This document summarizes a presentation on racial and ethnic differences in obesity given by Professor TH Lam. Some key points: - Asians generally have higher body fat percentage at a given BMI compared to Caucasians. The same is true for different ethnic groups within Asia. - Studies show associations between obesity measures like BMI, waist circumference, and body fat percentage with health risks like diabetes and cardiovascular disease. However, more data is needed comparing different ethnic groups using standardized methods. - Factors like socioeconomic development and differences between populations in different regions/countries may help explain some ethnic/racial differences in obesity and health risks. Considering populations at different stages of obesity epidemics is also important.

1. WCRF International and IASO Joint Conference 2013
16-17 April 2013
Racial and ethnic differences in
measures and effects of obesity
Professor TH Lam, JP, BBS
MD, FFPH, FFOM, Hon FHKCCM, FHKAM, FRCP
School of Public Health
The University of Hong Kong

2. What is Obesity?
• Simple yet complex
• Epidemiologically: general (total, global) versus
central - simplistic definitions and classification
• Body weight, body fat and body fat percent (BF
%)
• BMI most commonly used for general obesity:
only data available in most studies
• Waist circumference (and WHR): central
obesity: data available only in more recent
studies
• Different methods to measure body fat: all with
limitations

3. Racial/Ethnic Differences: BF%/BMI
Deurenberg et al 2002 review
• Indonesians (Malays, Chinese); Singaporean
Chinese, Malays and Indians; Hong Kong
Chinese
• All Asians studied: higher BF% at a lower BMI
compared to Caucasians:
Same BMI, Asian BF% 3-5% points higher
Same BF%, Asian BMI 3-4% points lower
• Different BF%/BMI ratio: body build, i.e. trunk-to-
leg length ratio and slenderness, muscularity

4. BF%/BMI Ethnic Specific
• Relationships between BF% and BMI differ
between ethnic groups
• Not all “Asians” are equal: Chinese, Indonesians
of Malays ancestry and Thais
• Not all “Chinese” are equal: New York, Beijing
and Hong Kong
(Deurenberg et al 2002)

5. Problems and Challenges
• Data limited and most reports had small sample
size, uncertain representativeness, different
methods/assumptions/equations for body fat
assessment
• Studies with different ethnic groups measured in
the same laboratory using the same
methodologies are needed.
• Universal BMI cut-off points are not appropriate
(Deurenberg et al 2002)

6. Some Comments
• Obesity, adiposity, BF%, BMI, WC, etc are all
continuous variables
• Using cut-off points for obesity (general or
central) are needed but would it add to our
understanding of the causes and effects of
obesity and its mechanisms?
• Or would it generate more confusion?

7. Is this normal ?

8. Is this underweight ?

9. Is this central obesity ?

10. Is this central and general obesity ?

11. • Meta-analysis/systematic reviews on ethnic
differences are based on studies with
different methods at different time periods in
different places with different socio-
economic developments. Many studies
were not specifically designed to compare
ethnic/racial differences
Some Comments

12. • Could ethnic/racial differences be explained
by extraneous factors: regional,
socioeconomic developments (high, middle
and low income countries, or regions within
the same countries): gradual developments in
many decades versus recent rapid
developments; immigration, inter-generational
differences
Some Comments

13. Obesity Increases Risks of Many Diseases
• Cardiovascular, type 2 diabetes, some cancer
(see WCRF reports) and all-cause mortality
(prospective evidence)
• Obesity associated with many risk factors:
dyslipidemia, high blood pressure (cross-sectional
associations)
• Obesity has many determinants: e.g. diet,
sedentary living, physical inactivity, energy
balance; socio-economic and obesity control
(WCRF 2007: Body fatness, convincing-oesophagus, pancreas,
colorectum, breast postmenopausal, endometrial, kidney)

14. Obesity Increases Risks of Many Diseases
• Evidence predominantly from Western
populations, and mainly from BMI
• Difficulties in separating the effect of obesity from
its associated risk factors
• Adjustment of risk factors, treating them as
“confounders” may not clarify the effects of
obesity and its interaction with other risk factors

