Measurements of Abdominal Obesity are Associated with Metabolic Syndrome Severity Independent of Hypertensive Phenotype in White but not Black Young Adults.

PURPOSE: This study sought to determine if metabolic syndrome severity (MetSindex) was differentially associated with abdominal obesity based on waist circumference (WC) site and the presentation of hypertensive phenotypes in a group of young White and Black adults. METHODS: A total of 139 young adult (22.5 ± 3.3 years) non-Hispanic White (n = 73) and non-Hispanic Black (n = 66) males and females (M 53, 86 F) completed this cross-sectional evaluation. Participants had their WC measured at three distinct locations along the abdomen which were used to calculate waist-to-hip and waist-to-height ratios. Systolic (SBP) and diastolic blood pressure (DBP) were collected and used to calculate mean arterial pressure (MAP). In addition to traditional metabolic syndrome (MetS) risk factors, BP values were individually used to produce three separate MetSindex scores representing three specific hypertensive phenotypes (MetSSBP, MetSDBP, MetSMAP), and each of these were evaluated against each abdominal obesity estimate. RESULTS: MetSDBP and MetSSBP were significantly higher than all other indices for females (all p ≤ 0.002) and males (all p < 0.001), respectively. MetSDBP was significantly higher than MetSMAP for White females (p = 0.039), and MetSSBP was significantly higher than MetSDBP and MetSMAP (both p < 0.001) for Black males. Standalone and joint estimates of abdominal obesity were uniquely associated with MetSindex across hypertensive phenotypes for White, but not Black males and females. CONCLUSIONS: Specific hypertensive phenotypes may differentially determine MetSindex, but these estimates are not associated with abdominal obesity in young Black adults regardless of measurement location. Healthcare professionals should address this disparity by providing more comprehensive MetS screening procedures for young Black adults. CLINICAL TRIALS REGISTRATION: NCT05885672.

Validation of a Novel Perceptual Body Image Assessment Method Using Mobile Digital Imaging Analysis: A Cross-Sectional Multicenter Evaluation in a Multiethnic Sample.

Given that mobile digital imaging analyses (DIA) are equipped to automate body composition and subsequently alter one's appearance at a given objective body fat percent (BF%), the purpose of this study was to validate the use of this tool for assessments of body image. Participants (f = 134, m = 89) from two separate centers underwent body composition scans using a mobile DIA and completed the Multidimensional Body Self-Relations Questionnaire-Appearance Scale (MBSRQ-AS). Using a DIA-generated avatar, participants altered their figure so that it represented their perceived body, ideal body, and what a partner would find attractive. Distortion was calculated as perceived minus actual BF% and dissatisfaction was calculated as either ideal or partner minus perceived BF%. The total sample and females (p < 0.050), but not males, had significantly lower perceived BF% compared to their actual. Ideal and partner BF% was significantly lower than the perceived BF% for all groups (all p < 0.050). Ideal and partner BF% mean differences (MD) from perceived were positively associated with appearance evaluation (AE) and body area satisfaction (BAS) and negatively associated with overweight preoccupation and self-classified weight for the total sample (all p < 0.050). PerceivedMD demonstrated negative associations with AE and BAS (p < 0.050), but only for females when separated by sex. Perceptual body image measured by DIA is significantly associated with attitudinal body image and may allow practitioners to better quantify this growing issue.

Fat-free mass is associated with exercise pressor responses, but not cold pressor responses, in humans: influence of maximal voluntary contraction.

Objective: This study examined the contributions of fat mass (FM) and fat-free mass (FFM) to the magnitude of exercise pressor responses in humans. Methods: The cumulative blood pressure responses (blood pressure index; BPI) to handgrip exercise (BPIhg), post-exercise-circulatory-occlusion (BPIpeco), and cold-pressor activation (BPIcpt) were collected from 67 individuals grouped by BMI (27.8 ± 7.3 kg/m2), FFM index (FFMi, 29.1 ± 3.8 kg/m2), and FM index (FMi 12.5 ± 4.8 kg/m2) quartiles. BPI responses to HG were also normalized to the time-tension index of HG, providing a relative index of exercise pressor response magnitude (BPInorm). Results: BPIhg and BPIpeco were significantly elevated in the third FFMi quartile (p ≤ 0.034), while BPInorm significantly decreased in the second and fourth quartiles (p ≤ 0.029). In contrast, no differences in BPIcpt were observed across any FFMi, BMI, or FMi quartiles (p ≥ 0.268). FFM was independently associated with BPIhg, BPI-peco, and BPInorm (all p ≤ 0.049), however, FFM was eliminated as an independent predictor when maximal voluntary contraction (MVC) was included in these regression models (all p ≥ 0.495). Neither FFM nor MVC was associated with BPIcpt (p ≥ 0.229). Conclusions: These findings indicate that exercise pressor responses, but not cold-pressor responses, are significantly associated with FFM in humans, and that this association is driven by FFM related differences in MVC.

