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.
www2.warwick.ac.uk/go/cappuccio
Presenter Disclosure Information
Francesco P Cappuccio, MD MSc FRCP FFPH
Body size and blood pressure: a collaborative analysis of 18,072 participants from
Africa and the African diaspora
Financial disclosure
F.P.C. is Technical Expert for the World Health Organization, Geneva
2
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).
3
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.
4
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
5
Methods
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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)
6
Analysis
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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)
7
Men (n=7,893)
Country
Sample size (n)
Overall
Untreated only
Rx (%)
Systolic B.P. (mmHg per unit of BMI)
Overall
Untreated only
Diastolic B.P. (mmHg per unit of BMI)
Overall
Untreated only
AFRICA
Nigeria §
1306
Ghana (Kumasi)
298
293
1
1.17 (0.84 to 1.51)
0.84 (0.63 to 1.04)
1.72 (0.92 to 2.53)
1.73 (0.93 to 2.54)
1.02 (0.51 to 1.52)
1.01 (0.50 to 1.51)
0.95 (0.64 to 1.27)
0.78 (0.54 to 1.02)
Cameroon §
779
Ghana (Accra)
1080
1018
6
1.52 (1.23 to 1.82)
1.45 (1.15 to 1.76)
1.12 (0.94 to 1.31)
1.07 (0.88 to 1.26)
54
49
7
1.58 (-0.09 to 3.26)
2.10 (0.08 to 4.11)
0.97 (0.04 to 1.90)
1.35 (0.30 to 2.40)
1665
1631
3
0.95 (0.75 to 1.16)
0.87 (0.66 to 1.08)
0.48 (0.34 to 0.62)
0.43 (0.28 to 0.57)
442
301
29
0.85 (0.52 to 1.19)
1.01 (0.65 to 1.38)
0.50 (0.29 to 0.72)
0.66 (0.42 to 0.90)
542
519
5
1.34 (0.90 to 1.78)
1.30 (0.87 to 1.73)
0.83 (0.53 to 1.14)
0.86 (0.56 to 1.15)
South Africa
Tanzania
Seychelles
Republic of Congo
CARIBBEAN
Jamaica
Barbados
St Lucia
612
550
10
1.23 (0.90 to 1.55)
1.18 (0.84 to 1.53)
0.94 (0.69 to 1.19)
0.90 (0.65 to 1.15)
196
166
16
0.47 (-0.11 to 1.04)
0.29 (-0.37 to 0.94)
0.34 (-0.03 to 0.71)
0.28 (-0.13 to 0.69)
293
281
4
0.74 (0.19 to 1.30)
0.72 (0.16 to 1.28)
0.90 (0.50 to 1.30)
0.89 (0.48 to 1.30)
US/UK
US blacks
UK blacks
418
305
208
149
26
0.27 (-0.01 to 0.56)
0.26 (-0.07 to 0.58)
0.15 (-0.06 to 0.36)
0.28 (0.03 to 0.52)
23
0.61 (-0.10 to 1.32)
0.89 (0.06 to 1.73)
0.64 (0.27 to 1.00)
0.76 (0.31 to 1.21)
All adjusted for age and calculated for each country separately; § all untreated
8
Women (n=10,179)
Country
Sample size (n)
Overall
Untreated only
Rx (%)
Systolic B.P. (mmHg per unit of BMI)
Overall
Untreated only
Diastolic B.P. (mmHg per unit of BMI)
Overall
Untreated only
AFRICA
Nigeria §
1611
Ghana (Kumasi)
481
467
2
0.46 (0.22 to 0.69)
0.50 (0.36 to 0.63)
1.15 (0.68 to 1.61)
1.23 (0.92 to 1.54)
0.92 (0.68 to 1.16)
0.92 (0.68 to 1.16)
0.49 (0.22 to 0.77)
0.31 (0.13 to 0.50)
Cameroon §
797
Ghana (Accra)
1644
1546
6
1.09 (0.90 to 1.28)
1.01 (0.82 to 1.20)
0.76 (0.66 to 0.86)
0.72 (0.61 to 0.82)
195
183
8
0.08 (-0.55 to 0.72)
0.04 (-0.64 to 0.72)
0.41 (0.05 to 0.78)
0.42 (0.03 to 0.81)
2048
1966
5
0.69 (0.53 to 0.85)
0.61 (0.45 to 0.77)
0.45 (0.35 to 0.56)
0.42 (0.31 to 0.52)
538
332
35
0.58 (0.32 to 0.84)
0.47 (0.22 to 0.72)
0.41 (0.25 to 0.57)
