Changes In Fat Mass Index Research Articles

Changes in Fat Mass Index and Fat-Free Mass Index Vary Significantly by Age and Sex of the Patient, and by Type of Bariatric Surgery.

The loss of fat-free mass after rapid weight loss following bariatric surgery shows BMI is inadequate for reporting weight loss, emphasizing the need for a more accurate body composition metric. This study assessed changes in fat mass index (FMI), fat-free mass index (FFMI), and dietary intake over 6months after one-anastomosis gastric bypass (OAGB), Roux-en-Y gastric bypass (RYGB), and sleeve gastrectomy (SG) across age and sex groups. This prospective observational study included 151 bariatric surgery candidates. Data on demographics, anthropometric, body composition, and food intake data were collected before and 6months after surgery. SPSS version 22 was used for analysis, employing ANOVA and t-tests to assess group differences. Younger patients (≤ 35years) had higher percent total and excess weight loss (%TWL and %EWL) across all bariatric surgeries, and those undergoing SG experienced more favorable changes in fat-free mass (FFM) and visceral fat compared to other procedures (P = 0.002). Males had higher percent change in fat mass index (%∆ FMI) and visceral fat than females with OAGB and RYGB (P < 0.05). Women undergoing SG and RYGB had a more significant decrease in energy intake compared to OAGB (P < 0.001), and the ≤ 35 and 35-44 age groups demonstrated lower reductions in energy intake following OAGB. Age, sex, and surgery type significantly affect bariatric surgery outcomes. Younger patients achieved greater weight-related improvements, while men undergoing RYGB experienced more substantial fat mass changes than women.

Increased skeletal muscle mass index was involved in glycemic efficacy following diabetes treatment, and changes in fat mass index correlated with the changes in the lipid ratio in type 2 diabetes

AimThis study aimed to investigate the association between changes in body composition, glycated hemoglobin, and lipid ratio during the treatment of patients with type 2 diabetes mellitus (T2DM). MethodsThis retrospective analysis used data from outpatients with T2DM who had confirmed body composition and measured laboratories at administration and after treatment. The baseline characteristics and prescribed treatment were collected. The total cholesterol/high-density lipoprotein cholesterol (HDL) ratio, low-density lipoprotein cholesterol (LDL)/HDL ratio, and triglyceride–glucose (TyG) index were also calculated. ResultsA total of 207 patients (mean patient age, 62.0 ± 13.7 years; 68.1 % males) were enrolled. Fat mass index (FMI) changes correlated with the changes in the lipid ratio, whereas skeletal muscle mass index (SMI) changes inversely correlated with glycated hemoglobin (HbA1c) changes. Multiple regression analysis showed that changes in LDL/HDL and TyG correlated with FMI changes (t = 2.388, p = 0.017, t = 2.022, p = 0.044). Conversely, HbA1c changes correlated with SMI changes (t = −2.552, p = 0.011). ConclusionIn patients with T2DM, increased SMI was involved in glycemic efficacy, and FMI changes were associated with LDL/HDL and TyG.

