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BACKGROUND: The vegan diet (VEGD) has gained popularity in recent years for ecological and ethical reasons, as well as for its health benefits. In addition to the type of diet, the resistance training program (RTP) plays a fundamental role as one of the main natural anabolic stimuli to increase musculoskeletal mass and reduce fat mass. METHODS: The study was a 16-week non-randomized controlled clinical trial consisting of three RTP sessions per week. The sample included 70 Chilean individuals, aged between 18 and 59 years, who had been following a VEGD or omnivorous diet (OMND) for the past 6 months. Four groups were established: Vegan Diet Resistance Training Program (VEGD-RTP), Vegan Diet Control (VEGD-C), Omnivorous Diet Resistance Training Program (OMND-RTP), and Omnivorous Diet Control (OMND-C). RESULTS: The sample consisted of 47 women and 23 men, with a mean age of 30.1 (±8.6) years. A reduction of 1.20% in the percentage of fat mass (%FM) was observed in the VEGD-RTP group (r = 0.554, p = 0.016), as well as a reduction of 0.70 kg in kilograms of fat mass (KFM) (r = 0.480, p = 0.036). The OMND-RTP group decreased %FM by 0.90% (r = 0.210, p = 0.432) and KFM by 0.50 kg (r = 0.109, p = 0.683). CONCLUSIONS: RTP combined with VEGD or OMND significantly reduced the percentage of fat mass, although its effect was more significant in the VEGD-RTP participants.

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Introduction: Chrononutrition studies the relation between diet, circadian rhythms and metabolism, which may alter the metabolic intrauterine environment, influencing infant fat-mass (FM) development and possibly increasing obesity risk. Aim: To evaluate the association of chrononutrition in pregnancy and infant FM at 6 months. Methods: Healthy pregnant women and term-babies (n = 100pairs) from the OBESO cohort (2017-2023) were studied. Maternal registries included pregestational body-mass-index (BMI), gestational complications/medications, weight gain. Diet (three 24 h-recalls, 1 each trimester) and sleep-schedule (first and third trimesters) were evaluated computing fasting (hours from last-first meal), breakfast and dinner latencies (minutes between wake up-breakfast and dinner-sleep, respectively), number of main meals/day, meal skipping (≥1 main meal/d on three recalls) and nighttime eating (from 9:00 pm-5:59 am on three recalls). Neonatal weight, length, BMI/age were assessed. At 6 months, infant FM (kg, %; air-displacement plethysmography) was measured, and FM index (FMI-kgFM/length2) computed. Exclusive breastfeeding (EBF) was recorded. Multiple linear regression models evaluated the association between chrononutrition and 6 month infant FM. Results: Mean fasting was 11.7 ± 1.3 h; breakfast, dinner latency were 87.3 ± 75.2, 99.6 ± 65.6 min, respectively. Average meals/day were 3.0 ± 0.5. Meal skipping was reported in 3% (n = 3) of women and nighttime eating in 35% (n = 35). Most neonates had normal BMI/age (88%, n = 88). Compared to those who did not, mothers engaged in nighttime-eating had infants with higher %FM (p = 0.019). Regression models (R 2 ≥ 0.308, p ≤ 0.001) showed that nighttime eating was positively associated with %FM (B: 2.7, 95%CI: 0.32-5.16). When analyzing women without complications/medications (n = 80), nighttime eating was associated with higher FM [%FM, B: 3.24 (95%CI: 0.59-5.88); kgFM, B: 0.20 (95%CI: 0.003-0.40); FMI, B: 0.54 (95%CI: 0.03-1.05)]. Infant sex and weight (6 months) were significant, while maternal obesity, pregnancy complications/medications, parity, energy intake, birth-BMI/age, and EBF were not. Conclusion: Maternal nighttime eating is associated with higher adiposity in 6 month infants.

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This research aimed to explore the changes produced in body mass index (BMI), fat mass percentage (FMP), muscle mass percentage (MMP), and visceral fat percentage (VFP) in 60-year-old or over overweight or obese people after a multicomponent exercise program. This quasi-experimental study involved 70 overweight or obese older people between 60 and 86 years old (M = 73.15; SD = 5.94) who were randomly assigned to a control group (CG, n = 35) and an experimental group (EG, n = 35). At the beginning and at the end of the intervention program, anthropometric and body composition data were collected. The results showed an increase in BMI after the intervention in the CG (p = 0.010) and a decrease in the EG (p < 0.001). The results regarding the FMP indicate a significant decrease in the EG (p < 0.001) after the intervention, as occurs with the VFP (p = 0.003). The MMP increased in the EG (p < 0.001) after the intervention program. Regarding gender, statistically significant differences were found in the MMP after the intervention (p = 0.025), with higher percentages in men in the EG. VFP decreased in both men (p = 0.005) and women (p = 0.019) in the EG. From the results obtained, we can say that a 6-month multicomponent program produces a decrease in BMI, FMP, and VFP and an increase in MMP in its participants. This type of intervention seems to produce a greater increase in muscle mass in men than in women and a decrease in VFP in both genders.

