Assess Body Fat Research Articles

Obesity and metabolic syndrome in a diverse pediatric kidney transplant population: which anthropometric measure best predicts arterial stiffness?

Obesity and metabolic syndrome (MS) accelerate arterial stiffening, increasing cardiovascular (CV) risk after transplant. BMI is limited by inability to differentiate muscle, fat mass, and fat distribution patterns. The aim of this study was to identify the best anthropometric measure to detect arterial stiffness as assessed by pulse wave velocity (PWV) in a racially diverse pediatric transplant population. Kidney transplant recipients 6-20years old and ≥ 6months post-transplant were prospectively enrolled. PWV was measured oscillometrically by Mobil-O-Graph. Skeletal muscle-to-fat mass ratio (SM:FM) and percent body fat (PBF) were evaluated by dual-frequency bioelectrical impedance. BMI and waist-to-height ratio (WHR) were calculated. Associations of arterial stiffness (high PWV) with obesity and MS as defined by WHR, SM:FM, PBF, and BMI were evaluated. Participants (n = 67) were 15 (IQR 11, 18) years old and 39 (IQR 10, 68) months post-transplant. Participants with SM:FM-obesity (OR 3.2) and WHR-obesity (OR 3.0) had increased odds of high PWV (p = 0.04) while PBF-obesity (OR 2.6, p = 0.09) and BMI-obesity (OR 2.2, p = 0.17) were not significant. Participants with WHR-MS (OR 12.5, p = 0.02), SM:FM-MS (OR 5.2, p = 0.03), and PBF-MS (OR 5.0, p = 0.02) had increased odds of arterial stiffness, while BMI-MS was not significant (OR 3.7, p = 0.08). Obesity is associated with arterial stiffness in a racially diverse cohort of pediatric transplant recipients. Anthropometric measures that assess body fat distribution (WHR) and body composition (SM:FM) are more strongly associated with arterial stiffness than BMI. MS has a stronger association with arterial stiffness than obesity alone, particularly when WHR is used.

Association between four anthropometric indices with age-related Macular Degeneration from NHANES 2005–2008

BackgroundAge-related macular degeneration (AMD) decrease vision and presents considerable challenges for both public health and clinical management strategies. Obesity is usually implicated with increased AMD, and body mass index (BMI) does not reflect body fat distribution. An array of studies has indicated a robust relationship between body fat distribution and obesity. This research is to evaluate the relationship between anthropometric measurements and AMD in the United States citizens in a cohort of patients.MethodsOur study included a cohort of 3,127 participants, all of whom were selected from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2008. Various anthropometric indices, including weight (WT), waist circumference (WC), Body Mass Index (BMI), waist-to-height ratio (WtHR), circularity index (CI), weight-adjusted waist circumference index (WWI), body roundness index (BRI), a body size index (ABSI), and visceral adiposity index (VAI), have been studied extensively within public health and nutrition to assess body fat distribution. Odds ratios (OR) for each anthropometric index, in relation to AMD and its different stages, were computed, adjusting for confounding variables. Smoothed curve fitting, coupled with weighted multivariable logistic regression analysis, was used to examine the impact of these anthropometric measures on the prevalence of AMD. Subgroup analyses were conducted according to gender, age, BMI, drinking, smoking, CVD, diabetes, hypertension, cataract operation, and glaucoma.ResultsAfter adjusting for all variables, significant positive correlations were observed between WtHR (OR = 1.237 (1.065−1.438)), BRI (OR = 1.221 (1.058−1.410)), CI (OR = 1.189 (1.039−1.362)), and WWI (OR = 1.250 (1.095−1.425)) with AMD, particularly for early AMD. However, no significant effects of these indicators were observed in late AMD. CI exhibited a positive linear relationship with AMD. Two-segment linear regression modeling revealed positive nonlinear associations between WtHR, BRI, and WWI with AMD. The positive association was more pronounced with excessive alcohol consumption for WtHR, BRI, CI, and WWI (P for interaction = 0.0033, 0.0021, 0.0194, and 0.0022, respectively). Additionally, WWI and CI exhibited stronger associations with AMD in females (P for interaction = 0.0146 and 0.0117, respectively). Furthermore, WtHR was associated with AMD in non-smokers (P for interaction = 0.0402).ConclusionThis study confirmed a increased risk between four anthropometric measures, including WtHR, BRI, CI, and WWI, with AMD, especially early AMD. The findings suggest that these four anthropometric indices should be more broadly utilized to improve early AMD prevention and treatment strategies. Additionally, we found that the positive association between these four body measurement indices and AMD was more pronounced in individuals with high alcohol consumption.

