CovidFranceV1, Main, Exploration, bibRecord, 001011

Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study.

Identifieur interne : 001011 ( Main/Exploration ); précédent : 001010; suivant : 001012

Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study.

Auteurs : Camille Lassale [Royaume-Uni] ; Bamba Gaye [France] ; Mark Hamer [Royaume-Uni] ; Catharine R. Gale [Royaume-Uni] ; G David Batty [Royaume-Uni]

Source :

Brain, behavior, and immunity [ 1090-2139 ] ; 2020.

RBID : pubmed:32497776

Descripteurs français

English descriptors

KwdEn :
- African Continental Ancestry Group (statistics & numerical data), Aged (MeSH), Asian Continental Ancestry Group (statistics & numerical data), Betacoronavirus (MeSH), Body Mass Index (MeSH), C-Reactive Protein (immunology), Cohort Studies (MeSH), Comorbidity (MeSH), Coronavirus Infections (ethnology), Coronavirus Infections (immunology), Coronavirus Infections (therapy), Diabetes Mellitus (epidemiology), Diabetes Mellitus (ethnology), England (epidemiology), European Continental Ancestry Group (statistics & numerical data), Female (MeSH), Forced Expiratory Volume (MeSH), Glycated Hemoglobin A (metabolism), Health Status (MeSH), Healthcare Disparities (ethnology), Hospitalization (statistics & numerical data), Humans (MeSH), Inflammation (MeSH), Male (MeSH), Mental Health (MeSH), Middle Aged (MeSH), Pandemics (MeSH), Patient Health Questionnaire (MeSH), Pneumonia, Viral (ethnology), Pneumonia, Viral (immunology), Pneumonia, Viral (therapy), Socioeconomic Factors (MeSH).
MESH :
- chemical , immunology : C-Reactive Protein.
- geographic , epidemiology : England.
- epidemiology : Diabetes Mellitus.
- ethnology : Coronavirus Infections, Diabetes Mellitus, Healthcare Disparities, Pneumonia, Viral.
- immunology : Coronavirus Infections, Pneumonia, Viral.
- chemical , metabolism : Glycated Hemoglobin A.
- statistics & numerical data : African Continental Ancestry Group, Asian Continental Ancestry Group, European Continental Ancestry Group, Hospitalization.
- therapy : Coronavirus Infections, Pneumonia, Viral.
- Aged, Betacoronavirus, Body Mass Index, Cohort Studies, Comorbidity, Female, Forced Expiratory Volume, Health Status, Humans, Inflammation, Male, Mental Health, Middle Aged, Pandemics, Patient Health Questionnaire, Socioeconomic Factors.

Abstract

BACKGROUND

Differentials in COVID-19 hospitalisations and mortality according to ethnicity have been reported but their origin is uncertain. We examined the role of socioeconomic, mental health, and pro-inflammatory factors in a community-based sample.

METHODS

We used data on 340,966 men and women (mean age 56.2 years) from the UK Biobank study, a prospective cohort study with linkage to hospitalisation for COVID-19. Logistic regression models were used to estimate associations between ethnicity and hospitalisation for COVID-19.

RESULTS

There were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of COVID-19 infection (odds ratio; 95% confidence interval: 4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the 'other' non-white group (1.84; 1.13, 2.99). After controlling for potential explanatory factors which included neighbourhood deprivation, household crowding, smoking, body size, inflammation, glycated haemoglobin, and mental illness, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31).

CONCLUSIONS

There were clear ethnic differences in risk of COVID-19 hospitalisation and these do not appear to be fully explained by measured factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage.

