scholarly journals Association between Exercise-Induced Changes in Cardiorespiratory Fitness and Adiposity among Overweight and Obese Youth: A Meta-Analysis and Meta-Regression Analysis

Children ◽  
2020 ◽  
Vol 7 (9) ◽  
pp. 147
Author(s):  
Antonio García-Hermoso ◽  
Mikel Izquierdo ◽  
Alicia M. Alonso-Martínez ◽  
Avery Faigenbaum ◽  
Jordi Olloquequi ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Confidence Interval ◽  
Cardiorespiratory Fitness ◽  
Body Fat ◽  
Health Care Providers ◽  
Percent Body Fat ◽  
Care Providers ◽  
Obese Youth ◽  
Meta Regression ◽  
Meta Regression Analysis

The aim of this study was to determine the minimum change in cardiorespiratory fitness (CRF) required to reduce adiposity (percent body fat) in exercise programs for overweight and obese youth. Studies were identified through a systematic search of five databases. Studies were limited to randomized controlled trials (RCTs) of exercise training (e.g., aerobic, strength, concurrent) that assessed percent body fat and CRF for both exercise and control groups in overweight and obese children and adolescents. A series of meta-regressions were conducted to explore links between change in CRF (maximum oxygen consumption, ml/kg/min) and change in percent body fat. Twenty-three RCTs were included (n = 1790, 59% females). Meta-regression analysis suggested that increases of at least 0.38 mL/kg/min in CRF (p < 0.001) were considered to be a clinically important reduction of percent body fat (−2.30%, 95% confidence interval −3.02 to −1.58; p < 0.001; I2 = 92.2%). Subgroup analysis showed that increases of at least 0.17 mL/kg/min in CRF favored a reduction of percent body fat of −1.62% (95% confidence interval −2.04 to −1.20; p < 0.001; I2 = 69.9%). In conclusion, this change in CRF could be considered by pediatric researchers, youth fitness specialists, and health care providers to determine the effectiveness in body fat reductions through exercise.

scholarly journals Development and Cross-Validation of a Simple Model to Estimate Percent Body Fat in Persons with Multiple Sclerosis

2021 ◽  
Author(s):  
Fabio Bertapelli ◽  
Stephanie L. Silveira ◽  
Stamatis Agiovlasitis ◽  
Robert W. Motl
Keyword(s):  
Multiple Sclerosis ◽  
Body Composition ◽  
Body Fat ◽  
Health Care Providers ◽  
Cross Validation ◽  
Strong Association ◽  
Absolute Error ◽  
Percent Body Fat ◽  
Care Providers ◽  
Separate Sample

Abstract Background: Persons with multiple sclerosis (MS) have higher body composition variability compared with the general population. Monitoring body composition requires accurate methods for estimating percent body fat (%BF). We developed and cross-validated an equation for estimating %BF from body mass index (BMI) and sex in persons with MS. Methods: Seventy-seven adults with MS represented the sample for the equation development. A separate sample of 33 adults with MS permitted the equation cross-validation. Dual-energy xray absorptiometry (DXA) provided the criterion %BF. Results: The model including BMI and sex (mean ± SD age: women, 49.2 ± 8.8 years; men, 48.6 ± 9.8 years) had high predictive ability for estimating %BF (P &lt; .001, R2 = 0.77, standard error of estimate = 4.06%). Age, MS type, Patient-Determined Disease Steps score, and MS duration did not improve the model. The equation was %BF = 3.168 + (0.895 × BMI) – (10.191 × sex); sex, 0 = woman; 1 = man. The equation was cross-validated in the separate sample (age: women, 48.4 ± 9.4 years; men, 43.8 ± 15.4 years) based on high accuracy as indicated by strong association (r = 0.89, P &lt; .001), nonsignificant difference (mean: 0.2%, P &gt; .05), small absolute error (mean: 2.7%), root mean square error (3.5%), and small differences and no bias in Bland-Altman analysis (mean difference: 0.2%, 95% CI: −6.98 to 6.55, rs = −0.07, P = .702) between DXA-determined and equation-estimated %BF. Conclusions: Health care providers can use this developed and cross-validated equation for estimating adiposity in persons with MS when DXA is unavailable.

scholarly journals Mapping global prevalence of depression among postpartum women

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ziyi Wang ◽  
Jiaye Liu ◽  
Huan Shuai ◽  
Zhongxiang Cai ◽  
Xia Fu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Postpartum Depression ◽  
Life Stress ◽  
Primary Care Providers ◽  
Developed Countries ◽  
Care Providers ◽  
Comprehensive Overview ◽  
Global Epidemiology ◽  
Meta Regression ◽  
Meta Regression Analysis

AbstractPostpartum depression (PPD) is the most common psychological condition following childbirth, and may have a detrimental effect on the social and cognitive health of spouses, infants, and children. The aim of this study was to complete a comprehensive overview of the current literature on the global epidemiology of PPD. A total of 565 studies from 80 different countries or regions were included in the final analysis. Postpartum depression was found in 17.22% (95% CI 16.00–18.51) of the world’s population. Meta-regression analysis showed that study size, country or region development, and country or region income were the causes of heterogeneity. Multivariable meta-regression analysis found that study size and country or area development were the most important predictors. Varied prevalence rates were noted in geographic regions with the highest rate found in Southern Africa (39.96%). Of interested was a significantly lower rate of PPD in developed countries or high-income countries or areas. Furthermore, the findings showed that there was a substantial difference in rates of PPD when marital status, educational level, social support, spouse care, violence, gestational age, breast feeding, child mortality, pregnancy plan, financial difficulties, partnership, life stress, smoking, alcohol intake, and living conditions were considered in the pooled estimates. Our results indicated that one out of every five women experiences PPD which is linked to income and geographic development. It is triggered by a variety of causes that necessitate the attention and committed intervention of primary care providers, clinicians, health authorities, and the general population.

scholarly journals The Elasticity of Taxable Income: A Meta-Regression Analysis*

2021 ◽  
Author(s):  
Carina Neisser
Keyword(s):  
Regression Analysis ◽  
Policy Analysis ◽  
Selective Reporting ◽  
Tax Base ◽  
Taxable Income ◽  
Income Elasticities ◽  
Elasticity Of Taxable Income ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Key Parameter

Abstract The elasticity of taxable income (ETI) is a key parameter in tax policy analysis. To examine the large variation found in the literature of taxable and broad income elasticities, I conduct a comprehensive meta-regression analysis using information from 61 studies containing 1,720 estimates. My findings reveal that estimated elasticities are not immutable parameters. They are correlated with contextual factors and the choice of the empirical specification influences the estimated elasticities. Finally, selective reporting bias is prevalent, and the direction of bias depends on whether deductions are included in the tax base.

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