Endurance training enhances skeletal muscle mitochondrial respiration by promoting MOTS-c secretion.

The mitochondrial open reading frame of 12S rRNA-c (MOTS-c) is a biologically active mitochondria-derived peptide. However, the relationship between MOTS-c, skeletal muscle mitochondrial function, and endurance exercise adaptations is unknown. Here, we tested indices such as maximal oxygen uptake and serum MOTS-c levels in marathon runners and sedentary subjects. In addition, we tested aerobic exercise capacity, skeletal muscle mitochondrial respiration rate, and serum MOTS-c levels in mice subjected to long-term endurance training groups and sedentary groups. Our results indicated a close association between serum MOTS-c levels and aerobic exercise capacity. Circulating MOTS-c levels are expected to be an important indicator for predicting aerobic exercise capacity and assessing body fat status, endurance training load, and physical function. More importantly, we found that endurance training may enhance the mitochondrial respiratory function of skeletal muscle by promoting the secretion of MOTS-c and activating the AMPK/PGC-1α pathway.

Interplay between lipid profile and anthropometric measures as indicators of cardiometabolic risk in women with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that often coexists with cardiometabolic risk factors. Women with PCOS have a two-fold increased risk of developing type 2 diabetes and substantially elevated risk for cardiovascular disease (CVD) events later in life. PCOS patients may require more comprehensive metabolic screening to identify populations at higher risk of developing CVD and dyslipidemia. It is recommended to evaluate lipid profile, glucose tolerance and of women with PCOS every 2-3 years. Simple, short, and easy methods for the assessment of CVD risk in women with PCOS may be useful tools for implementing CVD prevention strategies by doctors or nutritionists. The aim of this study was to investigate the usefulness of anthropometric indices in the assessment of cardiometabolic risk based on lipid profile in patients with PCOS. The study involved 49 of Caucasian women aged 18-39 who were diagnosed with PCOS based on the Rotterdam criteria and divided into two groups with normal lipid profile (N=14) and dyslipidemia (N=35). Biochemical parameters were tested in the morning while fasting. Anthropometric parameters such as Body Mass Index (BMI), Body Adiposity Index (BAI), Waist-to-Hip Ratio (WHR), and Waist-to-Height Ratio (WHtR) were calculated, while the Percent of Body Fat was measured using a body analyzer. The study demonstrated that women with dyslipidemia were older than the control group, 33 years (27-37) vs 24 years (21-26), p<0.01. Neither BMI nor BAI (%) correlated with total cholesterol (p=0.63 and p=0.27). Other lipid parameters, such as serum HDL cholesterol (R=-0.68, p<0.01; R=-0.58, p<0.01), LDL cholesterol (R=0.34, p=0.02; R=0.37, p=0.01), non-HDL cholesterol (R=0.40, p<0.01; R=0.42, p<0.01), and triglycerides (R=0.56, p<0.01; R=0.51, p<0.01) correlated with BMI and BAI (%). ROC analysis demonstrated a high predictive value for age in identifying dyslipidemia. ROC analysis demonstrated poor predictive value for BMI, BAI, WHR, WHtR in identifying dyslipidemia. Analysis of simple and rapid parameters used to assess body fat, such as BMI, BAI, WHR, and WHtR, has shown that they are poor predictors of dyslipidemia in women with PCOS. In young women with PCOS, age appears to be a more reliable predictor of dyslipidemia.

Response of Irritable Bowel Syndrome to Abdominal Fat Reduction

Objectives: The study aimed to evaluate the response of Irritable Bowel Syndrome (IBS) among patients having central obesity to reducing abdominal fat using Focused Ultrasound (cavitation) in addition with aerobic exercise as well as a low calorie, low-FODMAPs diet. Methods: A total of 60 individuals, between the ages of 20 and 45, who were diagnosed with both irritable bowel syndrome (IBS) as well as abdominal obesity, having a body mass index (BMI) ranging from 30 to 39.9 kg/m², were divided into two groups of similar size by a random assignment process. Group A were given focused ultrasound cavitation accompanied by moderate aerobic exercise and a low calorie, low-FODMAPs diet over a period of three months, whereas Group B (control group) were given moderate aerobic exercise and a low calorie, low-FODMAPs diet only. Assessments of total body fat, abdominal fat, severity of IBS, as well as quality of life related to IBS were conducted prior to and after the study period. Results: Overall body fat mass, abdominal fat mass, IBS severity, and IBS quality of life were all significantly improved in both groups. All evaluated variables showed a highly significant improvement in favor of the study group when comparing the two groups. Conclusion: Focused Ultrasound (cavitation) in addition with aerobic exercise as well as a low calorie, low-FODMAPs diet cause more improvement of irritable bowel syndrome symptoms and quality of life.

