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

ABSTRACT: BACKGROUND/OBJECTIVES: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. SUBJECTS/METHODS: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, R2 values and root mean square error (RMSE) were estimated in the full data set. RESULTS:Models that included age, ethnicity, height, weight, BMI and BIA assessments (resistance, reactance and height2/resistance) had R2 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 R2 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 R2~0.2. CONCLUSIONS: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.

SUBMITTER: Stevens J

PROVIDER: S-EPMC5675766 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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

Stevens J J Truesdale K P KP Cai J J Ou F-S FS Reynolds K R KR Heymsfield S B SB

International journal of obesity (2005) 20170724 11

<h4>Background/objectives</h4>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.<h4>Subjects/methods</h4>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 bod ...[more]

PMID: 28736441

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Project description:BackgroundThere is a paucity of specific data on early stages of chronic kidney disease (CKD) among Asian Americans (AAs). The objective of this study was to examine the independent association of Asian race/ethnicity and socio-demographic and co-morbidity factors with markers of early kidney damage, ascertained by ACR levels, as well as kidney dysfunction, ascertained by eGFR levels in a large cross-sectional sample of AAs enrolled in the National Health and Nutrition Examination Survey (NHANES).MethodsSecondary data analyses of the NHANES 2011-2014 data of a nationally representative sample of 5907 participants 18?years and older, US citizens, and of Asian and White race. NHANES data included race (Asian vs. White), as well as other socio-demographic information and comorbidities. Urine albumin-to-creatinine ratio (ACR) categories and estimated glomerular filtration rate (eGFR) were used as indicators for CKD. Descriptive analyses using frequencies, means (standard deviations), and chi-square tests was first conducted, then multivariable logistic regression serial adjustment models were used to examine the associations between race/ethnicity, other socio-demographic factors (age, sex, education), and co-morbidities (obesity, diabetes, hypertension) with elevated ACR levels (A2 & A3 - CKD Stages 3 and 4-5, respectively) as well as reduced eGFR (G3a-G5 and G3b -G5 - CKD Stage 3-5).ResultsAAs were more likely than White participants to have ACR levels >?300?mg/g (A3) (adjusted OR (aOR) (95% CI) 2.77 (1.55, 4.97), p?=?0.001). In contrast, adjusted analyses demonstrated that AAs were less likely to have eGFR levels <?60?ml/min/1.73?m2 (G3a-G5) (aOR (95% CI) 0.50 (0.35, 0.72), p?<?.001).ConclusionsThis is one of the first large U.S. population-based studies of AAs that has shown a comparatively higher risk of elevated ACR?>?300?mg/g levels (A3) but lower risk of having eGFR levels <?60?ml/min/1.732?m2 (G3a-G5). The findings support the need to address the gaps in knowledge regarding disparities in risk of early stage CKD among AAs.

Project description:BackgroundObesity is protective of bone health; however, abdominal obesity is associated with a higher fracture risk. Little is known about whether body composition protects or adversely affects osteoporotic fractures because of practical issues regarding assessment tools. This study aimed to evaluate the association of predicted body composition with fracture risk to determine the distinctive and differing effects of muscle or fat mass on bone health outcomes in the general population.MethodsThis population-based, longitudinal cohort study used 2009-2010 Korean National Health Insurance Service data and follow-up data from 1 January 2011 to 31 December 2013, to determine the incidence of osteoporotic fracture (total, spine, and non-spine) defined using the International Classification of Diseases, Tenth Revision codes. The study participants were aged ≥50 years (men, 158 426; women, 131 587). The predicted lean body mass index (pLBMI), appendicular skeletal muscle index (pASMI), and body fat mass index (pBFMI) were used to assess body composition, using anthropometric prediction equations.ResultsOver a 3 year follow-up, we identified 2350 and 6175 fractures in men and women, respectively. The mean age of the participants was 60.2 ± 8.3 and 60.7 ± 8.4 years in men and women, respectively. In a multivariable-adjusted Cox proportional hazards regression model, increasing pLBMI or pASMI was significantly associated with a decreased risk of total fractures in men and women. When comparing individuals in the lowest pLBMI and pASMI (reference groups), men with the highest pLBMI and pASMI had adjusted hazard ratios of 0.63 [95% confidence interval (CI) 0.47-0.83] and 0.62 (95% CI 0.47-0.82), and women with the highest pLBMI and pASMI had adjusted hazard ratios of 0.72 (95% CI 0.60-0.85) and 0.71 (95% CI 0.60-0.85), respectively, for total fractures. The pBFMI had no significant association with total fractures in men or women. Regarding sex-specific or site-specific differences, the protective effects of the pLBMI and pASMI on fractures were greater in men and reduced the risk of spinal fractures. An increased pBFMI was associated with an increased risk of spinal fractures in women.ConclusionsAn increased pLBMI or pASMI was significantly associated with decreased total osteoporotic fracture risk; however, the pBFMI showed no statistically significant association. Muscle mass was more important than fat mass in preventing future osteoporotic fractures based on anthropometric prediction equations.

Dataset Information

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

Publications

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

Similar Datasets

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