Association between body mass index and body fat in 9-11-year-old children from countries spanning a range of human development.
Ontology highlight
ABSTRACT:
SUBMITTER: Katzmarzyk PT
PROVIDER: S-EPMC4850619 | biostudies-other | 2015 Dec
REPOSITORIES: biostudies-other
Similar Datasets
Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.
| S-EPMC7808627 | biostudies-literature
Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.
| S-EPMC5710345 | biostudies-literature
Project description:BACKGROUND:Phthalates are hypothesized to cause obesity, but few studies have assessed whether prenatal phthalate exposures are related to childhood body mass index (BMI). METHODS:We included 707 children from three prospective cohort studies enrolled in the US between 1998 and 2006 who had maternal urinary phthalate metabolite concentrations measured during pregnancy, and measures of weight and height at ages 4 to 7 years. We calculated age- and sex-standardized BMI z scores and classified children with BMI percentiles ?85 as overweight/obese. We used mixed effects regression models to estimate associations between a 1 standard deviation increase in natural log phthalate metabolite concentrations and BMI z scores and overweight/obesity. We estimated associations in multiple metabolite models adjusted for confounders, and evaluated heterogeneity of associations by child's sex, race/ethnicity, and cohort. RESULTS:Mono-3-carboxypropyl phthalate concentrations were positively associated with overweight/obese status in children (odds ratio [95% credible interval] = 2.1 [1.2, 4.0]) but not with BMI z scores (? = -0.02 [-0.15, 0.11]). We did not observe evidence of obesogenic effects for other metabolites. However, monoethyl phthalate and summed di-(2-ethylhexyl) phthalate metabolites (?DEHP) concentrations were inversely associated with BMI z scores among girls (monoethyl phthalate beta = -0.14 [-0.28, 0.00]; ?DEHP beta = -0.12 [-0.27, 0.02]). CONCLUSIONS:Maternal urinary mono-3-carboxypropyl phthalate, a nonspecific metabolite of several phthalates, was positively associated with childhood overweight/obesity. Metabolites of diethyl phthalate and DEHP were associated with lower BMI in girls but not in boys, suggesting that prenatal exposures may have sexually dimorphic effects on physical development.
| S-EPMC4821741 | biostudies-literature
Project description:ObjectivesAging, 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.MethodsThe 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.ResultsAlthough 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).ConclusionsThese 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.
| S-EPMC4475062 | biostudies-literature
Project description:BackgroundThe association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor.Methodology/principal findingsWC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R(2)) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m(2) and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different.Conclusion/significanceThe prediction of IAFM by WC is not improved by addition of BMI.
| S-EPMC3286444 | biostudies-literature
Project description:For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height(2)/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2-4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity.
| S-EPMC3902432 | biostudies-other
Project description:BackgroundObesity is pathophysiologically complex in older adults compared to that in young and middle-aged adults. The aim of the present study was to determine the appropriate body mass index (BMI) range based on geriatric evaluation parameters in which complications can be minimized in older adults.MethodsA total of 1,051 older adult patients who underwent comprehensive geriatric assessment were included. The patients' demographic characteristics, comorbid diseases, number of drugs, BMI, basic and instrumental activities of daily living (BADL and IADL), Tinetti balance and walking scale, Mini Nutritional Assessment, Geriatric Depression Scale-15, Mini-Mental State Examination, Time Up and Go test, and handgrip strength measurement were extracted from patient records.ResultsOf the patients who took part, 73% were female, and the mean age was 77.22±7.10 years. The most negative results were observed in those with a BMI <25 kg/m2 and in those with a BMI >35 kg/m2. Receiver operating characteristic (ROC) analysis of the optimum BMI cutoff levels to detect the desirable values of geriatric assessment parameters was found to be 31-32 and 27-28 kg/m2 for female and male, respectively.ConclusionOlder adults with BMI <25 and >35 kg/m2 were at a higher risk of a decrease in functional capacity, and experienced gait and balance problems, fall risk, decrease in muscle strength, and malnutrition. Data from this study suggest that the optimum range of BMI levels for older adults is 31-32 and 27-28 kg/m2 for female and male, respectively.
| S-EPMC8984168 | biostudies-literature
Project description:Overt parental restriction of food has previously been associated with child weight; however, most research has relied on self-reported feeding behaviour, or observations which give little opportunity to observe restriction of food. Using a novel lab-based observational technique to increase the opportunity to observe maternal feeding restriction, we explored the relationships between maternal restriction, child responses to restriction and child temperament with child body mass index (BMI) Z-scores over time. Sixty-two mother child dyads were recruited to the study when their children were aged 3⁻5 years and were followed up 2 years later (N = 39 dyads). Families were observed during a feeding interaction in the laboratory where cookies were offered with the main meal to increase the opportunity for maternal restriction of food. Feeding observations were coded and child temperament and BMI were measured. Controlling for current child BMI Z-scores, greater maternal verbal and physical restriction of food at 3⁻5 years was related to higher child BMI Z-scores at 5⁻7 years. More emotional children were less likely to experience restriction and less likely to accept attempts to restrict their food intake. Further research should consider children’s reactions to parental feeding behaviours in greater depth and explore how feeding practices interact with child temperament in the prediction of changes in child weight.
| S-EPMC6025183 | biostudies-literature
Project description:ObjectiveThis population-based study aimed (1) to test the presence of an association between regular voluntary exercise behaviour (EB) that is performed in leisure time and body mass index (BMI) in youth and (2) to investigate the causal nature of this association using a longitudinal design in genetically informative subjects.Design and methodsBoth EB and BMI were assessed repeatedly over time in 21 458 twin individuals from the Netherlands Twin Register (47.5% male) - first by parental report (ages 7, 10 and 12) and subsequently through self-report surveys (ages 14, 16 and 18). EB was quantified as weekly metabolic equivalent of task hours.ResultsCorrelations over time were higher for BMI than for EB (r ≈ 0.70 vs. r ≈ 0.35) across 12 different follow-up periods. Cross-sectionally, regular involvement in EB was not associated with lower BMI in childhood and in genetically identical twin pairs discordant for EB; the exercising twin did not have a lower BMI than the non-exercising twin. Longitudinally, linear and quadratic relationships between EB and BMI were non-significant. Changes in EB over time did not induce opposite changes in BMI.ConclusionsNo consistent association between regular EB and BMI was observed from ages 7 to 18 years.
| S-EPMC5523672 | biostudies-literature
Project description:Background: Excess adiposity is one of the main risk factors for the development of cardiovascular and metabolic diseases. The purpose of this study is to compare cardiometabolic risk factors in eutrophic adolescents with a high body fat percentage (%BF) with eutrophic adolescents with adequate %BF and those with excess weight and %BF. Methods: Cross-sectional study with 1043 adolescents. This study presented power equal to 99.75%. Body fat and anthropometric, clinical and biochemical indicators were evaluated. Participants were grouped according to body composition classified by body mass index (BMI) and body fat percentage. Statistical analyses were performed using R software version 4.0.2, adopting a significance level of 5%. The Mann–Whitney test, principal components analysis and logistic regression were performed. Results: It was observed that the SG was more similar to GC2 than to GC1 for both sexes, demonstrating that there was a greater similarity between these groups in relation to the evaluated factors. Higher values for TC, SBP and TG were associated with the SG when the CG1 was used as reference, controlled for sex and age. Likewise, higher TC values and lower levels of SBP, TG and LDL were related to SG when the CG2 was used as reference. Conclusion: Body fat assessment is more effective in predicting risk factors and cardiometabolic diseases than BMI alone.
| S-EPMC9915438 | biostudies-literature