The variations of body mass index and body fat in adult Thai people across the age spectrum measured by bioelectrical impedance analysis.
ABSTRACT: BACKGROUND: The measurements of body mass index (BMI) and percentage of body fat are used in many clinical situations. However, special tools are required to measure body fat. Many formulas are proposed for estimation but these use constant coefficients of age. Age spectrum might affect the predicted value of the body composition due to body component alterations, and the coefficient of age for body fat prediction might produce inconsistent results. The objective of this study was to identify variations of BMI and body fat across the age spectrum as well as compare results between BMI predicted body fat and bioelectrical impedance results on age. METHODS: Healthy volunteers were recruited for this study. Body fat was measured by bioelectrical impedance. The age spectrum was divided into three groups (younger: 18-39.9; middle: 40-59.9; and older: ≥60 years). Comparison of body composition covariates including fat mass (FM), fat free mass (FFM), percentage FM (PFM), percentage FFM (PFFM), FM index (FMI) and FFM index (FFMI) in each weight status and age spectrum were analyzed. Multivariable linear regression coefficients were calculated. Coefficient alterations among age groups were tested to confirm the effect of the age spectrum on body composition covariates. Measured PFM and calculated PFM from previous formulas were compared in each quarter of the age spectrum. RESULTS: A total of 2324 volunteers were included in this study. The overall body composition and weight status, average body weight, height, BMI, FM, FFM, and its derivatives were significantly different among age groups. The coefficient of age altered the PFM differently between younger, middle, and older groups (0.07; P = 0.02 vs 0.13; P < 0.01 vs 0.26; P < 0.01; respectively). All coefficients of age alterations in all FM- and FFM-derived variables between each age spectrum were tested, demonstrating a significant difference between the younger (<60 years) and older (≥60 years) age groups, except the PFFM to BMI ratio (difference of PFM and FMI [95% confidence interval]: 17.8 [12.8-22.8], P < 0.01; and 4.58 [3.4-5.8], P < 0.01; respectively). The comparison between measured PFM and calculated PFM demonstrated a significant difference with increments of age. CONCLUSION: The relationship between body FM and BMI varies on the age spectrum. A calculated formula in older people might be distorted with the utilization of constant coefficients.
Project description:BACKGROUND/OBJECTIVES:To develop age- and sex-specific centile reference curves for fat-free mass (FFM) and fat mass (FM) adjusted for height in an adult Kenyan population and to investigate the association between FM, FFM and blood pressure (BP). SUBJECTS/METHODS:Measures of body composition from bioimpedance analyses and BP were collected in 1995 participants aged ?50 years in Nakuru County, Kenya. Reference curves were produced using the LMS method. Multivariable linear regression models were used to test the cross-sectional association between body composition indexes and BP. RESULTS:The age- and sex-specific reference curves for body composition (FMI and FFMI) confirmed that FFMI is lower in both men and women with increasing age. FMI declines with age in women while among men the decline starts after 70 years. FFM was higher in men (47.4?±?7.2?kg) than in women (38.8?±?5.5?kg), while FM was lower in men (17.3?±?8.1?kg) than in women (24.4?±?10.2?kg). FMI, FFMI and BMI were all positively associated with systolic and diastolic BP, and after adjusting for body weight, FFMI remained positively associated with systolic BP and the FMI remained positively associated with diastolic BP. There was no evidence to suggest that FMI and FFMI were superior to measurement of BMI alone. CONCLUSIONS:These body composition reference curves provide normative data on body composition for older adults in Kenya. Further research should consider the prospective associations with health, including frailty-related outcomes.