Body fat variation and redistribution across different stages of life measured by dual-energy x-ray absorptiometry.

The global obesity epidemic of all ages has increased the demand for accurate management of body fat in each stage of life. The primary aim of this study was to provide reference centiles of body fat indices for Chinese children and adults and compare those with ethnicities from USA using dual-energy x-ray absorptiometry (DXA). The samples were drawn from two nationwide cross-sectional surveys of China Body Composition Life-course Study (2013-2023) and the US National Health and Nutrition Examination Survey (2011-2018). Age- and sex-specific centile curves were generated for a set of fat measurements, including total fat mass (FM), fat mass index (FMI), body fat percentage (BF%), trunk-to-leg fat ratio (TLR), android-to-gynoid fat ratio (AGR) and visceral-to-subcutaneous fat ratio (VSR), using the general additive model for location scale and shape method. The age-related variations from childhood to adulthood were generally similar among Chinese, Non-Hispanic Whites, Non-Hispanic Blacks and Mexican American population, with distinct levels across races and ethnicities. For whole-body fat (FM, FMI, and BF%), Mexican American population consistently presented the highest levels before 40 years old, followed by Non-Hispanic White, Non-Hispanic Black and Chinese individuals. For central fats indices, although the TLR and AGR levels in Chinese males were second to Mexican American counterparts in most stages of life, the VSR was much higher in Chinese than other races and ethnicities from eight years old. DXA-based centiles for body fat quantity and distribution in Chinese population aged 3-60 years old were presented, and their differences with other race and ethnicity were noted across periods from early childhood to middle adulthood. Our findings will promote age-, sex- and ethnic-specific assessment of life-course body fat and obesity-related risks in clinical practice.

Mobile-Based Platform With a Low-Calorie Dietary Intervention Involving Prepackaged Food for Weight Loss for People With Overweight and Obesity in China: Half-Year Follow-Up Results of a Randomized Controlled Trial.

Obesity is a rapidly increasing health problem in China, causing massive economic and health losses annually. Many techniques have emerged to help people with obesity better adhere to intervention programs and achieve their weight loss goals, including food replacement and internet-delivered weight loss consultations. Most studies on weight loss interventions mainly focused on the change in body weight or BMI; however, body fat, especially visceral fat mass, is considered the main pathogenic factor in obesity. In China, more reliable evidence is required on this topic. Moreover, it is unclear whether an integrated weight loss program combining food replacement products, mobile app-based platforms, and daily body composition monitoring using a wireless scale is useful and practical in China. In this 2-arm, parallel-designed, randomized study, we explored the effectiveness and safety of the Metawell (Weijian Technologies Inc) weight loss program in China, which combines prepackaged biscuits, a wireless scale, and a mobile app. Participants in the intervention group were guided to use food replacement products and a scale for weight loss and monitoring, whereas participants in the control group received printed material with a sample diet and face-to-face education on weight loss at enrollment. The intervention lasted for 3 months, and follow-up visits were conducted at months 3 and 6 after enrollment. Dual-energy x-ray absorptiometry and quantitative computed tomography were used to assess body fat. A multilevel model for repeated measurements was used to compare differences between the 2 groups. In total, 220 patients were randomly assigned to intervention (n=110) and control (n=110) groups. Participants in the intervention group had significantly greater decreases in BMI, total body fat, visceral adipose area, and subcutaneous adipose area (all P<.001) than those in the control group. However, the rate of change in lean mass was not significantly different between the 2 groups (P=.62). Further, 35 participants in the intervention group reported adverse events. Constipation was the most frequently reported adverse event (11/110), followed by dizziness (6/110), hypoglycemia (4/110), fatigue (3/110), and gastritis (3/35). The Metawell program was effective for weight loss. After the intervention, participants in the intervention group lost more body weight and body fat while retaining muscle mass than those in the control group.

