Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg,Sweden.

A longitudinal population study of 1462 women aged 38-60 was carried out in Gothenburg, Sweden, in 1968-9. In univariate analysis the ratio of waist to hip circumference showed a significant positive association with the 12 year incidence of myocardial infarction, angina pectoris, stroke, and death. The association with incidence of myocardial infarction remained in multivariate analysis and was independent of age, body mass index, smoking habit, serum cholesterol concentration, serum triglyceride concentration, and systolic blood pressure. The relation between the ratio of waist to hip circumference and the end points of myocardial infarction, angina pectoris, stroke, and death was stronger than for any other anthropometric variable studied.     

非肥胖者发生非酒精性脂肪肝的预测指标

目的：探讨能够预测非肥胖者是否发生非酒精性脂肪肝（Nonalcohohc fatty liver disease,NAFLD）的临床指标。方法：从广州社区人群中选取体重指数〈25且年龄、性别相匹配的NAFLD和非NAFLD个体分别为38和82例,测量其身高、体重、腰围、臀围及空腹血糖、甘油三脂、胆固醇、低密度脂蛋白、高密度脂蛋白、HBsAg和空腹胰岛素,计算体重指数、腰臀比、腰围身高比和HOMA胰岛素抵抗指数。先采用t检验和x^2检验对上述临床指标进行分析,对两组间存在显著差异者进行Logisde回归以发现独立的预测指标,再针对各预测指标进行受试者工作特征（reciever operating charactefistic,ROC）曲线分析判断各指标的预测准确度,并确定最佳的预测截断值。结果：NAFLD和非NAFLD的体重、腰围、臀围、体重指数、腰臀比、腰围身高比及空腹血糖、甘油三脂、低密度脂蛋白、胰岛素、HOMA胰岛素抵抗指数均有显著差异,但仅腰围、低密度脂蛋白和HOMA胰岛素抵抗指数进入Logistic回归方程,且其ROC曲线下面积均大于0．5（分别是0．821,0．665和0、722）。以腰围的预测准确度最高,且在80．5cm处敏感性和特异性之和最大。结论：腰围是预测非肥胖者是否发生NAFLD的合适指标,80．5cm为其最佳预测截断值。     

Hip Circumference and Cardiovascular Morbidity and Mortality in Men and Women

Objective: It has recently been demonstrated that, in middle‐aged women, a wide hip circumference is a protective factor for a number of health endpoints in later years. The effect seems to be independent of both overweight and waist circumference. This paper aims to replicate this finding in another population‐based sample consisting of women and men. Research Methods and Procedures: This was a prospective observational study consisting of a random subset of adult Danes. A total of 2987 subjects born in 1922, 1932, 1942, or 1952 and 35, 45, 55, or 65 years of age (at examination in 1987 to 1988) participated in the Danish MONICA (MONItoring trends and determinants of CArdiovascular disease) project, with measurements of height, weight, and hip and waist circumference taken. Through personal identification numbers, incidence of coronary heart disease (CHD) and cardiovascular disease (CVD) until the end of 1998 and all causes of death until 2001 were retrieved from the National Registers of Hospital Discharge. There was an average of 10 years of follow‐up for incidence of CVD and CHD and 13 years of follow‐up for total mortality. Results: Large hip circumference, relative to body size and waist circumference, predicted less incidence of CVD, CHD, and total death in women. This was not the case in men; BMI and waist circumference were the strongest independent predictors. Discussion: A large hip circumference seems to have independent and positive effects on CVD and CHD morbidity and mortality in women, but no protective effect on cardiovascular health in men. However, a borderline significant protective effect on total mortality was observed.     