MP72-13 AI CHARACTERIZATION OF LONGITUDINAL CHANGES IN BODY COMPOSITION: PREDICTORS OF CHANGE AFTER RADICAL CYSTECTOMY

You have accessJournal of UrologyCME1 Apr 2023MP72-13 AI CHARACTERIZATION OF LONGITUDINAL CHANGES IN BODY COMPOSITION: PREDICTORS OF CHANGE AFTER RADICAL CYSTECTOMY Anthony Fadel, Vidit Sharma, Matthew K. Tollefson, Daniel J. Blezek, Robert F. Tarrell, Prabin Thapa, Lyndsay D. Viers, Aaron M. Potretzke, Stephen A. Boorjian, Igor Frank, Robert P. Hartman, and Boyd R. Viers Anthony FadelAnthony Fadel More articles by this author , Vidit SharmaVidit Sharma More articles by this author , Matthew K. TollefsonMatthew K. Tollefson More articles by this author , Daniel J. BlezekDaniel J. Blezek More articles by this author , Robert F. TarrellRobert F. Tarrell More articles by this author , Prabin ThapaPrabin Thapa More articles by this author , Lyndsay D. ViersLyndsay D. Viers More articles by this author , Aaron M. PotretzkeAaron M. Potretzke More articles by this author , Stephen A. BoorjianStephen A. Boorjian More articles by this author , Igor FrankIgor Frank More articles by this author , Robert P. HartmanRobert P. Hartman More articles by this author , and Boyd R. ViersBoyd R. Viers More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003340.13AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Long term body composition changes after radical cystectomy (RCx) are unknown. Herein, we characterize changes in body composition over one year after RCx and determine predictors of unfavorable change in radiographic nutritional indices. METHODS: CT images for 843 RCx patients from 2009-2017 were collected at baseline, 3 months, and 1 year. Artificial intelligence algorithms extracted two-dimensional axial skeletal muscle and adipose areas at the L3 level. Skeletal muscle index (SMI) and fat mass index (FMI) were calculated, and multivariable logistic regression models were performed to determine factors associated with unfavorable body composition change: absolute top tertile change in FMI and SMI. RESULTS: Muscle and fat body parameters decreased from baseline to 3 months but increased from 3 months to 1 year (Figure 1). However, the distributions of changes in SMI and FMI across these timepoints (Figure 2) show that some patients were able to maintain muscle and fat mass after surgery. In the first 3 months, increasing age and higher BMI were associated with greater loss in FMI (odds ratio (OR) < 1, p<.05); while neoadjuvant chemotherapy was associated with increased gains (OR 1.5, p=.03). After 3 months, robotic surgery was associated with greater gains in FMI (OR 1.8, p=.03). In the first 3 months, on multivariable analysis, men (OR 2.06), increasing BMI (OR 1.08), neoadjuvant chemotherapy (OR 3.98), and any 30-day complications (OR 1.79) were associated with greater loss in SMI from baseline to 3 months (p<.05 for all). After 3 months, older patients had smaller gains in SMI (p<.05), as did patients with bladder cancer recurrences (p<.05). On the contrary, patients with continent diversion were associated with greater gains in SMI (p<.05). CONCLUSIONS: Long-term changes in body composition after RCx are common, and clinically relevant predictors of unfavorable body composition change were identified indicating a catabolic state. Individualized rehabilitation interventions based on these predictors warrants further study. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1029 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Anthony Fadel More articles by this author Vidit Sharma More articles by this author Matthew K. Tollefson More articles by this author Daniel J. Blezek More articles by this author Robert F. Tarrell More articles by this author Prabin Thapa More articles by this author Lyndsay D. Viers More articles by this author Aaron M. Potretzke More articles by this author Stephen A. Boorjian More articles by this author Igor Frank More articles by this author Robert P. Hartman More articles by this author Boyd R. Viers More articles by this author Expand All Advertisement PDF downloadLoading ...

Longitudinal Change In Physical Activity And Adiposity In Transition From Adolescence To Adulthood

The current recommendations for moderate- and vigorous-intensity physical activity (MVPA) have a poorly-justified, abrupt transition that recommends youth achieve ≥60 minutes/day (min/d) and adults achieve ≥150 minutes/week (≥22 min/d on average). PURPOSE: To examine how body fat mass changes according to changes in MVPA from late adolescence (age 18 years) to early adulthood (age 22 years). METHODS: The study sample included 2,099 participants (1,113 females) from the 1993 Pelotas (Brazil) Study. At ages 18 and 22 years, MVPA was measured using wrist-worn accelerometry and fat mass was measured using dual-energy X-ray absorptiometry. MVPA at age 18 was categorized into two groups: 0-59 and ≥ 60 min/d (no [N] and yes [Y] for meeting the youth recommendation). MVPA at age 22 was categorized into three groups: 0-21, 22-59, and ≥ 60 min/d (N, Y22, and Y60 for meeting the adult or youth recommendation). The combination of these groups created six MVPA groups (N&N, N&Y22, N&Y60, Y&N, Y&Y22, and Y&Y60). Sex-specific multivariable linear regression analyses were conducted to estimate changes in fat mass index (FMI, kg/m2) from age 18 to 22 years according to the six MVPA groups. RESULTS: Among males, compared to Y&Y60 (FMI increase = 1.2 [95% CI = 1.0, 1.4]), Y&Y22 and Y&N had larger FMI increases (1.9 [1.6, 2.1] and 1.9 [1.2, 2.5], respectively). Among females, Y&Y60 and Y&Y22 had an equal FMI increase (1.6 [1.4, 1.9] for both groups), while Y&N had a larger FMI increase (2.4 [1.8, 3.0]). For males and females who were inactive at age 18 years, the FMI increase was the smallest among those with ≥60 min/d of MVPA at age 22 years (0.6 [0.1, 1.1] for males and 1.0 [0.5, 1.5] for females), followed by 22-59 min/d (1.0 [0.6, 1.3] for males and 1.4 [1.1, 1.6] for females), and 0-21 min/d (1.7 [1.1, 2.3] for males and 1.7 [1.4, 2.1] for females). CONCLUSION: These findings suggest that among those who were active in late adolescence, engaging in ≥22 min/d of MVPA in adulthood (adult recommendation) is sufficient to lower fat accumulation for females, but insufficient for males. With respect to healthy adiposity levels, these findings call into question the abrupt change in MVPA recommendations for young adult males.

