ArticleEuropean journal of clinical nutrition2023
Predictive equations for fat mass in older Hispanic adults with excess adiposity using the 4-compartment model as a reference method.
Article in European journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Evaluation of Skinfolds Based Predictive Equations for Estimating Body Fat Percentage in Older Adults: A Comparison Using Digital Adipometer (Lipowise) and Dual-Energy X-Ray Absorptiometry (DXA).Clinical obesity · 2026Article
- Development and cross-validation of predictive equations for fat-free mass estimation by bioelectrical impedance analysis in Brazilian subjects with overweight and obesity.Frontiers in nutrition · 2025Article
- Novel BMI cutoff points for obesity diagnosis in older Hispanic adults.Scientific reports · 2024Article
- Association between the risk of malnutrition and sarcopenia at 4.2 years of follow-up in community-dwelling older adults.Frontiers in medicine · 2024Article
- Agreement Between Bioelectrical Impedance Analysis and Dual-Energy X-ray Absorptiometry to Estimate Fat Mass in Hispanic Adults With Type 2 Diabetes Mellitus: A Cross-Sectional Study.Clinical medicine insights. Endocrinology and diabetes · 2024Article
- Incidence of the Risk of Malnutrition and Excess Fat Mass, and Gait Speed as Independent Associated Factors in Community-Dwelling Older Adults.Nutrients · 2023Article
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Authors and funding
9 authors.
Funding
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Abstract
backgroundPredictive equations are the best option for assessing fat mass in clinical practice due to their low cost and practicality. However, several factors, such as age, excess adiposity, and ethnicity can compromise the accuracy of the equations reported to date in the literature.
objectiveTo develop and validate two predictive equations for estimating fat mass: one based exclusively on anthropometric variables, the other combining anthropometric and bioelectrical impedance variables using the 4C model as the reference method. SUBJECTS/
methodsThis is a cross-sectional study that included 386 Hispanic subjects aged ≥60 with excess adiposity. Fat mass and fat-free mass were measured by the 4C model as predictive variables. Age, sex, and certain anthropometric and bioelectrical impedance data were considered as potential predictor variables. To develop and to validate the equations, the multiple linear regression analysis, and cross-validation protocol were applied.
resultsEquation 1 included weight, sex, and BMI as predictor variables, while equation 2 considered sex, weight, height squared/resistance, and resistance as predictor variables. R
conclusionsThe new predictive equations are reliable for estimating body composition and are interchangeable with the 4C model. Thus, they can be used in epidemiological and clinical studies, as well as in clinical practice, to estimate body composition in older Hispanic adults with excess adiposity.
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