Y Commodore-Mensah1, C Agyemang2, J A Aboagye3, J B Echouffo-Tcheugui4, E Beune2, L Smeeth5, K Klipstein-Grobusch6, I Danquah7, M Schulze8, D Boateng9, K A C Meeks10, S Bahendeka11, R S Ahima12. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Johns Hopkins School of Nursing, MD, United States. Electronic address: ycommod1@jhmi.edu. 2. Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, The Netherlands. 3. Department of Surgery, Howard University, Washington, District of Columbia, United States. 4. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States. 5. Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, United Kingdom. 6. Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. 7. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany; Charité - Universitaetsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Social Medicine, Epidemiology and Health Economics, Berlin, Germany. 8. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany; Institute of Nutritional Sciences, University of Potsdam, Nuthetal, Germany. 9. Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. 10. Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, The Netherlands; Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States. 11. MKPGMS-Uganda Martyrs University, Kampala, Uganda. 12. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Johns Hopkins School of Nursing, MD, United States; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Abstract
BACKGROUND: The association between anthropometric variables and cardiovascular disease (CVD) risk among Africans is unclear. We examined the discriminative ability of anthropometric variables and estimate cutoffs for predicting CVD risk among Africans. METHODS: The Research on Obesity and Diabetes among African Migrants (RODAM) study was a multisite cross-sectional study of Africans in Ghana and Europe. We calculated AHA/ACC Pooled Cohort Equations (PCE) scores for 3661 participants to ascertain CVD risk, and compared a body shape index (ABSI), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), Relative Fat Mass (RFM), and Waist to Height Ratio (WHtR). Logistic regression and receiver operating curve analyses were performed to derive cutoffs for identifying high predicted CVD risk (PCE score ≥7.5%). RESULTS: Among men, WC (adjusted Odds Ratio (aOR): 2.25, 95% CI; 1:50-3:37) was strongly associated with CVD risk. Among women, WC (aOR: 1.69, 95% CI: 1:33-2:14) also displayed the strongest association with CVD risk in the BMI-adjusted model but WHR displayed the strongest fit. All variables were superior discriminators of high CVD risk in men (c-statistic range: 0.887-0.891) than women (c-statistic range: 0.677-0.707). The optimal WC cutoff for identifying participants at high CVD risk was 89 cm among men and identified the most cases (64%). Among women, the recommended WC cutoff of 94 cm or WHR cutoff of 0.90 identified the most cases (92%). CONCLUSIONS: Anthropometric variables were stronger discriminators of high CVD risk in African men than women. Greater WC was associated with high CVD risk in men while WHR and WC were associated with high CVD risk in women.
BACKGROUND: The association between anthropometric variables and cardiovascular disease (CVD) risk among Africans is unclear. We examined the discriminative ability of anthropometric variables and estimate cutoffs for predicting CVD risk among Africans. METHODS: The Research on Obesity and Diabetes among African Migrants (RODAM) study was a multisite cross-sectional study of Africans in Ghana and Europe. We calculated AHA/ACC Pooled Cohort Equations (PCE) scores for 3661 participants to ascertain CVD risk, and compared a body shape index (ABSI), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), Relative Fat Mass (RFM), and Waist to Height Ratio (WHtR). Logistic regression and receiver operating curve analyses were performed to derive cutoffs for identifying high predicted CVD risk (PCE score ≥7.5%). RESULTS: Among men, WC (adjusted Odds Ratio (aOR): 2.25, 95% CI; 1:50-3:37) was strongly associated with CVD risk. Among women, WC (aOR: 1.69, 95% CI: 1:33-2:14) also displayed the strongest association with CVD risk in the BMI-adjusted model but WHR displayed the strongest fit. All variables were superior discriminators of high CVD risk in men (c-statistic range: 0.887-0.891) than women (c-statistic range: 0.677-0.707). The optimal WC cutoff for identifying participants at high CVD risk was 89 cm among men and identified the most cases (64%). Among women, the recommended WC cutoff of 94 cm or WHR cutoff of 0.90 identified the most cases (92%). CONCLUSIONS: Anthropometric variables were stronger discriminators of high CVD risk in African men than women. Greater WC was associated with high CVD risk in men while WHR and WC were associated with high CVD risk in women.
Authors: Sanda Umar Ismail; Evans Atiah Asamane; Hibbah Araba Osei-Kwasi; Daniel Boateng Journal: Int J Environ Res Public Health Date: 2022-03-05 Impact factor: 3.390