Diet Quality in Relation to Fat, Lean, and Bone Mass in Children: A Population-based Study (P18-105-19)

AB0250 The adipose tissue as predictive factor of disease activity in rheumatoid arthritis patients: evaluation of body fat composition by bioelectrical impedance analysis and ultrasonography

The importance of body composition assessment in the rehabilitation process

The significance of high bone density in children

The aim of this study was to examine associations of body composition (fat mass index, % fat mass, fat-free mass index, body mass index) and physical fitness (cardiorespiratory fitness and handgrip strength) with gestational diabetes and cardiovascular health in early pregnancy. This cross-sectional study utilized baseline data (n = 303) collected in early pregnancy from the HealthyMoms trial. Body composition was measured using air-displacement plethysmography, cardiorespiratory fitness was assessed by means of the 6-min walk test and handgrip strength using a dynamometer. Logistic regression was used to estimate odds ratios (ORs) for gestational diabetes as well as high (defined as 1 SD above the mean) blood pressure, homeostatic model assessment for insulin resistance (HOMA-IR), and metabolic syndrome score (MetS score) per 1 SD increase in body composition and fitness variables. Fat mass index, % fat mass and body mass index were all strongly associated with gestational diabetes (ORs: 1.72–2.14, P ≤ 0.003), HOMA-IR (ORs: 3.01–3.80, P < 0.001), blood pressure (ORs: 1.81–2.05, P < 0.001) and MetS score (ORs: 3.29–3.71, P < 0.001). Associations with fat-free mass index were considerably weaker (ORs: 1.26–1.82, P = 0.001–0.15) and were strongly attenuated after adjustments for fat mass index (ORs: 0.88–1.54, P = 0.039–0.68). Finally, greater cardiorespiratory fitness was associated with lower risk of high HOMA-IR and MetS score (ORs: 0.57–0.63, P ≤ 0.004) although these associations were attenuated when accounting for fat mass index (ORs: 1.08-1.11, P ≥ 0.61). In conclusion, accurately measured fat mass index or % fat mass were strongly associated with gestational diabetes risk and markers of cardiovascular health although associations were not stronger than the corresponding ones for body mass index. Fat-free mass index had only weak associations with gestational diabetes and cardiovascular health which support that the focus during clinical care would be on excess fat mass and not fat-free mass.

Female reproductive status influences body composition, including fat mass (FM), fat-free mass (FFM), and bone health. We aimed to examine differences in body composition, bone health, and bioelectrical impedance analysis (BIA) parameters, including phase angle (PhA), among women with healthy menstruation, dysmenorrhea, and postmenopause. Forty-five female participants were included and divided into control (healthy menstruation; n = 13), dysmenorrhea (n = 14), and postmenopausal (n = 18) groups. Body composition, bone mineral density (BMD), bone mineral content (BMC), and BIA parameters were measured using dual-energy X-ray absorptiometry and multifrequency BIA. The postmenopausal group had significantly lower BMD, BMC, and PhA. In the control group, PhA was positively correlated with body mass, body mass index, FM, FM index, FFM, and FFM index, whereas no correlations were observed in the other groups. Classic bioelectrical impedance vector analysis (BIVA) parameters were consistent with FFM and FFM index, while specific BIVA aligned with body fat. Graphical BIVA analysis showed signs of edema and decreased body cell mass in the postmenopausal group. These findings highlight important differences in body composition, bone health, and bioelectrical parameters across reproductive stages, with a focus on managing muscle loss and edema according to reproductive status.

Increased rates of overweight/obesity have been reported in recent years in developed countries. This population study of healthy subjects evaluated the changes in overweight/obesity prevalence in 2003, compared with 1993, and determined the association of age, sex and leisure-time activity with body mass index (BMI), fat-free mass index (FFMI) and fat mass index (FMI). Two transversal samples of convenience. Healthy volunteers (1993, n = 802; 2003, n = 1631). Fat-free mass was determined using the bioelectrical impedance multiple regression equation. Multivariable linear regression, including confounding variables (age, sex, leisure-time activity), was used to model the body composition evolution between the 1993 and the 2003 subjects. BMI and FMI were higher in 2003 than in 1993, P < 0.001. FFMI was not higher in 2003 than in 1993, P = 0.38. More subjects were overweight/obese in 2003 than in 1993 (27.5 versus 17.2%, chi-square P < 0.001), and had a high FFMI (30.2 versus 21.8%, chi-square P < 0.001) and high FMI (28.0 versus 20.3%, chi-square P < 0.001). Multivariate linear regressions showed that leisure-time activity was negatively, and sex, age and inclusion year were positively associated with BMI, FFMI and FMI (the exception was a negative association with sex) (P < 0.001). Overweight prevalence increased between 1993 and 2003 in a Swiss city, and was associated with a higher fat mass. This observation remained statistically significant after adjustment for age, sex and leisure-time activity.

