Health insurance coverage and its determinants among middle-income households in Urban Puducherry: A mixed methods study.

BACKGROUND: In India, there exists public health insurance for government employees and poor people. However, the middle-income households (MIHs) remain neglected. OBJECTIVES: The study was conducted to find out the coverage of health insurance and its determinants among MIH. METHODS: It was a community-based sequential exploratory mixed methods study. Group interview and key informant interview were conducted among various stakeholders related to insurance coverage. The quantitative survey was done among 400 randomly selected head of households (HoHs) in an urban area of Puducherry. Manual content analysis was done for qualitative data. Generalized linear model with Poisson distribution was used to calculate the adjusted prevalence ratio (aPR) using Stata software. RESULTS: The coverage of health insurance among the MIH was 41% (95% confidence interval [CI]: 36.1-50). The major reasons reported for not having insurance were poor financial status (63.7%) and lack of felt needs (59.4%). The significant determinants for the lack of health insurance among MIH were unskilled occupation (aPR: 1.62, 95% CI: 1.13-2.34) and lower education status (aPR: 1.79, 95% CI: 1.22-2.64) of HoH and less monthly family income (aPR: 2.19, 95% CI: 1.18-4.08). CONCLUSION: The health insurance coverage of 41% among MIH is better despite the fact that there was no public insurance scheme available for them in Puducherry. The MIH with the identified determinants might be considered in future for including them under publicly sponsored health insurance scheme.

Constructing Practical and Realistic Asset-Based Socioeconomic Status Assessment Scale Using Principal Component Analysis for Urban Population of Puducherry, India.

BACKGROUND: Socioeconomic status (SES) is a key determinant of health. However, ascertaining the SES in developing countries is really challenging. Hence, we decided to develop an asset-based simple and rational SES tool for urban population of Puducherry and compare it with Modified Kuppuswamy's (MK) scale. MATERIALS AND METHODS: Sequential mixed methods design was used. The list of local household assets to determine SES was created based on group interviews with stakeholders and review of literature. Then, survey was carried out among 500 urban households by trained medical interns after obtaining informed consent. EpiCollect-5, mobile-based software, was used to capture data. Principal component analysis (PCA) was carried out to construct a wealth index using SPSS version 24. The assets included in the final PCA were ranked based on their contribution to the index by linear regression. RESULTS: The eigenvalue for the first principal component was 6.7 accounting for 33.6% of the variance in the original data. Finally, reduced 10-item-based SES scale was created and scoring system was formulated based on regression coefficient. The weighted kappa statistics and correlation coefficient measure of reliability between household quintiles on 20-item and 10-item reduced SES tool were 0.77 and 0.95, respectively. There was a moderate correlation between SES obtained from MK scale and newly constructed scale. CONCLUSIONS: The newly devised SES scale is context specific, reliable, easy to administer, and quick to ascertain the SES and thus can be used for a similar context in future health research.