Total Fat Percentage Research Articles

Sarcopenia Prediction for Elderly People Using Machine Learning: A Case Study on Physical Activity.

Sarcopenia is a well-known age-related disease that can lead to musculoskeletal disorders and chronic metabolic syndromes, such as sarcopenic obesity. Numerous studies have researched the relationship between sarcopenia and various risk factors, leading to the development of predictive models based on these factors. In this study, we explored the impact of physical activity (PA) in daily life and obesity on sarcopenia prediction. PA is easier to measure using personal devices, such as smartphones and watches, or lifelogs, than using other factors that require medical equipment and examination. To demonstrate the feasibility of sarcopenia prediction using PA, we trained various machine learning models, including gradient boosting machine (GBM), xgboost (XGB), lightgbm (LGB), catboost (CAT), logistic regression, support vector classifier, k-nearest neighbors, random forest (RF), multi-layer perceptron, and deep neural network (DNN), using data samples from the Korea National Health and Nutrition Examination Survey. Among the models, the DNN achieved the most precise accuracy on average, 81%, with PA features across all data combinations, and the accuracy increased up to 90% with the addition of obesity information, such as total fat mass and fat percentage. Considering the difficulty of measuring the obesity feature, when adding waist circumference to the PA features, the DNN recorded the highest accuracy of 84%. This model accuracy could be improved by using separate training sets according to gender. As a result of measurement with various metrics for accurate evaluation of models, GBM, XGB, LGB, CAT, RF, and DNN demonstrated significant predictive performance using only PA features including waist circumference, with AUC values at least around 0.85 and often approaching or exceeding 0.9. We also found the key features for a highly performing model such as the quantified PA value and metabolic equivalent score in addition to a simple obesity measure such as body mass index (BMI) and waist circumference using SHAP analysis.

Feeding strategies to increase sow colostrum quality and yield

Effects of nutritional strategies on colostrum quality and yield are variable as influenced by sow colostrum production capacity, parity, farrowing induction protocol, and gestation length. The greatest opportunity to maximize colostrum yield and quality is through proper management of body condition in gestation such that sows are not in a negative energy balance when entering farrowing. Total colostrum fat percentage can be increased through the addition of dietary fat or oil. Colostrum fatty acid composition can also be changed by addition of dietary oil or increased branched chain amino acids. Colostrum protein and immunoglobulins are more challenging to influence.

Body composition predicts hypertension using machine learning methods: a cohort study

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35–70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

The efficacy and safety of cupping as complementary and alternative therapy for metabolic syndrome: A systematic review and meta-analysis.

This systematic review and meta-analysis aimed to assess the efficacy and safety of cupping therapy in patients with metabolic syndrome (MetS). This systematic review focused on patients with MetS and included randomized controlled trials (RCTs) that compared the effects of cupping therapy with control groups. A total of 12 electronic databases were searched from inception until February 03, 2023. The main outcome after the meta-analysis was waist circumference; the others included anthropometric variables, blood pressure, lipid profile, fasting blood glucose level, and high-sensitivity C-reactive protein level. The incidence of adverse events and the follow-up courses were also evaluated. Risk of bias (ROB) was evaluated using ROB 2.0 from the Cochrane Handbook. This systematic review included five studies involving 489 patients. Some risks of bias were also identified. The meta-analysis revealed a statistically significance in waist circumference (MD = -6.07, 95% CI: -8.44 to -3.71, P < .001, I2 = 61%, τ2 = 3.4), body weight (MD = -2.46, 95% CI: -4.25 to -0.68, P = .007, I2 = 0%, τ2 = 0) and body mass index (MD = -1.26, 95% CI: -2.11 to -0.40, P = .004, I2 = 0%, τ2 = 0) between the cupping therapy and control groups. However, there were no significant results in total fat percentage and blood pressure values. Regarding biochemical markers, cupping significantly lowered the concentration of low-density lipoprotein cholesterol (MD = -3.98, 95% CI: -6.99 to -0.96, P = .010, I2 = 0%, τ2 = 0) but had no significant effect on total cholesterol, triglyceride, high-density lipoprotein cholesterol, fasting blood glucose, and high-sensitivity C-reactive protein. 3 RCTs reported no adverse events. Despite some ROB and low to substantial heterogeneity of the included studies, cupping therapy can be considered a safe and effective complementary intervention for reducing waist circumference, body weight, body mass index, and low-density lipoprotein cholesterol in patients with MetS. In the future, well-designed, high-quality, rigorous methodology, and long-term RCTs in this population are required to assess the efficacy and safety of cupping therapy.

