Obesity

We projected future prevalence and BMI distribution based on national survey data (National Health and Nutrition Examination Study) collected between 1970s and 2004. Future obesity‐related health‐care costs for adults were estimated using projected prevalence, Census population projections, and published national estimates of per capita excess health‐care costs of obesity/overweight. The objective was to illustrate potential burden of obesity prevalence and health‐care costs of obesity and overweight in the United States that would occur if current trends continue. Overweight and obesity prevalence have increased steadily among all US population groups, but with notable differences between groups in annual increase rates. The increase (percentage points) in obesity and overweight in adults was faster than in children (0.77 vs. 0.46–0.49), and in women than in men (0.91 vs. 0.65). If these trends continue, by 2030, 86.3% adults will be overweight or obese; and 51.1%, obese. Black women (96.9%) and Mexican‐American men (91.1%) would be the most affected. By 2048, all American adults would become overweight or obese, while black women will reach that state by 2034. In children, the prevalence of overweight (BMI ≥ 95th percentile, 30%) will nearly double by 2030. Total health‐care costs attributable to obesity/overweight would double every decade to 860.7–956.9 billion US dollars by 2030, accounting for 16–18% of total US health‐care costs. We continue to move away from the Healthy People 2010 objectives. Timely, dramatic, and effective development and implementation of corrective programs/policies are needed to avoid the otherwise inevitable health and societal consequences implied by our projections.

Research Methods and Procedures: High‐fat (HF) diet feeding can induce obesity and metabolic disorders in rodents that resemble the human metabolic syndrome. However, this dietary intervention is not standardized, and the HF‐induced phenotype varies distinctly among different studies. The question which HF diet type is best to model the metabolic deterioration seen in human obesity remains unclear. Therefore, in this review, metabolic data obtained with different HF diet approaches are compiled. Both whole‐body and organ‐specific diet effects are analyzed.

Results: On the basis of these results, we conclude that animal fats and ω‐6/ω‐9‐containing plant oils can be used to generate an obese and insulin‐resistant phenotype in rodents, whereas fish oil‐fed animals do not develop these disorders.

Discussion: Looking at the present data, it does not seem possible to define an ideal HF diet, and an exact definition of diet composition and a thorough metabolic characterization of the HF diet effects in a researcher's specific laboratory setting remains essential for metabolic studies with this model.

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

Background: Sobal and Stunkard's review (1989) of 34 studies from developed countries published after 1941, found inconsistent relationships between socioeconomic status (SES) and childhood adiposity. Inverse associations (36%), no associations (38%), and positive associations (26%) were found in similar proportions. In view of the trends in pediatric obesity, the relationship between SES and adiposity may have changed.

Objective: To describe the cross‐sectional association between SES and adiposity in school‐age children from western developed countries in epidemiological studies since 1989.

Methods and Procedures: PubMed database was searched to identify potentially relevant publications. Epidemiological studies from western developed countries presenting cross‐sectional data on the bivariate association between an SES indicator and objectively measured adiposity in childhood (5–18 years), carried out after 1989 were included. SES indicators included parental education, parental occupation, family income, composite SES, and neighborhood SES.

Results: Forty‐five studies satisfied the review criteria. SES was inversely associated with adiposity in 19 studies (42%), there was no association in 12 studies (27%), and in 14 studies (31%) there was a mixture of no associations and inverse associations across subgroups. No positive SES‐adiposity associations were seen in unadjusted analyses. With parental education as the SES indicator, inverse associations with adiposity were found in 15 of 20 studies (75%).

Discussion: Research carried out within the past 15 years finds that associations between SES and adiposity in children are predominately inverse, and positive associations have all but disappeared. Research is needed to understand the mechanisms through which parental social class influences childhood adiposity.

Objective: To examine the independent associations of abdominal fat (visceral and subcutaneous) and liver fat with all‐cause mortality.

