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.     

Relationship between the percentage of body fat and surrogate indices of fatness in male and female Polish active and sedentary students

Background

Limited data have indicated that body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and waist to height ratio (WHtR) of athletes and young adults provide misleading results concerning body fat content. This study was aimed at the evaluation of the relationship between different surrogate indices of fatness (BMI, WC, WHR, WHtR and body adiposity index (BAI)) with the percentage of body fat in Polish students with respect to their sex and physical activity.

Methods

A total of 272 students volunteered to participate in the study. Of these students, 177 physical education students (90 males and 87 females) were accepted as active (physical activity of 7 to 9 hours/week); and 95 students of other specializations (49 males and 46 females) were accepted as sedentary (physical activity of 1.5 hours/week). Weight, height, waist and hip circumferences were measured, and BMI, WHR, WHtR and BAI were calculated. Body fat percentage was assessed using four skinfold measurements.

Results

Classification of fatness according to the BMI and the percentage of body fat have indicated that BMI overestimates fatness in lean subjects (active men and women, sedentary men), but underestimates body fat in obese subjects (sedentary women). In all groups, BMI, WHR, WHtR and BAI were significantly correlated with the percentage of body fat (with the exception of WHR and hip circumference in active and sedentary women, respectively). However, coefficients of determination not exceeding 50% and Lin’s concordance correlation coefficients lower than 0.9 indicated no relationship between measured and calculated body fat.

Conclusion

The findings in the present study support the concept that irrespective of physical activity and sex none of the calculated indices of fatness are useful in the determination of body fat in young adults. Thus, it seems that easily calculated indices may contribute to distorted body image and unhealthy dietary habits observed in many young adults in Western countries, but also in female athletes.     

Bioelectrical impedance underestimates total and truncal fatness in abdominally obese women

Objective: To compare estimates of total and truncal fatness from eight‐electrode bioelectrical impedance analysis equipment (BIA₈) with those from DXA in centrally obese women. The secondary aim was to examine BMI and waist circumference (WC) as proxy measures for percentage total body fat (%TBF) and truncal body fat percentage (tr%BF). Research Methods and Procedures: This was a cross‐sectional study of 136 women (age, 48.1 ± 7.7 years; BMI, 30.4 ± 2.9 kg/m²; %TBF_DXA, 46.0 ± 3.7%; WC, 104 ± 8 cm). Fatness was measured by DXA and Tanita BC‐418 equipment (Tanita Corp., Tokyo, Japan). Agreement among methods was assessed by Bland‐Altman plots, and regression analysis was used to evaluate anthropometric measures as proxies for total and abdominal fatness. Results: The percentage of overweight subjects was 41.9%, whereas 55.9% of the subjects were obese, as defined by BMI, and all subjects had a WC exceeding the World Health Organization cut‐off point for abdominal obesity. Compared with DXA, the BIA₈ equipment significantly underestimated total %BF (?5.0; ?3.6 to ?8.5 [mean; 95% confidence interval]), fat mass (?3.6; ?3.9 to ?3.2), and tr%BF (?8.5; ?9.1 to ?7.9). The discrepancies between the methods increased with increasing adiposity for both %TBF and tr%BF (both p < 0.001). Variation in BMI explained 28% of the variation in %TBF_DXA and 51% of %TBF_BIA8. Using WC as a proxy for truncal adiposity, it explained only 18% of tr%BF_DXA variance and 27% of tr%BF_BIA8 variance. The corresponding figures for truncal fat mass were 49% and 35%, respectively. No significant age effects were observed in any of the regressions. Discussion: BIA₈ underestimated both total and truncal fatness, compared with DXA, with higher dispersion for tr%BF than %TBF. The discrepancies increased with degree of adiposity, suggesting that the accuracy of BIA is negatively affected by obesity.     

