Alcohol intake, insulin resistance, and abdominal obesity in elderly men

Objective: Moderate and high alcohol intake have been associated with decreased and increased risk of type 2 diabetes, respectively. Insulin resistance, insulin secretion, and abdominal obesity are major predictors of diabetes, but the links with alcohol intake remain contradictory because of limited data. Research Methods and Procedures: In a population‐based cohort of 807 men (age, 70 years), we studied whether alcohol intake was related to insulin sensitivity, measured with the gold standard technique (euglycemic clamp), insulin secretion (early insulin response), or adiposity [BMI, waist circumference (WC), waist‐to‐hip ratio]. Alcohol intake was self‐reported (questionnaire) and was assessed from a validated 7‐day dietary record. The cross‐sectional associations were evaluated using multivariable linear regression, adjusting for smoking, education level, physical activity, dietary total energy intake, hypertension, diabetes, triglycerides, and cholesterol. Results: In multivariable models, self‐estimated alcohol intake was not related to insulin sensitivity, early insulin response, or BMI, but was positively related to WC (β‐coefficient, 0.77; 95% confidence interval, 0.15 to 1.39; p = 0.02) and waist‐to‐hip ratio (0.006 [0.002–0.009], p = 0.003). The association with WC and waist‐to‐hip ratio was most pronounced in men in the lowest tertile of BMI. The results using dietary records were similar. Discussion: Evaluated in a large sample in elderly men, neither insulin sensitivity measured by clamp technique nor insulin secretion was significantly associated with alcohol intake. However, high alcohol intake was associated with abdominal obesity, which might explain the higher diabetes risk previously observed in high alcohol consumers.     

Influence of Waist on Adiponectin and Insulin Sensitivity in Adolescence

It has been hypothesized that abdominal obesity leads to insulin resistance partly through decreased adiponectin. However, the cross‐sectional and longitudinal associations among waist, adiponectin, and insulin sensitivity have not been examined in older adolescents. Non‐Hispanic white and black children were recruited from the Minneapolis school district and underwent three examinations at mean ages 13, 15, and 19. Insulin sensitivity (measured using the gold‐standard euglycemic clamp) and waist circumference were measured at all exams. Adiponectin was measured at mean ages 15 and 19. Partial correlations were used to examine associations among waist, adiponectin, and insulin sensitivity at mean age 15 (n = 308) and mean age 19 (n = 218). Longitudinal correlations and a longitudinal regression model were used to predict adiponectin and insulin sensitivity measured at ages 15 and 19, from age 13 waist and change in waist. At age 15, waist and adiponectin were significantly correlated (r = ?0.32). At age 19, waist and adiponectin were significantly correlated (r = ?0.36), as were waist and insulin sensitivity (r = ?0.16). Both baseline waist and change in waist were significantly inversely associated with age 19 adiponectin but with age 19 insulin sensitivity only in men. In conclusion, in adolescents, the association between waist and adiponectin appears to develop several years before the association between waist and insulin sensitivity and there is a longitudinal association between waist and adiponectin. These results support the hypothesis that adiponectin may contribute to the association of waist and insulin sensitivity.     

Secular trends of obesity and cardiovascular risk factors in a Mediterranean population

Objective: To evaluate time trends of obesity, abdominal obesity, and cardiovascular risk factors (CRFs) according to BMI and waist circumference (WC) categories in a Mediterranean population. Research Methods and Procedures: Subjects were Spanish men (n = 2383) and women (n = 2525) 25 to 74 years old, examined in 1994 to 1995 and 1999 to 2000 in two independent population‐based cross‐sectional surveys in the northeast of Spain. Lifestyle measures, CRFs, and anthropometric variables were analyzed. Results: Over the 5 years of the study, mean age‐standardized BMI increased by 1.0 units in men and by 0.8 units in women. At the same time the prevalence of obesity increased from 15.4% to 21.9% in men and from 15.4% to 21.4% in women. An upward trend was observed for WC and abdominal obesity (WC > 102 cm in men and WC > 88 cm in women) only in men. The proportion of men and women with hypercholesterolemia, diabetes, and low high‐density lipoprotein‐cholesterol plasma concentration remained stable within BMI and WC categories. The proportion of hypertension and smoking in obese men significantly increased from 1995 to 2000. Discussion: The 5‐year increase in BMI and WC is of considerable magnitude in the present population, although several CRFs remained stable within BMI and WC categories.     