The Correlation of Apolipoprotein B with Alterations in Specific Fat Depots Content in Adults.

Body mass index (BMI) and blood biomarkers are not enough to predict cardiovascular disease risk. Apolipoprotein B was identified to be associated with cardiovascular disease (CVD) progression. The Dual-energy X-ray Absorption (DXA) results could be considered as a predictor for cardiovascular disease in a more refined way based on fat distribution. The prediction of CVD risk by simple indicators still cannot meet clinical needs. The association of ApoB with specific fat depot features remains to be explored to better co-predict cardiovascular disease risk. An amount of 5997 adults from National Health and Nutrition Examination Survey (NHANES) were enrolled. Their demographic information, baseline clinical condition, blood examination, and DXA physical examination data were collected. Multivariate regression was used to assess the correlation between ApoB and site-specific fat characteristics through different adjusted models. Smooth curve fittings and threshold analysis were used to discover the turning points with 95% confidence intervals. ApoB is positively correlated with arms percent fat, legs percent fat, trunk percent fat, android percent fat, gynoid percent fat, arm circumference and waist circumference after adjustment with covariates for age, gender, race, hypertension, diabetes, hyperlipidemia, coronary heart disease, smoking status and vigorous work activity. The smooth curve fitting and threshold analysis also showed that depot-specific fat had lower turning points of ApoB in both males and females within the normal reference range of ApoB. Meanwhile, females have a lower increase in ApoB per 1% total percent fat and android percent fat than males before the turning points, while females have a higher growth of ApoB per 1% gynoid percent fat than males. The combined specific fat-depot DXA and ApoB analysis could indicate the risk of CVD in advance of lipid biomarkers or DXA alone.

The relationship between FGF23 and body composition according to albuminuria stage in type 1 diabetes

AimsFibroblast growth factor 23 (FGF23) and obesity are linked to kidney disease. However, the relationship between FGF23 and body composition is unclear. Associations between FGF23 and body composition were investigated in type 1 diabetes from the Finnish Diabetic Nephropathy Study according to albuminuria stages. MethodsData were available from 306 adults with type 1 diabetes (229 normal albumin excretion rate, T1Dnormo; 38 microalbuminuria, T1Dmicro; 39 macroalbuminuria, T1Dmacro), and 36 controls. Serum FGF23 was measured by ELISA. Body composition was assessed with dual-energy X-ray absorptiometry. Associations between body composition and serum FGF23 were investigated using linear regression models. ResultsCompared with T1Dnormo, individuals with more advanced kidney disease were older, had longer diabetes duration, higher serum hsCRP, and higher FGF23 concentration. However, FGF23 concentration was comparable between T1Dnormo and controls. Adjusted for potential confounders, in T1Dmicro, FGF23 was positively associated with the percentages of total fat, visceral fat, and android fat tissues, while negative associations between FGF23 and lean tissue were observed. FGF23 was not associated with body composition in T1Dnormo, T1Dmacro, and controls. ConclusionsIn type 1 diabetes, the relationship between FGF23 and body composition is dependent on albuminuria stages.

Hepatic follistatin increases basal metabolic rate and attenuates diet-induced obesity during hepatic insulin resistance

