AJCN Tufts Nutrition Symposium, Boston & Online Sept 2009
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.
Agricola
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.
American Journal of Clinical Nutrition, Vol. 80, No. 5, 1129-1136, November 2004
© 2004 American Society for Clinical Nutrition


ORIGINAL RESEARCH COMMUNICATION

Appropriate body mass index and waist circumference cutoffs for categorization of overweight and central adiposity among Chinese adults1,2,3

Rachel P Wildman, Dongfeng Gu, Kristi Reynolds, Xianfeng Duan and Jiang He

1 From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans (RPW, KR, and JH); the Cardiovascular Institute and Fu Wai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (DG and XD); the Department of Medicine, Tulane University School of Medicine, New Orleans (JH); and the Tulane Hypertension and Renal Center of Excellence, Tulane University Health Sciences Center, New Orleans (JH)

2 This study was funded by a contractual agreement between Tulane University and Pfizer Inc. The analysis and interpretation of the data were supported in part by the National Institutes of Health (grant number 1 K12 HD43451-01 to RPW). JH received support from the National Heart, Lung and Blood Institute/National Institutes of Health (grants HL68057 and HL72507).

3 Address reprint requests to RP Wildman, Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2000, SL-18, New Orleans, LA 70112. E-mail: rwildman{at}tulane.edu.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Recent data suggest that current overweight and central adiposity guidelines based on Western populations are not appropriate for Asian populations. The published data among Chinese are insufficient to address this issue.

Objective: We aimed to identify cutoffs for body mass index (BMI; in kg/m2) and waist circumference that confer increased risk of cardiovascular disease in Chinese adults as would be consistent with overweight and central adiposity.

Design: A nationally representative, cross-sectional sample of 15 239 Chinese adults aged 35–74 y was studied.

Results: Mean blood pressure, total cholesterol, LDL-cholesterol, triacylglycerol, and glucose values were incrementally higher and mean HDL-cholesterol values were incrementally lower with each unit increase in BMI and waist circumference in both men and women. Both the point at which sensitivity equaled specificity and the shortest distance in the receiver operating characteristic curves for hypertension, dyslipidemia, diabetes, or ≥2 of these risk factors suggested a BMI cutoff of 24 and a waist circumference cutoff of 80 cm for both men and women.

Conclusions: Lower cutoffs for BMI and waist circumference are needed in the identification of Chinese patients at high risk of cardiovascular disease.

Key Words: Obesity • China • body mass index • waist circumference • cardiovascular disease risk factors • cutoffs


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
In Western populations, obesity has been shown to increase cardiovascular disease incidence and mortality as well as all-cause mortality among middle-aged and elderly participants in longitudinal studies (1-4). Obesity has also been shown to be associated with numerous cardiovascular disease risk factors, such as hypertension, dyslipidemia, type 2 diabetes, and insulin resistance (5, 6).

The current definitions of overweight [body mass index (BMI, in kg/m2) ≥ 25] and central adiposity (waist circumference ≥ 94 cm for men and ≥ 80 cm for women) recommended by the World Health Organization (WHO; 7) are based on data from Western populations. However, a growing body of literature indicates that these cutoffs likely need to be lower among Asian populations and may not even be appropriate among Western populations in the United States and Europe (8, 9). Several epidemiologic studies in Asian populations have shown that Asians have higher amounts of body fat at lower BMIs and waist circumferences than do Western populations (10-12), perhaps leading to the greater prevalence of cardiovascular disease risk factors at lower BMIs in Asian populations than in Western populations (13-16).

