The Effect of Weight Loss on Sleep‐disordered Breathing in Obese Teenagers

The objective of this study was to assess the effect of weight loss on sleep‐disordered breathing (SDB) in obese teenagers attending a residential treatment center. We also assessed whether the presence of SDB at the start of the weight management therapy was correlated with the amount of weight loss achieved. Obese teenagers were recruited and underwent anthropometry and sleep screening. Subjects with SDB (apnea hypopnea index (AHI) ≥ 2) received a follow‐up screening after weight loss therapy. Sixty‐one obese subjects were included (age = 14.8 ± 2.3; BMI z score = 2.7 ± 0.4). Thirty‐one subjects were diagnosed with SDB with 38% continuing to have residual SDB after a median weight loss of 24.0 kg. Subjects with SDB had a higher median relative decrease in BMI z score compared to subjects without SDB which was 30.5, 33.6, and 50.4% in the group with AHI of the baseline screening study < 2, 2 ≤ AHI < 5, and AHI ≥ 5, respectively (P = 0.02). AHI of the baseline screening study correlated significantly with the relative decrease in BMI z score (partial r = 0.37; P = 0.003), controlling for gender, age, initial BMI z score, and time between both studies. In conclusion, weight loss was successful in treating SDB in obese teenagers. In addition, there was a positive association between the severity of SDB at the start of the treatment and the amount of weight loss achieved. These findings are in favor of considering weight loss as a first‐line treatment for SDB in obese children and adolescents.     

A comparison of adiposity measures as predictors of all-cause mortality: the Melbourne Collaborative Cohort Study

Objective: Our goal was to examine five different measures of adiposity as predictors of all‐cause mortality. Research Methods and Procedures: Subjects were 16,969 men and 24,344 women enrolled between 1990 and 1994 in the Melbourne Collaborative Cohort Study (27 to 75 years of age). There were 2822 deaths over a median follow‐up period of 11 years. BMI, waist circumference, and waist‐to‐hip ratio were obtained from direct anthropometric measurements. Fat mass and percentage fat were estimated by bioelectric impedance analysis. Results: Comparing the top quintile with the second quintile, for men there was an increased risk of between 20% and 30% for all‐cause mortality associated with each of the anthropometric measures. For women, there was an increased risk of 30% (95% confidence interval for hazard ratio, 1.1–1.6) observed for waist circumference and 50% (1.2–1.8) for waist‐to‐hip ratio, but little or no increased risk for BMI, fat mass, and percentage fat. Waist‐to‐hip ratio was positively and monotonically associated with all‐cause mortality for both men and women. There was a linear association between waist circumference and all‐cause mortality for men, whereas a U‐shaped association was observed for women. Discussion: Measures of central adiposity were better predictors of mortality in women in the Melbourne Collaborative Cohort Study compared with measures of overall adiposity. We recommend measuring waist and hip circumferences in population studies investigating the risk of all‐cause mortality associated with obesity. The use of additional measures such as bioelectric impedance is not justified for this outcome.     

Defining Health‐Related Obesity in Prepubertal Children

Objective: The purpose of this study was to develop percentage of fat and waist circumference cut‐points in prepubertal children with the intention of defining obesity associated with cardiovascular disease (CVD) risk. Research Methods and Procedures: A cross‐sectional analysis of 87 prepubertal children aged 4 to 11 years was used. Percentage of body fat was determined by DXA. Waist circumference was measured to the nearest millimeter. Receiver Operating Characteristic analyses of percentage of fat and waist circumference were used to develop cut‐points for individuals with adverse levels of CVD risk factors. Results: The risk factors selected for analyses (i.e., fasting insulin, high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol, triglycerides, and total cholesterol/high‐density lipoprotein cholesterol) were significantly related to percentage of body fat and waist circumference. Likelihood ratios were used to identify percentage of fat and waist circumference cut‐points associated with adverse cardiovascular risk profiles. Two cut‐points, an upper cut‐point of 33% body fat and a lower cut‐point of 20% body fat, were derived. Waist circumference cut‐points indicative of adverse and normal risk‐factor profiles were 71 cm and 61 cm, respectively. Discussion: The data indicate that children with ≥33% body fat and children with a waist circumference ≥71 cm were more likely to possess an adverse CVD risk‐factor profile than a normal risk‐factor profile. The likelihood of children with <20% body fat or a waist circumference <61 cm possessing an adverse CVD risk‐factor profile as opposed to a normal risk‐factor profile was small. The cut‐points describe an adequate health‐related definition of childhood obesity.     

