Body size and blood pressure: a collaborative analysis of 18,072 participants

1. Body size and blood pressure: a collaborative analysis of 18,072 participants from Africa and the African diaspora FP Cappuccio, SM Kerry, A Adeyemo, A Luke, AGB Amoah, P Bovet, MD Connor, T Forrester, J-P Gervasoni, G Kimbally Kaki, J Plange-Rhule, M Thorogood & RS Cooper Warwick Medical School, Coventry, UK; St George’s, University of London, UK; University College Hospital, Ibadan, Nigeria; Howard School of Medicine, Baltimore, USA; Loyola University Stritch School of Medicine, Maywood, IL, USA; University of Ghana Medical School, Accra, Ghana; University of Lausanne, Switzerland; Ministry of Health, Victoria, Seychelles; Johannesburg Hospital, Johannesburg, South Africa; University of the West Indies, Kingston, Jamaica; Ministry of Regional Administration and Local Government, Dar es Salaam, Tanzania; C.H.U., Brazzaville, Republic of Congo; Kwame Nkrumah University of Science & Technology, Kumasi, Ghana.

2. Presenter Disclosure InformationFrancesco P Cappuccio, MD MSc FRCP FFPHBody size and blood pressure: a collaborative analysis of 18,072 participants from Africa and the African diasporaFinancial disclosureF.P.C. is Technical Expert for the World Health Organization, Geneva

3. Background • Blood pressure (BP) directly associated with body mass index (BMI) in populations worldwide • Clinical trials of weight reduction suggest a causal association • The relationship may be different in populations of African origin (Bunker et al. 1995; Kaufman et al. 1997; Bell et al. 2002; Kerry et al. 2005), perhaps reflecting associated changes in body composition (Luke et al. 2004).

4. Background • Blood pressure (BP) is directly associated with body mass index (BMI) in populations worldwide • Clinical trials of weight reduction suggest a causal association • The relationship may be different in populations of African origin (Bunker et al. 1995; Kaufman et al. 1997; Bell et al. 2002; Kerry et al. 2005), perhaps reflecting associated changes in body composition (Luke et al. 2004). • During the past decade, several population-based studies in people of black African origin in Africa, the Caribbean, UK and USA. • Opportunity to make international comparisons in genetically similar populations, with differing environmental exposures (largely due to different stages of the ‘epidemiologic transition’), and differing levels of BP and obesity.

5. Aim • To study the relationship between BP and BMI in a collaborative analysis of 13 studies in African populations across the world living in rural and urban settings • Wide range of average levels of BMI, of prevalence of hypertension and obesity, degree of association between BP and BMI

6. Methods • Search of data published or available since 1990 on BP and BMI in populations of black African origin • Thirteen population surveys with standardized data on BP, its treatment, height and weight • Africa: Cameroon, Nigeria, Ghana (2), Republic of Congo, Tanzania, South Africa, Seychelles - Caribbean: Barbados, St. Lucia, Jamaica - UK: South London - USA: NHANES-III • Individual data on sex, age, SBP, DBP, height, weight, treatment of hypertension, method of BP measurement • Response rates between 54% to >90% • Analysis restricted to 18,072 participants (44% men) aged 35-64 years • 8 studies used Hg sphygmomanometers, the remaining automated machines • BP values mean of 2-3 measurements after 5-10 minutes rest • Standardization and validation of BP measurements in most studies (Ataman et al. 1996; Cooper RS et al. 1997)

7. Analysis • Linear regression to calculate age-adjusted means (95% CIs) within sex and country using 45 years as reference age • Linear regression to estimate age-adjusted relationship between BP and BMI with sex and country • Regression coefficients plotted against mean BMI (adjusted for age and sex) weighting for the inverse of the standard error • Random effect model used to estimate the relationship between the regression coefficients and mean BMI weighting for the inverse of the standard error (more weight to larger studies) • Sensitivity analysis – adjusting BP of those on treatment by a random amount of 10, 15, 20 and 25 mmHg - to estimate by how much the effect of anti-hypertensive treatment would be likely to reduce the relationship between BP and BMI • Results are means (95% CIs)

8. Men (n=7,893) All adjusted for age and calculated for each country separately; § all untreated

9. Women (n=10,179) All adjusted for age and calculated for each country separately; § all untreated

10. Relationship between the change in systolic and diastolic BP with BMI and the average BMI in men (n=7,893; triangles) and women (n=10,179; circles) aged 35-64 years Diastolic BP Systolic BP Size of symbols proportional to sample size

11. Relationship between the change in systolic and diastolic BP with BMI and the average BMI in untreated men (n=7,347) and women (n=9,163) aged 35-64 years Diastolic BP Systolic BP Size of symbols proportional to sample size

12. Meta-regression of slope of BP on BMI in each country by sex against mean BMI for sex and country ***P<0.001; **P<0.01; *p<0.05 Interaction between sexes p=0.042 (SBP) p=0.17 (DBP) without adjustment for anti-hypertensive therapy. Interaction between sexes p=0.054 (SBP) p=0.52 (DBP) in untreated only. Model 1: BP = b0 + b1age + b2BMI within country and sex strata.

13. Sensitivity analysis for effect of anti-hypertensive treatment. Meta regression of slope of BP on BMI in each country by sex against mean BMI for sex and country (7,893 men and 10,179 women) People on anti-hypertensive therapy have BP adjusted by random amount from a normal distribution with mean 10, 15, 20 and 25 mmHg and SD equal to the mean ***P<0.001; **P<0.01; *p<0.05

14. Strengths and Limitations • First pooled analysis of populations of African origin • Large samples • Analysis of individual data (less biased within-population estimates) • Studies post-1990 – stringent standardized methods • Variable response rates • Variations in methods of BP measurement • Difference in the prevalence of anti-hypertensive treatment

15. One possible explanation … • Resting energy expenditure (REE) related to BP, independently of BMI or adiposity(Luke et al. 2004) • REE is primarily determined by lean mass(Nelson et al. 1992; Luke et al. 2004) • Hence muscle mass, associated to body mass, the link • Increases in BMI largely reflect increases in adipose tissue relative to lean mass • Smaller increases in metabolically active fat-free body mass would lead to smaller increment in BP relative to increments in BMI • Effect not biased by changing resting energy expenditures (similar in rural Nigerians and US blacks)(Luke et al. 2000)

16. Conclusions • BP and BMI levels vary substantially among populations of the black African diaspora • The effect of BMI on BP levels diminishes as BMI increases • REE – determined by lean mass – relate to BP • Smaller increments in lean mass are observed in obese as BMI increases • This could be the underlying physiological mechanism • This interpretation would alter the standard view that increasing fat mass, per se, is the cause of increased risk of hypertension in obese blacks