Dataset Information

Relative Fat Mass (RFM) as an Estimate of Total Adiposity in Older Adults

ABSTRACT: Abstract

Objectives

It is imperative to accurately estimate whole body fat percentage (%fat) in order to understand the deleterious nature of excess adiposity on cardiometabolic disease risk. However, cost and accessibility often preclude the use of advanced assessment methods. Relative fat mass (RFM), an emerging estimator of whole body %fat based upon waist circumference, height, and biological sex, has yet to be evaluated in an older adult population. The purpose of this study was to examine the relationship between RFM and gold standard measures of adiposity among older adults, and to evaluate whether changes in RFM reflected changes in %fat following a 12-month lifestyle intervention.

Methods

This study was ancillary to a randomized controlled trial investigating the effects of a lifestyle intervention with and without intentional energy restriction. (Clinicaltrials.gov #NCT00955903). Older adults with obesity (N = 163, 37.4% male, 70.3 ± 4.7 years) were randomized to one of three groups: exercise only, exercise + nutrient-dense weight maintenance diet, or exercise + nutrient-dense energy restriction of 500 kcal/d. Total and regional adiposity were determined by dual-energy X-ray absorptiometry (DXA) at baseline and 12 months. Data were analyzed using Spearman's correlations, Wilcoxon, Kruskal-Wallis, and linear regression tests.

Results

At baseline, significant correlations were observed between RFM and DXA whole body %fat (r = 0.751, P < 0.001), DXA total fat (r = 0.353, P < 0.001), and DXA trunk %fat (r = 0.661, P < 0.001). Additionally, RFM was a significant predictor of DXA whole body %fat (P < 0.001) and accounted for 63.5% of model variance. From baseline to 12 months, a significant reduction in RFM was observed among participants in the exercise only and exercise + energy restriction groups (P = 0.020, P < 0.001, respectively). Magnitude of RFM change did not differ among groups. Notably, changes in RFM were significantly correlated with changes in DXA whole body %fat (r = 0.279, P = 0.001) and DXA trunk %fat (r = 0.276, P = 0.001).

Conclusions

Results support use of RFM as an estimate of whole body %fat, as well as an indicator of its sensitivity to change in fat mass over 12 months in older adults. Incorporation of RFM in cardiometabolic research may provide meaningful information not reflected in conventional body composition measures such as body mass index.

Funding Sources

NIH

SUBMITTER: Senkus K

PROVIDER: S-EPMC8181950 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Analysis of body composition is becoming increasingly important for the assessment, understanding and monitoring of multiple health issues. The body mass index (BMI) has been questioned as a tool to estimate whole-body fat percentage (FM%). Recently, a simple equation described as relative fat mass (RFM) was proposed by Woolcott & Bergman. This equation estimates FM% using two anthropometric measurements: height and waist circumference (WC). The authors state that due to its simplicity and better performance than BMI, RFM could be used in daily clinical practice as a tool for the evaluation of body composition. The aim of this study was to externally validate the equation of Woolcott & Bergman to estimate FM% among adults from north-west Mexico compared with Dual-energy X-ray absorptiometry (DXA) as an alternative to BMI and secondly, to make the same comparison using air displacement plethysmography (ADP), Bioelectrical Impedance Analysis (BIA) and a 4-compartment model (4C model). METHODS:Weight, height and WC were measured following standard procedures. The RFM index was calculated for each of the 61 participating subjects (29 females and 32 males, ages 20-37 years). The RFM was then regressed against each of the four body composition methods for estimating FM%. RESULTS:Compared with BMI, RFM was a better predictor of FM% determined by each of the body composition methods. In terms of precision the best equation was RFM regressed against DXA (y = 1.12 + 0.99 x; R2 = 0.84 p<0.001). Accuracy (represented by the closeness to the zero-intercept) was 1.12 (95% CI: -2.44, to 4.68) and thus, not significantly different from zero. For the rest of the methods, precision in the prediction of FM% was improved compared to BMI, with significant increases in the R2 and reduction of the root mean squared error (RMSE). However, the intercepts of each regression did not show accuracy since they were different from zero, for ADP: -9.95 (95%CI: -15.7 to -4.14), for BIA: -12.6 (95%CI: -17.5 to -7.74) and for the 4C model: -13.6 (95%CI: -18.6 to -8.60). Irrespectively, FM% measured by each of the body composition methods was higher for DXA than the other three methods (p<0.001). CONCLUSIONS:This external validation proved that the performance of the RFM equation used in this study to estimate FM% was more consistent than BMI in this Mexican population, showing a stronger correlation with DXA than with the other body composition methods.

Project description:Background/objectives/introductionIt is imperative to accurately estimate whole body fat percentage (%fat) to understand the deleterious nature of excess adiposity on cardiometabolic disease risk. Cost and accessibility often preclude the use of advanced imaging methods like dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI). Relative fat mass (RFM) is an emerging estimator of whole body %fat based on waist circumference, height, and biological sex. The purpose of this ancillary study was to examine the relationship between RFM and gold-standard measures of adiposity among community-dwelling older adults with obesity and to evaluate if changes in RFM reflect changes in %fat following a 12-month lifestyle intervention (clinicaltrials.gov #NCT00955903).Patients/materials and methodsParticipants (N = 163, 37.4% male, 70.3 ± 4.7 years) were randomized to the exercise only group, exercise + nutrient-dense weight maintenance group, or exercise + nutrient-dense energy restriction of 500 kcal/d group. Total and regional adiposity assessed by DXA and MRI, as well as anthropometrics, were evaluated at baseline and 12 months.ResultsRFM was significantly positively correlated with DXA whole body %fat and DXA trunk %fat at baseline. Equivalence testing revealed that RFM was considered equivalent to DXA whole body %fat for females only. Additionally, from baseline to 12 months, a significant reduction in RFM was observed among female participants in the exercise + energy restriction group only. Changes in RFM were significantly correlated with changes in DXA whole body %fat, DXA trunk fat, and total abdominal fat tissue determined by MRI.ConclusionResults support the use of RFM as an estimate of whole body %fat where advanced imaging techniques are not feasible. Furthermore, results suggest that this index is sensitive to changes in fat mass over 12 months in female older adults with obesity. KEY MESSAGESRelative fat mass (RFM), an emerging estimator of whole body %fat based on waist circumference, height, and biological sex, was intentionally developed to be a simple estimate of adiposity that overcomes limitations of measures like body mass index.In the current study, results from correlations and agreement analyses support the use of RFM to estimate whole-body fat percentage in a community-dwelling older adult population with obesity when advanced methods, namely dual-energy X-ray absorptiometry, are not feasible.Significant reductions in RFM were also observed over a 12-month period that was significantly correlated with changes in whole body fat percentage; thus, supporting the sensitivity of RFM to lifestyle changes.

Project description:ObjectivesThe body mass index (BMI) largely underestimates excess body fat, suggesting that the prevalence of obesity could be underestimated. Biologically, women are known to have higher body fat than men. This study aimed to compare the temporal trends in general obesity by sex, ethnicity and age among adults in the USA using the relative fat mass (RFM), a validated surrogate for whole-body fat percentage and BMI.DesignPopulation-based study.SettingUS National Health and Nutrition Examination Survey, from 1999-2000 to 2017-March 2020.ParticipantsA representative sample of adults 20-79 years in the USA.Main outcome measuresAge-adjusted prevalence of general obesity. RFM-defined obesity was diagnosed using validated cut-offs to predict all-cause mortality: RFM≥40% for women and ≥30% for men. BMI-defined obesity was diagnosed using a cut-off of 30 kg/m2.ResultsAnalysis included data from 47 667 adults. Among women, RFM-defined obesity prevalence was 64.7% (95% CI 62.1% to 67.3%) in 2017-2020, a linear increase of 13.9 percentage points (95% CI 9.0% to 18.9%; p<0.001) relative to 1999-2000. In contrast, the prevalence of BMI-defined obesity was 42.2% (95% CI 39.4% to 45.0%) in 2017-2020. Among men, the corresponding RFM-defined obesity prevalence was 45.8% (95% CI 42.0% to 49.7%), a linear increase of 12.0 percentage points (95% CI 6.6% to 17.3%; p<0.001). In contrast, the prevalence of BMI-defined obesity was 42.0 (95% CI 37.8% to 46.3%). The highest prevalence of RFM-defined obesity across years was observed in older adults (60-79 years) and Mexican Americans, in women and men. Conversely, the highest prevalence of BMI-defined obesity across years was observed in middle-age (40-59 years) and older adults, and in African American women.ConclusionsThe use of a surrogate for whole-body fat percentage revealed a much higher prevalence of general obesity in the USA from 1999 to 2020, particularly among women, than that estimated using BMI, and detected a disproportionate higher prevalence of general obesity in older adults and Mexican Americans.

Project description:Body-mass index (BMI), waist circumference, and waist-hip ratio are commonly used anthropometric indices of adiposity. However, over the past 10 years, several new anthropometric indices were developed, that more accurately correlated with body fat distribution and total fat mass. They include relative fat mass (RFM), body-roundness index (BRI), weight-adjusted-waist index and body-shape index (BSI). In the current study, we included 8295 adults from the PREVEND (Prevention of Renal and Vascular End-Stage Disease) observational cohort (the Netherlands), and sought to examine associations of novel as well as established adiposity indices with incident heart failure (HF). The mean age of study population was 50 ± 13 years, and approximately 50% (n = 4134) were women. Over a 11 year period, 363 HF events occurred, resulting in an overall incidence rate of 3.88 per 1000 person-years. We found that all indices of adiposity (except BSI) were significantly associated with incident HF in the total population (P < 0.001); these associations were not modified by sex (P interaction > 0.1). Amongst adiposity indices, the strongest association was observed with RFM [hazard ratio (HR) 1.67 per 1 SD increase; 95% confidence interval (CI) 1.37-2.04]. This trend persisted across multiple age groups and BMI categories, and across HF subtypes [HR: 1.76, 95% CI 1.26-2.45 for HF with preserved ejection fraction; HR 1.61, 95% CI 1.25-2.06 for HF with reduced ejection fraction]. We also found that all adiposity indices (except BSI) improved the fit of a clinical HF model; improvements were, however, most evident after adding RFM and BRI (reduction in Akaike information criteria: 24.4 and 26.5 respectively). In conclusion, we report that amongst multiple anthropometric indicators of adiposity, RFM displayed the strongest association with HF risk in Dutch community dwellers. Future studies should examine the value of including RFM in HF risk prediction models.