The Nutrition Transition Program The University of North Carolina at Chapel Hill Ethnic Differences in the Association Between Body Mass Index and Hypertension.

Slides:



Advertisements
Similar presentations
به نام ايزد يكتا دكتر داودخليلي. Cut points of OBESITY Dr. Khalili PhD candidate in epidemiology Shahid beheshti university (MC)
Advertisements

1 Baseline BMI and Age-Adjusted Incidence of Diabetes Mellitus White Men Level of BMI Percent
Body mass index and waist circumference as predictors of mortality among older Singaporeans Authors: Angelique Chan, Chetna Malhotra, Rahul Malhotra, Truls.
© NOO 2011 noo National Obesity Observatory Examining available data for the adult population.
Definitions Body Mass Index (BMI) describes relative weight for height: weight (kg)/height (m 2 ) Overweight = 25–29.9 BMI Obesity = >30 BMI.
Proportion of cases and controls who are obese or overweight S. Yusuf, Lancet 2005; 366:
Associations between Obesity and Depression by Race/Ethnicity and Education among Women: Results from the National Health and Nutrition Examination Survey,
Understanding Your Fitness
© NOO 2012 noo National Obesity Observatory Examining available data for the adult population.
The association between blood pressure, body composition and birth weight of rural South African children: Ellisras longitudinal study Makinta MJ 1, Monyeki.
THE PREVALENCE OF OVERWEIGHT, OBESITY, DIAGNOSED DIABETES MELLITUS AND HYPERTENSION IN THE SWAHILI COMMUNITY OF OLD TOWN AND KISAUNI DISTRICTS IN MOMBASA.
Statistics on Obesity, PA & Diet: England, Jan 08 i Compiled by Sally Cornfield on behalf of PAN-WM Headline Findings.
Assessment of adults and older people in emergencies: Approaches, Issues and priorities, Recommendations By Dolline Busolo HelpAge International.
Chapter 1: CKD in the General Population 2014 A NNUAL D ATA R EPORT V OLUME 1: C HRONIC K IDNEY D ISEASE.
REVISITING THE SOCIOECONOMIC GRADIENT IN OBESITY Looking Beyond the Obesity Threshold Inaugural Conference of the Singapore Health Economics Association.
Cross-sectional study. Definition in Dictionary of pharmaceutical medicine 2009 by G Nahler Dictionary of pharmaceutical medicine cross-sectional study.
OBESITY and CHD Nathan Wong. OBESITY AHA and NIH have recognized obesity as a major modifiable risk factor for CHD Obesity is a risk factor for development.
The Nutrition Transition Program The University of North Carolina at Chapel Hill Popkin, Public Health Nutrition, Feb 2002 THE NUTRITION TRANSITION AND.
NHANES III Prevalence of Hypertension* According to BMI
Journal Club Alcohol, Other Drugs, and Health: Current Evidence July-August 2007.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence January–February 2009.
Journal Club Alcohol and Health: Current Evidence March-April 2005.
Journal Club Alcohol and Health: Current Evidence July–August 2004.
1 Background Hypertension Type 2 diabetes Coronary heart disease Gallbladder disease Certain cancers Dyslipidemia Stroke Osteoarthritis Sleep apnea Approximately.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence May-June 2008.
K yriakos S. Markides, PhD University of Texas Medical Branch Galveston, Texas, USA Adelaide, Australia, July 2, 2011.
Body Weight and Mortality: New Population Based Evidences Body Weight and Mortality: New Population Based Evidences Dongfeng Gu, MD Dongfeng Gu, MD Fu.
השמנת יתר חמד " ע פרופ ' ארדון רובינשטין.
Andrew To Cardiologist North Shore Hospital, Auckland, New Zealand June 2014 Cardiovascular Health in Chinese New Zealanders.
The epidemiology of overweight and obesity Katherine M. Flegal, Ph.D. Centers for Disease Control and Prevention National Center for Health Statistics.
Metabolic Factors / NAFLD on the Natural History of Chronic Hepatitis B or C in Asia Pei-Jer Chen National Taiwan University & Hospital.
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence January–February 2014.
Low level of high density lipoprotein cholesterol in children of patients with premature coronary heart disease. Relation to own and parental characteristics.
The effects of initial and subsequent adiposity status on diabetes mellitus Speaker: Qingtao Meng. MD West China hospital, Chendu, China.