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SUMMARY: Diabetes is a form of endocrine disease. Dual-energy X-ray Absorptiometry (DXA) provides a detailed view of the body composition to find out what makes people with diabetes different from those with other diseases. We scanned 371 patients with DXA to analyze their body composition parameters. Three hundreds and seventy one patients (178 women/193 men), who with different diseases, with a mean±SD Body Mass Index (BMI) of 25.32±8.3 kg/m2 were included. The body composition of 371 patients was assessed. Bone Mineral Density (BMD), Fat Weight, Lean Weight, waist-to-hip ratio, Lean Mass Index (LMI), Fat Mass Index (FMI), the relationship between Fat percentage and BMI were analyzed. The 371 patients included 156 diabetics and 215 non-diabetics. Non-diabetic patients also included 5 obesity patients, 9 patients with fatty liver, 39 patients with hypertension, 22 patients with hyperlipidemia, 18 patients with cardiovascular disease, 11 patients with chest and lung disease, 4 patients with chronic disease, 14 patients with brain disease and 93 patients with other diseases. Among 156 diabetic patients, 129 had VAT > 100 cm2 and 27 had VAT ≤100 cm2. The lean weight (LW) of male diabetic patients was significantly higher than that of female diabetic patients. The fat weight (FW) of female patients with diabetes was significantly higher than that of male patients. The waist-hip ratio (WHR) was 1.37 ± 0.25 in male diabetic patients and 1.18 ± 0.21 in female diabetic patients. Among the 215 non-diabetic patients, the obese and fatty liver patients, which the weight (WT) (obesity: 83.87 ± 8.34 kg fat liver: 85.64±28.60 kg), FW (obesity: 28.56 ± 4.18 kg fat liver: 28.61 ± 10.79 kg), LW (obesity: 52.62 ± 9.64 kg fat liver: 54.29±17.58 kg), BMI (obesity: 28.76 ± 1.88 kg/m2 fat liver: 29.10 ± 5.95 kg/m2), was much higher than other patients. Diabetes patients had less fat mass than non- diabetic patients; the difference was around 2 kg. BMI is also a modest number. BMD doesn't differ all that much. Non-diabetic patients with fatty liver obesity and cardiovascular disease had higher fat mass and BMI than patients with other illnesses. Body composition can provide precise information on the makeup of different body areas, but further in-depth exams are required to ascertain the body's endocrine profile.

La diabetes es una enfermedad endocrina. La absorciometría de rayos X de energía dual (DXA) proporciona una vista detallada de la composición corporal para descubrir qué diferencia a las personas con diabetes de aquellas con otras enfermedades. Escaneamos a 371 pacientes con DXA para analizar sus parámetros de composición corporal. Se incluyeron 371 pacientes (178 mujeres/193 hombres), con diferentes enfermedades, con un Índice de Masa Corporal (IMC) medio ± DE de 25,32 ± 8,3 kg/m2. Se evaluó la composición corporal de 371 pacientes. Se analizaron la densidad mineral ósea (DMO), el peso graso, el peso magro, la relación cintura-cadera, el índice de masa magra (LMI), el índice de masa grasa (FMI), y la relación entre el porcentaje de grasa y el IMC. De los 371 pacientes 156 eran diabéticos y 215 no diabéticos. Los pacientes no diabéticos también incluyeron 5 con obesidad, 9 con hígado graso, 39 con hipertensión, 22 con hiperlipidemia, 18 con enfermedad cardiovascular, 11 con enfermedad torácica y pulmonar, 4 con enfermedad crónica, 14 con enfermedad cerebral y 93 pacientes con otras enfermedades. Entre los 156 pacientes diabéticos, 129 tenían un IVA > 100 cm2 y 27 tenían un IVA ≤100 cm2. El peso magro (PV) de los hombres diabéticos fue significativamente mayor que el de las mujeres diabéticas. El peso graso (FW) de las mujeres diabéticas fue significativamente mayor que el de los hombres diabéticos. El índice cintura-cadera (ICC) fue de 1,37 ± 0,25 en hombres diabéticos y de 1,18 ± 0,21 en mujeres diabéticas. Entre los 215 pacientes no diabéticos, los pacientes obesos y con hígado graso, cuyo peso (WT) (obesidad: 83,87 ± 8,34 kg hígado graso: 85,64 ± 28,60 kg), FW (obesidad: 28,56 ± 4,18 kg hígado graso: 28,61 ± 10,79 kg), PV (obesidad: 52,62 ± 9,64 kg, hígado graso: 54,29 ± 17,58 kg), IMC (obesidad: 28,76 ± 1,88 kg/m2, hígado graso: 29,10 ± 5,95 kg/m2), fue mucho mayor que otros pacientes. Los pacientes diabéticos tenían menos masa grasa que los pacientes no diabéticos; la diferencia fue de alrededor de 2 kg. La DMO no difiere mucho. Los pacientes no diabéticos con obesidad debido al hígado graso y enfermedades cardiovasculares tenían mayor masa grasa e IMC que los pacientes con otras enfermedades. La composición corporal puede proporcionar información precisa sobre la composición de diferentes áreas del cuerpo, pero se requieren exámenes más profundos para determinar el perfil endocrino del cuerpo.