Longitudinal change in physical activity and adiposity in the transition from adolescence to early adulthood: the 1993 Pelotas cohort study

BackgroundIn the current Physical Activity Guidelines (PAG) for moderate- and vigorous-intensity physical activity (MVPA), abrupt transition from ≥ 60 min/day [youth PAG] to ≥ 150 min/week (≥ 22 min/day on average) [adult PAG] during emerging adulthood is poorly justified. The aim of this study was to examine body fat mass changes according to whether meeting the youth and adult PAGs in late adolescence (age 18 years) to early adulthood (age 22 years).MethodsThe study sample included 2,099 participants (1,113 females) from the 1993 Pelotas (Brazil) Study. At ages 18 and 22 years, MVPA was measured using wrist-worn accelerometry and fat mass was measured using dual-energy X-ray absorptiometry. MVPA at age 18 was categorized into two groups: 0–59 or ≥ 60 min/day (no [N] or yes [Y] for meeting the youth recommendation, respectively). MVPA at age 22 was categorized into three groups: 0–21, 22–59, or ≥ 60 min/day (N, Y22, or Y60 for not meeting the adult recommendation, meeting the adult recommendation, or meeting the youth recommendation, respectively). The combination of these groups created six MVPA groups (N&N, N&Y22, N&Y60, Y&N, Y&Y22, and Y&Y60). Sex-specific multivariable linear regression analyses were conducted to estimate change in fat mass index (FMI) from age 18 to 22 years in the six MVPA groups.ResultsAmong males, compared to Y&Y60 (FMI increase = 1.2 kg/m2 [95% CI = 1.0, 1.4]), Y&Y22 and Y&N had larger FMI increases (1.9 [1.6, 2.1] and 1.9 [1.2, 2.5], respectively). Among females, Y&Y60 and Y&Y22 had an equal FMI increase (1.6 [1.4, 1.9] for both groups), while Y&N had a larger FMI increase (2.4 [1.8, 3.0]).ConclusionsThese findings suggest that among those who were active in late adolescence, engaging in ≥ 22 min/day of MVPA in adulthood is associated with lower body fat gain for females, but not for males.

Area-level and family-level socioeconomic position and body composition trajectories: longitudinal analysis of the UK Millennium Cohort Study

SummaryBackgroundInequalities in the trajectories of body composition in childhood and adolescence have been infrequently studied. Despite the importance of environmental factors in obesity development, little research has looked at area-level socioeconomic position, independent of family socioeconomic position. We aimed to assess how inequalities in body composition develop with age.MethodsThe Millennium Cohort Study is a longitudinal study of 19 243 families who had a child born between 2000 and 2002 in the UK. Multilevel growth curve models were applied to examine change in fat mass index (FMI), fat free mass index (FFMI; using the Benn index), and fat mass to fat free mass ratio (FM:FFM), measured using Bioelectrical Impedance Analysis, from ages 7 years to 17 years by the Index of Multiple Deprivation (IMD) and household income at baseline.FindingsInequalities in FMI and FM:FFM ratio are evident at age 7 years and widen with age. At age 17 years, adolescents in the most disadvantaged IMD group had FMI 0·57 kg/mB (B=Benn parameter; 95% CI 0·43 to 0·70) higher and FM:FFM ratio 0·037 (95% CI 0·026 to 0·047) higher compared with the most advantaged group. Disadvantaged socioeconomic position is associated with higher FFMI but is reversed in adolescence after adjustment for FMI. Inequalities were greater in girls at age 7 years (mean FMI 0·22 kg/mB; 95% CI 0·13 to 0·32) compared with boys of the same age (0·05 kg/mB; –0·04 to 0·15, p=0·3), but widen fastest in boys, especially for FMI, in which there was over an 11 times increase in the inequality from age 7 years of 0·05kg/mB (95% CI –0·04 to 0·15) to 0·62 kg/mB at 17 years (0·42 to 0·82). Inequalities for the IMD were similar to income, and persisted at age 17 years independent of family socioeconomic position.InterpretationChildhood and adolescence is an important period to address inequalities in body composition, as they emerge and widen. Policies should consider FFM as well as FM, and inequalities in the environment.FundingMedical Research Council, Economic and Social Research Council.