Smartphone derived anthropometrics: Agreement between a commercially available smartphone application and its parent application intended for use at point-of-care.

BACKGROUND & AIMS: Smartphone applications can now automate body composition and anthropometric measurements remotely, prompting applications intended for use at point-of-care to provide commercially available smartphone applications intended for personal use. However, the agreement between such anthropometrics remain unclear. METHODS: A total of 123 apparently healthy participants (F: 69; M: 54; age: 28.1 ± 11.3; BMI: 26.9 ± 5.9) completed consecutive body composition scans using a 3D smartphone application intended for personal use (MeThreeSixty; MTS) and it stationary counterpart intended for use in practice (Mobile Fit Booth; MFB). Agreement between devices were evaluated using root mean square error (RMSE), Bland-Altman analyses, and linear regression for all measurements, and additional equivalence testing was conducted for all circumference and limb length comparisons. RESULTS: When evaluated against the MFB, MTS significantly overestimated all measurements other than waist circumference (p = 0.670) using paired t-tests. RMSE was 2.5 % for body fat percentage (BF%), 0.64-3.74 cm for all body circumferences, 0.71-2.3 kg for all lean mass estimates, and 126-659 cm2 and 608-4672 cm3 across all body surface area and body volume estimates, respectively. BF% was the only body composition estimate that did not demonstrate proportional bias (p = 0.221). Circumferences of the chest, shoulder, biceps, forearm, and ankle all demonstrated proportional bias (all coefficients: p < 0.050), but only chest, shoulder, and arm circumferences did not demonstrate equivalence. Arm surface area (p < 0.001) and arm (p = 0.002) and leg volumes (p = 0.004) were the only body surface area and volume estimates to reveal proportional biases. CONCLUSIONS: These findings demonstrate the agreement between 3D anthropometric applications intended for clinical and personal use, particularly for whole-body composition estimates and clinically meaningful body circumferences. Given the advantages of commercially available remote applications, practitioners and consumers may consider using this method in place of those intended for clinical practice, but should express caution when overestimation is a concern.

Conflicting Associations among Bioelectrical Impedance and Cardiometabolic Health Parameters in Young White and Black Adults.

PURPOSE: The purpose of this cross-sectional evaluation was to determine the associations between raw bioelectrical impedance and cardiometabolic health parameters in a sample of young non-Hispanic White and African American adults. METHODS: A total of 96 (female: 52, male: 44) non-Hispanic White ( n = 45) and African American adults ( n = 51) between the ages of 19 and 37 yr (22.7 ± 3.83 yr) completed several fasted assessments including resting systolic blood pressure (rSBP), blood glucose (FBG), blood lipids, and bioelectrical impedance spectroscopy. Bioelectrical impedance spectroscopy-derived measurements included phase angle, bioimpedance index (BI), impedance ratio (IR), reactance index (XCi), fat-free mass (FFM), FFM index (FFMi), and absolute (a) and relative (%) total body water (TBW) and extracellular (ECF) and intracellular fluid (ICF). All bioelectric variables were collected at 50 kHz other than IR (250 kHz/5 kHz). Multiple regressions were conducted and adjusted for sex, age, and body mass index. RESULTS: rSBP was positively, and HDL was inversely, associated with all bioelectrical impedance and absolute hydration variables (all P ≤ 0.050) other than XCi for rSBP and XCi and FFMi for HDL. rSBP ( P < 0.001) was inversely, and HDL ( P = 0.034) was positively, associated with IR. FBG was positively associated with BI, XCi, FFM, TBWa, and ECFa (all P < 0.050). Metabolic syndrome severity was positively associated with BI, FFM, TBWa, and ECFa for women (all P ≤ 0.050) and with ICFa for African American women ( P = 0.016). CONCLUSIONS: Given the rapid increase in the prevalence of cardiometabolic health risks among young adults and the broad use of bioelectrical impedance in practice, the conflicting associations we observed in this age group suggest that bioelectrical impedance parameters should be used with caution in the context of cardiometabolic health risks and age.