ObjectiveBody weight change and obesity follow the variance of excess energy input balanced against tightly controlled EE (energy expenditure). Since insulin resistance can reduce energy storage, we investigated whether genetic disruption of hepatic insulin signaling reduced adipose mass with increased EE. MethodsInsulin signaling was disrupted by genetic inactivation of Irs1 (Insulin receptor substrate 1) and Irs2 in hepatocytes of LDKO mice (Irs1L/L·Irs2L/L·CreAlb), creating a state of complete hepatic insulin resistance. We inactivated FoxO1 or the FoxO1-regulated hepatokine Fst (Follistatin) in the liver of LDKO mice by intercrossing LDKO mice with FoxO1L/L or FstL/L mice. We used DEXA (dual-energy X-ray absorptiometry) to assess total lean mass, fat mass and fat percentage, and metabolic cages to measure EE (energy expenditure) and estimate basal metabolic rate (BMR). High-fat diet was used to induce obesity. ResultsHepatic disruption of Irs1 and Irs2 (LDKO mice) attenuated HFD (high-fat diet)-induced obesity and increased whole-body EE in a FoxO1-dependent manner. Hepatic disruption of the FoxO1-regulated hepatokine Fst normalized EE in LDKO mice and restored adipose mass during HFD consumption; moreover, hepatic Fst disruption alone increased fat mass accumulation, whereas hepatic overexpression of Fst reduced HFD-induced obesity. Excess circulating Fst in overexpressing mice neutralized Mstn (Myostatin), activating mTORC1-promoted pathways of nutrient uptake and EE in skeletal muscle. Similar to Fst overexpression, direct activation of muscle mTORC1 also reduced adipose mass. ConclusionsThus, complete hepatic insulin resistance in LDKO mice fed a HFD revealed Fst-mediated communication between the liver and muscle, which might go unnoticed during ordinary hepatic insulin resistance as a mechanism to increase muscle EE and constrain obesity.

Physical Performance and Morphological Characteristics of Young Basketball Players before and after COVID-19

The aim of this study was to determine possible changes in physical performance and morphological characteristics in young basketball players before and after quarantine caused by COVID-19. The research was conducted on a total sample of 46 young basketball players. Participants were measured before the quarantine and pandemic in January 2020 and then after the quarantine period, one year later in March 2021. The results indicate the existence of significant differences in total muscle mass (p < 0.01) in favor of higher values measured before quarantine. Moreover, total fat percentage was higher (p < 0.03) after quarantine. As for physical performance, significant differences were also observed in the counter movement jump test (p < 0.05) and the 20 m shuttle run test (p < 0.05), with significantly poorer results for the group of participants measured after quarantine. The authors conclude that the consequences of the quarantine and pandemic of the SARS-CoV-2 virus were definitely negative, as higher values of body fat and lower values of the percentage of total muscle mass were observed. In addition, a lower level of the explosive power of lower limbs was observed, accompanied by lower aerobic endurance in young basketball players.

An updated validation of the Dietary Quality Score: associations with risk factors for cardiometabolic diseases in a Danish population.

This study assessed the validity of the Dietary Quality Score (DQS) and investigated the association between the DQS and risk factors for cardiometabolic diseases. The DQS was calculated based on an updated 23-item FFQ and validated against a 376-item FFQ. A sub-sample of 450 men and women aged 18-73years, from the Danish Diet, Cancer and Health-Next generations (DCH-NG) cohort, completed the updated 23-item FFQ. We investigated the associations between the DQS and risk factors for cardiometabolic diseases (lipids, haemoglobin A1c (HbA1c), high-sensitive C-reactive protein (hs-CRP), blood pressure (BP), waist circumference (WC), visceral and total fat mass) using linear regression models. A high DQS, i.e. healthy dietary habits, was significantly associated with a higher intake of fruits, vegetables, fish, fibre, several vitamins and minerals and a lower intake of saturated fat. Moreover, a high DQS was significantly associated with lower levels of LDL cholesterol (P = 0.0133), Hs-CRP (P = 0.0449), WC (P = 0.0161), visceral fat (P = 0.0003), total fat mass (P = 0.0106) and total fat percentage (P = 0.0030) and significantly associated with a higher HDL cholesterol (P = 0.0379) level, when adjusting for education, smoking habits and physical activity. There was no association with total cholesterol, triglycerides, HbA1c, BP and BMI. The DQS, based on the updated 23-item FFQ, is a valid tool to classify individuals into groups with low, average and high dietary quality in the Danish population. Furthermore, a high DQS is significantly associated with lower levels of several risk factors for cardiometabolic diseases.

Association Between Different Parameters of Adipose Distribution and Transient Elastography-Assessed Hepatic Steatosis in American Adults with Diabetes, Prediabetes and Normal Glucose Tolerance.