Age-Related Changes in Body Composition and Bone Mineral Density and Their Relationship with the Duration of Diabetes and Glycaemic Control in Type 2 Diabetes.

PurposeTo investigate age-related changes in body composition (BC) and bone mineral density (BMD) in type 2 diabetes (T2D) and analyse whether diabetes duration or glycaemic control affects these factors.Patients and MethodsWe enrolled 1474 hospitalized T2D patients (817 males and 657 females; 45–85 years). BC and BMD were assessed by dual-energy X-ray absorptiometry (DEXA). Patients were stratified into age groups: 45–54, 55–64, 65–74, and ≥75 years. Continuous variables were compared using t-tests or one-way analysis of variance (ANOVA), and categorical variables were compared using chi-square tests. Effects of age, diabetes duration, and haemoglobin A1C (HbA1c) on BC and BMD were assessed with multiple linear regression models.ResultsIn T2D, in females, changes in fat mass index (FMI) were positively correlated with age, while changes in lean mass index (LMI) were unrelated to age. Changes in FMI or LMI in males were unrelated to age. For regional BC distribution, changes in visceral adipose tissue (VAT) were positively correlated with age for both males and females, while changes in appendage lean mass (ALM) were negatively correlated with age. For BMD, changes in total BMD (TBMD) in males were not correlated with age, while changes in lumbar spine BMD (LBMD) were positively correlated with age, and femoral neck BMD (FNBMD) was negatively correlated with age. Changes in BMD in all parts of females were negatively correlated with age. In addition, changes in BC and BMD were unrelated to diabetes duration, and HbA1c was mainly associated with decreases in lean mass but had little effect on other BC and BMD parameters.ConclusionIn T2D, changes in BC and BMD were associated with age but not diabetes duration. A higher HbA1c is associated with lower lean mass.

Role of ultra-processed food in fat mass index between 6 and 11 years of age: a cohort study.

Ultra-processed food consumption and obesity have been highlighted as an important relationship to public health. We aimed to evaluate the association between ultra-processed food consumption and body fat from 6 to 11 years of age. We assessed the association between ultra-processed food consumption (from food frequency questionnaires) and body fat (measured by air displacement plethysmography) between 6 and 11 years of age among participants of the Pelotas-Brazil 2004 Birth Cohort. The NOVA classification was used to classify foods according to the processing degree. Body fat was evaluated relative to the height using fat mass index (FMI). Generalized estimating equations were used to answer the main research question and mediation analyses were run to assess the direct and indirect effect of ultra-processed food in body fat. At fully adjusted analysis, an increase of 100 g in contribution from ultra-processed food to daily food intake at between 6 and 11 years of age was associated with a gain of 0.14 kg/m² in FMI in the same period; 58% of the total effect of ultra-processed food intake at 6 years (in grams) over the change in FMI from 6 to 11 years was mediated by its calorie content. Ultra-processed food consumption was associated with an increase in body fat from childhood to early adolescence, and this association was not just due to the effect of ultra-processed food on calorie content.

Longitudinal changes in body composition and waist circumference by self-reported levels of physical activity in leisure among adolescents: the Troms\xf8 study, Fit Futures

BackgroundIt is not clear how physical activity affects body composition in adolescents. Physical activity levels are often reduced during this period, and the relative proportion of body fat mass and lean mass undergo natural changes in growing adolescents. We aimed to examine whether self-reported physical activity in leisure time at baseline or change in activity during follow-up affect changes in four measures of body composition; body mass index (kg/m2), waist circumference, fat mass index (fat mass in kg/m2) and lean mass index (lean mass in kg/m2).MethodsWe used data from the Tromsø Study Fit Futures, which invited all first year students in upper secondary high school in two municipalities in northern Norway in 2010–2011. They were reexamined in 2012–2013. Longitudinal data was available for 292 boys and 354 girls. We used multiple linear regression analyses to assess whether self-reported level of physical activity in leisure time at baseline predicted changes in body composition, and analysis of covariance to assess the effects of change in level of activity during follow-up on change in body composition. All analyses were performed sex-specific, and a p-value of < 0.05 was considered statistically significant.ResultsThere were no associations between self-reported leisure time physical activity in the first year of upper secondary high school and changes in any of the considered measure of body composition after 2 years of follow up, with the exception of waist circumference in boys (p = 0.05). In boys, change in fat mass index differed significantly between groups of activity change (p < 0.01), with boys adopting activity or remaining physically active having less increase in fat mass index than the consistently inactive. In girls, change in lean mass index differed significantly between groups of activity change (p = 0.04), with girls adopting physical activity having the highest increase.ConclusionsSelf-reported leisure time physical activity does not predict changes in body composition in adolescents after 2 years of follow up. Change in the level of physical activity is associated with change in fat mass index in boys and lean mass index in girls.

