Relationship between Body Mass Index and Percent Body Fat in Vietnamese: Implications for the Diagnosis of Obesity

BackgroundThe burden of obesity in Vietnam has not been well defined because there is a lack of reference data for percent body fat (PBF) in Asians. This study sought to define the relationship between PBF and body mass index (BMI) in the Vietnamese population.MethodsThe study was designed as a comparative cross-sectional investigation that involved 1217 individuals of Vietnamese background (862 women) aged 20 years and older (average age 47 yr) who were randomly selected from the general population in Ho Chi Minh City. Lean mass (LM) and fat mass (FM) were measured by DXA (Hologic QDR 4500). PBF was derived as FM over body weight.ResultsBased on BMI ≥30, the prevalence of obesity was 1.1% and 1.3% for men and women, respectively. The prevalence of overweight and obesity combined (BMI ≥25) was ~24% and ~19% in men and women, respectively. Based on the quadratic relationship between BMI and PBF, the approximate PBF corresponding to the BMI threshold of 30 (obese) was 30.5 in men and 41 in women. Using the criteria of PBF >30 in men and PBF >40 in women, approximately 15% of men and women were considered obese.ConclusionThese data suggest that body mass index underestimates the prevalence of obesity. We suggest that a PBF >30 in men or PBF >40 in women is used as criteria for the diagnosis of obesity in Vietnamese adults. Using these criteria, 15% of Vietnamese adults in Ho Chi Minh City was considered obese.     

Waist Circumference,BMI, and Visceral Adipose Tissue in White Women and Women of African Descent

Although waist circumference (WC) is a marker of visceral adipose tissue (VAT), WC cut‐points are based on BMI category. We compared WC‐BMI and WC‐VAT relationships in blacks and whites. Combining data from five studies, BMI and WC were measured in 1,409 premenopausal women (148 white South Africans, 607 African‐Americans, 186 black South Africans, 445 West Africans, 23 black Africans living in United States). In three of five studies, participants had VAT measured by computerized tomography (n = 456). Compared to whites, blacks had higher BMI (29.6 ± 7.6 (mean ± s.d.) vs. 27.6 ± 6.6 kg/m², P = 0.001), similar WC (92 ± 16 vs. 90 ± 15 cm, P = 0.27) and lower VAT (64 ± 42 vs. 101 ± 59 cm², P < 0.001). The WC‐BMI relationship did not differ by race (blacks: β (s.e.) WC = 0.42 (.01), whites: β (s.e.) WC = 0.40 (0.01), P = 0.73). The WC‐VAT relationship was different in blacks and whites (blacks: β (s.e.) WC = 1.38 (0.11), whites: β (s.e.) WC = 3.18 (0.21), P < 0.001). Whites had a greater increase in VAT per unit increase in WC. WC‐BMI and WC‐VAT relationships did not differ among black populations. As WC‐BMI relationship did not differ by race, the same BMI‐based WC guidelines may be appropriate for black and white women. However, if WC is defined by VAT, race‐specific WC thresholds are required.     

Differential Effects of Abdominal Adipose Tissue Distribution on Insulin Sensitivity in Black and White South African Women

Black South African women are more insulin resistant than BMI‐matched white women. The objective of the study was to characterize the determinants of insulin sensitivity in black and white South African women matched for BMI. A total of 57 normal‐weight (BMI 18–25 kg/m²) and obese (BMI > 30 kg/m²) black and white premenopausal South African women underwent the following measurements: body composition (dual‐energy X‐ray absorptiometry), body fat distribution (computerized tomography (CT)), insulin sensitivity (S_I, frequently sampled intravenous glucose tolerance test), dietary intake (food frequency questionnaire), physical activity (Global Physical Activity Questionnaire), and socioeconomic status (SES, demographic questionnaire). Black women were less insulin sensitive (4.4 ± 0.8 vs. 9.5 ± 0.8 and 3.0 ± 0.8 vs. 6.0 ± 0.8 × 10^?5/min/(pmol/l), for normal‐weight and obese women, respectively, P < 0.001), but had less visceral adipose tissue (VAT) (P = 0.051), more abdominal superficial subcutaneous adipose tissue (SAT) (P = 0.003), lower SES (P < 0.001), and higher dietary fat intake (P = 0.001) than white women matched for BMI. S_I correlated with deep and superficial SAT in both black (R = ?0.594, P = 0.002 and R = 0.495, P = 0.012) and white women (R = ?0.554, P = 0.005 and R = ?0.546, P = 0.004), but with VAT in white women only (R = ?0.534, P = 0.005). In conclusion, body fat distribution is differentially associated with insulin sensitivity in black and white women. Therefore, the different abdominal fat depots may have varying metabolic consequences in women of different ethnic origins.     

