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Objective: To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study., Methods: We used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMIPM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMISR). The usefulness of including demographics and perceived weight category in those models was also examined., Results: The model that used BMISR, compared to BMIPM, as the only variable produced a larger R2 (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m2) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m2). The performance of the model containing BMISR alone was not substantially improved by the addition of demographics, perceived weight category or BMIPM., Conclusions: Our work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMIM when the time interval between measures is relatively long. Other time frames and alternatives to in-person collection of self-reported data need to be examined., Competing Interests: The authors have declared that no competing interests exist.

Background: Percent body fat equations are usually developed in specific populations and have low generalizability., Objectives: To use a nationally representative sample of the American youth population (8-17 years old) from the 1999-2004 National Health and Nutrition Examination Survey data to develop gender-specific percent body fat equations., Methods: Percent body fat equations were developed for girls and boys using information on weight, height, waist circumference, triceps skin-folds, age, race/ethnicity and menses status compared to dual-emission X-ray absorptiometry. Terms were selected using forward and backward selection in regression models in a 2/3 development sample and were cross-validated in the remaining sample. Final coefficients were estimated in the full sample., Results: Final equations included ten terms in girls and eight terms in boys including interactions with age and race/ethnicity. In the cross-validation sample, the adjusted R2 was 0.818 and the root mean squared error was 2.758 in girls. Comparable estimates in boys were 0.893 and 2.525. Systematic bias was not detected in the estimates by race/ethnicity or by body mass index categories., Conclusion: Gender-specific percent body fat equations were developed in youth with a strong potential for generalizability and utilization by other investigators studying adiposity-related issues in youth., (© 2013 The Authors. Pediatric Obesity © 2013 International Association for the Study of Obesity.)

Obesity prevention trials are designed to promote healthy weight. The success of these trials is often assessed using one of three metrics--means, incidence or prevalence. In this study, we point out conceptual shortcomings of these metrics and introduce an alternative that we call 'excess gain'. A mathematical demonstration using simulated data shows a scenario in which the statistical power of excess gain compares favorably with that of incidence and prevalence. Prevention of excess gain communicates an easily understood public health message that is applicable to all individuals regardless of weight status.

The objective of this study was to examine the effect of weight history on blood pressure. Extant data from the Atherosclerosis Risk in Communities (ARIC) study were used to compare blood pressure in women (n=5,675) and men (n=4,893) with different 3-year weight histories, but similar current BMI. We used mixed models regression adjusted for ethnicity, age, education, field center, smoking, alcohol consumption, antihypertensive medications, interval length, and BMI at follow-up. We also examined associations between 3-year weight history and blood pressure within weight status categories (normal weight (>or=18.5 to <25.0 kg/m2), overweight (>or=25.0 to <30.0 kg/m2), and obese (>or=30.0 kg/m2)). We found weight history affected both systolic and diastolic blood pressures. Compared to men at the same BMI who had maintained their weight, men who had experienced a 10% weight gain over the previous 3 years had systolic and diastolic blood pressures that were 2.6 and 1.9 mm Hg higher, respectively (P<0.001 for both). Associations in women were in the same direction, but smaller at 0.9 and 0.6 mm Hg (P<0.001). With the exception of diastolic blood pressure in normal weight women, we found no significant interactions between weight change and current weight status. In conclusion, some of the variation in blood pressure among individuals at the same BMI may be due to weight change history. Effects of 3-year weight change history appear to be stronger and more consistent in men than in women, and generally similar regardless of current weight status.

Few studies have focused on the impact of weight maintenance on cardiovascular disease risk factors or addressed whether changes differ by baseline weight status and medication usage. The authors examined these issues using 9 years of follow-up data on 3,235 men and women from the Atherosclerosis Risk in Communities (ARIC) Study who were aged 45-64 years at baseline (1987-1989). In participants not using medications, glucose (3.0 mg/dl, 95% confidence interval (CI): 2.4, 3.5) and triglycerides (10.1 mg/dl, 95% CI: 8.3, 11.9) increased, while total cholesterol (-9.6 mg/dl, 95% CI: -10.6, -8.6), low density lipoprotein cholesterol (-9.9 mg/dl, 95% CI: -10.9, -9.0), and high density lipoprotein cholesterol (-1.7 mg/dl, 95% CI: -2.1, -1.3) decreased. Systolic blood pressure (7.9 mmHg, 95% CI: 7.3, 8.4) increased, but diastolic blood pressure (-1.1 mmHg, 95% CI: -1.4, -0.7) declined. Normal weight (body mass index: 18.5-<25.0 kg/m(2)) participants had smaller increases in glucose compared with obese (body mass index: >/=30.0 kg/m(2)) participants. In contrast, the authors found less favorable changes in total, low density lipoprotein, and high density lipoprotein cholesterol, triglycerides, and diastolic blood pressure among normal weight compared with obese participants who maintained their weight. These patterns were similar across weight status groups regardless of medication usage.

Objectives: To examine whether changes in cardiovascular disease (CVD) risk factors differ by baseline weight status among young adults who maintained or gained weight., Design: Longitudinal cohort study., Subjects: White and African Americans who either maintained (+/-5 pounds; n=488) or gained (>5 pounds; n=2788) weight over 15 years., Measurements: Anthropometrics and CVD risk factors were measured at baseline (1985-1986) and follow-up. Participants were classified as normal weight (body mass index (BMI) 18.5-24.9 kg/m2) or overweight (BMI >or=25 kg/m2) at baseline. Multivariable models were stratified by ethnicity and weight change category., Results: Normal weight maintainers tended to have more favorable risk factors at baseline and follow-up than overweight maintainers. Size and direction of 15-year changes in risk factors were similar by weight status, except that in white normal weight maintainers changes in high-density lipoprotein (HDL)-cholesterol (3.3 mg/dl (95% confidence interval (CI): 0.4, 6.3)) and triglycerides (-14.7 mg/dl (-25.8, -3.7)) were more favorable. Weight gain was associated with unfavorable changes in risk factors. Weight gainers normal weight at baseline had less adverse changes in glucose, blood pressure, HDL-cholesterol (whites only) and triglycerides (African Americans only) than overweight gainers. However, normal weight African-American weight gainers had more adverse changes in total (3.1 mg/dl (0.2, 6.1)) and low-density lipoprotein-cholesterol (3.4 mg/dl (0.6, 6.3))., Conclusions: Baseline weight status does not appear to influence the size or direction of risk factor changes among adults who maintained their weight over 15 years. In contrast, weight gain was associated with changes in some risk factors differentially by baseline weight status.

Few studies have examined the impact of weight history. Extant data from the Atherosclerosis Risk in Communities Study were used to compare risk factors for normal-weight (body mass index: 18.5-24.9 kg/m(2)) adults with a history of weight loss (n = 775) with those for persons with a history of weight maintenance (n = 5,164). In this 1987-1998 US study, the authors also compared risk factors for pre-obese (body mass index: 25.0-29.9 kg/m(2)) adults with a history of weight gain (n = 1,296) versus weight maintenance (n = 6,721). They used mixed-models regression to adjust for ethnicity, gender, age, education, field center, smoking, alcohol consumption, follow-up time, and follow-up body mass index. Compared with adults with a history of weight maintenance, adults with a 3-year history of weight loss had more favorable total and low density lipoprotein cholesterol levels and similar glucose, high density lipoprotein cholesterol, and triglyceride levels. In contrast, pre-obese adults with a 3-year history of weight gain had equivalent glucose and lipid levels at follow-up compared with adults with a history of weight maintenance. These findings suggest that, in addition to current weight, weight history may impact glucose and lipid levels.