Study on Body Composition of Patients with Diabetes Mellitus by Dual-Energy X-Ray Absorptiometry: A Morphological Study

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.

Predictive value of body composition and related factors in early detection of gestational diabetes mellitus among pregnant women / 中华健康管理学杂志

Objective:Explore the predictive value of body composition and related factors in early detection of gestational diabetes mellitus (GDM).Methods:949 pregnant women (142 cases in GDM group and 807 cases in normal group) in early pregnancy were selected from March 2019 to March 2020 in Suzhou Municipal Hospital, subject's clinical data were recorded. Body composition was measured by bioelectrical impedance method before the 13th week of pregnancy, and the relationship between age, protein, basal metabolic rate, body mass index (BMI) before pregnancy, body fat percentage, fat mass index (FMI), pregnancy times and the screening results of glucose tolerance in the second trimester of pregnancy were analyzed. The risk factors of GDM were further identified by multivariate regression analysis. Finally, the ROC curve was drawn to determine the diagnostic value of GDM, and the best boundary value was found to calculate the sensitivity and specificity of the indicators.Results:The age (20.82±2.60 vs 22.35±3.64), BMI before pregnancy (20.82±2.60 vs 22.35±3.64), percentage of body fat (29.37±5.63 vs 32.14±5.77), FMI [6.06(5.00, 7.30) vs 6.87(5.60, 8.60)] and pregnancy times [1(1, 2)vs 2(2, 3)] in GDM group were higher than those in normal group. Pregnancy times ( OR=1.232, 95% CI: 1.033-1.471) and FMI ( OR=1.228, 95% CI: 1.057-1.426) are independent risk factors of GDM. When FMI was used to predict the incidence of GDM, the area under the curve (AUC) was 63.0%. Conclusion:Pregnancy times and FMI in early pregnancy can be used as independent predictors of GDM. They provide a basis for scientific adjustment of diet and reasonable exercise, thereby preventing the GDM as early as possible. FMI can be reduced by adjusting the dietary structure and engaging in reasonable exercise, to reduce its risk among pregnant women.

Establishment of a nomogram prognostic model for risk factors of comprehensive complication index after radical gastrectomy for gastric cancer / 中华临床营养杂志

Objective:To explore the independent risk factors of comprehensive complication index (CCI) ≥ 26.2 after radical gastrectomy for gastric cancer and to establish and verify a nomogram model.Methods:Clinical data of patients undergoing radical gastrectomy for gastric cancer in Jinling Hospital from September 2017 to March 2019 were retrospectively collected. CCI score of each patient was obtained using CCI calculator. Potential risk factors of CCI ≥ 26.2 were screened by multivariate logistic regression analysis and a nomogram model was established. Besides, the nomogram model was evaluated for differentiation, consistency and clinical usefulness using area under the curve, calibration curves and decision curve, respectively.Results:A total of 237 patients undergoing radical gastrectomy were included, of whom 38 (16.0%) had a CCI ≥ 26.2. Multivariate logistic regression analysis showed that the third lumbar skeletal muscle mass index ( OR = 3.98, P = 0.001), the third lumbar fat mass index ( OR = 3.38, P = 0.002) and age ≥ 65 years( OR = 2.50, P = 0.018) were independent risk factors for postoperative CCI ≥ 26.2. The established nomogram model showed good differentiation, prediction consistency and clinical benefit (AUC = 0.753). Conclusion:The nomogram model based on 3 independent risk factors has good predictive performance and clinical benefit for CCI ≥ 26.2 after radical gastrectomy, which can be applied and promoted in clinical practice to a certain extent.

Fat mass index performs best in monitoring management of obesity in prepubertal children / Índice de massa gorda apresenta melhor desempenho no monitoramento do tratamento da obesidade em crianças pré-púberes

