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2.
Prev Chronic Dis ; 17: E119, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-33006541

RESUMO

INTRODUCTION: Little is known about the social needs of low-income households with children during the coronavirus-2019 (COVID-19) pandemic. Our objective was to conduct a cross-sectional quantitative and qualitative descriptive analysis of a rapid-response survey among low-income households with children on social needs, COVID-19-related concerns, and diet-related behaviors. METHODS: We distributed an electronic survey in April 2020 to 16,435 families in 4 geographic areas, and 1,048 responded. The survey asked families enrolled in a coordinated school-based nutrition program about their social needs, COVID-19-related concerns, food insecurity, and diet-related behaviors during the pandemic. An open-ended question asked about their greatest concern. We calculated descriptive statistics stratified by location and race/ethnicity. We used thematic analysis and an inductive approach to examine the open-ended comments. RESULTS: More than 80% of survey respondents were familiar with COVID-19 and were concerned about infection. Overall, 76.3% reported concerns about financial stability, 42.5% about employment, 69.4% about food availability, 31.0% about housing stability, and 35.9% about health care access. Overall, 93.5% of respondents reported being food insecure, a 22-percentage-point increase since fall 2019. Also, 41.4% reported a decrease in fruit and vegetable intake because of COVID-19. Frequency of grocery shopping decreased and food pantry usage increased. Qualitative assessment identified 4 main themes: 1) fear of contracting COVID-19, 2) disruption of employment status, 3) financial hardship, and 4) exacerbated food insecurity. CONCLUSION: Our study highlights the compounding effect of the COVID-19 pandemic on households with children across the spectrum of social needs.


Assuntos
Economia/estatística & dados numéricos , Abastecimento de Alimentos , Determinação de Necessidades de Cuidados de Saúde , Pobreza , Determinantes Sociais da Saúde , Betacoronavirus , Criança , Infecções por Coronavirus/economia , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Inquéritos sobre Dietas , Emprego/estatística & dados numéricos , Características da Família , Feminino , Abastecimento de Alimentos/métodos , Abastecimento de Alimentos/normas , Humanos , Masculino , Pandemias/economia , Pandemias/prevenção & controle , Pneumonia Viral/economia , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Pobreza/economia , Pobreza/estatística & dados numéricos , Serviços de Saúde Escolar/estatística & dados numéricos , Estados Unidos/epidemiologia
5.
Medicine (Baltimore) ; 99(38): e22245, 2020 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-32957371

RESUMO

BACKGROUND: CMS recently decided to produce private "healthcare disparities reports" that include dual eligibility (DE) as the sole stratifying variable used to assess pneumonia readmission disparities. RESEARCH DESIGN: We measure the relationship between DE status and readmissions, both with and without conceptually relevant social risk factors, including air pollution, severe housing problems, and food insecurity, using data from county- and hospital-level readmission rates, DE status, and social risk factors. RESULTS: At the county level, the relationship between DE status and readmissions is partially confounded by at least three social risk factors. DE populations vary widely across hospitals, creating unequal between-hospital comparisons. CONCLUSIONS: Because of differences in the DE population, between-hospital comparisons could be misleading using a methodology that stratifies by DE only. We suggest viable alternatives to sole-factor stratification to properly account for social risk factors and better isolate quality differences that might yield readmission rate inequities. IMPLICATIONS: CMS's healthcare disparities reports provided to hospitals are limited by relying exclusively on DE proportion as the measure of social risk, undercutting the power of quality measurement and its related incentives to close or minimize healthcare inequities.


Assuntos
Definição da Elegibilidade , Disparidades em Assistência à Saúde , Medicaid/organização & administração , Medicare/organização & administração , Determinantes Sociais da Saúde , Poluição do Ar/efeitos adversos , Abastecimento de Alimentos , Habitação , Humanos , Readmissão do Paciente , Pneumonia/terapia , Fatores de Risco , Estados Unidos
9.
Rev Panam Salud Publica ; 44, sept. 2020
Artigo em Inglês | PAHO-IRIS | ID: phr-52265