Associations between eating behaviors and metabolic syndrome severity in young adults.

Metabolic syndrome (MetS), a precursor to cardiovascular disease and type II diabetes, is rapidly increasing in young adults. Accordingly, earlier interventions aimed at combating the onset of MetS in young adults are required. However, current behavioral interventions have failed to consider the eating behaviors that precede disease development, likely contributing to the consistently high failure rates of these interventions. The purpose of this cross-sectional study was to evaluate the associations between eating behaviors and MetS severity (MetSindex) in a sample of young adults. A sample of 104 (non-Hispanic White: 45; non-Hispanic Black: 49; Hispanic White: 5; Asian: 5) young adult (age: 23.1 ± 4.4) males and females (F:61, M:43) completed anthropometric, blood pressure, blood glucose, and blood lipid assessments; each of which were used to calculate a continuous MetSindex score. Participants also completed the revised version of the 18-item Three-factor Eating Questionnaire to measure emotional eating (EmE), uncontrolled eating (UE), and cognitive restraint (CR). EmE was positively associated with MetSindex for young adult females (p = 0.033) and non-Hispanic Black participants (p = 0.050), but not male (p = 0.506) or non-Hispanic White participants (p = 0.558). Additionally, MetSindex was greater in the highest EmE tertile compared to the lowest EmE tertile for the total sample (p = 0.037) and young adult females (p = 0.015). UE and CR were not associated with MetSindex. These data suggest a potential link between EmE and MetS severity in young adults, and that behavioral interventions aimed at MetS prevention should focus on treating the underlying EmE behaviors common in young adults, particularly for young female and Black adults at the greatest risk.

Differences in Perceptual and Attitudinal Body Image Between White and African-American Adults Matched for Sex, Age, and Body Composition.

PURPOSE: The purpose of this study was to evaluate the differences in perceptual and attitudinal body image between White and African-American males and females matched for sex, age, BMI, and other body composition components using a combination of 3-dimensional mobile digital imaging analysis (DIA) and the Multidimensional Body-Self Relations Questionnaire-Appearance Scale (MBSRQ-AS). METHODS: One-hundred non-Hispanic White (n=50) and non-Hispanic African-American (n=50) adults (M=34, F=66) matched for sex, age, BMI, and body composition components completed this cross-sectional study. Participants underwent several anthropometric assessments, completed the MBSRQ-AS, and rated their perceived appearance, ideal appearance, and the appearance they believed a partner would find societally attractive using a state of the art mobile 3-dimensional DIA produced using broad developmental populations. Body image distortion was measured as the perceived minus actual appearance, and body image dissatisfaction was defined as the ideal appearance and appearance a partner would find attractive minus the perceived appearance. RESULTS: Using the DIA, only African-American females demonstrated significant body image distortion (p<0.001); reporting perceived appearances significantly lower their than their actual. Further, AA females demonstrated significantly larger differences between their ideal and perceived appearance (p=0.009), perceived larger bodies as more attractive to a potential partner (p=0.009), and reported higher ratings of appearance evaluation (p=0.001) and body area satisfaction (p=0.011) compared to White females. CONCLUSIONS: After accounting for all anthropometric determinants of body image, perceptual and attitudinal body image differs between White and African-American adults with differences supporting larger body size acceptance for African-American individuals, particularly African-American females.

Hemodynamic responses to handgrip and metaboreflex activation are exaggerated in individuals with metabolic syndrome independent of resting blood pressure, waist circumference, and fasting blood glucose.