Prediction of Visceral Adipose Tissue from Simple Anthropometric Measurements in Youths with Obesity

OWENS, SCOTT, MARK LITAKER, JERRY ALLISON, SHARON RIGGS, MICHAEL FERGUSON, AND BERNARD GUTIN. Prediction of visceral adipose tissue from simple anthropometric measurements in youths with obesity. Obes Res. 1999;7:16–22. Objective : Although visceral adipose tissue (VAT) is the component of body composition most highly associated with cardiovascular risk factors, its measurement requires expensive procedures, such as magnetic resonance imaging. This study examined the ability of simple demographic and anthropometric measurements to predict magnetic resonance imaging-derived VAT in 76 apparently healthy, black and white youths with obesity who were 7 years to 16 years of age. Research Methods and Procedures : Stepwise multiple linear regression was used to develop a prediction equation for VAT based on 13 simple anthropometric variables (height, weight, body mass index, triceps skinfold, calf skinfold, sagittal diameter, waist circumference, hip circumference, thigh circumference, waist/hip ratio, waist/thigh ratio, sagittal diameter/thigh ratio, and percent body fat from the sum of calf and triceps skinfolds) and three demographic variables (age, gender and ethnicity). Results : The stepwise multiple regression procedure yielded a final model that included two anthropometric variables (sagittal diameter and waist/hip ratio) and one demographic variable (ethnicity). The prediction equation was: VAT = ?124.06+16.67 (ethnicity)+4.15 (sagittal diameter)-+17.89 (waist/hip ratio), where ethnicity was coded as 0 = black and 1 = white. The model explained 63% of the variance in VAT and was associated with a measurement error of 23.9%. Discussion : Although the model seems to lack sufficient explanatory power for routine use in clinical settings with individual patients, it may have some utility in epidemiological studies given its relatively small (<25%) standard error of estimate.     

Obesity as Assessed by Body Adiposity Index and Multivariable Cardiovascular Disease Risk

To assess the role of body adiposity index (BAI) in predicting cardiovascular disease (CVD) and coronary heart disease (CHD) mortality, in comparison with body mass index (BMI), waist circumference (WC), and the waist circumference to hip circumference ratio (WHR). This study was a prospective 15 year mortality follow-up of 4175 Australian males, free of heart disease, diabetes and stroke. The Framingham Risk Scores (FRS) for CHD and CVD death were calculated at baseline for all subjects. Multivariable logistic regression was used to assess the effects of the measures of obesity on CVD and CHD mortality, before adjustment and after adjustment for FRS. The predictive ability of BAI, though present in the unadjusted analyses, was generally not significant after adjustment for age and FRS for both CVD and CHD mortality. BMI behaved similarly to BAI in that its predictive ability was generally not significant after adjustments. Both WC and WHR were significant predictors of CVD and CHD mortality and remained significant after adjustment for covariates. BAI appeared to be of potential interest as a measure of % body fat and of obesity, but was ineffective in predicting CVD and CHD.     

Body fat measured by a near-infrared interactance device as a predictor of cardiovascular events: the FINRISK'92 cohort

We evaluated how body fat percentage, measured by a portable near-infrared interactance (NIR) device predicts cardiovascular (CVD), coronary heart disease (CHD), and ischemic stroke events in a prospective population-based survey. The study population consisted of 2,842 men and 3,196 women, who participated in the FINRISK'92 survey. Obesity was assessed with BMI, waist circumference, and waist-to-hip ratio (WHR) and body fat percentage measured with an NIR. Mean length of follow-up was 9 years and 3 months. In Cox proportional hazards regression analyses for men, BMI, waist circumference, and WHR as well as body fat percentage were predictors of a CVD event when adjusted for age and for major risk factors. Hazard ratio (HR) per 1 s.d. was 1.27 (95% confidence interval: 1.10-1.48) for body fat percentage, 1.30 (1.16-1.46) for BMI, and 1.31 (1.16-1.50) for waist circumference. Among women, the body fat lost its predictive power in a fully adjusted model. Body fat percentage, BMI, waist circumference, and WHR were predictors of a CHD event both among men and women, whereas body fat percentage did not predict ischemic stroke among either gender. We observed that body fat percentage measured by an NIR device was a significant predictor of CVD and CHD events among men and women, but in our population-based survey, it did not provide any additional predictive power over and above the simpler measures, such as BMI or WHR.     

