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American Journal of Clinical Nutrition, Vol. 81, No. 6, 1313-1321, June 2005
© 2005 American Society for Clinical Nutrition

ORIGINAL RESEARCH COMMUNICATION

Measures of adiposity in the identification of metabolic abnormalities in elderly men 1,2,3,4

S Goya Wannamethee, A Gerald Shaper, Richard W Morris and Peter H Whincup

1 From the Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, United Kingdom (SGW, AGS, and RWM), and the Department of Public Health Sciences, St George's Medical School Hospital, London, United Kingdom (PHW)

2 The views expressed in this publication are those of the authors and not necessarily those of the Department of Health (United Kingdom).

3 The British Regional Heart Study is a British Heart Foundation Research Group and receives support from the Department of Health (United Kingdom).

4 Address reprint requests to SG Wannamethee, Department of Primary Care and Population Sciences, Royal Free and University College Medical School, Rowland Hill Street, London NW3 2PF, United Kingdom. E-mail: goya{at}pcps.ucl.ac.uk.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Body mass index (BMI; in kg/m2) is considered a poor indicator of overall and abdominal obesity in the elderly.

Objectives: Our goal was to determine which simple anthropometric measurements [BMI, waist-to-hip ratio (WHR), waist circumference (WC), percentage body fat (%BF), or fat mass (FM)] are most closely associated with metabolic risk factors and insulin resistance in elderly men.

Design: This was a cross-sectional study of 2924 men aged 60–79 y with no history of coronary heart disease, stroke, or diabetes who were drawn from general practices in 24 British towns.

Results: BMI and WC were the measures most strongly associated with the metabolic syndrome (≥3 of the following: hypertension, low HDL cholesterol, high triacylglycerols, or high blood glucose) and insulin resistance. For a 1-SD increase in BMI, WC, WHR, %BF, and FM, the odds ratios (95% CIs) of having the metabolic syndrome after adjustment for age, socioeconomic status, smoking status, and physical activity were as follows: BMI, 1.61 (1.44, 1.79); WC, 1.65 (1.48, 1.81); WHR, 1.49 (1.34, 1.66); %BF, 1.41 (1.25, 1.59); and FM, 1.53 (1.38, 1.70). For insulin resistance, the odds ratios (95% CIs) were as follows: 2.48 (2.22, 2.77), 2.46 (2.19, 2.65), 1.75 (1.59, 1.93), 1.79 (1.60, 2.00), and 2.10 (1.88, 2.34), respectively. In normal-weight (BMI < 25) and overweight (BMI 25–29.9) men, the presence of the metabolic syndrome and insulin resistance increased with increasing WC; this did not occur in obese men.

Conclusions: BMI and WC are the simple measures of adiposity most strongly associated with metabolic abnormalities in elderly men. Our findings suggest that WC can be used as a complementary measurement to identify health risks in normal-weight and overweight elderly persons.

Key Words: BMI • waist circumference • percentage body fat • metabolic syndrome • insulin resistance


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The metabolic syndrome, which is defined by a cluster of risk factors that include obesity, hypertension, hyperglycemia, and dyslipidemia, identifies individuals at increased risk of type 2 diabetes and cardiovascular disease (1, 2). As obesity has become more common (3), the prevalence of the metabolic syndrome has increased, and these trends are likely to continue (4, 5). It is estimated that {approx}27% of US adults have the metabolic syndrome, and this figure increases to >40% in subjects aged >60 y (4, 5). Body mass index (BMI; in kg/m2) is widely used to measure overweight and obesity, and the World Health Organization (WHO) and the National Institutes of Health (NIH) use similar BMI cutoffs to define overweight (BMI > 25) and obesity (BMI > 30) (6, 7). It is now accepted that the distribution of body fat is an important determinant of metabolic abnormalities, possibly more so than the degree of excess weight as measured by BMI (8). In particular, intraabdominal obesity or visceral fat is strongly associated with metabolic disturbances and insulin resistance (9, 10).

