Examining individual and school characteristics associated with child obesity using a multilevel growth model.

Soc Sci Med

Virginia Tech, Department of Educational Leadership and Policy Studies, 318 East Eggleston Hall (0302), Blacksburg, VA, USA.

Published: March 2015

The childhood obesity epidemic continues to be a serious concern in the U.S., disproportionately affecting low socioeconomic and minority groups. Because many interventions are based in schools, both individual and school factors contributing to obesity were examined in this study. Employing data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 (ECLS-K), a three level hierarchical linear model was used to estimate children's body mass index (BMI) growth trajectories within their school contexts. Results indicated an inverse relationship between BMI and socioeconomic status (SES), except for black males. Additionally, results showed that low school SES and rural locality of the school were school-level risk factors of obesity. Lastly, a major portion of the between-schools variance was explained by aggregated student characteristics, indicating that students were more likely to attend schools with peers of similar BMI who had similar SES and race/ethnicity, supporting a school-level compositional effect associated with obesity.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.socscimed.2014.12.032DOI Listing

Publication Analysis

Top Keywords

individual school
8
school
5
obesity
5
examining individual
4
school characteristics
4
characteristics associated
4
associated child
4
child obesity
4
obesity multilevel
4
multilevel growth
4

Similar Publications

Our previous studies revealed the existence of a Universal Receptive System that regulates interactions between cells and their environment. This system is composed of DNA- and RNA-based Teazeled receptors (TezRs) found on the surface of prokaryotic and eukaryotic cells, as well as integrases and recombinases. In the current study, we aimed to provide further insight into the regulatory role of TezR and its loss in Staphylococcus aureus gene transcription.

View Article and Find Full Text PDF

Background: Cancer requires interdisciplinary intersectoral care. The Care Coordination Instrument (CCI) captures patients' perspectives on cancer care coordination. We aimed to translate, adapt, and validate the CCI for Germany (CCI German version).

View Article and Find Full Text PDF

Background: The potential therapeutic role of magnesium (Mg) in type 2 diabetes mellitus (T2DM) remains insufficiently studied despite its known involvement in critical processes like lipid metabolism and insulin sensitivity. This study examines the impact of Mg-focused nutritional education on lipid profile parameters, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in T2DM patients.

Methods: Thirty participants with T2DM were recruited for this within-subject experimental study.

View Article and Find Full Text PDF

Latent tuberculosis prevalence in healthcare workers in Laos: a cross-sectional study.

Trop Med Health

January 2025

LaoLuxLab/Vaccine Preventable Diseases Laboratory, Institut Pasteur du Laos, Vientiane, Laos.

Background: Individuals with latent tuberculosis infection (LTBI) have a high risk of active infection, morbidity and mortality. Healthcare workers are a group who have increased risk of infection and onward transmission to their patients and other susceptible individuals; however, LTBI is often undiagnosed, and individuals are asymptomatic. Interferon gamma release assays (IGRA) can detect evidence of TB infection in otherwise asymptomatic individuals and are a good indication of LTBI.

View Article and Find Full Text PDF

Background: Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. However, the complexity of the gut microbiome, data sparsity, compositionality, and population-specificity present significant challenges. Microbiome data transformations can alleviate some of the aforementioned challenges, but their usage in machine learning tasks has largely been unexplored.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!