In response to these findings, the Western Pacific regional office of the WHO, the International Association for the Study of Obesity (IASO), and the International Obesity Task Force (IOTF) collaborated in the creation of new recommendations for BMI and waist circumference cutoffs among Asian populations, labeling these recommendations as provisional and calling for their validation by additional clinical and epidemiologic study (17). In these recommendations, overweight is defined as a BMI ≥ 23, and the suggested waist circumference cutoffs are 90 cm for men and 80 cm for women (17). These recommendations are based on a limited literature concerning the distribution of BMI and waist circumference measures in Asian populations and the associations between these measures and the prevalence of cardiovascular disease risk factors or risk of cardiovascular disease. The purpose of the present study was 2-fold: 1) to identify cutoffs for BMI and waist circumference that confer increased risk of cardiovascular disease in Chinese adults as would be consistent with overweight and central adiposity, and 2) to compare our findings with the cutoffs identified in the WHO/IASO/IOTF recommendations.


    SUBJECTS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Sample design
A detailed description of the study population and the methods of the International Collaborative Study of Cardiovascular Disease in Asia (InterASIA) are published elsewhere (18). Briefly, InterASIA used a 4-stage stratified sampling method to select a nationally representative sample of the general population in China aged 35–74 y. The sample process was stratified by rural versus urban areas and north versus south. The final stage of sampling was stratified by sex (50% men and 50% women) and by age distribution on the basis of 1990 China census data. Only 1 participant was selected from each household, without replacement.

A total of 19 012 individuals were randomly selected from 20 primary sampling units (street districts in urban areas or townships in rural areas) and invited to participate. A total of 15 838 individuals completed the survey and examination, a response rate of 83.3% (82.1% in men and 84.5% in women; 82.2% in urban areas and 84.4% in rural areas).

The Institutional Review Board at Tulane University Health Sciences Center approved the InterASIA study. In addition, ethics committees and other relevant regulatory bodies in China approved the study. Informed consent was obtained from each participant before data collection.

Anthropometric measurements
Data collection involved one visit to 1 of 20 examination centers at local health stations or in community clinics in the participants' residential areas. During the examinations, a standard questionnaire assessing demographic information and medical history was administered by trained research staff.

Anthropometric measures were taken according to a standard protocol by observers trained by an investigator from the United States (JH). Body weight was measured while the subjects were without clothes or shoes by using a double balance placed on a firm surface; balances at all 20 examination centers were identical and were calibrated with a standard InterASIA protocol. Height was measured by using a Frankfort place positioned at a 90° angle against a wall-mounted metal tape. Waist circumference was measured with a standard tape measure on bare skin, 1 cm above the naval; identical tape measures were used at all examination centers. BMI was calculated as weight in kg divided by height in m2.

Blood pressure measurement
Three blood pressure measurements were obtained by trained nurses and physicians according to a standard protocol adapted from American Heart Association recommendations; the measurements were made with the participant in a sitting position after ≥5 min of rest (19). A standard mercury sphygmomanometer was used with 1 of 4 cuff sizes (pediatric, regular adult, large adult, or thigh). The participants were advised to refrain from coffee, tea, or alcohol intake; cigarette smoking; and vigorous exercise for ≥30 min before their examination. All study investigators and staff members successfully completed a training program orienting them to both the aims of the study and the specific tools and methods used.

Hypertension was defined as self-reported use of antihypertensive medication within the past 2 wk or an average systolic blood pressure ≥ 140 mm Hg, an average diastolic blood pressure ≥ 90 mm Hg, or both.

Laboratory methods
After the subjects had fasted overnight, blood samples were drawn by venipuncture to measure serum total cholesterol, HDL cholesterol, triacylglycerols, and glucose. Blood specimens were processed at the field center, were stored at –70 °C, and were shipped by air monthly to the central clinical laboratory at the Department of Population Genetics at Fuwai Hospital of the Chinese Academy of Medical Sciences in Beijing. Here the specimens were again stored at –70 °C until laboratory assays could be performed. This laboratory participates in the Lipid Standardization Program of the US Centers for Disease Control and Prevention.

