We observed substantial variations in household health spending at the state and village levels compared with India's districts and regions. The large variation in CHS attributable to states indicates interstate inequality in the accessibility to and cost of health care. Our findings suggest that contextual factors at the macro and micro political units are important to reduce India's household health spending and CHS.
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.
Background
In India, breast and cervical cancers account for two-fifths of all cancers and are predominantly prevalent among women in the reproductive age group. The Government of India recommended screening of breast and cervical cancer among women aged 30 years and over. This study examines the socio-economic and regional variations of breast and cervical screening among Indian women in the reproductive age.
Methods
A full sample of 707,119 women aged 15–49 and a sub-sample of 357,353 women aged 30–49 from National Family Health Survey-5 (2019-21) were used in the analysis. Self-reported ever screening for breast and cervical cancer for women aged 15–49 and women aged 30–49 were outcome variables. A set of socio-economic and risk factors associated with breast and cervical cancer screening were used as the predictors. Logistic regression was used to understand the significant correlates of cancer screening and, concentration index and concentration curve were used to assess the socio-economic inequality in breast and cervical cancer screening.
Results
The proportion of breast and cervical cancer screening among women aged 30–49 were 877 and 1965 per 100,000 women respectively. Cancer screening was lower among women who were poor, young, had lower educational attainment and resided in rural areas. The concentration index was 0.2 for ever screening of breast cancer and 0.15 for cervical cancer among women aged 30–49 years. The concertation curve for screening of both breast and cervical cancers was pro-rich. Women with higher educational attainment [OR:1.46, 95% CI: 1.31–1.62], aged 40–49 years [OR:1.35; 95% CI: 1.28–1.43], resided in the western [OR:1.62; 95% CI:1.4–1.87] or southern [OR:6.66; 95% CI:5.93–7.49] region had significantly higher odds of up taking either of the screening. The pattern of breast and cervical cancer screening among women aged 15–49 was similar to that of women 30–49.
Conclusion
The overall proportion of cancer screening among women in 30–49 age group is low in India. Early screening and treatment can reduce the burden of these cancers. Creating awareness and providing knowledge on cancer could be a key strategy for reducing the burden of breast and cervical cancers among women in the reproductive age in India.
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