Key Points Question What are the changes in the rural-urban distribution of the primary care workforce in the US from 2009 to 2017? Findings In this cross-sectional study of 3143 US counties (1167 urban and 1976 rural) using county-level data, the density of primary care clinicians increased significantly in both rural and urban counties from 2009 to 2017. The increase in primary care clinician density was more pronounced in urban counties compared with rural counties. Meaning In this study, the density of primary care clinicians increased overall, yet rural-urban disparities in the primary care workforce are increasing in the US.

Chronic disease and opioid-related hospitalizations in the United States are increasing. We analyzed nationally representative data on patients aged 18 years or older from the 2011–2015 National Inpatient Sample to assess the association between opioid-related hospitalization and chronic diseases. We found that most patients with opioid-related hospitalization were white, aged 35–54 years, in urban hospitals, and had 2 or more comorbid conditions. Patients with 2 or more chronic conditions accounted for more than 90% of opioid-related hospitalizations in all years. The results suggest a need for targeted interventions to prevent opioid misuse in patients with multiple chronic conditions.

Introduction: Previous studies have reported a "weekend effect" on stroke mortality, whereby stroke patients admitted during weekends have a higher risk of in-hospital death than those admitted during weekdays. Aims:We aimed to investigate whether patients with different types of stroke admitted during weekends have a higher risk of in-hospital mortality in rural and urban hospitals in the US. Methods:We used data from the 2016 National Inpatient Sample and used logistic regression to assess in-hospital mortality for weekday and weekend admissions among stroke patients aged 18 and older by stroke type (ischemic or hemorrhagic) and rural or urban status.Results: Crude stroke mortality was higher in weekend admissions (p <0.001). After adjusting for confounding variables, in-hospital mortality among hemorrhagic stroke patients was significantly greater (22.0%) for weekend admissions compared to weekday admissions (20.2%, p

BackgroundStudents live outside of their family homes for the first time in college and are expected to make their own decisions regarding dietary choices. College food environment could be a major determinant of dietary intake and is of importance in relation to obesity. This research determines the impact of removing cafeteria trays on student’s food choice.MethodA quasi experimental pre-post research with control treatment was conducted in university dining halls. The participants were the dining hall patrons at a large public university in Southern US, spring 2015. The dining hall trays were removed from the intervened dining hall for five consecutive days during regular university session. Outcome measures of food choice were collected by observing tray waste before and after the tray removal in the intervened dining hall with parallel observation in the control dining hall. Difference-in-difference analysis was done to find the intervention effect.ResultsA total of 3153 trays were observed (N = 1564 in control and N = 1589 in intervention dining). Removal of trays resulted in a significant decrease in the total number of lunch plates (1.76 vs 1.66 servings, p < .006), drink glasses (1.32 vs 1.02 servings, p < .0001), dishes with leftovers (0.56 vs 0.39 serving, P < .001), and lunch plates with leftovers (0.51 vs 0.35 servings, p < .005).ConclusionsStudent food choices can be affected by removing trays from dining halls, specifically favoring fewer beverages, and without sacrificing salad consumption. Studies with more precise measures of tray waste are needed to understand the direct effect on energy and nutrient consumption.

Background Disparities in cardiovascular disease (CVD) outcomes persist across the United States. Social determinants of health play an important role in driving these disparities. The current study aims to identify the most important social determinants associated with CVD mortality over time in US counties. Methods and Results The authors used the Agency for Healthcare Research and Quality's database on social determinants of health and linked it with CVD mortality data at the county level from 2009 to 2018. The age‐standardized CVD mortality rate was measured as the number of deaths per 100 000 people. Penalized generalized estimating equations were used to select social determinants associated with county‐level CVD mortality. The analytic sample included 3142 counties. The penalized generalized estimating equation identified 17 key social determinants of health including rural–urban status, county's racial composition, income, food, and housing status. Over the 10‐year period, CVD mortality declined at an annual rate of 1.08 (95% CI, 0.74–1.42) deaths per 100 000 people. Rural counties and counties with a higher percentage of Black residents had a consistently higher CVD mortality rate than urban counties and counties with a lower percentage of Black residents. The rural–urban CVD mortality gap did not change significantly over the past decade, whereas the association between the percentage of Black residents and CVD mortality showed a significant diminishing trend over time. Conclusions County‐level CVD mortality declined from 2009 through 2018. However, rural counties and counties with a higher percentage of Black residents continued to experience higher CVD mortality. Median income, food, and housing status consistently predicted higher CVD mortality.