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Objective The purpose of this study was to investigate the association of sodium intake with obesity in US children and adolescents. Methods Cross-sectional data were analyzed for 9,026 children and adolescents in the National Health and Nutrition Examination Survey (NHANES) 2009-2016. Usual sodium intake was estimated from 24-hour dietary recalls using a measurement error model. Logistic regression was used to assess the association of sodium intake with overweight/obesity, obesity, and central obesity (waist to height ratio [WtHR] ≥ 0.5; waist circumferences (WC) ≥ age- and sex-specific 90th percentile). Results Mean (SE) sodium intake was 3,010 (9) and 3,404 (20) mg/d for children and adolescents, respectively. The adjusted odds ratio (AOR) comparing Q4 versus Q1 (87.5th vs. 12.5th percentile of sodium intake) among children was 1.98 (95% CI: 1.19-3.28) for overweight/obesity, 2.20 (1.30-3.73) for obesity, 2.10 (1.12-3.95) for WC ≥ 90th percentile, and 1.68 (0.95-2.97) for WtHR ≥ 0.5, adjusting for demographics, energy, and sugar-sweetened beverage intake. Among adolescents, AOR was 1.81 (0.98-3.37) for overweight/obesity, 1.71 (0.82-3.56) for obesity, 1.62 (0.71-3.66) for WC ≥ 90th percentile, and 1.73 (0.85-3.50) for WtHR ≥ 0.5. Conclusions Sodium intake was positively associated with overweight/obesity, obesity, and central obesity among US children independent of energy and SSB intake, but the association did not reach significance among adolescents.

The 2000 CDC growth charts are based on national data collected between 1963 and 1994 and include a set of selected percentiles between the 3rd and 97th and LMS parameters that can be used to obtai...

BACKGROUND: The association between body mass index (BMI) and adiposity differs by race/ethnicity. OBJECTIVE: To examine differences in adiposity by race/Hispanic origin among US youth and explore how those differences relate to differences in BMI using the most recent national data, including non-Hispanic Asian youth. METHODS: Weight, height, and DXA-derived fat mass index (FMI) and percentage body fat (%BF) from 6923 youth 8-19y in the National Health and Nutrition Examination Survey (NHANES) 2011-2018 were examined. Age-adjusted mean BMI, FMI and %BF were reported. Sex-specific linear regression models predicting %BF and FMI were adjusted for age, BMI category and BMI category*race/Hispanic origin interaction. RESULTS: %BF was highest among Hispanic males (28.2%) and females (35.7%). %BF was lower among non-Hispanic Black (23.9%) compared with non-Hispanic White (26.0%) and non-Hispanic Asian (26.6%) males. There was no difference between non-Hispanic Black females (32.7%) and non-Hispanic White (33.2%) or non-Hispanic Asian (32.7%) females. FMI was higher among Hispanic youth compared with non-Hispanic White youth. Among youth with underweight/healthy weight, predicted %BF and FMI were lower among non-Hispanic Black males (−2.8%; −0.5) and females (−2.0%; −0.3), compared with non-Hispanic White youth, and higher among Hispanic males (0.9%; 0.2) and females (2.0%; 0.5), while %BF but not FMI was higher among non-Hispanic Asian males (1.3%) and females (1.4%). Among females with obesity, non-Hispanic Asian females had lower %BF (−2.3%) and FMI (−1.7) than non-Hispanic White females. CONCLUSIONS: Differences in %BF and FMI by race/Hispanic origin were not consistent by BMI category among U.S. youth in 2011-2018.

Objective-This report presents trends in mean weight, recumbent length, height, waist circumference, and body mass index (BMI) among children and adolescents in the United States from 1999 through 2018.

This report presents trends in mean weight, recumbent length, height, waist circumference, and body mass index among children and adolescents in the United States from 1999 through 2018.

BMI z (BMIz) score based on the Centers for Disease Control and Prevention growth charts is widely used, but it is inaccurate above the 97th percentile. We explored the performance of alternative metrics based on the absolute distance or % distance of a child’s BMI from the median BMI for sex and age. We used longitudinal data from 5628 children who were first examined 3 years. The ICCs of the age-adjusted metrics were also higher compared with that of BMIz among children who were overweight or obese. Unlike BMIz, these alternative metrics do not have an upper limit and can be used for assessing BMI in all children, even those with very high BMIs. The age-adjusted % from median (on a log or linear scale) works well for all ages, while unadjusted % from median is better limited to older children or short follow-up periods.

Based on nationally representative anthropometric data, the National Center for Health Statistics (NCHS) has published reference tables on the distribution of various body measurements for the U.S. population (1-5). National Health and Nutrition Examination Survey (NHANES) data are the primary source of body measurement information for the U.S. population. These measurements reflect the mean weight, height, length, and various circumferences of U.S. children and adults. Anthropometry is a measure of nutritional or general health status, dietary adequacy, and growth. This report presents anthropometric reference data from the years 2015-2018 for U.S. children and adults.

Objective Although the Centers for Disease Control and Prevention (CDC) growth charts are widely used, BMI-for-age z-Scores (BMIz) are known to be uninformative above the 97th percentile. This study compared the relations of BMIz and other BMI metrics (%BMIp95, percent of 95th percentile, and ΔBMIp95, BMI minus 95th percentile) to circumferences, skinfolds, and fat mass. We were particularly interested in the differences among children with severe obesity (%BMIp95 ≥ 120). Methods Data was used from 30,003 2- to 19-year-olds who were examined from 1999-2000 through 2013-2014 in the National Health and Nutrition Examination Survey (NHANES). Results The theoretical maximum BMIz based on the growth charts varied by more than threefold across ages. The BMI metrics were strongly intercorrelated, but BMIz was less strongly related to the adiposity measures than were ΔBMIp95 and %BMIp95. Among children with severe obesity, circumferences and triceps skinfold showed almost no association with BMIz (r ≤ 0.10), whereas associations with %BMIp95 and ΔBMIp95 ranged from r = 0.32 to 0.79. Corresponding associations with fat mass ÷ height2 ranged from r = 0.40 (BMIz) to r =0.82 (%BMIp95) among 8- to 19-year-olds. Conclusions Among children with severe obesity, BMIz is only weakly associated with other measures of body fatness. Very high BMIs should be expressed relative to the CDC 95th percentile, particularly in studies that evaluate obesity interventions.