Total cholesterol, HDL cholesterol, and triacylglycerols were analyzed enzymatically on a Hitachi 7060 clinical analyzer (Hitachi High-Technologies Corporation, Tokyo) by using commercial reagents (20). LDL-cholesterol concentrations were calculated by using the Friedewald equation for the participants who had triacylglycerol concentrations < 400 mg/dL: LDL cholesterol = total cholesterol -HDL cholesterol -triacylglycerols/5 (21). Dyslipidemia was defined as either total cholesterol ≥ 200 mg/dL, LDL cholesterol ≥ 130 mg/dL, or HDL cholesterol < 35 mg/dL. The same HDL cutoff was used for both men and women because of similar HDL-cholesterol concentrations between men and women in China (22). Plasma glucose was measured by using a modified hexokinase enzymatic method. Diabetes was defined as fasting plasma glucose ≥ 126 mg/dL, use of insulin or oral hypoglycemic agents, or a self-reported history of diabetes.

Statistical methods
Of the 15 838 participants who completed the InterASIA examination and survey, the following were excluded from the current analyses: 298 for being outside of the 35–74-y age range, 281 for missing laboratory data, and 21 for missing BMI or waist circumference data. Therefore, data from 15 238 participants were used in the current analyses.

The mean and prevalence of cardiovascular disease risk factors were weighted to represent the total Chinese population aged 35–74 y. Weights were calculated based on the 2000 China population census data and took into account several features of the survey, including oversampling for specific age or geographic subgroups, nonresponse, and other demographic or geographic differences between the sample and the total Chinese population. Standard errors were calculated to take into account the stratified sampling design and the weights resulting from the complex survey design. Age-standardization was performed by the direct method by using the 2000 China population aged 35–74 y as the standard population. The sensitivity and specificity of each BMI and waist circumference level for the detection of hypertension, dyslipidemia, diabetes, and 2 or more of these risk factors were calculated by creating dichotomous variables for each BMI and waist circumference value (eg, BMI < 22 versus BMI ≥ 22). Additionally, the distance on the receiver operating characteristic (ROC) curve of each BMI and waist circumference value was calculated as the square root of [(1 – sensitivity)2 + (1 – specificity)2]. The BMI or waist circumference value with the shortest distance on the ROC curve was considered in the determination of appropriate cutoffs. All data analyses were conducted by using SUDAAN (version 8.0; Research Triangle Institute, Research Triangle Park, NC).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Body mass index
For both men and women, mean blood pressure, total cholesterol, LDL-cholesterol, triacylglycerol, and glucose values were higher, whereas mean HDL-cholesterol values were lower, with higher BMI in a linear fashion (Table 1Go). Likewise, when continuous risk factors were categorized, the prevalences of hypertension; diabetes; high total cholesterol, LDL cholesterol, triacylglycerols, and glucose; and low HDL cholesterol, as well as the mean number of risk factors, were higher with higher BMI for both men and women (Table 2Go).


View this table:
[in this window]
[in a new window]
 
TABLE 1. Age-standardized cardiovascular disease risk factors in the Chinese population by BMI category

 

View this table:
[in this window]
[in a new window]
 
TABLE 2. Age-standardized prevalence of risk factors in the Chinese population by BMI category1

 
The proportion of individuals having either hypertension, dyslipidemia, diabetes, or a combination of the 3 by BMI category for both men and women is shown in Figure 1Go. The frequency of having at least one risk factor doubled from a BMI of <21 to a BMI of ≥29, in large part because of the persons with ≥2 risk factors.



View larger version (34K):
[in this window]
[in a new window]
 
FIGURE 1.. Frequency of one or more risk factors (hypertension, dyslipidemia, and diabetes) by BMI category in men and women: {blacksquare}, 1 of 3 risk factors; {cjs2108}, 2 of 3 risk factors; {square}, all 3 risk factors.

 
The population percentile of each BMI level and the sensitivity, specificity, and distance on the ROC curve for the detection of hypertension, dyslipidemia, diabetes, and ≥2 of these risk factors are presented in Table 3Go for men and women separately. The specificity, sensitivity, and distances on the ROC curves were similar for all 3 cardiovascular disease risk factors among both men and women. The point at which sensitivity equaled specificity was between a BMI of 23 and a BMI of 24 among both men and women for all risk factors, with the exception of dyslipidemia for men (BMI between 22 and 23). The shortest distance on the ROC curve of ≥2 risk factors was at a BMI of 24 for men and women.