Introduction: Prior studies report conflicting evidence regarding exercise pressor and metaboreflex responses in individuals with metabolic syndrome (MetS). Purpose: To test the hypotheses that 1) exercise pressor and metaboreflex responses are exaggerated in MetS and 2) these differences may be explained by elevated resting blood pressure. Methods: Blood pressure and heart rate (HR) were evaluated in 26 participants (13 MetS) during 2 min of handgrip exercise followed by 3 min of post-exercise circulatory occlusion (PECO). Systolic (SBP), diastolic (DBP), and mean arterial pressure (MAP), along with HR and a cumulative blood pressure index (BPI), were compared between groups using independent samples t-tests, and analyses of covariance were used to adjust for differences in resting blood pressure, fasting blood glucose (FBG), and waist circumference (WC). Results: ΔSBP (∼78% and ∼54%), ΔMAP (∼67% and ∼55%), and BPI (∼16% and ∼20%) responses were significantly exaggerated in individuals with MetS during handgrip and PECO, respectively (all p ≤ 0.04). ΔDBP, ΔMAP, and BPI responses during handgrip remained significantly different between groups after independently covarying for resting blood pressure (p < 0.01), and after simultaneously covarying for resting blood pressure, FBG, and WC (p ≤ 0.03). Likewise, peak SBP, DBP, MAP, and BPI responses during PECO remained significantly different between groups after adjusting for resting blood pressure (p ≤ 0.03), with peak SBP, MAP, and BPI response remaining different between groups after adjusting for all three covariates simultaneously (p ≤ 0.04). Conclusion: These data suggest that exercise pressor and metaboreflex responses are significantly exaggerated in MetS independent of differences in resting blood pressure, FBG, or WC.

Raw bioelectrical impedance measurements are not different between White and Black adults when matched for sex, age, BMI, and other physical characteristics.

Raw bioelectrical impedance measurements are often used as a prognosticator of health status because of their association with disease states and malnutrition. Although studies consistently show the effect of physical characteristics on bioelectrical impedance, few investigations describe the effect of race, particularly for Black adults, and many bioelectrical impedance standards were produced from primarily White adults almost 2 decades ago. Therefore, this study sought to evaluate the racial differences in bioelectrical impedance measurements using bioimpedance spectroscopy between non-Hispanic White and non-Hispanic Black adults matched for age, sex, and body mass index. We hypothesized that Black adults would have a lower phase angle from higher resistance and lower reactance compared with White adults. One hundred non-Hispanic White (n = 50) and non-Hispanic Black (n = 50) males (n = 34) and females (n = 66) matched for sex, age, and body mass index completed this cross-sectional study. Participants underwent several anthropometric assessments, including height, weight, waist circumference, hip circumference, bioimpedance spectroscopy, and dual-energy X-ray absorptiometry. Bioelectrical impedance measures of resistance, reactance, phase angle, and impedance were all collected at frequencies of 5, 50, and 250 kHz and bioelectrical impedance vector analysis was performed using 50-kHz data. There were no significant differences for any anthropometric variable between Black and White participants in the total sample or by sex groups. In addition, there were no significant racial differences for any bioelectrical impedance assessment, including bioelectrical impedance vector analysis. Differences in bioelectrical impedance are likely not a function of race between Black and White adults and concerns regarding its utility should not be based on this characteristic.

Evaluation of automated anthropometrics produced by smartphone-based machine learning: a comparison with traditional anthropometric assessments.

Automated visual anthropometrics produced by mobile applications are accessible and cost effective with the potential to assess clinically relevant anthropometrics without a trained technician present. Thus, the aim of this study was to evaluate the precision and agreement of smartphone-based automated anthropometrics against reference tape measurements. Waist and hip circumference (WC; HC), waist:hip ratio (WHR) and waist:height ratio (W:HT) were collected from 115 participants (69 F) using a tape measure and two smartphone applications (MeThreeSixty®, myBVI®) across multiple smartphone types. Precision metrics were used to assess test-retest precision of the automated measures. Agreement between the circumferences produced by each mobile application and the reference were assessed using equivalence testing and other validity metrics. All mobile applications across smartphone types produced reliable estimates for each variable with intraclass correlation coefficients ≥ 0·93 (all P < 0·001) and root mean square coefficient of variation between 0·5 and 2·5 %. Precision error for WC and HC was between 0·5 and 1·9 cm. WC, HC, and W:HT estimates produced by each mobile application demonstrated equivalence with the reference tape measurements using 5 % equivalence regions. Mean differences via paired t-tests were significant for all variables across each mobile application (all P < 0·050) showing slight underestimation for WC and slight overestimation for HC which resulted in a lack of equivalence for WHR compared with the reference tape measure. Overall, the results of our study support the use of WC and HC estimates produced from automated mobile applications, but also demonstrates the importance of accurate automation for WC and HC estimates given their influence on other anthropometric assessments and clinical health markers.

Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.