To investigate the association between adipose distribution and hepatic steatosis in American adults and to assess whether this association varies among different blood glucose states. Data from the American National Health and Nutrition Examination Survey (NHANES) 2017-2018 were analyzed. The subjects were divided into three groups: diabetes, prediabetes and normal glucose tolerance (NGT). Hepatic steatosis was quantified by median controlled attenuation parameter (CAP), which was measured by ultrasound transient elastography. Total abdominal fat volume, visceral adipose tissue (VAT) volume, total percent fat, trunk percent fat, android percent fat and android to gynoid ratio (AGR) was measured by dual-energy X-ray absorptiometry (DXA). Data pertaining to 2986 participants (1581 with hepatic steatosis) were included in the analysis. In the NGT group, the proportion of S0 (<5% of the hepatocytes with fatty infiltration) was 58.9%, and 25.2% for S3 (≥66% of the hepatocytes with fatty infiltration). In contrast, the proportion of S0 was 11.1%, while S3 accounts for as high as 68.7% in the diabetes group. In the NGT group, all parameters of fat distribution revealed a positive relation with the occurrence of hepatic steatosis (p<0.05) except total percent fat (p=0.872) after adjusting for confounding factors. In the prediabetes group, VAT volume, trunk percent fat, android percent fat and AGR had significant influence on hepatic steatosis (p<0.05). As for diabetes, only AGR remained significantly correlated with hepatic steatosis (p=0.004). For NGT individuals, high level of total abdominal fat volume, VAT volume, trunk percent fat, android percent fat and AGR all can be used to predict hepatic steatosis. For diabetes, only AGR can predict hepatic steatosis among the surveyed parameters of adipose distribution.

Body composition of type 2 diabetes patients in Uganda: A case-control study.

The prevalence of obesity among people diagnosed with Type 2 Diabetes Mellitus (T2DM) has been widely documented. However, the specific composition of this bodyweight remains largely unknown. The study aimed to understand the body composition of T2DM patients using the bioelectric impedance analysis technique, comparing findings to sex and agematched controls. A comparative case-control study was carried out among 139 known cases of Type 2 diabetes aged 18 to 78 years randomly sampled from the diabetic clinic of Mbarara Regional Referral Hospital. We matched them to 139 hospital controls who were healthy non-diabetic attendants. Body composition parameters were computed and summarized as medians and interquartile ranges. Differences in the medians of body composition parameters were further assessed using the Mann- Whitney U test. Fat-free and fat mass indices were derived to offer a precise estimation of body composition parameters adjusted for height differences among study participants. Cases had significantly higher median systolic blood pressure, pulse rate, weight, Body Mass Index (BMI), Waist-Hip Ratio (WHR), total fat percentage, fat mass amount, Fat Mass Index, visceral fat, and metabolic age than their counterparts, whereas controls had significantly higher median total body water percentage versus cases. The highest significant differences occurred in fat percentage composition (Cases: β: 6.9 (95% C.I: 4.4, 9.4); Controls: Ref) followed by visceral fat (Cases: β: 3.5 (95% C.I: 2.5, 4.4); controls: Ref) and Fat Mass Index (Cases: 95% C.I: 2.6 (95% C.I: 1.6, 3.7). Cases had significantly higher Fat Mass Index, visceral fat and fat percentage (all p<0.05) than controls. Routine assessment of body composition of T2DM patients needs to be done to assess the amount, type and pattern of weight gain to prevent increases in adiposity.

Almond Consumption during Energy Restriction Lowers Truncal Fat and Blood Pressure in Compliant Overweight or Obese Adults