Resting Energy Expenditure Changes With Weight Loss: Racial Differences

It is controversial whether weight loss reduces resting energy expenditure (REE) to a different magnitude in black and white women. This aim of this study was to determine whether changes in REE with weight loss were different between black and white postmenopausal women, and whether changes in body composition (including regional lean and fat mass) were associated with REE changes within each race. Black (n = 26) and white (n = 65) women (age = 58.2 ± 5.4 years, 25 < BMI < 40 kg/m²) completed a 20‐week weight‐loss intervention. Body weight, lean and fat mass (total body, limb, and trunk) via dual‐energy X‐ray absorptiometry, and REE via indirect calorimetry were measured before and after the intervention. We found that baseline REE positively correlated with body weight, lean and fat mass (total, limb, and trunk) in white women only (P < 0.05 for all). The intervention decreased absolute REE in both races similarly (1,279 ± 162 to 1,204 ± 169 kcal/day in blacks; 1,315 ± 200 to 1,209 ± 185 kcal/day in whites). REE remained decreased after adjusting for changes in total or limb lean mass in black (1,302–1,182 kcal/day, P = 0.043; 1,298–1,144 kcal/day, P = 0.006, respectively), but not in white, women. Changes in REE correlated with changes in body weight (partial r = 0.277) and fat mass (partial r = 0.295, 0.275, and 0.254 for total, limb, and trunk, respectively; P < 0.05) independent of baseline REE in white women. Therefore, with weight loss, REE decreased in proportion to the amount of fat and lean mass lost in white, but not black, women.     

Adiponectin and leptin in African Americans

Objective: African Americans (AAs) have less visceral and more subcutaneous fat than whites, thus the relationship of adiponectin and leptin to body fat and insulin sensitivity in AA may be different from that in whites. Methods and Procedures: Sixty‐nine non‐diabetic AA (37 men and 32 women), aged 33 ± 1 year participated. The percent fat was determined by dual‐energy X‐ray absorptiometry, abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) volume by computerized tomography (CT), and insulin sensitivity by homeostasis model assessment (HOMA). Results: VAT was greater in men (1,619 ± 177 cm³ vs. 1,022 ± 149 cm³; P = 0.01); women had a higher percentage of body fat (34.1 ± 1.4 vs. 24.0 ± 1.2; P < 0.0001), adiponectin (15.8 ± 1.2 μg/ml vs. 10.4 ± 0.8 μg/ml; P = 0.0004) and leptin (23.2 ± 15.8 ng/ml vs. 9.2 ± 7.2 ng/ml; P < 0.0001). SAT and HOMA did not differ because of the sex. Adiponectin negatively correlated with VAT (r = ?0.41, P < 0.05) in men, and with VAT (r = ?0.55, P < 0.01), and SAT (r = ?0.35, P < 0.05) in women. Adiponectin negatively correlated with HOMA in men (r = ?0.38, P < 0.05) and women (r = ?0.44, P < 0.05). In multiple regression, sex (P = 0.02), HOMA (P = 0.03) and VAT (P = 0.003) were significant predictors of adiponectin (adj R ² = 0.38, P < 0.0001). Leptin positively correlated with VAT, SAT, percent fat and HOMA in men (r = 0.79, r = 0.86, r = 0.89, and r = 0.53; P < 0.001) and women (r = 0.62, r = 0.75, r = 0.83, and r = 0.55; P < 0.01). In multiple regression VAT (P = 0.04), percent body fat (P < 0.0001) and sex (P = 0.01), but not HOMA were significant predictors of serum leptin (adj R ²= 0.82, P < 0.0001). Discussion: The relationship of adiponectin and leptin to body fat content and distribution in AA is dependent on sex. Although VAT and insulin sensitivity are significant determinants of adiponectin, VAT and percent body fat determine leptin.     

