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Background: Adolescent obesity is a major public health concern. Open to all high school students regardless of weight status, HealthCorps is a nationwide program offering a comprehensive high school-based participatory educational program to indirectly address obesity. We tested a hypothesis that the HealthCorps program would decrease BMI z-scores among overweight or obese students, and reduce obesity rates, and evaluated its effects on health knowledge and behaviors., Methods: HealthCorps aimed to improve student knowledge and behaviors regarding nutrition quality, physical activity, sleep, breakfast intake, and mental resilience. Participating students received through HealthCorps coordinators weekly or bi-weekly classroom lessons either for a semester or a year in addition to various during- and after-school health-promoting activities and mentorship. Self-reported height and weight were collected along with questionnaires assessing knowledge and behaviors during 2013-2014 academic year among 14 HealthCorps-participating New York City high schools. This quasi experimental two-arm pre-post trial included 611 HealthCorps and 221 comparison arm students for the analytic sample. Sex-specific analyses stratified by weight status were adjusted for age and Hispanic ethnicity with clustering effects of schools and students taken into account., Results: HealthCorps female overweight/obese and obese student had a significant decrease in BMI z-scores (post-pre delta BMI z-score = -0.16 (95%CI = (-0.26, -0.05), p = 0.004 for the former; and = -0.23 (-0.44, -0.03), p = 0.028, for the latter) whereas comparison female counterparts did not. The HealthCorps students, but not the comparison students, had a significant increase for all knowledge domains except for the breakfast realm, and reported a greater number of significant behavior changes including fruit and vegetable intake and physical activities., Conclusions: The HealthCorps program was associated with reduced BMI z-score in overweight/obese and obese female adolescents, with enhanced health knowledge and behavior for both sexes. With its wide reach, this may be a promising program to help combat adolescent obesity in schools., Trial Registration: This study is registered as a clinical trial at the ClinicalTrials.gov registry with trial number NCT02277496 on September 10, 2014 (Retrospectively registered).

Importance: Body mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents., Objective: To compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents., Design, Setting, and Participants: Cross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016., Main Outcomes and Measures: Dual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight., Results: Participants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2 = 0.64 vs 0.38 in boys and R2 = 0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P < .001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P = .62)., Conclusions and Relevance: The tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Objective: To evaluate the percentage of body fat (%BF)-BMI relationship, identify %BF levels corresponding to adult BMI cut points, and examine %BF-BMI agreement in a diverse Hispanic/Latino population., Methods: %BF by bioelectrical impedance analysis was corrected against %BF by (18) O dilution in 434 participants of the ancillary Hispanic Community Health Study/Study of Latinos. Corrected %BF was regressed against 1/BMI in the parent study (n = 15,261), fitting models for each age group, by sex, and Hispanic/Latino background; predicted %BF was then computed for each BMI cut point., Results: Bioelectrical impedance analysis underestimated %BF by 8.7 ± 0.3% in women and 4.6 ± 0.3% in men (P < 0.0001). The %BF-BMI relationship was nonlinear and linear for 1/BMI. Sex- and age-specific regression parameters between %BF and 1/BMI were consistent across Hispanic/Latino backgrounds (P > 0.05). The precision of the %BF-1/BMI association weakened with increasing age in men but not women. The proportion of participants classified as nonobese by BMI but as having obesity by %BF was generally higher among women and older adults (16.4% in women vs. 12.0% in men aged 50-74 years)., Conclusions: %BF was linearly related to 1/BMI with consistent relationship across Hispanic/Latino backgrounds. BMI cut points consistently underestimated the proportion of Hispanics/Latinos with excess adiposity., (© 2016 The Obesity Society.)