View this table:
[in this window]
[in a new window]
 
TABLE 3. Sensitivity (Sens), specificity (Spec), and distance in the receiver operating characteristic (ROC) curve for BMI cutoffs

 
Waist circumference
For both men and women, mean systolic blood pressure, diastolic blood pressure, total cholesterol, LDL-cholesterol, and triacylglycerol values were higher, whereas HDL-cholesterol values were lower, with higher waist circumference in a linear fashion (Table 4Go). When continuous risk factors were categorized, the prevalence of hypertension; diabetes; high total cholesterol, LDL cholesterol, triacylglycerols, and glucose; and low HDL cholesterol was higher among higher waist circumference categories for both men and women (Table 5Go). Additionally, the mean number of risk factors was higher among higher waist circumference categories.


View this table:
[in this window]
[in a new window]
 
TABLE 4. Age-standardized mean cardiovascular disease risk factors in the Chinese population by waist circumference category

 

View this table:
[in this window]
[in a new window]
 
TABLE 5. Age-standardized prevalence of risk factors in the Chinese population by waist circumference category1

 
The proportion of individuals having either hypertension, dyslipidemia, diabetes, or a combination of the 3 by waist circumference categories for both men and women is shown in Figure 2Go. The frequency of having at least one risk factor doubled from a waist circumference of <75 cm to a waist circumference of ≥95 cm, in large part because of the persons with ≥2 risk factors.



View larger version (34K):
[in this window]
[in a new window]
 
FIGURE 2.. Frequency of one or more risk factors (hypertension, dyslipidemia, and diabetes) by waist circumference category in men and women: {blacksquare}, 1 of 3 risk factors; {cjs2108}, 2 of 3 risk factors; {square}, all 3 risk factors.

 
The population percentile of each waist circumference level as well as the sensitivity, specificity, and distance on the ROC curve for the detection of hypertension, dyslipidemia, diabetes, and ≥2 of these risk factors are presented in Table 6Go for men and women separately. The specificity, sensitivity, and distances on the ROC curves were similar for all 3 cardiovascular disease risk factors among both men and women. For men, the point at which sensitivity equaled specificity was between waist circumference values of 80 and 85 cm for all risk factors, with exception of dyslipidemia (waist circumference between 75 and 80 cm). For women, the point at which sensitivity equaled specificity was between waist circumference values of 75 and 80 cm for all risk factors. The shortest distance on the ROC curve was at 80 cm for both men and women for all risk factors, except for dyslipidemia among women (75 cm).


View this table:
[in this window]
[in a new window]
 
TABLE 6. Sensitivity (Sens), specificity (Spec), and distance in the receiver operating characteristic (ROC) curve for waist circumference cutoffs

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
These data show that most of the general Chinese adult population has a BMI <25 and a waist circumference <94 cm for men and <80 cm for women, the current WHO cutoffs for the designation of overweight and central adiposity, respectively (7). Additionally, these data show a continuous increase in mean cardiovascular disease risk factor levels and prevalence of hypertension, diabetes, and dyslipidemia with higher BMIs and waist circumferences among Chinese adults. Based on the sensitivity, specificity, and ROC calculations, these data suggest a BMI of 24 and a waist circumference of 80 cm for both men and women as more appropriate cutoffs for the designation of overweight and central adiposity in the Chinese population.

Despite low BMIs and waist circumferences in China, cardiovascular disease is now the leading cause of death in China, with mortality projected to increase over the next decade (23, 24). In the current study, mean values of cardiovascular disease risk factors and prevalences of hypertension, dyslipidemia, and diabetes were higher with each successively higher BMI and waist circumference level. These data agree with other studies in Chinese and other Asian populations documenting linear relations between BMI or waist circumference and cardiovascular disease risk factors (13, 25-27). Evidence shows that Asian populations have a higher percentage of body fat than do Western populations for a given BMI or waist circumference (10-12, 28, 29). This may be partially responsible for the greater prevalence of cardiovascular disease risk factors at low BMI and waist circumference values as shown by the present study and others (13-16). These findings strongly corroborate the need for Asian-specific cutoffs of BMI and waist circumference as called for by the report of the joint WHO/IASO/IOTF committee.

