COVID-19 mortality in Lombardy: the vulnerability of the oldest old and the resilience of male centenarians.
Identifieur interne : 000858 ( Main/Exploration ); précédent : 000857; suivant : 000859COVID-19 mortality in Lombardy: the vulnerability of the oldest old and the resilience of male centenarians.
Auteurs : Gabriella Marcon [Italie] ; Mauro Tettamanti [Italie] ; Giorgia Capacci [Italie] ; Giulia Fontanel [Italie] ; Marco Span [Italie] ; Alessandro Nobili [Italie] ; Gianluigi Forloni [Italie] ; Claudio Franceschi [Italie, Russie]Source :
- Aging [ 1945-4589 ] ; 2020.
Descripteurs français
- KwdFr :
- Besoins et demandes de services de santé (MeSH), Betacoronavirus (physiologie), Disparités de l'état de santé (MeSH), Facteurs sexuels (MeSH), Facteurs âges (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (immunologie), Infections à coronavirus (prévention et contrôle), Infections à coronavirus (thérapie), Infections à coronavirus (épidémiologie), Inflammation (virologie), Inflammation (épidémiologie), Italie (épidémiologie), Mortalité (MeSH), Mâle (MeSH), Pandémies (prévention et contrôle), Pneumopathie virale (immunologie), Pneumopathie virale (prévention et contrôle), Pneumopathie virale (thérapie), Pneumopathie virale (épidémiologie), Populations vulnérables (MeSH), Santé publique (méthodes), Services de santé pour personnes âgées (statistiques et données numériques), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Vieillissement (physiologie), Vieillissement (psychologie).
- MESH :
- immunologie : Infections à coronavirus, Pneumopathie virale.
- méthodes : Santé publique.
- physiologie : Betacoronavirus, Vieillissement.
- prévention et contrôle : Infections à coronavirus, Pandémies, Pneumopathie virale.
- psychologie : Vieillissement.
- statistiques et données numériques : Services de santé pour personnes âgées.
- thérapie : Infections à coronavirus, Pneumopathie virale.
- virologie : Inflammation.
- épidémiologie : Infections à coronavirus, Inflammation, Italie, Pneumopathie virale.
- Besoins et demandes de services de santé, Disparités de l'état de santé, Facteurs sexuels, Facteurs âges, Femelle, Humains, Mortalité, Mâle, Populations vulnérables, Sujet âgé, Sujet âgé de 80 ans ou plus.
- Wicri :
- geographic : Italie.
English descriptors
- KwdEn :
- Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Aging (physiology), Aging (psychology), Betacoronavirus (physiology), Coronavirus Infections (epidemiology), Coronavirus Infections (immunology), Coronavirus Infections (prevention & control), Coronavirus Infections (therapy), Female (MeSH), Health Services Needs and Demand (MeSH), Health Services for the Aged (statistics & numerical data), Health Status Disparities (MeSH), Humans (MeSH), Inflammation (epidemiology), Inflammation (virology), Italy (epidemiology), Male (MeSH), Mortality (MeSH), Pandemics (prevention & control), Pneumonia, Viral (epidemiology), Pneumonia, Viral (immunology), Pneumonia, Viral (prevention & control), Pneumonia, Viral (therapy), Public Health (methods), Sex Factors (MeSH), Vulnerable Populations (MeSH).
- MESH :
- geographic , epidemiology : Italy.
- epidemiology : Coronavirus Infections, Inflammation, Pneumonia, Viral.
- immunology : Coronavirus Infections, Pneumonia, Viral.
- methods : Public Health.
- physiology : Aging, Betacoronavirus.
- prevention & control : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- psychology : Aging.
- statistics & numerical data : Health Services for the Aged.
- therapy : Coronavirus Infections, Pneumonia, Viral.
- virology : Inflammation.
- Age Factors, Aged, Aged, 80 and over, Female, Health Services Needs and Demand, Health Status Disparities, Humans, Male, Mortality, Sex Factors, Vulnerable Populations.