Objective Although the CDC growth charts are widely used, BMIz is known to be uninformative above the 97th percentile. We compared the relations of BMIz and other BMI metrics (%BMIp95, percent of 95th percentile, and ΔBMIp95, BMI minus 95th percentile) to circumferences, skinfolds and fat mass. We were particularly interested in the differences among children with severe obesity (%BMIp95 ≥ 120). Methods We used data from 30,003 2- to 19-year-olds who were examined from 1999-2000 through 2013-14 in NHANES. Results The theoretical maximum BMIz based on the growth charts varied by more than 3-fold across ages. The BMI metrics were strongly intercorrelated, but BMIz was less strongly related to the adiposity measures than were ΔBMIp95 and %BMIp95. Among children with severe obesity, circumferences and triceps skinfold showed almost no association with BMIz (r ≤ 0.10), whereas associations with %BMIp95 and ΔBMIp95 ranged from r=0.32 to 0.79. Corresponding associations with fat mass ÷ height2 ranged from r=0.40 (BMIz) to r=0.82 (%BMIp95) among 8- to 19-year-olds. Conclusions Among children with severe obesity, BMIz is only weakly associated with other measures of body fatness. Very high BMIs should be expressed relative to the CDC 95th percentile, particularly in studies that evaluate obesity interventions.

Background Although the prevalence of a body mass index [BMI (in kg/m2)] ≥30 has tripled among US adults since the 1960s, BMI is only moderately correlated with body fatness. Because skinfolds can more accurately estimate body fatness than can BMI, it is possible that skinfolds could be useful in monitoring secular trends in body fatness. Objective We examined whether there were similar secular trends for skinfolds (triceps and subscapular), BMI, and waist circumference between US adults. Design This study was an analysis of 45,754 adults who participated in the NHANES from 1988-1994 through 2009-2010. Approximately 19% of the subjects were missing ≥1 skinfold-thickness measurement. These missing values were imputed from other characteristics. Results Trends in mean levels and in the prevalence of high levels of the 4 body size measures were fairly similar between men, with mean levels increasing by ≥5% from 1988-1994 through 2009-2010. Slightly larger increases were seen in women for BMI and waist circumference (7-8%), but trends in skinfolds were markedly different. The mean triceps skinfold, for example, increased by 2 mm through 2003-2004, but subsequently decreased so that the mean in 2009-2010 did not differ from that in 1988-1994. Compared with obese women in 1988-1994, the mean BMI of obese women in 2009-2010 was 1 higher, but mean levels of both skinfolds were 5-10% lower. Conclusions Although there were fairly similar trends in levels of BMI, waist circumference, and skinfold thicknesses in men in the United States from 1988-1994 through 2009-2010, there were substantial differences in women. Our results indicate that it is unlikely that skinfold thicknesses could be used to monitor trends in obesity.

BMI z (BMIz) score based on the Centers for Disease Control and Prevention growth charts is widely used, but it is inaccurate above the 97th percentile. We explored the performance of alternative metrics based on the absolute distance or % distance of a child's BMI from the median BMI for sex and age. We used longitudinal data from 5628 children who were first examined12 years to compare the tracking of three BMI metrics: distance from median, % distance from median and % distance from median on a log scale. We also explored the effects of adjusting these metrics for age differences in the distribution of BMI. The intraclass correlation coefficient (ICC) was used to compare tracking of the metrics. Metrics based on % distance (whether on the original or log scale) yielded higher ICCs compared with distance from median. The ICCs of the age-adjusted metrics were higher than that of the unadjusted metrics, particularly among children who were (1) overweight or had obesity, (2) younger and (3) followed for3 years. The ICCs of the age-adjusted metrics were also higher compared with that of BMIz among children who were overweight or obese. Unlike BMIz, these alternative metrics do not have an upper limit and can be used for assessing BMI in all children, even those with very high BMIs. The age-adjusted % from median (on a log or linear scale) works well for all ages, while unadjusted % from median is better limited to older children or short follow-up periods.

Objective The aim of this study was to compare national estimates of self-reported and measured height and weight, BMI, and obesity prevalence among adults from US surveys. Methods Self-reported height and weight data came from the National Health and Nutrition Examination Survey (NHANES), the National Health Interview Survey, and the Behavioral Risk Factor Surveillance System for the years 1999 to 2016. Measured height and weight data were available from NHANES. BMI was calculated from height and weight; obesity was defined as BMI ≥ 30. Results In all three surveys, mean self-reported height was higher than mean measured height in NHANES for both men and women. Mean BMI from self-reported data was lower than mean BMI from measured data across all surveys. For women, mean self-reported weight, BMI, and obesity prevalence in the National Health Interview Survey and Behavioral Risk Factor Surveillance System were lower than self-report in NHANES. The distribution of BMI was narrower for self-reported than for measured data, leading to lower estimates of obesity prevalence. Conclusions Self-reported height, weight, BMI, and obesity prevalence were not identical across the three surveys, particularly for women. Patterns of misreporting of height and weight and their effects on BMI and obesity prevalence are complex.

Background Both excessive sodium intake and obesity are risk factors for hypertension and cardiovascular disease. The association between sodium intake and obesity is unclear, with few studies assessing sodium intake using 24-h urine collection. Objectives Our objective was to assess the association between usual 24-h sodium excretion and measures of adiposity among US adults. Methods Cross-sectional data were analyzed from a sample of 730 nonpregnant participants aged 20-69 y who provided up to 2 complete 24-h urine specimens in the NHANES 2014 and had data on overweight or obesity [body mass index (kg/m2) ≥25] and central adiposity [waist circumference (WC): >88 cm for women, >102 cm for men]. Measurement error models were used to estimate usual sodium excretion, and multiple linear and logistic regression models were used to assess its associations with measures of adiposity, adjusting for sociodemographic, health, and dietary variables [i.e., energy intake or sugar-sweetened beverage (SSB) intake]. All analyses accounted for the complex survey sample design. Results Unadjusted mean ± SE usual sodium excretion was 3727 ± 43.5 mg/d and 3145 ± 55.0 mg/d among participants with and without overweight/obesity and 3653 ± 58.1 mg/d and 3443 ± 35.3 mg/d among participants with or without central adiposity, respectively. A 1000-mg/d higher sodium excretion was significantly associated with 3.8-units higher BMI (95% CI: 2.8, 4.8) and a 9.2-cm greater WC (95% CI: 6.9, 11.5 cm) adjusted for covariates. Compared with participants in the lowest quartile of sodium excretion, the adjusted prevalence ratios in the highest quartile were 1.93 (95% CI: 1.69, 2.20) for overweight/obesity and 2.07 (95% CI: 1.74, 2.46) for central adiposity. The associations also were significant when adjusting for SSBs, instead of energy, in models. Conclusions Higher usual sodium excretion is associated with overweight/obesity and central adiposity among US adults.