Differences in daily energy expenditure in lean and obese women: the role of posture allocation

Objective: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat‐free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. Methods and Procedures: Twenty healthy, non‐smoking, pre‐menopausal women (10 lean and 10 obese) participated in this 14‐day observational study on free‐living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X‐ray absorptiometry (DXA). Results: RMR was similar in the obese vs. lean women (1601 ± 109 vs. 1505 ± 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 ± 3.2 h vs. 10.1 ± 2.0 h, P < 0.05), stood 2 h less (2.7 ± 1.0 h vs. 4.7 ± 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 ± 1.5 h vs. 5.4 ± 1.9 h, P = 0.002). Discussion: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.     

Comparison of Regional Fat Distribution and Health Risk Factors in Middle‐Aged White and African American Women: The Healthy Transitions Study

Objective: Both ethnicity and menopause appear to influence intra‐abdominal fat distribution. This study evaluated intra‐abdominal fat distribution and obesity‐related health risks in perimenopausal white and African American women. Research Methods and Procedures: Baseline data from a longitudinal study of changes in body composition and energy balance during menopause are reported. Healthy women (55 African Americans and 103 whites) who were on no medication and had at least five menstrual cycles in the previous 6 months were recruited. Body composition was assessed by DXA, and visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were assessed by computed tomography scan. SAT was divided into deep and superficial layers demarcated by the fascia superficialis. Results: African American women were slightly younger (46.7 ± 0.2 vs. 47.7 ± 0.2 years, p = 0.002) and fatter (42.4% ± 1.0% vs. 39.4% ± 0.8% body fat, p = 0.02) than white women. In unadjusted data, African Americans had significantly more total abdominal fat and total, deep, and superficial SAT than whites. After adjustment for percent body fat and age, only total and superficial SAT remained significantly higher in African Americans. VAT although slightly less in African American women, did not differ significantly by race. In multiple regression analysis, VAT was the strongest predictor of serum lipids, glucose, and insulin in women of both races, although superficial SAT was significantly associated with fasting glucose in whites. Conclusions: Middle‐aged African American women have larger SAT depots, adjusted for total body fatness, but do not differ from white women with regard to VAT. The complexity of the relationship between abdominal fat and metabolic risk is increased by ethnic differences in such associations.     

Low resting energy expenditure in Asians can be attributed to body composition

Objective: To compare resting energy expenditure (REE) between Asians and whites after adjusting for fat‐free mass measured with a two‐ or more‐compartment model. Methods and Procedures: Participants were 10 white men (28 ± 3 years), 10 Asian men (30 ± 4 years), 10 white women (22 ± 4 years), and 11 Asian women (31 ± 7 years). REE was measured with a ventilated hood system under strictly controlled conditions. Body composition was measured with a two‐compartment model based on body mass (BM) and body volume (hydrodensitometry), a three‐compartment model adding total body water (TBW) (deuterium dilution), and a four‐compartment model incorporating bone mass (dual‐energy X‐ray absorptiometry (DXA)) as well. Lean BM in the trunk and in the extremities was assessed with DXA. All measurements were performed at Maastricht University. Measurements on Asian subjects were performed within 3 months after their arrival in the Netherlands. Results: Absolute REE was lower in Asians (5.87 ± 0.91 MJ/day) than in whites (7.00 ± 1.11 MJ/day). There was no significant difference in REE between the two races after adjustment for fat‐free mass. Discussion: There were no significant differences in REE between Asians and whites after adjustment for differences in body composition based on a two‐ or more‐compartment model.     

Is Body Mass Index a Measure of Adiposity in Elderly Women?

Objective: To evaluate the accuracy of body mass index (BMI) as a predictor of body fat in elderly women. Research Methods and Procedures: A total of 1423 women aged 67 ± 5 (mean ± SD, range: 60 to 88) years were consecutively enrolled into the study. Fat mass (FM) was measured using DXA. Results: BMI explained 72.9% of FM variance (p < 0.0001), with a root mean square error of estimate (RMSE) of 3.5 kg. After standardization of RMSE on the dependent variable as RMSE%, the prediction error equaled 15%. BMI explained 54.8% of FM% variance (p < 0.0001), with an RMSE of 4.1%, corresponding to an RMSE% of 11%. Discussion: The relatively high RMSE% of the FM and FM%‐BMI associations caution against the use of BMI as an adiposity index in individual elderly women. However, an error corresponding to 11% of FM% may be accepted for population studies of body fat in elderly women.     

