Body Mass Index, Waist Circumference, and Health Risk:  Evidence in Support of Current National Institutes of Health Guidelines FREE

IN 1998, the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) published evidence-based clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults.¹ These guidelines included a classification system for assessing health risk based on the body mass index (BMI; calculated as weight in kilograms divided by the square of height in meters) and waist circumference (WC). In this classification system, a patient is placed in 1 of 6 BMI categories (underweight, normal-weight, overweight, or class I, II, or III obese) and 1 of 2 WC categories (normal or high). The relative health risk is then graded on the basis of the combined BMI and WC. The health risk increases in a graded fashion when moving from the normal-weight through class III obese BMI categories,^2- 3 and it is assumed that within the normal-weight, overweight, and class I obese BMI categories, patients with high WC values have a greater health risk than patients with normal WC values. This classification system was developed on the basis of the knowledge that an increase in BMI is associated with an increase in health risk, that abdominal or android obesity is a greater risk factor than lower-body or gynoid obesity, and that the WC is an index of abdominal fat content.¹

The sex-specific WC cutoff points used in the NIH guidelines were originally developed by Lean and colleagues,⁴ who compared the WC and the BMI in a large and heterogeneous sample of white men and women. In that sample, a WC of 102 cm in men and 88 cm in women corresponded to a BMI of 30.0. Although subsequent studies have shown that men and women with WC values above 102 and 88 cm, respectively, are at increased health risk compared with men and women with WC values below these cutoff points,^5- 10 these studies did not control for the effects of BMI when examining the differences in disease between individuals with high and low WC values. Thus, no evidence confirms that the NIH WC cutoff points predict health risk beyond that already predicted by the BMI.

The purpose of this investigation was to determine whether the prevalence of hypertension, type 2 diabetes mellitus, dyslipidemia, and a clustering of metabolic risk factors is greater in individuals with high WC values compared with individuals with normal WC values within the same BMI category. We used metabolic and anthropometric data from the Third National Health and Nutrition Examination Survey (NHANES III), which is a large cohort representative of the US population.

The NHANES III was conducted by the National Center for Health Statistics, Hyattsville, Md, and the Centers for Disease Control and Prevention, Atlanta, Ga, to estimate the prevalence of major diseases, nutritional disorders, and potential risk factors for these diseases. The NHANES III was a nationally representative, 2-phase, 6-year, cross-sectional survey conducted from 1988 through 1994. The complex sampling plan used a stratified, multistage, probability-cluster design. The total sample included 33 199 persons. Full details of the study design, recruitment, and procedures are available from the US Department of Health and Human Services.^11- 12 Of the total sample, 14 924 subjects were 17 years or older in whom measures of the WC, height, weight, and metabolic variables were obtained and who fit the BMI categories examined. Informed consent was obtained from all participants, and the protocol was approved by the National Center for Health Statistics.

Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively, using standardized equipment and procedures.^11- 13 The BMI was subsequently determined from these measures. The WC measurement was made at minimal inspiration to the nearest 0.1 cm, midway between the last rib and the iliac crest.^11- 13

Three blood pressure measurements were obtained at 60-second intervals with the subject in a seated position using a standard manual mercury sphygmomanometer.^11- 12 We used the average of the 3 readings for this analysis. Blood samples were obtained after a minimum 6-hour fast for the measurement of serum cholesterol, triglyceride, lipoprotein, and glucose levels as described in detail elsewhere.^11- 12,14 Briefly, cholesterol and triglyceride levels were measured enzymatically in a series of coupled reactions hydrolyzing cholesterol ester and triglyceride to cholesterol and glycerol, respectively. Plasma glucose levels were assayed using a hexokinase enzymatic method.^11- 12,15

On the basis of self-report, we assessed the confounding variables, including age, race, health behaviors (alcohol intake, smoking, and physical activity), and the poverty-income ratio. Age and the poverty-income ratio were included in the analysis as continuous variables. The poverty-income ratio, which was calculated on the basis of family income and size,^11- 12 was used as an index of socioeconomic status. Race was coded as 0 for non-Hispanic white, 1 for non-Hispanic black, and 2 for Hispanic subjects and as 3 for subjects of other races. Alcohol consumption was graded as none (0 drinks/mo), moderate (1-15 drinks/mo), or heavy (>15 drinks/mo). Subjects were considered current smokers if they smoked at the time of the interview, previous smokers if they were not current smokers but had smoked 100 cigarettes, 20 cigars, or 20 pipefuls of tobacco in their entire life, and nonsmokers if they smoked less than these amounts. Leisure-time physical activity was graded as none (<4 times/mo), low (4-10 times/mo), moderate (11-19 times/mo), or high (>19 times/mo).