Importance Differences in obesity by sex, age group, race and Hispanic origin among US adults have been reported, but differences by urbanization level have been less studied. Objectives To provide estimates of obesity by demographic characteristics and urbanization level and to examine trends in obesity prevalence by urbanization level. Design, Setting, and Participants Serial cross-sectional analysis of measured height and weight among adults aged 20 years or older in the 2001-2016 National Health and Nutrition Examination Survey, a nationally representative survey of the civilian, noninstitutionalized US population. Exposures Sex, age group, race and Hispanic origin, education level, smoking status, and urbanization level as assessed by metropolitan statistical areas (MSAs; large: ≥1 million population). Main Outcomes and Measures Prevalence of obesity (body mass index [BMI] ≥30) and severe obesity (BMI ≥40) by subgroups in 2013-2016 and trends by urbanization level between 2001-2004 and 2013-2016. Results Complete data on weight, height, and urbanization level were available for 10 792 adults (mean age, 48 years; 51% female [weighted]). During 2013-2016, 38.9% (95% CI, 37.0% to 40.7%) of US adults had obesity and 7.6% (95% CI, 6.8% to 8.6%) had severe obesity. Men living in medium or small MSAs had a higher age-adjusted prevalence of obesity compared with men living in large MSAs (42.4% vs 31.8%, respectively; adjusted difference, 9.8 percentage points [95% CI, 5.1 to 14.5 percentage points]); however, the age-adjusted prevalence among men living in non-MSAs was not significantly different compared with men living in large MSAs (38.9% vs 31.8%, respectively; adjusted difference, 4.8 percentage points [95% CI, −2.9 to 12.6 percentage points]). The age-adjusted prevalence of obesity was higher among women living in medium or small MSAs compared with women living in large MSAs (42.5% vs 38.1%, respectively; adjusted difference, 4.3 percentage points [95% CI, 0.2 to 8.5 percentage points]) and among women living in non-MSAs compared with women living in large MSAs (47.2% vs 38.1%, respectively; adjusted difference, 4.7 percentage points [95% CI, 0.2 to 9.3 percentage points]). Similar patterns were seen for severe obesity except that the difference between men living in large MSAs compared with non-MSAs was significant. The age-adjusted prevalence of obesity and severe obesity also varied significantly by age group, race and Hispanic origin, and education level, and these patterns of variation were often different by sex. Between 2001-2004 and 2013-2016, the age-adjusted prevalence of obesity and severe obesity significantly increased among all adults at all urbanization levels. Conclusions and Relevance In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity and severe obesity in 2013-2016 varied by level of urbanization, with significantly greater prevalence of obesity and severe obesity among adults living in nonmetropolitan statistical areas compared with adults living in large metropolitan statistical areas.

Importance Differences in childhood obesity by demographics and urbanization have been reported. Objective To present data on obesity and severe obesity among US youth by demographics and urbanization and to investigate trends by urbanization. Design, Setting, and Participants Measured weight and height among youth aged 2 to 19 years in the 2001-2016 National Health and Nutrition Examination Surveys, which are serial, cross-sectional, nationally representative surveys of the civilian, noninstitutionalized population. Exposures Sex, age, race and Hispanic origin, education of household head, and urbanization, as assessed by metropolitan statistical areas (MSAs; large: ≥ 1 million population). Main Outcomes and Measures Prevalence of obesity (body mass index [BMI] ≥95th percentile of US Centers for Disease Control and Prevention [CDC] growth charts) and severe obesity (BMI ≥120% of 95th percentile) by subgroups in 2013-2016 and trends by urbanization between 2001-2004 and 2013-2016. Results Complete data on weight, height, and urbanization were available for 6863 children and adolescents (mean age, 11 years; female, 49%). In 2013-2016, the prevalence among youth aged 2 to 19 years was 17.8% (95% CI, 16.1%-19.6%) for obesity and 5.8% (95% CI, 4.8%-6.9%) for severe obesity. Prevalence of obesity in large MSAs (17.1% [95% CI, 14.9%-19.5%]), medium or small MSAs (17.2% [95% CI, 14.5%-20.2%]) and non-MSAs (21.7% [95% CI, 16.1%-28.1%]) were not significantly different from each other (range of pairwise comparisons P = .09-.96). Severe obesity was significantly higher in non-MSAs (9.4% [95% CI, 5.7%-14.4%]) compared with large MSAs (5.1% [95% CI, 4.1%-6.2%]; P = .02). In adjusted analyses, obesity and severe obesity significantly increased with greater age and lower education of household head, and severe obesity increased with lower level of urbanization. Compared with non-Hispanic white youth, obesity and severe obesity prevalence were significantly higher among non-Hispanic black and Hispanic youth. Severe obesity, but not obesity, was significantly lower among non-Hispanic Asian youth than among non-Hispanic white youth. There were no significant linear or quadratic trends in obesity or severe obesity prevalence from 2001-2004 to 2013-2016 for any urbanization category ( P range = .07-.83). Conclusions and Relevance In 2013-2016, there were differences in the prevalence of obesity and severe obesity by age, race and Hispanic origin, and household education, and severe obesity was inversely associated with urbanization. Demographics were not related to the urbanization findings.

Obesity is associated with serious health risks. Monitoring obesity prevalence is relevant for public health programs that focus on reducing or preventing obesity. Between 2003–2004 and 2013–2014, there were no significant changes in childhood obesity prevalence, but adults showed an increasing trend. This report provides the most recent national estimates from 2015–2016 on obesity prevalence by sex, age, and race and Hispanic origin, and overall estimates from 1999–2000 through 2015–2016.

Objective To examine the associations among several body mass index (BMI) metrics ( z -scores, percent of the 95th percentile (%BMI p95 ) and BMI minus 95th percentile (ΔBMI p95 ) as calculated in the growth charts from the Centers for Disease Control and Prevention (CDC). It is known that the widely used BMI z -scores (BMIz) and percentiles calculated from the growth charts can differ substantially from those that directly observed in the data for BMIs above the 97th percentile ( z = 1.88). Study design Cross-sectional analyses of 8.7 million 2- to 4-year-old children who were examined from 2008 through 2011 in the CDC's Pediatric Nutrition Surveillance System. Results Because of the transformation used to calculate z -scores, the theoretical maximum BMIz varied by >3-fold across ages. This results in the conversion of very high BMIs into a narrow range of z -scores that varied by sex and age. Among children with severe obesity, levels of BMIz were only moderately correlated (r ~ 0.5) with %BMI p95 and ΔBMI p95 . Among these children with severe obesity, BMIz levels could differ by more than 1 SD among children who had very similar levels of BMI, %BMI p95 and ΔBMI p95 due to differences in age or sex. Conclusions The effective upper limit of BMIz values calculated from the CDC growth charts, which varies by sex and age, strongly influences the calculation of z -scores for children with severe obesity. Expressing these very high BMIs relative to the CDC 95th percentile, either as a difference or percentage, would be preferable to using BMI-for-age, particularly when assessing the effectiveness of interventions.

