Nationally representative equations that include resistance and reactance for the prediction of percent body fat in Americans.

BACKGROUND/OBJECTIVES: Resistance and reactance collected by bioelectrical impedance (BIA) can be used in equations to estimate percent body fat at relatively low cost and subject burden. To our knowledge, no such equations have been developed in a nationally representative sample. SUBJECTS/METHODS: Dual-energy X-ray absorptiometry assessed percent body fat from the 1999 to 2004 National Health and Nutrition Survey was the criterion method for development of sex-specific percent body fat equations using up to 6467 males or 4888 females 8-49 years of age. Candidate variables were studied in multiple mathematical forms and interactions using the Least Absolute Shrinkage and Selection Operator. Models were fit in 2/3's of the data and validated in 1/3 of the data selected at random. Final coefficients, R2 values and root mean square error (RMSE) were estimated in the full data set. RESULTS: Models that included age, ethnicity, height, weight, BMI and BIA assessments (resistance, reactance and height2/resistance) had R2 values of 0.831 in men and 0.864 in women in the full data set. RMSE measurements were between 2 and 3 body fat percentage points, and all equations showed low bias across groups formed by age, race/ethnicity or body mass index category. The addition of triceps skinfold and waist circumference increased the R2 to 0.905 in males and 0.883 in females. Adding other anthropometrics (plus menses in females) had little impact on performance. Reactance and resistance alone (in multiple mathematical forms) performed poorly with R2~0.2. CONCLUSIONS: Equations that included BIA assessments along with demographic and anthropometric variables provided percent body fat assessments that had high generalizability, strong predictive ability and low bias.

Prediction of percent body fat measurements in Americans 8 years and older.

BACKGROUND/OBJECTIVES: Although numerous equations to predict percent body fat have been published, few have broad generalizability. The objective of this study was to develop sets of equations that are generalizable to the American population 8 years of age and older. SUBJECTS/METHODS: Dual-emission X-ray absorptiometry (DXA) assessed percent body fat from the 1999-2006 National Health and Nutrition Examination Survey (NHANES) was used as the response variable for development of 14 equations for each gender that included between 2 and 10 anthropometrics. Other candidate variables included demographics and menses. Models were developed using the Least Absolute Shrinkage and Selection Operator (LAASO) and validated in a » withheld sample randomly selected from 11 884 males or 9215 females. RESULTS: In the final models, R(2) ranged from 0.664 to 0.845 in males and from 0.748 to 0.809 in females. R(2) was not notably improved by development of equations within, rather than across, age and ethnic groups. Systematic over or under estimation of percent body fat by age and ethnic groups was within 1 percentage point. Seven of the fourteen gender-specific models had R(2) values above 0.80 in males and 0.795 in females and exhibited low bias by age, race/ethnicity and body mass index (BMI). CONCLUSIONS: To our knowledge, these are the first equations that have been shown to be valid and unbiased in both youth and adults in estimating DXA assessed body fat. The equations developed here are appropriate for use in multiple ethnic groups, are generalizable to the US population and provide a useful method for assessment of percent body fat in settings where methods such as DXA are not feasible.

Three-year weight change and cardiometabolic risk factors in obese and normal weight adults who are metabolically healthy: the atherosclerosis risk in communities study.

BACKGROUND/OBJECTIVES: Approximately 17% of obese Americans are free of the cardiometabolic risk factors, but few studies have compared responses to weight change in metabolically healthy obese (MHO) and metabolically healthy normal weight (MHNW) adults. We compared the impact of weight loss, weight maintenance and weight gain on cardiometabolic risk factors in the MHO and the MHNW. SUBJECTS/METHODS: Data were from the Atherosclerosis Risk in Communities (ARIC) study. Multiple observations on 2710 participants were included, yielding 4541 observations of sequential 3-year intervals. Metabolically healthy was defined as absence of all components of metabolic syndrome excluding waist circumference. Mixed effects models were used to compare changes in each of five cardiometabolic risk factors within weight change categories (<-3% for weight loss, ±3% for weight maintenance and >3% for weight gain). RESULTS: Weight loss was associated with comparable small changes or no changes in cardiometabolic risk factors in MHO and MHNW individuals. Weight gain was associated with larger increases in systolic (8.6 vs 6.2 mm Hg) and diastolic (3.9 vs 2.5 mm Hg) blood pressure, triglycerides (21.9 vs 15.8 mg/dl) and glucose (4.9 vs 1.9 mg/dl) in MHO individuals compared with MHNW individuals. Weight maintenance was associated with larger increases in triglycerides (10.0 vs 6.4 mg/dl) and glucose (1.7 vs 0.9 mg/dl) in MHO compared with MHNW individuals. MHO weight losers had more favorable changes in the five cardiometabolic risk factors compared to MHO weight maintainers (P<0.02) or gainers (P<0.0001). CONCLUSIONS: This work showed differences between MHNW and MHO adults and supports recommendations for weight loss in the MHO in order to avoid increases in risk factors associated with weight maintenance and weight gain.

Obesity Paradox should not interfere with public health efforts.

The Obesity Paradox could result in confusing messages that derail beneficial environmental changes and lead to reduced efforts by physicians to provide healthy lifestyle treatment plans to their obese patients. The Obesity Paradox applies in the main to individuals who have a disease, and therefore observed associations with mortality illustrating the Paradox may be more susceptible to certain types of bias than would be found in healthy individuals. Although individualization of weight loss advice for patients with serious disease is appropriate in medical settings, this does not supplant the need for general efforts to prevent and treat obesity.

