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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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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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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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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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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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This study aimed to investigate the effect of chemotherapy (CT) and its different types of regimens on the anthropometry and body composition of women with breast cancer. Three-hundred-and-four women with breast cancer were enrolled in this multicenter study. The participants were evaluated before the infusion of the first cycle of CT (pre-CT), and until two weeks after CT completion (post-CT), regarding body weight, body mass index (BMI); waist circumference (WC); waist-to-height ratio (WHtR); conicity index (C-index); fat mass index (FMI); and fat-free mass index (FFMI). CT regimens were classified as anthracycline-based (AC-doxorubicin or epirubicin); anthracyclines and taxane (ACT); cyclophosphamide, methotrexate, and 5-fluorouracil (CMF); or isolated taxanes (paclitaxel or docetaxel). Women significantly increased BMI and FMI post-CT (p < 0.001 and p = 0.007, respectively). The ACT regimen increased FMI (p < 0.001), while FFMI increased after AC (p = 0.007). It is concluded that the CT negatively impacted body composition and the type of regime had a strong influence. The ACT regimen promoted an increase in FMI compared to other regimens, and the AC increased FFMI. These findings reinforce the importance of nutritional monitoring of breast cancer patients throughout the entire CT treatment.

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BACKGROUND: Body composition in infancy plays a central role in the programming of metabolic diseases. Fat mass (FM) is determined by personal and environmental factors. Anthropometric measurements allow for estimations of FM in many age groups; however, correlations of these measurements with FM in early stages of life are scarcely reported. The aim of this study was to evaluate anthropometric and clinical correlates of FM in healthy term infants at 6 months of age. METHODS: Healthy term newborns (n = 102) from a prospective cohort. Weight, length, skinfolds (biceps, triceps, subscapular and the sum -SFS-) and waist circumference (WC) were measured at 6 months. Body mass index (BMI) and WC/length ratio were computed. Type of feeding during the first 6 months of age was recorded. Air displacement plethysmography was used to asses FM (percentage -%-) and FM index (FMI) was calculated. Correlations and general linear models were performed to evaluate associations. RESULTS: Significant correlations were observed between all anthropometric measurements and FM (% and index)(p < 0.001). Exclusive/predominant breastfed infants had higher FM and anthropometric measurements at 6 months. Models that showed the strongest associations with FM (% and index) were SFS + WC + sex + type of feeding. CONCLUSIONS: Anthropometry showed good correlations with FM at 6 months of age. Skinfolds sum and waist circumference were the strongest anthropometric variables associated to FM. Exclusive/predominant breastfeeding was strongly associated with FM.

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BACKGROUND: Impaired physical performance (IPP) and physical disability (PD) are two serious public health problems in older adult populations worldwide. While studies show that changes in body composition are important risk factors for developing these conditions, there is little evidence that the fat-free mass (FFM) and fat mass (FM) indices (FFMI and FMI, respectively) are associated with IPP in older men and women. This study assessed the association among FFMI, FMI, and IPP using Short Physical Performance Battery (SPPB) in Mexican men and women aged over 60 years. METHODS: This cross-sectional study included 217 older people (men 34.6%, women 65.4%; 60-92 years). FFM and FM were assessed by dual X-ray absorptiometry, assuming a two-compartment model. FFM and FM were adjusted by height squared and the indices were obtained. After assessment of physical performance by SPPB, subjects with scores ≤6 were classified as having IPP. Associations were tested by multiple logistic regression analysis in separated models. RESULTS: IPP prevalence was 14.3%. Women were affected more than men. Regression analysis showed no significant association between FFMI and IPP, but FMI was strongly-associated, as for each unit increase in FMI, the risk of IPP rose significantly (OR: 1.14), and this result remained significant after adjusting for age, comorbidity, polypharmacy, and the appendicular skeletal muscle mass index (OR: 1.23; p ≤ 0.001). These results emphasize the importance of preventing increases in FM and avoiding overweight and obesity in older men and women.

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PURPOSE: Asthma is a highly prevalent noncommunicable lung disease. The aim of this study was to evaluate the longitudinal association of obesity/adiposity with wheezing and atopy. METHODS: The population of the study was composed of participants from the 1993 Pelotas (Brazil) Birth Cohort. The following outcome variables were measured at 22 years: wheezing in the last 12 months, wheezing with atopy, wheezing without atopy, only atopy, and persistent wheezing at 18 and 22 years. Exposure variables were obesity body mass index, percent fat mass (FM), and fat mass index, which were obtained by precise methods (BOD POD and dual-energy X-ray absorptiometry [DXA]). Crude and adjusted logistic and multinomial logistic regressions were used in the analyses. RESULTS: The prevalence of wheezing (with and without atopy), wheezing without atopy, only atopy, and persistent wheezing were 10.6%, 3.9%, 30.9%, and 4.0%, respectively. To be obese or to belong to the highest tertile of obesity/adiposity at two follow-ups showed a cumulative and positive association with wheezing in the adjusted analysis; for atopy there was no significant association. The odds ratio (OR) for wheezing according to the percentage of total FM measured by DXA in the highest tertile at both follow-ups was 1.58 (95% CI: 1.14-2.20) against an OR of 1.16 (95% CI: 0.92-1.47) for atopy. Persistent wheezing was also associated with adiposity, but without statistical significance. CONCLUSIONS: We found a positive longitudinal association between several measures of adiposity and wheezing at 22 years old. The effect was higher for cumulative adiposity; the results for atopy were not consistent.