Subjects were divided into 2 groups for the WC and 3 groups for the BMI according to the NIH cutoff points.¹ Men and women with WC values of no greater than 102 and 88 cm, respectively, were considered to have a normal WC, whereas men and women with WC values of greater than 102 and 88 cm, respectively, were considered to have a high WC. On the basis of their BMI, subjects were classified as normal weight (18.5-24.9), overweight (25.0-29.9), or class I obese (30.0-34.9). Because all subjects who were underweight (BMI<18.5) had normal WC values and all subjects with class II and III obesity (BMI≥35.0) had high WC values, they were excluded from the data analysis.

Hypertension and type 2 diabetes were defined according to the guidelines of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure¹⁶ and the American Diabetes Association,¹⁷ respectively. Dyslipidemia and the metabolic syndrome were defined according to the latest National Cholesterol Education Program guidelines.¹⁸ The metabolic syndrome, which is also known as syndrome X and the insulin resistance syndrome, represents a clustering of plasma lipid and glucose and blood pressure risk factors. Hypertension was defined as systolic blood pressure of at least 140 mm Hg, diastolic blood pressure of at least 90 mm Hg, or the use of antihypertensives. Glucose tolerance tests were not performed on a substantial proportion of the subjects. Therefore, we considered subjects to have type 2 diabetes if they reported that their physician had ever told them they had diabetes (only if diabetes was diagnosed after age 25 years and occurred outside of pregnancy), if they reported using insulin or a hypoglycemic agent, or if they had a fasting glucose level of greater than125 mg/dL (>6.9 mmol/L). Dyslipidemia was defined as hypercholesterolemia (total cholesterol level, ≥240 mg/dL [≥6.2 mmol/L]), high low-density lipoprotein (LDL) cholesterol level (≥160 mg/dL [≥4.1 mmol/L]), low high-density lipoprotein (HDL) cholesterol level (<40 mg/dL [<1.0 mmol/L]), or hypertriglyceridemia (serum triglyceride level, ≥200 mg/dL [≥2.3 mmol/L]). Metabolic syndrome was defined as 3 or 4 of the following: triglyceride level of at least 150 mg/dL (≥1.7 mmol/L), HDL cholesterol level of less than 40 mg/dL (<1.0 mmol/L) in men or less than 50 mg/dL (<1.3 mmol/L) in women, blood pressure of at least 130/85 mm Hg, or fasting glucose level of at least 110 mg/dL (≥6.1 mmol/L).

The Intercooled Stata 7 program¹⁹ was used to properly weight the sample to be representative of the population and to take into account the complex sampling strategy of the NHANES III design. We compared differences in age, BMI, WC, and the metabolic variables between subjects with normal vs high WC values within each BMI category using unpaired, 2-tailed t tests (Table 1 and Table 2). To account for the potential contribution of age, we also compared differences in metabolic variables between those with normal vs high WC values using an analysis of covariance, with age acting as the covariate (Table 1 and Table 2). We compared prevalences of hypertension, type 2 diabetes, dyslipidemia, and the metabolic syndrome in those with normal vs high WC values within each BMI category using χ² statistics (Table 1 and Table 2). We used logistic regression analysis to examine the associations between WC classification and metabolic risk within the normal-weight, overweight, and class I obese BMI categories (Table 3). Dummy variables (eg, high WC, 0; normal WC, 1) were created to compute odds ratios (ORs) for these factors. A normal WC was used as the reference category (OR, 1.00). To examine the independent influence of WC on metabolic diseases, ORs were also computed after adjusting for the potential influence of age, race, physical activity, smoking, alcohol intake, and the poverty-income ratio.