15. BMI/WC/WHR and Cardiovascular Risk
Huxley et al 2010 review
• Most evidence from Caucasians
• Type II diabetes (Vazquez et al 2007), meta-
analysis of 32 cohort studies
• BM/WC/WHR: RR of 1.87-1.88 for incident
diabetes per standard deviation - similar
associations
• Effect stronger in Caucasian than Asian for
WHR but not BMI or WC

16. Pooled relative risk for BMI, WC and WHR with incident
diabetes stratified by age, gender and geographical region
Abbreviations: F, female; M, male
Adapted from Vazquez et al., (2007)
(Huxley et al 2010)

17. Obesity in Asia Collaboration
(Huxley et al 2008)
• Cross-sectional meta-analysis >263,000 subjects
(73% Asian)
• Except Caucasian men, central obesity more
strongly associated with prevalent diabetes than
BMI
Per 0.5 SD: BMI - 20-30% prevalent OR
WC and WHR - 40%
• Hypertension:
BMI/WC/WHR: Similar OR for both men and
women per 0.5 SD
Stronger OR in Caucasian (40%) than non-
Causasian men (30%)

18. (Huxley et al 2008)

19. (Huxley et al 2008)

20. Diabetes Epidemiology: Collaborative Analysis
of Diagnostic Criteria in Asia Study
(DECODA, 2008)
• 16 cross-sectional studies
• DM and BMI/WC/WHR: little differences
• But a slightly stronger association with
Weight/Height ratio in both men and women

21. Dyslipidaemia
OAC (Barzi et al 2010)
• Most comprehensive analysis
• Total cholesterol, LDL and triglycerides and
global/central obesity
• Cross-sectional associations broadly similar
between Asians and non-Asians
• No single measure of body size was superior
for discriminating dyslipidaemia
• WHR of 0.8 in women and 0.9 in men
applicable across both regions for
discriminating any form of dyslipidaemia (also
for diabetes and hypertension, Huxley 2008)

22. Some Comments
• Cross-sectional associations - causation
uncertain
• Data on central obesity - more recent and
scarce
• Data from different countries/regions at different
time periods
• Variations of obesity and lipid measurement and
results, and heterogeneity in the associations
within and between Asian and non-Asian
populations

23. Asia Pacific Cohort Studies Collaboration
(APCSC 2006)
Obesity Indices and CVD Risk
• >40 cohort studies: Asia and ANZ
• 33 cohorts (310,000 people): BMI and
CV events
• 6 cohorts (45,998): waist and hip
circumference - 601 CHD and 346
stroke events

24. • One SD associated with excess risk
CHD(%) Stroke(%)
Association No association
BMI 17(7-27) 3 (-9-16)
WC 27(14-40) 5(-9-20)
HC 10(1-20) 0(-11-13)
WHR 36(21-52) 9(-8-28)
Association: stronger in
aged <65, men, non-
Asians strongest for WC
and WHR; weakest HC
No association
across age, sex,
region
(Huxley et al 2010)

25. Some Comments
• APCSC - a large individual data meta-analysis
 small number of cohorts (6/44) and events
for comparing different obesity indices and
regional ethnic differences
• Data mainly from ANZ; Asian cohorts had short
follow up (mean 3.3 years or less; confounded
by pre-existing diseases)
• Broad similarity: (a) different indices and CV risk
and risk factors; (b) regions/ethnicity
• Regional differences are NOT racial/ethnic
differences

26. Obesity and Cancer: Ethnic Differences?
APCSC 2010
• BMI and cancer mortality
• 39 cohorts, 424,519 people (77% Asian)
• 4,872 cancer death from 401,215
(excluding FU <3y)