Objectives: Adult body mass (MB) empirically scales as height (Ht) squared (MB ∝ Ht(2) ), but does regional body mass and body composition as a whole also scale as Ht(2) ? This question is relevant to a wide range of biological topics, including interpretation of body mass index (BMI)., Methods: Dual-energy X-ray absorptiometry (DXA) was used to quantify regional body mass [head (MH), trunk, arms, and legs] and whole-body composition [fat, lean soft tissue (LST), and bone mineral content (BMC)] in non-Hispanic (NH) white, NH black, Mexican American, and Korean adults participating in the National Health and Nutrition Examination Survey (NHANES; n = 17,126) and Korean NHANES (n = 8,942). Regression models were developed to establish Ht scaling powers for each measured component with adjustments for age and adiposity., Results: Exploratory analyses revealed a consistent scaling pattern across men and women of the four population groups: regional mass powers, head (∼0.8-1) < arms and trunk (∼1.8-2.3) < legs (∼2.3-2.6); and body composition, LST (∼2.0-2.3) < BMC (∼2.1-2.4). Small sex and population differences in scaling powers were also observed. As body mass scaled uniformly across the eight sex and population groups as Ht(∼2) , tall and short subjects differed in body shape (e.g., MH/MB ∝ Ht(-∼1) ) and composition., Conclusions: Adult human body shape and relative composition are a function of body size as represented by stature, a finding that reveals a previously unrecognized phenotypic heterogeneity as defined by BMI. These observations provide new pathways for exploring mechanisms governing the interrelations between adult stature, body morphology, biomechanics, and metabolism., (© 2014 Wiley Periodicals, Inc.)

Background: Body mass index (BMI) is formulated on the assumption that body weight (BW) scales to height with a power of 2 (BW∝height(2)), independent of sex and race-ethnicity. Powers differing from 2 are observed in studies of selected samples, thus raising the question if BMI is a generalizable metric that makes BW independent of height across populations., Objectives: The objectives were to test the hypothesis that adult BW scales to height with a power of 2 independent of sex and race-ethnicity and to advance an understanding of BMI as a measure of shape by extending allometric analyses to waist circumference (WC)., Design: We conducted cross-sectional subject evaluations, including body composition, from the NHANES and the Korean NHANES (KNHANES). Variations of the allometric model (Y = αX(β)) were used to establish height scaling powers (β ± SE) across non-Hispanic white and black, Mexican American, and Korean men and women., Results: Exploratory analyses in population samples established age and adiposity as important independent determinants of height scaling powers (i.e., β). After age and adiposity in the next series of analyses were controlled for, BW scaling powers were nonsignificantly different between race/ethnic groups within each sex group; WC findings were similar in women, whereas small but significant between-race differences were observed in the men. Sex differences in β values were nonsignificant except for BW in non-Hispanic blacks and WC in Koreans (P < 0.05). Nationally representative powers for BW were (NHANES/KNHANES) 2.12 ± 0.05/2.11 ± 0.06 for men and 2.02 ± 0.04/1.99 ± 0.06 for women and for WC were 0.66 ± 0.03/0.67 ± 0.05 for men and 0.61 ± 0.04/0.56 ± 0.05 for women., Conclusions: Adult BW scales to height with a power of ∼2 across the 8 sex and race/ethnic groups, an observation that makes BMI a generalizable height-independent measure of shape across most populations. WC also follows generalizable scaling rules, a finding that has implications for defining body shape in populations who differ in stature., (© 2014 American Society for Nutrition.)

Objective: The heritability of food neophobia, the tendency to avoid new foods, was tested in 4-7-year-old twins. We also examined whether food neophobia is associated with parent-child feeding relations or child body fat., Design and Methods: 66 same-sex twin pairs, including 37 monozygotic (MZ) and 29 dizygotic (DZ) pairs were studied. Food neophobia was assessed by parent questionnaire (Child Food Neophobia Scale, CFNS), as were child-feeding practices and "division of responsibility" feeding relations. Child anthropometry and percent body fat were directly measured., Results: MZ and DZ twin pair correlations for food neophobia were r = 0.71 and r = -0.01, respectively: heritability= 72%. Greater food neophobia was associated with reduced child eating compliance of prompted foods (P < 0.001) reduced eating compliance of initially refused foods (P < 0.001), and--among girls only--fewer parental food demands (P = 0.01). Interestingly, the correlation between maternal BMI and child BMI z-score was significant only for children high (P = 0.03), but not low (P = 0.55), in food neophobia., Conclusion: Child food neophobia, a highly heritable trait previously linked to emotionality, was associated with less compliant parent-child feeding relations. Strategies to combat food neophobia and foster more harmonious feeding relationships may have a role in obesity prevention., (Copyright © 2013 The Obesity Society.)