Anthropometric measurements as a key diagnostic tool for familial partial lipodystrophy in women

BackgroundFamilial Partial Lipodystrophy (FPLD) is a disease with wide clinical and genetic variation, with seven different subtypes described. Until genetic testing becomes feasible in clinical practice, non-invasive tools are used to evaluate body composition in lipodystrophic patients. This study aimed to analyze the different anthropometric parameters used for screening and diagnosis of FPLD, such as thigh skinfold thickness (TS), Köb index (Köbi), leg fat percentage (LFP), fat mass ratio (FMR) and leg-to-total fat mass ratio in grams (LTR), by dual-energy X-ray absorptiometry, focusing on determining cutoff points for TS and LFP within a Brazilian population.MethodsThirty-seven patients with FPLD and seventy-four healthy controls matched for body mass index, sex and age were studied. Data were collected through medical record review after signing informed consent. All participants had body fat distribution evaluated by skinfolds and DXA measures. Fasting blood samples were collected to evaluate glycemic and lipid profiles. Genetic studies were carried out on all patients. Two groups were categorized based on genetic testing and/or anthropometric characteristics: FPLD+ (positive genetic test) and FPLD1 (negative genetic testing, but positive clinical/anthropometric criteria for FPLD).ResultsEighteen (48.6%) patients were classified as FPLD+, and 19 (51.4%) as FPLD1. Unlike what is described in the literature, the LMNA variant in codon 582 was the most common. Among the main diagnostic parameters of FPLD, a statistical difference was observed between the groups for, Köbi, TS, LFP, FMR, and LTR. A cutoff point of 20 mm for TS in FPLD women was found, which is lower than the value classically described in the literature for the diagnosis of FPLD. Additionally, an LFP < 29.6% appears to be a useful tool to aid in the diagnosis of these women.ConclusionCombining anthropometric measurements to assess body fat distribution can lead to a more accurate diagnosis of FPLD. This study suggests new cutoff points for thigh skinfold and leg fat percentage in women with suspected FPLD in Brazil. Further studies are needed to confirm these findings.

What About Water? Implications for Body Composition Assessment in Military Personnel.

Sergi, TE, Roberts, BM, and Heileson, JL. What About Water? Implications for Body Composition Assessment in Military Personnel. J Strength Cond Res 38(9): e534-e540, 2024-Body composition standards ensure service members maintain physical fitness, wellness, and support mission readiness. Anthropometric techniques (i.e., height/mass, circumference-based "tape test") have been the primary screening and percent body fat (%BF) assessment method in military personnel for about 4 decades. Recently, the Army and Marine Corps have implemented more advanced body composition assessment methods, such as air displacement plethysmography (ADP), multifrequency bioelectrical impedance analysis (MF-BIA), and dual-energy x-ray absorptiometry (DXA), to serve as supplemental %BF assessment after failing the tape test. Although supplemental assessments are intended to improve on the accuracy and precision of the tape test, preassessment standardization, specifically regarding acute water ingestion (AWI), is lacking. Thus, the purpose of this narrative review was to (a) summarize the available literature regarding the influence of AWI on body composition estimates derived from ADP, MF-BIA, and DXA and (b) provide evidence-based recommendations for researchers and practitioners. Studies indicate that AWI increases %BF estimates with ADP (4 of 6 [4/6] observations) and MF-BIA (6/7), whereas AWI increases muscle mass (6/6) and likely decreases %BF (2/3) when obtained by DXA. In conclusion, ADP, MF-BIA, and DXA are susceptible to confounding from AWI, leading to inaccurate body composition estimates that may negatively affect the careers of military personnel. Based on the findings from this narrative review, military practitioners and researchers should (a) follow manufacturer guidelines for calorie intake [food and fluid] and exercise avoidance, (b) conduct urine-specific gravity testing [if possible], and (c) limit AWI to <250 ml before assessment.

