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.     

Central obesity as a risk factor for prostatic hyperplasia

Objective: Obesity‐related metabolic diseases may influence prostatic hyperplasia. This study examined the impact of obesity on prostate volume in men without overt obesity‐related metabolic diseases. Research Methods and Procedures: We recruited 146 men over the age of 40 years who did not have overt obesity‐related diseases, such as diabetes, impaired fasting glucose, hypertension, or dyslipidemia. Transrectal ultrasonography was performed on all subjects. The subjects were divided into three groups according to their BMI: normal (18.5 to 22.9 kg/m²), overweight (23 to 24.9 kg/m²), and obese (≥25 kg/m²), and two groups according to their waist circumference: normal waist (≤90 cm) and central obesity (>90 cm). The classification of the subgroups was based on the Asia‐Pacific criteria of obesity. We compared the prostate volume among subgroups and assessed factors related to prostatic hyperplasia. Results: Mean prostate volume was 18.8 ± 5.0, 21.8 ± 7.2, and 21.8 ± 5.6 mL in the normal, overweight, and obese groups, respectively, and was 20.0 ± 5.9 and 23.7 ± 5.3 mL in the normal waist and central obesity group, respectively. Prostate volume was significantly greater in the obese group than in the normal group (P = 0.03) and in the central obesity group compared with the normal waist group (P = 0.002). Prostate volume was positively correlated with BMI and waist circumference after adjustment for age. After adjusting for confounding factors, central obesity was an independent factor affecting prostatic hyperplasia, which was defined as a prostate volume >20 mL (odds ratio = 3.37, p = 0.037). Relative to men with both low BMI (18.5 to 22.9 kg/m²) and normal waist circumference, those with high BMI (≥25 kg/m²) and central obesity were at significantly increased risk of prostatic hyperplasia (odds ratio = 4.88, p = 0.008). However, those with high BMI (≥25 kg/m²) and normal waist circumference were not at significantly increased risk. Discussion: Prostate volume was greater in the obese and central obesity groups than in the normal group after patients with overt obesity‐related metabolic diseases were excluded. Although both BMI and waist circumference were positively correlated with prostate volume, central obesity was the only independent factor affecting prostate hyperplasia. We suggest that central obesity is an important risk factor for prostatic hyperplasia.     

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.     

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.     

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.     

Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino,African‐American,and White Women

Objective: To compare ethnic differences in visceral adipose tissue (VAT), assessed by computed tomography, and type 2 diabetes risk among 55‐ to 80‐year‐old Filipino, African‐American, and white women without known cardiovascular disease. Research Methods and Procedures: Subjects were participants in the Rancho Bernardo Study (n = 196), the Filipino Women's Health Study (n = 181), and the Health Assessment Study of African‐American Women (n = 193). Glucose and anthropometric measurements were assessed between 1995 and 2002. Results: African‐American women had significantly higher age‐adjusted BMI (29.7 kg/m²) and waist girth (88.1 cm) compared with Filipino (BMI, 25.5 kg/m²; waist girth, 81.9 cm) or white (BMI: 26.0 kg/m²; waist girth: 80.7 cm) women. However, VAT was significantly higher among Filipino (69.1 cm³) compared with white (62.3 cm³; p = 0.037) or African‐American (57.5 cm³, p < 0.001) women. VAT correlated better with BMI (r = 0.69) and waist (r = 0.77) in whites, compared with Filipino (r = 0.42; r = 0.59) or African‐American (r = 0.50; r = 0.56) women. Age‐adjusted type 2 diabetes prevalence was significantly higher in Filipinas (32.1%) than in white (5.8%) or African‐American (12.1%) women. Filipinas had higher type 2 diabetes risk compared with African Americans [adjusted odds ratio, 2.30; 95% confidence interval (CI), 1.09 to 4.86] or whites (adjusted odds ratio, 7.51; 95% CI, 2.51 to 22.5) after adjusting for age, VAT, exercise, education, and alcohol intake. Discussion: VAT was highest among Filipinas despite similar BMI and waist circumference as whites. BMI and waist circumference were weaker estimates of VAT in Filipino and African‐American women than in whites. Type 2 diabetes prevalence was highest among Filipino women at every level of VAT, but VAT did not explain their elevated type 2 diabetes risk.     

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.     

