ABSTRACT
Introduction: Catastrophic health expenditure during COVID-19 hospitalization has altered the economic picture of households, especially in low resource settings with high rates of COVID-19 infection. This study aimed to estimate the out of pocket (OOP) expenditure and the proportion of households that incurred catastrophic health expenditure due to COVID-19 hospitalization in Kerala, South India. Materials and Methods: A cross-sectional study was conducted among a representative sample of 155 COVID-19 hospitalized patients in Kottayam district over four months, using a pretested interview schedule. The direct medical and non-medical costs incurred by the study participants during hospitalization and the total monthly household expenditure were obtained from the respective COVID-19 affected households. Catastrophic health expenditure was defined as direct medical expenditure exceeding 40% of the household's capacity to pay. Results: From the study, median and mean OOP expenditure was obtained as USD 93.57 and USD 502.60 respectively. The study revealed that 49.7% of households had catastrophic health expenditure, with 32.9% having incurred distress financing. Multivariate analysis revealed being below poverty line, hospitalization in private healthcare facility, and presence of co-morbid conditions as significant determinants of catastrophic health expenditure. Conclusion: High levels of catastrophic health expenditure and distress financing revealed by the study have unveiled major unaddressed challenges in the road to universal health coverage.
ABSTRACT
BACKGROUND: The distribution of body fat and its variation is of great importance in determining the pathogenesis of insulin resistance. Central obesity has been recognized as an independent risk factor for diabetes. The objective of the study was to evaluate the predictive accuracy of various anthropometric measures of body fat in determining impaired glucose tolerance (IGT) or prediabetes among South Indian population. METHODOLOGY: This was a community-based comparative cross-sectional study where the anthropometric measures of a representative sample of 171 individuals with glycosylated hemoglobin (HbA1c) in the range for IGT were compared with age- and gender-matched controls with HbA1c in the normal range. The predictive accuracy of the various anthropometric measures of obesity to identify individuals with IGT was estimated using the area under the receiver operating characteristic (ROC) curve. RESULTS: Patients with IGT in both genders had significantly higher BMI, waist circumference (WC), neck circumference (NC), and waist-to-height ratio (WHtR). ROC analysis revealed WHtR in females and NC among males to have the largest area under the curve for predicting IGT. In both genders, WC, WHtR, and NC had better predictive accuracy for prediabetes as compared to BMI and waist-to-hip ratio (WHR). CONCLUSION: It is suggested that the WHtR and WC are better screening tools for prediabetes in comparison to BMI and WHR among the South Indian population.