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NAFLD has become the leading cause of chronic liver disease in children, as a direct consequence of the high prevalence of childhood obesity. This study aimed to characterize body composition trajectories from childhood to adolescence and their association with the risk of developing nonalcoholic fatty liver disease (NAFLD) during adolescence. The participants were part of the 'Chilean Growth and Obesity Cohort Study', comprising 784 children who were followed prospectively from age 3 years. Annual assessments of nutritional status and body composition were conducted, with ultrasound screening for NAFLD during adolescence revealing a 9.8% prevalence. Higher waist circumference measures were associated with NAFLD from age 3 years (p = 0.03), all skin folds from age 4 years (p < 0.01), and DXA body fat measurements from age 12 years (p = 0.01). The fat-free mass index was higher in females (p = 0.006) but not in males (p = 0.211). The second and third tertiles of the fat mass index (FMI) had odds ratios for NAFLD during adolescence of 2.19 (1.48-3.25, 95% CI) and 6.94 (4.79-10.04, 95% CI), respectively. Elevated waist circumference, skin folds, and total body fat were identified as risk factors for future NAFLD development. A higher FMI during childhood was associated with an increased risk of NAFLD during adolescence.

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Background: Cardiovascular diseases (CVDs) are a global health threat, significantly impacting Latin America. Cardiometabolic abnormalities (CAs), encompassing lipid profile, fasting plasma glucose, and blood pressure, contribute to CVD prevalence. Despite high CA incidence, research in Latin America has primarily focused on traditional adiposity indices, overlooking the intricate relationship between fat and lean body components. The study aimed to analyze the association between the lean-to-fat mass ratio (LFMR) and CAs in the adult Peruvian population. Methods: This was an analytical cross-sectional study using secondary data from the PERU MIGRANT study (2007, 989 participants). The main outcome variable was CA defined as having ≥ 2 out of six metabolic components (high triglycerides, impaired fasting glucose, high blood pressure, low high-density lipoprotein (HDL)-cholesterol, insulin resistance, and high C-reactive protein). The main exposure variable LFMR was divided into tertiles. A generalized linear model was used with log link and robust variance Poisson family to calculate crude (cPR) and adjusted prevalence ratios (aPRs) and 95% confidence intervals (95% CIs). Results: A total of 959 adults aged 30 years or older were included in the analysis (53% females). The prevalence of CA was 50.9%. Females aged 30 - 44 years old showed statistically significant inverse associations for the middle (aPR: 0.57, 95% CI: 0.42 - 0.78) and highest (aPR: 0.22, 95% CI: 0.14 - 0.35) LFMR categories. Similar trends were seen for females aged 45 - 59 years and ≥ 60 years, and males aged 30 - 44 years, while for males aged 45 - 59 years, only the middle LFMR category was associated. No statistically significant association between LFMR and CA was found among old males. Conclusions: LFMR was negatively associated with CA, among the Peruvian adult population. These findings underscore the relevance of LFMR in understanding cardiometabolic health disparities.