A Prospective Study of Adiposity and All‐Cause Mortality: The Malmö Diet and Cancer Study

Objective: This study aims to examine the association between various measures of adiposity and all‐cause mortality in Swedish middle‐aged and older men and women and, additionally, to describe the influences of age and sex on these associations. Research Methods and Procedures: A prospective analysis was performed in a cohort of 10,902 men and 16,814 women ages 45 to 73 years who participated in the Malmö Diet and Cancer Study in Sweden. Baseline examinations took place between 1991 and 1996, and 982 deaths were documented during an average follow‐up of 5.7 years. All‐cause mortality was related to the following variables measured at baseline: body mass index (BMI), percentage of body fat, lean body mass (LBM), and waist‐to‐hip ratio (WHR), with adjustment for age and selected covariates. Body composition data were derived from bioelectrical impedance analysis. Results: The association between percentage of body fat and mortality was modified by age, particularly in women. For instance, fatness was associated with excess mortality in the younger women but with reduced mortality in the older women. Weaker associations were seen for BMI than for percentage of body fat in both sexes. Placement in the top quintiles of waist‐to‐hip ratio, independent of overall body fat, was a stronger predictor of mortality in women than in men. The observed associations could not be explained by bias from early death or antecedent disease. Discussion: The findings reveal sex and age differences for the effects of adiposity and WHR on mortality and indicate the importance of considering direct measures of adiposity, as opposed to BMI, when describing obesity‐related mortality risks.     

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 Adiposity Index versus Body Mass Index and Other Anthropometric Traits as Correlates of Cardiometabolic Risk Factors

Objective

The worldwide prevalence of obesity mandates a widely accessible tool to categorize adiposity that can best predict associated health risks. The body adiposity index (BAI) was designed as a single equation to predict body adiposity in pooled analysis of both genders. We compared body adiposity index (BAI), body mass index (BMI), and other anthropometric measures, including percent body fat (PBF), in their correlations with cardiometabolic risk factors. We also compared BAI with BMI to determine which index is a better predictor of PBF.

Methods

The cohort consisted of 698 Mexican Americans. We calculated correlations of BAI, BMI, and other anthropometric measurements (PBF measured by dual energy X-ray absorptiometry, waist and hip circumference, height, weight) with glucose homeostasis indices (including insulin sensitivity and insulin clearance from euglycemic clamp), lipid parameters, cardiovascular traits (including carotid intima-media thickness), and biomarkers (C-reactive protein, plasminogen activator inhibitor-1 and adiponectin). Correlations between each anthropometric measure and cardiometabolic trait were compared in both sex-pooled and sex-stratified groups.

Results

BMI was associated with all but two measured traits (carotid intima-media thickness and fasting glucose in men), while BAI lacked association with several variables. BAI did not outperform BMI in its associations with any cardiometabolic trait. BAI was correlated more strongly than BMI with PBF in sex-pooled analyses (r = 0.78 versus r = 0.51), but not in sex-stratified analyses (men, r = 0.63 versus r = 0.79; women, r = 0.69 versus r = 0.77). Additionally, PBF showed fewer correlations with cardiometabolic risk factors than BMI. Weight was more strongly correlated than hip with many of the cardiometabolic risk factors examined.

Conclusions

BAI is inferior to the widely used BMI as a correlate of the cardiometabolic risk factors studied. Additionally, BMI’s relationship with total adiposity may not be the sole determinate of its association with cardiometabolic risk.     