Since the joint WHO/IASO/IOTF committee report, several studies have examined appropriate cutoffs for overweight in Asian populations (13, 14, 16, 26, 27, 30). The cutoffs proposed to define overweight and central adiposity have been lower than those established in the original WHO recommendations, with the exception of waist circumference for women (7), and have also been lower than those recommended by the joint WHO/IASO/IOTF committee for central adiposity (90 cm for men and 80 cm for women) (17). Most studies have suggested a BMI cutoff of 22–24 for men and women and a waist circumference cutoff near 75–80 cm for women and 80–85 cm for men (13, 14, 16, 25-27, 30). The present study is the first to examine appropriate BMI and waist circumference cutoffs in a representative sample of the general adult Chinese population and suggests cutoffs similar to those reported in other studies of Asian populations.

Efficient clinical practice requires guidelines for the identification of individuals who should be targeted for monitoring, prevention, and possible treatment. The cutoffs recommended here were identified as the values of BMI and waist circumference that best balanced sensitivity and specificity. This decision rule accommodates the desire to prevent a significant proportion of cardiovascular disease events, the clinical practice burden of population-wide prevention and treatment efforts, and the patient burden of being labeled as being at increased risk of cardiovascular disease. Given the continuous increase in prevalence of cardiovascular disease risk factors with increasing BMI and waist circumference shown by the present data, it must be acknowledged that all cutoffs are arbitrary; no threshold in BMI or waist circumference can be determined whereby values below the threshold confer no increased risk of cardiovascular disease and values above confer a uniform increased risk. We encourage the use of these data by a collaboration of public health agencies and health professionals in China and other Asian countries who can first decide on the collective tolerance of false positives and false negatives that should correspond to official overweight and central adiposity definitions.

The slight differences in suggested values between all of the studies that have sought to determine Asian-specific clinical cutoffs for BMI and waist circumference may reflect different decision rules regarding the acceptable relative amounts of over- and underpresumption of cardiovascular disease risk. Alternatively, they may represent underlying differences in the body fat percentage corresponding to a given BMI or waist circumference value between Asians of different ethnic backgrounds (28). Whether it is appropriate to apply the same BMI and waist circumference cutoffs to all Asian populations needs to be addressed further.

The present study has several strengths. This was a representative sample of the general adult Chinese population. Thus, these results can be generalized to the full adult population of mainland China aged 35–74 y. Additionally, we provided data for a wide range of BMI and waist circumference values, stratified by sex, to enable the use of these data by Asian public health officials for the development of BMI and waist circumference definitions based on decision rules that may differ from those we applied. These data are cross-sectional, however. One meta-analysis utilizing prospective data confirmed the need for a lower cutoff among Chinese adults, but this was not based on a nationally representative sample (31). However, prospective studies assessing all-cause mortality have not shown a need for lower cutoffs in Asians; relative risk of mortality was increased only for those in the highest BMI categories (BMI of 30–39.9; 32). Future studies in a representative sample of the adult Chinese population that prospectively relate the BMI and waist circumference cutoffs suggested here to the incidence of hypertension, dyslipidemia, diabetes, clinical cardiovascular disease events, cardiovascular disease mortality, and all-cause mortality are needed. To adequately address inconsistencies in the literature, these future studies will need to examine Asian and Western populations together, enabling direct comparisons (33). These future studies will also need to examine the suggested cutoffs on the basis of both relative risk of cardiovascular disease and sensitivity-specificity. The present study did not have direct measures of body fatness or fat distribution. Because BMI and waist circumference are supposed surrogates for body fatness and fat distribution, future research is needed into racial-ethnic differences in the relations between BMI, waist circumference, and actual body fatness and body fat distribution.