When data are available on multiple individuals measured at multiple time points that may vary in number or inter-measurement interval, hierarchical linear models (HLM) may be an ideal option. The present paper offers an applied tutorial on the use of HLM for developing growth curves depicting natural changes over time. We illustrate these methods with an example of body mass index (BMI; kg/m(2)) among overweight and obese adults. We modelled among-person variation in BMI growth curves as a function of subjects' baseline characteristics. Specifically, growth curves were modelled with two-level observations, where the first level was each time point of measurement within each individual and the second level was each individual. Four longitudinal databases with measured weight and height met the inclusion criteria and were pooled for analysis: the Framingham Heart Study (FHS); the Multiple Risk Factor Intervention Trial (MRFIT); the National Health and Nutritional Examination Survey I (NHANES-I) and its follow-up study; and the Tecumseh Mortality Follow-up Study (TMFS). Results indicated that significant quadratic patterns of the BMI growth trajectory depend primarily upon a combination of age and baseline BMI. Specifically, BMI tends to increase with time for younger people with relatively moderate obesity (25 BMI <30) but decrease for older people regardless of degree of obesity. The gradients of these changes are inversely related to baseline BMI and do not substantially depend on gender., (Copyright 2003 John Wiley & Sons, Ltd.)

Background: Limited research has been done to explore differences between ethnic groups, including Hispanic Americans (HAs), in the association between percentage body fat (PBF) and body mass index (BMI; in kg/m(2)); the numbers of HAs are increasing in the US population., Objective: We investigated whether the relation between PBF and BMI in adult HAs differed from that of African Americans (AAs) and European Americans (EAs)., Design: We used a multiple regression model in which PBF measured with dual energy X-ray absorptiometry was predicted by the reciprocal of BMI (1/BMI; in m(2)/kg) in a sample of 487 men (n(EA) = 192, n(AA) = 148, and n(HA) = 147) and 933 women (n(EA) = 448, n(AA) = 304, and n(HA) = 181)., Results: For men, our results showed no significant differences between HAs and EAs, AAs and EAs, or HAs and AAs in the slope of the line relating 1/BMI to PBF. In women, there were significant differences in PBF as predicted by BMI between HAs and EAs (P < 0.002) and AAs and HAs (P = 0.020), but not between AAs and EAs. When PBF was estimated on the basis of predicting equations, the trend of the predicted PBF value in women differed according to ethnic group and BMI category. At a BMI < 30, HAs tended to have more body fat than did EAs and AAs, and at a BMI > 35, EAs tended to have more body fat than did the other groups., Conclusions: Our results show that the relation between PBF and BMI in HA women differs from that of EA and AA women.

Background The normal-weight BMI range (18.5–24.9 kg/m2) includes adults with body shape and cardiometabolic disease risk features of excess adiposity, although a distinct phenotype developed on a large and diverse sample is lacking. Objective To identify demographic, behavioral, body composition, and health-risk biomarker characteristics of people in the normal-weight BMI range who are at increased risk of developing cardiovascular and metabolic diseases based on body shape. Methods Six nationally representative waist circumference index (WCI, weight/height0.5) prediction formulas, with BMI and age as covariates, were developed using data from 17,359 non-Hispanic (NH) white, NH black, and Mexican-American NHANES 1999–2006 participants. These equations were then used to predict WCI in 5594 NHANES participants whose BMI was within the normal weight range. Men and women in each race/Hispanic-origin group were then separated into high, medium, and low tertiles based on the difference (residual) between measured and predicted WCI. Characteristics were compared across tertiles; P values for significance were adjusted for multiple comparisons. Results Men and women in the high WCI residual tertile, relative to their BMI and age-equivalent counterparts in the low tertile, had significantly lower activity levels; higher percent trunk and total body fat (e.g. NH white men, X ± SE, 25.3 ± 0.2% compared with 20.4 ± 0.2%); lower percent appendicular lean mass (skeletal muscle) and bone mineral content; and higher plasma insulin and triglycerides, higher homeostatic model assessment of insulin resistance (e.g. NH white men, 1.45 ± 0.07 compared with 1.08 ± 0.06), and lower plasma HDL cholesterol. Percent leg fat was also significantly higher in men but lower in women. Similar patterns of variable statistical significance were present within sex and race/ethnic groups. Conclusions Cardiometabolic disease risk related to body shape in people who are normal weight according to BMI is characterized by a distinct phenotype that includes potentially modifiable behavioral health risk factors. [ABSTRACT FROM AUTHOR]