Obesity in South Africa: The South African Demographic and Health Survey

Objectives: To ascertain the anthropometric profile and determinants of obesity in South Africans who participated in the Demographic and Health Survey in 1998. Research Methods and Procedures: A sample of 13,089 men and women (age, ≥15 years) were randomly selected and then stratified by province and urban and nonurban areas. Height, weight, mid-upper arm circumference, and waist and hip circumference were measured. Body mass index (BMI) was used as an indicator of obesity, and the waist/hip ratio (WHR) was used as an indicator of abdominal obesity. Multivariate regression identified sociodemographic predictors of BMI and waist circumference in the data. Results: Mean BMI values for men and women were 22.9 kg/m² and 27.1 kg/m², respectively. For men, 29.2% were overweight or obese (≥25 kg/m²) and 9.2% had abdominal obesity (WHR ≥1.0), whereas 56.6% of women were overweight or obese and 42% had abdominal obesity (WHR >0.85). Underweight (BMI <18.5 kg/m²) was found in 12.2% of men and 5.6% of women. For men, 19% of the variation of BMI and 34% of the variation in waist circumference could be explained by age, level of education, population group, and area of residence. For women, these variables explained 16% of the variation of BMI and 24% of the variation in waist circumference. Obesity increased with age, and higher levels of obesity were found in urban African women. Discussion: Overnutrition is prevalent among adult South Africans, particularly women. Determinants of overnutrition include age, level of education, ethnicity, and area of residence.     

Hypocretin Deficiency in Narcoleptic Humans Is Associated with Abdominal Obesity

Objective: To determine the prevalence of obesity among patients with narcolepsy, to estimate associated long‐term health risks on the basis of waist circumference, and to distinguish the impact of hypocretin deficiency from that of increased daytime sleepiness (i.e., reduced physical activity) on these anthropometric measures. Research Methods and Procedures: A cross‐sectional, case‐control study was conducted. Patients with narcolepsy (n = 138) or idiopathic hypersomnia (IH) (n = 33) were included. Age‐matched, healthy members of the Dutch population (Monitoring Project on Risk Factors for Chronic Diseases and Doetinchem Project; n = 10, 526) were used as controls. BMI and waist circumference were determined. Results: Obesity (BMI ≥ 30 kg/m²) and overweight (BMI 25 to 30 kg/m²) occurred more often among narcolepsy patients [prevalence: 33% (narcoleptics) vs. 12.5% (controls) and 43% (narcoleptics) vs. 36% (controls), respectively; both p < 0.05]. Narcoleptics had a larger waist circumference (mean difference 5 ± 1.4 cm, p < 0.001). The BMI of patients with IH was significantly lower than that of narcolepsy patients (25.6 ± 3.6 vs. 28.5 ± 5.4 kg/m²; p = 0.004). Discussion: Overweight and obesity occur frequently in patients with narcolepsy. Moreover, these patients have an increased waist circumference, indicating excess fat storage in abdominal depots. The fact that patients with IH had a lower BMI than narcoleptics supports the notion that excessive daytime sleepiness (i.e., inactivity) cannot account for excess body fat in narcoleptic patients.     

Association of Common Polymorphisms in the Fractalkine Receptor (CX3CR1) With Obesity

The inflammatory component in obesity is now well established. The CX3CR1 gene encodes the fractalkine (CX3CL1) receptor and has two coding single‐nucleotide polymorphisms, V249I and T280M, linked to a lower risk of other inflammatory diseases such as coronary artery disease (CAD) and asthma. To determine whether CX3CR1 is associated with obesity, we genotyped the V249I and T280M polymorphisms of the CX3CR1 gene in subjects with a BMI ≥30 kg/m² and nonobese controls with a BMI <30 kg/m². Binary logistic regression analyses revealed that the 280MM genotype was associated with obesity (P = 0.022). A gender‐specific one‐way ANOVA was also conducted to investigate mean BMI and waist circumference differences between genotypes of each polymorphism. For both polymorphisms independently, women carrying two copies of the minor allele had significant higher mean waist circumference than those carrying only one copy of the minor allele (MM > TM, P = 0.031; II > VI, P = 0.013) or those who were homozygous for the major allele (MM > TT, P = 0.005; II > VV, P = 0.006). We also observed significant higher mean waist circumference in men carrying one copy of the minor allele when compared to those who were homozygous for the major allele for the T280M polymorphism (TM > TT, P = 0.029). This study suggests that CX3CR1, a biomarker of obesity in this sample, constitutes a potential target for further investigation of the role of inflammation in the expression of obesity‐related phenotypes.     

