Distinct Phenotypic Characteristics of Normal-Weight Adults at Risk Of

Distinct phenotypic characteristics of normal-weight adults at risk of Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 developing cardiovascular and metabolic diseases

Abishek Stanley,1 John Schuna,2 Shengping Yang,1 Samantha Kennedy,1 Moonseong Heo,3 Michael Wong,4 John Shepherd,4 and Steven B Heymsfield1

1Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA; 2College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA; 3Department of Public Health Sciences, Clemson University , Clemson, South Carolina, SC, USA; and 4University of Hawaii Cancer Center, Honolulu, HI, USA

ABSTRACT Introduction 2 Background: The normal-weight BMI range (18.5–24.9 kg/m ) Controversy surrounds the concept of “normal” body weight includes adults with body shape and cardiometabolic disease risk based on BMI, weight/height2 (1). Not only is BMI modestly features of excess adiposity, although a distinct phenotype developed correlated with adiposity level (2), a key marker of health on a large and diverse sample is lacking. risks, but mortality studies identify a wide range of relative Objective: To identify demographic, behavioral, body composition, weights consistent with optimum health and longevity (3). To and health-risk biomarker characteristics of people in the normal- compensate for BMI limitations, some overweight and obesity weight BMI range who are at increased risk of developing guidelines include waist circumference (WC)as an additional cardiovascular and metabolic diseases based on body shape. anthropometric measure of a person’s health risks (4). WC relates Methods: Six nationally representative waist circumference index to health risks through its empirical correlations with visceral (WCI, weight/height0.5) prediction formulas, with BMI and age as covariates, were developed using data from 17,359 non-Hispanic adipose tissue and ectopic lipids, known mediators of adiposity’s (NH) white, NH black, and Mexican-American NHANES 1999– adverse metabolic and cardiovascular effects (5). 2006 participants. These equations were then used to predict As currently applied, single WC cut-points identifying men > > WCI in 5594 NHANES participants whose BMI was within the and women (e.g. 102 cm and 88 cm, respectively) who are normal weight range. Men and women in each race/Hispanic-origin at high risk of developing chronic cardiovascular and metabolic group were then separated into high, medium, and low tertiles diseases are incorporated into guidelines without consideration based on the difference (residual) between measured and predicted for between-individual differences in stature, age, and in some WCI. Characteristics were compared across tertiles; P values for cases, race and ethnicity (4–6). To overcome these limitations, significance were adjusted for multiple comparisons. a recent study reported a waist-circumference index (WCI) Results: Men and women in the high WCI residual tertile, relative incorporating adjustment for height (7) analogous to BMI; that 0.5 to their BMI and age-equivalent counterparts in the low tertile, is, WCI (waist circumference/height ) is a height-independent 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 This work was partially supported by NIH NORC Center Grants P30DK072476, Pennington/Louisiana, P30DK040561, Harvard, and (skeletal muscle) and bone mineral content; and higher plasma R01DK109008, Shape UP! Adults. insulin and triglycerides, higher homeostatic model assessment of Data described in the manuscript and code book are publicly and freely ± insulin resistance (e.g. NH white men, 1.45 0.07 compared with available without restriction at https://wwwn.cdc.gov/nchs/nhanes/Default.a 1.08 ± 0.06), and lower plasma HDL cholesterol. Percent leg fat spx. was also significantly higher in men but lower in women. Similar Supplemental Tables 1–6, Supplementary Methods I–III, Supplemental patterns of variable statistical significance were present within sex Figures 1 and 2, and the Supplementary Literature Review are available from and race/ethnic groups. the “Supplementary data” link in the online posting of the article and from the Conclusions: Cardiometabolic disease risk related to body shape in same link in the online table of contents at https://academic.oup.com/ajcn/. people who are normal weight according to BMI is characterized by Address correspondence to SBH (e-mail: [email protected]). a distinct phenotype that includes potentially modifiable behavioral Abbreviations used: ALST, appendicular lean soft tissue; MA, Mexican American; NH, non-Hispanic; WC, waist circumference; WCI, waist health risk factors. Am J Clin Nutr 2020;112:967–978. circumference index; WCIR waist circumference index residual. Received April 3, 2020. Accepted for publication June 23, 2020. Keywords: body shape, body composition, obesity, waist circum- First published online July 20, 2020; doi: https://doi.org/10.1093/ajcn/ ference, chronic disease nqaa194.

Am J Clin Nutr 2020;112:967–978. Printed in USA. Copyright © The Author(s) on behalf of the American Society for Nutrition 2020. 967 968 Stanley et al. Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020

