A protective effect of breastfeeding on overweight (binary) has been reported by meta-analyses using logistic regression, whereas studies using linear regression and BMI (continuous) detected no significant association. To assess the relationship of these differences with different outcome classification, we compared results for linear, logistic, and quantile regression models in a cross-sectional data set of considerable size. Height, weight, and questionnaire data on 9,368 preschool children were collected during school-entry examinations in 1999 and 2002 in Bavaria, Southern Germany. We calculated multivariable linear, logistic, and quantile regression models with outcomes BMI, overweight, obesity, and BMI quantiles (as appropriate). Models considered the covariates breastfeeding (breastfed vs. never breastfed), gender, age, smoking in pregnancy, TV watching, maternal BMI, parental education, and early infant weight gain. No significant association was found in the linear regression model. In the logistic model, a significant association was observed for obesity (odds ratio: 0.72 (95% confidence interval (CI) 0.55, 0.94)). In quantile regression no significant point estimates were observed for the percentiles of 0.4-0.8. However, breastfeeding reduced the BMI of children having values on the 90th and 97th percentiles by -0.23 (95% CI -0.39, -0.07) and -0.26 (95% CI -0.45, -0.07) kg/m(2), respectively, on average. In contrast, breastfeeding was significantly associated with a low shift toward higher BMI values for BMI quantiles of 0.03 and from 0.1 to 0.3. The detection of associations between breastfeeding and childhood body composition might be related to the coding of the response variable (continuous or binary) and the statistical method used (linear, logistic, or quantile regression). Quantile regression should additionally be applied in such studies.
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http://dx.doi.org/10.1038/oby.2008.432 | DOI Listing |
J Acad Nutr Diet
January 2025
Division of Research and Evaluation, Public Health Foundation Enterprises WIC Program, a program of Heluna Health. Electronic address:
Background: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides benefits redeemable for select healthy foods, aligned with the Dietary Guidelines for Americans, to support healthy diets among pregnant and postpartum women, and their children to age 5 years, living in low-income households. WIC benefits are often not fully redeemed, limiting nutritional benefits of participation.
Objective: The objective of this study was to assess the associations of WIC participant, caregiver, and household characteristics with WIC food benefit redemption.
Front Cardiovasc Med
January 2025
Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.
Introduction: The COVID-19 pandemic, starting in 2020, raised concerns about potential long-term health impacts, including its effects on cardiovascular health and related biomarkers. This study part of the Bus Santé in Geneva, Switzerland, compared cardiovascular and metabolic profiles pre- (2016-2019) and post-pandemic (2023-2024) among individuals aged 30-75.
Methods: Participants completed questionnaires and underwent a clinical visit, including a physical examination and fasting blood test to assess lipid and glycemic profiles.
Ecotoxicol Environ Saf
January 2025
Department of Rehabilitation, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China. Electronic address:
The existing evidence indicating that prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with a range of adverse outcomes, including alterations in anthropometric indices, underscores the need for further investigation into the underlying mechanisms. This study aims to examine the effects of prenatal PAH exposure on anthropometric indices and telomere length (TL), as well as to explore whether changes in TL can serve as a predictor of alterations in anthropometric measures. The study was conducted in Shenyang, China, with 2460 pregnant women participating between 2022 and 2023.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Faculty of Arts and Society, Charles Darwin University, Darwin, Australia. Electronic address:
This is a comparative study that investigates the role of green growth, green technological innovations, agricultural eco-efficiency and trade openness on carbon neutrality in the top three carbon emitting countries, namely, China, the USA and India, using panel quantile regression with quarterly data for the time period of 2010-2022. The results reveal different findings which have important policy implications. Firstly, carbon emissions vs green growth and carbon emissions vs green technological innovation have a significant U-shaped relationship, which indicate that when green growth and green technological innovations increases, the rate of carbon emissions continues to decline up to a threshold point and start to increase thereafter.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Economics, University Carlos III, Getafe, Spain.
Climate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact. The value added of this paper lies in introducing a quantitative methodology grounded in the trend analysis of temperature distribution quantiles to analyze climate change heterogeneity (CCH). By converting these quantiles into time series objects, the methodology empowers the definition and measurement of various relevant concepts in climate change analysis (warming, warming typology, warming amplification and warming acceleration) in a straightforward and robust testable linear regression format.
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