An Increase in Fat Mass Index Predicts a Deterioration of Running Speed.

A low fat mass is associated with a good running performance. This study explores whether modifications in body composition predicted changes in running speed. We included people who underwent several measurements of body composition by bioelectrical impedance analysis between 1999 and 2016, at the “Course de l’Escalade”, taking place yearly in Geneva. Body composition was reported as a fat-free mass index (FFMI) and fat mass index (FMI). Running distances (men: 7.2 km; women: 4.8 km) and running times were used to calculate speed in km/h. We performed multivariate linear mixed regression models to determine whether modifications of body mass index, FFMI, FMI or the combination of FFMI and FMI predicted changes in running speed. The study population included 377 women (1419 observations) and 509 men (2161 observations). Changes in running speed were best predicted by the combination of FFMI and FMI. Running speed improved with a reduction of FMI in both sexes (women: ß −0.31; 95% CI −0.35 to −0.27, p < 0.001. men: ß −0.43; 95% CI −0.48 to −0.39, p < 0.001) and a reduction of FFMI in men (ß −0.20; 95% CI −0.26 to −0.15, p < 0.001). Adjusted for body composition, the decline in running performance occurred from 50 years onward, but appeared earlier with a body mass, FFMI or FMI above the median value at baseline. Changes of running speed are determined mostly by changes in FMI. The decline in running performance occurs from 50 years onward but appears earlier in people with a high body mass index, FFMI or FMI at baseline.

Short Malnourished Children and Fat Accumulation With Food Supplementation.

In moderate acute malnutrition programs, it is common practice to not measure mid-upper arm circumference (MUAC) of children whose length is <67 cm. This is based on expert opinion that supplementation of shorter children with low MUAC and weight-for-height z score ≥-2 may increase risk of excessive fat accumulation. Our aim was to assess if shorter children gain more fat than taller children when treated for moderate acute malnutrition diagnosed by low MUAC alone. In this observational study, we included children aged 6 to 23 months with a MUAC between 115 and 125 mm and a weight-for-height z score ≥-2. On the basis of length at admission, children were categorized as short if <67 cm and long if ≥67 cm. Linear mixed-effects models were used to assess body composition on the basis of deuterium dilution and skinfold thickness. After 12 weeks of supplementation, there was no difference in change in fat mass index (-0.038 kg/m2, 95% confidence interval [CI]: -0.257 to 0.181, P = .74) or fat-free mass index (0.061 kg/m2, 95% CI: -0.150 to 0.271, P = .57) in short versus long. In absolute terms, the short children gained both less fat-free mass (-230 g, 95% CI: -355 to -106, P < .001) and fat mass (-97 g, 95% CI: -205 to 10, P = .076). There was no difference in changes in absolute subscapular and triceps skinfold thickness and z scores (P > .5). Short children with low MUAC do not gain excessive fat during supplementation. With these data, we support a recommendation for policy change to include all children ≥6 months with low MUAC in supplementary feeding programs, regardless of length. The use of length as a criterion for measuring MUAC to determine treatment eligibility should be discontinued in policy and practice.

Cord blood leptin and gains in body weight and fat mass during infancy.

Low early-life leptin concentrations may promote faster weight gain in infancy. We aimed to examine the associations between cord blood leptin concentrations and changes in weight and body composition during infancy. Serum leptin was measured at 15 weeks gestation, in umbilical cord blood collected at delivery and at 2 years in 334 children from the Cork Baseline Birth Cohort Study. Body composition was measured at 2 days and 2 months using air displacement plethysmography. Conditional change in weight standard deviation scores over a number of age intervals in the first 2 years and conditional change in fat mass index (FMI) and fat-free mass index (FFMI) (kg/(length)m(2)) between birth and 2 months were calculated and associations with cord blood leptin were examined using linear regression. At birth, cord blood leptin was positively correlated with FMI (r = 0.48, P < 0.001) and showed a weaker correlation with FFMI (r = 0.12, P = 0.05). After adjustment for confounders, higher cord blood leptin (per ng/mL) was associated with slower conditional weight gain between birth and 2 months (β (95% CI): -0.024 (-0.035, -0.013), P < 0.001) but not over subsequent age intervals. Cord blood leptin was also inversely associated with conditional change in FMI (-0.021 (-0.034, -0.007, P = 0.003) but not FFMI between birth and 2 months. These are the first data to show that associations between higher cord blood leptin and slower weight gain during infancy are driven by lower increases in adiposity, at least in early infancy.

