The Application of Fat-Free Mass Index for Survival Prediction in Cancer Patients With Normal and High Body Mass Index.
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ABSTRACT:
SUBMITTER: Zhang X
PROVIDER: S-EPMC8371389 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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:AIMS:Central adiposity is associated with increased cardiovascular disease (CVD) risk, even among people with normal body mass index (BMI). We tested the hypothesis that regional body fat deposits (trunk or leg fat) are associated with altered risk of CVD among postmenopausal women with normal BMI. METHODS AND RESULTS:We included 2683 postmenopausal women with normal BMI (18.5 to <25?kg/m2) who participated in the Women's Health Initiative and had no known CVD at baseline. Body composition was determined by dual energy X-ray absorptiometry. Incident CVD events including coronary heart disease and stroke were ascertained through February 2017. During a median 17.9?years of follow-up, 291 incident CVD cases occurred. After adjustment for demographic, lifestyle, and clinical risk factors, neither whole-body fat mass nor fat percentage was associated with CVD risk. Higher percent trunk fat was associated with increased risk of CVD [highest vs. lowest quartile hazard ratio (HR) = 1.91, 95% confidence interval (CI) 1.33-2.74; P-trend <0.001], whereas higher percent leg fat was associated with decreased risk of CVD (highest vs. lowest quartile HR = 0.62, 95% CI 0.43-0.89; P-trend = 0.008). The association for trunk fat was attenuated yet remained significant after further adjustment for waist circumference or waist-to-hip ratio. Higher percent trunk fat combined with lower percent leg fat was associated with particularly high risk of CVD (HR comparing extreme groups = 3.33, 95% CI 1.46-7.62). CONCLUSION:Among postmenopausal women with normal BMI, both elevated trunk fat and reduced leg fat are associated with increased risk of CVD.
| S-EPMC6933870 | biostudies-literature
Project description:Background/objectivesWe aimed to investigate the association of waist circumference (WC) with body composition among individuals with a normal body mass index (BMI) to distinguish muscle and fat mass, as both affect health differently.Subjects/methodsWe analyzed dual-energy X-ray absorptiometry data (derived from the Korean National Health and Nutrition Survey, which includes information on fat and lean mass) of 7,493 adults with a normal BMI. Subjects were categorized into four groups of increasing WC. The fourth group was defined as being centrally obese. Each number of subjects are as follows: 1,870, 695, 231, and 39 among men and 3,054, 1,100, 406, and 98 among women. We conducted a sex-stratified linear regression analysis of body composition according to WC group after adjustments for covariates.ResultsWe observed a positive association of body fat with increasing WC in both men and women (all P for trend: < 0.001). The adjusted mean values for percent body fat with 95% confidence intervals (CIs) according to the four WC groups in ascending order were 17.8 (17.5-18.3), 21.0 (20.6-21.5), 22.1 (21.5-22.8), and 25.1 (24.2-26.1) in men and 29.7 (29.4-30.0), 32.0 (31.6-32.3), 32.9 (32.4-33.4), and 34.7 (33.2-36.1) in women. However, there was an inverted J-shaped association between muscle mass and WC. The fourth group had a higher percent body fat and lower muscle mass than other groups. The adjusted mean values for appendicular skeletal muscle mass index (kg/m2) with 95% CIs according to the four WC groups in ascending order were 7.55 (7.51-7.59), 7.62 (7.56-7.68), 7.65 (7.56-7.74), and 7.22 (7.04-7.41) in men and 5.83 (5.80-5.85), 5.96 (5.92-6.00), 6.03 (5.96-6.10), and 5.88 (5.73-6.03).ConclusionsThere was a positive association between body fat and WC among individuals with normal BMI; conversely there was an inverted J-shaped association between lean body mass and WC. Our findings support the WC measurement should be included in obesity evaluations for adults with a normal BMI.
| S-EPMC8446684 | biostudies-literature
Project description:With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.
| S-EPMC5287118 | 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:BackgroundOur study evaluated the association between body mass index (BMI) and absolute lymphocyte count (ALC) in breast cancer patients and healthy females. Additionally, we determined the prognostic value of these factors in breast cancer.MethodsWe retrospectively identified 1225 primary invasive breast cancer patients and 35,991 healthy females. Factors including BMI and complete blood count associated with disease-free survival (DFS) were assessed using a multi-variable Cox proportional hazard model.ResultsBMI and ALC were positively correlated in breast cancer patients and healthy females (both P < 0.001). In multi-variable analysis, overweight or obese participants had worse DFS (hazards ratio [HR], 1.98; 95% confidence interval [CI], 1.34-2.92; P = 0.001) than underweight or normal-weight individuals, but patients with high ALC had better DFS than those with low ALC (HR, 0.43; 95% CI, 0.29-0.65; P < 0.001). After risk stratification according to BMI/ALC, high-risk patients with high BMI/low ALC had worse DFS than others (HR, 2.48; 95% CI, 1.70-3.62; P < 0.001).ConclusionsBMI and ALC were positive correlated, but their effect on breast cancer prognosis was opposite. Patients with high BMI/low ALC had worse DFS than others. Underlying mechanisms for effect of BMI/ALC on breast cancer prognosis should be studied in the future.