RESUMO

[ABSTRACT]. Objective. To identify socioeconomic factors associated with antimicrobial resistance of Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli in Chilean hospitals (2008–2017). Methods. We reviewed the scientific literature on socioeconomic factors associated with the emergence and dissemination of antimicrobial resistance. Using multivariate regression, we tested findings from the literature drawing from a longitudinal dataset on antimicrobial resistance from 41 major private and public hospitals and a nationally representative household survey in Chile (2008–2017). We estimated resistance rates for three priority antibiotic–bacterium pairs, as defined by the Organisation for Economic Co-operation and Development; i.e., imipenem and meropenem resistant P. aeruginosa, cloxacillin resistant S. aureus, and cefotaxime and ciprofloxacin resistant E. coli. Results. Evidence from the literature review suggests poverty and material deprivation are important risk factors for the emergence and transmission of antimicrobial resistance. Most studies found that worse socioeconomic indicators were associated with higher rates of antimicrobial resistance. Our analysis showed an overall antimicrobial resistance rate of 32.5%, with the highest rates for S. aureus (40.6%) and the lowest for E. coli (25.7%). We found a small but consistent negative association between socioeconomic factors (income, education, and occupation) and overall antimicrobial resistance in univariate (p < 0.01) and multivariate analyses (p < 0.01), driven by resistant P. aeruginosa and S. aureus. Conclusion. Socioeconomic factors beyond health care and hospital settings may affect the emergence and dissemination of antimicrobial resistance. Preventing and controlling antimicrobial resistance requires efforts above and beyond reducing antibiotic consumption.


[RESUMEN]. Objetivo. Determinar los factores socioeconómicos relacionados con la resistencia a los antimicrobianos de Pseudomona aeruginosa, Staphylococcus aureus y Escherichia coli en hospitales chilenos (2008-2017). Métodos. Se revisó la bibliografía científica acerca de los factores socioeconómicos relacionados con la aparición y el incremento de la resistencia a los antimicrobianos. Mediante una regresión con múltiples variables se examinaron los resultados de la bibliografía respecto a un conjunto de datos longitudinales sobre resistencia a los antimicrobianos de 41 importantes hospitales privados y públicos, así como a una encuesta domiciliaria representativa a nivel nacional en Chile (2008-2017). Se estimaron las tasas de resistencia para tres pares de antibióticos y bacterias prioritarios, de conformidad con lo definido por la Organización de Cooperación y Desarrollo Económicos, es decir: P. aeruginosa, resistente a imipenem y meropenem; S. aureus, resistente a cloxacilina y E. coli, resistente a la cefotaxima y ciprofloxacino. Resultados. La evidencia de la revisión bibliográfica es indicativa de que la pobreza y la privación material suponen importantes factores de riesgo para la aparición y transmisión de la resistencia a los antimicrobianos. La mayoría de los estudios ha demostrado que los peores indicadores socioeconómicos están asociados a mayores tasas de resistencia a los antimicrobianos. Este análisis ha indicado una tasa general de resistencia a los antimicrobianos de 32,5 %, con las tasas más elevadas para S. aureus (40,6 %) y las más bajas para E. coli (25,7 %). Se apreció una asociación negativa mínima, aunque uniforme, entre los factores socioeconómicos (ingresos, educación y ocupación) y la resistencia general a los antimicrobianos en un análisis de variable única (p < 0,01) y análisis multifactoriales (p < 0,01), impulsadas por las bacterias P. aeruginosa y S. aureus resistentes. Conclusiones. Los factores socioeconómicos no relacionados con la atención de la salud y los entornos hospitalarios pueden afectar la aparición y la propagación de la resistencia a los antimicrobianos. Su prevención y control precisan esfuerzos adicionales que se sumen a la reducción del consumo de antibióticos.


[RESUMO]. Objetivo. Identificar os fatores socioeconômicos associados à resistência antimicrobiana de Pseudomonas aeruginosa, Staphylococcus aureus e Escherichia coli em hospitais chilenos (2008-2017). Métodos. Fizemos uma revisão da literatura científica sobre os fatores socioeconômicos associados ao surgimento e à disseminação da resistência antimicrobiana. Usando a regressão multivariada, testamos os resultados da literatura baseando-nos em um conjunto de dados longitudinais sobre a resistência antimicrobiana em 41 grandes hospitais privados e públicos e em uma pesquisa domiciliar representativa da realidade nacional no Chile (2008-2017). Estimamos as taxas de resistência em três pares prioritários de bactérias e antibióticos, como definido pela Organização para a Cooperação e o Desenvolvimento Econômico: P. aeruginosa resistente a imipenem e meropenem, S. aureus resistente a cloxacilina e E. coli resistente a cefotaxima e ciprofloxacino. Resultados. As evidências desta revisão da literatura sugerem que a pobreza e a privação material são fatores de risco importantes para o surgimento e a transmissão da resistência antimicrobiana. A maior parte dos estudos constatou que piores indicadores socioeconômicos estão associados a taxas mais altas de resistência antimicrobiana. A nossa análise mostrou uma taxa global de resistência antimicrobiana de 32,5%; S. aureus apresentou as taxas mais altas (40,6%) e E. coli as mais baixas (25,7%). As análises univariadas (p<0,01) e multivariadas (p<0,01) identificaram uma associação negativa pequena, porém consistente, entre fatores socioeconômicos (renda, educação e ocupação) e a resistência antimicrobiana global em P. aeruginosa e S. aureus. Conclusão. Fatores socioeconômicos, para além dos cuidados de saúde e dos ambientes hospitalares, podem afetar o surgimento e a disseminação da resistência antimicrobiana. Para prevenir e controlar esta resistência, é preciso fazer esforços que não se limitem à redução do consumo de antibióticos.