Background/objectives: Three-dimensional optical (3DO) imaging systems that rapidly and accurately provide body shape and composition information are increasingly available in research and clinical settings. Recently, relatively low-cost and space efficient 3DO systems with the ability to report and track individual assessments were introduced to the consumer market for home use. This study critically evaluated the first 3DO imaging device intended for personal operation, the Naked Body Scanner (NBS), against reference methods.Participants/methods: Circumferences at six standardized anatomic sites were measured with a flexible tape in 90 participants ranging in age (5-74 years), ethnicity, and adiposity. Regression analysis and Bland-Altman plots compared these direct measurements and dual-energy X-ray absorptiometry (DXA) %fat estimates to corresponding NBS values. Method precision was analyzed from duplicate anthropometric and NBS measurements in a subgroup of 51 participants.Results: The NBS exhibited greater variation in test-retest reliability (CV, 0.4-2.7%) between the six measured anatomic locations when compared with manually measured counterparts (0.2-0.4%). All six device-derived circumferences correlated with flexible tape references (R2s, 0.84-0.97; p < 0.0001). Measurement bias was apparent for three anatomic sites while mean differences were present for five. The NBS's %fat estimates also correlated with DXA results (R2 = 0.73, p < 0.0001) with no significant bias.Conclusions: This system opens a new era of digital home-based assessments that can be incorporated into weight loss or exercise interventions accessible to clinical investigators as well as individual users. [ABSTRACT FROM AUTHOR]

Purpose Some studies suggest that anthropometric measures of abdominal obesity may be superior to body mass index (BMI) for the prediction of cardiometabolic risk factors; however, most studies have been cross-sectional. Our aim was to prospectively examine the association of change in BMI, waist-to-hip ratio (WHR), waist circumference (WC), and waist circumference-to-height ratio (WCHtR) with change in markers of cardiometabolic risk in a population of postmenopausal women. Methods We used a subsample of participants in the Women's Health Initiative aged 50 to 79 years at entry with available fasting blood samples and anthropometric measurements obtained at multiple time points over 12.8 years of follow-up ( n = 2672). The blood samples were used to measure blood glucose, insulin, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglycerides at baseline, and at years 1, 3, and 6. We conducted mixed-effects linear regression analyses to examine associations at baseline and longitudinal associations between change in anthropometric measures and change in cardiometabolic risk factors, adjusting for covariates. Results In longitudinal analyses, change in BMI, WC, and WCHtR robustly predicted change in cardiometabolic risk, whereas change in WHR did not. The strongest associations were seen for change in triglycerides, glucose, and HDL-C (inverse association). Conclusion Increase in BMI, WC, and WCHtR strongly predicted increases in serum triglycerides and glucose, and reduced HDL-C. WC and WCHtR were superior to BMI in predicting serum glucose, HDL-C, and triglycerides. WCHtR was superior to WC only in predicting serum glucose. BMI, WC, and WCHtR were all superior to WHR. [ABSTRACT FROM AUTHOR]

The mechanisms linking short stature with an increase in cardiovascular and cerebrovascular disease risk remain elusive. This study tested the hypothesis that significant associations are present between height and blood pressure in a representative sample of the US adult population. Participants were 12,988 men and women from a multiethnic sample (age ≥ 18 years) evaluated in the 1999 to 2006 National Health and Nutrition Examination Survey who were not taking antihypertensive medications and who had complete height, weight, % body fat, and systolic and diastolic arterial blood pressure (SBP and DBP) measurements; mean arterial blood pressure and pulse pressure (MBP and PP) were calculated. Multiple regression models for men and women were developed with each blood pressure as dependent variable and height, age, race/ethnicity, body mass index, % body fat, socioeconomic status, activity level, and smoking history as potential independent variables. Greater height was associated with significantly lower SBP and PP, and higher DBP (all P < .001) in combined race/ethnic–sex group models beginning in the 4th decade. Predicted blood pressure differences between people who are short and tall increased thereafter with greater age except for MBP. Socioeconomic status, activity level, and smoking history did not consistently contribute to blood pressure prediction models. Height-associated blood pressure effects were present in US adults who appeared in the 4th decade and increased in magnitude with greater age thereafter. These observations, in the largest and most diverse population sample evaluated to date, provide support for postulated mechanisms linking adult stature with cardiovascular and cerebrovascular disease risk.

