Health Disparities in COVID-19: Addressing the Role of Social Determinants of Health in Immune System Dysfunction to Turn the Tide

Baumer, Yvonne; Farmer, Nicole; Premeaux, Thomas A.; Wallen, Gwenyth R.; Powell‐Wiley, Tiffany M.

doi:10.3389/fpubh.2020.559312

Cited by 22 publications

(26 citation statements)

References 124 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These factors disproportionately affect minorities [11] , placing them at high risk of Covid-19 infection and mortality [ 4 , 7 ]. Clinically it has been postulated that the stress levels due to low socioeconomic status, social inequalities, and unhealthy behaviors increase cytokine interleukin-6 (IL-6) and immune system dysfunction, which trigger Covid-19 complications [12] .…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

Paul

Adeyemi

Ghosh

et al. 2021

Annals of Epidemiology

View full text Add to dashboard Cite

Purpose To determine the association of social factors with Covid-19 mortality and identify high-risk clusters. Methods Data on Covid-19 deaths across 3,108 contiguous U.S. counties from the Johns Hopkins University and social determinants of health (SDoH) data from the County Health Ranking and the Bureau of Labor Statistics were fitted to Bayesian semi-parametric spatiotemporal Negative Binomial models, and 95% credible intervals (CrI) of incidence rate ratios (IRR) were used to assess the associations. Exceedance probabilities were used for detecting clusters. Results As of October 31, 2020, the median mortality rate was 40.05 per 100, 000. The monthly urban mortality rates increased with unemployment (IRR adjusted :1.41, 95% CrI: 1.24, 1.60), percent Black population (IRR adjusted :1.05, 95% CrI: 1.04, 1.07), and residential segregation (IRR adjusted :1.03, 95% CrI: 1.02, 1.04). The rural monthly mortality rates increased with percent female population (IRR adjusted : 1.17, 95% CrI: 1.11, 1.24) and percent Black population (IRR adjusted :1.07 95% CrI:1.06, 1.08). Higher college education rates were associated with decreased mortality rates in rural and urban counties. The dynamics of exceedance probabilities detected the shifts of high-risk clusters from the Northeast to Southern and Midwestern counties. Conclusions Spatiotemporal analyses enabled the inclusion of unobserved latent risk factors and aid in scientifically grounded decision-making at a granular level.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

Paul

Adeyemi

Ghosh

et al. 2021

Annals of Epidemiology

View full text Add to dashboard Cite

show abstract

“…32 Access to an adequate diet is influenced by multiple parameters such as socioeconomic status or neighbourhood environment. 33 …”

Section: Discussionmentioning

confidence: 99%

“…32 Access to an adequate diet is influenced by multiple parameters such as socioeconomic status or neighbourhood environment. 33 During the first wave of the COVID-19 epidemic in Spain, social services were also overwhelmed and many local associations had to help to meet essential and home care needs to ensure a minimum level of welfare for large sections of the population. 34 The COVID-19 pandemic has highlighted the need to reinforce local administrations and to continue providing social services and programmes for engaging and supporting patients, especially the most vulnerable such as older adults, during this difficult time of physical distancing and stay-at-home orders.…”

Section: Open Accessmentioning

confidence: 99%

How patients with COVID-19 managed the disease at home during the first wave in Spain: a cross-sectional study

et al. 2021

View full text Add to dashboard Cite

ObjectiveMost patients with mild COVID-19 had to stay at home trying to implement an optimal quarantine. The aim of this study was to describe the COVID-19 cases during the first wave of the pandemic in Spain, how they managed the disease at home, focusing on differences by age, as well as differences in knowledge, attitudes and preventive practices, compared with the uninfected population.DesignAn online survey was used to conduct a cross-sectional study of individuals who were 14 years or older living in Spain during the COVID-19 lockdown. The main variable was a COVID-19 case. Logistic regression models for COVID-19 cases were obtained using a backward stepwise procedure to assess the association between social variables, disease knowledge, attitudes, prevention practices and emotional impact.Results3398 people completed the survey. Participants’ mean age was 49.6 (SD=14.3). COVID-19 was significantly more prevalent among married people (5.3%) and those currently doing an on-site work (8.7%). Most of the COVID-19 cases stayed at home (84.0%) during the episode. There were significant age-based differences with regard to self-isolation conditions at home during the disease. COVID-19 cases showed better attitudes, practices and knowledge about disease symptoms and transmission than the uninfected population. COVID-19 cases also felt more depressed (adjusted OR: 3.46, 95% CI 1.45 to 8.26) and had better preventive behaviour than the uninfected population, such as always wearing a mask outside the home (adjusted OR 1.58, 95% CI 1.06 to 2.30).ConclusionCOVID-19 cases found it difficult to comply with recommended home self-isolation conditions, with differences by age group. COVID-19 had an important impact on care dependency in non-hospitalised patients, who were mostly dependent on their families for care. It is necessary to reinforce social and health services and to be ready to meet the care needs of populations during the different waves or in future epidemics.

show abstract

“…Seligman et al also found high incidence of deaths among individuals of non-white ethnicity, less than high school level of education, and veterans. Baumer et al (2020) add poor living conditions and neighborhood deprivation because they inflict psychosocial stress of individuals and cause immune system disfunction.…”

Section: Literature Reviewmentioning

confidence: 99%

The Use of Decision Trees for Analysis of the Potential Determinants for the Incidence of Deaths and Cases of Coronavirus (Covid-19) in Different Countries

Wyrobek¹

2020

ERSJ

View full text Add to dashboard Cite

Purpose: The objective of this paper is to identify the key economic factors determining the intensity of COVID virus infections and deaths in various countries. Design/Methodology/Approach: The publication uses the methods of k-means clustering, knearest neighbors algorithm, DBSCan algorithm to divide countries into different groups in terms of the level of disease and death from COVID. The decision tree analysis provided potential determinants for the severity of the pandemic in different regions of the world. We analyzed 211 countries. As potential determinants, we examined the following factors: average temperature, average precipitation, GDP per capita, population density (in 2018), hospital beds per 1.000 citizens, doctors per 1.000 citizens, share of people aged 65 years or above, pollution (based on the PM2.5 indicator from The World Bank), total tests per 1.000 citizens and health expenditure as a percentage of GDP. Findings: Our analysis revealed that the COVID pandemic intensity in analyzed countries depends on the number of doctors, population density, average temperature, total tests per 1.000 citizens, and GDP per capita by using data from the World Bank. Practical Implications: Research suggests that the efficient healthcare system supports immunological response of population to the COVID virus. Another critical factor is the density of population. These two factors proved to play a critical role in determining the level of the COVID cases in deaths in various countries. Nevertheless, countries with the lowest GDP per capita had very low levels of COVID cases, which suggests that either they do not recognize COVID patients correctly or they will experience the pandemic with time delay. Originality/value: Economic factors proved to be good predictors of the COVID virus development in the analyzed countries, however, contrary to expectations, countries with low GDP per capita so far suffered the least from the COVID virus pandemic.

show abstract

Health Disparities in COVID-19: Addressing the Role of Social Determinants of Health in Immune System Dysfunction to Turn the Tide

Cited by 22 publications

References 124 publications

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

How patients with COVID-19 managed the disease at home during the first wave in Spain: a cross-sectional study

The Use of Decision Trees for Analysis of the Potential Determinants for the Incidence of Deaths and Cases of Coronavirus (Covid-19) in Different Countries

Contact Info

Product

Resources

About