Biochemical and Anthropometric Characterization of Morbid Obesity in a Large Utah Pedigree

A Utah family with morbid obesity was extended to include 122 persons in four generations for the purpose of characterizing anthropometric and biochemical variables in family members with and without morbid obesity. Seventy-seven subjects had blood drawn for biochemical analyses. Of the 77 subjects, 12 were morbidly obese (≥44.5 kg or 100 pounds overweight), 20 were between 22.5–45.4 kg (50 and 99 pounds) overweight and 45 were less than 22.5 kg (50 pounds) overweight Sixty-two randomly-ascertained controls were used for comparisons of age- and gender-adjusted study variables. Morbidly obese subjects had mean body mass indices (BMI) of 41.0 kg/m² (62 kg over ideal weight) compared to 25.3 kg/m² (10 kg overweight) in the <22.5 kg family members (p<0.001). The <22.5 kg family members had lower BMI than the random controls (27.6 kg/m², p<0.05), indicating clear bimodality of obesity within the pedigree. Percent body fat from bioelectrical impedance was 35% versus 24% in the morbidly obese and the <22.5 kg subjects, respectively. Ideal body weight was similar among the three pedigree weight groups. Hip and waist circumferences were much larger in the morbidly obese and the waist-to-hip ratio remained significantly greater in the morbidly obese subjects compared to the <22.5 kg group. Morbidly obese subjects had elevated triglycerides and VLDL-C levels, low HDL-levels, and normal LDL-C levels. Fasting insulin was the best predictor of morbid obesity of all biochemical and lipid measurements (odds ratio of 4.5). Fasting insulin levels and the insulin-to-glucose ratio were more than twice as high as control levels. Even after adjusting for differences in BMI, fasting insulin and the insulin to glucose ratio were elevated in the morbidly obese subjects indicating that insulin levels were inappropriately high for their weight compared to this relationship found in the other groups. Adjusted insulin levels for the 22.5–45.4 kg group were similar to controls, indicating insulin level was at the predicted level for their weight. In conclusion, individuals with morbid obesity appeared to have greater insulin resistance than could be explained by their weight. CHD risk from elevated LD L-C was not present, but CHD risk was increased by the so-called multiple metabolic syndrome (insulin resistance, high triglycerides and low HDL-C).     

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.     

Excess Weight and the Risk of Incident Coronary Heart Disease Among Men and Women

Overweight and obesity have been prospectively associated with the risk of coronary heart disease (CHD). Less clear is the relation of excess weight to risk of CHD among men and women with comorbid conditions, and the proportion of CHD risk attributable to excess weight in the US population. To assess the risk of CHD associated with excess weight among men and women with and without associated comorbid conditions, and determine the population attributable risk of CHD associated with excess weight. The study population consisted of two prospective cohorts, the Health Professionals Follow‐up Study (HPFS) (N = 42,351 men; age range at baseline, 39–75 years) and the Nurses' Health Study (NHS) (N = 76,703 women; age range at baseline, 39–65 years). A total of 2,771 incident cases of CHD among the men and 2,359 among the women were documented over the 16 years of follow‐up. Overall, the relative risk (RR) of CHD associated with BMI ≥30 kg/m² compared with BMI 18.5–22.9 kg/m² was 2.13 (95% confidence interval (CI), 1.82–2.48) among the men and 2.48 (95% CI, 2.20–2.80) among the women. The risk of CHD increased with BMI, both with and without the presence of comorbid conditions. Our estimates suggest that more than a third of all incident CHD in US men and women may be attributed to excess weight. Excess weight is associated with increased risk of CHD among men and women, both alone and in combination with comorbid conditions, though the results require careful interpretation. A substantial proportion of incident CHD may be attributed to excess weight.     

Neck Circumference as a Simple Screening Measure for Identifying Overweight and Obese Patients

Objective: There are numerous methods of assessing overweight and obesity. We undertook an observational study to test a method of identifying overweight or obese patients solely by measuring the circumference of the neck. Research Methods and Procedures: A test sample and a second validation sample included 979 subjects (460 men and 519 women), who visited a family medicine clinic in a southern Israeli urban district for any reason between the randomly chosen months of January and September 1998. Main outcome included neck, waist, and hip circumferences; body mass index (BMI); and waist:hip ratio measures. Results: Pearson's correlation coefficients indicated a significant association between neck circumference (NC) and: BMI (men, r = 0.83; women, r = 0.71; each, p < 0.0001), age (men, r = 0.33; women, r = 0.36; each, p < 0.0001), weight (men, r = 0.7; women, r = 0.81; each, p < 0.0001), waist circumference (men, r = 0.86; women, r = 0.85; each, p < 0.0001), hip circumference (men, r = 0.62; women, r = 0.56; each, p < 0.0001), and waist:hip ratio (men, r = 0.66; women, r = 0.87; each, p < 0.0001). NC ≥37 cm for men and ≥34 cm for women were the best cutoff levels for determining the subjects with BMI ≥25.0 kg/m² using the receiver output curve analysis. In the validation unrelated group, the test characteristics were excellent with 98% sensitivity, 89% specificity, and 94% accuracy for men, and 100% sensitivity, 98% specificity, and 99% accuracy for women. NC ≥39.5 cm for men and ≥36.5 cm for women were the best cutoff levels for determining the subjects with BMI ≥30 kg/m² using the receiver output curve analysis. In the validation unrelated group, the test characteristics were excellent with 93% sensitivity, 90% specificity, and 91% accuracy for men, and 93% sensitivity, 98% specificity, and 97% accuracy for women. Discussion: NC measurement is a simple and time‐saving screening measure that can be used to identify overweight and obese patients. Men with NC <37 cm and women with NC <34 cm are not to be considered overweight. Patients with NC ≥37 cm for men and ≥34 cm for women require additional evaluation of overweight or obesity status.     