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Introduction: Currently, there is only scarce evidence of a causal association between risk of malnutrition (RM) by the mini-nutritional assessment (MNA) and the incidence of sarcopenia. This study was designed to assess such an association at 4.2 years of follow-up in community-dwelling subjects over 60 years old. Methods: The data used were from the FraDySMex cohort study. The exposition variables were RM diagnosed by the long forma of the MNA (MNA-LF) and short form (MNA-SF). The last one included the body mass index and calf circumference at baseline, while sarcopenia was diagnosed by the EWGSOP2 at follow-up and taken as the response variable. Several covariates involved in the association were also considered. A multiple logistic regression analysis was performed to test the association. Results: At baseline, 27.0 and 37.9% of subjects had RM by the MNA-LF and MNA-SF, respectively. The incidence of sarcopenia was 13.7%. The fat mass variable significantly modified the association, so it was tested in each stratum. Two independent models showed that subjects with RM by the MNA-LF in the normal fat mass stratum were at a higher risk for developing sarcopenia at follow-up than those without RM (OR 9.28; IC 95% 1.57-54.76) after adjusting for age, sex, and waist circumference. No association was found for the excess fat mass stratum subjects. Subjects with RM by the MNA-SF in the excess fat mass stratum were more likely to develop sarcopenia at follow-up than those without RM by the MNA-SF (OR 3.67; IC 95% 1.29-10.43). This association was not found in the subjects in the normal fat mass stratum. Conclusion: The association was dependent on the variable fat mass. The two forms of the MNA should not be applied indistinctly with older adults. Based on these results, it is clear that the risk of malnutrition precedes the onset of sarcopenia.

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Body composition assessment using instruments such as dual X-ray densitometry (DXA) can be complex and their use is often limited to research. This cross-sectional study aimed to develop and validate a densitometric method for fat mass (FM) estimation using 3D cameras. Using two such cameras, stereographic images, and a mesh reconstruction algorithm, 3D models were obtained. The FM estimations were compared using DXA as a reference. In total, 28 adults, with a mean BMI of 24.5 (±3.7) kg/m2 and mean FM (by DXA) of 19.6 (±5.8) kg, were enrolled. The intraclass correlation coefficient (ICC) for body volume (BV) was 0.98-0.99 (95% CI, 0.97-0.99) for intra-observer and 0.98 (95% CI, 0.96-0.99) for inter-observer reliability. The coefficient of variation for kinetic BV was 0.20 and the mean difference (bias) for BV (liter) between Bod Pod and Kinect was 0.16 (95% CI, -1.2 to 1.6), while the limits of agreement (LoA) were 7.1 to -7.5 L. The mean bias for FM (kg) between DXA and Kinect was -0.29 (95% CI, -2.7 to 2.1), and the LoA was 12.1 to -12.7 kg. The adjusted R2 obtained using an FM regression model was 0.86. The measurements of this 3D camera-based system aligned with the reference measurements, showing the system's feasibility as a simpler, more economical screening tool than current systems.

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PURPOSE: Combining different statistical methods to identify dietary patterns (DP) may provide new insights on how diet is associated with adiposity. This study investigated the association of DP derived from three data-driven methods and adiposity indicators over time. METHODS: This study used data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). DP were identified at baseline applying three statistical methods: Factor Analysis (FA), Treelet Transform (TT), and Reduced Rank Regression (RRR). The association between DP and adiposity indicators (weight, body mass index, waist circumference, body fat percentage and fat mass index) over the period of 8.2 years of follow-up was assessed by linear mixed-models. RESULTS: Convenience DP, marked by unhealthy food groups, was associated with higher adiposity over the follow-up period, regardless of the method applied. The DP identified by TT and marked by high consumption of rice and beans was associated with lower adiposity, whereas the similar DP identified by FA, but additionally characterised by consumption of poultry and red meat was associated with higher adiposity. Prudent DP, marked by plant-based food groups and fish, identified by FA was associated with lower adiposity across the median follow-up time. CONCLUSION: Applying different methods to identify DP showed that a convenience DP was associated with higher adiposity independent of the method applied. We also identified the nuances within adherence to a Brazilian traditional dietary pattern characterised by the consumption of rice and beans, that only when combined with reduced consumption of animal protein and unhealthy foods was associated with lower adiposity over time.