Percent body fat prediction equations for 8- to 17-year-old American children.

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.

Prevention of excess gain.

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.

Impact of overweight and obesity on hospitalization: race and gender differences.

OBJECTIVE: To examine associations between weight status and number of all-cause and cause-specific hospitalizations overall, and by race and gender. DESIGN: Longitudinal cohort study. SUBJECTS: White and black adults (n=15 355) from the Atherosclerosis Risk in Communities Study who were normal weight (body mass index: >or=18.5 to <25.0 kg m(-2); n=4997), overweight (>or=25.0 to <30.0 kg m(-2); n=6100), or obese (>or=30.0 kg m(-2); n=4258) at baseline. MEASUREMENTS: Information on hospitalizations was collected using community and cohort surveillance methods. Negative binomial models adjusted for race, gender, field center, age, physical activity, education level, smoking status, alcoholic beverage consumption and health insurance at baseline. Adjusted numbers of hospitalizations were calculated after setting covariates to the mean value (for continuous variables) or to the average distribution (for categorical variables) observed in the entire cohort and are expressed as the number of hospitalizations per 1000 adults followed over a period of 13 years. RESULTS: The covariate-adjusted average number of all-cause hospitalizations was 1316 per 1000 normal weight, 1543 per 1000 overweight and 2025 per 1000 obese. Normal weight women had significantly fewer hospitalizations than normal weight men (1173 versus 1515 per 1000), but the increase associated with being obese on the number of all-cause hospitalizations was larger in women than men (791 versus 589 per 1000). There was no significant difference detected between the number of hospitalizations in normal weight whites and blacks, and the increase in hospitalizations with overweight or obesity was also not different. Effects of weight status on several primary causes of hospitalization differed by gender and race group. CONCLUSION: Our work suggests that obesity prevention may reduce hospitalizations, a major component of rising healthcare costs. The impact of successful obesity prevention is likely to be larger in women than in men, and similar in blacks and whites.

Selection of measures in epidemiologic studies of the consequences of obesity.

The most popular measure for conducting analyses in studies of adiposity is body mass index (BMI); however, BMI does not discriminate between muscle and adipose tissue and does not directly assess regional adiposity. In this article, we address the question of whether alternatives to BMI should be used in epidemiologic analyses of the consequences of obesity. In general, measures of fat distribution such as waist circumference and sagittal abdominal diameter are more highly correlated with cardiovascular disease risk factors and diabetes than BMI; however, differences are usually small. Precise measures of adiposity from methods such as dual-energy x-ray absorptiometry may provide more specific and larger associations with disease, but published studies show that this is not always true. Further, practical considerations such as cost and feasibility must influence the choice of measure in many studies of large populations. Measures of adiposity are highly correlated with each other, and the additional cost of a more precise measure may not be justified in many circumstances. Validated prediction equations that include multiple anthropometric measures, along with demographic variables, may offer a practical means of obtaining assessments of total adiposity in large populations, whereas waist circumference can provide a feasible assessment of abdominal adiposity. Finally, public health messages to the public must be simple to be effective. Therefore, investigators may need to consider the ease of translation of results to the public when choosing a measure.

Modest changes in dietary intake across the menstrual cycle: implications for food intake research.

Food intake varies across the menstrual cycle in mammals, energy intake usually being greater in the premenstrual phase compared with the postmenstrual phase. Premenstrual increments in energy intake and a preferential selection of carbohydrate have been suggested to be greater in women with premenstrual syndrome (PMS), who may be more sensitive to cyclical hormonal or neurotransmitter fluctuations. This has direct implications for research within populations of women, especially where the primary outcome is diet or a change in energy balance. We aimed to determine whether: the premenstrual intake of energy and macronutrients differed from the postmenstrual intake; the change in intake across the menstrual cycle differed in women with PMS compared with controls; and the change in intake was related to the severity of premenstrual symptoms. We collected 3 d dietary intake data during the postmenstrual and premenstrual phases of the menstrual cycle in thirty-one women with PMS and twenty-seven control women. The consumption of energy and macronutrient intake were similar between the phases of the cycle in women with PMS. Conversely, intakes were usually greater premenstrually in control women, although not all differences were statistically significant. Exceptions were with non-milk extrinsic sugars and alcohol, which were both consumed in greater amounts in the premenstrual phase in women with PMS. Significant correlations were observed between the severity of symptoms and the change in the consumption of these nutrients. These data suggest that a consideration of the menstrual cycle phase and PMS in diet may not be warranted, especially in cross-sectional analysis, although it may need to be taken into account when examining change in intake during dietary interventions.

Changes in risk factors for cardiovascular disease by baseline weight status in young adults who maintain or gain weight over 15 years: the CARDIA study.

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.

The definition of weight maintenance.

There is currently no consensus on the definition of weight maintenance in adults. Issues to consider in setting a standard definition include expert opinion, precedents set in previous studies, public health and clinical applications, comparability across body sizes, measurement error, normal weight fluctuations and biologic relevance. To be useful, this definition should indicate an amount of change less than is clinically relevant, but more than expected from measurement error or fluctuations in fluid balance under normal conditions. It is an advantage for the definition to be graded by body size and to be easily understood by the public as well as scientists. Taking all these factors into consideration, the authors recommend that long-term weight maintenance in adults be defined as a weight change of <3% of body weight.