Assuntos
Resistência Microbiana a Medicamentos , Antibacterianos , Condições Sociais , Determinantes Sociais da Saúde , América Latina , Resistência Microbiana a Medicamentos , Antibacterianos , Condições Sociais , Determinantes Sociais da Saúde , América Latina , Resistência Microbiana a Medicamentos , Condições Sociais , Determinantes Sociais da Saúde
10.
Infect Dis Poverty ; 9(1): 124, 2020 Aug 31.
Artigo em Inglês | MEDLINE | ID: mdl-32867851

RESUMO

BACKGROUND: Coronavirus disease 2019 (COVID-19) was confirmed in Brazil in February 2020. Since then, the disease has spread throughout the country, reaching the poorest areas. This study analyzes the relationship between COVID-19 and the population's living conditions. We aimed to identify social determinants related to the incidence, mortality, and case fatality rate of COVID-19 in Brazil, in 2020. METHODS: This is an ecological study evaluating the relationship between COVID-19 incidence, mortality, and case fatality rates and 49 social indicators of human development and social vulnerability. For the analysis, bivariate spatial correlation and multivariate and spatial regression models (spatial lag model and spatial error models) were used, considering a 95% confidence interval and a significance level of 5%. RESULTS: A total of 44.8% of municipalities registered confirmed cases of COVID-19 and 14.7% had deaths. We observed that 56.2% of municipalities with confirmed cases had very low human development (COVID-19 incidence rate: 59.00/100 000; mortality rate: 36.75/1 000 000), and 52.8% had very high vulnerability (COVID-19 incidence rate: 41.68/100 000; mortality rate: 27.46/1 000 000). The regression model showed 17 indicators associated with transmission of COVID-19 in Brazil. CONCLUSIONS: Although COVID-19 first arrived in the most developed and least vulnerable municipalities in Brazil, it has already reached locations that are farther from large urban centers, whose populations are exposed to a context of intense social vulnerability. Based on these findings, it is necessary to adopt measures that take local social aspects into account in order to contain the pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde , Adolescente , Brasil/epidemiologia , Criança , Pré-Escolar , Intervalos de Confiança , Infecções por Coronavirus/mortalidade , Educação , Emprego , Humanos , Incidência , Renda , Longevidade , Análise Multivariada , Pandemias , Pneumonia Viral/mortalidade , Pobreza , Análise de Regressão , Saneamento , Esgotos , Condições Sociais , Análise Espacial , Abastecimento de Água/normas , Adulto Jovem
12.
Health Educ Behav ; 47(5): 665-670, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32896177

RESUMO

Health education and promotion researchers and practitioners are committed to eliminating health disparities, and the Society for Public Health Education (SOPHE) has continuously supported this effort through its journals, professional development, annual conferences, and advocacy. The COVID-19 pandemic elucidated inequities directly caused by racism and other social determinants of health. In order to achieve health equity, we need to become antiracist in our research, practice, and advocacy work by standing united against racist policies and practices. I invite us all to heed the call to action on these five points: place racism on the agenda, practice cultural humility, claim your privilege and eliminate microaggressions, utilize strategies that promote inclusion and equity, and embrace your inner leader and activist. Just as SOPHE as an organization pivoted its annual conference from on ground to virtual in March 2020, so can we be innovative and brave as professionals to face the hard work and dedication needed to become antiracist.


Assuntos
Infecções por Coronavirus/epidemiologia , Equidade em Saúde/organização & administração , Promoção da Saúde/organização & administração , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde/etnologia , Betacoronavirus , Equidade em Saúde/normas , Promoção da Saúde/normas , Humanos , Pandemias , Racismo
13.
Rev Esp Salud Publica ; 942020 09 16.
Artigo em Espanhol | MEDLINE | ID: mdl-32935664