Because body fat is more likely to be deposited in the abdominal cavity with increasing age, it is claimed that BMI becomes a poor indicator of overall and abdominal fatness in older persons (11, 12). Waist circumference (WC) has been recommended as a better indicator of abdominal visceral fat than BMI (11, 13). Recent studies, mainly carried out in younger or middle-aged populations, suggest that WC is a better anthropometric guide to metabolic risk factor status than is BMI and that WC and not BMI explains obesity-related health risks (14, 15). Bioelectrical impedance analysis has been used to estimate body fatness, and percentage body fat (%BF) estimated by this method may be superior to BMI as an index of body fatness (16). Thus, in older men, measures of body fat such as WC and %BF may potentially be more sensitive indicators of disease risk than is BMI. Despite this, a previous report from this study in older men (aged 60–79 y) showed BMI to be strongly associated with cardiovascular disease risk factors and insulin resistance (17). Other measures of adiposity, however, such as WC and %BF, were not addressed in that report.

We have now examined the associations between several indicators of adiposity [BMI, WC, waist-to-hip ratio (WHR), %BF, and fat mass (FM)] and metabolic factors associated with cardiovascular disease risk (hyperinsulinemia, serum triacylglycerols, serum HDL cholesterol, hypertension, blood glucose, and the metabolic syndrome) in men aged 60–79 y. The aim was to 1) determine which of these adiposity measures are the best predictors of metabolic risk factors and 2) assess whether the combination of BMI and other adiposity measures, particularly WC, is a better indicator of metabolic risk in older men than is BMI alone.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
The British Regional Heart Study is a prospective study of cardiovascular disease involving 7735 men aged 40–59 y selected from the age-sex registers of one general practice in each of 24 British towns and who were screened between 1978 and 1980 (18). Ethical approval was provided by all relevant local research ethics committees. All men provided written informed consent to the investigation, which was carried out in accordance with the Declaration of Helsinki. In 1998–2000, all surviving men, now aged 60–79 y, were invited for a 20th year follow-up examination. All men completed a questionnaire (Q20) that included questions on their medical history and lifestyle. The men were requested to fast for a minimum of 6 h, during which time they were instructed to drink only water, and to then attend a measurement session at a specified time between 0800 and 1800. All men were asked to provide a blood sample, which was collected by using the Sarstedt Monovette system (Sarstedt, Numbrecht, Germany). A total of 4252 men (77% of the survivors) attended the examination. Men with a physician's diagnosis of diabetes and those with a fasting glucose concentration ≥ 7 mmol/L (WHO criteria) were considered to have prevalent diabetes and were excluded (n = 497). To avoid confounding by cardiovascular disease, we further excluded men with a recall of a diagnosis of coronary heart disease, angina, or stroke (n = 831), because many of these men were likely to be taking lipid-lowering drugs, and a diagnosis of cardiovascular disease may lead to weight reduction (19). Thus, 2924 men were available for analysis. In a subsidiary analysis, we examined the relation in the 831 men with a diagnosis of cardiovascular disease.

Cardiovascular disease risk factors
Details of the measurement and classification methods for smoking status, physical activity, BMI, social class, blood pressure, HDL cholesterol, and triacylglycerols in this cohort have been described (17, 18, 20, 21). From the combined information collected at the initial screening (Q1; 1978–80), through follow-up questionnaires in 1996 (Q96), and at the re-screening (Q20), the men were classified into 5 smoking groups: 1) those who had never smoked, 2) exsmokers since the screening, 3) smokers at baseline who gave up smoking between the screening and Q96, 4) smokers at screening and Q96 who gave up smoking after 1996, and 5) current cigarette smokers at Q20. The longest held occupation of each man was recorded at the screening, and the men were grouped into one of 6 socioeconomic groups: I, II, III nonmanual (nonmanual groups), III manual, IV, and V (manual groups). Those whose longest occupation was in the armed forces formed a separate group. The men were grouped into 6 broad categories on the basis of their total physical activity score: inactive, occasional, light, moderate, moderately vigorous, and vigorous (20). The men were asked to report the number of alcoholic drinks taken weekly and were classified into 5 groups: none, <1 drink/d, 1–2 drinks/d, 3–4 drinks/d, and ≥5 drinks/d. Plasma glucose was measured by a glucose oxidase method with a Falcor 600 (A Menarini Diagnostics, Wokingham, United Kingdom) automated analyzer (22). Serum insulin was measured by using an enzyme-linked immunosorbent assay that does not cross-react with proinsulin (23). Triacylglycerols, blood glucose, and insulin concentrations were adjusted for the effects of fasting duration and time of day (21). Insulin resistance was estimated according to homeostasis model assessment (HOMA; 24):

(1)
HOMA showed a correlation with fasting insulin of 0.98.