Development of Health‐Related Waist Circumference Thresholds Within BMI Categories

Objective: To develop and cross‐validate waist circumference (WC) thresholds within BMI categories. The utility of the derived values was compared with the single WC thresholds (women, 88 cm; men, 102 cm) recommended by NIH and Health Canada. Research Methods and Procedures: The sample included adults classified as normal weight (BMI = 18.5 to 24.9), overweight (BMI = 25 to 29.9), obese I (BMI = 30 to 34.9), and obese II+ (BMI ≥ 35) from the Third U.S. National Health and Nutrition Examination Survey (NHANES III; n = 11, 968) and the Canadian Heart Health Surveys (CHHS; n = 6286). Receiver operating characteristic curves were used to determine the optimal WC thresholds that predicted high risk of coronary events (top quintile of Framingham scores) within BMI categories using the NHANES III. The BMI‐specific WC thresholds were cross‐validated using the CHHS. Results: The optimal WC thresholds increased across BMI categories from 87 to 124 cm in men and from 79 to 115 cm in women. The validation study indicated improved sensitivity and specificity with the BMI‐specific WC thresholds compared with the single thresholds. Discussion: Compared with the recommended WC thresholds, the BMI‐specific values improved the identification of health risk. In normal weight, overweight, obese I, and obese II+ patients, WC cut‐offs of 90, 100, 110, and 125 cm in men and 80, 90, 105, and 115 cm in women, respectively, can be used to identify those at increased risk.     

Minimal versus umbilical waist circumference measures as indicators of cardiovascular disease risk

Objective: Measures of central obesity are strongly correlated with cardiovascular disease (CVD) risk. Although waist circumference (WC) is a commonly used measure of central obesity, there is no standard measurement location. We examined two WC locations to determine which was more highly correlated with CVD risk factors and metabolic syndrome (MS). Research Methods and Procedures: WC measures were taken on 266 sedentary, overweight men and women 45 to 60 years old. Intravenous glucose tolerance tests, fasting plasma lipid analysis, and computed tomography scans were conducted. Correlational analyses followed by the Test for Equal Correlations determined whether one WC measure better correlated with the cardiovascular risk factors. Results: In women, minimal waist had higher correlation coefficients than umbilical waist for all eight variables presented. High‐density lipoprotein‐cholesterol, low‐density lipoprotein particle size, and MS score were significantly correlated with minimal waist, but not umbilical waist. For high‐density lipoprotein size and insulin sensitivity, minimal waist was a better correlate, although the difference between waist measures only approached statistical significance (p < 0.06). In men, minimal waist had a higher correlation coefficient than umbilical waist for insulin sensitivity, fasting insulin, and visceral adipose tissue. Additionally, minimal waist was significantly correlated with MS in men and umbilical waist was not. For both genders, minimal waist was more highly correlated with visceral adipose tissue than umbilical waist. Discussion: For every metabolic variable presented, minimal WC was more highly correlated with CVD risk than was umbilical WC in women. The data for women indicate that WC location is important when determining CVD risk. In men, minimal waist was better, although the data were less compelling.     

Overweight,Waist Circumference,Age, Gender,and Insulin Resistance as Risk Factors for Hyperleptinemia