SummaryBackground Few studies have assessed how well body mass index (BMI), waist circumference (WC), or waist to height ratio (WtHR) perform in identifying cardio-metabolic risk among youth. Objective The objective of this study was to evaluate the utility of BMI and WC percentiles and WtHR to distinguish adolescents with and without cardio-metabolic risk. Methods A cross-sectional analysis of data from 6097 adolescents aged 10–13 years who participated in the HEALTHY study was conducted. Receiver operating characteristic curves determined the discriminatory ability of BMI and WC percentiles and WtHR. Results The discriminatory ability of BMI percentile was good (area under the curve [AUC] ≥ 0.80) for elevated insulin and clustering of ≥3 risk factors, with optimal cut-points of 96 and 95, respectively. BMI percentile performed poor to fair (AUC = 0.57–0.75) in identifying youth with the majority of individual risk factors examined (elevated glucose, total cholesterol, low-density lipoprotein, blood pressure, triglycerides and high-density lipoprotein). WC percentile and WtHR performed similarly to BMI percentile. Conclusions The current definition of obesity among US children performs well at identifying adolescents with elevated insulin and a clustering of ≥3 cardio-metabolic risk factors. Evidence does not support WC percentile or WtHR as superior screening tools compared with BMI percentile for identifying cardio-metabolic risk.

BACKGROUND AND OBJECTIVES:Regular aerobic and muscle-strengthening physical activity in youth has been positively associated with health and may help prevent obesity. The purpose of this study is to provide reference values on 4 core, upper, and lower body measures of muscle strength among US children and adolescents and to investigate the association between these measures of strength and weight status.METHODS:We assessed muscular strength using 4 different tests (plank, modified pull-up, knee extension, and grip strength) in 1224 youth aged 6 to 15 years collected during the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey. Mean and median estimates are provided by gender, age, and weight status. Weight status was defined based on standard categories of obesity, overweight, normal weight, and underweight using the gender-specific BMI-for-age Centers for Disease Control and Prevention growth charts.RESULTS:There were significant positive trends with age for each of the strength tests (P < .001) except the modified pull-up among girls. The length of time the plank was held decreased as weight status increased for both girls and boys (P < .001). As weight status increased the number of modified pull-ups decreased (P < .001 boys and girls). Scores on the knee extension increased as weight status increased (P < .01). Grip strength increased as weight status increased (P < .01).CONCLUSIONS:Increasing weight status had a negative association with measures of strength that involved lifting the body, but was associated with improved performances on tests that did not involve lifting the body.

Objective: A recent, cross-sectional analysis of adults found that the hip circumference divided by height1.5 minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X-ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease. Design and Methods: Cross-sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988-1994. Results: As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p < 0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race-ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels. Conclusions: Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.

Terminology and measures used in studies of weight and adiposity in children can be complex and confusing. Differences arise in metrics, terminology, reference values, and reference levels. Most studies depend on body mass index (BMI) calculated from weight and height, rather than on more direct measures of body fatness. Definitions of overweight and obesity are generally statistical rather than risk-based and use a variety of different reference data sets for BMI. As a result, different definitions often do not give the same results. A basic problem is the lack of strong evidence for any one particular definition. Rather than formulate the question as being one of how to define obesity, it might be useful to consider what BMI cut-points best predict future health risks and how efficiently to screen for such risks. The answers may be different for different populations. In addition, rather than depending solely on BMI to make screening decisions, it is likely to be useful to also consider other factors, including not only race-ethnicity, sex and age, but also factors such as family history. Despite their limitations, BMI-based definitions of overweight and obesity provide working practical definitions that are valuable for general public health surveillance and screening.

Background: The 2000 Centers for Disease Control and Prevention (CDC) growth charts included lambda-mu-sigma (LMS) parameters intended to calculate smoothed percentiles from only the 3rd to the 97th percentile. Objective: The objective was to evaluate different approaches to describing more extreme values of BMI-for-age by using simple functions of the CDC growth charts. Design: Empirical data for the 99th and the 1st percentiles of body mass index (BMI)-for-age were calculated from the data set used to construct the growth charts and were compared with estimates extrapolated from the CDC-supplied LMS parameters and to various functions of other smoothed percentiles. A set of reestimated LMS parameters that incorporated a smoothed 99th percentile were also evaluated. Results: Extreme percentiles extrapolated from the CDC-supplied LMS parameters did not match well to the empirical data for the 99th percentile. A better fit to the empirical data was obtained by using 120% of the smoothed 95th percentile. The empirical first percentile was reasonably well approximated by extrapolations from the LMS values. The reestimated LMS parameters had several drawbacks and no clear advantages. Conclusions: Several approximations can be used to describe extreme high values of BMI-for-age with the use of the CDC growth charts. Extrapolation from the CDC-supplied LMS parameters does not provide a good fit to the empirical 99th percentile values. Simple approximations to high values as percentages of the existing smoothed percentiles have some practical advantages over imputation of very high percentiles. The expression of high BMI values as a percentage of the 95th percentile can provide a flexible approach to describing and tracking heavier children. Am J Clin Nutr doi: 10.3945/ajcn.2009.28335.

Parent-reported height and weight are often used to estimate BMI and overweight status among children. The quality of parent-reported data has not been compared to measured data on a national scale for all race/ethnic groups in the United States. Parent-reported height and weight for 2-17-year-old children in two national health interview surveys--the 1999-2004 National Health Interview Survey (NHIS) and the 2003-2004 National Survey of Children's Health (NSCH)--were compared to measured values from a national examination survey-the 1999-2004 National Health and Nutrition Examination Survey (NHANES). Compared to measured data, parent-reported data overestimated childhood overweight in both interview surveys. For example, overweight prevalence among 2-17-year-olds was 25% (s.e. 0.2) using parent-reported NHIS data vs. 16% (s.e. 0.6) using measured NHANES data. Parent-reported data overestimated overweight among younger children, but underestimated overweight among older children. The discrepancy between reported and measured estimates arose mainly from reported height among very young children. For children aged 2-11 years, the mean reported height from NHIS was 3-6 cm less than mean measured height from NHANES (P < 0.001) vs. no difference among children aged 16-17 years. Measured data remains the gold standard for surveillance of childhood overweight. Although this analysis compared mean values from survey populations rather than parent-reported and measured data for individuals, the results from nationally representative data reinforce previous recommendations based on small samples that parent-reported data should not be used to estimate overweight prevalence among preschool and elementary school-aged children.

Background: Body mass index (BMI), waist circumference (WC), and the waist-stature ratio (WSR) are considered to be possible proxies for adiposity. Objective: The objective was to investigate the relations between BMI, WC, WSR, and percentage body fat (measured by dual-energy X-ray absorptiometry) in adults in a large nationally representative US population sample from the National Health and Nutrition Examination Survey (NHANES). Design: BMI, WC, and WSR were compared with percentage body fat in a sample of 12,901 adults. Results: WC, WSR, and BMI were significantly more correlated with each other than with percentage body fat (P < 0.0001 for all sex-age groups). Percentage body fat tended to be significantly more correlated with WC than with BMI in men but significantly more correlated with BMI than with WC in women (P < 0.0001 except in the oldest age group). WSR tended to be slightly more correlated with percentage body fat than was WC. Percentile values of BMI, WC, and WSR are shown that correspond to percentiles of percentage body fat increments of 5 percentage points. More than 90% of the sample could be categorized to within one category of percentage body fat by each measure. Conclusions: BMI, WC, and WSR perform similarly as indicators of body fatness and are more closely related to each other than with percentage body fat. These variables may be an inaccurate measure of percentage body fat for an individual, but they correspond fairly well overall with percentage body fat within sex-age groups and distinguish categories of percentage body fat.