Definition of metabolic risk factors and the metabolic syndrome
We defined metabolic risk factors as follows: 1) high glucose as fasting plasma glucose concentrations ≥110 mg/dL (6.1 mmol/L); 2) high triacylglycerols as serum triacylglycerol concentrations ≥150 mg/dL (1.7 mmol/L); 3) low HDL cholesterol as serum HDL-cholesterol concentrations <40 mg/dL (1.04 mmol/L), based on National Cholesterol Education Program (NCEP) definitions (25); and 4) hypertension as blood pressure of ≥140/90 mm Hg or receiving antihypertensive treatment. The NCEP definition (blood pressure ≥ 130/85 mm Hg) was not used for hypertension because 82% of the men would have been classified as hypertensive by this criterion. Men with ≥3 of these conditions were classified as having the metabolic syndrome. Although the NCEP guidelines include WC as a component of the metabolic syndrome, for our analysis, we did not include high WC in the diagnosis because it was one of the adiposity measures being compared with others. High HOMA (insulin resistance) was defined as being in the top quartile of the HOMA distribution.

Anthropometric measurements
The anthropometric variables measured at the reexamination included height, weight, waist and hip circumferences, %BF, and fat mass. Subjects were measured in light clothing without shoes. Height and weight were both measured while the subjects were standing. Height was measured with a Harpenden stadiometer (Critikon Service Center, Berkshire, United Kingdom) to the last complete 0.1 cm and weight with a Soehnle digital electronic scale (Critikon Service Center) to the last complete 0.1 kg. BMI (in kg/m2) was calculated for each man. BMI was not available for 10 men. Waist and hip circumferences were measured in duplicate with an insertion tape (CMS Ltd, London, United Kingdom); hip circumference was measured at the point of maximum circumference over the buttocks. The waist measurement was taken from the midpoint between the iliac crest and the lower ribs measured at the sides. WHR was calculated as WC divided by hip circumference (cm). WC was not available for 13 men and WHR was missing for 14 men. Within-subject variation for WC, BMI, and WHR was examined in a small repeatability study of 110 subjects who were measured by the same team of observers on both occasions. The correlations between measurements taken 1 wk apart were 0.995 for BMI, 0.992 for WC, and 0.928 for WHR. The within-subject correlations for WC were similar in nonobese and obese men (r = 0.988 and 0.968, respectively). FM and %BF were estimated by the bioelectrical impedance method with a Bodystat 500 apparatus (Bodystat Ltd, Douglas, United Kingdom) and by applying the equation of Deurenberg et al (26). Fat-free mass (FFM) was calculated as 6710 x height (m2)/resistance ({Omega}) + 7. FM was calculated as body weight – FFM. %BF was calculated as (body weight – FFM)/body weight. Data on %BF were missing in 93 men. WHR and WC were used as measures of abdominal (central) adiposity. BMI, FM, and %BF were used as measures of general adiposity.

Classification of groups
The NIH and WHO classifications of overweight (BMI of 25–29.9) and obesity (BMI ≥ 30) were used (6, 7). Within the overweight category, the men were further divided into 2 separate groups to assess whether there were any differences between men in the lower and upper ranges of the overweight category. The men were classified into 5 groups on the basis of their current BMI: <22.5, 22.5–24.9 (normal weight), 25–27.4 and 27.5–29.9 (overweight), and >30 (obese). For comparisons with the BMI groups, WC, WHR, FM, and %BF groups were derived by identifying values that approximated the percentile corresponding with the cutoffs for the 5 BMI groups. Statistical analyses were performed by using SAS version 8.2 (SAS Institute Inc, Cary, NC). Multiple logistic regression was used to assess the adjusted relative odds of having the metabolic syndrome or high HOMA by the percentile groups of the adiposity measures (PROC LOGIST SAS). The standardized odds ratio for a 1-SD increase in the adiposity measures was also used to compare the magnitude of association between the different adiposity measures and insulin resistance and the metabolic syndrome with adjustment for confounders. WC was divided into 3 groups (<94, 94–101, and ≥102 cm) on the basis of levels associated with increased cardiovascular disease risk (27) to determine whether the combined use of WC and BMI provided a better indicator of metabolic risk than either measure alone.