Objective: To evaluate the influence of overweight, waist circumference, age, gender, and insulin resistance as risk factors for hyperleptinemia. Research Methods and Procedures: A cross‐sectional study was carried out in a population of 197 subjects: 59 men (21 aged <60 years and 38 aged ≥60 years) and 138 women (37 aged <60 years and 101 aged ≥60 years). The groups were stratified by overweight and normal weight. After a 12‐hour fasting period, we measured serum leptin and insulin levels with radioimmunoassay methods. We also measured serum glucose and lipid profile. The data were analyzed by means of comparative tests. A variance‐stabilizing transformation (natural logarithmic) was used to meet multiple linear regression, analysis of covariance, and logistic regression models. Results: The leptin serum levels were higher and statistically significant in young and older women than they were in men. We observed an interaction between gender and body mass index to explain the difference in leptin levels (p < 0.0001). Our study demonstrated an inverse relationship between leptin with age and high‐density lipoprotein cholesterol. In logistic regression analysis, the overweight × gender interaction and waist circumference have a statistically significant influence as independent variables on hyperleptinemia (overweight × gender odds ratio = 6.81; 95% confidence interval, 1.10 to 46.86; p < 0.05 and waist circumference odds ratio = 4.34; 95% confidence interval, 1.47 to 12.83; p = 0.001). Discussion: Women who were overweight or had a higher waist circumference (women ≥ 88 cm and men ≥ 102 cm) have a significantly higher risk of having hyperleptinemia. The increase in age as an isolated variable is not a risk factor for hyperleptinemia.     

BMI compared with central obesity indicators in relation to diabetes and hypertension in Asians

Objective: To compare BMI with waist circumference (WC), waist‐to‐hip ratio (WHR), and waist‐to‐stature ratio (WSR) in association with diabetes or hypertension. Methods and Procedures: Cross‐sectional data from 16 cohorts from the DECODA (Diabetes Epidemiology: Collaborative Analysis of Diagnostic criteria in Asia) study, comprising 9,095 men and 11,732 women, aged 35–74 years, of different ethnicities were included in this meta‐analysis. Results: Age‐adjusted odds ratios (ORs) for diabetes in men (women) for 1 s.d. increase in BMI, WC, WHR, and WSR were 1.52 (1.59), 1.54 (1.70), 1.53 (1.50), and 1.62 (1.70), respectively; and the corresponding ORs for hypertension were 1.68 (1.55), 1.66 (1.51), 1.45 (1.28), and 1.63 (1.50). Paired homogeneity tests (BMI with each of the three) adjusted for age and cohort showed that diabetes had stronger association with WSR than BMI (P = 0.001) in men but with WC and WSR than BMI (both P < 0.05) in women. Hypertension had stronger association with BMI than WHR in men (P < 0.001) and had the strongest with BMI than the others (WHR P < 0.001; WSR P < 0.01; and WC P < 0.05) in women. Areas under the receiver operating characteristic (ROC) curves adjusted for age and cohort were slightly larger for diabetes for WSR 0.735 (0.748) in men (women) and WC 0.749 (women only) than BMI 0.725 (0.742) while for hypertension larger for BMI 0.760 (0.766) than WHR 0.748 (0.751), but their 95% CIs were all overlapped. Discussion: WSR was stronger than BMI in association with diabetes, but these indicators were equally strongly associated with hypertension in Asians.     

First nationwide survey of prevalence of overweight, underweight, and abdominal obesity in Iranian adults

Objective: The goal was to estimate the prevalence of overweight, obesity, underweight, and abdominal obesity among the adult population of Iran. Research Methods and Procedures: A nationwide cross‐sectional survey was conducted from December 2004 to February 2005. The selection was conducted by stratified probability cluster sampling through household family members in Iran. Weight, height, and waist circumference (WC) of 89,404 men and women 15 to 65 years of age (mean, 39.2 years) were measured. The criteria for underweight, normal‐weight, overweight, and Class I, II, and III obesity were BMI <18.5, 18.5 to 24.9, 25 to 29.9, 30 to 34.9, 35 to 39.9, and ≥40 (kg/m²), respectively. Abdominal obesity was defined as WC ≥102 cm in men and ≥88 cm in women. Results: The age‐adjusted means for BMI and WC were 24.6 kg/m² in men and 26.5 kg/m² in women and 86.6 cm in men and 89.6 cm in women, respectively. The age‐adjusted prevalence of overweight or obesity (BMI ≥25) was 42.8% in men and 57.0% in women; 11.1% of men and 25.2% of women were obese (BMI ≥30), while 6.3% of men and 5.2% of women were underweight. Age, low physical activity, low educational attainment, marriage, and residence in urban areas were strongly associated with obesity. Abdominal obesity was more common among women than men (54.5% vs. 12.9%) and greater with older age. Discussion: Excess body weight appears to be common in Iran. More women than men present with overweight and abdominal obesity. Prevention and treatment strategies are urgently needed to address the health burden of obesity.     