To compare the prevalence of shortness, underweight, and overweight by using the Centers for Disease Control and Prevention (CDC) 2000 and the World Health Organization (WHO) 2006 growth charts. These comparisons are undertaken with 2 sets of cutoff values.Data from the National Health and Nutrition Examination Survey 1999-2004 were used to calculate the prevalence estimates in US children aged 0 to 59 months (n = 3920). Cutoff values commonly used in the United States, on the basis of the 5th percentile of height-for-age to define shortness, the 5th percentile of weight-for-height or weight-for-age to define underweight, and the 95th percentile of weight-for-height or body mass index-for-age to define overweight were compared with the cutoff values recommended by WHO, which use-2 z-score (equivalent to 2.3rd percentile) to define shortness and underweight andor=2 z-score (equivalent to 97.7th percentile) to define overweight. A comparison with the same cutoff values (5th and 95th) in the 2 charts was also performed.Applying the 5th or 95th percentile, we observed a higher prevalence of shortness and overweight for all the age groups when the WHO 2006 growth charts were used than when the CDC 2000 growth charts were used. Applying the 5th percentile to the WHO 2006 charts produced lower rates of underweight than did the CDC 2000 charts. However, applying the 5th or 95th percentiles to the CDC 2000 charts and the WHO-recommended cutoff values of -2 or +2 z-score to the WHO charts produced smaller differences in the prevalence of shortness and overweight than were seen when the 5th and 95th percentiles were applied to both the CDC and WHO charts.Estimates of the prevalence of key descriptors of growth in children aged 0 to 59 months vary by the chart used and the cutoff values applied. The use of the 5th and 95th percentiles for the CDC growth charts and the 2.3rd and 97.7th percentiles for the WHO growth charts appear comparable in the prevalence of shortness and overweight, but not underweight. If practitioners were to use the WHO growth charts, it might be more appropriate to adopt the WHO recommended cutoff values as well, but this would be a change for office practice.

Although the body mass index (BMI, kg m(-2)) is widely used as a measure of adiposity, it is a measure of excess weight, rather than excess body fat. It has been suggested that skinfold thicknesses be measured among overweight children to confirm the presence of excess adiposity.The present study examined the additional information provided by skinfold thicknesses on body fatness, beyond that conveyed by BMI-for-age, among healthy 5- to 18-years old (n = 1196).Total body dual-energy X-ray absorptiometry (DXA) provided estimates of % body fat, and the sum of two skinfolds (triceps and subscapular) was used as an indicator of the overall skinfold thickness.As assessed by the multiple R(2)s and the residuals of various regression models, information on the skinfold sum significantly ( p0.001) improved the prediction of body fatness beyond that obtained with BMI-for-age. For example, the use of the skinfold sum, in addition to BMI-for-age, increased the multiple R(2)s for predicting % body fat from 0.81 to 0.90 (boys), and from 0.82 to 0.89 (girls). The use of the skinfold sum also reduced the overall prediction errors (absolute value of the residuals) for % body fat by 20-30%, but these reductions varied substantially by BMI-for-age. Among overweight children, defined by a BMI-for-age/=95th percentile, the skinfold sum reduced the predication errors for % body fat by only 7-9%.Although skinfold thicknesses, when used in addition to BMI-for-age, can substantially improve the estimation of body fatness, the improvement among overweight children is small.

INTRODUCTION: Although decline in muscle mass and quality and resulting declines in muscle strength are associated with aging, more research is needed in general populations to assess the utility of handgrip strength as an indicator of muscle strength and cardiovascular disease risk. METHODS: Data from 4,221 participants aged ≥20 years in the 2011–2012 cycle of National Health and Nutrition Examination Survey were analyzed during 2014–2015. Standing isometric relative handgrip strength (calculated as maximal absolute handgrip strength from both hands divided by BMI) was used to predict cardiovascular biomarkers, including blood pressure (measured systolic and diastolic blood pressure); serum lipids (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides); and plasma insulin and glucose. RESULTS: Results from regression analyses showed that higher relative grip strength was significantly associated with lower systolic blood pressure, triglycerides, and plasma insulin and glucose, and higher high-density lipoprotein cholesterol in male and female participants (p

Objective-This report presents national anthropometric reference data for all ages of the U.S. population in 2003-2006, adding to results published previously from 1960-2002. Methods-Data are from the National Health and Nutrition Examination Survey (NHANES), a complex, stratified, and multistage probability sample of the civilian, noninstitutionalized U.S. population. Anthropometry measurements were obtained from 19,593 survey participants. The anthropometric measures included weight, height, recumbent length, circumferences, limb lengths, and skinfold thickness measurements. Results-The tables in this report include weighted population means, standard errors of the means, and selected percentiles of body measurement values. Because measurements varied by sex and age (as well as race and ethnicity in adults), results are reported by these subgroups. Conclusions-These latest NHANES data add to the knowledge about trends in child growth and development and trends in the distribution of body measurements, such as weight and height, in the U.S. population .

The availability of epidemiologic data on childhood obesity has increased in response to public health concerns regarding childhood obesity trends. For example, researchers in several nations have begun to collect school surveillance data to monitor the prevalence of childhood obesity (1–5). Data quality can be variable (6), and researchers investigating obesity must address how to identify biologically implausible values (BIVs) in anthropometric data (height, weight, body mass index (BMI)). This may be of particular concern because height and weight measurements often are collected in non–research settings such as schools and when summarizing very high BMI values. In addition, a unique set of criteria may be needed for longitudinal studies to address biologically implausible change over time, such as weight loss/gain and shrinking/large height changes. The methodological process of identifying BIVs, 1 possible source of measurement error, has not been explored, and researchers have utilized a variety of methods that have not been compared or evaluated. It is not yet known how different methods for the identification of BIVs may affect study results or how often the issue of BIVs is addressed in large epidemiologic studies. Appropriate identification of BIVs will help to minimize measurement error, particularly data-recording and -entry errors, which may otherwise be more difficult to identify (6). Therefore, the current study aimed 1) to track how often large epidemiologic studies in youth address the issue of BIVs, 2) to review available methods for addressing cross-sectional and longitudinal BIVs in youth anthropometric data, and 3) to apply each unique set of BIV criteria to a large longitudinal data set from Get Healthy Philly of low-income minority youth and compare the effects on weight status and BIV prevalence estimates.

Studies in a variety of countries have shown increases in the prevalence of overweight among children in recent years. These increases have given rise to concern about children's health and well-being. The terminology used in these studies varies considerably. However, whatever the terminology used, such studies are generally based on weight [expressed as body mass index (BMI), a measure of weight for height, calculated as weight in kilograms divided by the square of height in meters] and not on body fatness per se. There are many different BMI references that can be used to define childhood overweight or obesity. Children are defined as overweight for population surveillance purposes using a variety of BMI cut points. BMI is a screening tool, not a diagnostic tool. Children with a BMI over these cut points do not necessarily have clinical complications or health risks related to overfatness. More in-depth assessment of individual children is required to ascertain health status. The definitions of overweight generally used are working definitions that are valuable for general public health surveillance, screening and similar purposes.