Background: The inclusion of almonds in an energy-restricted diet has been reported both to enhance or to have no effect on weight loss. Their effects specifically on visceral body fat stores during energy restriction have not been widely examined. In addition, almond consumption has been associated with reduced blood pressure (BP), but whether this is linked to or independent of changes in body composition has to our knowledge not been examined.Objective: We evaluated the effects of consuming almonds as part of an energy-restricted diet on body composition, specifically visceral adipose tissue (VAT) and BP, compared to a nut-free energy-restricted diet.Methods: A randomized controlled 12-wk clinical trial of 86 healthy adults [body mass index (in kg/m2): 25–40] was conducted. Participants were randomly assigned to 1 of 2 energy-restricted (500-kcal deficit/d) diets: an almond-enriched diet (AED) (15% energy from almonds) or a nut-free diet (NFD). A linear mixed-model analysis on primary outcomes such as body weight, body fat, VAT, and BP was performed on all participants [intention-to-treat (ITT) analysis] and compliant participants (complier analysis).Results: Body weight, truncal and total fat percentage, VAT, and systolic BP decreased after 12 wk of energy restriction in both the ITT and complier analyses (P < 0.05). The complier analysis (but not the ITT analysis) indicated a greater mean ± SEM reduction in truncal fat (AED: −1.21% ± 0.26%; NFD: −0.48% ± 0.24%; P = 0.025), total fat (AED: −1.79% ± 0.36%; NFD: −0.74% ± 0.33%; P = 0.035), and diastolic BP (AED: −2.71 ± 1.2 mm Hg; NFD: 0.815 ± 1.1 mm Hg; P = 0.029), and a greater tendency for VAT loss (AED: −8.19 ± 1.8 cm2; NFD: −3.99 ± 1.7 cm2; P = 0.09) over time in the AED group than the NFD group.Conclusions: Moderate almond consumption by compliant overweight and obese individuals during energy restriction results in greater proportional reductions of truncal and total body fat as well as diastolic BP and hence may help to reduce metabolic disease risk in obesity. This trial was registered at clinicaltrials.gov as NCT02360787.

Knowledge about NCD in medical students and screening for their nutritional status

Background: Creating awareness about NCD prevention and screening medical students’ nutritional status will help them to follow a healthy lifestyle. Thus, ensuring that as future doctors, they will be effective in community education of NCD prevention through their own health. Methods: A two-hour awareness session was taken for 150 medical students to explain importance of assessing their risk factors for NCD. The age range was 18-21 years. They were offered a free health check-up and 89.33% (136) signed up. For screening of obesity - anthropometric measurements were taken 1) weight by electronic weighing scale 2) height- using analog measuring tape 3) waist hip measurement 4) body fat composition measured by Omron (Karada scan- body composition monitor HBF-375). BMI was calculated using both WHO and Asian cut-offs and waist circumference using WHO and ICMR cut-offs. Results: In 132 (M=55, F=79) participants, significant incidence was seen of overweight (21.21%), obesity (43.18%) by Asia Pacific BMI standards and 36.36% overweight, 36.36% obesity by total body fat measurement. Abdominal obesity measured by waist circumference was seen in 3.22% of males and 21.52% of females by WHO; 15.09% of males and 41.77% of females by ICMR standards. Females showed a higher incidence of obesity and overweight than males according to Asia Pacific BMI, total fat percent and ICMR waist circumference. Conclusions: These students will benefit from interventions to inculcate a healthy lifestyle and maintain a healthy weight. Healthy medical students tracking into healthy doctors will act as ambassadors for NCD prevention.

COVID-19 Induces Body Composition and Metabolic Alterations.

Background Individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are highly susceptible to disease-related metabolic dysregulation given the hyperinflammatory immune response of coronavirus disease 2019 (COVID-19). These changes are remarkably involved in multiple steps in adipogenesis and lipolysis. This study aimed to elaborate on the significant relations of COVID-19 infection with body fat distribution, changes in serum insulin, and homeostasis model assessment-estimated insulin resistance (HOMA-IR) levels before and after the infection. Methods In this follow-up study, from July 2021 to September 2021, persons referred to a university-affiliated Nutrition Counselling Clinic were randomly selected for the study samples. Validated food frequency (FFQ) and physical activity questionnaires were completed. Body composition was assessed in this investigation. On the second visit, those who reported mild to moderate COVID-19 infection (without hospitalization) were selected as the case group and the asymptomatic individuals as the control group. All measurements were re-measured in the second visit. Results In a total of 441 patients, the mean age was 38.82±4.63 years. There were 224 (50.79%) male subjects, and 217 (49.20%) were females. There was a statistically significant difference in the longitudinal change in total fat percentage between subjects with and without COVID-19. Also, the difference in HOMA-IR before and after COVID-19 in case groups (both males and females) was statistically significant (P-value < 0.001). Moreover, serum insulin levels were significantly increased in all cases (P-value < 0.001), while remaining stable in control groups. When compared to their initial visit, COVID-19 patients' total fat percentage rose significantly (almost 2%) following a hypocaloric diet. Participants who were not infected with COVID-19 had a lower total fat percentage than those who were. Serum insulin and HOMA-IR levels increased significantly after infection compared to the primary measurements. Conclusion Individuals with COVID-19 infection may require tailored medical nutrition therapy to improve short and long-term COVID-19 outcomes such as muscle loss and fat accommodation.

