
Inequality
|
| Country: |
Asia
India
|
| Published: |
OCT 2021 |
| Abstract: |
Objectives: This study explores population-level variation in different types of health insurance coverage in India. We aimed to estimate the extent to which contextual factors at community, district, and state levels may contribute to place-based inequalities in coverage after accounting for household-level socioeconomic factors.
Methods: We used data from the 2015-2016 National Family Health Survey in India, which provides the most recent and comprehensive information available on reports of different types of household health insurance coverage. We used multilevel regression models to estimate the relative contribution of different population levels to variation in coverage by national, state, and private health insurance schemes.
Results: Among 601,509 households in India, 29% reported having coverage in 2015-2016. Variation in each type of coverage existed between population levels before and after adjusting for differences in the distribution of household socioeconomic and demographic factors. For example, the state level accounted for 36% of variation in national scheme coverage and 41% of variation in state scheme coverage after adjusting for household characteristics. In contrast, the community level was the largest contextual source of variation in private insurance coverage (accounting for 24%). Each type of coverage was associated with higher socioeconomic status and urban location.
Conclusions: Contextual factors at community, district, and state levels contribute to variation in household health insurance coverage even after accounting for socioeconomic and demographic factors. Opportunities exist to reduce disparities in coverage by focusing on drivers of place-based differences at multiple population levels. Future research should assess whether new insurance schemes exacerbate or reduce place-based disparities in coverage.
Keywords: India; NFHS; catastrophic spending; health insurance; health protection; multilevel modeling. |
| Web: |
https://pubmed.ncbi.nlm.nih.gov/34181806/ |
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