Unveiling Spatial Associations between COVID-19 Severe Health Index, Racial/Ethnic Composition, and Community Factors in the United States.

There are limited efforts to incorporate different predisposing factors into prediction models that account for population racial/ethnic composition in exploring the burden of high COVID-19 Severe Health Risk Index (COVID-19 SHRI) scores. This index quantifies the risk of severe COVID-19 symptoms among a county's population depending on the presence of some chronic conditions. These conditions, as identified by the Centers for Disease Control and Prevention (CDC), include Chronic Obstructive Pulmonary Disease (COPD), heart disease, high blood pressure, diabetes, and obesity. Therefore, the objectives of this study were (1) to investigate potential population risk factors preceding the COVID-19 pandemic that are associated with the COVID-19 SHRI utilizing non-spatial regression models and (2) to evaluate the performance of spatial regression models in comparison to non-spatial regression models. The study used county-level data for 3107 United States counties, utilizing publicly available datasets. Analyses were carried out by constructing spatial and non-spatial regression models. Majority White and majority Hispanic counties showed lower COVID-19 SHRI scores when compared to majority Black counties. Counties with an older population, low income, high smoking, high reported insufficient sleep, and a high percentage of preventable hospitalizations had higher COVID-19 SHRI scores. Counties with better health access and internet coverage had lower COVID-19 SHRI scores. This study helped to identify the county-level characteristics of risk populations to help guide resource allocation efforts. Also, the study showed that the spatial regression models outperformed the non-spatial regression models. Racial/ethnic inequalities were associated with disparities in the burden of high COVID-19 SHRI scores. Therefore, addressing these factors is essential to decrease inequalities in health outcomes. This work provides the baseline typology to further explore many social, health, economic, and political factors that contribute to different health outcomes.

Increased School Breakfast Participation from Policy and Program Innovation: The Community Eligibility Provision and Breakfast after the Bell.

School meals provide significant access to food and nutrition for children and adolescents, particularly through universal free meal mechanisms. Alongside added nutritional meal requirements under the Healthy, Hunger-Free Kids Act (2010), schools can utilize meal program and policy mechanisms such as the Community Eligibility Provision (CEP) and Breakfast after the Bell (BATB) to increase participation. This study examines longitudinal statewide school-level CEP and BATB adoption and estimates the impact on increased free and reduced-price (FRP) breakfast participation. We find that FRP breakfast participation increased for schools that utilize both CEP and BATB (14-percentage-point increase) and that CEP-participating schools are more likely to use BATB approaches such as breakfast in the classroom, grab-and-go carts, and second-chance breakfast. Additionally, using a conditional Difference-in-Differences (DiD) approach, we find that BATB adoption accounted for a 1.4-percentage-point increase in FRP school breakfasts served (p < 0.05). Study findings can inform policy and school official decision making around the policy and program mechanisms at their disposal to increase school meal participation and student nutrition.

Behavioral risk factors and Latino body mass index: a cross-sectional study in Missouri.

Obesity is the fastest-growing cause of disease and death in the United States, with minority populations suffering some of the most severe consequences. Latinos constitute 16% of the U.S. population as of 2010, and have a higher proportion of the population that is overweight and obese compared with their non-Hispanic Black and White counterparts. Although there are over 15.8 million Latino residents living in non-gateway states (outside California, Texas, Arizona, Illinois, and New York), there is little research exploring obesity factors among Latinos outside of gateway states. The aim of this paper was to study socio-economic characteristics, mental health, insurance status, physical activity, and fruit and vegetable consumption, in relation to body mass index (BMI) among Latinos living in a non-gateway state. The results showed that income, employment status, marital status, insurance status, physical activity, fruit and vegetable consumption, and mental health were all associated with BMI.