| S-EPMC8257741 | biostudies-literature
Project description:Weight loss in overweight or obese individuals with Type 2 diabetes (T2D) can normalize hepatic fat metabolism, decrease fatty acid oversupply to β cells and restore normoglycaemia. One in six people has BMI <27 kg/m2 at diagnosis, and their T2D is assumed to have different aetiology. The Personal Fat Threshold hypothesis postulated differing individual thresholds for lipid overspill and adverse effects on β-cell function. To test this hypothesis, people with Type 2 diabetes and body mass index <27kg/m2 (n = 20) underwent repeated 5% weight loss cycles. Metabolic assessments were carried out at stable weight after each cycle and after 12 months. To determine how closely metabolic features returned to normal, 20 matched normoglycemic controls were studied once. Between baseline and 12 months: BMI fell (mean ± SD), 24.8 ± 0.4 to 22.5 ± 0.4 kg/m2 (P<0.0001) (controls: 21.5 ± 0.5); total body fat, 32.1 ± 1.5 to 27.6 ± 1.8% (P<0.0001) (24.6 ± 1.5). Liver fat content and fat export fell to normal as did fasting plasma insulin. Post-meal insulin secretion increased but remained subnormal. Sustained diabetes remission (HbA1c < 48 mmol/mol off all glucose-lowering agents) was achieved by 70% (14/20) by initial weight loss of 6.5 (5.5-10.2)%. Correction of concealed excess intra-hepatic fat reduced hepatic fat export, with recovery of β-cell function, glycaemic improvement in all and return to a non-diabetic metabolic state in the majority of this group with BMI <27 kg/m2 as previously demonstrated for overweight or obese groups. The data confirm the Personal Fat Threshold hypothesis: aetiology of Type 2 diabetes does not depend on BMI. This pathophysiological insight has major implications for management.
| S-EPMC10472166 | biostudies-literature
Project description:ObjectiveHigh-dose glucocorticoids (GC) remain the primary therapy to induce remission in Juvenile Dermatomyositis (JDM). Studies of the natural history of GC associated weight gain in children are very limited, especially in the JDM population. This study aims to measure BMI changes in a cohort of JDM subjects over 60 months and to examine the changes in body composition by DXA.MethodsWe included all subjects with JDM who had 5 years of follow-up data and multiple DXA studies. BMI and total body fat (TBF) percentiles were calculated based on the CDC published percentile charts. To study the natural history of weight gain and TBF, we assessed the data at four-time points (T0 = baseline, T1 > 1.5 years, T2 = 1.51-3.49 years, T3 = 3.5-5 years).Results68 subjects (78% female, 70% white) were included in this retrospective study. Paired T-test showed a significant increase in the mean BMI percentile by 17.5 points (P = 0.004) after the initiation of medical treatment, followed by a gradual decrease over the study period. However, the TBF percentile did not change over the study period. TBF in the last visit (T3) had a strong correlation with the T1 BMI, and T1 TBF percentile (correlation coefficients 0.63, 0.56 P < 0.001, 0.002 respectively). Also, there was a positive correlation (correlation coefficients 0.39, P = 0.002) between the TBF percentile and muscle DAS but not the skin DAS.ConclusionsAlthough the BMI percentile decreased throughout the study, the TBF percentile remained high until the end of the study (60 months). This finding raises the concern that some of the reduction in the BMI percentile could reflect a drop in the lean body mass from muscle wasting rather than actual fat loss.
| S-EPMC8353815 | biostudies-literature
Project description:It is unclear whether there are different body mass index (BMI) trajectories among a population with normal BMI levels, and the association between BMI patterns and incident hypertension is not well characterized. This prospective cohort study includes surveys conducted at baseline and three follow-ups. 3939 participants who are free of hypertension at baseline or first two follow-ups were enrolled. At baseline, the age of participants ranged from 35 to 82 years and the mean age was 45.9 years. The BMI trajectories were identified using latent mixture modeling with data from the baseline and first two follow-ups. The effects of different BMI trajectories on the development of hypertension were analyzed using a Cox proportional hazard model. Four distinct BMI trajectories were identified over the study period (2004-2010): normal-stable (n = 1456), normal-increasing (n = 2159), normal-fluctuated (n = 166), and normal-sharp-increasing (n = 158). Relative to the normal-stable BMI group, the hazard ratios (HRs) and 95% confidence intervals (CIs) after adjustment for confounding factors of the normal-increasing, normal-fluctuated, and normal-sharp-increasing groups were 1.244 (1.103-1.402), 1.331 (1.008-1.756), and 1.641 (1.257-2.142), respectively. Additionally, subgroup analysis showed that the normal-fluctuated BMI trajectory was associated with a significantly higher risk of hypertension only in women (HR = 1.362; 95% CI = 1.151-1.611). The BMI trajectories were significant predictors of hypertension incidence, and increasing BMI trajectories within the currently designated normal range were associated with an increased hypertension risk, especially in women.
| S-EPMC8678668 | biostudies-literature