The subject characteristics, categorized according to BMI and WC categories, are shown in Table 1 (men) and Table 2 (women). In the normal-weight BMI category, 1.0% of the men and 13.7% of the women had WC values within the high range. In the overweight BMI category, 27.6% of the men and 71.6% of the women had WC values within the high range. In the class I obese BMI category, 84.8% of the men and 97.5% of the women had WC values within the high range. Independent of sex and within each of the 3 BMI categories, subjects with normal WC values were younger and tended to have a more favorable metabolic profile (eg, lower mean blood pressure and glucose and cholesterol values) compared with subjects with high WC values (Table 1 and Table 2). In addition, in both sexes and in all BMI categories, the prevalence of hypertension, type 2 diabetes, dyslipidemia (hypercholesterolemia, high LDL cholesterol or low HDL cholesterol level, or hypertriglyceridemia), and the metabolic syndrome tended to be higher in subjects with high WC values compared with those with normal WC values (Table 1 and Table 2).

Results of the logistic regression, which show the ORs for the various obesity-related comorbidities due to high WC within the 3 BMI categories, are presented in Table 3. In the normal-weight BMI category in men, the odds of hypertension and type 2 diabetes were increased (P<.05) for those with high WC values compared with those with normal WC values. In the normal-weight BMI category in women, the odds for all of the comorbidities were increased (P<.05) for those with high WC values. With the exception of hypertension in men and high LDL cholesterol level and type 2 diabetes in women, these observations remained significant (P<.05) after adjustment for the potential contributions of age, race, health behaviors (eg, physical activity, smoking, and alcohol intake), and the poverty-income ratio.

In the overweight BMI category, the ORs for all comorbidities were increased (P<.05) in the men and women with high WC values compared with the men and women with normal WC values (Table 3). Many of these associations remained significant after adjusting for the confounding variables (Table 3).

In the class I obese BMI category, the odds of hypertension and the metabolic syndrome were increased (P<.05) in men with high WC values. In women, the odds of hypertension, type 2 diabetes, high LDL cholesterol level, and the metabolic syndrome were increased (P<.05) for subjects with high WC values. With the exception of hypertension in men, the associations between a high WC value and these comorbidities in the class I obese subjects remained significant after adjusting for the confounding variables (P<.05; Table 3).

The results of this study indicate that the health risk is greater in normal-weight, overweight, and class I obese women with high WC values compared with normal-weight, overweight, and class I obese women with normal WC values, respectively. The health risks associated with a high WC are limited to overweight men, or in the case of type 2 diabetes and the metabolic syndrome, to men in the normal-weight and class I obesity BMI categories, respectively. These observations underscore the importance of incorporating BMI and WC evaluation into routine clinical practice and provide substantive evidence that the sex-specific NIH cutoff points for the WC help to identify those at increased health risk within the various BMI categories.

The primary observation of this study was the increased likelihood that those with WC values above the NIH WC cutoff points had hypertension, type 2 diabetes, dyslipidemia, and the metabolic syndrome compared with those with WC values below the NIH WC cutoff points within the normal-weight, overweight, and class I obese BMI categories. This finding has important clinical implications, given the widespread use of the NIH classification system, given that most (approximately 90%) Americans fit within the normal-weight, overweight, or class I obese BMI categories,²⁰ and given that a mixture of subjects with normal and high WC values was found within these 3 BMI categories (particularly the overweight category). Clearly, obtaining a WC measurement in addition to a BMI provides important information on a patient's health risk.

The additional health risk explained by the WC likely reflects its ability to act as a surrogate for abdominal, and in particular, visceral fat. Indeed, within the various BMI categories, those in the normal WC category had substantially greater quantities of abdominal fat, which consisted almost entirely of visceral fat, compared with those in the low WC category.²¹ Moreover, because WC is only a modest predictor of abdominal subcutaneous and nonabdominal (eg, subcutaneous fat in the periphery) fat after controlling for the BMI, abdominal subcutaneous and nonabdominal fat might not be the primary vehicles by which the WC explains health risk beyond that predicted by the BMI.²¹

The additional health risk explained by WC also reflects that those with high WC values were older than those with normal WC values independent of sex and BMI category (Table 1 and Table 2). Indeed, adjusting for age diminished the strength of the associations between high WC values and hypertension, diabetes, dyslipidemia, and the metabolic syndrome. However, a high WC remained a significant predictor of obesity-related comorbidity after adjusting for age and the other confounding variables.

