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Tracking Disparities in the Burden of Ischemic Heart Disease Attributable  To Modifiable Risk Factors in 137 Low- and Middle-Income Countries from 2000 to 2017: A Comparative Assessment

44 Pages Posted: 6 Aug 2020

See all articles by Chenran Wang

Chenran Wang

Weifang Medical University - School of Public Health and Management

Chunping Wang

Weifang Medical University - School of Public Health and Management

Yanghua Sun

Soochow University - Center for Genetic Epidemiology and Genomics

Mi Liu

Weifang Medical University - School of Public Health and Management

Juanjuan Liang

Weifang Medical University - School of Public Health and Management

Shiwei Liu

Chinese Center for Disease Control and Prevention (China CDC) - National Center for Chronic and Noncommunicable Disease Control and Prevention

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Abstract

Background: Ischemic heart disease (IHD) is the leading contributor to the global burden of disease attributable to potentially modifiable risk factors, especially in low- and middle-income countries (LMICs). However, the population-attributable fraction (PAF) and burden of IHD due to those risk factors and its epidemiological transition in LMICs remain unclear.

Methods: Under the updated framework of comparative risk assessment (CRA) from the 2017 Global Burden of Disease (GBD) study, PAFs and IHD deaths and disability-adjusted life years (DALYs) attributable to risk clusters and 24 individual risk factors in low-income countries (LICs), lower-middle income countries (Lower MICs), and upper-middle income countries (Upper MICs) were assessed by region, country, sex, and age, over the period 2000–2017, subdivided as 2000–2010 and 2010–2017.

Findings: In 2017, the PAF (%) of IHD deaths was highest in Lower MICs (94.7, 95% uncertainty interval: 92.7–96.3), followed by LICs (94.2, 92.0–96.1) and Upper MICs (93.6, 90.9–95.8). There was an over 10-fold difference between Peru and Uzbekistan in age-standardized rates (per 100,000) of attributable death (42.3 vs. 500.5) and DALY (754.4 vs. 7924.8). Environmental risks accounted for the highest proportion of deaths and DALYs in LICs, while MICs had larger IHD burdens attributable to behavioral and metabolic risks. Dietary risks accounted for the largest proportion of the behavioral burden of IHD among LMICs, of which diets low in nuts and seeds headed the list. High systolic blood pressure and high LDL cholesterol remained the two leading causes of DALYs, with the former leading the rank in 114 countries and the latter in 23 of the 137 countries. A descending trend was observed in the attributable age-standardized mortality rate in LMICs from 2000 to 2017, but its male-to-female ratio showed 9.4%, 13.7%, and 6.8% increases in LICs, Lower MICs, and Upper MICs, respectively, during the same period. Compared with 2000–2010, a slower annual average increase in attributed deaths and DALYs was observed among Lower MICs and Upper MICs from 2010 to 2017, while LICs experienced an opposite increasing trend.

Interpretation: Risk-attributable burden of IHD among LMICs remains high. Considerable heterogeneity was observed in epidemiological transitions among regions and countries. Tailored strategies of mitigating preventable IHD burden associated with modifiable risk factors should be priorities for countries at different economic levels.

Funding Statement: National Natural Science Foundation of China (81872721); National Key R&D Program of China (2017YFC1310902).

Declaration of Interests: We declare no competing interests.

Keywords: Ischemic heart disease, Risk factors, Low- and middle-income countries, Death, Disability-adjusted life years, Temporal trend

Suggested Citation

Wang, Chenran and Wang, Chunping and Sun, Yanghua and Liu, Mi and Liang, Juanjuan and Liu, Shiwei, Tracking Disparities in the Burden of Ischemic Heart Disease Attributable  To Modifiable Risk Factors in 137 Low- and Middle-Income Countries from 2000 to 2017: A Comparative Assessment (4/18/2020). Available at SSRN: https://ssrn.com/abstract=3582740 or http://dx.doi.org/10.2139/ssrn.3582740

Chenran Wang

Weifang Medical University - School of Public Health and Management

Weifang
China

Chunping Wang (Contact Author)

Weifang Medical University - School of Public Health and Management ( email )

Weifang
China

Yanghua Sun

Soochow University - Center for Genetic Epidemiology and Genomics

Mi Liu

Weifang Medical University - School of Public Health and Management

Weifang
China

Juanjuan Liang

Weifang Medical University - School of Public Health and Management

Weifang
China

Shiwei Liu

Chinese Center for Disease Control and Prevention (China CDC) - National Center for Chronic and Noncommunicable Disease Control and Prevention ( email )

Beijing 100050
China

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