Mediating Effects of Inflammatory Biomarkers on Insulin Resistance Associated with Obesity

Objective: Obesity is associated with elevated levels of biomarkers of inflammation and endothelial dysfunction [including C‐reactive protein (CRP), E‐selectin, and intercellular adhesion molecule‐1], as well as insulin resistance (IR) and type 2 diabetes. We tested the hypothesis that these biomarkers mediate associations among obesity, IR, and risk of diabetes. Research Methods and Procedures: We stratified 510 initially non‐diabetic women in the Nurses’ Health Study cohort into four phenotypes above/below median BMI (27 kg/m²) and waist circumference (81 cm): low BMI‐low waist (LBLW; N = 190), low BMI‐high waist (LBHW; N = 74), high BMI‐low waist (HBLW; N = 27), and high BMI‐high waist (HBHW; N = 219). Results: In models assessing associations of weight phenotype with IR [fasting insulin (FI)], adjusted for age and diabetes risk factors, mean FI was higher comparing HBHW women (13.6 μU/mL, p < 0.0001) and LBHW (11.5 μU/mL, p = 0.02) with LBLW women (8.6 μU/mL); HBLW and LBLW women were not significantly different. Differences in FI levels were most strongly attenuated after adjustment for E‐selectin comparing LBHW with LBLW women (11.7 vs. 9.7 μU/mL, p = 0.2). Discussion: In logistic regression models, LBHW predicted diabetes (risk factor‐adjusted relative risk 2.06, 1.05 to 6.40), compared with LBLW, but was no longer significant after adjustment for E‐selectin or CRP. After adjusting for CRP and E‐selectin, only HBHW and E‐selectin were significantly associated with risk of diabetes. In women with central adiposity and low BMI, endothelial dysfunction and inflammation may mediate the relationship among central fat, IR, and incident diabetes.     

Analysis of Obesity and Hyperinsulinemia in the Development of Metabolic Syndrome: San Antonio Heart Study

Objective: To use standardized cut‐offs of body mass index (BMI), waist circumference, waist‐to‐hip ratio, and fasting insulin levels to predict the development of metabolic disorders and metabolic syndrome. Research Methods and Procedures: We performed an 8‐year follow‐up study of 628 non‐Hispanic whites and 1340 Mexican Americans, ages 25 to 64 years, from the second cohort of the San Antonio Heart Study. We defined metabolic disorders as dyslipidemia (triglycerides ≥2.26 mM or high‐density lipoprotein <0.91 mM in men and <1.17 mM in women), hypertension (blood pressure ≥140/≥90 mm Hg, or receiving antihypertensive medications), and type 2 diabetes (fasting glucose ≥7.0 mM, 2‐hour test glucose ≥11.1 mM, or receiving anti‐diabetic medications). People with at least two metabolic disorders were defined as having metabolic syndrome. Results: High waist‐to‐hip ratio and fasting insulin levels were significant predictors of developing metabolic syndrome. High anthropometric indices remained significant predictors of metabolic syndrome after adjusting for fasting insulin. Waist circumference, BMI, and insulin had similar areas under the receiver operating characteristic curves (0.74 to 0.76). Further multivariate analyses combining these indices showed minimal increase in prediction. Of subjects who had a combination of high BMI (≥30 kg/m²) and high waist circumference (above “Action Level 2”), 32% developed metabolic syndrome, compared with 10% of subjects with both low BMI and low waist circumference. Discussion: These findings support the National Institutes of Health recommendations for reducing the risk of metabolic syndrome. Adjustment for baseline fasting insulin levels had only a small effect on the ability of anthropometric indices to predict the metabolic syndrome.     

Which Obesity Index Best Explains Prevalence Differences in Type 2 Diabetes Mellitus?

