Scott B Going

PMID: 12181389;Abstract:

Objective: To examine the relationship between percentage of total body fat (%Fat) and body mass index (BMI) in early postmenopausal women and to evaluate the validity of the BMI standards for obesity established by the NIH. Research Methods and Procedures: Three hundred seventeen healthy, sedentary, postmenopausal women (ages, 40 to 66 years; BMI, 18 to 35 kg/m²; 3 to 10 years postmenopausal) participated in the study. Height, weight, BMI, and %Fat, as assessed by DXA, were measured. Receiver operating characteristic analysis was performed to evaluate the ability of BMI to discriminate obesity from non-obesity using 38%Fat as the criterion value. Results: A moderately high relationship was observed between BMI and %Fat (r = 0.81; y = 1.41x + 2.65) with a SE of estimate of 3.9%. Eighty-one percent of other studies examined fell within 1 SE of estimate as derived from our study. Receiver operating characteristic analysis showed that BMI is a good diagnostic test for obesity. The cutoff for BMI corresponding to the criterion value of 38%Fat that maximized the sum of the sensitivity and specificity was 24.9 kg/m². The true-positive (sensitivity) and false-positive (1 - specificity) rates were 84.4% and 14.6%, respectively. The area under the curve estimate for BMI was 0.914. Discussion: There is a strong association between %Fat and BMI in postmenopausal women. Current NIH BMI-based classifications for obesity may be misleading based on currently proposed %Fat standards. BMI >25 kg/m² rather than BMI >30 kg/m² may be superior for diagnosing obesity in postmenopausal women.

PMID: 15263921;Abstract:

OBJECTIVE: This study analyzed baseline behavioral and psychosocial differences between successful and nonsuccessful participants in a behavioral weight management program. Success was defined by commonly used health-related criteria (5% weight loss). Noncompletion was also used as a marker of a failed attempt at weight control. SUBJECTS: A total of 158 healthy overweight and obese women (age, 48.0 ± 4.5 y; BMI, 31.0 ± 3.8 kg/m²; body fat, 44.5 ± 5.3%). INTERVENTION: Subjects participated in a 16-week lifestyle weight loss program consisting of group-based behavior therapy to improve diet and increase physical activity, and were followed for 1 y after treatment. METHODS: At baseline, all women completed a comprehensive behavioral and psychosocial battery assessing dieting/weight history, dietary intake and eating behaviors, exercise, self-efficacy, outcome evaluations, body image, and other variables considered relevant for weight management. Participants who maintained a weight loss of 5% or more at 16 months (or 10% or more of initial fat mass) were classified as successful. Nonsuccessful participants were those who dropped out and completers who had not lost weight at follow-up. RESULTS: Of all participants, 30% (n = 47) did not complete initial treatment and/or missed follow-up assessments (noncompleters). Noncompletion was independently associated with more previous weight loss attempts, poorer quality of life, more stringent weight outcome evaluations, and lower reported carbohydrate intake at baseline. In logistic regression, completion status was predicted correctly in 84% of all cases (χ² = 45.5, P 0.001), using baseline information only. Additional predictors of attrition were initial weight, exercise minutes, fiber intake, binge eating, psychological health, and body image. A large variation in weight loss/maintenance results was observed (range: 37.2 kg for 16-month weight change). Independent baseline predictors of success at 16 months were more moderate weight outcome evaluations, lower level of previous dieting, higher exercise self-efficacy, and smaller waist-to-hip ratio. Success status at follow-up was predicted correctly in 74% of all starting cases (χ² = 33.6, P 0.001). CONCLUSION: Psychosocial and behavioral variables (eg, dieting history, dietary intake, outcome evaluations, exercise self-efficacy, and quality of life) may be useful as pretreatment predictors of success level and/or attrition in previously overweight and mildly obese women who volunteer for behavioral weight control programs. These factors can be used in developing readiness profiles for weight management, a potentially important tool to address the issue of low success/completion rates in the current management of obesity.

Understanding the etiology of skeletal fragility during growth is critical for the development of treatments and prevention strategies aimed at reducing the burden of childhood fractures. Thus we evaluated the relationship between prior fracture and bone parameters in young girls. Data from 465 girls aged 8 to 13 years from the Jump-In: Building Better Bones study were analyzed. Bone parameters were assessed at metaphyseal and diaphyseal sites of the nondominant femur and tibia using peripheral quantitative computed tomography (pQCT). Dual-energy X-ray absorptiometry (DXA) was used to assess femur, tibia, lumbar spine, and total body less head bone mineral content. Binary logistic regression was used to evaluate the relationship between prior fracture and bone parameters, controlling for maturity, body mass, leg length, ethnicity, and physical activity. Associations between prior fracture and all DXA and pQCT bone parameters at diaphyseal sites were nonsignificant. In contrast, lower trabecular volumetric BMD (vBMD) at distal metaphyseal sites of the femur and tibia was significantly associated with prior fracture. After adjustment for covariates, every SD decrease in trabecular vBMD at metaphyseal sites of the distal femur and tibia was associated with 1.4 (1.1-1.9) and 1.3 (1.0-1.7) times higher fracture prevalence, respectively. Prior fracture was not associated with metaphyseal bone size (ie, periosteal circumference). In conclusion, fractures in girls are associated with lower trabecular vBMD, but not bone size, at metaphyseal sites of the femur and tibia. Lower trabecular vBMD at metaphyseal sites of long bones may be an early marker of skeletal fragility in girls.