Abstract
Italy was the first European nation to be affected by COVID-19. The biggest cluster of cases occurred in Lombardy, the most populous Italian region, and elderly men were the population hit in the hardest way. Besides its high infectivity, COVID-19 causes a severe cytokine storm and old people, especially those with comorbidities, appear to be the most vulnerable, presumably in connection to inflammaging. In centenarians inflammaging is much lower than predicted by their chronological age and females, presenting survival advantage in almost all centenarian populations, outnumber males, a phenomenon particularly evident in Northern Italy. Within this scenario, we wondered if: a) the COVID-19 mortality in centenarians was lower than that in people aged between 50 and 80 and b) the mortality from COVID-19 in nonagenarians and centenarians highlighted gender differences.We checked COVID-19-related vulnerability/mortality at the peak of infection (March 2020), using data on total deaths (i.e. not only confirmed COVID-19 cases). Our conclusion is that excess mortality increases steadily up to very old ages and at the same time men older than 90 years become relatively more resilient than age-matched females.
DOI: 10.18632/aging.103872
PubMed: 32788424
PubMed Central: PMC7467374
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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<term>Aging (psychology)</term>
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<front><div type="abstract" xml:lang="en">Italy was the first European nation to be affected by COVID-19. The biggest cluster of cases occurred in Lombardy, the most populous Italian region, and elderly men were the population hit in the hardest way. Besides its high infectivity, COVID-19 causes a severe cytokine storm and old people, especially those with comorbidities, appear to be the most vulnerable, presumably in connection to inflammaging. In centenarians inflammaging is much lower than predicted by their chronological age and females, presenting survival advantage in almost all centenarian populations, outnumber males, a phenomenon particularly evident in Northern Italy. Within this scenario, we wondered if: a) the COVID-19 mortality in centenarians was lower than that in people aged between 50 and 80 and b) the mortality from COVID-19 in nonagenarians and centenarians highlighted gender differences.We checked COVID-19-related vulnerability/mortality at the peak of infection (March 2020), using data on total deaths (i.e. not only confirmed COVID-19 cases). Our conclusion is that excess mortality increases steadily up to very old ages and at the same time men older than 90 years become relatively more resilient than age-matched females.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32788424</PMID>
<DateCompleted><Year>2020</Year>
<Month>09</Month>
<Day>10</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>09</Month>
<Day>15</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1945-4589</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>12</Volume>
<Issue>15</Issue>
<PubDate><Year>2020</Year>
<Month>08</Month>
<Day>12</Day>
</PubDate>
</JournalIssue>
<Title>Aging</Title>
<ISOAbbreviation>Aging (Albany NY)</ISOAbbreviation>
</Journal>
<ArticleTitle>COVID-19 mortality in Lombardy: the vulnerability of the oldest old and the resilience of male centenarians.</ArticleTitle>
<Pagination><MedlinePgn>15186-15195</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.18632/aging.103872</ELocationID>
<Abstract><AbstractText>Italy was the first European nation to be affected by COVID-19. The biggest cluster of cases occurred in Lombardy, the most populous Italian region, and elderly men were the population hit in the hardest way. Besides its high infectivity, COVID-19 causes a severe cytokine storm and old people, especially those with comorbidities, appear to be the most vulnerable, presumably in connection to inflammaging. In centenarians inflammaging is much lower than predicted by their chronological age and females, presenting survival advantage in almost all centenarian populations, outnumber males, a phenomenon particularly evident in Northern Italy. Within this scenario, we wondered if: a) the COVID-19 mortality in centenarians was lower than that in people aged between 50 and 80 and b) the mortality from COVID-19 in nonagenarians and centenarians highlighted gender differences.We checked COVID-19-related vulnerability/mortality at the peak of infection (March 2020), using data on total deaths (i.e. not only confirmed COVID-19 cases). Our conclusion is that excess mortality increases steadily up to very old ages and at the same time men older than 90 years become relatively more resilient than age-matched females.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Marcon</LastName>
