Prediction equations for fat and fat-free body mass in adolescents, based on body circumferences

Probabilistic prediction of segmental body composition in Iranian children and adolescents

Background

Adolescents' body composition is considered an important measure to evaluate health status. An examination of any of the segmental compartments by anthropometric indices is a more usable method than direct methods.

Objectives

To propose a method based on the network approach for predicting segmental body composition components in adolescent boys and girls using anthropometric measurements.

Methods

A dual-energy X-ray absorptiometry (DXA) dataset in the south of Iran, including 476 adolescents (235 girls and 241 boys) with a range of 9–18 years, was obtained. Several anthropometric prediction models based on the network approach were fitted to the training dataset (TRD 80%) using bnlearn, an R add-in package. The best fitted models were applied to the validation dataset (VAD 20%) to assess the prediction accuracy.

Results

Present equations consisting of age, weight, height, body mass index (BMI), and hip circumference accounted for 0.85 (P < 0.001) of the variability of DXA values in the corresponding age groups of boys. Similarly, reasonable estimates of DXA values could be obtained from age, weight, height, and BMI in girls over 13 years, and from age, weight, height, BMI, and waist circumference in girls under 13 years, respectively, of 0.77 and 0.83 (P < 0.001). Correlations between robust Gaussian Bayesian network (RGBN) predictions and DXA measurements were highly significant, averaging 0.87 for boys and 0.82 for girls (P < 0.001).

Conclusions

The results revealed that, based on the present study’s predictive models, adolescents' body composition might be estimated by input anthropometric information. Given the flexibility and modeling of the present method to test different motivated hypotheses, its application to body compositional data is highly appealing.

The Body Adiposity Index is not applicable to the Brazilian adult population

Background

Obesity is a serious disease that burdens public health systems around the world. It is a risk factor for the development of several non-communicable chronic diseases that are related to the amount and distribution of body fat. Body composition assessment using simple and low-cost techniques can help in the early detection of excess fat, allowing for the prevention and treatment of both obesity and associated diseases. Thus, identifying and proposing valid anthropometric indices for this purpose can be a great ally of health programs.

Objective

To verify the validity of the Body Adiposity Index (BAI) in relation to Dual Energy X-Ray Absorptiometry (DXA) for estimating body fat percentage in Brazilian adults, as well as to propose a new mathematical model to estimate the fat-free mass of this population.

Methods

In a cross-sectional study, 424 subjects (of which 220 were women), aged between 20 and 59 years, were evaluated by BAI and DXA, then randomly divided into two groups stratified by sex: the development group (n = 283) and the cross-validation group (n = 141). Statistical analyses to test the validity of BAI as a predictor of fat mass, in addition to proposing a new mathematical model for estimating fat-free mass, using DXA as a reference method. The analysis included paired t-test, stepwise multiple regression, coefficient of concordance correlation, and Bland-Altman plots.

Results

The BAI validity analysis showed a low correlation coefficient of agreement [CCC = 0.626; ρ (precision) = 0.795; C_b(accuracy) = 0.787]; in addition, the mean difference in the Bland-Altman plot was different from zero in the cross-validation group (p < 0.01) and limits of agreement (LOA) ranged between−8.0 and 14.4 kg, indicating a poor agreement between the BAI and the reference method. The new mathematical model for estimating FFM showed a high correlation coefficient of agreement (CCC = 0.952; ρ = 0.953; C_b = 0.999), in addition to acceptable LOA in the Bland-Altman plot (-6.7 and 6.7).

Conclusion

In the studied sample, the BAI showed low validity for estimating body fat, while the new proposed model was found to be a good option to assess the body composition of Brazilian adults.