RESUMO

OBJECTIVE: Social determinants and health inequalities have a huge impact on health of populations. It is important to study their role in the management of the Covid-19 epidemic, especially in cities, as certain variables like the number of tests and the access to health system cannot be assumed as equal. The aim of this work was to determine the relation of social determinants in the incidence of Covid-19 in the city of Barcelona. METHODS: An observational retrospective ecological study was performed, with the neighbourhood as the population unit, based on data of cumulative incidence published at May 14th, 2020 by the Public Health Agency of Barcelona. Covid-19 incidence disparities depending on the income of the neighbourhoods, the Pearson linear correlation of the variables selected (age, sex, net density, immigrants, comorbidities, smokers, Body Mass Index [BMI] and Available Income per Family Index [AIFI]) with the incidence and the correlation with a multivariant Generalized Linear Model (GLM) were estimated. RESULTS: It was found that neighbourhoods belonging to the lowest quintile of income had a 42% more incidence than those belonging to the highest quintile: 942 cases per 100,000 inhabitants versus 545 per 100,000 inhabitants of the highest quintile. The Pearson correlation was statistically significative between the incidence of Covid-19 and the percentage of population over 75 (r=0.487), the percentage of immigration of the neighbourhood and the origin of the immigrants (r=-0.257), the AIFI (r=-0.462), the percentage of smokers (r=0.243) and the percentage of people with BMI over 25 (r=0.483). The GLM showed that the most correlated variables with the incidence are the percentage of people over 75 (Z-score=0.258), the percentage of people from Maghreb (Z-score=-0.206) and Latin America (Z-score=0.19) and the percentage of people with BMI over 25 (Z-score=0.334). The results of the GLM were significative. CONCLUSIONS: Social determinants are correlated with the modification of the incidence of Covid-19 in the neighbourhoods of Barcelona, with special relevance of the prevalence of BMI over 25 and the percentage of immigrants and its origin.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde , Adulto , Betacoronavirus , Índice de Massa Corporal , Emigrantes e Imigrantes , Emigração e Imigração , Feminino , Acesso aos Serviços de Saúde , Disparidades nos Níveis de Saúde , Disparidades em Assistência à Saúde , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Pandemias , Características de Residência , Estudos Retrospectivos , Fumar , Fatores Socioeconômicos , Espanha/epidemiologia
15.
JAMA ; 324(12): 1215, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32960232
16.
JAMA ; 324(12): 1216-1217, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32960233
17.
JAMA ; 324(12): 1216, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32960234
18.
JAMA ; 324(12): 1217, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32960236
19.
J Prev Med Public Health ; 53(4): 220-227, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32752590

RESUMO

OBJECTIVES: The aim of this study was to assess how different social determinants of health (SDoH) may be related to variability in coronavirus disease 2019 (COVID-19) rates in cities and towns in Massachusetts (MA). METHODS: Data about the total number of cases, tests, and rates of COVID-19 as of June 10, 2020 were obtained for cities and towns in MA. The data on COVID-19 were matched with data on various SDoH variables at the city and town level from the American Community Survey. These variables included information about income, poverty, employment, renting, and insurance coverage. We compared COVID-19 rates according to these SDoH variables. RESULTS: There were clear gradients in the rates of COVID-19 according to SDoH variables. Communities with more poverty, lower income, lower insurance coverage, more unemployment, and a higher percentage of the workforce employed in essential services, including healthcare, had higher rates of COVID-19. Most of these differences were not accounted for by different rates of testing in these cities and towns. CONCLUSIONS: SDoH variables may explain some of the variability in the risk of COVID-19 across cities and towns in MA. Data about SDoH should be part of the standard surveillance for COVID-19. Efforts should be made to address social factors that may be putting communities at an elevated risk.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde/estatística & dados numéricos , Feminino , Humanos , Masculino , Massachusetts/epidemiologia , Pandemias , Pobreza/estatística & dados numéricos , Inquéritos e Questionários
20.
Artigo em Inglês | MEDLINE | ID: mdl-32785046

RESUMO

The Health Opportunity Index (HOI) is a multivariate tool that can be more efficiently used to identify and understand the interplay of complex social determinants of health (SDH) at the census tract level that influences the ability to achieve optimal health. The derivation of the HOI utilizes the data-reduction technique of principal component analysis to determine the impact of SDH on optimal health at lower census geographies. In the midst of persistent health disparities and the present COVID-19 pandemic, we demonstrate the potential utility of using 13-input variables to derive a composite metric of health (HOI) score as a means to assist in the identification of the most vulnerable communities during the current pandemic. Using GIS mapping technology, health opportunity indices were layered by counties in Ohio to highlight differences by census tract. Collectively we demonstrate that our HOI framework, principal component analysis and convergence analysis methodology coalesce to provide results supporting the utility of this framework in the three largest counties in Ohio: Franklin (Columbus), Cuyahoga (Cleveland), and Hamilton (Cincinnati). The results in this study identified census tracts that were also synonymous with communities that were at risk for disparate COVID-19 related health outcomes. In this regard, convergence analyses facilitated identification of census tracts where different disparate health outcomes co-exist at the worst levels. Our results suggest that effective use of the HOI composite score and subcomponent scores to identify specific SDH can guide mitigation/intervention practices, thus creating the potential for better targeting of mitigation and intervention strategies for vulnerable communities, such as during the current pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde/estatística & dados numéricos , Betacoronavirus , Censos , Mapeamento Geográfico , Humanos , Ohio/epidemiologia , Pandemias , Análise de Componente Principal , Fatores Socioeconômicos
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