Do people with different sociodemographic backgrounds value their health differently? Evaluating the role of positional objectivity

ObjectiveThe fundamental disconnect between the actual and the perceived health of an individual raises considerable skepticism on the self-reported health data as it may be confounded by an individual’s socio-economic status. In this light, the present study aims to assess if people with different sociodemographic backgrounds value their health differently.MethodsThe health-state valuation using time-trade off was performed in a cross-sectional survey among a representative sample of 2,311 adults from India. Individuals were selected using a multistage stratified random sampling from five Indian states to elicit their present health-state, and to perform the health-state valuation exercise using computer assisted personal interviewing. A single block of standardized health-states was valued by multiple individuals, each belonging to different socio-demographic group. The difference in the valuation of health was assessed using bivariate analysis. The impact of different sociodemographic factors on the health-state valuation was evaluated using Tobit regression model.ResultsDifferences in the valuation of health were observed among different groups of age, religion, family type, state of residence, substance abuse, presence of ailments at the time of valuation, and number of dependent members in the household. Even after controlling for the severity of the administered health states, factors having a significant association with the valuation of health are age, religion, state of residence, substance abuse, family type, number of dependent members in the household, and presence of chronic or both acute and chronic ailments. Younger individuals place a higher value to their health as compared to their older counterparts. As compared to a healthy individual, a person with ailments rates the same health-state as worse.ConclusionInequalities in self-reported ill-health cannot be attributed to positional objectivity; age, religion, state of residence, substance abuse, family type, dependents, and ailments impact individual health valuation

Evaluating efficiency and equity of prevention and control strategies for rheumatic fever and rheumatic heart disease in India: an extended cost-effectiveness analysis

Background: There is a dearth of evidence on the cost-effectiveness of a combination of population-based primary, secondary, and tertiary prevention and control strategies for rheumatic fever and rheumatic heart disease. The present analysis evaluated the cost-effectiveness and distributional effect of primary, secondary, and tertiary interventions and their combinations for the prevention and control of rheumatic fever and rheumatic heart disease in India. Methods: A Markov model was constructed to estimate the lifetime costs and consequences among a hypothetical cohort of 5-year-old healthy children. Both health system costs and out-of-pocket expenditure (OOPE) were included. OOPE and health-related quality-of-life were assessed by interviewing 702 patients enrolled in a population-based rheumatic fever and rheumatic heart disease registry in India. Health consequences were measured in terms of life-years and quality-adjusted life-years (QALY) gained. Furthermore, an extended cost-effectiveness analysis was undertaken to assess the costs and outcomes across different wealth quartiles. All future costs and consequences were discounted at an annual rate of 3%. Findings: A combination of secondary and tertiary prevention strategies, which had an incremental cost of ₹23 051 (US$30) per QALY gained, was the most cost-effective strategy for the prevention and control of rheumatic fever and rheumatic heart disease in India. The number of rheumatic heart disease cases prevented among the population belonging to the poorest quartile (four cases per 1000) was four times higher than the richest quartile (one per 1000). Similarly, the reduction in OOPE after the intervention was higher among the poorest income group (29·8%) than among the richest income group (27·0%). Interpretation: The combined secondary and tertiary prevention and control strategy is the most cost-effective option for the management of rheumatic fever and rheumatic heart disease in India, and the benefits of public spending are likely to be accrued much more by those in the lowest income groups. The quantification of non-health gains provides strong evidence for informing policy decisions by efficient resource allocation on rheumatic fever and rheumatic heart disease prevention and control in India