Cross-sectional association of grain and tubers with body composition among children and adolescents in South China

Objective To describe aerobic capacity and body composition of school-aged children in Shanghai and explore the potential relationship between body composition and aerobic capacity.Methods Totally 63 school-aged children in Shanghai were measured for height,weight,fat percentage (FAT％),and fat-free mass (FFM).Body composition was estimated from bioelectrical impedance analysis (BIA).Body mass index (BMI),fat mass index (FMI),and fat-free mass index (FFMI) were calculated.Aerobic capacity (VO2max and the maximum oxygen pulse) were measured using the COSMED fitmate metabolic systems (combined heart rate and cycling test).Results The boys who were obese or overweight had both higher absolute value of VO2max and lower relative values of VO2max than other boys [(1 038.50 ± 157.93) ml/min vs (923.90±82.03) ml/min,F=4.812,P=0.005; (23.62±4.22) ml/ (kg· min) vs (27.75 ±2.41) ml/ (kg · min),F =5.633,P =0.002].The girls who were obese or overweight tended to have higher absolute value of VO2max [(966.70 ± 131.22) ml/min vs (892.55 ± 108.71) ml/min] and lower relative values of VO2 max [(23.84 ± 4.30) ml/ (kg · min) vs (28.09 ± 4.52) ml/ (kg · min)] than other girls.After controlling for age,the relative VO2max values were negatively associated with body mass index (BMI),degree of obesity,FAT％,FM,FFM,FMI,FFMI (boys:r =-0.675,P ＜ 0.000 1 ; r =-0.634,P＜0.000 1; r=-0.667,P＜0.000 1; r=-0.726,P＜0.000 1; r=-0.594,P＜0.000 1;r=-0.686,P＜0.000 1; r=-0.456,P=0.010; girls:r=-0.651,P ＜0.000 1; r=-0.552,P=0.002; r=-0.527,P=0.003; r=-0.633,P＜0.000 1; r=-0.520,P=0.004; r=-0.579,P=0.001 ; r =-0.597,P =0.001).In boys,the maximum oxygen pulse was positively correlated with BMI,FFM,and FFMI (r =0.358,P=0.048; r =0.543,P=0.002; r =0.554,P=0.001); in girls,the maximum oxygen pulse was positively correlated with FFM and FFMI (r =0.378,P =0.043 ; r =0.449,P =0.014).Conclusions Aerobic capacity is associated with body composition in school-aged children.Higher degree of obesity is associated with poorer aerobic capacity.Maximum oxygen pulse is also associated with FFM. Key words: Body composition; Aerobic capacity; Childhood obesity

To observe the effect of age and menstrual status on body composition in healthy Beijing women. We measured body composition with dual-energy X-ray (GE Lunar Prodigy) in 316 healthy Beijing females aged 20 to 74 years (5-7 cases per age). Parameters provided by the software were as following: total body bone mineral content, lean mass, fat mass and fat percentage (%fat). Local regions measured included arm, leg, trunk, android region and gynoid region. Body mass index (BMI), fat mass index (FMI), free fat mass index (FFMI) and A/G were calculated. Volunteers were assigned to 6 groups according age by every ten years a group. BMC peaked during the 4th decade, LM peaked during the 5th decade, with a decline of 18.1% and 5.2% respectively at age 74 years. Total body fat mass and %fat showed a general increase with aging throughout the studied age range. Total body fat mass increased from 16+/-5 kg at age 20-29 years to 24+/-6 kg at age 70-74 years, while %fat increased from 31.3% to 39.5%. All local region %fat increased with aging at different extents. Android region %fat showed the largest raise extent (32.2%). BMI increased gradually from 21.1 kg/m2 at age 20-29 years to 26.1 kg/m2 at age 70-74 years. FMI changed more obviously than FFMI. A/G increased from 0.85 at age 20-29 years to 1.02 at age 70-74 years. Different menstrual status in women of 40-59 years had obvious effect on A/G and BMC (P<0.05), while it had no significant effect on BMI, body weight and waist circumference (P>0.05). Aging and menstrual status have evident effect on body composition distribution in healthy Beijing women.

