TY - JOUR
T1 - Nationwide Geospatial Analysis to Identify Variations in Primary Cardiovascular Risk in Ethiopia
AU - Alemu, Yihun Mulugeta
AU - Bagheri, Nasser
AU - Wangdi, Kinley
AU - Chateau, Dan
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: YMA is supported by the Australia National University Research Scholarship (International). KW is funded by Australian National Health and Medical Research Council Investigator Grants (2008697).
Publisher Copyright:
© The Author(s) 2024.
PY - 2024/11
Y1 - 2024/11
N2 - BACKGROUND: Cardiovascular disease (CVD) varies across regions due to socioeconomic, cultural, lifestyle, healthcare access, and environmental factors.OBJECTIVE: To find geographical variations in 10-year primary CVD risk and assess the impact of contextual factors on CVD risk.METHOD: Data from 2658 Ethiopians aged 40 to 69 years with no previous CVD who participated in a nationally representative World Health Organization (WHO) STEPS survey in 2015 were included in the analysis. The mean 10-year CVD risk for 450 enumeration areas (EA) was used to identify spatial autocorrelation (using Global Moran's
I) and CVD hot spots (using getas-Ord Gi*). Geographically Weighted Regression (GWR) analysis quantified the relationship between mean 10-year CVD risk and climate-related factors across areas.
RESULT: The spatial autocorrelation analysis identified significant spatial variation in the 10-year CVD risk at the EA level, with a global Moran's
I value of 0.016. Statistically significant hot spot areas with 10-year CVD risk were identified in Addis Ababa (the capital), Benishangul Gumuz, SNNPR (Southern Nations, Nationalities, and Peoples' Region), Amhara, Afar, Oromia, and Hareri regions. In a multivariable GWR analysis, average water vapor pressure was a statistically significant explanatory variable for the geographical variations in 10-year CVD risk.
CONCLUSION: Hot spot areas for 10-year CVD risk were identified across numerous country regions rather than concentrated in a specific region. Alongside these hot spot areas, regions with a higher annual water vapor pressure (humidity) were identified as geographical targets for CVD prevention.
AB - BACKGROUND: Cardiovascular disease (CVD) varies across regions due to socioeconomic, cultural, lifestyle, healthcare access, and environmental factors.OBJECTIVE: To find geographical variations in 10-year primary CVD risk and assess the impact of contextual factors on CVD risk.METHOD: Data from 2658 Ethiopians aged 40 to 69 years with no previous CVD who participated in a nationally representative World Health Organization (WHO) STEPS survey in 2015 were included in the analysis. The mean 10-year CVD risk for 450 enumeration areas (EA) was used to identify spatial autocorrelation (using Global Moran's
I) and CVD hot spots (using getas-Ord Gi*). Geographically Weighted Regression (GWR) analysis quantified the relationship between mean 10-year CVD risk and climate-related factors across areas.
RESULT: The spatial autocorrelation analysis identified significant spatial variation in the 10-year CVD risk at the EA level, with a global Moran's
I value of 0.016. Statistically significant hot spot areas with 10-year CVD risk were identified in Addis Ababa (the capital), Benishangul Gumuz, SNNPR (Southern Nations, Nationalities, and Peoples' Region), Amhara, Afar, Oromia, and Hareri regions. In a multivariable GWR analysis, average water vapor pressure was a statistically significant explanatory variable for the geographical variations in 10-year CVD risk.
CONCLUSION: Hot spot areas for 10-year CVD risk were identified across numerous country regions rather than concentrated in a specific region. Alongside these hot spot areas, regions with a higher annual water vapor pressure (humidity) were identified as geographical targets for CVD prevention.
KW - Humans
KW - Middle Aged
KW - Cardiovascular Diseases/epidemiology
KW - Ethiopia/epidemiology
KW - Female
KW - Male
KW - Adult
KW - Aged
KW - Spatial Analysis
KW - Heart Disease Risk Factors
KW - Risk Factors
KW - Spatial Regression
KW - Socioeconomic Factors
KW - geospatial analysis
KW - cardiovascular risk prediction
KW - climate history data
KW - geographical variations
KW - WHO STEPS data
UR - http://www.scopus.com/inward/record.url?scp=85208602824&partnerID=8YFLogxK
U2 - 10.1177/21501319241288312
DO - 10.1177/21501319241288312
M3 - Article
C2 - 39498891
SN - 2150-1319
VL - 15
SP - 1
EP - 15
JO - Journal of primary care & community health
JF - Journal of primary care & community health
ER -