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BACKGROUND: The association of ultra-processed food (UPF) consumption with obesity and adipose tissue in children/adolescents remains poorly understood. OBJECTIVE: To assess the association of UPF consumption with excessive weight (EW-defined as BMI-for-age ≥+1 z-score) and body composition at 15 years. METHODS: In a birth cohort, daily UPF consumption was estimated by Food Frequency Questionnaires at 6 and 15 years. Those in the higher tercile of UPF consumption at both follow-ups were the 'always-high consumers'. Air-displacement plethysmography provided fat mass (FM-kg), fat-free mass (FFM-kg), %FM, %FFM, FM index (FMI-kg/m2 ) and FFM index (FFMI-kg/m2 ). Logistic regression and linear regression were used to estimate, respectively, odds ratios and beta coefficients. RESULTS: Amongst 1584 participants, almost one in every seven were always-high consumers. In crude analyses, there was no association between variation in UPF consumption and EW, and body fat parameters were lower in the always-high consumer group than amongst the always-low consumers, in both sexes. With adjustment for confounders, the odds ratio for EW was higher in the always-high consumer than amongst the always-low consumer group, and the direction of the associations with FM parameters was reversed: males from the always-high consumer group presented almost twice as high FM (10.5 vs. 18.6 kg; p < 0.001) and twice as high FMI (3.4 vs. 6.3 kg/m2 ; p < 0.001) than the always-low consumer group, and females from the always-high consumer group presented on average 32% more FM and FMI than the always-low consumer group. CONCLUSIONS: In crude and adjusted analyses there was a strong association between high UPF consumption from childhood to adolescence, EW and higher body fat parameters at 15 years, but its deleterious association with body adiposity was only uncovered after adjusting for confounders.

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Background and Objective: Dehydration and hyperhydration impact athletes' performance. Exploring the fluid balance concerning body composition might help estimate individual hydration requirements. This area of research, particularly regarding sodium losses, has been relatively understudied. We evaluated the sweat rate (SR), sweat sodium losses, and their relationship with body composition in professional soccer players in Cali, Colombia. Materials and Methods: Thirty-two male players, aged 24.3 (±5.2) years, from the Colombian main soccer league, underwent high-intensity training at 32 °C (with a relative humidity of 79%). The outcome variables included SR, calculated using weight loss and fluid intake; forearm sweat sodium concentration (FSCC), measured through the direct ion-selective electrode method; and estimated the predicted whole sweat sodium loss (PWSSL) in mmol. Predictor variables (body mass, fat, and muscle masses) were estimated using the Deborah Kerr anthropometry method. The association between predictors and outcomes was assessed using linear regression. Results: The mean FSCC, PWSSL, and SR were 26.7 ± 11.3 mmol/L, 43 ± 15.9 mmol/L, and 1.7 ± 0.5 L/h, respectively. Body mass positively predicted FSCC in unadjusted and age/fat-mass-adjusted models [Beta 1.28, 95% confidence interval (CI) 0.39-2.18, p = 0.006], and continued related to FSCC after adjustment for muscle mass with marginal significance [Beta 0.85, 95% CI -0.02 to 1.73, p = 0.056]. Muscle mass was associated with the PWSSL in unadjusted and age/fat-mass-adjusted models [Beta 2.42, 95% CI 0.58-4.26, p = 0.012] and sustained an association with marginal statistical significance after adjustment for body mass [Beta 1.86, 95% CI -0.35 to 4.09, p = 0.097]. Conclusions: Under hot tropical weather conditions, FSCC was relatively low among the players. Body mass was better associated with the FSSC, and muscle mass better related to the PWSSL. Body and muscle masses could be regarded as potential factors to be explored in the estimation of individual sodium needs. However, further studies are required to validate and contrast our findings.

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Introduction: During pregnancy, women experience metabolic changes that may induce insulin resistance, which can be traced to the blood glucose levels A number of factors may intervene in the metabolism of glucose in pregnant women; one of them is body composition. This factor is useful for studying metabolic diseases, for which the identification of the fat mass/muscle mass index (FMMMI) considered an especially relevant factor. Owing to their nature, techniques such as bioimpedance have been sparsely used for analysis during pregnancy. Aim: This study aimed to identify the relationship between fat mass / muscle mass index and glucose metabolism in pregnant women. Methods: This descriptive cross-sectional study included 231 women between the ages of 18 and 35 years and 24-28 weeks of gestation, who attended a state hospital for regular check-ups and exhibited risk factors for the development of gestational diabetes (GD) according to the Current Practice Guidelines in Primary Care. The participants underwent a physical examination, anthropometric measurements bio impedance were obtained, and oral glucose tolerance curves were constructed. FMMMI was calculated. Results: The prevalence of gestational diabetes was observed to be 13.4%. Women with a GD diagnosis had a significantly higher FMMMI than in those with no GD (0.746 ± 0.168 vs 0.567 ± 0.167;p < 0.005). The assessment of the FMMMI tertiles revealed that GD prevalence was higher in tertile 3 than in tertiles 1 and 2 (tertile 1: 2.6%; tertile 2: 9.1%; tertile 3: 24%). Conclusion: FMMMI is associated with glucose tolerance test response in pregnant women and a higher prevalence of GD.