Receiver operating characteristic curves
Receiver operating characteristic (ROC) analysis was used to compare the ability to predict the presence of the metabolic syndrome and insulin resistance (28). Tests for differences between the curves were performed by using STATA software, version 7.0 (Stata Corp, College Station, TX) (29). The ROC curve tests the ability of a variable to predict an outcome by plotting sensitivity against 1 minus specificity. From this, the area under the curve (AUC) is an indicator of how well the measure of adiposity can predict a positive test outcome. AUC ranges from 0 to 1, with 0.5 indicating no predictive power and 1 indicating perfect power. The better the predictive ability, the further away from the diagonal line is the curve under examination.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The lifestyle characteristics, measures of adiposity, and prevalence of metabolic risk factors in the study population are shown in Table 1Go. The correlation between the different adiposity measures and the correlation with age is shown in Table 2Go. BMI and WC were highly correlated (r = 0.87). Both showed similar strong correlations with FM and to a lesser degree with %BF. Although mean BMI, %BF, FM, and FFM declined with increasing age, no association was seen between age and WC or WHR. The magnitude of the correlation between BMI and the other measures of adiposity was similar in the younger (aged 60–69 y) and older (aged 70–79 y) age groups.


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  		TABLE 1 Lifestyle characteristics, measures of adiposity, metabolic risk factors, and prevalence of metabolic disorders and the metabolic syndrome in men with no history of cardiovascular disease or diabetes 1

 

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  		TABLE 2 Correlations between measures of adiposity and age-adjusted correlations between adiposity and metabolic factors 1

 
The age-adjusted correlations between the adiposity measures and the metabolic risk factors are also shown in Table 2Go. BMI, WC, WHR, %BF, and FM were all significantly correlated with the metabolic factors, with the exception of blood glucose and %BF. The correlations of BMI and WC with the metabolic risk factors were of similar magnitude, whereas the magnitude of the correlation for lipids and insulin resistance (HOMA) was somewhat larger than that for the other adiposity measures. FFM showed much weaker associations with metabolic risk factors and was omitted from subsequent analyses.

Shown in Table 3Go are the relative odds for the individual components of the metabolic syndrome for a 1-SD increase in the measures of adiposity, adjusted for age, socioeconomic status, smoking status, physical activity, and alcohol intake. BMI and WC showed the strongest associations with all these factors. WHR showed weaker associations than did WC for low HDL cholesterol and high triacylglycerols; %BF showed the weakest associations. However, the relative odds were significant for virtually all the measures of adiposity.


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  		TABLE 3 Relative odds (95% CI) of the presence of individual components of the metabolic syndrome for a 1-SD increase in measures of adiposity, adjusted for age, socioeconomic status, smoking status, physical activity, and alcohol intake 1

 
The prevalence of the metabolic syndrome and high HOMA by levels of BMI, WC, WHR, FM, and %BF is shown in Table 4Go. About one-quarter of the men who were obese (BMI ≥ 30) had the metabolic syndrome, compared with {approx}22% in the top percentile group for the other indexes, and >55% of obese men were insulin resistant. Also shown in Table 4Go is the odds ratio for the 5 measures of adiposity using the lowest percentile group as the reference and with adjustment for lifestyle characteristics and socioeconomic status. Odds of the metabolic syndrome and high HOMA increased steeply with increasing BMI and with increasing WC and to a lesser extent with WHR, FM, and %BF. Men with BMI ≥ 30 (top 15% of the BMI distribution) had higher odds of the metabolic syndrome than did those in the top 15% of the other indexes. Comparisons between the adjusted standardized relative odds showed BMI and WC to have similar magnitude of increase for a 1-SD change after adjustment for potential confounders; %BF showed the weakest relation. The significant relations seen for BMI and WC remained even after adjustment for each other, although the independent relation was markedly attenuated because of the strong correlation between the 2 variables. WHR remained significantly associated with both the metabolic syndrome and high HOMA after adjustment for BMI. The relation between FM and %BF with the metabolic syndrome was attenuated after adjustment for WC but remained significant for HOMA.