Abstract Objective An early and accurate recognition of success in treating obesity may increase the compliance of obese children and their families to intervention programs. This observational, prospective study aimed to evaluate the ability and the time to detect a significant reduction of adiposity estimated by body mass index (BMI), percentage of fat mass (%FM), and fat mass index (FMI) during weight management in prepubertal obese children. Methods In a cohort of 60 prepubertal obese children aged 3–9 years included in an outpatient weight management program, BMI, %FM, and FMI were monitored monthly; the last two measurements were assessed using air displacement plethysmography. The outcome measures were the reduction of >5% of each indicator and the time to achieve it. Results The rate of detection of the outcome was 33.3% (95% CI: 25.9–41.6) using BMI, significantly lower (p < 0.001) than either 63.3% using %FM (95% CI: 50.6–74.8) or 70.0% (95% CI: 57.5–80.1) using FMI. The median time to detect the outcome was 71 days using FMI, shorter than 88 days using %FM, and similar to 70 days using BMI. The agreement between the outcome detected by FMI and by %FM was high (kappa 0.701), but very low between the success detected by BMI and either FMI (kappa 0.231) or %FM (kappa 0.125). Conclusions FMI achieved the best combination of ability and swiftness to identify reduction of adiposity during monitoring of weight management in prepubertal obese children.

Resumo Objetivo O reconhecimento precoce e preciso do sucesso no tratamento da obesidade pode aumentar a adesão de crianças obesas e suas famílias a programas de intervenção. Este estudo observacional prospectivo visa a avaliar a capacidade e o tempo de detecção de uma redução significativa na adiposidade estimada pelo índice de massa corporal (IMC) no percentual de massa gorda (% MG) e no índice de massa gorda (IMG) durante o controle de peso em crianças obesas pré-púberes. Métodos Em uma coorte de 60 crianças obesas pré-púberes entre três e nove anos, incluídas em um programa ambulatorial de controle de peso, o IMC, o % MG e o IMG foram monitorados mensalmente e as duas últimas medições avaliadas foram feitas com pletismografia por deslocamento de ar. As medições resultantes foram redução de > 5% de cada indicador e atingir o tempo para tanto. Resultados A taxa de detecção do resultado foi de 33,3% (IC de 95% 25,9-41,6) com o uso de IMC, significativamente menor (p < 0,001) do que 63,3% com % MG (IC de 95% 50,6-74,8) ou 70,0% (IC de 95% 57,5-80,1) com IMG. O tempo médio para detectar o resultado foi de 71 dias com o IMG, menos do que 88 dias com %MG e semelhante a 70 dias com o IMC. A concordância entre o resultado detectado pelo IMG e pelo % MG foi elevada (kappa 0,701), porém muito baixa entre o sucesso detectado pelo IMC e pelo IMG (kappa 0,231) ou %MG (kappa 0,125). Conclusões O IMG atingiu a melhor combinação de capacidade e precocidade para identificar redução na adiposidade durante o monitoramento do controle de peso em crianças obesas pré-púberes.

Reference Values of Body Composition Indices: The Korean National Health and Nutrition Examination Surveys

PURPOSE: An increase in the prevalence of obesity has been observed in children and adolescents. As remarkable changes in body composition occur with growth during the adolescent period, it is important that changes in body composition be monitored. The purpose of this study was to propose reference percentile values for body composition indices including body mass index (BMI) in children and adolescents in Korea. MATERIALS AND METHODS: This study was performed using data from the Fourth and Fifth Korea National Health and Nutrition Examination Surveys. Body composition data were obtained using dual-energy X-ray absorptiometry. The percentile curves of body composition indices were constructed by the LMS method. RESULTS: A total of 2123 children and adolescents between the ages of 10 and 19 years were included in this study. We obtained the percentile curves for BMI and body composition indices. CONCLUSION: The reference values for body composition from this study could help with assessing body composition in Korean adolescents.

Validity of simple, novel measures of generalized and central obesity among young Asian Indian women.