Role of β2‐Adrenergic Receptor Polymorphisms on Body Weight and Body Composition Response to Energy Restriction in Obese Women: Preliminary Results

We investigated the role of common β2‐adrenergic receptor (ADRB2) rs1042714 (Gln27Glu) and rs1042713 (Arg16Gly) polymorphisms on body weight and body composition response to 12‐week energy‐restricted diet in women. The study comprised 78 Spanish obese (BMI: 34.0 ± 2.8 kg/m²) women (age: 36.7 ± 7 years). We measured (before and after the dietary intervention) weight and height, and BMI calculated. Moreover, body fat mass and lean mass (LM) were measured by dual energy X‐ray absorptiometry. We observed an interaction effect between the Gln27Glu polymorphism and diet‐induced changes on body weight (P = 0.006), BMI (P = 0.004), and LM (P = 0.001). Women carrying the Glu allele had a greater reduction in body weight than non‐Glu allele carriers (9.5 ± 2.9 vs. 7.0 ± 3.5%, respectively, P = 0.002). Moreover, women with the Glu allele lost more LM than the Gln27Gln group (5.9 ± 2.7 vs. 4.0 ± 2.7%, respectively, P = 0.001). We did not find any significant interaction effect between the Arg16Gly polymorphism and diet‐induced changes on the outcome variables (all P > 0.1). The results suggest that the ADRB2 Gln27Glu polymorphism has a modulating effect on diet‐induced changes on body weight and body composition, and should be considered in future obesity treatments. These findings should be taken as preliminary and be replicated in further energy restriction studies with larger sample sizes.     

Racial Differences in the Tracking of Childhood BMI to Adulthood

Objective: The possibility that there are racial differences in the patterns of BMI (kilograms per meter squared) change throughout life has not been examined. For example, the high prevalence of obesity among black women could result from a higher prevalence of obesity among black girls or because normal‐weight black girls experience larger BMI increases in adolescence or adulthood than do their white counterparts. Therefore, we examined the tracking of childhood BMI into adulthood in a biracial (36% black) sample. Research Methods and Procedures: Five‐ to 14‐year‐old children (2392) were followed for (mean) 17 years. Childhood overweight was defined as BMI ≥ 95th percentile, and adult obesity was defined as BMI ≥ 30 kg/m². Results: The tracking of childhood BMI differed between whites and blacks. Among overweight children, 65% of white girls vs. 84% of black girls became obese adults, and predictive values among boys were 71% (whites) vs. 82% (blacks). These racial differences reflected contrasting patterns in the rate of BMI change. Although the initial BMI of black children was not higher than that of white children, BMI increases with age were larger among black girls and overweight black boys than among their white counterparts. In contrast, relatively thin (BMI < 50th percentile) white boys were more likely to become overweight adults than were their black counterparts. Discussion: These findings emphasize the black/white differences in BMI changes with age. Because of the adult health consequences of childhood‐onset obesity, early prevention should be given additional emphasis.     

Altered Intramuscular Lipid Metabolism Relates to Diminished Insulin Action in Men,but Not Women,in Progression to Diabetes

Whether sex differences in intramuscular triglyceride (IMTG) metabolism underlie sex differences in the progression to diabetes are unknown. Therefore, the current study examined IMTG concentration and fractional synthesis rate (FSR) in obese men and women with normal glucose tolerance (NGT) vs. those with prediabetes (PD). PD (n = 13 men and 7 women) and NGT (n = 7 men and 12 women) groups were matched for age and anthropometry. Insulin action was quantified using a hyperinsulinemic‐euglycemic clamp with infusion of [6,6^?2H₂]‐glucose. IMTG concentration was measured by gas chromatography/mass spectrometry (GC/MS) and FSR by GC/combustion isotope ratio MS (C‐IRMS), from muscle biopsies taken after infusion of [U^?13C]palmitate during 4 h of rest. In PD men, the metabolic clearance rate (MCR) of glucose was lower during the clamp (4.71 ± 0.77 vs. 8.62 ± 1.26 ml/kg fat‐free mass (FFM)/min, P = 0.04; with a trend for lower glucose rate of disappearance (Rd), P = 0.07), in addition to higher IMTG concentration (41.2 ± 5.0 vs. 21.2 ± 3.4 µg/mg dry weight, P ≤ 0.01), lower FSR (0.21 ± 0.03 vs. 0.42 ± 0.06 %/h, P ≤ 0.01), and lower oxidative capacity (P = 0.03) compared to NGT men. In contrast, no difference in Rd, IMTG concentration, or FSR was seen in PD vs. NGT women. Surprisingly, glucose Rd during the clamp was not different between NGT men and women (P = 0.25) despite IMTG concentration being higher (42.6 ± 6.1 vs. 21.2 ± 3.4 µg/mg dry weight, P = 0.03) and FSR being lower (0.23 ± 0.04 vs. 0.42 ± 0.06 %/h, P = 0.02) in women. Alterations in IMTG metabolism relate to diminished insulin action in men, but not women, in the progression toward diabetes.     

