Previous studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities. This cross-sectional study used county-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by the COVID-19 Community Vulnerability Index (CCVI). Effect estimates of COVID-19 fatality rates for risk factors such as comorbidities, sociodemographic factors and determinant of health. Factors associated with reducing COVID-19 fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influenced case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and chronic obstructive pulmonary disease (COPD) diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of chronic kidney disease (CKD) within counties were often the strongest predictor of increased case-fatality rates for several regions. Our findings highlight the importance of considering the full context when evaluating contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.

The emergence of COVID-19 virus has led to a pandemic with staggering morbidity and mortality. There is evidence showing that pre-existing conditions and environmental factors are associated with worse COVID-19 outcomes. Among these conditions, altitude is of particular interest. Altitude has been shown to influence the morbidity and mortality of multiple chronic pathologies such as cardiovascular disease, chronic obstructive pulmonary disease and lung cancer. COVID-19 fatality rate has been associated with as altitude as well, but findings are disputed. Therefore, we revisit this assessment with a comprehensive analysis of the relationship between COVID-19 fatality rates and altitude for the Mountain region of the United States while considering the effect of additional comorbidities and sociodemographic factors. A Generalized Additive Model (GAM) approach using one year of county data adjusted by population density was performed to evaluate associations within states and for the whole region. Our analysis revealed a consistent effect where COVID-19 case-fatality rate is decreased with higher altitude, even when controlling for pre-existing conditions and certain demographic variables. In summary, the work presented provides evidence that suggests that the protective effects of high altitude are likely to be influenced by physiologic factors but demographic trends that are associated with life at high altitude must also be considered.

IntroductionPrevious studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities.MethodsCounty-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by CCVI.ResultsFactors associated with reducing COVID-19 case fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influences case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and COPD diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of CKD within counties were often the strongest predictor of increased case-fatality rates for several regions.ConclusionOur findings highlight the importance of considering the full context when evaluating contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.

The objective of this study was to evaluate the impact of selected sociodemographic factors on childhood vaccination hesitancy and to define their role according to specific exemptions. This population-based cohort study utilized vaccination rate and sociodemographic data from 1st to 12th grade from 2017 to 2021 for all school districts in Colorado. Data included immunization status and exemptions for each vaccine, race, ethnicity, and free and reduced meal status. Data were evaluated through dimensional analysis and Generalized Linear Mixed Models. School districts with a higher representation of White students had lower immunization rates and use more personal exemptions while school districts with larger Hispanic populations and higher proportions of free and reduced lunches had higher vaccination rates and used more religious exemptions. Black and Pacific Islander populations had higher rates of incomplete vaccination records while Asian American population displayed increased vaccination compliance. Colorado is a robust example of how socioeconomic and cultural differences are important factors with a direct influence on vaccination rates. Future childhood vaccination campaigns and legislation should consider complex socioeconomic and cultural factors.