Relationships among fat mass, fat-free mass and height in adults: A new method of statistical analysis applied to NHANES data.
Level 4 - case-series / case-control
Cross-sectional analysis of observational population survey data (NHANES) and statistical modeling.
PubMed 27862528 · doi:10.1002/ajhb.22941
What was done
The authors developed a regression-based statistical method, verified via Monte Carlo simulation, to model the relationship between fat-free mass (FFM) and fat mass (FM) independent of height (expressed as ΔFFM/ΔFM, or K_F) and estimate theoretical fat-free BMI (BMI_0). The method regressed height^2 on FFM and FM, adjusted for variability in K_F around its mean, and applied this model to cross-sectional adult data from NHANES across Mexican American, non-Hispanic European American, and African American populations.
What was found
The abstract reports no specific numerical estimates, effect sizes, or confidence intervals. Qualitatively, relationships between FFM and FM were found to be linear rather than semilogarithmic. Mean K_F was similar between Mexican American men and women, but higher in men than women among non-Hispanic European Americans and African Americans. Mean BMI_0 was higher in men than women, and FM correlated more strongly with height than previously reported.
Why it matters
This method provides an analytical approach to adjust for height confounding when evaluating the relationship between fat mass and fat-free mass across diverse demographic groups.
Limits
No sample size (n), effect sizes, or numerical statistics are reported in the abstract. The underlying data are cross-sectional population observations rather than longitudinal tracking of body composition changes over time.
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