Objective: The study examined the validity of simple and novel measures of generalized obesity- [body mass index (BMI, kg/m 2 ), fat mass index (FMI, kg/m 2 ), and body fat percent (BF%)] and central obesity- [waist circumference (WC, cm), waist-hip ratio (WHR), and waist-to-height ratio (WC/ht ratio)] against BF% and BMI as criteria. It also aimed to predict fat-free mass index (FFMI, kg/m 2 ), FMI, and BF% ranges for various BMI categories. Design: Cross-sectional study. Materials and Methods: Weight, BF%, fat mass (FM), and fat-free mass (FFM) were measured using leg-to-leg bioelectrical impedance in 183 women. Height, hip, and waist circumferences were taken using standard methods. The indices [FMI, FFMI, WHR, W/ht ratio] were computed. Results: The study revealed that FMI, BMI, WC, and WC/ht ratio were highly correlated with BF% (r = 0.978; r = 0.939; r = 0.894; r = 0.890, respectively, P < 0.01), whereas WHR had the least correlation (r = 0.497, P < 0.01). The FMI showed a higher positive predictive value (PPV) in diagnosing generalized obesity compared to BMI with BF% as criterion and higher PPV than BF% with BMI as criterion. Considering only the indices of central obesity, WC was the most predictive in identifying women with high BF% (≥30% and ≥35%), whereas WC/ht ratio proved to be a better index in identifying women with BMI greater than 23 and 25 kg/m 2 . The normal BMI for Asians (18.5-23 kg/m 2 ), the at-risk group (23- 25 kg/m 2 ), and the obese class I (25-30 kg/m 2 ) corresponded to FFMI values of 14.1-15.1 kg/m 2 , 15.1-15.5 kg/m 2 , 15.5-16.1 kg/m 2 , respectively, and to FMI values of 4.4-7.9 kg/m 2 , 7.9-9.5 kg/m 2 , 9.5-13.9 kg/m 2 , respectively. The BMI cutoff of 18.5, 23, 25, 27.5, and 30 kg/m 2 corresponded to BF% of 23.6, 34.3, 38.3, 42.6, and 46.3%, respectively. Conclusion: FMI was a better predictor of generalized obesity compared to BMI and BF%. Considering abdominal obesity as an independent risk factor for insulin resistance, both WC and WC/ht ratio were able to predict central obesity better than WHR. Finally, the study presents ranges for FFMI and FMI for various BMI categories.

Relationship between body composition index and blood pressure among children aged 7-12 / 中华流行病学杂志

Objective To explore the relationship between body composition index and blood pressure of children, and to provide bases for early prevention against adult diseases. Methods A total of 4326 children aged 7-12 participated in this study, with height, weight, skinfold thickness (SFT)and blood pressure(BP)of all subjects measured. Body fat percentage(BF%)were calculated by regression equation, fat mass index(FMI)and fat-free mass index(FFMI)were calculated according to following expressions: FMI(kg/m2)=BF% × weight/height2 and FFMI(kg/m2)=(weight - BF% × weight)/height2. Results Systolic blood pressure(SBP)and diastolic blood pressure(DBP)were positively correlated with FMI and FFMI in both boys and girls. Correlation coefficients between SBP, DBP and FMI were 0.432-0.531, 0.316-0.450 for boys, and 0.413-0.485, 0.345-0.421 for girls respectively and the correlation coefficients between SBP, DBP and FFMI were 0.214-0.366, 0.090-0.250 for boys, and 0.108-0.383, 0.063-0.214 for girls respectively. The coefficient between BP and FMI were larger than those between BP and FFMI. The mean values of FMI and FFMI of children with high BP were significantly higher than those normal children, especially showed in FMI. Conclusion In order to prevent hypertension among children,priority should be comcentrated on controlling body fat and preventing obesity.

Optimal variables and corresponding cut-off points for identification of cardiovascular risk factors clustering among elderly males / 上海第二医科大学学报

Objective To explore the optimal cut-off points of body mass index(BMI),percentage of body fat(PBF) and body fat mass index(BFMI) for identification of cardiovascular risk factors clustering among elderly males. MethodsThe data of physical examinations from 1 052 Shanghai elderly males in 2007 were collected.The relationship between cardiovascular risk factors clustering and different strata of BMI,PBF and BFMI was analyzed.Receiver Operator Characteristic(ROC) curve analysis was employed to determine the optimal cut-points for identification of cardiovascular risk factors clustering,and area under curve(AUC) was worked out.The population attributable risk proportion(PARP) of risk factors clustering was calculated. Results Odds ratios of risk factors clustering tended to increase with BMI,PBF and BFMI.BMI≥24 kg/m2,PBF≥21% and BFMI≥5 kg/m2 were the cut-off points that had approximate sensitivity and specificity,and/or had the shortest distance in ROC curve.AUC of all the three indexes was larger than 0.5.Analysis of PARP indicated that BMI under 24 kg/m2,PBF under 21% and BFMI under 5 kg/m2 could prevent 27.1%,37.44% and 36.63% risk factors clustering,respectively. Conclusion BMI≥24 kg/m2,PBF≥21% and BFMI≥5 kg/m2 can well reflect the cardiovascular risk factors clustering among elderly males.