Effect of increased intake of skimmed milk, casein, whey or water on body composition and leptin in overweight adolescents: a randomized trial.

Dairy proteins may support muscle protein synthesis and improve satiety in adults. However, there are limited studies using exact measures of body composition, especially in adolescents. This study investigates the effect of milk proteins and water on body composition and leptin in overweight adolescents. Subjects (n = 193) aged 12-15 years were randomized to drink 1 L d(-1) of skimmed milk, whey, casein (all milk-based drinks 35 g protein L(-1) ) or water for 12 weeks. Twenty participants dropped out. A pre-test control group of 32 adolescents was examined 12 weeks before start of intervention. Outcomes included leptin and dual-energy X-ray absorptiometry scanning. The effects of the milk-based drinks on body composition and leptin were compared with baseline, pre-test control and water. Lean mass index (LMI) increased compared to baseline (all 95% confidence intervals 0.05-0.50 kg m(-2) , all P ≤ 0.009) and the pre-test control group (0.044-0.247 kg m(-2) , P ≤ 0.002) for all four test drinks. Fat mass index (FMI) increased only for milk-based drink groups compared with baseline (0.15-0.67 kg m(-2) , P < 0.001) and also compared with water (0.029-0.255 kg m(-2) , P ≤ 0.011). For pre-test control, there was no change in FMI or LMI. Leptin increased in the casein (1.016-3.246 ng mL(-1) , P < 0.001; 0.952-3.294 ng mL(-1) , P < 0.001) and whey groups (0.135-2.273 ng mL(-1) , P = 0.027; 0.069-2.322, P = 0.038) compared with water and pre-test control group, respectively. Although milk proteins increased LMI in overweight adolescents, there was a concurrent increase in FMI and leptin, whereas water only resulted in increased LMI. Thus, increased water intake may be beneficial for body composition in overweight adolescents.

The role of leptin and other hormones related to bone metabolism and appetite regulation as determinants of gain in body fat and fat-free mass in 8-11-year-old children.

Regulation of body composition during childhood is complex. Numerous hormones are potentially involved. Leptin has been proposed to restrain weight gain, but results are inconsistent. We examined whether baseline fasting levels of ghrelin, adiponectin, leptin, insulin, IGF-I, osteocalcin, and intact parathyroid hormone (iPTH) were associated with body composition cross sectionally and longitudinally in 633 8-11-year-olds. Data on hormones and body composition by dual-energy x-ray absorptiometry from the OPUS School Meal Study were used. We looked at baseline hormones as predictors of baseline fat mass index (FMI) or fat-free mass index (FFMI), and also subsequent changes (3 and 6 months) in FMI or FFMI using models with hormones individually or combined. Cross-sectionally, baseline leptin was positively associated with FMI in girls (0.211 kg/m(2) pr. μg/mL; 97.5% confidence interval [CI],0.186-0.236; P < .001) and boys (0.231 kg/m(2) pr. μg/mL; 97.5% CI, 0.200-0.261; P < .001). IGF-I in both sexes and iPTH in boys were positively associated with FMI. An inverse association between adiponectin and FFMI in boys and a positive association between IGF-I and FFMI were found in girls. In longitudinal models, baseline leptin was inversely associated with subsequent changes in FMI (-0.018 kg/m(2) pr. μg/mL; 97.5% CI, -0.034 - -0.002; P = .028) and FFMI (-0.014 kg/m(2) pr. μg/mL; 97.5% CI, -0.024 - -0.003; P = .006) in girls. Cross-sectional findings support that leptin is produced in proportion to body fat mass, but the longitudinal observations support that leptin inhibits gains in FMI and FFMI in girls, a finding that may reflect preserved leptin sensitivity in this predominantly normal weight population.

Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer

Sarcopenia and changes in body composition following neoadjuvant chemotherapy (NAC) may affect clinical outcome. We assessed the associations between CT body composition changes following NAC and outcomes in oesophageal cancer. A total of 35 patients who received NAC followed by oesophagectomy, and underwent CT assessment pre- and post-NAC were included. Fat mass (FM), fat-free mass (FFM), subcutaneous fat to muscle ratio (FMR) and visceral to subcutaneous adipose tissue ratio (VA/SA) were derived from CT. Changes in FM, FFM, FMR, VA/SA and sarcopenia were correlated to chemotherapy dose reductions, postoperative complications, length of hospital stay (LOS), circumferential resection margin (CRM), pathological chemotherapy response, disease-free survival (DFS) and overall survival (OS). Nine (26 %) patients were sarcopenic before NAC and this increased to 15 (43 %) after NAC. Average weight loss was 3.7 % ± 6.4 (SD) in comparison to FM index (-1.2 ± 4.2), FFM index (-4.6 ± 6.8), FMR (-1.2 ± 24.3) and VA/SA (-62.3 ± 12.7). Changes in FM index (p = 0.022), FMR (p = 0.028), VA/SA (p = 0.024) and weight (p = 0.007) were significant univariable factors for CRM status. There was no significant association between changes in body composition and survival. Loss of FM, differential loss of VA/SA and skeletal muscle were associated with risk of CRM positivity. • Changes in CT body composition occur after neoadjuvant chemotherapy in oesophageal cancer. • Sarcopenia was more prevalent after neoadjuvant chemotherapy. • Fat mass, fat-free mass and weight decreased after neoadjuvant chemotherapy. • Changes in body composition were associated with CRM positivity. • Changes in body composition did not affect perioperative complications and survival.

Fatness predicts decreased physical activity and increased sedentary time, but not vice versa: support from a longitudinal study in 8- to 11-year-old children

To examine independent and combined cross-sectional associations between movement behaviors (physical activity (PA), sedentary time, sleep duration, screen time and sleep disturbance) and fat mass index (FMI), as well as to examine longitudinal associations between movement behaviors and FMI. Cross-sectional and longitudinal analyses were done using data from the OPUS school meal study on 785 children (52% boys, 13.4% overweight, ages 8-11 years). Total PA, moderate-to-vigorous PA (MVPA), sedentary time and sleep duration (7 days and 8 nights) were assessed by an accelerometer and FMI was determined by dual-energy X-ray absorptiometry (DXA) on three occasions over 200 days. Demographic characteristics, screen time and sleep disturbance (Children's Sleep Habits Questionnaire) were also obtained. Total PA, MVPA and sleep duration were negatively associated with FMI, while sedentary time and sleep disturbances were positively associated with FMI (P⩽0.01). However, only total PA, MVPA and sleep duration were independently associated with FMI after adjustment for multiple covariates (P<0.001). Nevertheless, combined associations revealed synergistic effects among the different movement behaviors. Changes over time in MVPA were negatively associated with changes in FMI (P<0.001). However, none of the movement behaviors at baseline predicted changes in FMI (P>0.05), but higher FMI at baseline predicted a decrease in total PA and MVPA, and an increase in sedentary time (P⩽0.001), even in normal-weight children (P⩽0.03). Total PA, MVPA and sleep duration were independently associated with FMI, and combined associations of movement behaviors showed a synergistic effect with FMI. In the longitudinal study design, a high FMI at baseline was associated with lower PA and higher sedentary time after 200 days but not vice versa, even in normal-weight children. Our results suggest that adiposity is a better predictor of PA and sedentary behavior changes than the other way around.

Less fat reduction per unit weight loss in type 2 diabetic compared with nondiabetic obese individuals completing a very-low-calorie diet program

The objective was to compare weight loss and change in body composition in obese subjects with and without type 2 diabetes mellitus during a very-low-calorie diet (VLCD) program. Seventy weight-matched subjects with diabetes or normal fasting glucose (controls) participated in a 24-week VLCD study. Primary end points were changes in anthropometry, body composition, and fasting plasma insulin and β-hydroxybutyrate concentrations. Fifty-one subjects (24 with diabetes) completed the study. No difference in weight loss between the 2 groups at 24 weeks was found by intention-to-treat analysis. Both groups completing the study per protocol had near-identical weight change during the program, with similar weight loss at 24 weeks (diabetes: 8.5 ± 1.3 kg vs control: 9.4 ± 1.2 kg, P = .64). Change in fat mass index correlated with change in body mass index (BMI) in both groups (diabetes: r = 0.878, control: r = 0.920, both P < .001); but change in fat mass index per unit change in BMI was less in the diabetic group compared with controls (0.574 vs 0.905 decrease, P = .003), which persisted after adjusting for age, sex, and baseline BMI (P = .008). Insulin concentrations remained higher and peak β-hydroxybutyrate concentrations were lower in the diabetic compared with the control group. While following a 24-week VLCD program, obese subjects with and without diabetes achieved comparable weight loss; but the decrease in adiposity per unit weight loss was attenuated in diabetic subjects. Hyperinsulinemia may have inhibited lipolysis in the diabetic group; however, further investigation into other factors is needed.