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  		TABLE 4 Prevalence of the metabolic syndrome and high homeostasis model assessment (HOMA) by levels of the measures of adiposity and relative odds and standardized odds ratios (ORs) adjusted for age, socioeconomic status, smoking status, physical activity, and alcohol intake 1

 
When examined separately in the 2 age groups (60–69 and 70–79 y), the strongest associations with the metabolic syndrome and insulin resistance were seen for BMI and WC in both age groups, although the magnitude of association between BMI and HOMA was greater in the younger men (test for interaction, P = 0.02). For a 1-SD increase in each measure, the odds ratios of having the metabolic syndrome after adjustment for confounders were as follows: for BMI, 1.64 (95% CI: 1.44, 1.87), and for WC, 1.67 (95% CI: 1.45, 1.92) in the younger (<70 y) men. In the older men, the corresponding odds ratios were 1.56 (95% CI: 1.31, 1.86) and 1.58 (95% CI: 1.31, 1.88). For HOMA, the odds ratios in the younger men were as follows: for BMI, 2.72 (95% CI: 2.36, 3.16), and for WC, 2.57 (95% CI: 2.19, 2.90). In the older men, the corresponding odds were 2.12 (95% CI: 1.79, 2.52) and 2.26 (95% CI: 1.88, 2.72).

ROC analyses
ROC analyses are shown in Figure 1Go (for metabolic syndrome) and Figure 2Go (for insulin resistance). Areas under the curve for the metabolic syndrome were highest for BMI and WC (0.65 and 0.64), intermediate for WHR and FM (0.62), and lowest for %BF (0.59). Standard errors for each AUC were {approx}0.014. Differences in AUC were highly significant ({chi}2 = 28.8, df = 4, P < 0.001). Slightly larger AUCs were found for insulin resistance (0.73 for BMI, 0.72 for WC, 0.66 for %BF and WHR, and 0.70 for FM; SEs = 0.011). Again, differences were highly significant ({chi}2 = 69.8, df = 4, P < 0.001). For both conditions, BMI and WC were found to be the best predictors.



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  		FIGURE 1. Receiver operating characteristic (ROC) curves for BMI, waist circumference (WC), waist-to-hip ratio (WHR), percentage body fat (%BF), and fat mass (FM) for prediction of the metabolic syndrome in men with no history of cardiovascular disease or diabetes. ROC areas under the curve (95% CI) were as follows: BMI, 0.65 (0.63, 0.68); WC, 0.64 (0.61, 0.67); WHR, 0.62 (0.59, 0.65); %BF, 0.59 (0.56, 0.62); and FM, 0.62 (0.60, 0.65). Test for differences between ROC curves: {chi}2 = 28.8, df = 4, P < 0.001.

 


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  		FIGURE 2. Receiver operating characteristic (ROC) curves for BMI, waist circumference (WC), waist-to-hip ratio (WHR), percentage body fat (%BF), and fat mass (FM) for prediction of insulin resistance (high homeostasis model assessment) in men with no history of cardiovascular disease or diabetes. ROC areas under the curve (95% CI) were as follows: BMI, 0.73 (0.70, 0.75); WC, 0.72 (0.70, 0.74); WHR, 0.66 (0.64, 0.69); %BF, 0.66 (0.63, 0.68); and FM, 0.70 (0.64, 0.69). Test for differences between ROC curves: {chi}2 = 69.8, df = 4, P < 0.001.

 
Combined effects of BMI and waist circumference
Within the normal-weight, overweight, and obese BMI categories (BMI <25, 25–29.9, and ≥30), the men were initially divided into 3 WC groups (<94, 94–101, and ≥102 cm). Among men with a normal BMI, only 5 men had a WC >102 cm, however, and thus only 2 groups were used (<94 and ≥94 cm). Among obese men, only 6 men had a WC <94 cm, and thus only 2 groups were used (<102 and ≥102 cm). Prevalence of the metabolic syndrome and insulin resistance (HOMA) increased with increasing WC in normal-weight and overweight men but not in obese men (Table 5Go). In normal-weight and overweight men, elevated WC was associated with significantly higher odds of having the metabolic syndrome and in particular high HOMA. No association was seen in obese men. A test for interaction to assess whether the association between WC and the metabolic syndrome differed in obese and nonobese subjects (overweight and normal weight combined) was significant (P = 0.003), but for HOMA the interaction was not significant (P = 0.12). Thus, in normal-weight and overweight men, but not in obese men, WC provided additional power for predicting the presence of the metabolic syndrome.