Bioelectrical impedance and lung function—associations with gender and central obesity: results of the EpiHealth study

BackgroundObesity is a major public health concern associated with various health problems, including respiratory impairment. Bioelectrical impedance (BIA) is used in health screening to assess body fat. However, there is no consensus in healthcare on how body fat should be assessed in relation to lung function. In this study, we aimed to investigate how BIA in relation to waist circumference contribute, using data from a large Swedish population study.MethodsA total of 17,097 participants (aged 45–75 years) were included in the study. The relationships between fat mass, waist circumference, and lung function were analysed using weighted quantile sum regression.ResultsIncreased fat mass was significantly associated with decreased lung function (FEV1, FVC) in both sexes. Also, the influence of trunk fat and waist circumference on FVC and FEV1 differed by sex: in males, waist circumference and trunk fat had nearly equal importance for FVC (variable weights of 0.42 and 0.41), whereas in females, trunk fat was significantly more important (variable weights 0.84 and 0.14). For FEV1, waist circumference was more important in males, while trunk fat was more significant in females (variable weights male 0.68 and 0.28 and 0.23 and 0.77 in female).ConclusionsOur results suggest that trunk fat should be considered when assessing the impact of adipose tissue on lung function and should potentially be included in the health controls.

Association between frailty and acute kidney injury after cardiac surgery: unraveling the moderation effect of body fat through an international, retrospective, multi-cohort study.

Acute kidney injury (AKI) is a common and serious complication after cardiac surgery that significantly affects patient outcomes. Given the limited treatment options available, identifying modifiable risk factors is critical. Frailty and obesity, two heterogeneous physiological states, have significant implications for identifying and preventing AKI. Our study investigated the interplay among frailty, body composition, and AKI risk after cardiac surgery to inform patient management strategies. This retrospective cohort study included three international cohorts. Primary analysis was conducted in adult patients who underwent cardiac surgery between 2014 and 2019 at Wuhan XX Hospital, China. We tested the generalizability of our findings with data from two independent international cohorts, the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU Collaborative Research Database. Frailty was assessed using a clinical lab-based frailty index (FI-LAB), while total body fat percentage (BF%) was calculated based on a formula accounting for BMI, sex, and age. Logistic regression models were used to analyze the associations between frailty, body fat, and AKI, adjusting for pertinent covariates. A total of 8785 patients across three international cohorts were included in the study. In the primary analysis of 3,569 patients from Wuhan XX Hospital, moderate and severe frailty were associated with an increased AKI risk after cardiac surgery. Moreover, a nonlinear relationship was observed between body fat percentage and AKI risk. When stratified by the degree of frailty, lower body fat correlated with a decreased incidence of AKI. Extended analyses using the MIMIC-IV and eICU cohorts (n=3,951 and n=1,265, respectively) validated these findings and demonstrated that a lower total BF% was associated with decreased AKI incidence. Moderation analysis revealed that the effect of frailty on AKI risk was moderated by the body fat percentage. Sensitivity analyses demonstrated results consistent with the main analyses. Higher degrees of frailty were associated with an elevated risk of AKI following cardiac surgery, and total BF% moderated this relationship. This research underscores the significance of integrating frailty and body fat assessments into routine cardiovascular care to identify high-risk patients for AKI and implement personalized interventions to improve patient outcomes.

BODYFAT: a new calculator to determine the risk of being overweight validated in Spanish children between 11 and 17 years of age

The assessment of body fat of children in primary care requires consideration of the dynamic changes in height, weight, lean mass, and fat mass during childhood growth. To achieve this, we aim to develop a predictive equation based on anthropometric values, with optimal diagnostic utility. This is a cross-sectional observational study, involving schoolgoers aged 11–17 years in the Vigo metropolitan area. Out of 10,747 individuals, 577 were randomly recruited. Variables: age, sex, ethnicity/country of origin, weight, height, 8 skinfolds, 3 diameters, 7 perimeters, and 85% percentile of body fat mass as the gold standard. Generalized additive regression was selected by cross-validation and compared using receiver operating characteristic curves (ROC curves). Sensitivity, specificity, positive and negative predictive values, true positive and true negative values, false positive and false negative values, accuracy, and positive and negative likelihood ratios were calculated. Two models were identified. The optimal model includes sex, weight, height, leg perimeter, and arm perimeter, with sensitivity of 0.93 (0.83–1.00), specificity of 0.91 (0.83–0.96), accuracy of 0.91 (0.84–0.96), and area under the curve (AUC) of 0.957 (0.928–0.986). The second model includes sex, age, and body mass index, with sensitivity of 0.93 (0.81–1.00), specificity of 0.90 (0.80–0.97), accuracy of 0.90 (0.82–0.96), and an AUC of 0.944 (0.903–0.984).Conclusion: Two predictive models, with the 85th percentile of fat mass as the gold standard, built with basic anthropometric measures, show very high diagnostic utility parameters. Their calculation is facilitated by a complementary online calculator.What is Known:• In routine clinical practice, mainly in primary care, BMI is used to determine overweight and obesity. This index has its weaknesses in the assessment of children.What is New:• We provide a calculator whose validated algorithm, through the determination of fat mass by impedanciometry, makes it possible to determine the risk of overweight and obesity in the community setting, through anthropometric measurements, providing a new practical, accessible and reliable model that improves the classification of overweight and obesity in children with respect to that obtained by determining BMI.