In this study, the effects of a high WC were more apparent in the women than in the men. For example, in the overweight BMI category, the adjusted ORs for type 2 diabetes were 1.99 in the men with a high WC and 4.07 in the women with a high WC, compared with the men and women, respectively, with a normal WC. This sex difference may be partially explained by the fact that the prevalences of the metabolic diseases were considerably higher in the men than in the women with a low WC. In reference to the example used above, 2.7% of the overweight men with a normal WC had type 2 diabetes, whereas only 1.6% of the overweight women with a normal WC had type 2 diabetes. However, the prevalence of type 2 diabetes was similar in the overweight men (10.6%) and women (10.0%) with a high WC. Thus, because the ORs were determined within each sex by comparing the subjects with a high WC with the subjects with a normal WC, the higher ORs observed in the women with a high WC may be explained by the lower prevalences of the metabolic diseases in the women with a normal WC.

The finding that subjects with high WC values had a greater health risk compared with those with low WC values within the same BMI category does not imply that WC values of 102 cm in men and 88 cm in women are the ideal threshold values to denote increased health risk. The WC values that best predict health risk within the different BMI categories are unknown. Furthermore, considering that the relationship between the WC and visceral fat is influenced by race²² and age,^23- 24 the ideal WC cutoff points likely differ depending on race and age. Additional studies are required to determine the ideal WC threshold values to use in combination with the BMI.

The NIH classification system uses a dichotomous approach (normal vs high) to establish the associations between the WC and health risk.¹ However, the WC is related to health risk in a linear fashion.^5,25- 26 Thus, some authors have suggested using a graded system for assessment of health risk based on WC,^4- 5,8,27 which is similar to the method currently advocated for the BMI by the NIH. For example, Lean and colleagues⁴ proposed that WC values of less than 94 cm in men and of less than 80 cm in women denote a low health risk; those ranging from 94 to 102 cm in men and 80 to 88 cm in women, a moderately increased health risk; and those greater than 102 cm in men and greater than 88 cm in women, a substantially increased health risk. When we subdivided the subjects in the normal-weight and overweight BMI categories into the 3 WC categories proposed by Lean and colleagues,⁴ we observed that disease risk was lower in those with low WC values (men, <94 cm; women, <80 cm) compared with those with moderately elevated WC values (men, 94-102 cm; women, 80-88 cm); subjects with moderately elevated WC values in turn had a lower disease risk compared with those with high WC values (men, >102 cm; women, >88 cm) (data not shown). The clinical implication is that individuals with WC values moderately below the NIH cutoff points (eg, men, 94-102 cm; women, 80-88 cm) are at increased health risk compared with those within the same BMI category who have WC values considerably below the NIH cutoff points (eg, men, <94 cm; women <80 cm). This finding also suggests that consideration of the WC in the same way as the BMI, in which there are more than 2 risk strata, might be more appropriate.

Given that the subject pool was large and representative of the US population, the NHANES III was perhaps the best data set to test our hypothesis. Nonetheless, our study has 2 limitations that should be recognized. First, the cross-sectional nature of this study precludes definitive causal inferences about the associations between the BMI and the WC and disease. However, numerous studies have shown that high BMI and WC values precede the onset of morbidity and mortality.^28- 31 Second, there was a potential bias due to survey nonresponse and missing values for some of the metabolic and confounding variables. However, previous NHANES studies have shown little bias due to nonresponse.³²

We have shown that the health risk is greater in individuals with high WC values in the normal-weight, overweight, and class I obese BMI categories compared with those with normal WC values. Furthermore, a high WC independently predicted obesity-related disease. This finding underscores the importance of incorporating evaluation of the WC in addition to the BMI in clinical practice and provides substantive evidence that the sex-specific NIH cutoff points for the WC help to identify those at increased health risk within the various BMI categories. Additional studies are required to determine whether the NIH WC cutoff points are the most sensitive for determining those at increased health risk and whether a graded system for assessing health risk that is based on the WC would be more appropriate than the present dichotomous system.

Accepted for publication February 27, 2002.

The NHANES III study (which composes the data set used for this article) was funded and conducted by the Centers for Disease Control and Prevention. Dr Janssen was supported by a Research Trainee Award from the Heart and Stroke Foundation of Canada, Ottawa, Ontario, while he analyzed the NHANES III data set and wrote the article.

Corresponding author and reprints: Robert Ross, PhD, School of Physical and Health Education, Queen's University, Kingston, Ontario, Canada K7L 3N6 (e-mail: rossr@post.queensu.ca).