ABSTRACT
Objectives@#Coronavirus disease 2019 (COVID-19) is classified as a natural hazard, and social vulnerability describes the susceptibility of social groups to potential damages from natural hazards. Therefore, the objective of this study was to examine the association between social vulnerability and the cumulative number of confirmed COVID-19 deaths (per 100,000) in 3,141 United States counties. @*Methods@#The cumulative number of COVID-19 deaths was obtained from USA Facts. Variables related to social vulnerability were obtained from the Centers for Disease Control and Prevention Social Vulnerability Index and the 2018 5-Year American Community Survey. Data were analyzed using spatial autoregression models. @*Results@#Lowest income and educational level, as well as high proportions of single parent households, mobile home residents, and people without health insurance were positively associated with a high cumulative number of COVID-19 deaths. @*Conclusion@#In conclusion, there are regional differences in the cumulative number of COVID-19 deaths in United States counties, which are affected by various social vulnerabilities. Hence, these findings underscore the need to take social vulnerability into account when planning interventions to reduce COVID-19 deaths.
ABSTRACT
Objectives@#Coronavirus disease 2019 (COVID-19) is classified as a natural hazard, and social vulnerability describes the susceptibility of social groups to potential damages from natural hazards. Therefore, the objective of this study was to examine the association between social vulnerability and the cumulative number of confirmed COVID-19 deaths (per 100,000) in 3,141 United States counties. @*Methods@#The cumulative number of COVID-19 deaths was obtained from USA Facts. Variables related to social vulnerability were obtained from the Centers for Disease Control and Prevention Social Vulnerability Index and the 2018 5-Year American Community Survey. Data were analyzed using spatial autoregression models. @*Results@#Lowest income and educational level, as well as high proportions of single parent households, mobile home residents, and people without health insurance were positively associated with a high cumulative number of COVID-19 deaths. @*Conclusion@#In conclusion, there are regional differences in the cumulative number of COVID-19 deaths in United States counties, which are affected by various social vulnerabilities. Hence, these findings underscore the need to take social vulnerability into account when planning interventions to reduce COVID-19 deaths.
ABSTRACT
Objectives@#The objective of this study was to determine the association between e-cigarette use and depression and examine how this association is different by gender among US adults. @*Methods@#Data from the 2017 Behavioral Risk Factor Surveillance System and Selected Metropolitan/ Micropolitan Area Risk Trends was used, and included 174,351 of 230,875 US adults aged 18 years and older. Data were analyzed using the multivariate logistic regression models. @*Results@#After adjusting for age, race, education, income, marital status, employment status, smoking status, and physical activity, firstly, “current daily e-cigarette users” (AOR = 2.487, p < 0.001), “current non-daily e-cigarette users” (AOR = 1.623, p < 0.001), and “former e-cigarette users” (AOR = 1.573, p < 0.001) were associated with increased odds of depression compared with “never e-cigarette users.”Secondly, women were associated with increased odds of depression compared with men (AOR = 1.797, p < 0.001). Finally, male “current daily e-cigarette users” (AOR = 1.366, p < 0.01) were associated with increased odds of depression compared with female “never e-cigarette users.” @*Conclusion@#Thus, even though women tend to be more vulnerable to depression compared with men, e-cigarette use was positively associated with depression among both men and women.
ABSTRACT
OBJECTIVES: The objective of this study was to examine the socio-demographic disparities in obesity among US adults across 130 metropolitan and micropolitan statistical areas. METHODS: This study used data from the 2015 Behavioral Risk Factor Surveillance System and Selected Metropolitan/Micropolitan Area Risk Trend of 159,827 US adults aged 18 years and older. Data were analyzed using the multilevel linear regression models. RESULTS: According to individual level analyses, socio-demographic disparities in obesity exist in the United States. Individuals with low socioeconomic status were associated with a higher body mass index. The participants from the Midwest United States tend to have higher body mass index than those who from the South. According to metropolitan and micropolitan statistical area level analyses, secondly, there were significant differences in obesity status between different areas and the relation of obesity with 5 socio-demographic factors varied across different areas. According to geospatial mapping analyses, even though obesity status by metropolitan and micropolitan statistical area level has improved overtime, differences in body mass index between United States regions are increasing from 2007 to 2015. CONCLUSION: Socio-demographic and regional disparities in obesity status persist among US adults. Hence, these findings underscore the need to take socio-environmental factors into account when planning obesity prevention on vulnerable populations and areas.