The high prevalences of hypertension, dyslipidemia, and diabetes at low BMI and waist circumference values shown here among Chinese adults strongly argue for lower Asian-specific BMI and waist circumference cutoffs for use in clinical practice. These data show a BMI value of 24 and a waist circumference value of 80 cm in both men and women as appropriate for use in the identification of high-risk Chinese patients. The continuous relation between cardiovascular disease risk factors and BMI and waist circumference documented here, together with the increasing incidence of cardiovascular disease morbidity and mortality in China, underscore the importance that Chinese health care professionals are given an appropriate definition of overweight for immediate use in screening.


    ACKNOWLEDGMENTS
 
RPW performed all data analyses and wrote the manuscript. KR aided in data management and provided significant advice and consultation on the manuscript. DG, XD, and JH aided in the design of the experiment and the collection of data and provided significant advice and consultation on the manuscript. Several researchers employed by Pfizer Inc were members of the steering committee that designed the study. However, the study was conducted, analyzed, and interpreted by the investigators independently of the sponsor.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Kurth T, Gaziano JM, Berger K, et al. Body mass index and the risk of stroke in men. Arch Intern Med 2002;162:2557-62.[Abstract/Free Full Text]
  2. Dey DK, Rothenberg E, Sundh V, Bosaeus I, Steen B. Waist circumference, body mass index, and risk for stroke in older people: a 15 year longitudinal population study of 70-year-olds. J Am Geriatr Soc 2002;50:1510-8.[Medline]
  3. Wilson PW, D'Agostino RB, Sullivan L, Parise H, Kannel WB. Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch Intern Med 2002;162:1867-72.[Abstract/Free Full Text]
  4. Stevens J, Cai J, Evenson KR, Thomas R. Fitness and fatness as predictors of mortality from all causes and from cardiovascular disease in men and women in the lipid research clinics study. Am J Epidemiol 2002;156:832-41.[Abstract/Free Full Text]
  5. National Heart, Lung, and Blood Institute. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. Obes Res 1998;6(suppl):51S-209S.[Medline]
  6. National Task Force on the Prevention and Treatment of Obesity. Overweight, obesity, and health risk. Arch Intern Med 2000;160:898-904.[Abstract/Free Full Text]
  7. WHO: Obesity: preventing and managing the global epidemic. Report of a WHO consultation of obesity, Geneva, 1997, World Health Organization. Obes Res 1998;6:51S-210S.
  8. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79:379-84.[Abstract/Free Full Text]
  9. Bigaard J, Tjonneland A, Thomsen BL, Overvad K, Heitmann BL, Sorensen TIA. Waist circumference, BMI, smoking, and mortality in middle-aged men and women. Obes Res 2003;11:895-903.[Medline]
  10. Deurenberg P, Yap M, van Staveren WA. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord 1998;22:1164-71.[Medline]
  11. Chang CJ, Wu CH, Chang CS, et al. Low body mass index but high percent body fat in Taiwanese subjects: implications of obesity cutoffs. Int J Obes Relat Metab Disord 2003;27:253-9.[Medline]
  12. He M, Tan KC, Li ET, Kung AW. Body fat determination by dual energy X-ray absorptiometry and its relation to body mass index and waist circumference in Hong Kong Chinese. Int J Obes Relat Metab Disord 2001;25:748-52.[Medline]
  13. Pan WH, Flegal KM, Chang HY, Yeh WT, Yeh CJ, Lee WC. Body mass index and obesity-related metabolic disorders in Taiwanese and US whites and blacks: implications for definitions of overweight and obesity for Asians. Am J Clin Nutr 2004;79:31-9.[Abstract/Free Full Text]