Concordance of the recently published body adiposity index with measured body fat percent in European-American adults

The body adiposity index (BAI; hip circumference (cm)/height (m)(1.5) - 18) has recently been shown to demonstrate a stronger correlation with percentage body fat (%fat) than that between the BMI and %fat in Mexican-American adults. Here, we compare the concordance between %fat from dual-energy X-ray absorptiometry (DXA) and BAI, and between %fat and BMI, in European-American adults (n = 623). Agreement between BAI, BMI, and %fat was assessed using Lin's concordance coefficients (ρ(c)), where values <0.90 are considered poor. In the sample as a whole, the agreement between BAI and %fat (ρ(c) = 0.752) was far better than that between BMI and %fat (ρ(c) = 0.445) but was nonetheless relatively poor. There were large mean differences in %fat between the BAI and DXA %fat, particularly at lower levels of adiposity (<20%), and further the BAI overestimated %fat in males and underestimated %fat in females. Optimizing the BAI formula for our sample only marginally improved performance. Results of the present study show that BAI provides a better indicator of adiposity in European-American adults than does BMI, but does not provide valid estimates of %fat, particularly at lower levels of body fatness. Further research is warranted to investigate the predictive ability of BAI for various health outcomes.     

Independent Association of Hip Circumference with Metabolic Profile in Different Ethnic Groups

Objective: In whites, a larger hip circumference has been shown to be associated with a better metabolic profile, after adjustment for BMI and waist circumference. Our aim was to investigate this association in a variety of ethnic groups, some highly susceptible to type 2 diabetes. Research Methods and Procedures: We measured weight, height, waist and hip circumferences, systolic and diastolic blood pressure, fasting and 2‐hour postload glucose, triglycerides, and high‐density lipoprotein‐cholesterol in 1020 Melanesians, 767 Micronesians, 3697 Indians, and 2710 Creoles from Pacific and Indian Ocean islands. Leptin and body fat percentage were determined in Indian and Creole Mauritians only. Results: In all ethnic groups, larger hip circumference was associated with lower glucose and triglyceride levels in both sexes and higher high‐density lipoprotein levels in women only, after adjustment for waist circumference, BMI, and age. Adjustment for height or leptin did not materially change the results. Discussion: In conclusion, we confirmed the protective association of relatively larger hips in four nonwhite ethnic groups. Leptin does not seem to play a mediating role in this association.     

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.     

Surrogate Markers of Visceral Adiposity in Young Adults: Waist Circumference and Body Mass Index Are More Accurate than Waist Hip Ratio,Model of Adipose Distribution and Visceral Adiposity Index

Surrogate indexes of visceral adiposity, a major risk factor for metabolic and cardiovascular disorders, are routinely used in clinical practice because objective measurements of visceral adiposity are expensive, may involve exposure to radiation, and their availability is limited. We compared several surrogate indexes of visceral adiposity with ultrasound assessment of subcutaneous and visceral adipose tissue depots in 99 young Caucasian adults, including 20 women without androgen excess, 53 women with polycystic ovary syndrome, and 26 men. Obesity was present in 7, 21, and 7 subjects, respectively. We obtained body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), model of adipose distribution (MOAD), visceral adiposity index (VAI), and ultrasound measurements of subcutaneous and visceral adipose tissue depots and hepatic steatosis. WC and BMI showed the strongest correlations with ultrasound measurements of visceral adiposity. Only WHR correlated with sex hormones. Linear stepwise regression models including VAI were only slightly stronger than models including BMI or WC in explaining the variability in the insulin sensitivity index (yet BMI and WC had higher individual standardized coefficients of regression), and these models were superior to those including WHR and MOAD. WC showed 0.94 (95% confidence interval 0.88–0.99) and BMI showed 0.91 (0.85–0.98) probability of identifying the presence of hepatic steatosis according to receiver operating characteristic curve analysis. In conclusion, WC and BMI not only the simplest to obtain, but are also the most accurate surrogate markers of visceral adiposity in young adults, and are good indicators of insulin resistance and powerful predictors of the presence of hepatic steatosis.     