BACKGROUND: Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the accuracy of the artificial intelligence used in DIA is reliant on the accuracy of the developmental methods. Few DIA applications are trained by multicompartment models, but this developmental strategy may be most accurate. Thus, the aim of the present study was to assess the precision and agreement of a DIA application with developmental software trained by a four-compartment (4C) model using an actual 4C model as the criterion method. METHODS: For this cross-sectional study, body composition estimations were collected from 102 participants (63 females, 39 males) using the methods necessary for a rapid 4C model and a DIA application using two different smartphones. RESULTS: Intraclass correlation coefficients (0.96-0.99; all p < 0.001) and root mean square coefficients of variation (0.5%-3.0%) showed good reliability for body fat percentage, fat mass and fat-free mass. There were no significant mean differences between the 4C model or the DIA estimates for the total sample, by sex, and for non-Hispanic White (n = 61) and Black/African-American (n = 32) participants (all p > 0.050). DIA estimates demonstrated equivalence with the 4C model for all variables but revealed proportional biases that underestimated body fat percentage (both ß = -0.25; p < 0.001) and fat mass (both ß = -0.07; p < 0.010) at higher degrees of each variable. CONCLUSIONS: DIA applications trained by a 4C model are reliable and produce body composition estimates equivalent to an actual 4C model.

Smartwatch-based bioimpedance analysis for body composition estimation: precision and agreement with a 4-compartment model.

Given that the prevalence of smartwatches has allowed them to become a hallmark in health monitoring, they are primed to provide accessible body composition estimations. The purpose of this study was to evaluate the precision and agreement of smartwatch-based bioimpedance analysis (SW-BIA) and multifrequency bioimpedance analysis (MFBIA) against a 4-compartment (4C) model criterion. A total of 186 participants (114 females) underwent body composition assessments necessary for a 4C model and SW-BIA and MFBIA. Values of total body water (TBW) from each device were compared with those obtained from bioimpedance spectroscopy. Precision was adequate though slightly lower for the smartwatch compared with other methods. No device demonstrated equivalence with the 4C model. Specifically, the SW-BIA overestimated and MFBIA underestimated body fat. MFBIA, but not SW-BIA, demonstrated equivalence for TBW. Overall error was higher for males using the smartwatch compared with females. While these findings do not invalidate the use of smartwatch-based estimates, clinicians should consider that there may be large errors relative to clinical measures. If this wearable device is intended to be used to monitor body composition change over time, these findings demonstrate the need for future research to evaluate its accuracy during follow-up testing.

Associations between visceral adipose tissue estimates produced by near-infrared spectroscopy, mobile anthropometrics, and traditional body composition assessments and estimates derived from dual-energy X-ray absorptiometry.

Assessments of visceral adipose tissue (VAT) are critical in preventing metabolic disorders; however, there are limited measurement methods that are accurate and accessible for VAT. The purpose of this cross-sectional study was to evaluate the association between VAT estimates from consumer-grade devices and traditional anthropometrics and VAT and subcutaneous adipose tissue (SAT) from dual-energy X-ray absorptiometry (DXA). Data were collected from 182 participants (female = 114; White = 127; Black/African-American (BAA) = 48) which included anthropometrics and indices of VAT produced by near-infrared reactance spectroscopy (NIRS), visual body composition (VBC) and multifrequency BIA (MFBIA). VAT and SAT were collected using DXA. Bivariate and partial correlations were calculated between DXAVAT and DXASAT and other VAT estimates. All VAT indices had positive moderate-strong correlations with VAT (all P < 0·001) and SAT (all P < 0·001). Only waist:hip (r = 0·69), VATVBC (r = 0·84), and VATMFBIA (r = 0·86) had stronger associations with VAT than SAT (P < 0·001). Partial associations between VATVBC and VATMFBIA were only stronger for VAT than SAT in White participants (r = 0·67, P < 0·001) but not female, male, or BAA participants individually. Partial correlations for waist:hip were stronger for VAT than SAT, but only for male (r = 0·40, P < 0·010) or White participants (r = 0·48, P < 0·001). NIRS was amongst the weakest predictors of VAT which was highest in male participants (r = 0·39, P < 0·010) but non-existent in BAA participants (r = -0·02, P > 0·050) after adjusting for SAT. Both anthropometric and consumer-grade VAT indices are consistently better predictors of SAT than VAT. These data highlight the need for a standardised, but convenient, VAT estimation protocol that can account for the relationship between SAT and VAT that differs by sex/race.