  14. Moon OR, Kim NS, Jang SM, Yoon TH, Kim SO. The relationship between body mass index and the prevalence of obesity-related diseases based on the 1995 National Health Interview Survey in Korea. Obes Rev 2002;3:191-6.[Medline]
  15. Vikram NK, Pandey RM, Misra A, Sharma R, Devi JR, Khanna N. Non-obese (body mass index < 25 kg/m2) Asian Indians with normal waist circumference have high cardiovascular risk. Nutrition 2003;19:503-9.[Medline]
  16. Deurenberg-Yap M, Chew SK, Deurenberg P. Elevated body fat percentage and cardiovascular risks at low body mass index levels among Singaporean Chinese, Malays and Indians. Obes Rev 2002;3:209-15.[Medline]
  17. The World Health Organization Western Pacific Region, The International Association for the Study of Obesity, and The International Obesity Task Force. The Asia-Pacific perspective: redefining obesity and its treatment. Sydney: Health Communications Australia Pty Limited, 2000.
  18. He J, Neal B, Gu D, et al. International Collaborative Study of Cardiovascular Disease in Asia: design, rationale, and preliminary results. Ethnic Dis 2004;14:260-8.[Medline]
  19. Perloff D, Grim C, Flack J, et al. Human blood pressure determination by sphygmomanometry. Circulation 1993;88:2460-70.[Free Full Text]
  20. Allain CC, Poon LS, Chan CSG, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem 1974;20:470-5.[Abstract]
  21. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of preparative ultracentrifuge. Clin Chem 1972;18:499-502.[Abstract]
  22. He J, Gu D, Reynolds K, et al. Serum total and lipoprotein cholesterol levels and awareness, treatment, and control of hypercholesterolemia in China. Circulation 2004;110:405-11.[Abstract/Free Full Text]
  23. Murray CJ, Lopez AD. Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997;349:1269-76.[Medline]
  24. Murray CJL, Lopez AD. Global pattern of cause of death and burden of disease in 1990, with projections to 2020 investing in health research and development. Report of the ad hoc Committee on Health Research Relation to Future Intervention Options. Geneva: World Health Organization, 1996.
  25. Ko GT, Chan JC, Cockram CS, Woo J. Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese. Int J Obes Relat Metab Disord 1999;23:1136-42.[Medline]
  26. Zhou BF, Cooperative Meta-Analysis Group of the Working Group on Obesity in China. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults–study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci 2002;15:83-96.[Medline]
  27. Li G, Chen X, Jang Y, et al. Obesity, coronary heart disease risk factors and diabetes in Chinese: an approach to the criteria of obesity in the Chinese population. Obes Rev 2002;3:167-72.[Medline]
  28. Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev 2002;3:141-6.[Medline]
  29. Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr 2000;72:694-701.[Abstract/Free Full Text]
  30. Ito H, Nakasuga K, Ohshima A, et al. Detection of cardiovascular risk factors by indices of obesity obtained from anthropometry and dual-energy X-ray absorptiometry in Japanese individuals. Int J Obes Relat Metab Disord 2003;27:232-7.[Medline]
  31. Zhou BF. Effect of body mass index on all-cause mortality and incidence of cardiovascular diseases–report for meta-analysis of prospective studies open optimal cut-off points of body mass index in Chinese adults. Biomed Environ Sci 2002;15:245-52.[Medline]
  32. Stevens J, Nowicki EM. Body mass index and mortality in Asian populations: implications for obesity cut-points. Nutr Rev 2003;61:104-7.[Medline]
  33. Stevens J. Ethnic-specific revisions of body mass index cutoffs to define overweight and obesity in Asians are not warranted. Int J Obes Relat Metab Disord 2003;27:1297-9.[Medline]
Received for publication April 5, 2004. Accepted for publication June 21, 2004.




