Shivani A Patel1, Mohammed K Ali2, Dewan Alam3, Lijing L Yan4, Naomi S Levitt5, Antonio Bernabe-Ortiz6, William Checkley7, Yangfeng Wu8, Vilma Irazola9, Laura Gutierrez9, Adolfo Rubinstein9, Roopa Shivashankar10, Xian Li11, J Jaime Miranda12, Muhammad Ashique Haider Chowdhury13, Ali Tanweer Siddiquee13, Thomas A Gaziano14, M Masood Kadir15, Dorairaj Prabhakaran10. 1. Hubert Department of Global Health, Emory University, Atlanta, GA, USA, and the Centre for Control of Chronic Conditions, New Delhi, India. Electronic address: s.a.patel@emory.edu. 2. Hubert Department of Global Health, Emory University, Atlanta, GA, USA, and the Centre for Control of Chronic Conditions, New Delhi, India. 3. Centre for Global Health Research, Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada, and Faculty of Health Sciences, York University, Toronto, Ontario, Canada. 4. The George Institute for Global Health at Peking University Health Science Center, Beijing, China; Duke Global Health Institute, and Global Health Research Center, Duke Kunshan University, Kunshan, China. 5. Chronic Disease Initiative for Africa (CDIA), University of Cape Town, Cape Town, South Africa; Division of Diabetic Medicine and Endocrinology, University of Cape Town, Cape Town, South Africa. 6. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru. 7. Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD, USA. 8. The George Institute for Global Health at Peking University Health Science Center, Beijing, China; Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing, China. 9. South American Center of Excellence for Cardiovascular Health (CESCAS), Institute for Clinical Effectiveness and Health Policy (IECS) Buenos Aires, Argentina. 10. Public Health Foundation of India (PHFI), the Centre for Chronic Disease Control, and the Centre for Control of Chronic Conditions, New Delhi, India. 11. The George Institute for Global Health at Peking University Health Science Center, Beijing, China. 12. CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru. 13. Chronic Non-Communicable Disease Unit (CNCDU), Center for Equity and Health Systems (CEHS), ICDDR, Dhaka, Bangladesh. 14. Brigham & Women's Hospital, Harvard School of Public Health, Harvard University, Cambridge, MA, USA; Division of Cardiovascular Medicine Brigham & Women's Hospital, Boston, MA, USA. 15. Department of Community Health Sciences, The Aga Khan University, Karachi, Pakistan.
Abstract
BACKGROUND: The implications of rising obesity for cardiovascular health in middle-income countries has generated interest, in part because associations between obesity and cardiovascular health seem to vary across ethnic groups. OBJECTIVE: We assessed general and central obesity in Africa, East Asia, South America, and South Asia. We further investigated whether body mass index (BMI) and waist circumference differentially relate to cardiovascular health; and associations between obesity metrics and adverse cardiovascular health vary by region. METHODS: Using baseline anthropometric data collected between 2008 and 2012 from 7 cohorts in 9 countries, we estimated the proportion of participants with general and central obesity using BMI and waist circumference classifications, respectively, by study site. We used Poisson regression to examine the associations (prevalence ratios) of continuously measured BMI and waist circumference with prevalent diabetes and hypertension by sex. Pooled estimates across studies were computed by sex and age. RESULTS: This study analyzed data from 31,118 participants aged 20 to 79 years. General obesity was highest in South Asian cities and central obesity was highest in South America. The proportion classified with general obesity (range 11% to 50%) tended to be lower than the proportion classified as centrally obese (range 19% to 79%). Every standard deviation higher of BMI was associated with 1.65 and 1.60 times higher probability of diabetes and 1.42 and 1.28 times higher probability of hypertension, for men and women, respectively, aged 40 to 69 years. Every standard deviation higher of waist circumference was associated with 1.48 and 1.74 times higher probability of diabetes and 1.34 and 1.31 times higher probability of hypertension, for men and women, respectively, aged 40 to 69 years. Associations of obesity measures with diabetes were strongest in South Africa among men and in South America among women. Associations with hypertension were weakest in South Africa among both sexes. CONCLUSIONS: BMI and waist circumference were both reasonable predictors of prevalent diabetes and hypertension. Across diverse ethnicities and settings, BMI and waist circumference remain salient metrics of obesity that can identify those with increased cardiovascular risk.
BACKGROUND: The implications of rising obesity for cardiovascular health in middle-income countries has generated interest, in part because associations between obesity and cardiovascular health seem to vary across ethnic groups. OBJECTIVE: We assessed general and central obesity in Africa, East Asia, South America, and South Asia. We further investigated whether body mass index (BMI) and waist circumference differentially relate to cardiovascular health; and associations between obesity metrics and adverse cardiovascular health vary by region. METHODS: Using baseline anthropometric data collected between 2008 and 2012 from 7 cohorts in 9 countries, we estimated the proportion of participants with general and central obesity using BMI and waist circumference classifications, respectively, by study site. We used Poisson regression to examine the associations (prevalence ratios) of continuously measured BMI and waist circumference with prevalent diabetes and hypertension by sex. Pooled estimates across studies were computed by sex and age. RESULTS: This study analyzed data from 31,118 participants aged 20 to 79 years. General obesity was highest in South Asian cities and central obesity was highest in South America. The proportion classified with general obesity (range 11% to 50%) tended to be lower than the proportion classified as centrally obese (range 19% to 79%). Every standard deviation higher of BMI was associated with 1.65 and 1.60 times higher probability of diabetes and 1.42 and 1.28 times higher probability of hypertension, for men and women, respectively, aged 40 to 69 years. Every standard deviation higher of waist circumference was associated with 1.48 and 1.74 times higher probability of diabetes and 1.34 and 1.31 times higher probability of hypertension, for men and women, respectively, aged 40 to 69 years. Associations of obesity measures with diabetes were strongest in South Africa among men and in South America among women. Associations with hypertension were weakest in South Africa among both sexes. CONCLUSIONS: BMI and waist circumference were both reasonable predictors of prevalent diabetes and hypertension. Across diverse ethnicities and settings, BMI and waist circumference remain salient metrics of obesity that can identify those with increased cardiovascular risk.
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