Objective: Obesity drives the diabetes epidemic. However, it is not known which obesity index best explains variations in type 2 diabetes mellitus prevalence across populations. Research Methods and Procedures: We analyzed three cross‐sectional studies from San Antonio, TX, (Mexican‐Americans and non‐Hispanic whites, n = 2839), Mexico City (n = 2233), and Spain (n = 2161) (age range, 35 to 64 years). We used the area under the receiver operating characteristic curve (AUC) to assess performance for identifying diabetic subjects and logistic regression analysis to examine differences in diabetes prevalence. Results: AUCs for waist circumference and BMI were similar in white subjects, but the AUC for waist circumference was greater in Mexican‐origin subjects (Mexican men, 0.594 vs. 0.549, p = 0.008; and women, 0.605 vs. 0.557, p = 0.002; Mexican‐American men, 0.648 vs. 0.600, p < 0.001; and women, 0.744 vs. 0.693, p < 0.001). The AUC for waist‐to‐height ratio tended to be greater than that for waist circumference, but statistical significance was demonstrated only in Mexican women (0.628 vs. 0.613, p = 0.044), Mexican‐American women (0.774 vs. 0.758, p < 0.001), and Spanish women (0.734 vs. 0.715, p = 0.039). No obesity index was consistently superior to the others for explaining differences in diabetes prevalence among populations. Conclusions: In white and Mexican‐origin men, waist circumference may be the preferred marker for identifying diabetic subjects on account of its simplicity; in women, waist‐to‐height ratio may be better. Differences in diabetes prevalence among these populations cannot be attributed to a single measure of obesity.     

The Association between Plasma Adiponectin and Insulin Sensitivity in Humans Depends on Obesity

Objective: In humans, low plasma adiponectin concentrations precede a decrease in insulin sensitivity and predict type 2 diabetes independently of obesity. However, it is possible that the contribution of adiponectin to insulin sensitivity is not equally strong over the whole range of obesity. Research Methods and Procedures: We investigated the cross‐sectional association between plasma adiponectin levels and insulin sensitivity in different ranges of body fat content [expressed as percentage of body fat (PFAT)] in a large cohort of normal glucose‐tolerant subjects (n = 900). All individuals underwent an oral glucose tolerance test (OGTT), and 299 subjects additionally a euglycemic hyperinsulinemic clamp. In longitudinal analyses, the association of adiponectin at baseline with change in insulin sensitivity was investigated in a subgroup of 108 subjects. Results: In cross‐sectional analyses, the association between plasma adiponectin and insulin sensitivity, adjusted for age, gender, and PFAT, depended on whether subjects were lean or obese [p for interaction adiponectin × PFAT = <0.001 (OGTT) and 0.002 (clamp)]. Stratified by quartiles of PFAT, adiponectin did not correlate significantly with insulin sensitivity in subjects in the lowest PFAT quartile (R² = 0.10, p = 0.13, OGTT; and R² = 0.10, p = 0.57, clamp), whereas the association in the upper PFAT quartile was rather strong (R² = 0.36, p < 0.0001, OGTT; and R² = 0.48, p = 0.003, clamp). In longitudinal analyses, plasma adiponectin at baseline preceded change in insulin sensitivity in obese (n = 54, p = 0.03) but not in lean (n = 54, p = 0.68) individuals. Discussion: These data suggest that adiponectin is especially critical in sustaining insulin sensitivity in obese subjects. Thus, interventions to reduce insulin resistance by increasing adiponectin concentrations may be effective particularly in obese, insulin‐resistant individuals.     

Waist circumference and BMI cut-off based on 10-year cardiovascular risk: evidence for "central pre-obesity"