Objectives: The prevalence of childhood overweight in the United States has markedly increased over the last 30 years. We examined differences in the secular trends for BMI, weight, and height among white, black, and Mexican-American children. Research Methods and Procedures: Analyses were based on nationally representative data collected from 2 to 17 year olds in four examinations (1971–1974 through 1999–2002). Results: Overall, black children experienced much larger secular increases in BMI, weight, and height than did white children. For example, over the 30-year period, the prevalence of overweight increased ∼3-fold (4% to 13%) among 6- to 11-year-old white children but 5-fold (4% to 20%) among black children. In most sex-age groups, Mexican-American children experienced increases in BMI and overweight that were between those experienced by blacks and whites. Race/ethnicity differences were less marked among 2 to 5 year olds, and in this age group, white children experienced the largest increase in overweight (from 4% to 9%). In 1999–2002, the prevalence of extreme BMI levels (≥99th percentile) reached 6% to 7% among black girls and Mexican-American boys. Discussion: Because of the strong tracking of childhood BMI levels into adulthood, it is likely that the secular increases in childhood overweight will greatly increase the burden of adult disease. The further development of obesity interventions in different racial/ethnic groups should be emphasized.

The prevalence of overweight, as assessed by a high body mass index (kg/m), has greatly increased among children and adolescents over the last three decades. Because body mass index is a measure of excess weight rather than excess body fatness, it is important to understand the ability of a high level to identify children who truly have excess adiposity. This review covers the measurement and classification of overweight and obesity, the expression of body composition data, and the relation of body mass index to adiposity.Although adiposity has typically been expressed as percentage body fat, the use of the fat mass index (fat mass/height) and the fat-free mass index (fat-free mass/height) may provide more information. For example, body mass index differences among relatively thin children have been found to largely reflect differences in fat-free mass index, whereas differences among relatively heavy children are primarily due to differences in fat mass index. In addition, the ability of overweight to identify obese children is greatly influenced by the cutpoints selected for body mass index and adiposity. The use of inappropriate cutpoints, rather than the limitations of body mass index, may account for the frequently reported finding that many obese children are not overweight.The use of fat mass index and fat-free mass index in expressing body composition data allows one to easily assess the contribution of each to body mass index. If appropriate cutpoints are used, a high body mass index level is a moderately sensitive and a very specific indicator of excess adiposity among children.

Overweight and obesity have been increasing in many countries. Our objective is to describe the trends in overweight and obesity occurring in the Mexican-American population in the United States. Data on measured height and weight for Mexican Americans come from the following surveys: the Hispanic Health and Nutrition Examination Survey (HHANES, 1982-84), the Third National Health and Nutrition Examination Survey (NHANES III, 1988-94), and NHANES 1999-2002. In 1999-2002, 73% of Mexican-American adults were overweight and 33% were obese. Obesity increased between NHANES III and NHANES 1999-2002, from 24% to 27% for men and from 35% to 38% for women. Increases were also seen for children and adolescents. The Mexican-American population in the United States, both children and adults, is showing trends in overweight and obesity over time that are similar to those seen in other segments of the U.S. population and indeed in many countries.

Because of the recognized benefits of exclusive breastfeeding,1–7 the American Academy of Pediatrics and the World Health Organization strongly encourage exclusive breastfeeding for the first 6 months of life.7,8 Unfortunately, national goals for exclusive breastfeeding in the United States are not yet established, at least in part because of a lack of data. The Third National Health and Nutrition Examination Survey (NHANES III) sample is nationally representative and particularly valuable in providing data on exclusive breastfeeding. We used NHANES III data to examine the prevalence of exclusive breastfeeding among US infants to obtain baseline data for program evaluation and public health policymaking.

Background Food insecurity can put children at greater risk of obesity because of altered food choices and nonuniform consumption patterns. Objective We examined the association between obesity and both child-level food insecurity and personal food insecurity in US children. Design Data from 9,701 participants in the National Health and Nutrition Examination Survey, 2001-2010, aged 2 to 11 years were analyzed. Child-level food insecurity was assessed with the US Department of Agriculture's Food Security Survey Module based on eight child-specific questions. Personal food insecurity was assessed with five additional questions. Obesity was defined, using physical measurements, as body mass index (calculated as kg/m 2 ) greater than or equal to the age- and sex-specific 95th percentile of the Centers for Disease Control and Prevention growth charts. Logistic regressions adjusted for sex, race/ethnic group, poverty level, and survey year were conducted to describe associations between obesity and food insecurity. Results Obesity was significantly associated with personal food insecurity for children aged 6 to 11 years (odds ratio=1.81; 95% CI 1.33 to 2.48), but not in children aged 2 to 5 years (odds ratio=0.88; 95% CI 0.51 to 1.51). Child-level food insecurity was not associated with obesity among 2- to 5-year-olds or 6- to 11-year-olds. Conclusions Personal food insecurity is associated with an increased risk of obesity only in children aged 6 to 11 years. Personal food-insecurity measures may give different results than aggregate food-insecurity measures in children.

Background The sagittal abdominal diameter (SAD) measured in supine position is an alternative adiposity indicator that estimates the quantity of dysfunctional adipose tissue in the visceral depot. However, supine SAD’s distribution and its association with health risk at the population level are unknown. Here we describe standardized measurements of SAD, provide the first, national estimates of the SAD distribution among US adults, and test associations of SAD and other adiposity indicators with prevalent dysglycemia. Methods and Findings In the 2011–2012 National Health and Nutrition Examination Survey, supine SAD was measured (“abdominal height”) between arms of a sliding-beam caliper at the level of the iliac crests. From 4817 non-pregnant adults (age ≥20; response rate 88%) we used sample weights to estimate SAD’s population distribution by sex and age groups. SAD’s population mean was 22.5 cm [95% confidence interval 22.2–22.8]; median was 21.9 cm [21.6–22.4]. The mean and median values of SAD were greater for men than women. For the subpopulation without diagnosed diabetes, we compared the abilities of SAD, waist circumference (WC), and body mass index (BMI, kg/m2) to identify prevalent dysglycemia (HbA1c ≥5.7%). For age-adjusted, logistic-regression models in which sex-specific quartiles of SAD were considered simultaneously with quartiles of either WC or BMI, only SAD quartiles 3 (p

Background: Several different sets of reference body mass index (BMI) values are available to define overweight in children. Objective: The objective of this study was to compare the prevalence of overweight in US children calculated with 3 sets of reference BMI values: the revised growth charts of the Centers for Disease Control and Prevention (CDC-US growth charts), international standards proposed by Cole et al, and values developed by Must et al. Design: Data for children and adolescents came from cross-sectional nationally representative US surveys: cycles II and III of the National Health Examination Survey (1963-1965 and 1966-1970) and the first, second, and third National Health and Nutrition Examination Surveys: NHANES I (1971-1974), II (1976-1980), and III (1988-1994). The reference values of Cole et al equivalent to a BMI of 25 were compared with the 85th percentiles from the other 2 methods; the values equivalent to a BMI of 30 were compared with the 95th percentiles. Results: The 3 methods gave similar but not identical results. The reference values of Cole et al gave lower estimates than did the CDC-US growth charts for young children but higher estimates for older children. The reference values of Must et al gave much higher prevalences for younger girls than did the other 2 methods. Conclusions: Differences between methods were related to differences in data sets, smoothing methods, and theoretical approaches. All 3 methods are based on statistical criteria and incorporate arbitrary assumptions. These methods should be used cautiously, with awareness of the possible limitations.

