Abstract

Abstract Background The sustainable development goal number 3, target 4 (SDG 3.4) seeks by 2030, a 30% reduction in four premature chronic disease mortality (4CHD) from 2015 values. Since the implementation of SDG 3.4 in 2016, the highest risk of dying from CHD was observed in low and lower-income countries mainly in Africa. This study examined the relationship between contextual factors and diabetes-related deaths as an example of the 4CHD; to enable an improved contextualized evidence-based approach, to attain in part the SDG 3.4 among United Nations Member States in Africa region (UNMSAFR). Methods Country-level data was retrieved for post SDG initiative years (2016-2019) from multiple publicly available data sources for 32 selected UNMSAFR located in the International Diabetes Federation (IDF) East and West Africa Region. Multiple linear regression was employed to ascertain the association between diabetes-related deaths in individuals 20-79 years in UNMSAFR and contextual factors identified in the SDGs framework. Two regression models were tested by conducting unweighted and weighted data analysis. Results The unweighted analysis showed that diabetes-related deaths in individuals 20-79 years/1,000 varied across the selected UNMSAFR in IDF East and West Regions (n = 31), with a range of 0.06 - 0.48/1,000 and an average of 0.24/1,000. Contextual factors, i.e., unemployment rate and geographical region explained 23% variability in diabetes-related deaths across the selected UNMSAFR. However, in the weighted data analysis, voice and accountability explained 47% variability in diabetes-related deaths across selected UNMSAFR in IDF East and West Region (n = 32). Conclusions Contextual factors such as unemployment rate, geographical region, and voice and accountability (governance) were associated with diabetes mortality; identifying that salient modifiable features can inform targeted interventions and policies to reduce premature CHD mortality. Key messages Contextual factors should be considered in policies and interventions for a comprehensive approach to premature CHD mortality reduction. Spatial clustering of CHD is critical for region interventions.

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