Association between dietary protein and change in body composition among children (EYHS)

Growth hormone (GH) affects body composition by a relatively reduced fat mass and increased fat free mass. The intake of protein as well as the specific amino acids arginine and lysine potently stimulate GH secretion. This study investigated associations between intakes of protein, arginine, lysine and subsequent 6-year change in body composition among 8-10-year-old children. Data of 364 children were collected from Odense, Denmark, during 1997-1998 and 6-year later as part of the European Youth Heart Study. Body mass index among children was subdivided by fat free mass index (FFMI) and fat mass index (FMI), based on skinfold measurements. Dietary intake was estimated via 24h recall. Associations between intakes of protein as well as arginine, lysine and change in FFMI and FMI were analysed by multiple linear regressions, adjusted for social economic status, puberty stage and physical activity level. Among lean girls inverse associations were found between protein as well as arginine and lysine intake and change in fat mass index (beta=-1.12+/-0.56, p=0.03, beta=-1.10+/-0.53, p=0.04, beta=-1.13+/-0.51, p=0.03 respectively). Furthermore among girls with a body mass index in the 5th quintile, protein intake was associated with DeltaFFMI (p=0.04), and more specific when LYS intake was high, ARG intake was associated with DeltaFFMI (p=0.04). Among girls high protein intakes may decrease body fat gain and increase fat free mass gain, depending on the available amounts and combinations of arginine and lysine.

Patterns of Growth Associated With the Timing of Adiposity Rebound

This study was undertaken to evaluate the effects of age of adiposity rebound (AR) on measures of fat mass between ages 7 and 11 years, maturity, and adiposity in 458 children from a birth cohort studied to age 26 years. Patterns of growth between ages 3 and 26 years and changes in fat mass index between 7 and 11 years in groups with early (<5.5 years for boys and <5 years for girls), average (between 5.5 and 7.5 years for boys and between 5 and 7 years for girls), and late AR (> or =7.5 years for boys and > or =7 years for girls) are described. The mean z-scores for BMI, height, and weight increased between age 3 years and adolescence in the early-rebound group and decreased in the late-rebound group. The differences were maintained until adulthood for BMI and weight. Disproportionately high increases in fat mass index during growth (7-11 years), more advanced bone age in boys at age 7 years, and earlier menarche in girls were evident in the early-rebound group. The relative risks at 26 years of being overweight (BMI 25-29.9 kg/m(2)) and obese (BMI > or =30 kg/m(2)) were 2.70 (95% confidence interval (CI): 1.55, 4.66) and 5.91 (95% CI: 3.03, 11.55) respectively, using the average group as the reference. The corresponding relative risks for adult waist girths exceeding international cut points were 2.12 (95% CI: 1.09, 4.13) and 3.32 (95% CI: 1.46, 7.54). Thus, early rebound is associated with increased depositions of fat in middle childhood, and risks associated with early rebound persist at least until early adulthood.

Energy density of the diet and change in body fatness from childhood to adolescence; is there a relation?

BackgroundThe contribution of energy density (ED) of the total diet to increased risk of obesity from childhood into adolescence is unclear. ObjectiveWe assessed the relation between the ED of the diet in childhood, calculated in a number of ways, and change in adiposity from childhood to adolescence. DesignIn a prospective study, 48 children (30 boys, 18 girls) were initially studied at age 6–8 y (baseline) and followed up at age 13–17 y. Daily ED, energy intake, and food intake were assessed at baseline by 7-d weighed food records concurrent with estimates of total energy expenditure (TEE) by doubly labeled water. ED was calculated with the use of 5 published methods. Obesity risk was defined with the use of body fat from total body water by isotope dilution. Body fat was normalized for height and expressed as fat mass index (FMI). Change in adiposity was calculated as follow-up FMI minus baseline FMI. ResultsMisreporting of energy intake at the group level at baseline was low relative to the TEE. ED of the total diet at baseline by the 3 methods for calculating ED that excluded all or most beverages was prospectively associated with change in FMI. However, ED of the total diet by any of the methods was not associated with change in the percentage body fat, body mass index, or waist circumference z scores. ConclusionThe methods used to calculate ED and to assess obesity risk lead to different conclusions about the relation between the ED of the diet in childhood and gain in fat into adolescence.