Elderly People With Low Body Weight May Have Subtle Low‐grade Inflammation

Low‐grade inflammation, which plays important roles in the development of fatal diseases, is commonly observed in obese people. However, this has not been evaluated in lean people, who have relatively increased mortality risk compared with people of normal weight. Here, we elucidate the association between systemic low‐grade inflammation and low body weight, with particular emphasis on aging. We examined the relationship between circulating C‐reactive protein (CRP) and BMI in a cross‐sectional study of 2,675 apparently healthy adults who had undergone a medical check‐up. Overall, subjects with low BMI (<21.0 kg/m², n = 585) showed a favorable cardiovascular profile without being undernourished. In the elderly (≥55 years old), logarithmic CRP (LogCRP) showed a sigmoid curve against BMI with a base at BMI 21.0–22.9 kg/m², but not against waist circumference (WC), even in nonsmokers. In contrast, in middle‐aged people, LogCRP showed an almost linear relationship with both BMI and WC. LogCRP levels in elderly nonsmokers with low BMI, but not normal or high BMI, were significantly higher than those in middle‐aged with corresponding BMI (P < 0.05). After adjustment for age, sex, smoking status, and weight change over the past 2 years, the adjusted means of LogCRP still had a similar sigmoid curve against BMI in the elderly. These results suggest that elderly people with low body weight may have subtle low‐grade inflammation irrespective of a favorable cardiovascular risk, which remains to be confirmed in further studies.     

Obesity‐related Comorbidities in Obese African Americans in an Outpatient Weight Loss Program

Objective: To identify, among obese African‐American enrollees in an outpatient weight loss program, differences between those with and without obesity‐related comorbidities (ORCMs). Research Methods and Procedures: Data were from 237 obese African Americans (BMI, 30 to 50 kg/m²; 90% women) who enrolled in a 10‐week lifestyle weight loss program. Analyses compared subgroups defined by ORCM status (from medical history) on baseline characteristics, program attendance, and postprogram weight change. Results: Most participants (76%) had one or more ORCMs. Those with versus without ORCMs, respectively, were older (mean age, 45.6 vs. 37.1 years; p < 0.001), were less educated (59.2% vs. 76.6% with >12 years; p = 0.031), were more likely to perceive a physical limitation affecting activity (22.2% vs. 1.8%; p < 0.001), and had higher waist circumference (mean, 113.7 vs. 106.9 cm; p < 0.001) but not BMI (38.3 vs. 37.0 kg/m²; p = 0.095). Logistic regression analyses confirmed the independence of these associations. Having ORCMs was not associated with class attendance or return for data collection after the 10‐week program. Postprogram weight change (n = 134) was unrelated to ORCMs, but better weight loss was seen among those without perceived physical limitations (1.9 vs. 0.4 kg in those without versus with limitations; p = 0.069). Conclusion: Data from this clinical sample of obese African Americans suggest that waist circumference is relevant to ORCM status at BMI levels up to 50 kg/m². Clear indications for tailoring of treatment based on ORCM status were not identified, although the possible influence of ORCM‐related activity limitations warrants further study.     

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.     

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.     

Race, childhood insulin, childhood caloric intake, and class 3 obesity at age 24: 14-year prospective study of schoolgirls

The prevalence of Class 3 obesity (BMI ≥40 kg/m²) has more than doubled in the past 25 years. In a 14‐year prospective study from age 10 to 24 of a biracial schoolgirl cohort (293 black, 256 white), we assessed childhood correlates of Class 3 BMI at age 24. Of 42 girls with Class 3 BMI at age 24, 36 (86%) were black. By logistic regression, significant explanatory variables of Class 3 BMI at age 24 included top decile waist circumference at age 11 (odds ratio (OR) 5.7, 95% confidence interval (CI) 2.3–13.9, P = 0.0002), age 10 BMI ≥ the Center for Disease Control (CDC) 2000 top 15% (OR 7.0, 95% CI 2.5–19.3, P = 0.0002), and a three‐way interaction between race, childhood insulin, and average caloric intake from age 10 to age 19 (for each unit increase, OR 1.7 95% CI 1.3–2.2, P = 0.0003). Age 10 BMI, age 11 waist circumference, and interaction of race, childhood insulin, and childhood caloric intake predict Class 3 obesity in young adulthood, facilitating childhood identification of girls at high risk for developing Class 3 obesity.