Anthropometric Indices and the Incidence of Hypertension: A Comparative Analysis

Objective: To investigate the association between several anthropometric measurements of obesity with the incidence of hypertension. Research Methods and Procedures: Participants were 592 individuals free of hypertension, selected at random from the community. In the baseline evaluation, they were submitted to completed measures of demographics, anthropometrics, blood pressure, and other risk factors for hypertension. Incident hypertension was defined by blood pressure equal or higher than 140/90 mm Hg or use of blood pressure‐lowering drugs. Results: During a mean follow‐up time of 5.6 ± 1.1 years, 127 developed hypertension. The hazard ratios for the development of hypertension, adjusted for age, baseline blood pressure, gender, and alcohol consumption, were 1.042 (p = 0.091) for BMI, 1.023 (p = 0.028) for waist circumference, 1.042 (p = 0.013) for waist‐to‐height ratio, 1.061 (p = 0.014) for waist‐to‐height² index, 1.079 (p = 0.022) for waist‐to‐height³ index, and 1.033 (p = 0.006) for the waist‐to‐hip ratio. Discussion: The correction of the circumference of waist for stature or hip circumference improves its performance in the prediction of the incidence of hypertension.     

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.     

Waist Circumference,BMI, Smoking,and Mortality in Middle‐Aged Men and Women

Objective: Measurement of waist circumference alone as a proxy of abdominal fat mass has been suggested as a simple clinical alternative to BMI for detecting adults with possible health risks due to obesity. Research Methods and Procedures: From 1993 to 1997, 27, 178 men and 29, 875 women, born in Denmark, 50 to 64 years of age, were recruited in the Danish prospective study Diet, Cancer and Health. By the end of the year 2000, 1465 deaths had occurred. We evaluated the relationship between waist circumference and BMI (simultaneously included in the model) and all‐cause mortality. We used Cox regression models to estimate the mortality‐rate ratios and to consider possible confounding from smoking. Results: Waist circumference among both men and women showed a strong dose‐response type of relationship with mortality when adjusted for BMI, whereas the low range of BMI was inversely associated with mortality when adjusted for waist circumference. A 10% larger waist circumference corresponded to a 1.48 (95% confidence interval: 1.36 to 1.61) times higher mortality over the whole range of waist circumference. The associations were independent of age and time since baseline examination. Restriction to never smokers showed a similar pattern, but a weakening of the associations. Discussion: Despite the high correlation between waist circumference and BMI, the combination may be very relevant in clinical practice because waist circumference for given BMI was a strong predictor of all‐cause mortality. The inverse association between BMI and mortality for given waist circumference was diminished in never smokers, particularly for high values of BMI.     

Associations of Fat Distribution and Obesity with Hypertension in a Bi‐ethnic Population: The ARIC Study

Objective: To examine associations of hypertension with obesity and fat distribution among African American and white men and women. Research Methods and Procedures: The analysis sample included 15,063 African American and white men and women between the ages of 45 and 64 years who were participants in the 1987 through 1989 examination of the Atherosclerosis Risk in Communities Study (ARIC). Odds ratios and adjusted prevalences of hypertension were calculated across sexspecific quintiles of body mass index (BMI), waist‐to‐hip ratio (WHR), waist circumference, and waist‐to‐height ratio (waist/height) and adjusted for age, research center, smoking, education, physical activity, alcohol consumption, hormone replacement therapy, and menopausal status. Results: The prevalence of hypertension was higher among African Americans than whites. In the lowest quintile of BMI, 41% of African American women and 43% of African American men had hypertension compared with 14% of white women and 19% of white men. Elevated BMI, WHR, waist circumference, and waist/height were associated with increased odds of hypertension in African American and white men and women. In women, but not in men, there were significant interactions between ethnicity and the anthropometric variables studied here. The direction of the interaction indicated larger odds ratios for hypertension with increasing levels of anthropometric indices in white compared with African American women. Discussion: Obesity and abdominal fat preponderance were associated with increased prevalence of hypertension in African American and white men and women. Associations were similar among African American and white men, but obesity and fat patterning were less strongly associated with hypertension in African American than in white women.     

