Objective: To identify county characteristics associated with high versus low well-being among high-poverty counties.
Design: Observational cross-sectional study at the county level to investigate the associations of 29 county characteristics with the odds of a high-poverty county reporting population well-being in the top quintile versus the bottom quintile of well-being in the USA. County characteristics representing key determinants of health were drawn from the Robert Wood Johnson Foundation County Health Rankings and Roadmaps population health model.
Setting: Counties in the USA that are in the highest quartile of poverty rate.
Main Outcome Measure: Gallup-Sharecare Well-being Index, a comprehensive population-level measure of physical, mental and social health. Counties were classified as having a well-being index score in the top or bottom 20% of all counties in the USA.
Results: Among 770 high-poverty counties, 72 were categorised as having high well-being and 311 as having low well-being. The high-well-being counties had a mean well-being score of 71.8 with a SD of 2.3, while the low-well-being counties had a mean well-being score of 60.2 with a SD of 2.8. Among the six domains of well-being, basic access, which includes access to housing and healthcare, and life evaluation, which includes life satisfaction and optimism, differed the most between high-being and low-well-being counties. Among 29 county characteristics tested, six were independently and significantly associated with high well-being (p<0.05). These were lower rates of preventable hospital stays, higher supply of primary care physicians, lower prevalence of smoking, lower physical inactivity, higher percentage of some college education and higher percentage of heavy drinkers.
Conclusions: Among 770 high-poverty counties, approximately 9% outperformed expectations, reporting a collective well-being score in the top 20% of all counties in the USA. High-poverty counties reporting high well-being differed from high-poverty counties reporting low well-being in several characteristics.
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http://dx.doi.org/10.1136/bmjopen-2019-035645 | DOI Listing |
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Int J Biometeorol
January 2025
West China School of Public Health and West China Fourth Hospital, Sichuan University, Renmin South Road, Chengdu, 610041, China.
Previous studies investigating the influence of hot spring bathing on sleep quality have predominantly focused on the short-term effects through questionnaire surveys without blood collection for biochemical tests. Here, we undertook a comprehensive investigation of the long-term health effects of hot spring bathing among the residents of Hot Spring Village. A total of 140 participants were enrolled, and their demographic characteristics and the patterns of hot spring bathing were obtained via face-to-face interview, and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI).
View Article and Find Full Text PDFSci Rep
January 2025
Business School, Hebei University of Economics and Business, Shijiazhuang, 050062, China.
The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the "dual carbon" goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion model and a carbon footprint model to simulate the carbon footprint of county energy consumption in the YRB. Employing spatial autocorrelation and spatial Durbin models, the study examines the temporal-spatial evolution characteristics and spatial effect mechanism.
View Article and Find Full Text PDFCancer Epidemiol Biomarkers Prev
January 2025
Peking University Cancer Hospital, Beijing, China.
Background: Esophageal squamous cell carcinoma (ESCC) exhibits a long latency period and has a significant geographical disparity in incidence, which underscores the need for models predicting the long-term absolute risk adaptable to regional disease burden.
Methods: 31,883 participants in a large-scale population-based screening trial (Hua County, China) were enrolled to develop the model. Severe dysplasia and above (SDA) identified at screening or follow-up were defined as the outcome.
Rev Cardiovasc Med
January 2025
Department of Cardiology Center, Hebei General Hospital, 050051 Shijiazhuang, Hebei, China.
Background: Heart failure (HF) remains a global challenge with disappointing long-term outcomes. Malnutrition is prevalent in patients with HF and disrupts the equilibrium of immune and inflammatory responses, resulting in further deterioration of the HF. Novel indicators emerge as immune nutrition indices, including the prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), Controlling Nutritional Status (CONUT) score, and cholesterol-modified prognostic nutritional index (CPNI).
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