Objective: The objective was to assess the waist circumference (WC) cut‐off point that best identifies a level of 10‐year cardiovascular disease (CVD) risk with optimal balance of sensitivity and specificity in Chinese subjects according to their predicted 10‐year CVD risk. Research Methods and Procedures: A community‐based cross‐sectional observational study involving 14,919 Hong Kong Chinese subjects. The 10‐year CVD risk based on various prediction models was calculated. The projected WC cut‐off points were then determined. Results: There were 4837 (32.4%) men and 10,082 (67.6%) women (mean age ± standard deviation, 47.3 ± 13.5 years; age range, 18 to 93 years; median age, 45.0 years). The mean optimal WC or BMI predicting a 15% to 30% 10‐year CVD risk were 83 to 88 cm and 25 kg/m² for men, and 76 cm and 23 kg/m² for women, respectively. With WC ≥90 cm in men and ≥80 cm in women, the likelihood ratio at various WC cut‐off points to develop a ≥20% 10‐year CVD risk is 1.5 to 2.0 in men and 3.0 in women. The likelihood ratio was 1.5 in men with WC at 84 cm and in women at 70 cm. Discussion: Our results agree with the present guidelines on the definition of general and central obesity in Asia‐Pacific regions. We propose the creation of an intermediate state of high WC, the “central pre‐obesity” for Chinese men with WC ≥84 to 90 cm (≥33 to 36 inches) and women with WC ≥74 to 80 cm (≥29 to 32 inches). People with central pre‐obesity, similar to those with overweight (BMI ≥23 to 25 kg/m²), already have an increased risk of co‐morbidities.     

Triglyceride‐to‐HDL‐cholesterol Ratio and Metabolic Syndrome as Contributors to Cardiovascular Risk in Overweight Patients

Insulin resistance increases cardiovascular risk of obese patients. Triglyceride to high‐density lipoprotein cholesterol ratio (TG/HDL) ≥3.0 (in mg/dl) is a marker of insulin resistance in overweight persons. We aimed at assessing cardiovascular risk profile in 301 overweight elderly Neapolitan outpatients, according to TG/HDL ratio and metabolic syndrome (MS), diagnosed by National Cholesterol Education Program (NCEP) and International Diabetes Federation (IDF) criteria. TG/HDL ratio was ≥3.0 in 97 patients (group A) and <3.0 in 204 (group B). Overall, 93–97% of group A patients and 38–51% of group B patients had MS, depending on the diagnostic criterion. Group A patients with MS had significantly higher waist‐to‐hip ratio, total and non‐HDL cholesterol than group B patients with MS. In group B, MS and non‐MS patients had similar waist‐to‐hip ratio, blood pressure, total and non‐HDL cholesterol. Ten year coronary risk, calculated by the Framingham equations (n = 243), was 10.3 ± 5% in group B, non‐MS patients; 13.1 ± 6% in group B, MS patients; 19.9 ± 8% in group A (F = 32.8; P < 0.001). At the multiple regression analysis, TG/HDL ratio was associated with coronary risk (r² = 0.227) more closely than gender, blood pressure, waist‐to‐hip ratio, non HDL cholesterol, and MS considered as a whole. A separate regression analysis showed that the logarithmically transformed TG/HDL ratio, an index of the HDL cholesterol esterification rate, is also associated with coronary risk (r² = 0.252). Thus, TG/HDL ratio could help to characterize high‐risk overweight patients deserving a special therapeutic effort. Cardiovascular risk profile of insulin‐sensitive patients, identified by lower values of this parameter, is only moderately affected by MS.     

Obesity in the Elderly and Its Relationship with Cardiovascular Risk Factors in Taiwan**

Objectives: The obese elderly are at increased risk of mortality, morbidity, and functional disability. In this study, we examined the prevalence of obesity and relationship between various anthropometric indices (AI) and cardiovascular disease (CVD) risk factors in the elderly. Research Methods and Procedures: A stratified multistage clustered sampling scheme was used in the Elderly Nutrition and Health Survey in Taiwan during 1999 to 2000. 2432 non‐institutionalized subjects (age, 72.8 ± 9.4 years; BMI, 23.6 ± 6.4 kg/m²) were recruited. The receiver operating characteristic analysis was used to compare predictive validity of CVD risk factors among various AI, including BMI, waist circumference (WC), and waist‐to‐hip ratio (WHR). Results: The prevalence of obesity was 29.0% in men and 36.8% in women by obesity criteria for Asians (BMI ≥ 25 kg/m²) and 13.3% in men and 21.0% in women by the Taiwanese definition (BMI ≥ 27 kg/m²). Odds ratios of acquiring various CVD risk factors increased significantly with increment of WC, WHR, and BMI. The areas under the curve predicting metabolic syndrome were all <0.8. The cut‐off values of WC corresponding to the highest sensitivity and the highest specificity in predicting various CVD risk factors were 86.2–88.0 cm in men and 82.0–84.0 cm in women, respectively. Discussion: Obesity was prevalent in the Taiwanese elderly. WC was related to CVD risk factors to a greater extent than BMI and WHR. However, none of them alone was a good screening tool for CVD risk factors. Therefore, how to apply AI prudently to screen elderly for CVD risk factors needs further research.     