FIGURE 1 Algorithm used to classify people in the normal-weight BMI range according to their “residual” waist circumference index, calculated as the difference between their measured and predicted waist circumference index. Predicted values for WCI were derived from sex and race/Hispanic origin-specific regression models developed on a nationally representative sample of the US noninstitutionalized civilian population (Supplementary Table 4). People in the high WCIR tertile are defined as having the metabolically obese, normal weight phenotype. WCI, waist circumferenceR index;WCI , waist circumference index residual; MONW, metabolically obese, normal weight. measure of adult body shape. When used in tandem with BMI The first analysis stage involved the development and vali- and age in race and Hispanic origin-specific prediction models, dation of 6 WCI prediction models based on BMI and age for a high WCI identifies people in the overweight and obese range men and women across the NH white, NH black, and Mexican- with a distinct phenotype (7): high percent total body and trunk American NHANES participants. The residual WCI (WCIR) fat and low percent skeletal muscle mass. Subjects who have was then calculated for each normal-weight (BMI, ≥18.5–24.9) this phenotype also have a high cardiovascular and metabolic participant as the difference between their actual and predicted disease risk profile as assessed by laboratory and blood pressure WCI value. People with a high WCIR thus had a relatively large studies. The current study aim was to test the hypothesis that this WC for their sex, race and Hispanic origin, BMI, and age. previously reported phenotype is also present in people whose Normal-weight participants within each sex and race and BMI is within the normal weight range (18.5–24.9 kg/m2). Hispanic origin group were next allocated into tertiles based on WCIR: actual value greater than, like, or smaller than predicted for their BMI and age. The mean (±SE) values for demographic Methods variables, body composition, blood studies, and blood pressure were then compared across the high and low WCIR tertiles. Study design The algorithm for identifying people in the 3 WCIR tertiles is Participants in the 1999–2006 NHANES had body shape and summarized in Figure 1. composition evaluated using a combination of anthropometric and imaging methods as previously reported (8, 9). Participants were excluded if they were aged <18 y, amputees, pregnant, not in NHANES categories of non-Hispanic (NH) white, NH Data sources/study population black, or Mexican American, and in subgroup analyses if The baseline characteristics of the 6 NHANES sex and they were taking medications known to influence their test race/Hispanic origin groups are summarized in Supplementary results. The overall disposition of participants in the multiple Methods I, Table 2 for all participants and in Supplementary analyses is summarized in Supplementary Methods I (Figure 1, Table 3 for the normal-weight group defined by BMI. Overall, Table 1A–C). All participants as outlined in the figure and tables there were 17,359 total participants with 5594 classified as having were included in analyses and no outlying data was removed. a normal weight after exclusions. Of the normal-weight group, Health risk phenotype 969 a b c a b c a b b a a b ab a b a b c a ab b a ab b a a b 0.2 0.2 0.2 0.01 0.01 0.02 2.6 2.2 2.3 0.6 0.6 0.7 0.2 0.3 0.3 2.0 2.2 2.2 0.3 0.3 0.2 0.1 0.1 0.1 1.4 1.5 1.9 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 74.5 79.0 85.2 5.88 6.21 6.69 65.0 56.7 48.9 a b c a b c a b b 1.11.01.6 41.9 37.1 39.7 0.40.40.6 57.9 58.4 59.5 0.3 0.3 0.5 0.03 0.02 0.04 5.85.24.9 78.0 72.2 68.2 4.5 4.3 4.4 0.60.50.6 160.9 162.0 162.5 0.10.10.2 22.4 22.2 22.5 2.53.72.7 14.2 16.6 20.0 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± column are significantly different. Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 36.8 33.2 35.1 56.5 56.9 56.8 75.5 80.0 85.4 6.01 6.35 6.78 57.2 55.2 57.0 65.7 47.4 47.9 158.0 158.8 158.8 a b c a b a a b b a a b a b c a ab b a a b 0.6 0.6 0.5 1.2 1.4 1.3 0.6 0.6 0.5 0.20.20.20.4 22.6 0.5 22.5 0.5 22.5 0.03 0.04 0.04 2.0 5.0 3.7 2.83.13.85.1 7.2 4.4 13.3 4.1 10.1 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± can American, NHB, non-Hispanic black; NHW, 40.7 35.5 40.6 58.3 59.0 61.0 22.3 22.0 22.5 73.0 77.7 84.3 5.75 6.08 6.58 83.1 71.4 61.6 18.2 16.7 21.6 58.2 53.6 38.8 on “do you currently smoke at least a cigarette a day?” 161.3 163.6 164.5 a b c a b b a ab b a a b a a b a b c a ab b a a b a a b 1.1 1.5 1.7 1.9 1.8 2.5 0.3 0.3 0.3 0.6 0.7 1.0 0.3 0.3 0.3 0.1 0.1 0.1 0.2 0.2 0.3 0.02 0.02 0.02 2.6 2.1 2.6 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 48.0 42.5 43.4 59.0 59.1 60.7 22.1 22.0 22.5 75.1 79.4 85.9 5.88 6.20 6.71 71.1 69.0 60.1 163.2 163.7 164.1 a b c ab a b a b c a a b ab a b a b c a a b 0.1 0.1 0.1 2.32.42.31.9 93.6 2.2 90.0 2.0 86.1 17.0 19.7 28.2 0.6 0.5 0.7 0.4 0.4 0.3 0.2 0.2 0.2 0.01 0.02 0.02 2.0 2.2 2.4 0.3 0.3 0.3 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 0.0167). Education level is expressed as the percent of participants who responded as having at = 79.7 82.9 88.4 6.05 6.28 6.67 63.9 57.6 48.3 0.05/3 < a b c a b c a ab b P 0.20.10.1 22.6 22.4 22.7 4.75.13.83.5 67.0 4.5 61.0 2.4 60.4 26.0 29.9 27.9 1.20.91.1 38.1 36.2 38.2 0.70.70.6 68.3 68.7 70.4 0.4 0.4 0.5 0.03 0.03 0.03 3.7 4.7 4.6 0.60.60.5 173.6 174.8 176.0 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 32.4 32.6 33.7 64.5 65.2 66.7 79.4 83.3 87.9 6.11 6.40 6.73 50.7 40.3 34.4 169.1 169.5 170.4 Men Women a b c 1 a b ab a ab b a ab b a b c ab a b 1.0 1.2 0.10.10.1 22.5 22.6 22.9 0.6 0.6 0.5 0.4 0.4 0.5 0.03 0.03 0.04 4.84.24.53.2 48.1 3.3 40.0 4.1 34.1 3.9 15.3 3.2 22.8 4.4 14.9 1.1 0.5 0.6 0.5 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 69.4 69.5 71.5 77.2 79.6 86.1 5.83 5.98 6.45 62.5 59.6 64.3 37.1 38.5 32.1 62.9 64.6 50.4 175.4 177.3 178.5 a b c a a b a a b a b c a ab b a ab b a b b 0.80.80.5 35.6 0.4 38.5 0.6 0.4 0.10.10.1 22.5 0.3 22.1 0.3 22.4 0.02 0.02 0.02 3.3 2.4 2.5 2.7 2.4 2.6 0.4 0.5 0.3 1.6 2.5 2.1 1.0 39.6 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 466–467 241–242 225 932–934 563 160–161 208–209 931–933 SE. Sample sizes given as ranges; details are presented in Supplementary Table 1A. Values with different superscript letters within the same cell and MediumHighMediumHigh 40.5 Medium 42.2 High 177.5 LowMedium 179.0 High 71.3 Medium 73.1 High 22.6 22.8 LowMedium 22.8 High 85.8 Medium 91.3 High 6.45 6.21 Medium 6.83 High 83.5 Medium 82.7 High 28.5 36.8 67.7 60.0 ± Demographic characteristics of the normal-weight NHANES sample 2 0.5 Results are mean 1 1 TABLE 1 CharacteristicN TertileHeight, cmWeight, kg NHW LowBMI, kg/m LowWC, NHB cm 176.3 WCI, cm 71.0 Low MAEducation, %Smoking, % Low Total 82.4 Activity, % Low 90.6 NHW Low 25.5 NHB 78.1 MA Total Age, years Low 42.2 least a high school orActivity General levels Education are Development reported degree. as Smoking the is percent expressed as of the participants percentage engaging of in participants a who minimum responded of “yes” 150 to min the of questi moderate to vigorous physical activity weekly. MA, Mexi non-Hispanic white; WC, waist circumference; WCI, waist circumference index. Pairwise comparisons across tertiles for each variable were performed with a Bonferroni correction ( 970 Stanley et al. a a b

