OBJECTIVES: In India, both communicable and non-communicable diseases have been argued to disproportionately affect certain socioeconomic strata of the population. Using the 60th (2004) and 71st (2014) rounds of the National Sample Survey, this study assessed the balance between infectious diseases and cardiovascular diseases (CVD) from 2004 to 2014, as well as changes in the disease burden in various socioeconomic and demographic subpopulations. METHODS: Prevalence rates, hospitalization rates, case fatality rates, and share of in-patients deaths were estimated to compare the disease burdens at these time points. Logistic regression and multivariate decomposition were used to evaluate changes in disease burden across various socio-demographic and socioeconomic groups. RESULTS: Evidence of stagnation in the infectious disease burden and rapid increase in the CVD burden was observed. Along with the drastic increase in case fatality rate, share of in-patients deaths became more skewed towards CVD from 2004 to 2014. Logistic regression analysis demonstrated a significant shift of the chance of succumbing to CVD from the privileged class, comprising non-Scheduled Castes and Tribes, more highly educated individuals, and households with higher monthly expenditures, towards the underprivileged population. Decomposition indicated that a change in the probability of suffering from CVD among the subcategories of age, social groups, educational status, and monthly household expenditures contributed to the increase in CVD prevalence more than compositional changes of the population from 2004 to 2014. CONCLUSIONS: This study provides evidence of the ongoing tendency of CVD to occur in older population segments, and also confirms the theory of diffusion, according to which an increased probability of suffering from CVD has trickled down the socioeconomic gradient.
Cardiovascular Diseases* ; Communicable Diseases ; Diffusion ; Educational Status ; Family Characteristics ; Health Expenditures ; Hospitalization ; Humans ; India* ; Logistic Models ; Mortality ; Population Groups ; Prevalence ; Social Class ; Socioeconomic Factors