Dual‐energy X‐ray Absorptiometry and Anthropometric Estimates of Visceral Fat in Black and White South African Women

Visceral adipose tissue (VAT) is associated with increased risk for cardiovascular disease, and therefore, accurate methods to estimate VAT have been investigated. Computerized tomography (CT) is the gold standard measure of VAT, but its use is limited. We therefore compared waist measures and two dual‐energy X‐ray absorptiometry (DXA) methods (Ley and Lunar) that quantify abdominal regions of interest (ROIs) to CT‐derived VAT in 166 black and 143 white South African women. Anthropometry, DXA ROI, and VAT (CT at L4–L5) were measured. Black women were younger (P < 0.001), shorter (P < 0.001), and had higher body fat (P < 0.05) than white women. There were no ethnic differences in waist (89.7 ± 18.2 cm vs. 90.1 ± 15.6 cm), waist:height ratio (WHtR, 0.56 ± 0.12 vs. 0.54 ± 0.09), or DXA ROI (Ley: 2.2 ± 1.5 vs. 2.1 ± 1.4; Lunar: 2.3 ± 1.4 vs. 2.3 ± 1.5), but black women had less VAT, after adjusting for age, height, weight, and fat mass (76 ± 34 cm² vs. 98 ± 35 cm²; P < 0.001). Ley ROI and Lunar ROI were correlated in black (r = 0.983) and white (r = 0.988) women. VAT correlated with DXA ROI (Ley: r = 0.729 and r = 0.838, P < 0.01; Lunar: r = 0.739 and r = 0.847, P < 0.01) in black and white women, but with increasing ROI android fatness, black women had less VAT. Similarly, VAT was associated with waist (r = 0.732 and r = 0.836, P < 0.01) and WHtR (r = 0.721 and r = 0.824, P < 0.01) in black and white women. In conclusion, although DXA‐derived ROIs correlate well with VAT as measured by CT, they are no better than waist or WHtR. Neither DXA nor anthropometric measures are able to accurately distinguish between high and low levels of VAT between population groups.     

Central adiposity and other anthropometric factors in relation to risk of macrosomia in an african american population

Objective:

Previous studies have consistently identified maternal obesity and gestational weight gain (GWG) as risk factors for macrosomia, but little is known about the effects of central adiposity and body fat distribution. Using self‐reported data from the Black Women's Health Study (BWHS), a large follow‐up study of US black women, we examined the risk of macrosomia in relation to prepregnancy waist circumference, prepregnancy waist‐to‐hip ratio (WHR), prepregnancy BMI, and GWG.

Design and Methods:

During 1995–2003, BWHS participants ages 21–44 years delivered 6,687 full‐term singleton births (gestational age >37 weeks). We compared mothers of 691 infants weighing ≥4,000 g with mothers of 5,996 infants weighing <4,000 g. Generalized estimating equation models (GEE) that accounted for more than one birth per mother were used to estimate multivariable odds ratios (OR) and 95% confidence intervals (CI).

Results:

Independent of prepregnancy BMI, prepregnancy waist circumference was positively associated with risk of macrosomia (OR = 1.58, 95% CI: 1.07–2.32, for ≥35.0 vs. <27.0 inches (≥88.9 vs. <68.6 cm); P trend = 0.04). As expected, prepregnancy BMI was also positively associated with macrosomia (OR = 1.74, 95% CI: 1.25–2.41 for BMI ≥35.0 vs. 18.5–24.9 kg m^?2). GWG above the amount recommended by the 2009 Institute of Medicine report was associated with an increased risk of macrosomia and the association was present in each category of prepregnancy BMI (18.5–24.9, 25.0–29.9, and ≥30.0 kg m^?2; P trend <0.001).

Conclusions:

Our data suggest that overall obesity, high GWG, and high waist circumference are independent risk factors for macrosomia among US black women.

     

Korean and Caucasian overweight premenopausal women have different relationship of body mass index to percent body fat with age.