a a b a b c a a b a a b there were 1399 NH white, 725 NH black, and 675 Mexican- 0.3 0.2 0.2 0.02 0.02 0.03 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 American men. Similarly, there were 1689 NH white, 481 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± NH black, and 625 Mexican-American women. The NHANES protocol was approved by the Institutional Review Board of 13.4 14.1 15.8 14.3 13.9 13.2 26.8 26.5 25.7 the National Center for Health Statistics, CDC. All participants provided written informed consent. Three demographic and behavioral variables were evaluated in a ab b a ab b a ab b

0.40.50.40.3 33.2 0.4 33.6 0.4 34.8 0.2 0.3 0.2 0.2 0.3 0.2 0.030.040.07 3.54 3.52 3.38 the current study, education, smoking status, and activity levels

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± (Supplementary Methods II). Education level is reported as the percentage of participants who responded as having at least a high Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 34.7 35.1 35.7 15.1 15.7 17.1 13.8 13.6 12.8 25.4 25.0 24.3 3.48 3.42 3.37 school or General Education Development degree (10). Smoking is reported as the percentage of participants who responded “yes” Women to the question “do you currently smoke at least a cigarette a ab a b rs within the same cell and column are ab a b a a b a ab b a a b day?” (11). Activity levels are reported as the percentage of 0.6 0.4 0.5 0.3 0.3 0.3 0.3 0.2 0.2 0.3 0.2 0.3 0.05 0.04 0.05

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± participants engaging in a minimum of 150 minutes of moderate to vigorous physical activity weekly (12). 31.5 31.8 33.3 11.6 12.2 14.3 14.5 14.1 13.4 28.9 28.5 27.5 3.67 3.68 3.51 Hispanic white; WC, waist circumference index; WCI, waist

Measurements a a b a a b a b c a b c a a b Anthropometry. 0.2 0.2 0.3 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.02 0.02 0.03

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± Body weight, height, and WC were measured according

33.3 33.9 35.3 13.3 14.3 16.1 14.5 14.0 13.4 26.2 26.0 25.2 3.46 3.44 3.27 to standard NHANES procedures and are summarized in

0.0167). Separate models for each body composition variable were fitted for each of the Supplementary Methods II (13, 14). BMI was calculated as body

= weight/height2 (kg/m2) and WCI as WC/height0.5 (cm/cm0.5 or 0.5 a b c cm ). a b c a b c a b c a b c 0.05/3 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.02 0.02 0.02 0.1 0.1 0.1 0.1 0.1 < P ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