Project description:Favourable body composition has been associated with higher dietary protein intake. However, little is known regarding this relationship in a population of Chinese Americans (CHA), who have lower BMI compared with other populations. The aim of the present study was to assess the relationship between dietary protein intake, fat mass (FM) and fat-free mass (FFM) in CHA. Data were from the Chinese American Cardiovascular Health Assessment (CHA CHA) 2010-2011 (n 1707); dietary intake was assessed using an adapted and validated FFQ. Body composition was assessed using bioelectrical impedance analysis. The associations between protein intake (% energy intake) and BMI, percentage FM (FM%), percentage FFM (FFM%), FM index (FMI) and FFM index (FFMI) were examined using multiple linear regression adjusted for age, sex, physical activity, acculturation, total energy intake, sedentary time, smoking status, education, employment and income. There was a significant positive association between dietary protein and BMI (B = 0·056, 95 % CI 0·017, 0·104; P = 0·005), FM (B = 0·106, 95 % CI 0·029, 0·184; P = 0·007), FM% (B = 0·112, 95 % CI 0·031, 0·194; P = 0·007) and FMI (B = 0·045, 95 % CI 0·016, 0·073; P = 0·002). There was a significant negative association between dietary protein and FFM% (B = -0·116, 95 % CI -0·196, -0·036; P = 0·004). In conclusion, higher dietary protein intake was associated with higher adiposity; however, absolute FFM and FFMI were not associated with dietary protein intake. Future work examining the relationship between protein source (i.e. animal) and body composition is warranted in this population of CHA.
Project description:<h4>Background</h4>Obesity is known to be related to the development of type 2 diabetes mellitus (T2D). The most commonly used anthropometric indicator (body mass index [BMI]) presents several limitations such as the lack of possibility to distinguish adipose tissue distribution. Thus, this study examines the suitability of a body shape index (ABSI) for prediction of body composition and sarcopenic obesity in obese or overweight T2D subjects.<h4>Methods</h4>Cross-sectional study in 199 overweight/obese T2D adults. Anthropometric (BMI, ABSI) and body composition (fat mass [FM], fat-free mass [FFM], fat mass index [FMI] and fat-free mass index, and the ratio FM/FFM as an index of sarcopenic obesity) data was collected, as well as metabolic parameters (glycated haemoglobin [HbA<sub>1c</sub>], mean blood glucose, fasting plasma glucose [FPG], high-density-lipoprotein cholesterol [HDL], low-density-lipoprotein cholesterol, total cholesterol, and triglycerides [TG] levels; the ratio TG/HDL was also calculated as a surrogate marker for insulin resistance).<h4>Results</h4>ABSI was significantly associated with age and waist circumference. It showed a statistically significant correlation with BMI exclusively in women. Regarding body composition, in men, ABSI was associated with FM (%), while in women it was associated with both FM and FFM. Both males and females groups with high ABSI scores were significantly older (men: 59.3?±?10.8 vs 54.6?±?10.1, p???0.05; women: 65.1?±?9.8 vs 58.1?±?13.3, p???0.005) and showed lower FFM values (men: 62.3?±?9.0 vs 66.2?±?9.3, p???0.05; women: 48.7?±?5.6 vs 54.5?±?8.9, p???0.001) compared with low-ABSI groups. Multiple linear regression revealed that ABSI independently predict FMI and the FM/FFM ratio in women. Sarcopenic obesity was identified in 70 (36.5%) individuals according to the FM/FFM ratio. The AUROC of ABSI was 63.1% (95% CI 54.6-71.6%; p?=?0.003) and an ABSI value of 0.083 m<sup>11/6</sup> kg<sup>-2/3</sup> was the optimal threshold in discriminating patients with sarcopenic obesity (sensitivity: 48%, specificity: 73%). Moreover, a significant association between ABSI and FPG was found in men.<h4>Conclusions</h4>ABSI could be useful to identify visceral and sarcopenic obesity in overweight/obese adults with T2D, adding some relevant clinical information to traditional anthropometric measures.