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  		TABLE 5 Combination of BMI and waist circumference and prevalence and adjusted relative odds of having the metabolic syndrome and high homeostasis model assessment (HOMA) 1

 
Men with cardiovascular disease
In the 831 men with a history of coronary heart disease or stroke, the pattern of relations seen between the measures of adiposity and the presence of the metabolic syndrome and high HOMA was similar to that seen in men without cardiovascular disease, although the magnitude of association with HOMA was greater. For a 1-SD increase in the measures of adiposity, the odds ratios of having the metabolic syndrome after adjustment for age, socioeconomic status, smoking status, and physical activity were as follows: for BMI, 1.55 (95% CI: 1.29, 1.87); for WC, 1.56 (95% CI: 1.28, 1.85); for WHR, 1.35 (95% CI: 1.12, 1.65); for %BF, 1.46 (95% CI: 1.18, 1.82); and for FM, 1.57 (95% CI: 1.29, 1.91). For insulin resistance, the odds ratios were 3.48 (95% CI: 2.74, 4.4), 3.40 (95% CI: 2.74, 4.30), 2.11 (95% CI: 1.73, 2.55), 2.19 (95% CI: 1.77, 2.71), and 2.90 (95% CI: 2.34, 3.64), respectively. Tests for interaction showed BMI and WC to have a greater association with high HOMA in men with cardiovascular disease than in men without cardiovascular disease (P = 0.0002 for BMI and P < 0.0001 for WC).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
In this study of elderly British men with no history of diabetes or cardiovascular disease, BMI and WC were strongly correlated and were the simple adiposity measures most strongly associated with the metabolic syndrome and insulin resistance after adjustment for other lifestyle characteristics. WHR and FM showed weaker associations with the metabolic syndrome and insulin resistance, and BMI and %BF showed the weakest associations. It has been argued that BMI might be a poor indicator of risk in the elderly because it does not reflect regional fat distribution (11, 12, 27). A recent report from the British Regional Heart study showed that BMI is strongly associated with morbidity and cardiovascular disease risk factors in these elderly men (17). The present study extends the findings and indicates that BMI and WC are of similar value in indicating the presence of the clustering of metabolic abnormalities (metabolic syndrome) and insulin resistance in elderly men both with and without cardiovascular disease. The strong relation between BMI and the metabolic syndrome and insulin resistance was seen even in men aged ≥70 y, in whom a decline in muscle mass is most likely to occur.

Waist circumference and BMI
WC is increasingly being proposed as a better predictor of cardiovascular risk than BMI (27). However, few direct comparisons exist between BMI and WC as predictors of metabolic abnormalities in the elderly, and evidence tends to come from studies with a wide population range. In the third National Health and Nutrition Examination Study and in population studies from Canada, Hong Kong, and Japan, WC was more closely related to metabolic risk factors than was BMI (14, 15, 30-32). However, the age range in these study populations was broad and included subjects as young as 20 y and analyses were not carried out separately by age groups. Turcato et al (33) found WC and abdominal sagittal diameter to be more closely related to metabolic risk factors in old age (67–78 y) than BMI and considered that BMI and cardiovascular risk factors were no longer significantly associated after adjustment for WC. However, the data in that study show that the correlations with cardiovascular disease risk factors were similar for WC and BMI. In contrast, several studies with broad age ranges reported similar associations between BMI and WC and metabolic risk factors in men (34-38). In a study of >11 000 Australian adults aged ≥25 y, WC showed a stronger association with diabetes than did BMI, but similar associations were seen with dyslipidemia, hypertension, and having one or more risk factors in men after adjustment for age (34). In the Kuopio Ischemic Heart Disease Study of men aged 42–60 y, BMI and WC showed a similar magnitude of correlations with cardiovascular disease risk factors, whereas WHR showed weaker correlations (37), as were seen in the present study. In the Baltimore Longitudinal Study, WC showed stronger correlations with coronary heart disease risk factors than did BMI in younger subjects (<65 y) but not in older subjects (38). Whether BMI or WC is a better predictor of cardiovascular (metabolic) risk factors may depend on age. BMI and WC have been shown to be strongly correlated with both total body fat and visceral fat in the elderly (39), although both were more closely related to total body fat than visceral fat. Thus, WC may not be as good a predictor of visceral fat in older individuals as in younger subjects.