Importance Between 1980 and 2000, the prevalence of obesity increased significantly among adult men and women in the United States; further significant increases were observed through 2003-2004 for men but not women. Subsequent comparisons of data from 2003-2004 with data through 2011-2012 showed no significant increases for men or women. Objective To examine obesity prevalence for 2013-2014 and trends over the decade from 2005 through 2014 adjusting for sex, age, race/Hispanic origin, smoking status, and education. Design, Setting, and Participants Analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional, nationally representative health examination survey of the US civilian noninstitutionalized population that includes measured weight and height. Exposures Survey period. Main Outcomes and Measures Prevalence of obesity (body mass index ≥30) and class 3 obesity (body mass index ≥40). Results This report is based on data from 2638 adult men (mean age, 46.8 years) and 2817 women (mean age, 48.4 years) from the most recent 2 years (2013-2014) of NHANES and data from 21 013 participants in previous NHANES surveys from 2005 through 2012. For the years 2013-2014, the overall age-adjusted prevalence of obesity was 37.7% (95% CI, 35.8%-39.7%); among men, it was 35.0% (95% CI, 32.8%-37.3%); and among women, it was 40.4% (95% CI, 37.6%-43.3%). The corresponding prevalence of class 3 obesity overall was 7.7% (95% CI, 6.2%-9.3%); among men, it was 5.5% (95% CI, 4.0%-7.2%); and among women, it was 9.9% (95% CI, 7.5%-12.3%). Analyses of changes over the decade from 2005 through 2014, adjusted for age, race/Hispanic origin, smoking status, and education, showed significant increasing linear trends among women for overall obesity ( P = .004) and for class 3 obesity ( P = .01) but not among men ( P = .30 for overall obesity; P = .14 for class 3 obesity). Conclusions and Relevance In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity in 2013-2014 was 35.0% among men and 40.4% among women. The corresponding values for class 3 obesity were 5.5% for men and 9.9% for women. For women, the prevalence of overall obesity and of class 3 obesity showed significant linear trends for increase between 2005 and 2014; there were no significant trends for men. Other studies are needed to determine the reasons for these trends.

Background Before estimating smoothed percentiles of weight-for-height and BMI-for-age to construct the WHO growth charts, WHO excluded observations that were considered to represent unhealthy weights for height. Objective The objective was to estimate the effects of similar data trimming on empirical percentiles from the CDC growth-chart data set relative to the smoothed WHO percentiles for ages 24-59 mo. Design We used the nationally representative US weight and height data from 1971 to 1994, which was the source data for the 2000 CDC growth charts. Trimming cutoffs were calculated on the basis of weight-for-height for 9722 children aged 24-71 mo. Empirical percentiles for 7315 children aged 24-59 mo were compared with the corresponding smoothed WHO percentiles. Results Before trimming, the mean empirical percentiles for weight-for-height in the CDC data set were higher than the corresponding smoothed WHO percentiles. After trimming, the mean empirical 95th and 97th percentiles of weight-for-height were lower than the WHO percentiles, and the proportion of children in the CDC data set above the WHO 95th percentile decreased from 7% to 5%. The findings were similar for BMI-for-age. However, for weight-for-age, which had not been trimmed by the WHO, the empirical percentiles before trimming agreed closely with the upper percentiles from the WHO charts. Conclusion WHO data-trimming procedures may account for some of the differences between the WHO growth charts and the 2000 CDC growth charts.

A recent, cross-sectional analysis of adults found that the hip circumference divided by height(1.5) minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X-ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease.Cross-sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988-1994.As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race-ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels.Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.

Background: BMI is one factor that is used to determine a child’s eligibility for lipid screening and treatment. BMI, which is an indirect measure of body fat, may inadequately represent the biological effect of body fat percentage on lipid concentrations. Objective: We examined the relation between directly measured body fat percentage and lipid concentrations in a representative sample of US youths. Design: Data from 7821 participants aged 8–19 y from the 1999– 2004 NHANES were analyzed. Body fat percentage was measured by dual-energy X-ray absorptiometry. Total and HDL-cholesterol concentrations were measured in serum. Serum triglyceride and LDL-cholesterol concentrations were measured in a subsample of 2661 fasting NHANES participants aged 12–19 y. Prevalences of adverse total cholesterol (.200 mg/dL), LDL cholesterol (.130 mg/dL), triglycerides (.150 mg/dL), and HDL cholesterol (,35 mg/dL) were measured. Results: Approximately 10.0% [60.7% (SE)] of participants had high total cholesterol, 7.0 6 0.4% of participants had low HDL cholesterol, 9.7 6 1.0% of participants had high triglycerides, and 7.6 6 0.7% of participants had high LDL cholesterol. Prevalence of adverse total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol in US youths with high adiposity (greater than or equal to the age- and sex-specific 75th percentile of body fat percentage) was significantly greater (P , 0.01) than for participants without high adiposity. In multiple linear regressions adjusted for age, survey period, and race-ethnicity, the variance in lipid concentrations explained by body fat percentage was 2–20% (P , 0.001). Conclusion: Adverse lipid concentrations and high adiposity are significantly associated in youths. Am J Clin Nutr 2011;94:877–83.

We sought to describe differences between normal weight, overweight, and obese adults in use of specific prescription medication classes.Cross-sectional analysis of prescription medication use among 9789 adults in the National Health and Nutrition Examination Survey, a nationally representative sample of the United States.In 2005-2008, 56.4% (95% confidence interval [CI], 54.6-58.3) of adults used 1+ prescription medication. Approximately one-quarter of adults used a hypertension medication (26.1%; 95% CI, 24.5%-27.8%). The use of hypertension medications increased with increasing weight status (normal weight: 17.2%; 95% CI, 15.6%-18.8%; overweight: 24.5%, 95% CI, 22.6%-26.4%; and obese: 35.1%, 95% CI, 32.8%-37.4%). Similarly, lipid-lowering, analgesic, antidepressant, proton pump inhibitors, thyroid, diabetes, and bronchodilator medication use was greater among obese compared with normal weight adults (each p.01). Among adults 65+ years, 72% (95% CI, 68.2%-75.8%) of men and 67.7% (95% CI, 64.3%-71.2%) of women used a hypertension medication and a majority of men (51.2%, 95% CI, 48.4%-54%) and 40.3% (95% CI, 36.8%-43.8%) of women used lipid lowering medications; the use of both was greater among obese adults compared to normal weight adults (both p.01).Obese adults in the United States use several prescription medication classes more frequently, than normal weight adults, including hypertension, lipid-lowering, and diabetes medications.