Visual body composition assessment methods: A 4-compartment model comparison of smartphone-based artificial intelligence for body composition estimation in healthy adults.

BACKGROUND & AIMS: Visual body composition (VBC) estimates produced from smartphone-based artificial intelligence represent a user-friendly and convenient way to automate body composition remotely and without the inherent geographical and monetary restrictions of other body composition methods. However, there are limited studies that have assessed the reliability and agreement of this method and thus, the aim of this study was to evaluate VBC estimates compared to a 4-compartment (4C) criterion model. METHODS: A variety of body composition assessments were conducted across 184 healthy adult participants (114 F, 70 M) including dual-energy X-ray absorptiometry and bioimpedance spectroscopy for utilization in the 4C model and automated assessments produced from two smartphone applications (Amazon Halo®, HALO; and myBVI®) using either Apple® or Samsung® phones. Body composition components were compared to a 4C model using equivalence testing, root mean square error (RMSE), and Bland-Altman analysis. Separate analyses by sex and racial/ethnic groups were conducted. Precision metrics were conducted for 183 participants using intraclass correlation coefficients (ICC), root mean squared coefficients of variation (RMS-%CV) and precision error (PE). RESULTS: Only %fat produced from HALO devices demonstrated equivalence with the 4C model although mean differences for HALO were <±1.0 kg for FM and FFM. RMSEs ranged from 3.9% to 6.2% for %fat and 3.1-5.2 kg for FM and FFM. Proportional bias was apparent for %fat across all VBC applications but varied for FM and FFM. Validity metrics by sex and specific racial/ethnic groups varied across applications. All VBC applications were reliable for %fat, fat mass (FM), and fat-free mass (FFM) with ICCs ≥0.99, RMS-%CV between 0.7% and 4.3%, and PEs between 0.3% and 0.6% for %fat and 0.2-0.5 kg for FM and FFM including assessments between smartphone types. CONCLUSIONS: Smartphone-based VBC estimates produce reliable body composition estimates but their equivalence with a 4C model varies by the body composition component being estimated and the VBC being employed. VBC estimates produced by HALO appear to have the lowest error, but proportional bias and estimates by sex and race vary across applications.

Sport Differences in Fat-Free Mass Index Among a Diverse Sample of NCAA Division III Collegiate Athletes.

ABSTRACT: Brandner, CF, Harty, PS, Luedke, JA, Erickson, JL, and Jagim, AR. Sport differences in fat-free mass index among a diverse sample of NCAA Division III collegiate athletes. J Strength Cond Res 36(8): 2212-2217, 2022-Fat-free mass index (FFMI) is becoming a popular metric to determine an athlete's potential for future fat-free mass accrual or to identify athletes who may be at risk for low fat-free mass (FFM). The aim of the current study was to examine sport-specific differences in FFMI among a cohort of collegiate athletes. NCAA Division III male ( n = 98; age: 20.1 ± 1.6 years, height: 1.82 ± 0.06 m, body mass: 92.7 ± 17.5 kg, %BF: 15.6 ± 8.8%) and female ( n = 92; age: 19.45 ± 1.1 years, height: 1.68 ± 0.06 m, body mass: 65.16 ± 11.04 kg, %BF: 22.71 ± 5.9%) athletes completed a body composition assessment using air displacement plethysmography. Fat-free mass index was calculated by dividing FFM by height squared. The mean ± SD FFMI was significantly higher ( p < 0.05) for males (23.37 ± 2.41 kg·m -2 ) compared with females (17.54 ± 1.8 kg·m -2 ). There was a significant main effect for sport category. Post hoc analysis indicated that throwers had a higher ( p < 0.001) FFMI (mean difference, 95% confidence interval) compared with sprinters and soccer athletes (4.17, 2.03-6.32 kg·m -2 ), endurance and weight-sensitive athletes (4.91, 2.67-7.14 kg·m -2 ), and court sport athletes (4.39, 1.97-6.81 kg·m -2 ), respectively, among female athletes. Post hoc analysis indicated that football players had a higher ( p < 0.01) FFMI than distance runners (3.89, 2.15, 5.62) and wrestlers (2.23, 0.78, 3.68), among male athletes. These findings indicate that sex differences in FFMI exist, with differences identified between sports. These findings can guide strength and nutritional programming decisions by providing sport-specific normative data profiles.