RESUMO
BACKGROUND: A clear understanding of public perceptions of the social determinants of health remains lacking. This paper aimed to describe the relationship between income and urbanicity levels and public views of the determinants of health in eight middle-and high-income countries that varied across multiple characteristics. METHODS: We conducted a cross-sectional online survey in Brazil, China, Germany, Egypt, India, Indonesia, Nigeria, and the United States. Respondents were asked to select what they considered to be most important for health out of a list of ten determinants. We stratified the results by income and urbanicity levels and tested significance of differences between groups using two-tailed χ2 tests. Multivariable logistic regression models tested associations between demographic factors and the likelihood of respondents selecting the genetics, healthcare, income and wealth, or social support determinants. RESULTS: Here we show 8753 respondents across eight countries. Rankings of determinants are similar across income groups, except for two determinants. Respondents in the highest income group rank genetics in higher proportions (32.4%, 95%CI: 29.0%,35.8%) compared to other income groups. Conversely, those in lowest income group rank social support more frequently (27.9%, 95%CI: 25.3%,30.7%) than other income groups. Those living in urban settings rank healthcare in higher proportions (61.2%, 95%CI: 59.0%,63.4%) compared to non-urban respondents; meanwhile, higher proportions (26.6%, 95%CI: 24.9%,28.3%) of non-urban respondents rank social support as important for health compared to urban respondents. CONCLUSION: Demographic factors play a role in shaping public views of what affects health. Advancing public understanding about determinants of health requires tailoring public health messaging to account for socioeconomic position within a population.
Various factors determine our health, such as our environment, education, and genetics. Here, we explore how people from different income and urban backgrounds view the factors that affect health. We surveyed participants from Brazil, China, Germany, Egypt, India, Indonesia, Nigeria, and the United States. Respondents selected the most important factors for health from a list of ten choices. Overall, people's views on these factors were comparable across income groups, with exceptions. Those with higher incomes tended to emphasize the importance of genetics more, while lower-income individuals valued social support. People in urban areas prioritized healthcare, while those in non-urban areas valued social support. These findings suggest that factors such as income and where people live influence their views about health determinants. These factors should be considered in public health messaging and strategies to promote health amongst different groups.
RESUMO
BACKGROUND: Studies from early in the COVID-19 pandemic showed that patients with ischemic stroke and concurrent SARS-CoV-2 infection had increased stroke severity. We aimed to test the hypothesis that this association persisted throughout the first year of the pandemic and that a similar increase in stroke severity was present in patients with hemorrhagic stroke. METHODS: Using the National Institute of Health National COVID Cohort Collaborative (N3C) database, we identified a cohort of patients with stroke hospitalized in the United States between March 1, 2020 and February 28, 2021. We propensity score matched patients with concurrent stroke and SARS-COV-2 infection and available NIH Stroke Scale (NIHSS) scores to all other patients with stroke in a 1:3 ratio. Nearest neighbor matching with a caliper of 0.25 was used for most factors and exact matching was used for race/ethnicity and site. We modeled stroke severity as measured by admission NIHSS and the outcomes of death and length of stay. We also explored the temporal relationship between time of SARS-COV-2 diagnosis and incidence of stroke. RESULTS: Our query identified 43,295 patients hospitalized with ischemic stroke (5765 with SARS-COV-2, 37,530 without) and 18,107 patients hospitalized with hemorrhagic stroke (2114 with SARS-COV-2, 15,993 without). Analysis of our propensity matched cohort revealed that stroke patients with concurrent SARS-COV-2 had increased NIHSS (Ischemic stroke: IRR=1.43, 95% CI:1.33-1.52, p<0.001; hemorrhagic stroke: IRR=1.20, 95% CI:1.08-1.33, p<0.001), length of stay (Ischemic stroke: estimate = 1.48, 95% CI: 1.37, 1.61, p<0.001; hemorrhagic stroke: estimate = 1.25, 95% CI: 1.06, 1.47, p=0.007) and higher odds of death (Ischemic stroke: OR 2.19, 95% CI: 1.79-2.68, p<0.001; hemorrhagic stroke: OR 2.19, 95% CI: 1.79-2.68, p<0.001). We observed the highest incidence of stroke diagnosis on the same day as SARS-COV-2 diagnosis with a logarithmic decline in counts. CONCLUSION: This retrospective observational analysis suggests that stroke severity in patients with concurrent SARS-COV-2 was increased throughout the first year of the pandemic.