Associations of leukocyte telomere length with body anthropometric indices and weight change in chinese women

Objective: This study evaluated associations of telomere length with various anthropometric indices of general and abdominal obesity, as well as weight change. Design and Methods: The study included 2,912 Chinese women aged 40‐70 years. Monochrome multiplex quantitative polymerase chain reaction was applied to measure relative telomere length. Results: Telomere length was inversely associated with body mass index (BMI), waist circumference, waist‐to‐height ratio, weight, and hip circumference (P_trend = 0.005, 0.004, 0.004, 0.010, and 0.026, respectively), but not waist‐to‐hip ratio (P_trend = 0.116) or height (P_trend = 0.675). Weight change since age 50 was further evaluated among women over age 55. Women who maintained their weight within ±5% since age 50, particularly within a normal range (BMI = 18.5‐24.9 kg/m²), or reduced their weight from overweight (BMI = 25‐29.9 kg/m²) or obesity (BMI ≥30 kg/m²) to normal range, had a longer mean of current telomere length than women who gained weight since age 50 (P_trend = 0.025), particularly those who stayed in obesity or gained weight from normal range or overweight to obesity (P = 0.023). Conclusion: Our findings show that telomere shortening is associated with obesity and that maintaining body weight within a normal range helps maintain telomere length.     

The Severity of Nocturnal Hypoxia but Not Abdominal Adiposity Is Associated with Insulin Resistance in Non-Obese Men with Sleep Apnea

Background

Beyond obesity, sleep apnea syndrome is frequently associated with excess abdominal adiposity that could contribute to the deteriorated cardiometabolic risk profile of apneic patients.

Methods

The present study addressed the respective contribution of the severity of sleep apnea syndrome and excess abdominal adiposity to the cardiometabolic risk profile of 38 non obese men with polysomnography-diagnosed sleep apnea syndrome (apnea-hypopnea index >15 events/hour). These otherwise healthy men performed a 75g-oral glucose tolerance test (OGTT) with plasma lipid/inflammatory and redox profiles. Twenty-one apneic men with high-waist circumference (>94 cm) were compared to 17 apneic men with low-waist circumference.

Results

Apneic men with high-waist circumference had higher AUC glucose and AUC insulin than apneic men with low-waist circumference. Accordingly, apneic men with high-waist circumference had higher hepatic insulin resistance as reflected by higher HOMA-resistance index, and lower global insulin sensitivity as reflected by lower insulin sensitivity index of Matsuda (derived from OGTT). The sleep structure and the apnea-hypopnea index were not different between the two groups. However, apneic men with high-waist circumference presented with lower mean nocturnal oxyhemoglobin (SpO₂). In the 38 men, waist circumference and mean nocturnal SpO₂ were inversely correlated (r = −0.43, p = 0.011) and were both associated with plasma glucose/insulin homeostasis indices: the higher the waist circumference, the lower the mean nocturnal SpO₂, the lower the insulin-sensitivity. Finally, in multivariable regression model, mean nocturnal SpO₂ and not waist circumference was associated with insulin-resistance.

Conclusion

Thus, excess abdominal adiposity in non obese apneic men was associated with a deteriorated insulin-sensitivity that could be driven by a more severe nocturnal hypoxemia.     

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.     

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.     