Obesity is a public health challenge throughout the world. Ongoing monitoring of trends in obesity is important to assess interventions aimed at preventing or reducing the burden of obesity. Since the 1960s, measured height and weight have been collected in the United States as part of the National Health and Nutrition Examination Survey (NHANES). In Canada, data on measured height and weight have been collected from nationally representative samples of the population less regularly. This changed in 2007 with the launch of the Canadian Health Measures Survey (CHMS), the scope and purpose of which are similar to those of NHANES. The objective of this report is to compare estimates of the prevalence of obesity between Canadian and American adults.

Data from the National Health and Nutrition Examination Survey, 2005-2008. Among men, obesity prevalence is generally similar at all income levels, however, among non-Hispanic black and Mexican-American men those with higher income are more likely to be obese than those with low income. Higher income women are less likely to be obese than low income women, but most obese women are not low income. There is no significant trend between obesity and education among men. Among women, however, there is a trend, those with college degrees are less likely to be obese compared with less educated women. Between 1988-1994 and 2007-2008 the prevalence of obesity increased in adults at all income and education levels.

A variety of different terms, metrics, and cut-off values have been used to describe and assess overweight and obesity in children. Body mass index (BMI) calculated as weight in kilograms divided by height in meters squared can be used to express weight adjusted for height. In order to account for variability by sex and age, BMI in children is compared to sex- and age-specific reference values. In the United States, the Centers for Disease Control and Prevention (CDC) 2000 growth charts serve as reference values. The terminology used for high BMI-for-age in children in the United States to date has been based on the recommendation of an expert committee convened by federal agencies. This committee recommended the use of BMI and defined overweight as a BMI-forage at or above the 95th percentile of a specified reference population and the designation of "at risk for overweight" for BMI values between the 85th and the 95th percentiles of BMI for age. More recently, although the cut-off values and the interpretation have not changed, changes in terminology were proposed. An American Medical Association expert committee report retained the two cut-off values of the 85th and 95th percentiles of BMI-for-age but used different terminology, referring to BMI-for-age from the 85th up to the 95th percentile as "overweight" and to BMI-for-age at or above the 95th percentile as "obesity." The National Center for Health Statistics (NCHS) and other CDC publications will continue to include prevalence estimates at the 85th and 95th percentiles as before but will change the terminology to use the term "overweight" for a BMI-for-age between the 85th and 95th percentile (formerly called "at risk for overweight") and the term "obesity" for a BMI-for-age at or above the 95th percentile (formerly called "overweight").

To examine racial/ethnic differences in the relationship between weight perception and weight management behaviors among overweight and obese adults.The study examined a nationally representative sample of 11,319 non-Hispanic White, non-Hispanic Black and Mexican American overweight and obese adults agedor = 20 years from the 1999-2006 National Health and Nutrition Examination Survey.Body mass index (BMI, defined as weight in kilograms divided by height in meters squared) was used to categorize overweight (25or = BMI30) and obesity (BMIor = 30). Measured height and weight were used to calculate BMI. Subjects reported self-perception of weight status (correct perception and misperception) and weight management behaviors over the previous 12 months (trying to lose weight, trying not to gain weight, and having a desired weight goal). Weight perception stratified logistic regression was used to model odds of weight management behavior by race/ethnicity.Among overweight and obese non-Hispanic White, non-Hispanic Black, and Mexican American adults, correct weight perception was positively associated with weight management behavior. In multiple logistic regression models, overweight non-Hispanic Blacks with a weight misperception were less likely to have tried to lose weight (adjusted odds ratio [aOR] = .7; 95% confidence interval [Cl] = .5,1.0) or to have tried not to gain weight (aOR = .7; 95% CI = .5,1.0) compared to overweight non-Hispanic Whites with a weight misperception. Among the obese with a misperception, non-Hispanic Blacks were less likely to desire to weigh less compared to non-Hispanic Whites (aOR = .5; 95% CI = .3,.9).Weight perception was associated with weight management behaviors, and this relationship varied by race/ethnicity. Weight perception may need to be addressed among overweight and obese individuals to increase appropriate weight management behaviors, particularly among minority communities.

Background: Body mass index (BMI)–for-age has been recommended as a screening test for excess adiposity in children and adolescents. Objective: We quantified the performance of standard categories of BMI-for-age relative to the population prevalence of high adiposity in children and adolescents overall and by race-ethnic group in a nationally representative US population sample by using definitions of high adiposity that are consistent with expert committee recommendations. Design: Percentage body fat in 8821 children and adolescents aged 8–19 y was measured by using dual-energy X-ray absorptiometry in 1999–2004 as part of a health examination survey. Results: With the use of several different cutoffs for percentage fat to define high adiposity, most children with high BMI-for-age (95th percentile of the growth charts) had high adiposity, and few children with normal BMI-for-age (,85th percentile) had high adiposity. The prevalence of high adiposity in intermediate BMI categories varied from 45% to 15% depending on the cutoff. The prevalence of a high BMI was significantly higher in non-Hispanic black girls than in non-Hispanic white girls, but the prevalence of high adiposity was not significantly different. Conclusions: Current BMI cutoffs can identify a high prevalence of high adiposity in children with high BMI-for-age and a low prevalence of high adiposity in children with normal BMI-for-age. By these adiposity measures, less than one-half of children with intermediate BMIs-for-age (85th to ,95th percentile) have high adiposity. Differences in high BMI ranges between race-ethnic groups do not necessarily indicate differences in high adiposity. Am J Clin Nutr 2010;91:1020–6.

This paper explores three issues related to the 2000 Centers for Disease Control and Prevention growth charts. First, it clarifies the methods that were used to create the charts as it has become apparent that the smoothing techniques have been somewhat misunderstood. The techniques included smoothing-selected percentiles between and including the 3rd and 97th percentiles and then approximating these smoothed curves using a procedure to provide the transformation parameters, lambda, mu, and sigma. Only the selected percentiles were used in this process due to small sample sizes beyond these percentiles. Second, given the concern that the infant charts were created with relatively few data points in the first few months of life, it compares the original observed percentiles with percentiles that include newly available US national data for the first few months of life. Third, it discusses the issues that arise if a 99th percentile is extrapolated based on the lambda, mu, and sigma parameters. The 99th percentile of the body mass index-for-age chart has been recommended to identify extremely obese children, yet the 97th percentile is the highest available percentile on the Centers for Disease Control and Prevention growth charts.