A population-based analysis of predictors of influenza vaccination uptake in pregnant women: The effect of gestational and calendar time.
Identifieur interne : 000112 ( Main/Exploration ); précédent : 000111; suivant : 000113A population-based analysis of predictors of influenza vaccination uptake in pregnant women: The effect of gestational and calendar time.
Auteurs : Luz Maria Vilca [Canada] ; Aman Verma [Canada] ; David Buckeridge [Canada] ; Magda Campins [Espagne]Source :
- Preventive medicine [ 1096-0260 ] ; 2017.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Deuxième trimestre de grossesse (MeSH), Espagne (MeSH), Facteurs temps (MeSH), Femelle (MeSH), Femmes enceintes (psychologie), Grippe humaine (prévention et contrôle), Grossesse (MeSH), Humains (MeSH), Troisième trimestre de grossesse (MeSH), Vaccination de masse (MeSH), Vaccins antigrippaux (usage thérapeutique), Études de cohortes (MeSH).
- MESH :
- prévention et contrôle : Grippe humaine.
- psychologie : Femmes enceintes.
- usage thérapeutique : Vaccins antigrippaux.
- Adulte, Deuxième trimestre de grossesse, Espagne, Facteurs temps, Femelle, Grossesse, Humains, Troisième trimestre de grossesse, Vaccination de masse, Études de cohortes.
English descriptors
- KwdEn :
- Adult (MeSH), Cohort Studies (MeSH), Female (MeSH), Humans (MeSH), Influenza Vaccines (therapeutic use), Influenza, Human (prevention & control), Mass Vaccination (MeSH), Pregnancy (MeSH), Pregnancy Trimester, Second (MeSH), Pregnancy Trimester, Third (MeSH), Pregnant Women (psychology), Spain (MeSH), Time Factors (MeSH).
- MESH :
- chemical , therapeutic use : Influenza Vaccines.
- prevention & control : Influenza, Human.
- psychology : Pregnant Women.
- Adult, Cohort Studies, Female, Humans, Mass Vaccination, Pregnancy, Pregnancy Trimester, Second, Pregnancy Trimester, Third, Spain, Time Factors.
Abstract
Pregnant women are vaccinated against influenza less frequently than other high-risk groups. To design effective vaccination strategies, we must understand how decisions regarding vaccination may vary by trimester and over vaccination campaigns. We used a Cox model indexed by calendar time to estimate the effect of gestational trimester and other factors on vaccination uptake in a large cohort of pregnant women in Catalonia (Spain) during 2008-09 to 2012-13 influenza vaccination campaigns. We analyzed 247,316 pregnancies. Vaccination coverage was 3.7%, 5.2%, 4.8%, 5.6% and 4.6% from 2008-09 to 2012-13 seasonal vaccination campaigns and 8.3% for the 2009 pandemic vaccination campaign. Pregnant women previously vaccinated had higher uptake than women not previously vaccinated and the hazard ratios (HRs) comparing these 2 groups decreased from 10, the first day of seasonal campaigns, to 1.3 the last day. During the pandemic campaign, HRs decreased over the course of the campaign from 8.6 to 1.9. Women in second and third trimester had higher uptake than women in first trimester, with HR=2.8 and 2.3, respectively, at the start of seasonal campaigns. Influenza vaccination coverage among this cohort of pregnant women was alarmingly low. Our analysis reveals that gestational and calendar time have distinct and interacting effects on vaccination uptake; women in their second trimester and third trimester and previously vaccinated were more prone to be vaccinated, but this effect wanes as the influenza season progresses.
DOI: 10.1016/j.ypmed.2017.02.010
PubMed: 28216380
Affiliations:
Links toward previous steps (curation, corpus...)