<ForeName>Gabriella</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>DAME, University of Udine, Udine, Italy.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Azienda Sanitaria Universitaria Giuliano-Isontina (ASUGI), Trieste, Italy.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Department of Medical Surgical and Health Sciences, University of Trieste, Trieste, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Tettamanti</LastName>
<ForeName>Mauro</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Capacci</LastName>
<ForeName>Giorgia</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>Directorate for Social Statistics and Population Census, Istat, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Fontanel</LastName>
<ForeName>Giulia</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>Department of Medical Surgical and Health Sciences, University of Trieste, Trieste, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Spanò</LastName>
<ForeName>Marco</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Azienda Sanitaria Universitaria Giuliano-Isontina (ASUGI), Trieste, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Nobili</LastName>
<ForeName>Alessandro</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Forloni</LastName>
<ForeName>Gianluigi</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Franceschi</LastName>
<ForeName>Claudio</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2020</Year>
<Month>08</Month>
<Day>12</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>Aging (Albany NY)</MedlineTA>
<NlmUniqueID>101508617</NlmUniqueID>
<ISSNLinking>1945-4589</ISSNLinking>
</MedlineJournalInfo>
<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>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age Factors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000375" MajorTopicYN="Y">Aging</DescriptorName>
<QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName>
<QualifierName UI="Q000523" MajorTopicYN="N">psychology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName>
<QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="Y">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006301" MajorTopicYN="N">Health Services Needs and Demand</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006299" MajorTopicYN="N">Health Services for the Aged</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D054624" MajorTopicYN="N">Health Status Disparities</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007249" MajorTopicYN="Y">Inflammation</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007558" MajorTopicYN="N" Type="Geographic">Italy</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009026" MajorTopicYN="Y">Mortality</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="Y">Pandemics</DescriptorName>
<QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="Y">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
<QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName>
<QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName>
<QualifierName UI="Q000628" MajorTopicYN="N">therapy</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011634" MajorTopicYN="N">Public Health</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D035862" MajorTopicYN="N">Vulnerable Populations</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">COVID-19</Keyword>
<Keyword MajorTopicYN="Y">centenarians</Keyword>
<Keyword MajorTopicYN="Y">inflammaging</Keyword>
<Keyword MajorTopicYN="Y">mortality</Keyword>
<Keyword MajorTopicYN="Y">oldest-old</Keyword>
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<Month>06</Month>
<Day>18</Day>
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<affiliations><list><country><li>Italie</li>
<li>Russie</li>
</country>
<region><li>Lombardie</li>
</region>
<settlement><li>Milan</li>
</settlement>
</list>
<tree><country name="Italie"><noRegion><name sortKey="Marcon, Gabriella" sort="Marcon, Gabriella" uniqKey="Marcon G" first="Gabriella" last="Marcon">Gabriella Marcon</name>
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<name sortKey="Capacci, Giorgia" sort="Capacci, Giorgia" uniqKey="Capacci G" first="Giorgia" last="Capacci">Giorgia Capacci</name>
<name sortKey="Fontanel, Giulia" sort="Fontanel, Giulia" uniqKey="Fontanel G" first="Giulia" last="Fontanel">Giulia Fontanel</name>
<name sortKey="Forloni, Gianluigi" sort="Forloni, Gianluigi" uniqKey="Forloni G" first="Gianluigi" last="Forloni">Gianluigi Forloni</name>
<name sortKey="Franceschi, Claudio" sort="Franceschi, Claudio" uniqKey="Franceschi C" first="Claudio" last="Franceschi">Claudio Franceschi</name>
<name sortKey="Marcon, Gabriella" sort="Marcon, Gabriella" uniqKey="Marcon G" first="Gabriella" last="Marcon">Gabriella Marcon</name>
<name sortKey="Marcon, Gabriella" sort="Marcon, Gabriella" uniqKey="Marcon G" first="Gabriella" last="Marcon">Gabriella Marcon</name>
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