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Context: The National Academy of Medicine recommends childhood obesity prevention efforts making healthier options the passive choice. This review evaluated the effectiveness of population-level policies and programs from natural experiments for childhood obesity prevention.
Evidence Acquistion: The search included PubMed, CINAHL, PsycINFO, and EconLit from 2000 to 2017 for policies evaluated by natural experiments reporting childhood BMI outcomes. The studies were analyzed in 2017-2018. Interventions were classified by environmental focus (food/beverage, physical activity, or both) and stratified by setting (school, community, both). Risk of bias was evaluated for each study.
Evidence Synthesis: Of 33 natural experiments, most (73%) took place in the school setting only. The most common environmental focus in any setting was food/beverage (48%). All four studies that focused on both food/beverage and physical activity in schools demonstrated decreased prevalence of overweight/obesity or BMI z-score by 0.04-0.17. BMI decreased in all four studies in both school and community settings. The largest effect size was a decrease in BMI z-score of 0.5, but most were <0.25. The risk of bias was high for most (76%) studies. Most (63%) of the eight studies with low/medium risk of bias took place in the school setting focused on the food/beverage environment; effects on BMI were mixed.
Conclusions: Natural experiments evaluating school-based policies focusing on both the food/beverage and physical activity environments (versus targeting only one) consistently showed improvement in BMI. However, most studies had high risk of bias, highlighting the need for improved methods for evaluation of natural experiments for childhood obesity prevention.
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http://dx.doi.org/10.1016/j.amepre.2018.08.023 | DOI Listing |
Glob Chang Biol
September 2025
Chair of Silviculture, Faculty of Environment and Natural Resources, Institute of Forest Sciences, University of Freiburg, Freiburg, Germany.
Mixed-species forests are proposed to enhance tree resistance and resilience to drought. However, growing evidence shows that tree species richness does not consistently improve tree growth responses to drought. The underlying mechanisms remain uncertain, especially under unprecedented multiyear droughts.
View Article and Find Full Text PDFInt J Nanomedicine
September 2025
The First Hospital of Hunan University of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan, People's Republic of China.
Ulcerative colitis (UC) is a chronic inflammatory bowel disease, the incidence of which continues to rise globally, and existing therapeutic options are limited by low drug bioavailability and systemic side effects. In this study, we systematically investigated the challenges of the special gastrointestinal environment of UC patients for oral drug delivery, such as extreme pH, degradation by digestive enzymes, metabolism of intestinal flora and obstruction of the intestinal mucosal barrier, and summarized the potential of plant-derived Exosome-like Nanovesicles (PELNs) as a novel delivery system. PELNs are produced by plant cells and mainly consist of proteins, RNA, lipids and plant active molecules.
View Article and Find Full Text PDFFront Microbiol
August 2025
College of Plant Protection, Southwest University, Chongqing, China.
Root-knot nematodes (RKNs), particularly , are one of the most destructive plant-parasitic nematodes (PPNs) affecting crop production worldwide. Previous earlier study revealed that calcinated oyster shell powder (OSP) possessed excellent suppression of tobacco RKN disease. However, the suppression mechanism of OSP against RKNs still remains unrevealed.
View Article and Find Full Text PDFBayesian Anal
January 2025
Department of Statistics, University of Washington, Seattle, USA.
We introduce the BREASE framework for the Bayesian analysis of randomized controlled trials with binary treatment and outcome. Approaching the problem from a causal inference perspective, we propose parameterizing the likelihood in terms of the aseline isk, fficacy, and dverse ide ffects of the treatment, along with a flexible, yet intuitive and tractable jointly independent beta prior distribution on these parameters, which we show to be a generalization of the Dirichlet prior for the joint distribution of potential outcomes. Our approach has a number of desirable characteristics when compared to current mainstream alternatives: (i) it naturally induces prior dependence between expected outcomes in the treatment and control groups; (ii) as the baseline risk, efficacy and risk of adverse side effects are quantities commonly present in the clinicians' vocabulary, the hyperparameters of the prior are directly interpretable, thus facilitating the elicitation of prior knowledge and sensitivity analysis; and (iii) we provide analytical formulae for the marginal likelihood, Bayes factor, and other posterior quantities, as well as an exact posterior sampling algorithm and an accurate and fast data-augmented Gibbs sampler in cases where traditional MCMC fails.
View Article and Find Full Text PDFJ Appl Stat
February 2025
Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA.
When analyzing real data sets, statisticians often face the question that the data are heterogeneous and it may not necessarily be possible to model this heterogeneity directly. One natural option in this case is to use the methods based on finite mixtures. The key question in these techniques often is what is the best number of mixtures or, depending on the focus of the analysis, the best number of sub-populations when the model is otherwise fixed.
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