0.36 (0.19 to 0.53)
494
470
6
1.32 (0.98 to 1.66)
1.24 (0.90 to 1.57)
0.75 (0.53 to 0.97)
0.71 (0.48 to 0.93)
South Africa
Tanzania
Seychelles
Republic of Congo
CARIBBEAN
Jamaica
Barbados
St Lucia
962
787
18
0.49 (0.29 to 0.69)
0.46 (0.27 to 0.66)
0.32 (0.19 to 0.45)
0.32 (0.18 to 0.46)
289
216
23
0.20 (-0.14 to 0.54)
0.19 (-0.14 to 0.53)
0.16 (-0.05 to 0.37)
0.15 (-0.09 to 0.39)
335
281
17
0.11 (-0.24 to 0.45)
-0.02 (-0.37 to 0.34)
0.02 (-0.21 to 0.25)
-0.02 (-0.28 to 0.23)
US/UK
US blacks
UK blacks
446
280
339
227
34
0.58 (0.35 to 0.81)
0.51 (0.24 to 0.77)
0.26 (0.11 to 0.40)
0.11 (-0.07 to 0.30)
24
0.33 (-0.09 to 0.75)
0.54 (0.06 to 1.02)
0.25 (0.03 to 0.48)
0.37 (0.11 to 0.63)
All adjusted for age and calculated for each country separately; § all untreated
9
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
2.00
Slope of DBP on BMI (mmHg*unit)
Slope of SBP on BMI (mmHg*unit)
2.00
1.50
1.00
0.50
1.50
1.00
0.50
0.00
0.00
20
25
Mean BMI (kg/m2)
30
20
25
30
Mean BMI (kg/m2)
10
Size of symbols proportional to sample size
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
Female
Female
Male
Male
2
2
Slope of DBP on BMI
Slope of SBP on BMI
1.5
1.5
1
1
.5
.5
0
0
20
25
Mean BMI
30
20
25
Mean BMI
30
11
Size of symbols proportional to sample size
Meta-regression of slope of BP on BMI in each country
by sex against mean BMI for sex and country
Systolic B.P.
(mmHg per unit of BMI)
Diastolic B.P.
(mmHg per unit of BMI)
-0.10 (-0.15 to -0.06)***
-0.11 (-0.16 to -0.06)***
-0.08 (-0.11 to -0.04)***
-0.08 (-0.12 to -0.05)*
Men (n=7,893)
Untreated only (n=7,347)
-0.17 (-0.26 to -0.08)*
-0.18 (-0.28 to -0.08)*
-0.11 (-0.18 to -0.04)**
-0.10 (-0.18 to -0.02)*
Women (n=10,179)
Untreated only (n=9,163)
-0.06 (-0.11 to -0.00)*
-0.06 (-0.13 to 0)
-0.05 (-0.09 to -0.01)**
-0.07 (-0.11 to -0.02)**
Both sexes (n=17,972)
Untreated only (n=16,510)
***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 + b 2BMI within country and sex strata.
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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
Systolic B.P.
(mmHg per unit of BMI)
Diastolic B.P.
(mmHg per unit of BMI)
No adjustment
-0.10 (-0.15 to -0.06)***
-0.08 (-0.11 to -0.04)***
10 mm Hg
-0.09 (-0.14 to -0.04)***
-0.06 (-0.09 to -0.02)***
15 mm Hg
-0.09 (-0.14 to -0.04)***
-0.05 (-0.09 to -0.02)**
20 mm Hg
-0.08 (-0.13 to -0.03)**
-0.05 (-0.09 to -0.02)**
25 mm Hg
-0.08 (-0.13 to -0.03)**
-0.04 (-0.09 to -0.01)*
***P<0.001; **P<0.01; *p<0.05
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Strengths and Limitations
• First pooled analysis of populations of African origin
• Large samples
• Analysis of individual data (less biased withinpopulation estimates)
• Studies post-1990 – stringent standardized methods
• Variable response rates
• Variations in methods of BP measurement
• Difference in the prevalence of anti-hypertensive
treatment
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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)
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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
16