Objective: To examine the association between bodyweight status and provision of population-based prevention services.
Data Sources: The National Association of City and County Health Officials 2005 Profile survey data, linked with two cross-sections of the Behavioral Risk Factor Surveillance System (BRFSS) survey in 2004 and 2005.
Study Design: Multilevel logistic regressions were used to examine the association between provision of obesity-prevention services and the change in risk of being obese or morbidly obese among BRFSS respondents. The estimation sample was stratified by sex. Low-income samples were also examined. Falsification tests were used to determine whether there is counterevidence.
Principal Findings: Provision of population-based obesity-prevention services within the jurisdiction of local health departments and specifically those provided by the local health departments are associated with reduced risks of obesity and morbid obesity from 2004 to 2005. The magnitude of the association appears to be stronger among low-income populations and among women. Results of the falsification tests provide additional support of the main findings.
Conclusions: Population-based obesity-prevention services may be useful in containing the obesity epidemic.
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http://dx.doi.org/10.1111/j.1475-6773.2012.01447.x | DOI Listing |
Am J Respir Cell Mol Biol
January 2025
Duke Medicine, Medicine, Durham, North Carolina, United States.
Becoming more frequent due to climate change, ozone (O) exposures can cause lung injury. Alveolar type 2 (AT2) cells and hyaluronan (HA), a matrix component, are critical to repairing lung injury and restoring homeostasis. Here, we define the impact of HA on AT2 cells following acute O exposure.
View Article and Find Full Text PDFAm J Respir Cell Mol Biol
January 2025
Rostock University Medical Center, Institute of Medical Microbiology, Virology and Hygiene, Rostock, Germany.
(Group A Streptococcus, GAS) is a human pathogen that causes local and systemic infections of the skin and mucous membranes. However, GAS is also found asymptomatically in the nasopharynx of infants. GAS infections, including pharyngitis and invasive pneumosepsis, pose significant public health concerns.
View Article and Find Full Text PDFJ Clin Oncol
January 2025
Aaron J. Scott, MD, University of Arizona Cancer Center, Tucson, AZ; Erin B. Kennedy, MHSc, American Society of Clinical Oncology, Alexandria, VA; and Sepideh Gholami, MD, MAS, Northwell Health, New Hyde Park, NY.
JCO Oncol Pract
January 2025
Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA.
Purpose: National Comprehensive Cancer Network Guidelines recommend initiating postoperative radiation therapy (PORT) within 6 weeks of surgery for patients with head and neck squamous cell carcinoma (HNSCC), but delays affect 50% of patients, disproportionately burden minoritized groups, and contribute to worse oncologic outcomes. This trial evaluates the efficacy of Navigation for Disparities and Untimely Radiation thErapy (NDURE), an enhanced navigation-based intervention, relative to usual care (UC) patient navigation for starting timely PORT.
Methods: Adults with locally advanced HNSCC planning to undergo surgery and PORT were randomly assigned 1:1 to standard multidisciplinary head and neck oncology care and either NDURE, a multilevel navigation-based intervention to enhance key processes of care and overcome barriers to timely PORT, or UC, which consisted of standard patient navigation.
Health Aff (Millwood)
January 2025
Jordan Everson, Office of the Assistant Secretary for Technology Policy, Washington, D.C.
Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES. We analyzed data from the 2023 American Hospital Association Annual Survey Information Technology Supplement to identify how AI and predictive models are used and evaluated for accuracy and bias in hospitals. Hospitals use AI and predictive models to predict health trajectories or risks for inpatients, identify high-risk outpatients to inform follow-up care, monitor health, recommend treatments, simplify or automate billing procedures, and facilitate scheduling.
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