Impact of Obesity and Body Fat Distribution on Cardiovascular Risk Factors in Hong Kong Chinese

Objective: Body fat distribution has been reported to differentially contribute to the development of cardiovascular risk. We report the relative associations between general and central obesity and risk factors in 2893 Chinese subjects recruited from the Hong Kong population. Research Methods and Procedures: Anthropometric parameters [waist circumference (WC) and BMI], surrogate measures of insulin resistance (fasting plasma glucose and insulin, oral glucose tolerance test, 2 hours glucose and insulin), fasting lipids (total, low‐density lipoprotein‐cholesterol, high‐density lipoprotein‐cholesterol, and triglycerides) and systolic and diastolic blood pressure were measured. General obesity was classified as BMI ≥25.0 kg/m² and central obesity as a WC ≥80 or ≥90 cm in women and men, respectively. Results: A total of 39.2% of the population was found to be obese. Obesity per se increased the levels of the risk factors, but central adiposity contributed to a greater extent to adverse high‐density lipoprotein‐cholesterol, triglyceride, and insulin resistance levels. There was a continuous relationship between increasing obesity, both general and central, and cardiovascular risk, with lowest risk associated with the lowest indices of obesity. In the 1759 nonobese subjects divided into quartiles of BMI or WC, the levels of the cardiovascular risk factors still significantly increased with increasing quartiles of adiposity. Discussion: Central adiposity appears to contribute to a greater extent than general adiposity to the development of cardiovascular risk in this population. The relationship between obesity parameters and risk is a continuum, with risk factors significantly increasing even at levels usually considered nonobese. These observations support the proposed redefinition of overweight and obesity in Asian populations using lower cut‐off points.     

BMI vs. waist circumference for identifying vascular risk

Objective: Current guidelines recommend measurement of both BMI and waist circumference (WC) in individuals with BMI between 25.0 and 34.9 kg/m². We investigated the relative contributions of BMI and WC toward identifying risk of adverse vascular events in a community‐based sample. Methods and Procedures: We evaluated Framingham Study participants (n = 4,195 person‐examinations, 53% women) using pooled logistic regression to assess the incremental prognostic utility of WC in predicting risk of a first cardiovascular disease (CVD) event in the three BMI categories (normal, <25 kg/m²; overweight, 25 to <30 kg/m²; obese, ≥ 30 kg/m²) and to assess the incremental prognostic utility of BMI and WC separately for predicting risk of a first cardiovascular event. Results: On follow‐up (16 years), 430 participants (158 women) had experienced a first CVD event. In overweight women, but not in overweight men, larger WC was found to be an independent predictor of CVD incidence, longitudinally (in women, multivariable‐adjusted odds ratio (OR) per s.d. increment in WC 1.86, 95% confidence interval (CI) = 1.03–3.36, P = 0.04; in men adjusted OR per s.d. increment in WC 0.91, 95% CI 0.60–1.38, P = 0.66). In obese individuals and in those with normal BMI, WC was not associated independently with incident CVD. When BMI and WC were analyzed separately for predicting risk of a first cardiovascular event, the c statistics associated with the multivariable CVD models incorporating BMI vs. WC were nearly identical in men and women. Discussion: Knowledge of WC aids identification of vascular risk among overweight women. Among normal weight or obese women and men (regardless of BMI category) WC did not appear to substantially add to prediction of risk of vascular events.     

Relationships between direct and indirect measures of central and total adiposity in children: What are we measuring?