Skinfolds and coronary heart disease risk factors are more strongly associated with BMI than with the body adiposity index

Objective:

A recent, cross‐sectional analysis of adults found that the hip circumference divided by height^1.5 minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X‐ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease.

Design and Methods:

Cross‐sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988‐1994.

Results:

As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p < 0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race‐ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels.

Conclusions:

Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.     

Abdominal obesity and coronary heart disease in Thai men

Objective: To determine the association of four simple anthropometric indices with coronary heart disease (CHD) in Thai men, and to determine the optimal cut‐off points for each index in the prediction of CHD. Research Methods and Procedures: This is a cohort study with 17 years of follow‐up. A total of 2536 male employees from the Electricity Generating Authority of Thailand 35 to 59 years of age at baseline were included in the study. Height, weight, waist circumference, and hip circumference were measured to generate BMI, waist circumference (WC), waist‐to‐hip ratio (WHR), and waist‐to‐height ratio (WHtR). Cox regression models were used to estimate hazard ratios by thirds of each index. Receiver operating characteristic curves were used to assess discrimination of CHD. Results: WHtR was most strongly associated with CHD events in Thai men. The age‐adjusted hazard ratio for those in the highest, compared with the lowest, third was 2.89 (1.37, 6.11). Although WHtR had the largest area under the receiver operating characteristic curve (AUC) with the optimal cut‐off estimated to be 0.51 (sensitivity, 55%; specificity, 61%), no statistically significant difference (p > 0.10) was found between the AUC for WHtR and that for the other three indices. Conclusion: WHtR is, marginally, the best of the four indices considered to predict CHD events in Thai men.     

Snoring as a risk factor for ischaemic heart disease and stroke in men.

The association of snoring with ischaemic heart disease and stroke was studied prospectively in 4388 men aged 40-69. The men were asked, in a questionnaire sent to them, whether they snored habitually, frequently, occasionally, or never. Hospital records and death certificates were checked for the next three years to establish how many of the men developed ischaemic heart disease or stroke: the numbers were 149 and 42, respectively. Three categories of snoring were used for analysis: habitual and frequent snorers (n = 1294), occasional snorers (n = 2614), and non-snorers (n = 480). The age adjusted relative risk of ischaemic heart disease between habitual plus frequent snorers and non-snorers was 1.91 (p less than 0.01) and for ischaemic heart disease or stroke, or both, 2.38 (p less than 0.001). There were no cases of stroke among the non-snorers. Adjustment for age, body mass index, history of hypertension, smoking, and alcohol use did not significantly decrease the relative risks, which were 1.71 (p greater than 0.05) for ischaemic heart disease and 2.08 (p less than 0.01) for ischaemic heart disease and stroke combined. At the beginning of follow up in 1981, 462 men reported a history of angina pectoris or myocardial infarction. For them the relative risk of ischaemic heart disease between habitual plus frequent snorers and non-snorers was 1.30 (NS); for men without previous ischaemic heart disease 2.72 (p less than 0.05). Snoring seems to be a potential determinant of risk of ischaemic heart disease and stroke.     

