Reporting heterogeneity in the measurement of hypertension and diabetes in India

Public health research in India frequently depends on self-reported data, which is usually a compromised method. Policies and programs based upon such data may not be efficient enough to estimate the actual burden of the diseases. Previous studies have looked at the issues of discrepancies between self-reported and measured estimates. However, the majority of them have failed to examine the reasons for such disparities. This pivotal research gap is decoded in this study, which explores the determinants of heterogeneity between self-reported and clinically-diagnosed hypertension and diabetes.

The study utilizes the data from the fourth round of the District Level Household and Facility Survey, 2012–13, and has considered 860,501 nationally representative samples of respondents aged 18 years and above from 18 demographically developed states of India. Age-adjusted prevalence rates of hypertension/diabetes and a multinomial logistic regression model are utilized to draw inferences from the data.

The findings bring out heterogeneity by comparing respondents’ Clinical, Anthropometric, and Biochemical (CAB) test results with their self-reported data. Heterogeneity included respondents who self-reported themselves as not suffering from hypertension/diabetes while their CAB test indicated otherwise, and those who had self-reported being hypertensive/ diabetic even though their CAB test data information proved otherwise. Additionally, respondent’s age, sex, wealth, and occupation are the major determinants of heterogeneous reporting.

The study suggests that the estimates obtained by self-reporting underrate the actual scenario. Thus, large-scale surveys should focus on collecting data using clinical diagnostic tools to access the actual burden of disease in the community.