Larger Thigh and Hip Circumferences Are Associated with Better Glucose Tolerance: The Hoorn Study

Objective: A higher waist‐to‐hip ratio, which can be due to a higher waist circumference, a lower hip circumference, or both, is associated with higher glucose levels and incident diabetes. A lower hip circumference could reflect either lower fat mass or lower muscle mass. Muscle mass might be better reflected by thigh circumference. The aim of this study was to investigate the contributions of thigh and hip circumferences, independent of waist circumference, to measures of glucose metabolism. Research Methods and Procedures: For this cross‐sectional study we used baseline data from the Hoorn Study, a population‐based cohort study of glucose tolerance among 2484 men and women aged 50 to 75. Glucose tolerance was assessed by a 75‐g oral glucose tolerance test; hemoglobin A_1c and fasting insulin were also measured. Anthropometric measurements included body mass index (BMI) and waist, hip, and thigh circumferences. Results: Stratified analyses and multiple linear regression showed that after adjustment for age, BMI, and waist circumference, thigh circumference was negatively associated with markers of glucose metabolism in women, but not in men. Standardized β values in women were ?0.164 for fasting, ?0.206 for post‐load glucose, ?0.190 for hemoglobin A_1c (all p < 0.001), and ?0.065 for natural log insulin levels (p = 0.061). Hip circumference was negatively associated with markers of glucose metabolism in both sexes (standardized betas ranging from ?0.093 to ?0.296, p < 0.05) except for insulin in men. Waist circumference was positively associated with glucose metabolism. Discussion: Thigh circumference in women and hip circumference in both sexes are negatively associated with markers of glucose metabolism independently of the waist circumference, BMI, and age. Both fat and muscle tissues may contribute to these associations.     

Body adiposity index and other indexes of body composition in the SAPHIR study: Association with cardiovascular risk factors

Objective:

The accuracy of anthropometric surrogate markers such as the body adiposity index (BAI) and other common indexes like the body mass index (BMI), waist‐to‐hip ratio (WHR) and waist‐to‐height ratio (WHtR) to predict metabolic sequelae is essential for its use in clinical practice.

Design and Methods:

Thus, we evaluated the strength of BAI and other indexes to relate with anthropometric parameters, adipocytokines, blood lipids, parameters of glucose‐homeostasis and blood pressure in 1,770 patients from the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk (SAPHIR) study in a crosssectional design. Measurements were BAI, BMI, WHR, WHtR, abdominal subcutaneous and visceral adipose tissue (aSAT and VAT), total body adipose tissue mass, body weight, waist‐ and hip circumference (WC and HC), leptin, adiponectin, high‐density lipoprotein‐cholesterol (HDL‐C), low‐density lipoprotein‐cholesterol (LDL‐C), triglycerides (TG), fasting plasma glucose, fasting plasma insulin, the homeostasis model assessment of insulin resistance (HOMAIR), systolic and diastolic blood pressure.

Results and Conclusions:

BAI was significantly associated with leptin and HC. We conclude that BAI was the best calculator for leptin. BAI was inferior to BMI to predict anthropometric parameters other than HC, adiponectin, blood lipids, parameters of glucose homeostasis, and blood pressure in this cross‐sectional study.     

A better index of body adiposity

Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)(1.5))-18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the "BetaGene" study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a "gold standard" for validation. Hip circumference (R = 0.602) and height (R = -0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the "Triglyceride and Cardiovascular Risk in African-Americans (TARA)" study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly.     

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.     

Brief communication: Body mass index,body adiposity index,and percent body fat in asians

Human obesity is a growing epidemic throughout the world. Body mass index (BMI) is commonly used as a good indicator of obesity. Body adiposity index (BAI = hip circumference (cm)/stature (m)^1.5 ? 18), as a new surrogate measure, has been proposed recently as an alternative to BMI. This study, for the first time, compares BMI and BAI for predicting percent body fat (PBF; estimated from skinfolds) in a sample of 302 Buryat adults (148 men and 154 women) living in China. The BMI and BAI were strongly correlated with PBF in both men and women. The correlation coefficient between BMI and PBF was higher than that between BAI and PBF for both sexes. For the linear regression analysis, BMI better predicted PBF in both men and women; the variation around the regression lines for each sex was greater for BAI comparisons. For the receiver operating characteristic (ROC) analysis, the area under the ROC curve for BMI was higher than that for BAI for each sex, which suggests that the discriminatory capacity of the BMI is higher than the one of BAI. Taken together, we conclude that BMI is a more reliable indicator of PBF derived from skinfold thickness in adult Buryats. Am J Phys Anthropol 152:294–299, 2013. © 2013 Wiley Periodicals, Inc.     