Objective: The relationship between central and total fat measured by anthropometry, dual energy X‐ray absorptiometry, and magnetic resonance imaging (MRI) with each other and systolic blood pressure (SBP) was examined. Design and Methods: Participants of the Avon Longitudinal Study of Parents and Children were examined at ages 9, 11, 13, and 15 years (n = 3,796‐6,567). MRI was available on a subset of children at 11 (n = 156) and 13 (n = 95). Results: Body mass index (BMI) and waist circumference (WC) were highly correlated (r = 0.84‐0.91, across ages), and total body fat mass (TBFM) and trunk fat mass (TFM) were very strongly correlated (r ≥ 0.98). Among boys, BMI vs. WC explained a similar degree of variation in TBFM and TFM (41‐71% vs. 43‐76%, across age and overweight groups); in girls, BMI accounted for 62‐73% variance and WC 47‐69%. Adiposity measures were generally similarly correlated with SBP within age groups. Further, the relationship between intra‐abdominal adipose tissue (IAAT) volume and adiposity measures did not vary greatly at 11 (0.65‐0.67) and 13 (0.64‐0.67). Conclusions: BMI and WC contain a large amount of overlapping information as evidenced by their high correlation and similarly sized associations with fat mass, SBP, and IAAT. This suggests that WC may be an inadequate marker of central adiposity during childhood.     

Association of Long‐term Change in Waist Circumference With Insulin Resistance

Recent studies have shown that fat accumulation is associated with insulin resistance; however, the risks associated with long‐term changes and fluctuations in central fatness are less clear. This study examined the longitudinal relationship between waist circumference (WC) and insulin resistance using three dimensions of WC: baseline WC, slope of linear changes in WC, and fluctuation of WC around the slope during 20 years of follow‐up. Anthropometry, insulin resistance (homeostasis model assessment (HOMA_IR)), and lifestyle factors were obtained in a population‐based, prospective observational study (Coronary Artery Risk Development in Young Adults (CARDIA)) during 1985–2006, excluding participants who had been diagnosed with diabetes at any examination. After adjusting for socio‐demographic and lifestyle factors, the evolution of HOMA_IR from CARDIA year 15 to 20 was 6.9% higher per standard deviation of year 0 WC (P trend <0.0001) and 6.3% higher per standard deviation increase in the change in WC over the long term (P trend <0.0001). However, WC fluctuations around the linear change were not associated with insulin resistance or its evolution. The level of HOMA_IR increased substantially with steeper linear WC slope among initially thinner participants at baseline, whereas this association tended to be weaker in those with higher initial WC (P interaction <0.0001). We conclude that year 0 WC and long‐term increment in WC are associated with worsening insulin resistance. However, the association of HOMA_IR with slope of WC change may vary across the range of initial WC.     

Polymorphisms in the SCD1 gene: associations with body fat distribution and insulin sensitivity

Objective: Obesity and insulin resistance are major risk factors for metabolic diseases and are influenced by lifestyle and genetics. The lipogenic enzyme, stearoyl‐coenzyme A‐desaturase (SCD), is related to obesity. Further, SCD1‐deficent mice are protected against obesity and insulin resistance. We hypothesized that genetic polymorphisms in the SCD1 gene would be associated with obesity, insulin sensitivity, and estimated SCD activity in humans. Research Methods and Procedures: The study population was 1143 elderly Swedish men taking part of a population‐based cohort study, the Uppsala Longitudinal Study of Adult Men. Associations between single nucleotide polymorphisms and obesity (waist circumference and BMI), insulin sensitivity (assessed by hyperinsulinemic euglycemic clamp), and estimated SCD activity (fatty acid ratios) were analyzed using linear regression analysis. Results: Subjects homozygous for the rare alleles of rs10883463, rs7849, rs2167444, and rs508384 had decreased BMI and waist circumference and improved insulin sensitivity. The rare allele of rs7849 demonstrated the strongest effect on both insulin sensitivity [regression coefficient (β) = 1.19, p = 0.007] and waist circumference (β = ?4.4, p = 0.028), corresponding to 23% higher insulin sensitivity and 4 cm less waist circumference. Conclusion: This study indicates that genetic variations in the SCD1 gene are associated with body fat distribution and insulin sensitivity, results that accord well with animal data. These results need confirmation in other populations with a larger sample size.