Effects of dataset curation on body condition score (BCS) determination with a vision transformer (ViT) applied to RGB+depth images

Body condition score (BCS) has been a useful tool in estimating the health of cattle for many years now. This categorical metric requires experienced observers to visually inspect cows and assess body fat deposits regularly via a time consuming, subjective process. Low cost RGB+depth cameras have been used alongside machine learning algorithms in the past and have shown great promise, however, more advanced techniques are projected to yield better performance. In this work, a vision transformer (ViT) is pretrained using a recently developed self-supervised pretraining method, masked image modeling, and then fine-tuned on RGB+depth BCS data with the objective of improving performance. Model accuracy was found to be highly dependent on dataset curation, ranging from 64% to 92% accuracy. These discrepancies are attributed to non-unique data in the training and test splits and an inherently unbalanced dataset, both of which are discussed in detail. It is recommended that engineers and animal scientists collaborate more closely, as certain details related to dataset curation are critical to thoroughly assess performance and robustness of automated methods for BCS determination.

Associations between body mass index and all-cause mortality among individuals with psoriasis: results from the NHANES database retrospective cohort study.

Previous findings imply a potential positive association between BMI and all-cause mortality in individuals with psoriasis, yet direct evidence remains absent. This study aimed to fill this gap. We utilized data from the National Health and Nutrition Examination Survey (NHANES) for the periods 2003-2006 and 2009-2014. Participants' BMI was categorized as lean (<25), overweight (25 ≤ BMI < 30), and obese (BMI ≥ 30). Psoriasis status was determined through self-reporting. The main outcome measured was all-cause mortality up to December 2019. We accounted for multiple covariates, such as sociodemographic factors and histories of smoking and alcohol consumption. Our statistical analyses mainly included Kaplan-Meier survival analysis, Restricted Cubic Spline (RCS) and Multivariate Cox Regression (MCR). We also applied propensity score matching (PSM) to verify the robustness of our findings. Among 22,876 participants, 618 (2.70%) reported a history of psoriasis. An overall effect from the MCR analysis showed that, among individuals with psoriasis, a higher baseline BMI was independently associated with an increased risk of all-cause mortality, noting a 5.5% rise in mortality risk per BMI unit [hazard ratio (HR) = 1.055, 95% CI: 1.004-1.110, p = 0.035]. This significant relationship persisted after PSM. A statistically significant positive correlation was consistent among males, smokers, and individuals younger than 60. However, no such association was found in individuals without a history of psoriasis. Additionally, no significant difference in mortality risk was found between lean and overweight groups with psoriasis, according to the RCS regression and stratified analysis. Our findings indicated a trend that, higher BMIs significantly correlated with increased risks of all-cause mortality in people with psoriasis, particularly among obese ones. However, the impact of being overweight on this relationship remains underexplored. Moreover, the necessity to employ alternative metrics beyond BMI for body fat assessment to further investigate these associations is critical.

Body Adiposity Index as a Predictor of Body Fat in an Oldest Old and Independent Cohort of Brazilian Older Adults.

Anthropometry and body mass index (BMI) do not assess body composition or its distribution in older adults; thus, individuals may have different fat percentages but similar BMI values. The body adiposity index (BAI) was recently proposed as a feasible and inexpensive method for estimating the percentage of body fat based on measurements of hip circumference and height. The present study evaluated whether BAI and BMI are useful alternatives to dual-energy X-ray absorptiometry (DXA), which is rarely used in clinical practice, for predicting body fat in independent long-lived older adults. In this cross-sectional study, we used DXA to calculate the percentage of body fat, which was compared with BAI and BMI values. We performed Pearson correlation analyses and used Cronbach's alpha, described by Bland and Altman, to compare the reliability between the indexes. Among 157 evaluated individuals (73.2% women, mean age 87±3.57 years), men had a lower percentage of total fat, as assessed by DXA, and lower BAI indices than women. The correlation between BAI and DXA was moderate (r=0.59 for men and r=0.67 for women, p&lt;0.001). We confirmed the reliability based on Cronbach's alpha coefficients of 0.67 in men and 0.77 in women. We also observed that the BAI was strongly positively correlated with BMI in both men and women. The BAI, used in combination with BMI, can be an alternative to DXA for the assessment of body fat in the oldest old in clinical practice, mainly women, and can be used to add information to BMI.