Project description:To determine age- and sex-specific body composition reference values and investigate age differences in these parameters for community-dwelling older Japanese men and women, using direct segmental multi-frequency bioelectrical impedance analysis.We conducted a pooled analysis of data collected in four cohort studies between 2008 and 2012: Kusatsu Longitudinal Study, Hatoyama Cohort Study, Itabashi Cohort Study, and Kashiwa Cohort Study. The pooled analysis included cross-sectional data from 4478 nondisabled, community-dwelling adults aged 65-94 years (2145 men, 2333 women; mean age: 72.9 years in men and 72.6 years in women). Body weight, fat mass (FM), percentage FM, fat-free mass (FFM), and appendicular lean soft tissue mass were measured using the InBody 720 and 430 (Biospace Co. Ltd, Seoul, Korea). The values were then normalized by height in meters squared to determine body mass index (BMI), FM index (FMI), FFM index (FFMI), and skeletal muscle mass index (SMI).Simple means (standard deviation) of BMI, percentage FM, FMI, FFMI, and SMI were 23.4 (2.9) kg/m(2), 24.9 (6.3)%, 5.96 (2.09) kg/m(2), 17.4 (1.5) kg/m(2), and 7.29 (0.76) kg/m(2), respectively, in men and 22.7 (3.3) kg/m(2), 31.7 (7.1)%, 7.40 (2.61) kg/m(2), 15.3 (1.2) kg/m(2), and 5.86 (0.67) kg/m(2), respectively, in women. We then calculated quartiles and quintiles for these indices after stratifying for sex and 5-year age group. FFMI and SMI decreased significantly with age in both sexes (P < 0.001 for trends), but FFMI remained constant among the women with only a 1% decrease up to age 84 years. Percentage FM increased significantly, with age (P < 0.001 in men and P = 0.045 in women for trends), but FMI was unchanged in both sexes (P = 0.147 in men and P = 0.176 in women for trends).The present data should be useful in the clinical evaluation of body composition of older Japanese and for international comparisons. The small age-related decrease in FFMI may be a noteworthy characteristic of body composition change in older Japanese women.
Project description:<h4>Background/objectives</h4>Low and high birth weight and rapid weight gain during infancy are associated with childhood obesity. Associations of birth and infancy body composition (BC) growth with childhood BC remain unknown in low-income countries. We aimed to investigate the associations of fat mass (FM) and fat-free mass (FFM) at birth and its accretion during early infancy with FM and FFM at the age of 4 years.<h4>Methods</h4>In the infant Anthropometry and Body Composition (iABC) cohort, BC was assessed at six consecutive time points from birth to 6 months and at 4 years of age by air displacement plethysmography. Multiple linear regression models were used to determine the association between FM and FFM at birth and their accretion rates during infancy and FM index (FMI) and FFM index (FFMI) at 4 years in 314 children.<h4>Results</h4>One kilogram higher FFM at birth was associated with a 1.07?kg/m<sup>2</sup> higher FFMI (95% CI 0.60, 1.55) at 4 years while a one SD increment in FFM accretion rate from 0 to 6 months was associated with a 0.24?kg/m<sup>2</sup> increment in FFMI (95% CI 0.11, 0.36) and with a 0.20?kg/m<sup>2</sup> higher FMI at 4 years (??=?0.20; 95% CI 0.04, 0.37). FFM at birth did not predict FMI at 4 years. FM at birth was associated with 1.17?kg/m<sup>2</sup> higher FMI at 4 years (95% CI 0.13, 2.22) whereas FM accretion from 0 to 4 months was associated with an increase in FMI of 0.30?kg/m<sup>2</sup> (95% CI 0.12, 0.47). FM at birth did not predict FFMI at 4 years, and neither did FM accretion from 0 to 4 months.<h4>Conclusions</h4>A higher FFM in early infancy predicted higher FFMI at 4 years while a higher FM accretion during early infancy predicted higher FMI at 4 years. Follow-up studies are merited to explore associations of childhood BC with cardio-metabolic risk later in life.