8.5 9.6 6.9 7.4 8.2 Body composition. 19.3 21.1 24.1 11.6 35.2 34.0 32.2 3.89 3.75 3.58 Each participant completed a whole-body DXA scan (15) as outlined in Supplementary Methods II. The following were

a b b measured and reported as a percentage of body weight in the a b c a b c a a b a b c 0.4 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.04 0.04 0.03 0.2 0.2 0.1 0.1 current study: total body, trunk, and leg fat mass; appendicular ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± lean soft tissue (ALST) mass (sum of lean soft tissue mass in

9.2 7.0 7.5 8.0 the arms and legs); and total bone mineral content. The ALST 20.3 22.5 24.6 10.8 12.1 34.0 32.6 31.4 3.74 3.58 3.47 component is a surrogate measure of total body skeletal muscle

Men mass (16) and bone mineral content is a measure of total body 1

a a b bone mass. a b c a b c a a b a b c 0.3 0.3 0.4 0.3 0.2 0.2 0.3 0.03 0.04 0.04 0.1 0.2 0.2 0.1 0.2 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± Avatar image development. 6.9 7.6 6.5 7.0 8.2 17.2 18.5 22.6 10.2 37.5 36.4 34.0 4.17 4.08 3.82 Three-dimensional avatars of men and women were generated as an aid to visualizing the typical body shape of people in the

a b c high and low WCIR tertiles using image prediction models as pre- a b c a b c a b c a b c viously reported (17) and detailed in Supplementary Methods II. 0.2 0.1 0.1 0.2 0.02 0.2 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.02 0.02 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

Health risk factors. Blood chemistries and blood pressure were measured according to standard NHANES procedures (18) as reported in Supplementary Methods III. Participants who were fasting overnight (≥8 h) and were not taking medications for diabetes

SE percentage of body weight. Sample sizes given as ranges; details are presented in Supplementary Table 1B. Values with different superscript lette were included in plasma glucose, insulin, and HOMA-IR MediumHighMediumHigh 22.2 Medium 25.3 High 10.5 Medium 12.4 High 7.6 MediumHigh 8.5 33.1 31.2 3.59 3.44 ± analyses. HOMA-IR was calculated as fasting insulin × fasting glucose/405 (18). Participants who were fasting overnight and were not taking lipid-lowering drugs were included in the Body composition of the waist circumference index residual tertiles cholesterol (total, HDL, and LDL) and triglyceride analyses. Participants who were not taking antihypertensive medications Results are mean 1 were included in the analyses of systolic and diastolic blood pres- circumference index. 5 NHANES imputed data sets. ALST, appendicular lean soft tissue; BMC, bone mineral content; MA, Mexican American; NHB, non-Hispanic black; NHW, non- TABLE 2 CharacteristicNTotal Fat TertileTrunk Fat LowLeg Fat NHW LowALST 20.4 LowBMC NHB 9.2 424–446 Low 7.2 Low MA 232–238 34.2 216–222 3.75 Total 878–905 NHW 524–539 NHB 154–159 MA 204–206 882–904 Total significantly different. Pairwise comparisons across tertiles for each variable were performed with a Bonferroni correction ( sure. Blood pressure was measured using standard procedures Health risk phenotype 971 as outlined in Supplementary Methods III and in the NHANES Results operations manual (19). WCI prediction models BMI was strongly correlated with WCI for total men and women (R2s, 0.839 and 0.824, both P <0.001) and for each of the Statistical analyses 6 sex and race/Hispanic origin groups (Supplementary Figure 2). Age added along with BMI to the WCI prediction models for The NHANES applies a complex multistage sampling strategy each race and Hispanic origin group (Supplementary Table 4) since random sampling is not feasible from the entire US with R2s ranging from 0.86 in Mexican-American women to 0.93 population that incudes subgroups of people who are institution- <

