Publications by authors named "B Neelon"
Article Synopsis
- This study analyzed trends in prepregnancy obesity and gestational weight gain in South Carolina, focusing on racial and ethnic differences during and before the COVID-19 pandemic.
- The research utilized hospital discharge codes and birth certificates from 306,344 full-term births, employing statistical models to assess weight gain adequacy and prepregnancy obesity risks.
- Findings showed an increase in inadequate weight gain across all groups before the pandemic, a stabilization during it, and a rise in prepregnancy obesity primarily among women of "other" races, with no overall changes for Hispanic, Black, and White women.
Background: Many states throughout the United States have introduced Quality Rating and Improvement Systems (QRIS) to address childhood obesity in preschool-age children, but few have examined the impact of these standards in Family Child Care Homes (FCCHs). In South Carolina, the ABC Grow Healthy Practices are specific QRIS items that include diet, physical activity and sleep practices.
Methods: The purposes of this cross-sectional study are to (1) describe physical activity levels, sleep duration and diet quality of children attending FCCHs in South Carolina and (2) compare physical activity levels, sleep duration and diet quality between children attending FCCHs that were enrolled versus not enrolled in the ABC programme.
Although cancer cachexia is classically characterized as a systemic inflammatory disorder, emerging evidence indicates that weight loss also associates with local tissue inflammation. We queried the regulation of this inflammation and its causality to cachexia by exploring skeletal muscle, whose atrophy strongly associates with poor outcomes. Using multiple mouse models and patient samples, we show that cachectic muscle is marked by enhanced innate immunity.
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- Identifying high-risk areas for infectious diseases is crucial for effective public health responses, and this paper introduces a new prediction metric using a Bayesian spatio-temporal model.
- The metric enhances current techniques by combining three key factors: the risk profile of an area, the trend of risk over time, and the influence of neighboring regions, all weighted appropriately for better accuracy.
- Through simulations, the study confirms that local risk and neighborhood effects significantly enhance sensitivity, while trend analysis improves the specificity and overall predictive accuracy of risk assessments, evidenced by its application to COVID-19 data in South Carolina.
Article Synopsis
- The study explored the relationship between reduced cannabis use and improvements in related problems and overall functioning among individuals in treatment for cannabis use disorder.
- Data from seven treatment trials with 920 participants were analyzed using various outcome measures to assess changes in cannabis use and associated improvements.
- Findings indicated that a significant reduction in cannabis use (approximately 50% fewer days and 75% less amount used) correlated with positive outcomes in clinician assessments, suggesting that decreasing cannabis consumption could benefit those with use disorder.