Measures of adiposity and cardiovascular disease risk factors

Objective: To determine which of five measures of adiposity maintains the strongest association with cardiovascular disease risk factors. Research Methods and Procedures: A nationally representative sample of 12,608 adult participants of the third National Health and Nutrition Examination Survey were examined. Waist circumference, total body fat, percent body fat, BMI, and skinfold thickness were measured following a standardized protocol. Results: In multivariable adjusted models including waist circumference and BMI as independent variables, waist circumference was a significantly better predictor. The odds ratios (95% confidence intervals) for each standard deviation higher waist circumference and BMI for men were as follows: 1.88 (1.43, 2.48) and 0.99 (0.76, 1.29), respectively, for hypertension; 1.51 (0.87, 2.59) and 1.23 (0.76, 1.99), respectively, for diabetes; and 1.85 (1.48, 2.32) and 1.00 (0.80, 1.24), respectively, for low high‐density lipoprotein‐cholesterol. The analogous odds ratios (95% confidence intervals) for women were as follows: 2.28 (1.74, 3.00) and 0.91 (0.69, 1.19), respectively, for hypertension; 2.72 (1.85, 4.00) and 0.82 (0.55, 1.23), respectively, for diabetes; and 1.90 (1.47, 2.47) and 1.07 (0.83, 1.38), respectively, for low high‐density lipoprotein‐cholesterol. Results were markedly similar for waist circumference in models adjusting for total body fat, percent body fat, and skinfold thickness separately. In contrast, waist circumference was not a significantly better predictor of elevated C‐reactive protein than the other measures of adiposity. Discussion: Waist circumference maintains a stronger association with cardiovascular disease risk factors than other measures of adiposity.     

Associations of body mass index and waist:hip ratio with hypertension.

Canada Fitness Survey data for people aged 20 to 69 years were analysed by means of linear discriminant analysis to determine the effect of age, weight relative to height (body mass index) and weight distribution (waist:hip ratio) on hypertension (defined as diastolic blood pressure of 90 mm Hg or more) for both sexes separately. All three variables had independent effects on hypertension, but partial correlation coefficients indicated that the contribution of waist:hip ratio was secondary to that of body mass index. The association of measurements of body fat (five skinfold measurements) with hypertension was also examined; overall these measurements gave no advantage over the more simply measured body mass index. The results confirm the importance of assessing the predominant location of body fat and the body mass index when examining excess weight in relation to disease.     

Relationship between anthropometric measures and body composition among Muslim females of West Bengal, India

The human body composition is assessed to determine percent body fat (PBF), fat mass (FM), and lean body mass or fat free mass (FFM). The topological distribution of body fat has been the subject of many studies in the world and India. To the best of our knowledge the present paper is the first report on the body composition in terms of PBF and FM, and their relationship with anthropometric measures in Muslim females in India. The present study examines anthropometric measurements and their relationship with the body composition among Muslim females of West Bengal, India. A cross-sectional study of 100 female, Muslim students of Howrah and Kolkata was undertaken to compare the relationships of biceps and triceps skinfold, waist, hip and upper arm circumference, waist hip ratio and conicity index with their body composition variables (PBF and FM). All anthropometric measures displayed significant (p < 0.05) correlation with body composition measures. The triceps skinfold, however, demonstrated a significant correlation with PBF (r = 0.90) and FM (r = 0.93). The greatest amount of variation of PBF (81.3 %) and FM (89.2 %) was explained by the triceps skinfold. In addition, a considerable amount of variation of PBF (72.8 %) and FM (86.0 %) was explained by the mid upper arm circumference. In conclusion, the present study displays a tendency of regional adiposity in the upper arm, triceps skinfold and mid upper arm circumference are much more strongly associated with body fat.     

Usefulness of truncal obesity indices as predictive factors for obstructive sleep apnea syndrome

Background: Optimization of the indications for nocturnal polysomnography in the diagnosis of obstructive sleep apnea syndrome (OSAS) could lead to significant reductions in health expenditure. To this end, we assessed the usefulness of truncal obesity measurements in the diagnosis of OSAS. Methods and Procedures: One hundred ninety‐two patients (152 men and 40 women) referred to our clinic with suspected OSAS underwent a complete polysomnography study and their BMI and truncal obesity measurements were obtained. Results: Comparison of patients defined as snorers with OSAS patients, by means of the Student's t ‐test revealed significant differences in the truncal obesity parameters such as waist‐to‐hip ratio (0.94 vs. 0.98) and waist circumference (100.7 cm vs. 106.3 cm). We found no significant differences between BMI values in the two groups. Indices of truncal obesity were analyzed as predictive factors for OSAS using a multivariate logistic regression model that included variable sex, and in which waist‐to‐hip ratio, BMI, neck circumference, and age were analyzed as binary variables. According to this model, our patients' risk of suffering from OSAS was 2.6 times greater if the waist‐to‐hip ratio was >1 in men and >0.85 in women. The risk of OSAS was also increased if the patients were men or over 52 years of age. Discussion: Obtaining simple measurements such as those for truncal obesity may help prioritize the use of polysomnography in patients with a greater risk of OSAS. Our results suggest that BMI is not a good predictor of OSAS in a group of patients with a high BMI.     