27. Obesity and Cancer: Ethnic Differences?
APCSC 2010
• Increased risk (HR (95% CI)) in BMI ≥30 vs BMI
18.5-24.9
– all-causes (excluding lung
and upper aerodigestive) 1.21(1.09-1.36)
– colon 1.50(1.13-1.99)
– rectum 1.68(1.06-2.67)
– breast(≥60y) 1.63(1.13-2.35)
– ovary 2.62(1.57-4.37)
– cervix 4.21(1.89-9.39)
– prostate 1.45(0.97-2.19)
– leukaemia 1.66(1.03-2.68)
(Parr et al 2010)

28. • No regional differences in HR for cancer
and BMI except oropharynx and larynx:
inverse in ANZ, absent in Asia
• Asian data: mainly Japan
• Insufficient data on WC, WHR
• Test of regional interaction
(heterogeneity): low stat. power
(Parr et al 2010)

29. Age- and smoking-adjusted hazard ratios with 95% CI for
mortality from colorectal cancer by region after left censoring
at 3 years according to categories of body-mass index
(Parr et al 2010)

30. Obesity and Colorectal Cancer Meta-analysis
(Moghaddan et al 2007)
• 31 studies (23 cohort, 8 case control), 70,000
events
• BMI: 7%(4-10%) per 2 kg/m2
WC: 4%(2-5%) per 2 cm
• Association with general obesity: smaller
strength than previously reported
• No ethnic differences but very few studies from
Asia
• 2 Japanese and 1 Korean cohort studies: BMI
association. No data on WC.

32. All-cause Mortality and BMI: Meta-analysis
(Flegal et al 2013)
• 97 studies, 2.88 million people, >270,000
deaths
• HR vs BMI : 18.5 to <25
overweight (25-<30) 0.94(0.91-0.96)
grade 1 obesity (30-<35) 0.95(0.88-1.01)
grade 2,3 obesity (≥35) 1.29(1.18-1.41)
obesity (1-3) (≥30) 1.18(1.12-1.25)
• Overweight: Lower all-cause mortality

33. Some Comments
• Baseline BMI to predict outcomes does not
account for
– Obesity/weight status (duration) and related
factors before and after baseline
– Age of subjects and latency period
– Duration of follow up - too short
– Confounders: some could be determinants or
outcomes of obesity
– Different socio-economic developments in
different countries/regions at different time
periods

34. Can we learn from
the Stages of
Epidemic of Tobacco?

35. Four Stages of the Tobacco Epidemic
(http://apps.who.int/bookorders/anglais/detart1.jsp?sesslan=1&codlan=1&codcol=76&codcch=22)

36. Stages of Tobacco Epidemic SE
• Stage 1 to 4 for different regions/
countries, by sex
• A large gap of several decades between
peak of tobacco consumption and the
peak of tobacco-induced deaths
• Full impact of adverse outcomes only
observed recently in the West (US/UK);
not yet in LMIC (Asia)
• Effective tobacco control  declining
consumption and mortality in the West

37. Stages of Epidemic of Obesity
• The West: Early stage, Stage 2
(a) Rising, high obesity level;
(b) Rising mortality
• LMIC: Stage 1
(a) Early rise of obesity;
(b) No or early rise of mortality
• Same for men and women?
• Need to interpret results and studies taking into
account stage developments
• Inappropriate to pool results from different stages
• Results observed in the past and now: Under-
estimate the full impacts in the West; grossly
under-estimate in LMIC

38. Life Course Studies of Obesity
• Obesity/overweight can start from early
childhood to late adulthood
• Trajectory of obesity/overweight; extent and
duration of obesity
• Factors affecting changes in obesity/overweight
(such as illnesses, efforts to reduce weight in
healthy people)
• Reverse causation
• Risk reversal of weight/obesity reduction
• Inter-generational effect: parental obesity,
pregnancy weight status on offsprings
• Different effects on different diseases

39. is needed for the
Stages of Epidemic Life Course
Obesity Research (SELCOR)
Growing and
Complex Global Epidemic of Obesity
and for
Different populations, regions,
races and ethnicity

40. Thank you very much