Resistance Exercise Training Increases Muscle Mass and Strength in Prostate Cancer Patients on Androgen Deprivation Therapy.

This study aimed to assess the effects of 20 wk resistance exercise training with or without protein supplementation on body composition, muscle mass, muscle strength, physical performance, and aerobic capacity in prostate cancer patients receiving androgen deprivation therapy (ADT). Sixty prostate cancer patients receiving ADT were randomly assigned to perform 20 wk of resistance exercise training with supplementation of 31 g whey protein (EX + PRO, n = 30) or placebo (EX + PLA, n = 30), consumed immediately after exercise and every night before sleep. A separate control group (CON, n = 36) only received usual care. At baseline and after 20 wk, body composition (dual-energy x-ray absorptiometry), muscle mass (computed tomography scan), muscle strength (1-repetition maximum strength tests), physical performance (Timed Up and Go Test, 30-Second Chair Stand Test, and Stair Climb Test), aerobic capacity (cardiopulmonary exercise test), and habitual dietary intake (food diary) were assessed. Data were analyzed using a two-factor repeated-measures ANOVA. Over time, muscle mass and strength increased in EX + PRO and EX + PLA and decreased in CON. Total fat mass and fat percentage increased in EX + PRO and CON, but not in EX + PLA. Physical performance did not significantly change over time in either group. Aerobic capacity was maintained in EX + PLA, but it decreased in EX + PRO and CON. Habitual protein intake (without supplements) averaged >1.0 g·kg body weight -1 ·d -1 , with no differences over time or between groups. In prostate cancer patients, resistance exercise training counteracts the adverse effects of ADT on body composition, muscle mass, muscle strength, and aerobic capacity, with no additional benefits of protein supplementation.

PMON219 Disparities in Musculoskeletal Health Profiles Across Race and Ethnicity in United States-Based Women with Polycystic Ovary Syndrome per the 2018 International Guideline

Abstract The magnitude and direction to which alterations in non-fat components of musculoskeletal composition (bone, muscle) may disproportionately impact diverse populations of women with polycystic ovary syndrome (PCOS) are unknown, despite clinical relevance. The uncertainty stems, partly, from heterogeneity in PCOS diagnostic criteria used and technical barriers in the reliable assessment of PCOS. We evaluated whether musculoskeletal (total and regional lean body mass [LBM] and bone mineral density [BMD]) outcomes were different in PCOS (n=126) across 4 prospectively recruited groups matched for age, body mass index, waist to hip ratio, and lack of recent (&amp;lt;3 mos) hormonal contraceptive and metformin use: self-identified (1) White (n=86); (2) Black (n=17); (3) Asian (n=12); and, (4) Hispanic (n=11) women in 3 academic medical centers in NY. PCOS was defined by the Rotterdam criteria using the recommended thresholds of the most recent (2018) PCOS Guideline. Fat and lean tissue mass and BMD were evaluated by dual-energy X-ray absorptiometry. Within the PCOS group, percentages of total body, trunk fat, and appendicular lean mass were comparable across races and ethnicities (All: P≥0.40); in contrast, total LBM and total and regional BMD were different across the groups (All: P&amp;lt;0.002). Post hoc pairwise comparisons revealed Asian women (mean±standard deviation; 39.64±6.42) exhibited lower total LBM vs. Black (53.93±10.60) and White (49.47±8.87; All: P&amp;lt;0.01) but not vs. their Hispanic (46.30±8.77 kg; P=0.29) counterparts. Total, upper, and lower limb BMD were higher in Black women (1.28±1.13; 0.82±0.09; 1.28±0.12) vs. all other counterparts: (White [1.12±0.9; 0.75±0.09; 1.18±0.10;]; Asian [1.09±0.09; 0.67±0.03; 1.08±0.05]; and, Hispanic [1.09±0.09; 0.72±0.15; 1.07±0.10] g/cm2; All: P&amp;lt;0.04), respectively. Similarly, lower limb BMD was compromised in Asian and Hispanic vs. White women (All: P≤0.03). Groups exhibited comparable glucoregulatory status (insulin and glucose responses to a standard 75-g oral glucose tolerance test), blood pressure, androgen status (Ferriman-Gallwey scores, total, free, and bioavailable testosterone), and intermenstrual interval length (All: P≥0.14). Conversely, groups differed by insulin-like-growth-factor-1 (IGF-1) and IGF-2 levels (All: P≤0.05). Post hoc pairwise comparisons showed lower IGF-1 in Black (255.92±145.12) and White (325.42±140.25) vs. Hispanic (549.21±266.26 ng/mL) women (All: P≤0.04). Also, Black women (426.74±82.66) had lower IGF-2 vs. White women (553.07±111.10 ng/mL; P≤0.4). Collectively, Asian women with PCOS show the lowest LBM and BMD, whereas their Black counterparts exhibit higher BMD after matching for age, body mass index, waist to hip ratio, lack of hormonal contraceptive and metformin use, and percentages of total body and trunk fat. Future research should delineate the true effects of PCOS-specific endocrine milieu (e.g., IGF axis) and relevance of genetic variants and/or environmental determinants of musculoskeletal health in this understudied clinical population. If confirmed by larger studies, our observations support the need for population-specific preventative and management considerations in future Guideline recommendations (e.g., PCOS-specific physical activity) to improve musculoskeletal health and associated reproductive and metabolic comorbidities. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