CO-FLOW: COvid-19 Follow-up care paths and Long-term Outcomes Within the Dutch health care system: study protocol of a multicenter prospective cohort study following patients 2 years after hospital discharge

BACKGROUND

First studies indicate that up to 6 months after hospital discharge, coronavirus disease 2019 (COVID-19) causes severe physical, cognitive, and psychological impairments, which may affect participation and health-related quality of life (HRQoL). After hospitalization for COVID-19, a number of patients are referred to medical rehabilitation centers or skilled nursing facilities for further treatment, while others go home with or without aftercare. The aftercare paths include 1] community-based rehabilitation; 2] in- and outpatient medical rehabilitation; 3] inpatient rehabilitation in skilled nursing facilities; and 4] sheltered care (inpatient). These aftercare paths and the trajectories of recovery after COVID-19 urgently need long-term in-depth evaluation to optimize and personalize treatment. CO-FLOW aims, by following the outcomes and aftercare paths of all COVID-19 patients after hospital discharge, to systematically study over a 2-year period: 1] trajectories of physical, cognitive, and psychological recovery; 2] patient flows, healthcare utilization, patient satisfaction with aftercare, and barriers/facilitators regarding aftercare as experienced by healthcare professionals; 3] effects of physical, cognitive, and psychological outcomes on participation and HRQoL; and 4] predictors for long-term recovery, health care utilization, and patient satisfaction with aftercare.

METHODS

CO-FLOW is a multicenter prospective cohort study in the mid-west of the Netherlands with a 2-year follow-up period. Measurements comprise non-invasive clinical tests and patient reported outcome measures from a combined rehabilitation, pulmonary, and intensive care perspective. Measurements are performed at 3, 6, 12, and 24 months after hospital discharge and, if applicable, at rehabilitation discharge. CO-FLOW aims to include at least 500 patients who survived hospitalization for COVID-19, aged ≥18 years.

DISCUSSION

CO-FLOW will provide in-depth knowledge on the long-term sequelae of COVID-19 and the quality of current aftercare paths for patients who survived hospitalization. This knowledge is a prerequisite to facilitate the right care in the right place for COVID-19 and comparable future infectious diseases.

TRIAL REGISTRATION

The Netherlands Trial Register (NTR), https://www.trialregister.nl . Registered: 12-06-2020, CO-FLOW trialregister no. NL8710.

Processed and ultra-processed foods are associated with high prevalence of inadequate selenium intake and low prevalence of vitamin B1 and zinc inadequacy in adolescents from public schools in an urban area of northeastern Brazil

Changes in eating behavior of adolescents are associated with high consumption of processed and ultra-processed foods. This study evaluated the association between these foods and the prevalence of inadequate micronutrient intake in adolescents. A cross-sectional study was conducted with 444 adolescents from public schools in the city of Natal, northeastern Brazil. The adolescents' habitual food consumption was evaluated using two 24-hour dietary recalls. Foods were categorized according to the degree of processing (processed and ultra-processed) and distributed into energy quartiles, using the NOVA classification system. Inadequacies in micronutrient intake were assessed using the estimated average requirement (EAR) as the cutoff point. Multivariate logistic regression models were used to estimate the relationship between energy percentage from processed and ultra-processed foods and prevalence of inadequate micronutrient intake. The mean (Standard Deviation (SD)) consumption of total energy from processed foods ranged from 5.8% (1.7%) in Q1 to 20.6% (2.9%) in Q4, while the mean consumption of total energy from ultra-processed foods ranged from 21.4% (4.9%) in Q1 to 61.5% (11.7%) in Q4. The rates of inadequate intake of vitamin D, vitamin E, folate, calcium, and selenium were above 80% for both sexes across all age groups. Energy consumption from processed foods was associated with higher prevalence of inadequate selenium intake (p < 0.01) and lower prevalence of inadequate vitamin B1 intake (p = 0.04). Energy consumption from ultra-processed foods was associated with lower prevalence of inadequate zinc and vitamin B1 intake (p < 0.01 and p = 0.03, respectively). An increase in the proportion of energy obtained from processed and ultra-processed foods may reflect higher prevalence of inadequate selenium intake and lower prevalence of vitamin B1 and zinc inadequacy.