in NH black men; all models were significant at P 0.001. The Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 alized. Therefore, to increase the representativeness of the sample prediction equations shown in Supplementary Table 4 were used at the individual subject level, probability sampling weights to calculate WCIR; participants were then sorted into the high, are applied considering survey nonresponse, oversampling, medium, and low WCIR shape tertiles. poststratification, and sampling errors. More details onthe NHANES sampling strategy can be found at the CDC website (20, 21). All parameter estimates were obtained using R (version 3.6.1; R Foundation for Statistical Computing) and its associated Characteristics of the study population “survey” package (22, 23) to yield nationally representative parameter estimates while accounting for the complex, multistage Demographic. probability design of NHANES. The R survey package is 1 of The demographic characteristics across the high, medium, and the software platforms recommended for analyzing NHANES low WCIR tertiles are summarized for men and women in the data. All models included appropriate sample weights to 3 race/Hispanic origin groups in Table 1. The overall sample account for noncoverage, nonresponse, and oversampling of had an average age of ∼40 y with NH white men and women some groups. Sample strata and weights were adjusted in the older than their NH black and Mexican-American counterparts, same manner as in the SAS SURVERYMEANS and SUR- in that order. People in the high WCIR tertile were, on average, VEYREG procedures (23). SEs were derived using Taylor series ∼1–2 cm taller than those in the corresponding low tertile. Body linearization. weight paralleled height across the tertiles such that average BMI Descriptive statistics characterizing the study cohort included was similar at ∼22 to 23 in all 6 sex and race/Hispanic origin categorical variables summarized as frequencies and continuous groups. As expected, WC decreased from the high to low WCIR variables as means and SEs. The WCI prediction models were tertiles. For example, among NH white men with the same age fitted using regression analysis in a complex sample framework. and BMI, the mean WC decreased from 91.3 cm in the high tertile After restricting the sample to normal-weight participants (BMI, to 85.8 cm and 82.4 cm in the medium and low WCIR tertiles, ≥18.5–24.9), additional regression models were fitted in a respectively. complex samples framework to evaluate heterogeneity across The percentage of people with General Education Devel- WCIR tertiles within each sex by race/ethnicity combination for opment degrees decreased from NH white to NH black and a variety of demographic, anthropometric, body composition, Mexican-American NHANES participants. The mean education and cardiometabolic variables. Models included WCI tertile level was lower in the high versus low WCIR tertile groups for designation (high, medium, or low), race/Hispanic origin (NH all 6 sex and race/Hispanic origin groups, although statistical white, NH black, Mexican American), and their interaction as significance was inconsistent. independent predictors. Graphical diagnostics of model residuals The percentage of participants who smoked ≥1 cigarette a day for plasma triglyceride analyses demonstrated evidence of was highest in NH black men (∼32–37%) and lowest in Mexican- heterogeneous variance. As such, a variance stabilizing transfor- American women (∼7–13%). The pattern of smoking across mation (natural logarithm) was employed prior to triglyceride- WCIR tertiles was like that observed for education, with people related analyses and all parameter estimates were later back in the high tertiles tending to have higher mean smoking per- transformed to their original scale to facilitate interpretation of centages than those in the low WCIR tertiles, although between- results. group statistical significance was inconsistent. Women in the high All analyses were stratified by sex and race/Hispanic ori- WCIR group had significantly less education and higher smoking gin combinations. For each variable, pairwise comparisons rates compared with their low tertile counterparts. across tertiles were performed with a Bonferroni correction The percentage of participants engaging in a minimum of (P <0.05/3 = 0.0167). 150 min of moderate to vigorous physical activity weekly was Specific to NHANES body composition analyses using DXA highest among the NH white men and women with lower levels in data, separate models were fitted for each of the 5 imputed NH black and Mexican-American men and women. A consistent data sets. Location and variance estimates were averaged across-WCIR tertile gradient in activity was present among men across models while adhering to Rubin’s rules (24)usingthe and women in the 3 race/Hispanic-origin groups: people in the “MIcombine” function. Critical t-statistic values were derived low WCIR tertile had the highest reported activity levels and those using Barnard and Rubin’s method (24) for penalizing Df as a in the high tertile had the lowest activity levels. The differences function of the data’s missingness. The complete-data Df used in activity levels between the high and low tertile groups were all in this derivation was 59 (number of primary sampling units – significant, including for total men and women, except forNH number of sampling strata). black men. 972 Stanley et al. Body composition. patterns were present for total and LDL cholesterol or for systolic The results of body composition estimates across the high, and diastolic blood pressure. To establish if these health risk biomarker patterns differ after medium, and low WCIR tertiles are summarized for men and women in the 3 race/Hispanic origin groups in Table 2. Total body adjusting for physical activity levels and smoking status, the and trunk percent fat decreased from high to low tertiles in all 6 analyses were re-run adjusting for both behavioral measures sex and race/Hispanic origin groups. The differences in total and (Supplementary Table 5). The