Waist-to-height ratio is an accurate and easier index for evaluating obesity in children and adolescents

Objectives: The present study aims to evaluate the accuracy of the index of waist‐to‐height ratio (WHTR), and proposed the optimal thresholds of WHTR in the definition of childhood overweight and obesity in a bi‐ethnic Chinese school‐aged population. Research Methods and Procedures: Overweight and obese were identified by BMI for age and gender in a random sample including 2055 Han and 2132 Uygur ethnic school‐aged children (8 to 18 years old). WHTR was calculated by waist circumference divided by height on the basis of standard anthropometric measurements. Receiver operating characteristic (ROC) curve analyses were performed to assess the accuracy of WHTR as a diagnostic test for childhood overweight and obesity, compared with waist circumference. The optimal thresholds of WHTR for defining overweight and obesity were recommended respectively by gender. The correlation between WHTR and age was analyzed and compared with BMI. Results: A‐values (area under curve) of WHTR for diagnosing overweight and obesity were both over 0.90 in both genders and better than those of waist circumference. A threshold of 0.445 was identified for overweight in both genders, with the sensitivity and specificity >0.80. The thresholds for defining obesity was 0.485 in boys and 0.475 in girls, both having the sensitivity and specificity >0.90. WHTR showed less association with age than BMI. Conclusions: WHTR is a simple, easy, accurate, and non‐age‐dependent index with high applicability to screening overweight and obesity in children and adolescents. The use of WHTR in the general childhood population has been justified by this study.     

Obesity in 70‐Year‐Old Subjects as a Risk Factor for 15‐Year Coronary Heart Disease Incidence

Objective: To investigate the role of obesity in general and waist circumference (WC) and BMI in particular as risk factors for 15‐year incidence of coronary heart disease (CHD) in the elderly. Research Methods and Procedures: This prospective study was based on 1597 (737 males and 860 females) 70‐year‐olds free from CHD and participants of three birth cohorts examined in 1971 to 1972 (Cohort I), 1976 to 1977 (Cohort II), and 1981 to 1982 (Cohort III) at Göteborg, Sweden. Fifteen‐year incidence of CHD (fatal and nonfatal) was ascertained from follow‐up examinations and registers. Relative risk (RR) for first ever CHD in reference to the lowest quartiles of WC and BMI was calculated from Cox regression. Results: In males, RRs for CHD in the highest WC and BMI quartiles were 1.36 [95% confidence interval (CI) 1.00 to 1.85] and 1.42 (95% CI 1.04 to 1.92), respectively, after adjustment for cohorts, smoking habits, diabetes, systolic blood pressure, and total cholesterol. In men, the risk associated with WC was independent of BMI. Neither WC nor BMI was related to CHD risk in females. After exclusion of first 5‐year all‐cause deaths, the adjusted RRs in the highest WC and BMI quartiles in males were 1.47 (95% CI 1.06 to 2.04) and 1.42 (1.04 to 1.92), respectively. In females, a significantly higher RR of 1.41 (95% CI 1.02 to 1.94) was observed in the second BMI quartile only after such exclusions. Discussion: WC, an indicator of both central and general obesity, appears to be a stronger predictor of CHD than BMI in elderly males, but in females, obesity was not a risk factor for CHD.     

Effects of Obesity and Body Fat Distribution on Lipids and Lipoproteins in Nondiabetic American Indians: The Strong Heart Study