What seems to be emerging from recent studies is that WC and BMI combined provide a better tool for identifying subjects with metabolic abnormalities or insulin resistance (40, 41). In the present study, WC helped to identify normal-weight and overweight men at higher metabolic risk but not obese men, probably by the ability of WC to identify those men with elevations in visceral fat (42, 43). A graded relation was seen between WC and metabolic risk within normal-weight and overweight men. Even within the range of BMI currently accepted as biologically normal (BMI ≤ 25), there would appear to be those who carry deposits of excess fat in areas specifically related to the induction of metabolic abnormalities. Although it is possible that the limited value of WC in obese men reflects the difficulty in measuring it accurately in obese men, correlations between WC measures taken 1 wk apart were similar to those of BMI and did not vary markedly between nonobese and obese men, which suggests that imprecision in the measurement of WC is unlikely to account for the findings.

Waist-to-hip ratio
Our findings of a weaker association between WHR and metabolic risk factors than between WC and metabolic risk factors agrees with the suggestion that WC is a better reflection of visceral fat than is WHR (12). Increased WHR may reflect both increased visceral fat and reduced muscle mass as quantified by hip circumference (44).

Percentage body fat by bioelectrical impedance
Significant changes in body composition occur with aging with a decline in fat-free mass (45) as was observed in the present study. Although some studies report fat mass to increase with age (45, 46), we observed a decline in fat mass with increasing age in men aged 60–79 y, which is consistent with several other findings (47, 48). Bioelectrical impedance analysis has been shown to be a more reliable measure of body composition than is BMI (16). In the few studies that have compared the associations between %BF and BMI, the findings are inconsistent. In a study of >12 000 Japanese men aged 30–69 y, Nagaya et al (49) observed %BF to be more strongly correlated with serum lipids than was BMI. By contrast, Ito et al (32) reported no significant difference between BMI and FM in the accuracy of detecting risk factors in Japanese individuals aged 20–79 y. In the present study %BF as assessed by BIA showed the weakest associations compared with other measures of adiposity. Fat mass provided a better indicator of metabolic abnormalities than did %BF but was less predictive overall than the WC or BMI. The calculation of fat mass and %BF in this study was based on Deurenberg's equation (26), which has been validated in an elderly population, although a recent study suggested that it may underestimate FFM by 7.9 kg in men (50). However, we also calculated FFM and %BF estimates derived from the equation developed by Sun et al (51), which was validated in a US population of men and women aged 12–94 y. This equation provided similar findings in that %BF had the weakest association with metabolic risk factors.

Strengths and limitations
Adiposity variables were measured in this study and are not subject to reporting bias. Although the findings from the present study are based on 77% of survivors, the mean BMI of those who attended the reexamination and those who did not were almost identical at the initial screening, even though persons with ill health were less likely to attend (52). This is unlikely to have affected the relations seen between the adiposity measures and metabolic abnormalities, because all men with cardiovascular disease or diabetes were excluded. The vast majority of men in this study were white. We cannot generalize our findings to other ethnic groups or to women. In a study carried out in both men and women, WC and BMI showed similar associations with metabolic abnormalities in men, but WC tended to have stronger associations than BMI in women (35).

Conclusion
The results of the present study show that BMI and WC are the best measures of adiposity for predicting the presence of metabolic risk in older men. Although they are less precise in measuring visceral fat than more sophisticated techniques used to assess regional body composition, BMI and WC are simple and relatively inexpensive to measure and are easily obtainable in nonlaboratory settings. Our findings suggest using current BMI cutoffs for the initial assessment of overweight and obesity and using WC as a complementary indicator of health risk in normal-weight and overweight subjects, which is consistent with the NIH clinical guidelines recommending the measurement of WC within BMI categories as a screening tool for increased health risk (6). Whereas the NIH uses 102 cm as a cutoff for WC, our findings indicate that metabolic risk is increased at much lower values and that a graded system such as that proposed by Lean et al (27) for WC (<94, 94–101, and ≥102 cm) may be more appropriate than a dichotomous cutoff.


   ACKNOWLEDGMENTS
 
SGW and AGS contributed to the idea and analysis and drafted the paper. RWM contributed to the statistical analysis. AGS designed the original study, and PHW was responsible for the 20 y rescreening of the study population. All authors contributed to the writing of the paper. None of the authors had a conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication October 6, 2004. Accepted for publication January 31, 2005.




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