Prediction of Percentage Body Fat in Rural Thai Population Using Simple Anthropometric Measurements

Objective: To develop and validate sex‐specific equations for predicting percentage body fat (%BF) in rural Thai population, based on BMI and anthropometric measurements. Research Methods and Procedures: %BF (DXA; GE Lunar Corp., Madison, WI) was measured in 181 men and 255 women who were healthy and between 20 and 84 years old. Anthropometric measures such as weight (kilograms), height (centimeters), BMI (kilograms per meter squared), waist circumference (centimeters), hip circumference (centimeters), thickness at triceps skinfold (millimeters), biceps skinfold (millimeters), subscapular skinfold (millimeters), and suprailiac skinfold (millimeters) were also measured. The sample was randomly divided into a development group (98 men and 125 women) and a validation group (83 men and 130 women). Regression equations of %BF derived from the development group were then evaluated for accuracy in the validation group. Results: The equation for estimating %BF in men was: %BF(men) = 0.42 × subscapular skinfold + 0.62 × BMI ? 0.28 × biceps skinfold + 0.17 × waist circumference ? 18.47, and in women: %BF(women) = 0.42 × hip circumference + 0.17 × suprailiac skinfold + 0.46 × BMI ? 23.75. The coefficient of determination (R²) for both equations was 0.68. Without anthropometric variables, the predictive equation using BMI, age, and sex was: %BF = 1.65 × BMI + 0.06 × age ? 15.3 × sex ? 10.67 (where sex = 1 for men and sex = 0 for women), with R² = 0.83. When these equations were applied to the validation sample, the difference between measured and predicted %BF ranged between ±9%, and the positive predictive values were above 0.9. Discussion: These results suggest that simple, noninvasive, and inexpensive anthropometric variables may provide an accurate estimate of %BF and could potentially aid the diagnosis of obesity in rural Thais.     

Larger Hip Circumference Independently Predicts Health and Longevity in a Swedish Female Cohort

Objective: The waist circumference is widely viewed as a simple but effective measure for assessing obesity‐related health risks, whereas measurement of the hip circumference is not currently prioritized. This study examines health risks associated specifically with hip circumference in a cohort of Swedish women, to determine whether information may be lost by excluding the hip circumference from health surveys. Research Methods and Procedures: The subjects described in this report constitute a population‐based sample of 38‐ to 60‐year‐old women who underwent anthropometric examinations in 1968. The 24‐year incidence rates have been ascertained for myocardial infarction, combined cardiovascular diseases, and diabetes. All‐cause, cardiovascular, and myocardial infarction mortality also were evaluated. Results: Hip circumference was a significant independent inverse risk estimator for all endpoints studied. Using Cox regression with adjustment for age, smoking, body mass index, and waist circumference, the remaining variability associated with larger hips was associated with significantly fewer adverse health outcomes. The hip circumference became statistically informative after body mass index adjustment. The strongest protective associations were observed for cardiovascular disease and diabetes endpoints, although significant trends were also seen for total mortality. Considering hip and waist simultaneously, the strength of the inverse association for large hips generally exceeded the positive association for waist. Discussion: Recent interest in the waist circumference as an effective screening tool has taken the focus off of the hip circumference. The present results suggest that collection of hip measurements should not be discontinued in assessment of obesity‐related risk status and health promotion.     