Objectives: To examine the relationship between obesity and lipoprotein profiles and compare the effects of total obesity and central adiposity on lipids/lipoproteins in American Indians. Research Methods and Procedures: Participants were 773 nondiabetic American Indian women and 739 men aged 45 to 74 years participating in the Strong Heart Study. Total obesity was estimated using body mass index (BMI). Central obesity was measured as waist circumference. Lipoprotein measures included triglycerides, high‐density lipoprotei in (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, apolipoprotein AI (apoAI), and apolipoprotein B (apoB). Partial and canonical correlation analyses were used to examine the associations between obesity and lipids/lipoproteins. Results: Women were more obese than men in Arizona (median BMI 32.1 vs. 29.2 kg/m²) and South Dakota and North Dakota (28.3 vs. 28.0 kg/m²), but there was no sex difference in waist circumference. Men had higher apoB and lower apoAI levels than did women. In women, when adjusted for center, gender, and age, BMI was significantly related to HDL cholesterol (r = ?0.24, p < 0.001). There was a significant but weak relation with apoAI (r = ?0.14 p < 0.001). Waist circumference was positively related to triglycerides (r = 0.14 p < 0.001) and negatively related to HDL cholesterol (r = ?0.23, p < 0.001) and apoAI (r = ?0.13, p < 0.001). In men, BMI was positively correlated with triglycerides (r = 0.30, p < 0.001) and negatively correlated with HDL cholesterol (r = ?0.35, p < 0.001) and apoAI (r = ?0.23, p < 0.001). Triglycerides increased with waist circumference (r = 0.30, p < 0.001) and HDL cholesterol decreased with waist circumference (r = ?0.36 p < 0.001). In both women and men there was an inverted U‐shaped relationship between obesity and waist with LDL cholesterol and apoB. In canonical correlation analysis, waist circumference received a greater weight (0.86) than did BMI (0.17) in women. However, the canonical weights were similar for waist (0.46) and BMI (0.56) in men. Only HDL cholesterol (?1.02) carried greater weight in women, whereas in men, triglycerides (0.50), and HDL cholesterol (?0.64) carried a large amount of weight. All the correlation coefficients between BMI, waist circumference, and the first canonical variable of lipids/lipoproteins or between the individual lipid/lipoprotein variables and the first canonical variable of obesity were smaller in women than in men. Triglycerides and HDL cholesterol showed clinically meaningful changes with BMI and waist circumference in men. All lipid/lipoprotein changes in women in relation to BMI and waist circumference were minimal. Discussion: The main lipoprotein abnormality related to obesity in American Indians was decreased HDL cholesterol, especially in men. Central adiposity was more associated with abnormal lipid/lipoprotein profiles than general obesity in women; both were equally important in men.     

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

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

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.     

Six‐Month Treatment of Obesity with Sibutramine 15 mg; A Double‐Blind,Placebo‐Controlled Monocenter Clinical Trial in a Hispanic Population

Objective: To evaluate the safety and efficacy of sibutramine 15 mg by mouth once per day in obese patients over a period of 6 months. Research Methods and Procedures: A monocenter, double‐blind, placebo controlled, parallel, prospective clinical trial was carried out. Sixty‐nine male and female obese patients (body mass index [BMI] > 30 kg/m²) aged 16 to 65 years entered the trial. Results: 22 of 35 patients in the sibutramine group and 9 of 34 patients in the placebo group completed the trial. The high dropout rate in the sibutramine group was due to adverse events in 3 cases, lack of efficacy (as judged by patients) in 7, loss to follow‐up in 2, and an orthopedic device being worn in 1; in the placebo group the dropouts were ascribed to lack of efficacy (as judged by patients) in 17 cases and to loss to follow‐up in 8 cases. Using the method of last observation carried forward, the weight loss in the sibutramine group was 10.27 kg (95% confidence intervals [95% CI] 7.66; 13.07) and 1.26 kg (95% CI 0.3; 2.23) in the placebo group. The BMI loss was 4.17 kg/m² (95% CI 3.11; 5.22) in the sibutramine group and 0.53 kg/m² (95% CI 0.13; 0.92) in the placebo group. The waist circumference reduction was 12.51 cm (95% CI 9.25; 15.77) in the sibutramine group and 3.26 cm (95% CI 1.38; 5.14) in the control group (p < 0.05 by paired Student's t test for all the intragroup comparisons). Twenty‐three sibutramine patients had 34 adverse events, the most frequent adverse events in the sibutramine group were upper respiratory tract infections (n = 6) and constipation (n = 6); 16 placebo patients had 21 adverse events. Three sibutramine patients withdrew their informed consent when they had adverse events. Discussion: The results show that sibutramine induces significant loss of body weight and waist circumference. Cardiovascular function was not significantly affected by sibutramine. Sibutramine was well tolerated by most of the patients.     