The aim of the study was to investigate in premenopausal women whether the relationship between percentage body fat (PBF) and body mass index (BMI; in kg/m2) differs between Korean Asians (Ko-As) living in Seoul, South Korea, and Caucasians (Ca) living in New York City. Healthy premenopausal women (50 Ko-As; 38 Ca), ages 22-50 yr, were studied. Weight, height, and PBF by dual-energy X-ray absorptiometry were measured. Total body dual-energy X-ray absorptiometry data were collected using GE-Lunar systems (Prodigy-Korea and DPXL-New York), and all scan analyses were performed by one technician in New York. Similar soft tissue phantoms were used for daily instrument calibrations at both sites. The relationship between PBF and BMI was assessed by multiple regression analysis with race, age, reciprocal of BMI (1/BMI), and a race-by-age interaction as the final independent variables. Race (P = 0.003) and 1/BMI (P < 0.001) were significantly related to PBF in this model. A significant race-by-age interaction (P = 0.039) indicated that the slope of the lines for PBF vs. age differed between Ko-As and Ca. This study demonstrates in a Ko-As sample that the BMI-fat relationship differs significantly from that in a comparable group of Caucasian women. Investigators who use BMI as an index of fatness should be aware of the well documented differences in the relationship of BMI and fatness across race/ethnic groups.     

Severe Obesity Is Associated With Impaired Arterial Smooth Muscle Function in Young Adults

The degree of arterial dilatation induced by exogenous nitrates (nitrate‐mediated dilatation, NMD) has been similar in obese and normal‐weight adults after single high‐dose glyceryl trinitrate (GTN). We examined whether NMD is impaired in obesity by performing a GTN dose‐response study, as this is a potentially more sensitive measure of arterial smooth muscle function. In this cross‐sectional study, subjects were 19 obese (age 31.0 ± 1.2 years, 10 male, BMI 44.1 ± 2.1) and 19 age‐ and sex‐matched normal‐weight (BMI 22.4 ± 0.4) young adults. Blood pressure (BP), triglycerides, high‐density lipoprotein (HDL), and low‐density lipoprotein (LDL)‐cholesterol, glucose, insulin, high‐sensitivity C‐reactive protein (hs‐CRP), carotid intima‐media thickness (CIMT), and flow‐mediated dilatation (FMD) were measured. After incremental doses of GTN, brachial artery maximal percent dilatation (maximal NMD) and the area under the dose‐response curve (NMD AUC) were calculated. Maximal NMD (13.4 ± 0.9% vs. 18.3 ± 1.1%, P = 0.002) and NMD AUC (54,316 ± 362 vs. 55,613 ± 375, P = 0.018) were lower in obese subjects. The obese had significantly higher hs‐CRP, insulin, and CIMT and lower HDL‐cholesterol. Significant bivariate associations existed between maximal NMD or NMD AUC and BMI‐group (r = ?0.492, P = 0.001 or r = ?0.383, P = 0.009), hs‐CRP (r = ?0.419, P = 0.004 or r = ?0.351, P = 0.015), and HDL‐cholesterol (r = 0.374, P = 0.01 or r = 0.270, P = 0.05). On multivariate analysis, higher BMI‐group remained as the only significant determinant of maximal NMD (r² = 0.242, β = ?0.492, P = 0.002) and NMD AUC (r² = 0.147, β = ?0.383, P = 0.023). In conclusion, arterial smooth muscle function is significantly impaired in the obese. This may be important in their increased cardiovascular risk.     

Association Between the 4 bp Proinsulin Gene Insertion Polymorphism (IVS‐69) and Body Composition in Black South African Women

The objective of the study was to examine the association between a functional 4 bp proinsulin gene insertion polymorphism (IVS‐69), fasting insulin concentrations, and body composition in black South African women. Body composition, body fat distribution, fasting glucose and insulin concentrations, and IVS‐69 genotype were measured in 115 normal‐weight (BMI <25 kg/m²) and 138 obese (BMI ≥30 kg/m²) premenopausal women. The frequency of the insertion allele was significantly higher in the class 2 obese (BMI ≥35kg/m²) compared with the normal‐weight group (P = 0.029). Obese subjects with the insertion allele had greater fat mass (42.3 ± 0.9 vs. 38.9 ± 0.9 kg, P = 0.034) and fat‐free soft tissue mass (47.4 ± 0.6 vs. 45.1 ± 0.6 kg, P = 0.014), and more abdominal subcutaneous adipose tissue (SAT, 595 ± 17 vs. 531 ± 17 cm², P = 0.025) but not visceral fat (P = 0.739), than obese homozygotes for the wild‐type allele. Only SAT was greater in normal‐weight subjects with the insertion allele (P = 0.048). There were no differences in fasting insulin or glucose levels between subjects with the insertion allele or homozygotes for the wild‐type allele in the normal‐weight or obese groups. In conclusion, the 4 bp proinsulin gene insertion allele is associated with extreme obesity, reflected by greater fat‐free soft tissue mass and fat mass, particularly SAT, in obese black South African women.     