Usefulness of Anthropometry and DXA in Predicting Intra‐abdominal Fat in Obese Men and Women

Objective: To investigate the usefulness of anthropometry and DXA in predicting intra‐abdominal fat (IAF) in obese men and women. Research Methods and Procedures: Observational, cross sectional study of 22 women and 18 men with a body mass index of 30 or above. IAF from 20 cm above and 10 cm below the L4 to L5 intervertebral disc was measured by magnetic resonance imaging (MRI) as a reference method. Central abdominal fat was measured from the upper border of L2 to the lower border of L4 by DXA. Waist and hip circumferences were also measured. Results: In obese women DXA, waist circumference and waist‐hip ratio were equally well correlated with IAF (r = 0.74, 0.75, and 0.70, respectively). In obese men DXA was moderately correlated with IAF measured by MRI (r = 0.46), whereas waist circumference and waist‐hip ratio were not significantly correlated with IAF. Discussion: The prediction of IAF in obese subjects was highly dependent on sex more than in non‐obese persons. Anthropometry and DXA were equally useful in obese women, whereas anthropometry had no predictive power and DXA was the only acceptable predictor of IAF in obese men.     

Birth Weight,Adult Body Composition,and Subcutaneous Fat Distribution

Objectives: To investigate if birth weight is related to both body mass index (BMI) and distribution of subcutaneous fat at adult age. Research Methods and Procedures: A 9‐year longitudinal study was performed in 229 subjects (192 women) with ages ranging from 27 to 36 years. Birth weight was retrieved by a questionnaire, and adult weight, height, skinfold thicknesses, and waist‐to‐hip ratio (WHR) were repeatedly measured at mean ages 27, 29, 31, and 36 years. BMI, sum of four skinfolds (S4S), the ratio between two truncal skinfolds and S4S (SS/S4S), and the ratio between WHR and the cross‐sectional area of the left thigh were calculated with the available data. Results: The adjusted model showed that in women, birth weight was significantly negatively related to adult S4S [β = ?5.211; (?9.768 to ?0.654)], waist circumference [β = ?1.449; (?2.829 to ?0.069)], and SS/S4S ratio [β = ?3.579; (?5.296 to ?1.862)]. In men, a significant negative association was observed between birth weight and adult WHR [β = ?1.096; (?2.092 to ?0.100)] only. Other relationships showed, although not significantly, the same negative trend, namely that lower birth weight is related to higher adult body fat mass (S4S) and a more truncal subcutaneous fat distribution (SS/S4S). No associations were found between birth weight and either adult BMI or the cross‐sectional area of the thigh. Discussion: Lower birth weight is, in both adult men and women, related to a higher adult subcutaneous fat mass and a more truncal distribution of subcutaneous fat, indicating a higher risk for obesity.     

Improved Prediction of Body Fat by Measuring Skinfold Thickness,Circumferences, and Bone Breadths

Objective: To develop improved predictive regression equations for body fat content derived from common anthropometric measurements. Research Methods and Procedures: 117 healthy German subjects, 46 men and 71 women, 26 to 67 years of age, from two different studies were assigned to a validation and a cross‐validation group. Common anthropometric measurements and body composition by DXA were obtained. Equations using anthropometric measurements predicting body fat mass (BFM) with DXA as a reference method were developed using regression models. Results: The final best predictive sex‐specific equations combining skinfold thicknesses (SF), circumferences, and bone breadth measurements were as follows: BFM_New (kg) for men = ?40.750 + [(0.397 × waist circumference) + [6.568 × (log triceps SF + log subscapular SF + log abdominal SF)]] and BFM_New (kg) for women = ?75.231 + [(0.512 × hip circumference) + [8.889 × (log chin SF + log triceps SF + log subscapular SF)] + (1.905 × knee breadth)]. The estimates of BFM from both validation and cross‐validation had an excellent correlation, showed excellent correspondence to the DXA estimates, and showed a negligible tendency to underestimate percent body fat in subjects with higher BFM compared with equations using a two‐compartment (Durnin and Womersley) or a four‐compartment (Peterson) model as the reference method. Discussion: Combining skinfold thicknesses with circumference and/or bone breadth measures provide a more precise prediction of percent body fat in comparison with established SF equations. Our equations are recommended for use in clinical or epidemiological settings in populations with similar ethnic background.     