patterns linking WCIR with trunk percent fat between the high and low tertile groups were health risk biomarkers shown in Table 3 were largely unchanged all significant except for total percent fat in the NH black and as summarized in Supplementary Table 6. Mexican-American women. A similar pattern was present for leg percent fat in the 3 groups of men, although the opposite trend Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 was present in women: leg percent fat decreased in the groups of Discussion women from low to high WCIR tertiles. The differences in leg percent fat between the high and low tertile groups of women An algorithm combining BMI and WCI estimates was used were all significant. Men thus had greater total and regional in the current study to identify normal-weight NHANES participants who were at increased risk of developing cardiovascular adiposity in the high WCIR tertile compared with their low tertile and metabolic diseases. Using this approach, people in the high counterparts. Women in the high WCIR tertile also had greater relative total and trunk adiposity but lower leg adiposity than their WCIR tertile relative to those in the low tertile, had a remarkably distinct phenotype: low activity levels, increased total body and low WCIR counterparts. All 6 sex and race/Hispanic origin groups and all men and trunk percent fat, low percent skeletal muscle (i.e. ALST) and bone (i.e. bone mineral content), and an array of unfavorably all women in the high WCIR tertiles had significantly smaller percentages of ALST and bone mineral content than those in directed risk markers including elevated plasma insulin and the low tertile except for bone mineral content in the NH triglycerides, HOMA-IR, and lowered plasma HDL cholesterol black and Mexican-American women whose values were in concentrations. Moreover, there was a sexual dimorphism in this the same direction but were not significant. Not including the phenotype, with women in the high WCIR tertile having relatively less leg fat than their low-WCIR counterparts; the opposite effect aforementioned exceptions, people with a high WCIR were thus characterized by smaller proportions of their body weight as was present in men. Adipose tissue in the thigh region is inversely skeletal muscle and bone than those with low residual WCIs. related to metabolic and cardiovascular disease risk (25), adding The main morphologic and body composition features of to the other risk factors noted in women who were in the high high- and low-tertile representative NH white men and women WCIR tertile. The pattern of demographic features of people with are shown as the digital avatars in Figure 2. The mean age, ahighWCIR is summarized in Figure 3. weight, height, and WC values for the 4 respective groups were At the core of the developed algorithm is WCI, WC adjusted used in generating the images with manifold regression analysis for between-individual differences in height (7). Absolute values (8, 17). Notable high-low tertile differences in body shape and of WC, notably single sex-specific cut-points, are often used composition, as shown in the bar graphs, are present with the in identifying patients with metabolic syndrome (6)orwhoare hypothetical people all the same race/Hispanic origin, age, and at risk of developing chronic diseases secondary to overweight BMI (∼22). and obesity (4). However, as confirmed in the current study, the body-size measure WC is strongly correlated with BMI (Supplementary Figure 2) and age, in addition to height (7), with differences present even after controlling for these 3 Health risk biomarkers. variables across sex and race/Hispanic origin groups. Notably, The health risk biomarkers organized according to WCIR WC adjusted for height as WCI varies independently with BMI tertiles are summarized in Table 3. About 10% of participants and age even within the normal weight range. These factors were overall were removed from the analyses because they were not controlled for in the current study and presumably helped to fasting or were taking medications that influenced metabolic identify the distinct phenotypes associated with a high WCIR. markers, lipid concentrations, or blood pressure (Supplementary The present study refines and extends many earlier studies, Table 1C and D). Plasma triglycerides tended to be lower and with smaller samples or limited detection methods that reported HDL cholesterol concentrations tended to be higher in the NH components of these phenotypes (Supplementary Literature black participants compared with the other 2 race/ethnic groups. Review IV). In 1981 and later in 1982, Ruderman and Systolic blood pressures were also higher in the NH black men colleagues (26, 27) first described obesity as a spectrum, and women. with some people who are normal weight, at the lower end The mean plasma concentrations of glucose, insulin, and of the adiposity distribution, having enlarged fat cells and HOMA-IR were higher in the high versus low WCIR tertiles; raised plasma insulin concentrations. These people tended differences were significant for all men and all women except to be inactive and had an unfavorable diet. Two decades for plasma glucose in the women. The mean plasma triglyceride later Ruderman et al. (28) revisited their concept of the concentrations were higher in the high versus low WCIR tertiles; “metabolically obese, normal-weight individual” and further differences were significant for NH white men and women and refined their “insulin resistance syndrome” phenotype to include for total men and women. The mean plasma HDL cholesterol central fat distribution. By then, a parallel knowledge-base concentrations were lower in the high versus low WCIR tertiles; had formed around the metabolic significance of central fat differences were significant for NH black men and NH white distribution as first reported by Vague in 195229 ( )and women and for total men and women. No consistent WCIR later by Krotkiewski et al. in 1983 (30). Others have now Health risk phenotype 973 Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020