Research Methods and Procedures: Participants included 291 men [97 decedents and 194 controls; mean age, 56.4 ± 12.0 (SD) years] who received a computed tomography (CT) examination at the preventive medicine clinic in Dallas, TX, between 1995 and 1999, with a mean mortality follow‐up of 2.2 ± 1.3 years. Abdominal fat was determined using contiguous CT images from the L3‐L4 to L4‐L5 intervertebral space. Liver fat was assessed using the CT‐determined liver attenuation value, which is inversely related to liver fat. Logistic regression was used to determine the independent association between the fat depots and all‐cause mortality.

Results: During the study, there were 97 deaths. Visceral fat [odds ratio (OR) per SD: 1.83; 95% CI: 1.23 to 2.73], abdominal subcutaneous fat (1.44; 1.02 to 2.03), liver fat (0.64; 0.46 to 0.87), and waist circumference (1.41; 1.01 to 1.98) were significant individual predictors of mortality after controlling for age and length of follow‐up. In a model including all three fat measures (subcutaneous, visceral, and liver fat), age, and length of follow‐up, only visceral fat (1.93; 1.15 to 3.23) was a significant predictor of mortality.

Discussion: Visceral fat is a strong, independent predictor of all‐cause mortality in men.

Vitamin D status is known to be poor in obese individuals; there is no consensus as to the reason. Cross‐sectional study of the relation between serum 25‐hydroxyvitamin D (25(OH)D) concentration and body size in the baseline data from unsupplemented adults entering two study cohorts in our research unit, N = 686. Regression analyses of body size variables against serum 25(OH)D concentration, using both linear and hyperbolic models. The fit to a hyperbolic model of 25(OH)D against body weight completely removed the obesity‐related component of inter‐individual variability in serum 25(OH)D concentration. The hyperbolic fit using total body weight was significantly better than any linear model, and specifically better than any using BMI. Dilution of ingested or cutaneously synthesized vitamin D in the large fat mass of obese patients fully explains their typically low vitamin D status. There is no evidence for sequestration of supplemental or endogenous cholecalciferol. Vitamin D replacement therapy needs to be adjusted for body size if desired serum 25(OH)D concentrations are to be achieved.

Obesity is the major risk factor for metabolic syndrome and through it diabetes as well as cardiovascular disease. Visceral fat (VF) rather than subcutaneous fat (SF) is the major predictor of adverse events. Currently, the reference standard for measuring VF is abdominal X‐ray computed tomography (CT) or magnetic resonance imaging (MRI), requiring highly used clinical equipment. Dual‐energy X‐ray absorptiometry (DXA) can accurately measure body composition with high‐precision, low X‐ray exposure, and short‐scanning time. The purpose of this study was to validate a new fully automated method whereby abdominal VF can be measured by DXA. Furthermore, we explored the association between DXA‐derived abdominal VF and several other indices for obesity: BMI, waist circumference, waist‐to‐hip ratio, and DXA‐derived total abdominal fat (AF), and SF. We studied 124 adult men and women, aged 18–90 years, representing a wide range of BMI values (18.5–40 kg/m²) measured with both DXA and CT in a fasting state within a one hour interval. The coefficient of determination (r²) for regression of CT on DXA values was 0.959 for females, 0.949 for males, and 0.957 combined. The 95% confidence interval for r was 0.968 to 0.985 for the combined data. The 95% confidence interval for the mean of the differences between CT and DXA VF volume was −96.0 to −16.3 cm³. Bland‐Altman bias was +67 cm³ for females and +43 cm³ for males. The 95% limits of agreement were −339 to +472 cm³ for females and −379 to +465 cm³ for males. Combined, the bias was +56 cm³ with 95% limits of agreement of −355 to +468 cm³. The correlations between DXA‐derived VF and BMI, waist circumference, waist‐to‐hip ratio, and DXA‐derived AF and SF ranged from poor to modest. We conclude that DXA can measure abdominal VF precisely in both men and women. This simple noninvasive method with virtually no radiation can therefore be used to measure VF in individual patients and help define diabetes and cardiovascular risk.