Fat-Free Mass and Bone Mineral Density of Young Soccer Players: Proposal of Equations Based on Anthropometric Variables

Background

The assessment of body composition may assist in optimizing competitive efficiency and monitoring the success of training regimes for young soccer players. The purpose of this study was to determine the predictors for Fat-Free Mass (FFM) and Bone Mineral Density (BMD) of young soccer players. Also, the goal was to propose regression equations to estimate FFM and BDM through anthropometric variables.

Methods

One hundred and sixty-seven young soccer players ages 10.0 to 19.9 years old were studied. Weight, height, trunk-cephalic length, right arm circumference, diameter of the humerus, and length of the foot were assessed. FFM and BDM were determined by using dual X-ray absorptiometry (DXA). Maturity status using Peak Height Velocity (PHV) was calculated.

Results

Maturity status, weight, and circumference of the relaxed arm positively related to the FFM (R² = 41–66%). Similarly, PHV, weight, diameter of the humerus, and length of the foot explained BDM in both groups of soccer players (goalkeepers and filed players) (R² = 45–82%). Six equations to predict FFM (R² = 62–69%) and six to predict BDM (R² = 69–90%) were created. Chronological age had a limited use for predicting FFM and BDM.

Conclusion

Results suggested the use and application of the regression equations as a non-invasive alternative for everyday use in soccer clubs.

Muscle Mass in Children and Adolescents: Proposed Equations and Reference Values for Assessment

Objectives: The goal of this study was to develop regression equations to estimate LM with anthropometric variables and to propose percentiles for evaluating by age and sex. Methods: A cross sectional study was conducted with 2,182 Chilean students (1,347 males and 835 females). Ages ranged from 5.0 to 17.9 years old. A total body scan was carried out with the double energy X-ray anthropometry (DXA) to examine and measure lean muscle mass of the entire body. Weight, height, and the circumference of the relaxed right arm were also measured. Results: Four anthropometric equations were generated to predict lean mass for both sexes (R ² = 83-88%, SEE = 3.7-5.0%, precision = 0.90-0.93, and accuracy = 0.99). The Lambda-mu-sigma method was used to obtain the sex-specific and age-specific percentile curves of lean mass (p3, p5, p10, p15, p25, p50, p75, p85, p90, p95, and p97). Conclusion: The four proposed equations were acceptable in terms of precision and accuracy to estimate lean mass in children and adolescents. The percentiles were created by means of anthropometric equations and real values for DXA. These are fundamental tools for monitoring LM in Chilean children and adolescents of both sexes.

Body composition and prediction equations using skinfold thickness for body fat percentage in Southern Brazilian adolescents

OBJECTIVES

The purpose of this study was to: a) determine the nutritional status of Brazilian adolescents, and; b) present a skinfold thickness model (ST) to estimate body fat developed with Brazilian samples, using dual energy x-ray absorptiometry (DXA) as reference method.

METHODS

The main study group was composed of 374 adolescents, and further 42 adolescents for the validation group. Weight, height, waist circumference measurements, and body mass index (BMI) were collected, as well as nine ST-biceps (BI), triceps (TR), chest (CH), axillary (AX) subscapularis (SB), abdominal (AB), suprailiac (SI), medial thigh (TH), calf (CF), and fat percentage (%BF) obtained by DXA.

RESULTS

The prevalence of overweight in adolescents was 20.9%, and obesity 5.8%. Regression analysis through ordinary least square method (OLS) allowed obtainment of three equations with values of R2 = 0.935, 0.912 and 0.850, standard error estimated = 1.79, 1.78 and 1.87, and bias = 0.06, 0.20 and 0.05, respectively.

CONCLUSION

the innovation of this study lies in presenting new regression equations for predicting body fat in Southern Brazilian adolescents based on a representative and heterogeneous sample from DXA.