Waist Circumference as the Best Predictor of Noninsulin Dependent Diabetes Mellitus (NIDDM) Compared to Body Mass Index,Waist/hip Ratio and Other Anthropometric Measurements in Mexican Americans—A 7-Year Prospective Study

Although a number of obesity-related variables are recognized risk factors for NIDDM, few studies have addressed which one is the best predictor. A cohort of 721 Mexican Americans aged 25–64 years who were free of NIDDM at baseline were followed for an average of 7.2 years; 105 new cases of NIDDM were diagnosed. Body weight, body mass index (BMI), waist and hip circumferences, waist/hip ratio (WHR), triceps and subscapular skinfolds were all positively predictive of NIDDM independent of age and sex. There were modest to strong correlations between these anthropometric variables, however, waist circumference was the strongest predictor of NIDDM. The predictive power of a single measurement of waist circumference was at least equal to that of WHR and BMI combined. The risk of NIDDM for those in the highest quartile of waist circumference was 11 times greater than for those in the lowest quartile (95% confidence interval: 4.2–28.8). The waist-NIDDM relation was stronger in subjects with BMI ≤ 27 kg/m² (OR: 6.0 for a 1 SD difference) than in subjects with BMI > 27 kg/m2 (OR: 1.7 for a 1 SD difference). In multivariate analysis, waist circumference was the only significant predictor of NIDDM in models that included other anthropometric variables either separately or simultaneously. WHR and BMI were independent predictors of NIDDM after adjustment for each other, however, their predictive abilities disappeared after adjustment for waist circumference. The data indicate that waist is the best obesity-related predictor of NIDDM. This finding suggests that the distribution of body fat, especially abdominal localization, is a more important determinant than the total amount of body fat of the development of NIDDM in Mexican Americans.     

Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample.

OBJECTIVE--To determine the frequency of cardiovascular risk factors in people categorised by previously defined "action levels" of waist circumference. DESIGN--Prevalence study in a random population sample. SETTING--Netherlands. SUBJECTS--2183 men and 2698 women aged 20-59 years selected at random from the civil registry of Amsterdam and Maastricht. MAIN OUTCOME MEASURES--Waist circumference, waist to hip ratio, body mass index (weight (kg)/height (m2)), total plasma cholesterol concentration, high density lipoprotein cholesterol concentration, blood pressure, age, and lifestyle. RESULTS--A waist circumference exceeding 94 cm in men and 80 cm in women correctly identified subjects with body mass index of > or = 25 and waist to hip ratios > or = 0.95 in men and > or = 0.80 in women with a sensitivity and specificity of > or = 96%. Men and women with at least one cardiovascular risk factor (total cholesterol > or = 6.5 mmol/l, high density lipoprotein cholesterol < or = 0.9 mmol/l, systolic blood pressure > or = 160 mm Hg, diastolic blood pressure > or = 95 mm Hg) were identified with sensitivities of 57% and 67% and specificities of 72% and 62% respectively. Compared with those with waist measurements below action levels, age and lifestyle adjusted odds ratios for having at least one risk factor were 2.2 (95% confidence interval 1.8 to 2.8) in men with a waist measurement of 94-102 cm and 1.6 (1.3 to 2.1) in women with a waist measurement of 80-88 cm. In men and women with larger waist measurements these age and lifestyle adjusted odds ratios were 4.6 (3.5 to 6.0) and 2.6 (2.0 to 3.2) respectively. CONCLUSIONS--Larger waist circumference identifies people at increased cardiovascular risks.