Changes in Body Weight and Waist Circumference Affect Incident Hypercholesterolemia During 7 Years of Follow‐up

Objective: To assess whether changes in total and regional adiposity affect the odds for becoming hypercholesterolemic. Methods and Procedures: Changes in BMI and waist circumference were compared to self‐reported physician‐diagnosed hypercholesterolemia in 24,397 men and 10,023 women followed prospectively in the National Runners' Health Study. Results: Incident hypercholesterolemia were reported by 3,054 men and 519 women during (mean ± s.d.) 7.8 ± 1.8 and 7.5 ± 2.0 years of follow‐up, respectively. Despite being active, men's BMI increased by 1.15 ± 1.71 kg/m² and women's BMI increased by 0.96 ± 1.89 kg/m². The odds for developing hypercholesterolemia increased significantly in association with gains in BMI and waist circumferences in both sexes. A gain in BMI ≥2.4 kg/m² significantly (P < 0.0001) increased the odds for hypercholesterolemia by 94% in men and 129% in women compared to those whose BMI declined (40 and 76%, respectively, adjusted for average of the baseline and follow‐up BMI, P < 0.0001). A gain of ≥6 cm in waist circumference increased men's odds for hypercholesterolemia by 74% (P < 0.0001) and women's odds by 70% (P < 0.0001) relative to those whose circumference declined (odds increased 40% at P < 0.0001 and 49% at P < 0.01, respectively adjusted for average circumference). BMI and waist circumference at the end of follow‐up were significantly associated (P < 0.0001) with the log odds for hypercholesterolemia in both men (e.g., coefficient ± s.e.: 0.115 ± 0.011 per kg/m²) and women (e.g., 0.119 ± 0.019 per kg/m²) when adjusted for baseline values, whereas baseline BMI and circumferences were unrelated to the log odds when adjusted for follow‐up values. Discussion: These observations are consistent with the hypothesis that weight gain acutely increases the risk for hypercholesterolemia.     

Body fat responses to a 1‐year combined exercise training program in male coronary artery disease patients

Objective:

To analyze the body fat (BF) content and distribution modifications in coronary artery disease (CAD) patients in response to a 1‐year combined aerobic and resistance exercise training (CET) program.

Design and Methods:

We followed two groups of CAD male patients for 12 months. One group consisted of 17 subjects (57 ± 12 years) who engaged in a CET program (CET group) and the other was a age‐matched control group of 10 subjects (58 ± 11 years). BF content and distribution were measured through dual energy X‐ray absorptiometry (DXA) at baseline and follow‐up.

Results:

We found no differences on body mass and BMI between baseline and end of follow‐up in both groups but, in CET group, we found significant reductions in all analyzed BF depots, including total BF (21.60 ± 6.00 vs. 20.32 ± 5.89 kg, P < 0.01), % total BF (27.8 ± 5.5 vs. 26.4 ± 5.4%, P < 0.05), trunk fat (12.54 ± 3.99 vs. 11.77 ± 4.01 kg, P < 0.05), % trunk fat (31.1 ± 6.9 and 29.2 ± 7.1%, P < 0.05), appendicular fat (8.22 ± 2.08 vs. 7.72 ± 2.037 kg, P < 0.01), % appendicular fat (25.7 ± 4.9 and 24.5 ± 4.9%, P < 0.05), and abdominal fat (2.95 ± 1.06 vs. 2.75 ± 1.10 kg, P < 0.05). Control group showed significant increase in appendicular fat (7.63 ± 1.92 vs. 8.10 ± 2.12 kg, P < 0.05).

Conclusions:

These results confirm the positive effect of CET on body composition of CAD patients, despite no changes in body mass or BMI. In this study, we observed no alterations on BF distribution meaning similar rate of fat loss in all analyzed BF depots. These results also alert for the limitations of BMI for tracking body composition changes.     

Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.