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Obesity is highly prevalent in breast cancer (BC) survivors. Adipose tissue promotes inflammation, affecting recurrence, morbidity, and quality of life. This study aimed to determine the relationship of body composition parameters with the levels of C-reactive protein (CRP) and interleukin 6 (IL-6) in female BC survivors. Additionally, we evaluated the association of log-transformed serum concentrations of CRP and IL-6 with the appendicular skeletal lean mass index (ASMI). The results showed that CRP was positively associated with body fat percentage (BFP; ß adjusted = .08, 95% CI: .02-.14) in all participants, and with fat mass index (FMI; ß = .24, 95% CI: .08-.40) only in premenopausal women. IL-6 was positively associated with FMI (ß adjusted = .16, 95% CI: .03-.29), while ASMI decreased as CRP levels increased (ß adjusted = -.30, 95% CI: -.53 to -.06). Interventions to improve body composition in BC survivors should also consider the role of inflammatory markers in changes in body composition to avoid sarcopenic obesity (SO) and the risk of BC recurrence.

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Introduction: The aging process is associated with changes in body composition, including fat gain and skeletal muscle loss from middle age onward. Moreover, increased risk of functional decline and the development of chronic diseases are also related to aging. Objective: This systematic review and meta-analysis aimed to evaluate the effects of whole-body vibration exercise (WBVE), as a physical exercise, on body composition in people over 60 years of age. Methods: Searches were performed on PubMed, Scopus, Web of Science, and Embase. Only randomized clinical trials evaluating the effects of WBVE on body composition in older individuals were considered. The methodological quality of the studies involved was assessed using the Physiotherapy Evidence Database (PEDro) scale, recommendations from the Cochrane Collaboration were used to assess risk of bias, and quality of evidence was assessed using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology. RevMan 5.4 was used to calculate standardized mean differences and confidence intervals of 95% (CIs). Results: Eight studies were included in this review with a mean methodological quality score of 7.5, which is considered high quality on the PEDro scale. The included studies suggest that more robust research with protocols and well-designed comparison groups is required to better assess changes in the body composition of older individuals through WBVE. Quantitative results were calculated, with differences in weighted means, differences in standardized means, and 95% confidence intervals (CIs). Conclusion: WBVE evaluated by the studies included in this review did not demonstrate improvements in body composition, and no significant effect of WBVE was found on fat mass with standardized differences (SD = -1.92; 95% CI: -4.81 to -0.98; p = 0.19), lean mass with standardized mean differences (SMD = 0.06 CI 95% [-0.21; -0.33]; p = 0.67), or skeletal muscle mass with standardized differences (SD = 0.10; CI 95% [-1.62; 1.83]; p = 0.91). Therefore, to date, there is lack of adequate evidence to state that WBVE can benefit the body composition of men and women over 60 years of age. However, further studies are required to better understand the physiological impacts of WBVE on body composition. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/#myprosperoCRD42021248871, identifier CRD42021248871.

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Pregnant women with diabetes often present impaired fetal growth, which is less common if maternal diabetes is well-controlled. However, developing strategies to estimate fetal body composition beyond fetal growth that could better predict metabolic complications later in life is essential. This study aimed to evaluate subcutaneous fat tissue (femur and humerus) in fetuses with normal growth among pregnant women with well-controlled diabetes using a reproducible 3D-ultrasound tool and offline TUI (Tomographic Ultrasound Imaging) analysis. Additionally, three artificial intelligence classifier models were trained and validated to assess the clinical utility of the fetal subcutaneous fat measurement. A significantly larger subcutaneous fat area was found in three-femur and two-humerus selected segments of fetuses from women with diabetes compared to the healthy pregnant control group. The full classifier model that includes subcutaneous fat measure, gestational age, fetal weight, fetal abdominal circumference, maternal body mass index, and fetal weight percentile as variables, showed the best performance, with a detection rate of 70%, considering a false positive rate of 10%, and a positive predictive value of 82%. These findings provide valuable insights into the impact of maternal diabetes on fetal subcutaneous fat tissue as a variable independent of fetal growth.