Project description:BACKGROUND:Obesity is the result of chronic positive energy balance. The mechanisms underlying the regulation of energy homeostasis and food intake are not understood. Despite large increases in fat mass (FM), recent evidence indicates that fat-free mass (FFM) rather than FM is positively associated with intake in humans. METHODS:In 184 humans (73 females/111 males; age 34.5±8.8 years; percentage body fat: 31.6±8.1%), we investigated the relationship of FFM index (FFMI, kg?m(-2)), FM index (FMI, kg?m(-2)); and 24-h energy expenditure (EE, n=127) with ad-libitum food intake using a 3-day vending machine paradigm. Mean daily calories (CAL) and macronutrient intake (PRO, CHO, FAT) were determined and used to calculate the relative caloric contribution of each (%PRO, %CHO, %FAT) and percent of caloric intake over weight maintaining energy needs (%WMENs). RESULTS:FFMI was positively associated with CAL (P<0.0001), PRO (P=0.0001), CHO (P=0.0075) and FAT (P<0.0001). This remained significant after adjusting for FMI. Total EE predicted CAL and macronutrient intake (all P<0.0001). FMI was positively associated with CAL (P=0.019), PRO (P=0.025) and FAT (P=0.0008). In models with both FFMI and FMI, FMI was negatively associated with CAL (P=0.019) and PRO (P=0.033). Both FFMI and FMI were negatively associated with %CHO and positively associated with %FAT (all P<0.001). EE and FFMI (adjusted for FMI) were positively (EE P=0.0085; FFMI P=0.0018) and FMI negatively (P=0.0018; adjusted for FFMI) associated with %WMEN. CONCLUSION:Food and macronutrient intake are predicted by FFMI and to a lesser degree by FMI. FFM and FM may have opposing effects on energy homeostasis.
Project description:Aging, body composition, and body mass index (BMI) are important factors in bone mineral density (BMD). Although several studies have investigated the various parameters and factors that differentially influence BMD, the results have been inconsistent. Thus, the primary goal of the present study was to further characterize the relationships of aging, body composition parameters, and BMI with BMD in Chinese Han males older than 50 years.The present study was a retrospective analysis of the body composition, BMI, and BMD of 358 Chinese male outpatients between 50 and 89 years of age that were recruited from our hospital between 2009 and 2011. Qualified subjects were stratified according to age and BMI as follows: 50-59 (n = 35), 60-69 (n = 123), 70-79 (n = 93), and 80-89 (n = 107) years of age and low weight (BMI: < 20 kg/m2; n = 21), medium weight (20 ? BMI < 24 kg/m2; n = 118), overweight (24 ? BMI < 28 kg/m2; n = 178), and obese (BMI ? 28 kg/m2; n = 41). Dual-energy X-ray absorptiometry (DEXA) was used to assess bone mineral content (BMC), lean mass (LM), fat mass (FM), fat-free mass (FFM), lumbar spine (L1-L4) BMD, femoral neck BMD, and total hip BMD. Additionally, the FM index (FMI; FM/height2), LM index (LMI; LM/height2), FFM index (FFMI; [BMC+LM]/height2), percentage of BMC (%BMC; BMC/[BMC+FM+LM] × 100%), percentage of FM (%FM; FM/[BMC+FM+LM] × 100%), and percentage of LM (%LM; LM/(BMC+FM+LM) × 100%) were calculated. Osteopenia or osteoporosis was identified using the criteria and T-score of the World Health Organization.Although there were no significant differences in BMI among the age groups, there was a significant decline in height and weight according to age (p < 0.0001 and p = 0.0002, respectively). The LMI and FFMI also declined with age (both p < 0.0001) whereas the FMI exhibited a significant increase that peaked in the 80-89-years group (p = 0.0145). Although the absolute values of BMC and LM declined with age (p = 0.0031 and p < 0.0001, respectively), there was no significant difference in FM. In terms of body composition, there were no significant differences in %BMC but there was an increase in %FM (p < 0.0001) and a decrease in %LM (p < 0.0001) with age. The femoral neck and total hip BMD significantly declined with age (p < 0.0001 and p = 0.0027, respectively) but there were no differences in L1-L4. BMD increased at all sites (all p < 0.01) as BMI increased but there were declines in the detection rates of osteoporosis and osteopenia (both p < 0.001). A logistic regression revealed that when the medium weight group was given a BMI value of 1, a decline in BMI was an independent risk factor of osteoporosis or osteopenia, while an increase in BMI was a protective factor for BMD. At the same time, BMD in L1-L4 exhibited a significant positive association with FMI (p = 0.0003) and the femoral neck and total hip BMDs had significant positive associations with FFMI and LMI, respectively (both p < 0.0001).These data indicate that LMI and FFMI exhibited significant negative associations with aging in Chinese Han males older than 50 years, whereas FMI had a positive association. BMD in the femoral neck and total hip declined with age but an increased BMI was protective for BMD. LMI and FFMI were protective for BMD in the femoral neck and total hip.