COHORT EFFECTS & CHANGING DISTRIBUTIONS Adam Hulmán (LEAD member) Department of Medical Physics and Informatics University.
Aging and Obesity Claire Zizza Tenth Annual Diabetes and Obesity Conference April 19, 2011.
Obesity among Hispanics - a brief demographic account Rodolfo Valdez, Ph.D., M. Sc. Division of Diabetes Translation Centers for Disease Control and Prevention.
Anthropometrics in Obesity Robert Kushner, MD Northwestern University Feinberg School of Medicine.
Chiu et al., CMAJ 2010 Do ethnic groups living in Ontario differ in their cardiovascular risk profiles? Maria Chiu, MSc, PhD Candidate Inst. of Medical.
HS499 Bachelor’s Capstone Week 6 Seminar Research Analysis on Community Health.
Illinois State University Exercise and Body Composition Relationships of Total and Regional Body Composition to Morbidity and Mortality.
Organizational criteria for Metabolic Syndrome National Cholesterol Education Program Adult Treatment Panel III World Health OrganizationAmerican Association.
Obesity Epidemic in America Going for the 3 Increases: Increase in Health, Increase in Happiness & Increase in Energy Strategies for Success in Weight.
Pai JK et al. N Engl J Med 2004; 351: Relative CHD risk by increasing baseline CRP plasma levels,* relative to CRP
© NOO 2012 noo National Obesity Observatory Examining available data for the adult population.
Lipoatrophy and lipohypertrophy are independently associated with hypertension: the effect of lipoatrophy but not lipohypertrophy on hypertension is independent.
Cardiovascular Disease Healthy Kansans 2010 Steering Committee Meeting April 22, 2005.
Obesity, Medication Use and Expenditures among Nonelderly Adults with Asthma Eric M. Sarpong AHRQ Conference September 10, 2012.
Low Fitness as a Predictor of Morbidity and Mortality
Department of Epidemiology &Biostatistics School of Public Health, Xinjiang Medical University.
Obesity in Asian & Pacific Islander Americans: Research Priorities and Directions May C. Wang, DrPH UCLA School of Public Health APIOPA Quarterly Meeting,
Identifying Persons in Need of Weight-loss Treatment: Evaluation of Potential Treatment Algorithms Caitlin Mason School of Physical and Health Education.
Bigger Waist Means Higher Asthma Risk Summary and Comment by Wendy S. Biggs, MD Published in Journal Watch Women's Health September 24, 2009Journal Watch.
Obesity and Socioeconomic Status in Adults: United States, 2005–2008 NCHS Data Brief ■ No. 50 ■ December 2010.
Employment Sorting by Size: The Role of Health Insurance Lan Liang and Barbara Schone.
Date of download: 5/31/2016 From: Metabolic Risk Factors Worsen Continuously across the Spectrum of Nondiabetic Glucose Tolerance: The Framingham Offspring.
Life expectancy at birth, OECD countries, 2013 NOTES: Countries with estimated life expectancies or series breaks for 2013 are not presented. Differences.
Obesity and Body Mass Index: Differences between Canadian and American Adults: Findings from the Joint Canada/United States Survey of Health (JCUSH) Jane.
1 Body-Mass Index and Mortality in Korean Men and Women Sun Ha Jee, Ph.D., Jae Woong Sull, Ph.D., Jung yong Park, Ph.D., Sang-Yi Lee, M.D. From the Department.
به نام خدا.
Associations between Depression and Obesity: Findings from the National Health and Nutrition Examination Survey, Arlene Keddie, Ph.D. Assistant.
Copyright © 2009 American Medical Association. All rights reserved.
Patterns and trends in adult obesity
Copyright © 2007 American Medical Association. All rights reserved.
Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults Risks and Assessment NHLBI Obesity Education.
WHI Observational Study: Cardiovascular death in women with hypertension but no history of CVD on monotherapy CVD death Diuretic, HR (95% CI) ACE inhibitor,
Risk for BMI outcome (%)
Risk Factors for CHD L.O – Describe the global distribution of CHD and the risk factors associated with it.
Baseline Lipid Parameters and Characteristics Among 3110 Men According to Quintiles of Total Cholesterol Ruben O. Halperin et al, Hypertension 2006;47;45-50.
Prevalence of high SAT or high VAT by BMI category in women (A) and men (B) and by waist circumference category in women (C) and men (D). Prevalence of.
Presentation transcript:

The Nutrition Transition Program The University of North Carolina at Chapel Hill Ethnic Differences in the Association Between Body Mass Index and Hypertension Colin Bell, Linda Adair, Barry Popkin Department of Nutrition, The University of North Carolina at Chapel Hill Department of Community Health, University of Auckland

The Nutrition Transition Program The University of North Carolina at Chapel Hill Does a BMI of 25 kg/m 2 mean the same thing in different populations?  BMI is only an approximate measure of body fatness  Good evidence exists that some populations have different levels of body fat at similar BMIs –Asian: smaller frames, higher % body fat than Caucasians (Deurenberg et al, Int J Obesity 1998,1999) –Polynesians: larger frames, more lean body mass, lower % body fat than Caucasians (Swinburn et al, Int J Obesity 1999)

The Nutrition Transition Program The University of North Carolina at Chapel Hill If body fat differs, do obesity related co-morbidities also differ?  In Hong Kong Chinese, Ko et al observed increased prevalence of type-2 diabetes, hypertension, dislipidaemia and albuminuria at a BMI of ~ 23 kg/m 2 (Ko et al, Int J Obesity 1999)  In Polynesian populations serum lipids tend to be lower than for Caucasians in spite of higher BMIs (Bell et al, NZ Med J 2001, Scragg et al, NZ Med J 1993)  However: –direct comparisons are needed in a variety of ethnic groups

The Nutrition Transition Program The University of North Carolina at Chapel Hill Objective  To determine whether there are ethnic differences in the association between BMI and hypertension in men and women aged years Ethnic groups  3,423 Chinese men and women (CHNS 1997)  1,929 Filipino women (CLHNS 1998)  7,957 non-Hispanic Whites, non-Hispanic Blacks, Mexican Americans (NHANES III )

The Nutrition Transition Program The University of North Carolina at Chapel Hill Methodology  Pooled cross-sectional data from three surveys Outcome = Hypertension  SBP  140 mm Hg, DBP  90 mm Hg, or on anti-hypertension medication  Including those on medication biased the result towards the null or had no effect (see following figure) Main explanatory variable = BMI Confounders = Age. Physical activity, smoking and alcohol consumption were not major confounders. (see following figure)

The Nutrition Transition Program The University of North Carolina at Chapel Hill We included pre-diagnoased individuals to boost cell size and because their inclusion biased the results towards the null

The Nutrition Transition Program The University of North Carolina at Chapel Hill Physical activity, smoking status and alcohol consumption had a minimal effect on the association between hypertension and BMI in all ethnic groups: eg NHBlack women

The Nutrition Transition Program The University of North Carolina at Chapel Hill Compared to US ethnic groups, Chinese men & women were less hypertensive; Filipino women had similar levels of hypertension to NHWhites

The Nutrition Transition Program The University of North Carolina at Chapel Hill Compared to US ethnic groups, Chinese men & women & Filipino women were less overweight (BMI  25 kg/m 2 )

The Nutrition Transition Program The University of North Carolina at Chapel Hill Chinese men had higher odds of prevalent hypertension, adjusted for age, than NH-Whites at every category of BMI, including kg/m 2

The Nutrition Transition Program The University of North Carolina at Chapel Hill Including waist circumference attenuated the association for both Chinese & NHWhite men but the ethnic differences remained

The Nutrition Transition Program The University of North Carolina at Chapel Hill The age-adjusted odds of prevalent hypertension for Chinese and Filipino women were similar to those for NH-Whites at low levels of BMI

The Nutrition Transition Program The University of North Carolina at Chapel Hill Two problems can arise when using odds ratios in this context  Odds ratios are dependent on a reasonable number of subjects in the reference category  Interpretation can be misleading because the analysis assumes that the underlying risk (or in this case prevalence) between the ethnic groups is the same

The Nutrition Transition Program The University of North Carolina at Chapel Hill Subject numbers were sufficient but hypertension prevalence differed markedly by ethnic group in the referent BMI category (BMI kg/m 2 )

The Nutrition Transition Program The University of North Carolina at Chapel Hill To overcome this problem, we used prevalence difference figures. A steeper slope was observed at low levels of BMI for Chinese men (10.8%  ) compared to NHWhite men (1.8%  )

The Nutrition Transition Program The University of North Carolina at Chapel Hill There was also some evidence of a steeper slope at low levels of BMI for Chinese women (7.6%  ) compared to NHWhite women (4.3%  ). Filipino women showed a 10.3%  between the categories and kg/m 2

The Nutrition Transition Program The University of North Carolina at Chapel Hill Current WHO weight status recommendations for Asia and the USA

The Nutrition Transition Program The University of North Carolina at Chapel Hill Should lower definitions of overweight and obesity be used for Asian populations?  We have shown some evidence that the association between hypertension and BMI may be stronger in Chinese compared to NHWhites  There was no evidence of a stronger association for Filipino women, however, a higher baseline prevalence may justify a lower cut-off  To fully justify lower cut-offs we need longitudinal studies, data on all co-morbidities, consensus on appropriate methodology and more specific definitions of ethnicity

The Nutrition Transition Program The University of North Carolina at Chapel Hill The value of ethnic-specific BMI cut-offs? At the clinical level:  In countries such as the USA, with considerable ethnic diversity, physicians would be better able to identify individuals at risk of obesity related co-morbidities At an international level:  At this level, the utility of a weight classification system is in the ability to compare populations and monitor changes overtime & therefore there is no advantage in having ethnic-specific cut-offs