Anthropometric variables accurately predict dual energy x-ray absorptiometric-derived body composition and can be used to screen for diabetes

Prediction of Android and Gynoid Body Adiposity via a Three-dimensional Stereovision Body Imaging System and Dual-Energy X-ray Absorptiometry

OBJECTIVE

Current methods for measuring regional body fat are expensive and inconvenient compared to the relative cost-effectiveness and ease of use of a stereovision body imaging (SBI) system. The primary goal of this research is to develop prediction models for android and gynoid fat by body measurements assessed via SBI and dual-energy x-ray absorptiometry (DXA). Subsequently, mathematical equations for prediction of total and regional (trunk, leg) body adiposity were established via parameters measured by SBI and DXA.

METHODS

A total of 121 participants were randomly assigned into primary and cross-validation groups. Body measurements were obtained via traditional anthropometrics, SBI, and DXA. Multiple regression analysis was conducted to develop mathematical equations by demographics and SBI assessed body measurements as independent variables and body adiposity (fat mass and percentage fat) as dependent variables. The validity of the prediction models was evaluated by a split sample method and Bland-Altman analysis.

RESULTS

The R(2) of the prediction equations for fat mass and percentage body fat were 93.2% and 76.4% for android and 91.4% and 66.5% for gynoid, respectively. The limits of agreement for the fat mass and percentage fat were -0.06 ± 0.87 kg and -0.11% ± 1.97% for android and -0.04 ± 1.58 kg and -0.19% ± 4.27% for gynoid. Prediction values for fat mass and percentage fat were 94.6% and 88.9% for total body, 93.9% and 71.0% for trunk, and 92.4% and 64.1% for leg, respectively.

CONCLUSIONS

The three-dimensional (3D) SBI produces reliable parameters that can predict android and gynoid as well as total and regional (trunk, leg) fat mass.

Urine creatinine-based estimates of fat-free mass in community-dwelling older persons: the Rancho Bernardo study

OBJECTIVES

To determine whether a previously developed and externally validated equation using common variables (demographics and weight) that are important determinants of muscle mass to estimate 24-hour urine creatinine excretion rate (eCER) is associated with muscle mass and whether spot urine creatinine (UCr) provides similar estimates of muscle mass.

DESIGN

Observational cross-sectional cohort study.

SETTING

The Rancho Bernardo Study, San Diego, California.

SUBJECTS

A total of 1,371 Caucasian, middle class, community-dwelling older adults.

INTERVENTION

Morning spot UCr and fat-free mass (FFM) by dual-energy x-ray absorptiometry were measured. eCER was calculated: eCER (mg/day) = 879.89 + 12.51 × weight (kilogram) - 6.19 × age + 34.51 if black - 379.42 if female. Pearson correlation coefficients and linear regression were used to determine strengths of association of eCER and spot UCr with FFM.

RESULTS

Mean age was 70 years, and 58% were women. eCER was strongly correlated with FFM (r = 0.95, P < .001), a correlation that was superior to that of spot UCr (r = 0.40, P < .001).

CONCLUSIONS

An equation incorporating age, weight, sex, and race to estimate eCER is highly correlated with FFM in community-dwelling older persons and provides a more precise estimate than spot UCr. A simple screening tool for sarcopenia in older persons may allow interventions to maintain or improve muscle mass. Future studies should evaluate whether eCER predicts sarcopenia-related frailty and mortality in older persons.

Percent body fat prediction equations for 8- to 17-year-old American children

BACKGROUND

Percent body fat equations are usually developed in specific populations and have low generalizability.

OBJECTIVES

To use a nationally representative sample of the American youth population (8-17 years old) from the 1999-2004 National Health and Nutrition Examination Survey data to develop gender-specific percent body fat equations.

METHODS

Percent body fat equations were developed for girls and boys using information on weight, height, waist circumference, triceps skin-folds, age, race/ethnicity and menses status compared to dual-emission X-ray absorptiometry. Terms were selected using forward and backward selection in regression models in a 2/3 development sample and were cross-validated in the remaining sample. Final coefficients were estimated in the full sample.

RESULTS

Final equations included ten terms in girls and eight terms in boys including interactions with age and race/ethnicity. In the cross-validation sample, the adjusted R2 was 0.818 and the root mean squared error was 2.758 in girls. Comparable estimates in boys were 0.893 and 2.525. Systematic bias was not detected in the estimates by race/ethnicity or by body mass index categories.

CONCLUSION

Gender-specific percent body fat equations were developed in youth with a strong potential for generalizability and utilization by other investigators studying adiposity-related issues in youth.

Application of alternative anthropometric measurements to predict metabolic syndrome

OBJECTIVE

The association between rarely used anthropometric measurements (e.g., mid-upper arm, forearm, and calf circumference) and metabolic syndrome has not been proven. The aim of this study was to assess whether mid-upper arm, forearm, calf, and waist circumferences, as well as waist/height ratio and waist-to-hip ratio, were associated with metabolic syndrome.

METHODS

We enrolled 387 subjects (340 women, 47 men) who were admitted to the obesity outpatient department of Istanbul Medeniyet University Goztepe Training and Research Hospital between September 2010 and December 2010. The following measurements were recorded: waist circumference, hip circumference, waist/height ratio, waist-to-hip ratio, mid-upper arm circumference, forearm circumference, calf circumference, and body composition. Fasting blood samples were collected to measure plasma glucose, lipids, uric acid, insulin, and HbA1c.

RESULTS

The odds ratios for visceral fat (measured via bioelectric impedance), hip circumference, forearm circumference, and waist circumference/hip circumference were 2.19 (95% CI, 1.30-3.71), 1.89 (95% CI, 1.07-3.35), 2.47 (95% CI, 1.24-4.95), and 2.11(95% CI, 1.26-3.53), respectively. The bioelectric impedance-measured body fat percentage correlated with waist circumference only in subjects without metabolic syndrome; the body fat percentage was negatively correlated with waist circumference/hip circumference in the metabolic syndrome group. All measurements except for forearm circumference were equally well correlated with the bioelectric impedance-measured body fat percentages in both groups. Hip circumference was moderately correlated with bioelectric impedance-measured visceral fat in subjects without metabolic syndrome. Muscle mass (measured via bioelectric impedance) was weakly correlated with waist and forearm circumference in subjects with metabolic syndrome and with calf circumference in subjects without metabolic syndrome.

CONCLUSION

Waist circumference was not linked to metabolic syndrome in obese and overweight subjects; however, forearm circumference, an unconventional but simple and appropriate anthropometric index, was associated with metabolic syndrome and bioelectric impedance-measured visceral fat, hip circumference, and waist-to-hip ratio.