Predicting Incident Diabetes in Jamaica: The Role of Anthropometry

Objective: To evaluate the performance of the body mass index (BMI), waist circumference, waist‐to‐hip ratio (WHR), and waist‐to‐height ratio (WHTR) in predicting incident diabetes in Jamaica. Research Methods and Procedures: A cohort of 728 nondiabetic adults (290 men and 438 women), ages 25 to 74 years and residents of Spanish Town, Jamaica, were followed for a mean of 4 years. Participants had fasting and 2‐hour postchallenge glucose concentrations measured at baseline and follow‐up. Results: There were 51 cases of incident diabetes (17 men and 34 women). All indices were independent predictors of diabetes, and none was clearly superior. The area under the receiver operating characteristics curves (95% confidence interval) for BMI was 0.74 (0.59 to 0.88) for men and 0.62 (0.51 to 0.72) for women. For waist circumference, these values were 0.78 (0.65 to 0.91) in men and 0.61 (0.50 to 0.71) in women. Similar results were obtained for WHR and WHTR. “Optimal” cut‐off points for BMI were 24.8 kg/m² (men) and 29.3 kg/m² (women). For waist circumference, these were 88 cm and 84.5 cm for men and women, respectively. Corresponding values for WHR were 0.87 and 0.80 and for WHTR were 0.51 and 0.54, respectively. Discussion: Cut‐off points for waist circumference and WHR were similar to those proposed in developed countries for women but lower in men. Waist circumference could be useful in health promotion as an alternative to BMI.     

Comparison of Overall Obesity and Body Fat Distribution in Predicting Risk of Mortality

Results of studies comparing overall obesity and abdominal adiposity or body fat distribution with risk of mortality have varied considerably. We compared the relative importance and joint association of overall obesity and body fat distribution in predicting risk of mortality. Participants included 5,799 men and 6,429 women aged 30–102 years enrolled in the third National Health and Nutrition Examination Survey who completed a baseline health examination during 1988–1994. During a 12‐year follow‐up (102,172 person‐years), 1,188 men and 925 women died. In multivariable‐adjusted analyses, waist‐to‐thigh ratio (WTR) in both sexes (P_trend <0.01 for both) and waist‐to‐hip ratio (WHR) in women (P_trend 0.001) were positively associated with mortality in middle‐aged adults (30–64 years), while BMI and waist circumference (WC) exhibited U‐ or J‐shaped associations. Risk of mortality increased with a higher WHR and WTR among normal weight (BMI 18.5–24.9 kg/m²) and obese (BMI ≥30.0 kg/m²) adults. In older adults (65–102 years), a higher BMI in both sexes (P_trend <0.05) and WC in men (P_trend 0.001) were associated with increased survival, while remaining measures of body fat distribution exhibited either no association or an inverse relation with mortality. In conclusion, ratio measures of body fat distribution are strongly and positively associated with mortality and offer additional prognostic information beyond BMI and WC in middle‐aged adults. A higher BMI in both sexes and WC in men were associated with increased survival in older adults, while a higher WHR or WTR either decreased or did not influence risk of death.     

Sensitivity and Specificity of Anthropometrics for the Prediction of Diabetes in a Biracial Cohort

Objective: To evaluate the ability of body mass index, waist circumference, waist‐to‐hip ratio, and combinations of these variables to discriminate individuals who will develop diabetes in adulthood. Research Methods and Procedures: Data were from 45‐ to 64‐year‐old men and women who were members of the Atherosclerosis Risk in Communities cohort. The analysis sample consisted of 12,814 African American and white participants who were free of diabetes at baseline. Body mass index, waist circumference, waist‐to‐hip ratio, and diabetes incidence (defined as one glucose measure ≥126 mg/dL after fasting for at least 8 hours, one nonfasting glucose measure ≥200 mg/dL, and self‐report of diabetes or report of taking medication for diabetes). Results: 1515 new cases of diabetes were identified over the 9‐year follow‐up. Areas under receiver operating characteristic curves ranged from 0.66 to 0.73 for single measures. The curves were smooth, with no indication of a threshold. Waist tended to have the highest receiver operating characteristic statistic in all groups, but differences were small. Discussion: The three anthropometric indices tested were approximately equivalent in their ability to predict diabetes. Sensitivity and specificities differed among ethnic and gender groups.