Project description:BackgroundWe aimed to describe newborn body composition and identify which anthropometric ratio (weight/length; BMI; or ponderal index, PI) best predicts fat mass (FM) and fat-free mass (FFM).MethodsAir-displacement plethysmography (PEA POD) was used to estimate FM, FFM, and body fat percentage (BF%). Associations between FFM, FM, and BF% and weight/length, BMI, and PI were evaluated in 1,019 newborns using multivariate regression analysis. Charts for FM, FFM, and BF% were generated using a prescriptive subsample (n=247). Standards for the best-predicting anthropometric ratio were calculated utilizing the same population used for the INTERGROWTH-21st Newborn Size Standards (n=20,479).ResultsFFM and FM increased consistently during late pregnancy. Differential FM, BF%, and FFM patterns were observed for those born preterm (34+0-36+6 weeks' gestation) and with impaired intrauterine growth. Weight/length by gestational age (GA) was a better predictor of FFM and FM (adjusted R2=0.92 and 0.71, respectively) than BMI or PI, independent of sex, GA, and timing of measurement. Results were almost identical when only preterm newborns were studied. We present sex-specific centiles for weight/length ratio for GA.ConclusionsWeight/length best predicts newborn FFM and FM. There are differential FM, FFM, and BF% patterns by sex, GA, and size at birth.
Project description:Breastfeeding has been implicated in the establishment of infant appetite regulation, feeding patterns and body composition (BC). A holistic approach is required to elucidate relationships between infant and maternal BC and contributing factors, such as breastfeeding parameters. Associations between maternal and breastfed term infant BC (n = 20) and feeding parameters during first 12 months of lactation were investigated. BC was measured at 2, 5, 9 and/or 12 months postpartum with ultrasound skinfolds (US; infants only) and bioimpedance spectroscopy (infants and mothers). 24-h milk intake (MI) and feeding frequency (FFQ) were measured. Higher FFQ was associated with larger 24-h MI (p ? 0.003). Higher 24-h MI was associated with larger infant fat mass (FM) (US: p ? 0.002), greater percentage FM (US: p ? 0.008), greater FM index (FMI) (US: p ? 0.001) and lower fat-free mass index (FFMI) (US: p = 0.015). Lower FFQ was associated with both larger FFM (US: p ? 0.001) and FFMI (US: p < 0.001). Greater maternal adiposity was associated with smaller infant FFM measured with US (BMI: p < 0.010; %FM: p = 0.004; FMI: p < 0.011). Maternal BC was not associated with FFQ or 24-h MI. These results reinforce that early life is a critical window for infant programming and that breastfeeding may influence risk of later disease via modulation of BC.
Project description:<h4>Background</h4>Chronic kidney disease (CKD) is characterized by accelerated aging, but the age-related changes in body composition and its modification by sex and race are unclear.<h4>Methods</h4>We assembled a cohort of 516 patients with CKD and 45 healthy controls and serially measured body composition using air-displacement plethysmography for up to 6?years. Mixed models were used to evaluate simultaneously the baseline and longitudinal changes in body composition as influenced by age, sex and race.<h4>Results</h4>Compared with healthy controls, patients with CKD had a greater weight, body mass index (BMI), fat mass (FM) and percent body fat (BF%), but the changes over time in body composition were similar. Older age (>60?years) was a strong determinant of loss of weight, BMI, FM and fat-free mass (FFM), but not BF%. Compared with non-blacks, blacks had a higher FFM at baseline, but they lost FFM more rapidly. Compared with women, men had an accelerated loss of FFM and accumulation of FM. Taking interactions into account, we found that young black men had no significant change in weight due to the loss of FFM and the accumulation of FM, thereby masking obesity by conventional measurements.<h4>Conclusion</h4>Among patients with CKD, the changes in body composition are influenced by age, sex and race. Young black men have changes in body composition that may remain undetectable by conventional methods thus masking the occurrence of obesity.