District-Level Inequalities in Hypertension among Adults in Indonesia: A Cross-Sectional Analysis by Sex and Age Group

Background: An estimated 1.28 billion adults 30–79 years old had hypertension globally in 2021, of which two-thirds lived in low- and middle-income countries (LMICs). Previous studies on geographic and socioeconomic inequalities in hypertension among adults have limitations: (a) most studies used individual-level data, while evidence from locality-level data is also crucial for policymaking; (b) studies from LMICs are limited. Thus, our study examines geographic and socioeconomic inequalities in hypertension among adults across districts in Indonesia. Methods: We combined geospatial and quantitative analyses to assess the inequalities in hypertension across 514 districts in Indonesia. Hypertension data were obtained from the Indonesian Basic Health Survey (Riskesdas) 2018. Socioeconomic data were obtained from the World Bank. Six dependent variables included hypertension prevalence among all adults (18+ years), male adults, female adults, young adults (18–24 years), adults (25–59 years), and older adults (60+ years). Results: We also found significant geographic and socioeconomic inequalities in hypertension among adults across 514 districts. All hypertension indicators were higher in the most developed region than in the least developed region. Districts in the Java region had up to 50% higher prevalence of hypertension among all adults, males, females, young adults, adults, and older adults. Notably, districts in the Kalimantan region had the highest prevalence of hypertension, even compared to those in Java. Moreover, income level was positively associated with hypertension; the wealthiest districts had higher hypertension than the poorest districts by up to 30%, but only among males and older adults were statistically significant. Conclusions: There were significant inequalities in hypertension among adults across 514 districts in the country. Policies to reduce such inequalities may need to prioritize more affluent urban areas and rural areas with a higher burden.