Beyond Obesity and Overweight: The Clinical Assessment and Treatment of Excess Body Fat in Children : Part 1 - Insulin Resistance as the Root Cause of Pediatric Obesity.

Pediatric obesity and comorbidities related to insulin resistance continue to be a growing public health crisis. If lifestyle measures are unsuccessful, pharmacological and surgical interventions are offered. In this paper, we describe the driving force of the obesity crisis: hyperinsulinemia and the development of insulin resistance. We give historical background of key policy issues which have contributed to this pandemic as well as the physiologic mechanisms of insulin resistance. The prevalence of obesity will continue to rise unless the root cause of hyperinsulinemia is addressed. Current research on insulin resistance demonstrates that a decreased consumption of carbohydrates is an effective first-line dietary intervention for the treatment of obesity and related metabolic diseases. Evidence shows it is safe and beneficial. A low-carbohydrate eating pattern can be helpful to address pediatric obesity. However, there must be policy guardrails in place to ensure that this is a sustainable and viable option for children and their families. There must be a change in the nutritional environment to help individuals battle the chronic disease of obesity.

Beyond Obesity and Overweight: the Clinical Assessment and Treatment of Excess Body Fat In Children : Part 2 - the Prescription of Low-Carbohydrate Eating as the First Approach.

Pediatric obesity and comorbidities related to insulin resistance continue to be a growing public health crisis. If lifestyle measures are unsuccessful, pharmacological and surgical interventions are offered. In this paper, we describe the driving force of the obesity crisis: hyperinsulinemia and the development of insulin resistance. We give historical background of key policy issues which have contributed to this pandemic as well as the physiologic mechanisms of insulin resistance. The prevalence of obesity will continue to rise unless the root cause of hyperinsulinemia is addressed. Current research on insulin resistance demonstrates that a decreased consumption of carbohydrates is an effective first-line dietary intervention for the treatment of obesity and related metabolic diseases. Evidence shows it is safe and beneficial. A low-carbohydrate eating pattern can be helpful to address pediatric obesity. However, there must be policy guardrails in place to ensure that this is a sustainable and viable option for children and their families. There must be a change in the nutritional environment to help individuals battle the chronic disease of obesity.

Abstract PO4-19-12: Trial in progress: An Observational Study to Examine Changes in Metabolic Syndrome Components in Patients With Breast Cancer Receiving (Neo)Adjuvant Aromatase Inhibitors

Abstract Background: (Neo) adjuvant systemic therapy has been shown to adversely impact metabolic health manifested as weight gain, dyslipidemia, and insulin resistance, which ultimately lead to the development of metabolic syndrome (MetS). MetS increases the risk of development for type 2 diabetes mellitus and cardiovascular disease and is associated with an increased risk of breast cancer recurrence, death due to breast cancer, and all-cause mortality. We have previously reported that 76% of metabolically healthy women receiving (neo) adjuvant chemotherapy will develop MetS at a median of 15 weeks. The impact of aromatase inhibitors (AIs) on metabolic health has not been systematically assessed in a longitudinal study. We hypothesize that AIs in the (neo) adjuvant setting will alter metabolic parameters and have embarked on a clinical trial to study this. Methods: This is a prospective observational study that will include: postmenopausal patients with newly diagnosed, early-stage hormone receptor (HR)-positive breast cancer with planned (neo)adjuvant treatment with an AI. Participants will be excluded if they have received or have planned treatment with (neo)adjuvant chemotherapy or are currently receiving antidiabetic medications or cholesterol-lowering agents. All patients will undergo a baseline assessment that includes: BMI, physical exam inclusive of blood pressure, waist circumference, assessment of body fat, lipid profile, insulin, metabolic biomarkers, and completion of the Functional Assessment of Cancer Therapy – Endocrine Symptoms (FACT-ES). Following institution of an AI, reassessment of the aforementioned tests will be repeated after 4 months and 12 months of therapy. The primary endpoint is the change in insulin resistance (as measured by HOMA-IR, homeostatic model assessment for insulin resistance) at 4 months. Secondary endpoints include the change in HOMA-IR at 12 months and the change in individual MetS components, metabolic biomarkers, anthropometric measurements, as well as FACT-ES scores from baseline to 4- and 12-months of AI treatment. The mean paired differences will be calculated for HOMA-IR measurements as well as for the secondary endpoints, and the 1-sided paired t-test will be used to test for statistical significance. One-way analysis of covariance will be used to compare means while adjusting for age, race/ethnicity, and BMI. Using a 1-sided paired t-test for the mean difference in HOMA-IR measurements from baseline to 4 months, we will have 80% power to detect an effect size of 0.405 with 40 patients (α = 0.05). Enrollment began in April 2023 and is ongoing. Contact alevee@coh.org for more information. Given the increased recognition of the importance of metabolic health in breast cancer outcomes, this data will inform future trials that focus on maintaining metabolic health in breast cancer survivors. Citation Format: Alexis LeVee, Nora Ruel, Victoria Seewaldt, Joanne Mortimer. Trial in progress: An Observational Study to Examine Changes in Metabolic Syndrome Components in Patients With Breast Cancer Receiving (Neo)Adjuvant Aromatase Inhibitors [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-19-12.