FIGURE 2 Three-dimensional representation of non-Hispanic white men (upper panel) and women (lower panel) who are in the low and high WCIR tertiles and a bar graph showing the high-low differences (, %) in fat and lean mass components. The average values for age, body weight, height, and WC were used from the men and women in the low and high WCIR tertiles to produce these avatars with manifold regression analysis as previously reported (17). The main feature depicted is the relatively large difference in central body volume even though all 4 avatars have the same BMI of ∼22 kg/m2 and an age of ∼40 y. The directional differences in body composition, calculated as the average high-low percentage for each component between the high and low WCIR groups, are shown in the 2 panels; positive differences are in red and negative differences are in blue. Skeletal muscle and bone mass are the anatomic representations of measured appendicular lean soft tissue mass and bone mineral content, respectively. All high-low body composition differences are statistically significant. ALST, appendicular lean soft tissue mass; BMC, bone mineral content; SM, skeletal muscle; WCIR, waist circumference index residual. 974 Stanley et al. a a b a a b a a b a b ab a b b a b a 3.1 2.4 3.7 1.0 1.1 1.3 0.05 0.07 0.08 2.2 2.9 3.3 0.2 0.3 0.3 0.6 0.6 1.2 0.7 0.8 0.8 1.9 2.9 3.2 0.5 0.7 0.6 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 5.2 5.5 6.8 81.1 75.5 96.9 65.5 60.3 57.8 112.4 104.9 108.8 ome measure. a ab b a b a a b ab ab a b 0.120.130.14 1.18 1.24 5.6 1.61 1.4 1.9 1.7 1.31.61.2 90.1 89.5 92.7 6.5 6.7 0.4 0.5 0.6 1.20.91.8 114.0 112.1 115.1 4.43.23.7 191.8 181.1 187.1 1.00.61.2 67.3 68.2 68.5 4.0 3.7 5.0 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 6.1 6.0 7.7 Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 1.44 1.36 1.79 78.3 59.1 61.3 54.2 102.7 103.2 each variable were performed with a a ab b a ab b ab a b a b ab 0.09 0.13 0.19 5.5 4.0 5.4 2.7 2.0 3.4 1.21.13.5 93.3 91.8 93.0 1.71.81.6 111.1 108.4 113.1 4.66.99.1 187.0 176.5 181.9 0.4 0.5 0.6 1.21.61.3 66.5 66.4 67.7 6.17.47.8 114.4 99.9 107.1 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± stolic blood pressure; MA, Mexican American; NHB, 4.9 5.7 6.9 1.06 1.26 1.65 60.3 58.9 79.2 69.1 58.9 60.1 115.1 115.0 117.9 rence index. a a b a a b a ab b a b b a b a 0.50.60.8 86.3 86.5 93.0 0.06 0.05 0.09 3.0 3.4 1.1 1.2 1.2 0.8 0.8 7.7 2.43.15.1 185.3 171.1 183.4 0.7 0.2 0.2 0.3 0.50.60.5 66.9 69.8 68.5 2.72.94.4 107.0 102.5 105.8 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 4.5 4.9 5.9 90.8 90.3 92.1 1.04 1.10 1.40 86.1 93.2 68.4 60.8 59.1 111.3 203.2 195.7 195.9 a a b a ab b a a b a a b a ab b a b b 0.60.6 112.8 114.4 0.6 115.7 3.3 3.3 5.5 0.50.50.5 68.5 68.5 69.3 0.05 0.04 0.07 1.5 1.4 2.3 3.1 3.3 2.23.03.0 115.8 112.4 113.7 0.6 1.2 1.0 1.1 0.2 0.1 0.3 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 4.9 5.3 6.5 1.16 1.27 1.59 183.5 186.3 194.3 108.4 114.3 115.6 ab a b ab a b a ab b a b b 6.1 5.1 1.20.8 117.6 119.4 4.4 1.0 118.8 8.46.19.7 86.9 87.2 102.0 0.71.01.1 68.8 68.1 69.9 5.4 5.7 6.3 4.43.5 96.1 98.1 0.5 0.3 0.6 1.0 94.0 0.13 0.08 0.16 1.71.71.3 58.0 53.3 52.9 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 95 5.8 5.3 7.3 1.38 1.33 1.86 54.9 51.7 51.0 101.1 101.9 Men Women a ab b ab a b a ab b a ab b 1 5.36.3 117.9 121.0 1.1 0.9 1.8 1.01.1 115.9 115.9 3.3 101.9 1.2 115.0 0.08 0.07 0.09 4.44.78.5 103.3 88.8 108.2 2.3 2.3 2.3 0.91.00.9 66.7 65.0 66.0 3.95.35.4 177.0 188.1 204.3 0.3 0.3 0.3 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 4.5 5.3 6.1 1.02 1.21 1.46 71.1 74.0 85.9 64.6 57.2 56.0 72.0 69.7 72.3 185.6 180.3 178.9 a ab b a b b a ab c a ab b a b ab a ab b 3.13.9 109.3 105.0 1.2 0.9 92.0 1.41.4 90.6 95.9 0.2 0.2 0.3 0.06 0.07 6.6 6.4 3.6 3.4 1.2 1.9 0.70.8 119.8 122.1 0.06 3.1 3.6 107.2 0.7 122.7 0.7 0.5 0.6 4.6 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 145–411 66–225 77–217 290–578 174–489 51–139 71–194 305–822 0.0167). Participants were removed from the analyses who were not fasting or who were taking medications known to moderate the specific evaluated outc = 0.05/3 SE. Values with different superscript letters within the same cell and column are significantly different. Pairwise comparisons across tertiles for MediumHigh 115.6 120.8 MediumHigh 96.8 96.4 MediumHighMediumHigh 5.2 MediumHigh 6.0 1.26 Medium 1.45 High 100.7 114.2 190.4 Medium 199.8 HighMediumHigh 50.9 51.8 117.2 120.3 MediumHigh 69.6 71.5 < ± P Health risk factors of the waist circumference index residual tertiles Results are mean Sample sizes given as ranges; detailsValues are are back-transformed presented geometric in means Supplementary and Table SEs 1c. from analytical models employing a natural logarithm transformation. C, cholesterol; DBP, dia mg/dL Low 89.4 1 2 3 3 2 HDL-C, mg/dL Low 54.4 Glucose, mg/dL Low 94.9 Insulin, uU/mL Low 4.5 TABLE 3 CharacteristicN TertileHOMA-IR NHWTG, LowTotal-C, mg/dL NHBLDL-C, mg/dL Low 1.08 MA LowSBP, 188.0 mmHg TotalDBP, mmHg 116.1 Low NHW Low 118.8 NHB 67.9 MA Total non-Hispanic black; NHW, non-Hispanic white; SBP, systolic blood pressure; TG, triglycerides; WC, waist circumference index; WCI, waist circumfe Bonferroni correction ( Health risk phenotype 975 Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020