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Obesity is a recognized risk factor for the development of cardiometabolic outcomes. Therefore, it is essential to evaluate anthropometric and body composition indicators used for its diagnosis. This study aimed to assess the diagnostic performance of body fat percentage (BF%), fat mass index (FMI) and body mass index (BMI) for detecting cardiometabolic outcomes in adults. A cross-sectional study was conducted involving adults at 30 years of age from Pelotas, RS (n = 3517) and at 37-39 years from Ribeirão Preto, SP (n = 1696). Receiver operating characteristic (ROC) curves were used to determine the cut-off points for predicting cardiometabolic risk factors, including altered blood pressure, blood glucose, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDDL-c), C-reactive protein and glycated hemoglobin. The cut-off points of BF% ranged from 25.2 to 27.8 in men and from 37.4 to 39.7 in women at 30 years, and from 26.1 to 27.8 in men and from 38.5 to 42.2 in women at 37-39 years. For FMI (kg/m2), the cut-off points ranged from 6.3 to 7.5 in men and from 9.5 to 10.8 in women at 30 years, and from 7.3 to 7.8 in men and from 10.2 to 12.2 in women at 37-39 years. The BMI cut-off points (kg/m2) ranged from 26.3 to 27.3 in men and from 25.4 to 27.2 in women at 30 years, and from 28.3 to 29.0 in men and from 27.2 to 29.6 in women at 37-39 years. The areas under the curve were similar for the three indicators, ranging from 0.523 to 0.746. BMI showed a performance similar to that of the body fat-based indicators in identifying cardiometabolic outcomes. The cut-off points of the three indicators showed acceptable discriminatory power in subjects with cardiometabolic risk factors.

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The present study investigates the relationship between the consumption of ultra-processed foods (UPF) and anthropometric indices of body composition in adults and seniors living in Teresina, the state capital of an area in northeastern Brazil. The article seeks to address two questions: Is UPF consumption linked to worsening body composition in different age groups? Do anthropometric indicators of body composition change with the increasing consumption of UPF? The study is a cross-sectional, household, population study, carried out with 490 adults and seniors. The food consumption was obtained with a 24 h food recall, and the foods were classified using NOVA. Anthropometric indicators evaluated were waist-to-height ratio, triceps skinfold thickness, arm circumference, corrected arm muscle area, subscapular skinfold thickness, and calf circumference. The association between energy contribution of UPF with anthropometric indicators was verified with a simple and multiple linear regression analysis. Individuals aged 20 to 35 years showed a significant association between UPF consumption and skinfold thickness (ß: 0.04; CI: 0.03/0.09), demonstrating an increase in this subcutaneous body fat marker with higher UPF consumption. Moreover, in participants aged 36 to 59 years, an inverse correlation between UPF intake and muscle mass markers, arm circumference (ß: -0.02; confidence interval: -0.03/-0.01), and corrected arm muscle area (ß: -0.07; confidence interval: -0.12/-0.02) were observed. Such results suggest there is decreased muscle mass with increasing UPF consumption. This is the first study that verified an association between UPF consumption and low-cost body composition indicators in different age groups.

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BACKGROUND: Heart failure (HF) is a complex syndrome that leads to changes in body composition and eventually results in unfavorable outcomes. AIM: This study aimed to evaluate body composition, lipid profiles and clinical parameters of patients with HF, and their associations with both survival and unfavorable clinical outcomes. METHODS: This prospective cohort study included 94 adults and older people with HF. Body composition was assessed by bioelectrical impedance analysis (BIA). Anthropometric variables and lipid profile were also evaluated. Electronic medical records were checked to collect information on clinical outcomes (mortality and hospitalization), considering a follow-up period of 24 months. Survival was calculated using the Kaplan-Meier estimate, and the curves compared using Log-Rank. The death risk rate (Hazard Ratio, HR) was calculated using Cox's univariate models. RESULTS: Mean age was 55.1 (13.9) years and there was a higher frequency of males. There was a predominance of HF with reduced ejection fraction, and ischemic etiology. Patients with New York Heart Association (NYHA) functional classification I/II had a better overall survival rate at 24 months than those with NYHA III/IV (univariate HR 4.93 (1.76-13.82); p = 0.001). Greater survival rates were found in patients without chronic kidney disease (CKD) (univariate HR 2.93 (1.59-5.39); p = 0.01). In the multivariate analyses, both dyslipidemia (adjusted HR 3.84 (1.22-12.00); p = 0.021) and increased fat mass index (FMI) were associated with overall survival rate (adjusted HR 3.59 (1, 10-11.74); p = 0.034). CONCLUSION: The severity of HF symptoms and the presence of chronic kidney disease are associated with higher mortality. Increased fat mass index and dyslipidemia are predictors of favorable outcomes in this population.