OR10-6 Sex Differences in Body Composition and Incident Diabetes Across BMI Categories in Older Versus Younger Adults

Abstract Background Body composition often changes with age. While body mass index (BMI) is used to define obesity, the degree to which BMI accurately or consistently reflects fatness in older versus younger adults remains unclear. Importantly, it is uncertain whether diabetes risk is similar for older versus younger adults within BMI-defined categories. Objectives We evaluated the relationship of older (≥65 years) versus younger age (&amp;lt;65 years) to dual-energy x-ray absorptiometry (DXA)-derived body composition measures and incident diabetes, stratified by BMI-defined categories for non-overweight/non-obese (&amp;lt;25 kg/m2), overweight (25-29.9 kg/m2) and obesity (≥30 kg/m2). Design: Participants without diabetes at first DXA visit in the Baltimore Longitudinal Study of Aging were included. Linear regression models were used to investigate the association of age categories to body composition at baseline, and Cox proportional hazard models were used to study the relationship of age categories to incident diabetes, within BMI categories for men and women. Diabetes was defined based on self-reported history, medication use, and/or ADA diagnostic criteria (fasting or 2-hour OGTT glucose levels). Results A total of 993 men (n=463 older, n=530 younger) and 1109 women (n=385 older, n=724 younger) were examined. Comparing older versus younger participants, body weight was significantly lower across all BMI categories for both men and women (all p&amp;lt;0.05). Percent total fat mass (%TFM) and fat mass/lean mass ratio (FM/LM) were significantly higher in older versus younger men across all BMI categories and in non-overweight/non-obese women. Among men, in multiple regression analyses adjusting for race, education, height and weight, the relationship (β±SE) of older versus younger age (reference) to %TFM remained significant (non-overweight/non-obese: 1.84±0.59, overweight: 2.60±0.47, obese: 1.81± 0.87; all p&amp;lt;0.05), as did the relationship to FM/LM, across all BMI categories. Among women, the relationships of older versus younger age (reference) to %TFM and FM/LM remained significant for non-overweight/non-obese women. Over a median follow-up of 7.3 years (IQR=1.9-16.6), there were 165 incident cases of diabetes. Older obese men had an almost three-fold higher risk of developing diabetes than younger obese men (HR=2.72 [95%CI: 1.12, 6.63]), accounting for race, education, height, weight and %TFM. Among women, no differences by age group in incident diabetes were observed. Conclusions In our study, sex differences were observed in the relationship of older versus younger age to several measures of body composition, suggesting greater relative fat mass with aging, particularly in men. Further, our results suggest that BMI-defined categories for overweight and obesity do not fully account for changes in fat mass with aging and that the risk for diabetes is significantly greater for older compared to younger obese men. Further studies are needed to investigate the optimal BMI thresholds that predict diabetes risk in older adults. Presentation: Sunday, June 12, 2022 12:15 p.m. - 12:30 p.m.