The Peroxisome Proliferator‐Activated Receptor α L162V Mutation Is Associated with Reduced Adiposity

Objective: To determine the contribution of the peroxisome proliferator‐activated receptor α (PPARα) L162V mutation to the variation of several indexes of body fatness obtained from healthy adults who participated in the Quebec Family Study. Research Methods and Procedures: The PPARα L162V mutation was determined by a mismatch polymerase chain reaction method. Adiposity phenotypes were obtained by standardized anthropometric measurements, underwater weighing technique, and computed tomography. Results: For all adiposity phenotypes, subjects carrying the V162 allele had lower values compared with L162 homozygotes (HMZs) [BMI (kg/m²): 27.8 ± 7.6 vs. 26.0 ± 5.6, p < 0.05; percentage body fat: 28.5 ± 10.7 vs. 25.7 ± 10.1, p < 0.05; waist circumference (cm): 89.0 ± 18.1 vs. 85.7 ± 15.8, p = 0.07; total computed tomography abdominal fat areas (cm²): 406 ± 221 vs. 359 ± 192, p = 0.15; means ± SD for L162 HMZs vs. V162 carriers, respectively]. Differences in cross‐sectional abdominal adipose tissue areas and waist circumference were abolished after adjustment for total body fat mass. Similar trends were observed when results were analyzed by gender, although associations seemed stronger in women. The odds ratio of having a BMI above 30 kg/m² reached 1.77 (1.02; 3.07, 95% confidence intervals) for L162 HMZs. This risk could be considered marginal on an individual basis, but because 85% of the subjects are affected by this small risk, the impact on the population is important. Discussion: The PPARα V162 allele is associated with reduced adiposity and has a substantial population‐attributable risk.     

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.     

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.     

Appropriate Body Mass Index and Waist Circumference Cutoffs for Categorization of Overweight and Central Adiposity among Uighur Adults in Xinjiang

Objective

The current overweight and central adiposity guidelines based on Western populations were not consistent with many studied based on the Asian populations. Uighur people live in Xinjiang Uighur Autonomous Region which is located in the center of Asia. Their overweight and central cutoffs were largely unknown. We aimed to identify cutoffs for body mass index (BMI; in kg/m²) and waist circumference (WC; in cm) for categorization of overweight and central adiposity among Uighur adults in Xinjiang.

Methods

4767 Uighur participants were selected from the Cardiovascular Risk Survey (CRS) which was carried out from October 2007 to March 2010. The age of the participants were from 35 to 101 years old with the mean age of 50.09 years. Anthropometric data, blood pressure, serum concentration of serum total cholesterol, triglyceride, low density lipoprotein (LDL), high density lipoprotein (HDL) and fasting glucose were documented. The prevalence, sensitivity, specificity and distance on the receiver operating characteristic (ROC) curve of each BMI and waist circumference values were calculated.

Results

The prevalence of hypertension, hypercholesterolemia and hypertriglyceridemia were higher with higher BMI for both men and women. The prevalence of hypertension and hypercholesterolemia were higher with higher waist circumference for both men and women. In women, the prevalence of hypertriglyceridemia was noticed to increase as the waist circumference increased. The shortest distance in the receiver operating characteristic curves for hypertension, dyslipidemia, diabetes, or ≥ 2 of these risk factors suggested a BMI cutoff of 26 and a waist circumference cutoff of 90 cm for both men and women.

Conclusions

Higher cutoffs for BMI and waist circumference are needed in the identification of Uighur patients at high risk of cardiovascular disease.     

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.