DOI: 10.1016/j.bbi.2020.05.074
PubMed: 32497776
PubMed Central: PMC7263214

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<term>Aged (MeSH)</term>
<term>Asian Continental Ancestry Group (statistics & numerical data)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Body Mass Index (MeSH)</term>
<term>C-Reactive Protein (immunology)</term>
<term>Cohort Studies (MeSH)</term>
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<term>Coronavirus Infections (ethnology)</term>
<term>Coronavirus Infections (immunology)</term>
<term>Coronavirus Infections (therapy)</term>
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<term>Glycated Hemoglobin A (metabolism)</term>
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<term>Healthcare Disparities (ethnology)</term>
<term>Hospitalization (statistics & numerical data)</term>
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<term>Middle Aged (MeSH)</term>
<term>Pandemics (MeSH)</term>
<term>Patient Health Questionnaire (MeSH)</term>
<term>Pneumonia, Viral (ethnology)</term>
<term>Pneumonia, Viral (immunology)</term>
<term>Pneumonia, Viral (therapy)</term>
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<term>Diabète (épidémiologie)</term>
<term>Disparités d'accès aux soins (ethnologie)</term>
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<term>Hospitalisation (statistiques et données numériques)</term>
<term>Humains (MeSH)</term>
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<term>Indice de masse corporelle (MeSH)</term>
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<term>Infections à coronavirus (immunologie)</term>
<term>Infections à coronavirus (thérapie)</term>
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<term>Mâle (MeSH)</term>
<term>Pandémies (MeSH)</term>
<term>Pneumopathie virale (ethnologie)</term>
<term>Pneumopathie virale (immunologie)</term>
<term>Pneumopathie virale (thérapie)</term>
<term>Population d'origine africaine (statistiques et données numériques)</term>
<term>Population d'origine asiatique (statistiques et données numériques)</term>
<term>Population d'origine européenne (statistiques et données numériques)</term>
<term>Protéine C-réactive (immunologie)</term>
<term>Questionnaire de santé du patient (MeSH)</term>
<term>Santé mentale (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Volume expiratoire maximal par seconde (MeSH)</term>
<term>État de santé (MeSH)</term>
<term>Études de cohortes (MeSH)</term>
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<term>Infections à coronavirus</term>
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<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>African Continental Ancestry Group</term>
<term>Asian Continental Ancestry Group</term>
<term>European Continental Ancestry Group</term>
<term>Hospitalization</term>
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<term>Population d'origine africaine</term>
<term>Population d'origine asiatique</term>
<term>Population d'origine européenne</term>
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<keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
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<term>Betacoronavirus</term>
<term>Body Mass Index</term>
<term>Cohort Studies</term>
<term>Comorbidity</term>
<term>Female</term>
<term>Forced Expiratory Volume</term>
<term>Health Status</term>
<term>Humans</term>
<term>Inflammation</term>
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<term>Middle Aged</term>
<term>Pandemics</term>
<term>Patient Health Questionnaire</term>
<term>Socioeconomic Factors</term>
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<keywords scheme="MESH" xml:lang="fr"><term>Adulte d'âge moyen</term>
<term>Betacoronavirus</term>
<term>Comorbidité</term>
<term>Facteurs socioéconomiques</term>
<term>Femelle</term>
<term>Humains</term>
<term>Indice de masse corporelle</term>
<term>Inflammation</term>
<term>Mâle</term>
<term>Pandémies</term>
<term>Questionnaire de santé du patient</term>
<term>Santé mentale</term>
<term>Sujet âgé</term>
<term>Volume expiratoire maximal par seconde</term>
<term>État de santé</term>
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<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>Differentials in COVID-19 hospitalisations and mortality according to ethnicity have been reported but their origin is uncertain. We examined the role of socioeconomic, mental health, and pro-inflammatory factors in a community-based sample.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>We used data on 340,966 men and women (mean age 56.2 years) from the UK Biobank study, a prospective cohort study with linkage to hospitalisation for COVID-19. Logistic regression models were used to estimate associations between ethnicity and hospitalisation for COVID-19.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>There were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of COVID-19 infection (odds ratio; 95% confidence interval: 4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the 'other' non-white group (1.84; 1.13, 2.99). After controlling for potential explanatory factors which included neighbourhood deprivation, household crowding, smoking, body size, inflammation, glycated haemoglobin, and mental illness, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31).</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>There were clear ethnic differences in risk of COVID-19 hospitalisation and these do not appear to be fully explained by measured factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage.</p>
</div>
</front>
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<Month>08</Month>
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<Title>Brain, behavior, and immunity</Title>
<ISOAbbreviation>Brain Behav. Immun.</ISOAbbreviation>
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<ArticleTitle>Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study.</ArticleTitle>
<Pagination><MedlinePgn>44-49</MedlinePgn>
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<ELocationID EIdType="doi" ValidYN="Y">10.1016/j.bbi.2020.05.074</ELocationID>
<Abstract><AbstractText Label="BACKGROUND">Differentials in COVID-19 hospitalisations and mortality according to ethnicity have been reported but their origin is uncertain. We examined the role of socioeconomic, mental health, and pro-inflammatory factors in a community-based sample.</AbstractText>
<AbstractText Label="METHODS">We used data on 340,966 men and women (mean age 56.2 years) from the UK Biobank study, a prospective cohort study with linkage to hospitalisation for COVID-19. Logistic regression models were used to estimate associations between ethnicity and hospitalisation for COVID-19.</AbstractText>
<AbstractText Label="RESULTS">There were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of COVID-19 infection (odds ratio; 95% confidence interval: 4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the 'other' non-white group (1.84; 1.13, 2.99). After controlling for potential explanatory factors which included neighbourhood deprivation, household crowding, smoking, body size, inflammation, glycated haemoglobin, and mental illness, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31).</AbstractText>