This article has been cited by other articles:


Home page
Am. J. Clin. Nutr.Home page
N. T Tuan, L. S Adair, C. M Suchindran, K. He, and B. M Popkin
The association between body mass index and hypertension is different between East and Southeast Asians
Am. J. Clinical Nutrition, June 1, 2009; 89(6): 1905 - 1912.
[Abstract] [Full Text] [PDF]


Home page
J. Nutr.Home page
N. T. Tuan, L. S. Adair, K. He, and B. M. Popkin
Optimal Cutoff Values for Overweight: Using Body Mass Index to Predict Incidence of Hypertension in 18- to 65-Year-Old Chinese Adults
J. Nutr., July 1, 2008; 138(7): 1377 - 1382.
[Abstract] [Full Text] [PDF]


Home page
Am J EpidemiolHome page
J. Stevens, K. P. Truesdale, E. G. Katz, and J. Cai
Impact of Body Mass Index on Incident Hypertension and Diabetes in Chinese Asians, American Whites, and American Blacks: The People's Republic of China Study and the Atherosclerosis Risk in Communities Study
Am. J. Epidemiol., June 1, 2008; 167(11): 1365 - 1374.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
S. A Lear, K. H Humphries, S. Kohli, A. Chockalingam, J. J Frohlich, and C L. Birmingham
Visceral adipose tissue accumulation differs according to ethnic background: results of the Multicultural Community Health Assessment Trial (M-CHAT)
Am. J. Clinical Nutrition, August 1, 2007; 86(2): 353 - 359.
[Abstract] [Full Text] [PDF]


Home page
Health Educ ResHome page
L. McLaren, L. M. Ghali, D. Lorenzetti, and M. Rock
Out of context? Translating evidence from the North Karelia project over place and time
Health Educ. Res., June 1, 2007; 22(3): 414 - 424.
[Abstract] [Full Text] [PDF]


Home page
JAMAHome page
D. Gu, J. He, X. Duan, K. Reynolds, X. Wu, J. Chen, G. Huang, C.-S. Chen, and P. K. Whelton
Body Weight and Mortality Among Men and Women in China
JAMA, February 15, 2006; 295(7): 776 - 783.
[Abstract] [Full Text] [PDF]


Home page
Int J EpidemiolHome page
M. Snijder, R. van Dam, M Visser, and J. Seidell
What aspects of body fat are particularly hazardous and how do we measure them?
Int. J. Epidemiol., February 1, 2006; 35(1): 83 - 92.
[Full Text] [PDF]


Home page
JAMAHome page
D. L. Bhatt, P. G. Steg, E. M. Ohman, A. T. Hirsch, Y. Ikeda, J.-L. Mas, S. Goto, C.-S. Liau, A. J. Richard, J. Rother, et al.
International Prevalence, Recognition, and Treatment of Cardiovascular Risk Factors in Outpatients With Atherothrombosis
JAMA, January 11, 2006; 295(2): 180 - 189.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
R. P Wildman, D. Gu, K. Reynolds, X. Duan, X. Wu, and J. He
Are waist circumference and body mass index independently associated with cardiovascular disease risk in Chinese adults?
Am. J. Clinical Nutrition, December 1, 2005; 82(6): 1195 - 1202.
[Abstract] [Full Text] [PDF]


Home page
Journals of Gerontology Series A: Biological Sciences and Medical SciencesHome page
A. Raman, R. J. Colman, Y. Cheng, J. W. Kemnitz, S. T. Baum, R. Weindruch, and D. A. Schoeller
Reference Body Composition in Adult Rhesus Monkeys: Glucoregulatory and Anthropometric Indices
J. Gerontol. A Biol. Sci. Med. Sci., December 1, 2005; 60(12): 1518 - 1524.
[Abstract] [Full Text] [PDF]


Home page
J Am Coll CardiolHome page
G. Levantesi, A. Macchia, R. Marfisi, M. G. Franzosi, A. P. Maggioni, G. L. Nicolosi, C. Schweiger, L. Tavazzi, G. Tognoni, F. Valagussa, et al.
Metabolic Syndrome and Risk of Cardiovascular Events After Myocardial Infarction
J. Am. Coll. Cardiol., July 19, 2005; 46(2): 277 - 283.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.
Agricola
Right arrow Articles by Wildman, R. P
Right arrow Articles by He, J.


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS