Details

Autor(en) / Beteiligte

• Stevens, J
• Truesdale, K P
• Cai, J
• Ou, F-S
• Reynolds, K R
• Heymsfield, S B

Titel

Nationally representative equations that include resistance and reactance for the prediction of percent body fat in Americans

Ist Teil von

• International Journal of Obesity, 2017-11, Vol.41 (11), p.1669-1675

Ort / Verlag

England: Nature Publishing Group

Erscheinungsjahr

2017

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Resistance and reactance collected by bioelectrical impedance (BIA) can be used in equations to estimate percent body fat at relatively low cost and subject burden. To our knowledge, no such equations have been developed in a nationally representative sample. Dual-energy X-ray absorptiometry assessed percent body fat from the 1999 to 2004 National Health and Nutrition Survey was the criterion method for development of sex-specific percent body fat equations using up to 6467 males or 4888 females 8-49 years of age. Candidate variables were studied in multiple mathematical forms and interactions using the Least Absolute Shrinkage and Selection Operator. Models were fit in 2/3's of the data and validated in 1/3 of the data selected at random. Final coefficients, R values and root mean square error (RMSE) were estimated in the full data set. Models that included age, ethnicity, height, weight, BMI and BIA assessments (resistance, reactance and height /resistance) had R values of 0.831 in men and 0.864 in women in the full data set. RMSE measurements were between 2 and 3 body fat percentage points, and all equations showed low bias across groups formed by age, race/ethnicity or body mass index category. The addition of triceps skinfold and waist circumference increased the R to 0.905 in males and 0.883 in females. Adding other anthropometrics (plus menses in females) had little impact on performance. Reactance and resistance alone (in multiple mathematical forms) performed poorly with R ~0.2. Equations that included BIA assessments along with demographic and anthropometric variables provided percent body fat assessments that had high generalizability, strong predictive ability and low bias.