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Woolcott, Orison O., Till Seuring, and Oscar A. Castillo. Lower prevalence of body fat-defined obesity at higher altitudes in Peruvian adults. High Alt Med Biol. 24:214-222, 2023. Background: Previous studies have reported a lower prevalence of obesity (defined as a body mass index [BMI] ≥30 kg/m2) in populations from higher altitudes. Since BMI does not distinguish fat mass and fat-free mass, it is unclear whether there is an inverse association between altitude and body fat-defined obesity. Methods: We performed an analysis of cross-sectional data to examine the association between altitude and body fat-defined obesity (as opposed to BMI-defined obesity) using individual-level data from a nationally representative sample of the Peruvian adult population living between 0 and 5,400 m altitude. Body fat-defined obesity was diagnosed using the relative fat mass (RFM), an anthropometric index validated to estimate whole-body fat percentage. RFM cutoffs for obesity diagnosis were ≥40% for women and ≥30% for men. We utilized Poisson regression to estimate the prevalence ratio and confidence intervals (CIs) as the measure of the association, adjusting for age, cigarette use, and diabetes. Results: Analysis comprised 36,727 individuals (median age, 39 years; 50.1% women). In rural areas, for a one-km increase in altitude, the prevalence of body fat-defined obesity decreased by 12% among women (adjusted prevalence ratio: 0.88; 95% CI, 0.86 - 0.90; p < 0.001) and 19% among men (adjusted prevalence ratio: 0.81; 95% CI, 0.77 - 0.86; p < 0.001), on average, when all the other variables were held constant. The inverse association between altitude and obesity was less strong in urban areas than in rural areas but remained significant among women (p = 0.001) and men (p < 0.001). However, the relationship between altitude and obesity in women who live in urban areas appears to be nonlinear. Conclusions: In Peruvian adults, the prevalence of body fat-defined obesity was inversely associated with altitude. Whether this inverse association is explained by altitude per se or confounded by socioeconomic or other environmental factors, or differences in race/ethnicity or lifestyle, warrants further investigation.

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SUMMARY: The aim of this cross-sectional study was to compare dietary intake to published recommendations and to analyze the potential relationship between body composition and dietary intake in collegiate athletes. Eighteen healthy male middle- and long- distance runners (age 20.11 ± 2.72 y; height, 174.7 ± 6.1 cm; body mass, 64.0 ± 7.7 kg), were recruited from a Mexican university track and field team at the beginning of the general preparation phase for national competitions. Participants completed three 24-hour dietary recalls, which were used to estimate dietary intake. Body composition was measured by Dual-energy X-ray absorptiometry (DXA). Athletes displayed high body fat values. Protein intake was significantly higher than published recommendations. Iron, zinc, sodium, and vitamin C intake were significantly higher than recommended values, while potassium and calcium intake were below established recommendations. No significant correlations between body composition variables (i.e body fat, lean body mass, bone mineral content) and dietary intake (i.e energy, macronutrients and selected vitamins and minerals) could be found. These findings suggest that coaches and practitioners should pay close attention to dietary intake and body composition of endurance athletes starting general preparation for competition. Future studies on changes of dietary intake and body composition during off-season and competitive phase, which also track physical activity, are warranted.

El objetivo de este estudio transversal fue comparar la ingesta dietética con las recomendaciones publicadas y analizar la relación potencial entre la composición corporal y la ingesta dietética en corredores universitarios. Dieciocho atletas masculinos sanos de media y larga distancia (edad 20,11 ± 2,72 años; altura, 174,7 ± 6,1 cm; masa corporal, 64,0 ± 7,7 kg), fueron reclutados de un equipo de atletismo de una universidad mexicana al comienzo de la fase de preparación general de competiciones nacionales. Los participantes completaron tres recordatorios dietéticos de 24 horas, que se utilizaron para estimar la ingesta dietética. La composición corporal se midió mediante absorciometría de rayos X de energía dual (DXA). Los atletas mostraron altos valores de grasa corporal. La ingesta de proteínas fue significativamente mayor que las recomendaciones publicadas. La ingesta de hierro, zinc, sodio y vitamina C fue significativamente superior a los valores recomendados, mientras que la ingesta de potasio y calcio estuvo por debajo de las recomendaciones establecidas. No se encontraron correlaciones significativas entre las variables de composición corporal (es decir, grasa corporal, masa corporal magra, contenido mineral óseo) y la ingesta dietética (es decir, energía, macronutrientes y vitaminas y minerales seleccionados). Estos hallazgos sugieren que los entrenadores y los practicantes deberían prestar mucha atención a la ingesta dietética y la composición corporal de los atletas de resistencia que comienzan la preparación general para la competencia. Se justifican estudios futuros sobre los cambios en la ingesta dietética y la composición corporal durante la fase fuera de temporada y competitiva, como también un seguimiento de la actividad física.

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