BackgroundObesity and overweight, as determined by the body mass index (BMI), are harmful to metabolic health. However, the BMI can not reflect body composition or fat distribution. The fat-free mass index (FFMI) and the fat mass index (FMI) can provide more information on body composition. The aim of the observational research was to determine whether the FMI and the FFMI are significantly associated with the risk of developing diabetes and prediabetes.MethodsThe investigators included data for 10,085 National Health and Nutrition Examination Survey (2011–2018) participants aged over 20 years who underwent dual-energy X-ray absorptiometry (DXA). The FFMI and the FMI were determined based on total fat mass and lean mass measured by DXA. Diabetes and prediabetes status were determined by medical history and laboratory examination. Logistic regression analyses were performed to explore the correlations between the FMI/FFMI and the risk of developing diabetes/prediabetes. Restricted cubic spline analysis was used to explore underlying nonlinear associations.ResultsIn the present study, 1,135 patients were diagnosed with diabetes, 3,258 had prediabetes, and 5,692 were classified as control participants. The FFMI (odds ratio (OR) = 1.10, 95% confidence interval (CI) = 1.04–1.16) and the FMI (OR = 1.08, 95% CI = 1.04–1.12) were independently related to an increased risk of developing diabetes. Moreover, the FFMI (OR 1.08, 95% CI 1.02–1.16) and the FMI (OR 1.07, 95% CI 1.02–1.13) also independently correlated with a rising risk of developing prediabetes. The restricted cubic spline (RCS) outcomes suggested that the associations are approximately linear.ConclusionsBoth the FMI and the FFMI significantly correlated with the danger of developing diabetes and prediabetes, and the correlations are approximately linear.

THU0168 Relationships between body fat composition assessed with bioelectrical impedance analysis, serum adipokines and disease activity in patients with rheumatoid arthritis

Running performance in a timed city run and body composition: A cross-sectional study in more than 3000 runners

The aims of this study were to identify the relationship of paternal feeding practices and preschool children's 1) eating behavior, 2) diet quality, and 3) weight status. Fathers of preschoolers (n=150) were recruited to participate in a one‐on‐one interview to assess feeding practices (Child Feeding Questionnaire), child eating behaviors (Children's Eating Behavior Questionnaire), and diet quality (24 hour recall, Healthy Eating Index). Height and weight for each father and child were measured and Body Mass Index (BMI) or BMI z‐score calculated. Linear regression was used to test the study aims. Paternal feeding practices were not related to child diet quality or weight status. However, child eating behaviors were associated with child BMI z‐score and these relationships were moderated by paternal feeding practices. For example, child satiety responsiveness was inversely (β= ‐.421, p= 0.031) associated with child BMI z‐score, only if paternal restriction scores were high, and was not significant when paternal restriction scores were low (β= ‐.200, p= 0.448). These results suggest that some child appetitive traits may be related to child weight status when exposed to certain paternal feeding practices. Future studies should consider the inclusion of fathers, in addition to mothers, as their feeding practices may influence the relationship between child eating behavior and child weight.

Diet Quality of Children in the United States by Race/Ethnicity Within Categories of Body Mass Index (P18-110-19)

Background/Objectives: Aging is linked to a loss of muscle mass and strength, which increases the risk of falls, disability, and lower quality of life. Identifying individuals at risk of sarcopenia, cachexia, or malnutrition is important. In settings with limited access to advanced diagnostics, simple anthropometric measurements can serve as practical alternatives. This study aimed to evaluate simple, quick, and non-invasive anthropometric measurements as indicators of muscle mass in older adults, based on body composition analysis (BIA). Methods: The study included 361 patients admitted to a geriatric ward. Standardized protocols were used to measure anthropometric and body composition parameters, including bioelectrical impedance analysis (BIA). Various body composition indices were calculated, such as body mass index (BMI), body adiposity index (BAI), waist-to-hip ratio (WHR), visceral adiposity index (VAI), fat-free mass index (FFMI), and fat mass index (FMI). Results: Strong positive correlations were found between body mass and muscle mass in both women and men. Among anthropometric measures, calf circumference showed the strongest correlation with muscle mass (R = 0.798 in women; R = 0.744 in men, p < 0.001). Other indices, including BMI (R = 0.733 in women; R = 0.606 in men, p < 0.001), FFMI (R = 0.697 in women; R = 0.721 in men, p < 0.001), and FMI (R = 0.600 in women; R = 0.354 in men, p < 0.001), were also positively correlated with muscle mass. Conclusions: Calf circumference is a simple, quick, and non-invasive measure that can effectively estimate muscle mass in older adults. Although other anthropometric parameters, such as body mass, BMI, FMI, and FFMI, also showed positive correlations with muscle mass, calf circumference appears to be the most practical, as it requires minimal equipment, little time, and limited preparation. This makes it particularly useful for routine assessments in primary care and long-term care settings, where access to advanced diagnostic tools like BIA or DXA is limited. These findings support the use of simple anthropometric measurements as cost-effective and easily accessible alternatives for estimating muscle mass in older adults. Further research is needed to determine appropriate cut-off points for specific populations and sexes.