FIGURE 3 Pattern of key demographic, body composition, and blood chemistry observations. Boxes in red represent the presence of significant differences between the high and low WCIR tertiles. Boxes in orange represent the same directional effects as their adjacent red counterparts but the between-group differences were not statistically significant. The direction of high-low (H-L) differences () is shown in the righthand column. The analyses used in generating the figure are presented in Tables 1–3. ALST, appendicular lean soft tissue; BMC, bone mineral content; HDL-C, plasma HDL cholesterol; NHB, non-Hispanic black; NHW, non-Hispanic white; TG, plasma triglyceride; WCIR, waist circumference index residual.

expanded the metabolically obese, normal-weight phenotype (education) and behavioral (smoking) characteristics. Genetic to include increased visceral fat (31–34), insulin resistance, (44) and dietary (26) effects may also contribute to the observed high concentrations of inflammatory cytokines, and dyslipidemia phenotypes. (35–38), different strategies to identify people at-risk (e.g. An important finding of the present study is that the identified ranking people who are normal weight by BMI, waist to high WCIR body shape and composition phenotype in people hip circumference ratio, or WC to height ratio [37, 39–42]), with a “normal” BMI, is identical to that observed in people who and introducing new nomenclature and acronyms such as are overweight and obese (7). This phenotype goes well beyond hypertriglyceridemic waist, NOW (normal-weight obesity), and a “large” WC, as is often inferred, and includes greater relative TOFI (thin-on-the-outside fat-on-the-inside [43]). The current amounts of total body fat, sex-specific regional fat distribution study consolidates these previous findings and provides insights patterns, and smaller relative amounts of skeletal muscle and into potential underlying interacting mechanisms, notably low bone even after controlling for BMI and age. These observations activity levels and, to a lesser extent, other demographic reveal the remarkable heterogeneity in human body shape and 976 Stanley et al. composition as well as their relations to chronic disease risk prone to variability caused by factors such as meal ingestion factors. than is WC (51). The NHANES evaluations were conducted both Despite recommendations by national, international, and fasting in the morning and in the early afternoon. We assume professional organizations to include WC measurements in that any meal-related effects on WC are randomly distributed patient evaluations (45–47), clinical uptake has been slow. across the tertiles. Nevertheless, body size measures such as Removing clothing, identifying the endorsed measurement site, neck circumference alone or in combination with WC should the need for observer training and skill, and a lack of agreed be evaluated in future studies as in the current report. Limited upon normative values, currently contribute to the limited clinical demographic and behavioral measures were evaluated in the use of WC measurements, particularly in people who are within current study and our findings highlight the need for in-depth the normal BMI range. Nevertheless, the distinct phenotype with analyses of these types of outcomes in future studies. A final Downloaded from https://academic.oup.com/ajcn/article/112/4/967/5873777 by ASN Member Access user on 16 November 2020 high WCIR in the current study identifies people at risk of concern is that within-race/ethnic and sex group across-tertile developing not only cardiovascular and metabolic diseases, but age heterogeneity was low and caution is therefore in order when conditions associated with aging such as sarcopenia (48)and extrapolating the current study findings to the general population. osteoporosis (49), reflecting low skeletal muscle and bone mass, respectively. Moreover, low activity levels, and even smoking, are modifiable risk factors amenable to behavioral management. Conclusions With an increasing clinical focus on disease prevention (50), The current study establishes that 3 clinical measurements, people with the distinct high WCIR phenotype observed in body weight, height, and WC; 2 calculated indices therefrom the current study are candidates for close scrutiny of their (BMI and WCI); along with a person’s sex, age, and race- behavioral and metabolic characteristics. Moreover, the current ethnicity designation can be used to estimate their cardiovascular study identifies linkages between behavioral and cardiometabolic and metabolic disease risk. Moreover, those individuals in the risk factors that can be tested for causality in future prospective high WCIR category are likely inactive and may have other proof-of-concept studies. predisposing features that are modifiable through behavioral Given the large number of people across the USA that approaches. Although the characteristics of these phenotypes are likely would be classified as having a high WCIR and the well recognized among people who are overweight and obese (7), nuances of accurately measuring WC (5, 51), are there other the current study establishes a practical clinical detection method diagnostic approaches that should be considered? Local WC that identifies those at risk even though they have a “normal” body norms developed by highly trained teams might reduce technical weight. measurement errors. Recently developed 3-dimensional optical imaging methods that can be applied in clinical settings reduce The authors’ contributions were as follows— AS, SK, MH, JSh, JSc, and human circumference measurement error, generate hundreds of SBH: concept and design; AS, JSc, SY, MH, MW, and SBH: acquisition, analysis, or interpretation of data; AS, SK, MH, JSc, and SBH: drafting of different anthropometric estimates, and offer a new opportunity the manuscript; all authors: critical revision of the manuscript for important to expand detection of increased risk body shape phenotypes (17, intellectual content; AS, JSc, SY, and MH: statistical analysis; JSh and 52). Advances in deep learning and other similar mathematical SBH: obtained funding; JSh and SBH: administrative, technical, or material methods offer a new opportunity to identify people at increased support; JSh and SBH: supervision; and all authors: read and approved the chronic disease risk using combinations of patient history and final manuscript. SBH is on the Tanita Medical Advisory Board; all other body measurements beyond those examined in the current report. authors report no conflicts of interest. Lastly, the current study reveals related demographic, body shape, body composition, and blood marker features of those at an increased risk of developing chronic diseases. References 1. Heymsfield SB, Cefalu WT. Does body mass index adequately convey a patient’s mortality risk? JAMA 2013;309(1):87–8. Limitations 2. Shah NR, Braverman ER. Measuring adiposity in patients: the utility of body mass index (BMI), percent body fat, and leptin. 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