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values.

This study uses various body values (length, circumference, and volume) that can be derived from 3D data to determine variables and areas that substantially affect obesity and suggests guidelines for diagnosing obesity that are more elaborate than existing obesity indices. Body data for 170 participants (87 men and 73 women aged 20–30 years) are collected for the chest, abdomen, hips, and arms/legs. A 3D scanner, which can produce accurate body point results, and dual-energy X-ray (DEXA), which can accurately determine the fat percentage, are used to derive fat rates for each body part. The fat percentage and total fat percentage for each body part are used as learning data. For the derived data, the eigenvalue for each body part is derived using a principal component analysis, and the following four clusters are created for each part: underweight, normal, overweight, and obese. A comparison with the obesity index, which diagnoses obesity based on the cluster model, showed that the accuracy of the model proposed in this study is higher at 80%. Therefore, this model can determine the body information necessary for accurate obesity diagnosis and be used to diagnose obesity with greater accuracy than obesity indices without a body fat measurement machine such as DEXA.

Association of daily sitting time and leisure-time physical activity with body fat among U.S. adults

BackgroundProlonged sitting and reduced physical activity lead to low energy expenditures. However, little is known about the joint impact of daily sitting time and physical activity on body fat distribution. We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults. MethodsThis was a cross-sectional analysis of U.S. nationally representative data from the National Health and Nutrition Examination Survey 2011–2018 among adults aged 20 years or older. Daily sitting time and leisure-time physical activity (LTPA) were self-reported using the Global Physical Activity Questionnaire. Body fat (total and trunk fat percentage) was determined via dual X-ray absorptiometry. ResultsAmong 10,808 adults, about 54.6% spent 6 h/day or more sitting; more than one-half reported no LTPA (inactive) or less than 150 min/week LTPA (insufficiently active) with only 43.3% reported 150 min/week or more LTPA (active) in the past week. After fully adjusting for sociodemographic data, lifestyle behaviors, and chronic conditions, prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes. When stratifying by LTPA, the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insufficiently active. In the joint analyses, inactive/insufficiently active adults who reported sitting more than 8 h/day had the highest total (female: 3.99% (95% confidence interval (95%CI): 3.09%–4.88%); male: 3.79% (95%CI: 2.75%–4.82%)) and trunk body fat percentages (female: 4.21% (95%CI: 3.09%–5.32%); male: 4.07% (95%CI: 2.95%–5.19%)) when compared with those who were active and sitting less than 4 h/day. ConclusionProlonged daily sitting time was associated with increased body fat among U.S. adults. The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.

SERPINE1 DNA Methylation Levels Quantified in Blood Cells at Five Years of Age Are Associated with Adiposity and Plasma PAI-1 Levels at Five Years of Age.

Plasminogen activator inhibitor (PAI-1) expression has been associated with a higher risk of development of obesity. DNA methylation (DNAm) is an epigenetic mechanism regulating gene transcription and likely involved in the fetal programming of childhood obesity. Our study aimed to assess the associations between PAI-1 gene (SERPINE1) DNAm, plasma PAI-1 levels, and adiposity at five years of age. We analyzed DNAm and anthropometric data from 146 girls and 177 boys from the Gen3G prospective birth cohort. We assessed adiposity using BMI z-scores, waist circumference, total skinfolds, and percentages of total, android, and trunk fat measured by dual-energy radiography (DXA). We estimated blood cell DNAm levels at 15 CpG sites within SERPINE1 using the methylationEPIC array. After correction for multiple testing, we found that lower DNAm in SERPINE1 intron 3 (cg11353706) was associated with greater adiposity levels in girls (waist circumference: r = −0.258, p = 0.002; skinfolds: r = −0.212, p = 0. 013; android fat: r = −0.215, p = 0.015; BMI z-score: r = −0.278, p < 0.001) and that lower DNAm in the SERPINE1 promoter (cg19722814) was associated with higher plasma PAI-1 levels in boys (r = −0.178, p = 0.021). Our study suggests that DNAm levels at the SERPINE1 gene locus are negatively correlated with adiposity, but not with plasma PAI-1 levels, in young girls only.