Many studies have examined the associations of body mass index (weight (kg)/height (m)2) with risk of various cancers. However, optimal scaling of weight for height may depend on the population studied. The authors used data from a large cohort study of women (Canadian National Breast Cancer Screening Study, 1980–2000; n = 89,835) to examine how the scaling of weight for height (W/Hx) influenced the association with risk of 19 different cancers. Cox proportional hazards models were used to estimate the hazard ratio for each cancer site with W/Hx, with x increasing from 0 to 3.0 by increments of 0.1. The correlation between weight and W/Hx decreased monotonically with increasing x, whereas W/Hx was minimally correlated with height when x = 1.4. W/Hx showed significant positive associations with postmenopausal breast cancer, endometrial cancer, kidney cancer, and lung cancer in never smokers. W/Hx was inversely associated with lung cancer in ever smokers. The value of x for which W/Hx produced the largest statistically significant hazard ratio ranged from 0.8 (endometrial cancer) to 1.7 (postmenopausal breast cancer). For lung cancer in ever smokers, the inverse association was statistically significant for all values of x. These findings suggest that the scaling of weight for height may vary depending on the cancer site and that optimal scaling may be considerably different from W/H2 or, alternatively, that a range of scaling should be considered when examining the association of body weight with risk of disease. [ABSTRACT FROM PUBLISHER]

Summary A footnote in Adolphe Quetelet's classic 1835 Treatise on Man described his algebraic analysis of how body weight (W$$ W $$) varies with height (H$$ H $$) in adult males and females. Using data on 12 short and 12 tall subjects of each sex, Quetelet established the rule that W$$ W $$ is approximately proportional (∝$$ \propto $$) to H2 in adults; that is, W∝H2$$ W\propto {H}^2 $$ when W≈αH2$$ W\approx \alpha {H}^2 $$ for some constant α$$ \alpha $$. Quetelet's Rule (W∝H2$$ W\propto {H}^2 $$), transformed and renamed in the twentieth century to body mass index (BMI=W/H2$$ \mathrm{BMI}=W/{H}^2 $$), is now a globally applied phenotypic descriptor of adiposity at the individual and population level. The journey from footnote to ubiquitous adiposity measure traveled through hundreds of scientific reports and many more lay publications. The recent introduction of highly effective pharmacologic weight loss treatments has heightened scrutiny of BMI's origins and appropriateness as a gateway marker for diagnosing and monitoring people with obesity. This contemporary context prompted the current report that delves into the biological and mathematical paradigms that underlie the simple index BMI=W/H2$$ \mathrm{BMI}=W/{H}^2 $$. Students and practitioners can improve or gain new insights into their understanding of BMI's historical origins and quantitative underpinning from the provided overview, facilitating informed use of BMI and related indices in research and clinical settings. [ABSTRACT FROM AUTHOR]

Numerous studies have documented a U- or J-shaped association between body mass index (BMI) (kg/m2) and mortality, such that increased mortality rate is associated with relatively low and high BMI values. It has been argued elsewhere that the elevated mortality rate observed at lower BMI values actually results from the effects of unmeasured confounding variables, in particular smoking status and preexisting disease. In this paper, the authors present an additional explanation for the phenomenon, i.e., nonspecific measurement. They propose that differential health consequences of fat mass and fat-free mass can be masked by the use of BMI when studied in relation to mortality. To illustrate this point, they use body composition data from 1,137 healthy adults and specify a hypothetical underlying BMI-mortality model in which the logit of death increased linearly with fat mass and decreased linearly with fat-free mass, and % fat increased monotonically with BMI. The results indicate that, even under these specifications, the authors can recover a U-shaped association between BMI and mortality. Consistent with previous suggestions in the literature, future epidemiologic studies that examine the association between adiposity and mortality should prioritize the use of body composition measures. Am J Epidemiol 1997;146:339-49. [ABSTRACT FROM AUTHOR]

Summary: Phenotyping adults for excess adiposity and related health risks usually include three body size measurements: height, weight and waist circumference (WC). Height and weight are now widely used as components of the body shape measure, body mass index (BMI, weight/height2), with the height power referred to as the scaling factor, α. At present, WC is usually not adjusted for height or is expressed as WC/height in which α = 1. Although other α values have been proposed, a critical review of these shape measures is lacking. Here, we examine classical pathways by which the scaling exponent for height used in BMI was developed and then apply this strategy to identify the optimum WC index characteristic of adult shape. Our analyses explored anthropometric, body composition and clinically‐relevant data from US and Korean National Health and Nutrition Surveys. Our findings provide further support for the WC index of WC/height0.5 as having the strongest associations with adiposity while having the weakest correlations with height across non‐Hispanic white and black, Mexican American and Korean men and women. The WC index, defined as WC/height0.5, when combined with BMI, can play an important role when phenotyping adults for excess adiposity and associated health risks in research and clinical settings. [ABSTRACT FROM AUTHOR]

Correction: Following the publication of the original article [1], it was brought to our attention that author Judith Wylie-Rosett was erroneously included as Judith Wylie. [ABSTRACT FROM AUTHOR]