Anthropometric Predictors of Health-Related Quality of Life in Obese Patients Attending a Tertiary Hospital in Nnewi, South-East Nigeria: A Cross-Sectional Study.

Obesity as a disorder with excess body fat directly decreases quality of life. While Body Mass Index (BMI) has been used largely in health studies as a measure of obesity, it is largely unable to differentiate between body fat and lean body mass, hence other anthropometric measures can be used to assess body fat. To determine the association of anthropometric indicators with health-related quality of life (HRQoL) in obese adults. A cross-sectional study of obese adults (BMI ≥30kg/m2) attending the general outpatient clinic was conducted over four months. The quality of life was assessed using the short form-36 (SF-36) questionnaire. The anthropometric indicators used were BMI, waist circumference (WC), waist hip ratio (WHR), and waist-height ratio (WHtR). Physical component summary (PCS) was significantly related to BMI, WHtR, and WC. After adjusting for co-variables (gender, age, occupation, and marital status), they remained significantly associated with PCS. Mental component summary (MCS) was significantly related to BMI, WHtR, and WC. After adjusting for the known determinants of HRQoL, only BMI remained significantly associated with MCS (P = -0.004; r = -0.146). When all the indicators were included in the same regression model, no anthropometric indicator was significantly related to MCS while only WHtR was significantly associated with PCS (P = 0.001; r = -0.465). HRQoL in obese patients is related to measures of body fat. The physical and mental components of health-related quality of life are correlated differently with the various anthropometric measures of obesity. The WHtR was found to be an independent predictor of the physical component of HRQoL.

Assessment of whole-body and regional body fat using abdominal quantitative computed tomography in Chinese women and men

BackgroundBeing overweight or obese has become a serious public health concern, and accurate assessment of body composition is particularly important. More precise indicators of body fat composition include visceral adipose tissue (VAT) mass and total body fat percentage (TBF%). Study objectives included examining the relationships between abdominal fat mass, measured by quantitative computed tomography (QCT), and the whole-body and regional fat masses, measured by dual energy X-ray absorptiometry (DXA), as well as to derive equations for the prediction of TBF% using data obtained from multiple QCT slices.MethodsWhole-body and regional fat percentage were quantified using DXA in Chinese males (n = 68) and females (n = 71) between the ages of 24 and 88. All the participants also underwent abdominal QCT measurement, and their VAT mass and visceral fat volume (VFV) were assessed using QCT and DXA, respectively.ResultsDXA-derived TBF% closely correlated with QCT abdominal fat percentage (r = 0.89–0.93 in men and 0.76–0.88 in women). Stepwise regression showed that single-slice QCT data were the best predictors of DXA-derived TBF%, DXA android fat percentage and DXA gynoid fat percentage. Cross-validation analysis showed that TBF% and android fat percentage could be accurately predicted using QCT data in both sexes. There were close correlations between QCT-derived and DXA-derived VFV (r = 0.97 in men and 0.93 in women).ConclusionClinicians can assess the TBF% and android and gynoid fat percentages of Chinese women and men by analysing existing abdominal CT-derived data using the QCT technique.