<AbstractText Label="CONCLUSIONS">There were clear ethnic differences in risk of COVID-19 hospitalisation and these do not appear to be fully explained by measured factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage.</AbstractText>
<CopyrightInformation>Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Lassale</LastName>
<ForeName>Camille</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; CIBER of Pathophysiology of Obesity and Nutrition (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Epidemiology and Public Health, University College London, UK. Electronic address: classale@imim.es.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Gaye</LastName>
<ForeName>Bamba</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>Integrative Epidemiology of Cardiovascular Diseases, Paris Cardiovascular Research Center-INSERM U970 (PARCC), France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hamer</LastName>
<ForeName>Mark</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Division of Surgery and Interventional Sciences, Faculty Medical Sciences, University College London, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Gale</LastName>
<ForeName>Catharine R</ForeName>
<Initials>CR</Initials>
<AffiliationInfo><Affiliation>MRC Lifecourse Epidemiology Unit, University of Southampton, UK; Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Batty</LastName>
<ForeName>G David</ForeName>
<Initials>GD</Initials>
<AffiliationInfo><Affiliation>Department of Epidemiology and Public Health, University College London, UK.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>R56 AG052519</GrantID>
<Acronym>AG</Acronym>
<Agency>NIA NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>R01 AG052519</GrantID>
<Acronym>AG</Acronym>
<Agency>NIA NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>06</Month>
<Day>01</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>Netherlands</Country>
<MedlineTA>Brain Behav Immun</MedlineTA>
<NlmUniqueID>8800478</NlmUniqueID>
<ISSNLinking>0889-1591</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D006442">Glycated Hemoglobin A</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="C517652">hemoglobin A1c protein, human</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>9007-41-4</RegistryNumber>
<NameOfSubstance UI="D002097">C-Reactive Protein</NameOfSubstance>
</Chemical>
</ChemicalList>
<SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName>
<SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName>
</SupplMeshList>
<CitationSubset>IM</CitationSubset>
<CommentsCorrectionsList><CommentsCorrections RefType="UpdateOf"><RefSource>medRxiv. 2020 May 26;:</RefSource>
<PMID Version="1">32511503</PMID>
</CommentsCorrections>
</CommentsCorrectionsList>
<MeshHeadingList><MeshHeading><DescriptorName UI="D044383" MajorTopicYN="N">African Continental Ancestry Group</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D044466" MajorTopicYN="N">Asian Continental Ancestry Group</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015992" MajorTopicYN="N">Body Mass Index</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002097" MajorTopicYN="N">C-Reactive Protein</DescriptorName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015331" MajorTopicYN="N">Cohort Studies</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015897" MajorTopicYN="N">Comorbidity</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000208" MajorTopicYN="Y">ethnology</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003920" MajorTopicYN="N">Diabetes Mellitus</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000208" MajorTopicYN="N">ethnology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D004739" MajorTopicYN="N" Type="Geographic">England</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D044465" MajorTopicYN="N">European Continental Ancestry Group</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005541" MajorTopicYN="N">Forced Expiratory Volume</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006442" MajorTopicYN="N">Glycated Hemoglobin A</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006304" MajorTopicYN="N">Health Status</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D054625" MajorTopicYN="N">Healthcare Disparities</DescriptorName>
<QualifierName UI="Q000208" MajorTopicYN="Y">ethnology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006760" MajorTopicYN="N">Hospitalization</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007249" MajorTopicYN="N">Inflammation</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008603" MajorTopicYN="N">Mental Health</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000073222" MajorTopicYN="N">Patient Health Questionnaire</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000208" MajorTopicYN="Y">ethnology</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012959" MajorTopicYN="N">Socioeconomic Factors</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">COVID-19</Keyword>
<Keyword MajorTopicYN="Y">Ethnicity</Keyword>
<Keyword MajorTopicYN="Y">Inflammatory factors</Keyword>
</KeywordList>
<CoiStatement>Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</CoiStatement>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year>
<Month>05</Month>
<Day>26</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2020</Year>
<Month>05</Month>
<Day>27</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>05</Month>
<Day>28</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>6</Month>
<Day>5</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>8</Month>
<Day>15</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>6</Month>
<Day>5</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">32497776</ArticleId>
<ArticleId IdType="pii">S0889-1591(20)31101-6</ArticleId>
<ArticleId IdType="doi">10.1016/j.bbi.2020.05.074</ArticleId>
<ArticleId IdType="pmc">PMC7263214</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>France</li>
<li>Royaume-Uni</li>
</country>
<region><li>Angleterre</li>
<li>Grand Londres</li>
<li>Écosse</li>
</region>
<settlement><li>Londres</li>
<li>Édimbourg</li>
</settlement>
<orgName><li>University College de Londres</li>
<li>Université d'Édimbourg</li>
</orgName>
</list>
<tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Lassale, Camille" sort="Lassale, Camille" uniqKey="Lassale C" first="Camille" last="Lassale">Camille Lassale</name>
</region>
<name sortKey="Batty, G David" sort="Batty, G David" uniqKey="Batty G" first="G David" last="Batty">G David Batty</name>
<name sortKey="Gale, Catharine R" sort="Gale, Catharine R" uniqKey="Gale C" first="Catharine R" last="Gale">Catharine R. Gale</name>
<name sortKey="Hamer, Mark" sort="Hamer, Mark" uniqKey="Hamer M" first="Mark" last="Hamer">Mark Hamer</name>
</country>
<country name="France"><noRegion><name sortKey="Gaye, Bamba" sort="Gaye, Bamba" uniqKey="Gaye B" first="Bamba" last="Gaye">Bamba Gaye</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>

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Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study.

Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study.

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