Background: Cardiovascular diseases (CVDs) accounted for over 17 million deaths and 353 million disabilityadjusted life years lost in 2016. The risk factors are also high and increasing with high blood pressure, smoking, and high body mass index contributed to up to 212 million disability-adjusted life years in 2016. To help reduce the burden, it is crucial to understand the geographic and socioeconomic disparities in CVD risk factors. Methods: Employing both geospatial and quantitative analyses, we analyzed the disparities in the prevalence of smoking, physical inactivity, obesity, hypertension, and diabetes in Indonesia. CVD data was from Riskesdas 2018, and socioeconomic data was from the World Bank. Results: Our findings show a very high prevalence of CVD risk factors with the prevalence of smoking, physical activity, obesity, hypertension ranged from 28 to 33%. Results also show the geographic disparity in CVD risk factors in all five Indonesian regions. Moreover, results show socioeconomic disparity with the prevalence of obesity, hypertension, and diabetes are higher among urban and the richest and most educated districts while that physical inactivity and smoking is higher among rural and the least educated districts. Conclusion: The CVD burden is high and increasing in particularly among urban areas and districts with higher income and education levels. While the government needs to continue tackling the persistent burden from maternal mortality and infectious diseases, they need to put more effort into the prevention and control of CVDs and their risk factors.
BACKGROUND: With 61.4 million smokers in 2018, Indonesia makes a significant contribution to the global number of smokers. The latest data show that smoking is increasingly common in youth.OBJECTIVE: To examine the density of cigarette retailers around formal and informal educational facilities in Indonesia.METHODS: We employed geospatial and quantitative analyses using data on cigarette retailers (from surveys during July–August 2019) and educational facilities in Depok City. Data analyses, in ArcMap 10.6 and Stata v15, compared the density within 100 m and 100–200 m from the facility.RESULTS: We found a 40% higher density of cigarette retailers in areas close to educational facilities. This high density is similar between formal (i.e., primary, junior high, and senior high schools) and informal educational facilities (i.e., early years education centers and mosques). Moreover, compared to the average, the density is higher near primary schools and senior high schools.CONCLUSION: There is a higher density of cigarette retailers around formal and informal educational facilities in Indonesia. This evidence confirms there is a need to regulate cigarette retailers near educational facilities, to enforce the ban on sale to minors and to ban product displays at retailers.
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