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To design effective vaccination strategies, we must understand how decisions regarding vaccination may vary by trimester and over vaccination campaigns. We used a Cox model indexed by calendar time to estimate the effect of gestational trimester and other factors on vaccination uptake in a large cohort of pregnant women in Catalonia (Spain) during 2008-09 to 2012-13 influenza vaccination campaigns. We analyzed 247,316 pregnancies. Vaccination coverage was 3.7%, 5.2%, 4.8%, 5.6% and 4.6% from 2008-09 to 2012-13 seasonal vaccination campaigns and 8.3% for the 2009 pandemic vaccination campaign. Pregnant women previously vaccinated had higher uptake than women not previously vaccinated and the hazard ratios (HRs) comparing these 2 groups decreased from 10, the first day of seasonal campaigns, to 1.3 the last day. During the pandemic campaign, HRs decreased over the course of the campaign from 8.6 to 1.9. Women in second and third trimester had higher uptake than women in first trimester, with HR=2.8 and 2.3, respectively, at the start of seasonal campaigns. Influenza vaccination coverage among this cohort of pregnant women was alarmingly low. Our analysis reveals that gestational and calendar time have distinct and interacting effects on vaccination uptake; women in their second trimester and third trimester and previously vaccinated were more prone to be vaccinated, but this effect wanes as the influenza season progresses.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28216380</PMID><DateCompleted><Year>2018</Year><Month>04</Month><Day>24</Day></DateCompleted><DateRevised><Year>2018</Year><Month>04</Month><Day>24</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1096-0260</ISSN><JournalIssue CitedMedium="Internet"><Volume>99</Volume><PubDate><Year>2017</Year><Month>Jun</Month></PubDate></JournalIssue><Title>Preventive medicine</Title><ISOAbbreviation>Prev Med</ISOAbbreviation></Journal><ArticleTitle>A population-based analysis of predictors of influenza vaccination uptake in pregnant women: The effect of gestational and calendar time.</ArticleTitle><Pagination><MedlinePgn>111-117</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0091-7435(17)30058-0</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.ypmed.2017.02.010</ELocationID><Abstract><AbstractText>Pregnant women are vaccinated against influenza less frequently than other high-risk groups. To design effective vaccination strategies, we must understand how decisions regarding vaccination may vary by trimester and over vaccination campaigns. We used a Cox model indexed by calendar time to estimate the effect of gestational trimester and other factors on vaccination uptake in a large cohort of pregnant women in Catalonia (Spain) during 2008-09 to 2012-13 influenza vaccination campaigns. We analyzed 247,316 pregnancies. Vaccination coverage was 3.7%, 5.2%, 4.8%, 5.6% and 4.6% from 2008-09 to 2012-13 seasonal vaccination campaigns and 8.3% for the 2009 pandemic vaccination campaign. Pregnant women previously vaccinated had higher uptake than women not previously vaccinated and the hazard ratios (HRs) comparing these 2 groups decreased from 10, the first day of seasonal campaigns, to 1.3 the last day. During the pandemic campaign, HRs decreased over the course of the campaign from 8.6 to 1.9. Women in second and third trimester had higher uptake than women in first trimester, with HR=2.8 and 2.3, respectively, at the start of seasonal campaigns. Influenza vaccination coverage among this cohort of pregnant women was alarmingly low. Our analysis reveals that gestational and calendar time have distinct and interacting effects on vaccination uptake; women in their second trimester and third trimester and previously vaccinated were more prone to be vaccinated, but this effect wanes as the influenza season progresses.</AbstractText><CopyrightInformation>Copyright © 2017. Published by Elsevier Inc.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Vilca</LastName><ForeName>Luz Maria</ForeName><Initials>LM</Initials><AffiliationInfo><Affiliation>Servei de Medicina Preventiva i Epidemiologia, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Passeig Vall d'Hebron 119-129, Barcelona 08035, Spain; Clinical & Health Informatics Research Group, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1140 Pine Avenue, Montreal, Quebec H3A 1A1, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Verma</LastName><ForeName>Aman</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Clinical & Health Informatics Research Group, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1140 Pine Avenue, Montreal, Quebec H3A 1A1, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Buckeridge</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Clinical & Health Informatics Research Group, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1140 Pine Avenue, Montreal, Quebec H3A 1A1, Canada. Electronic address: davidbuckeridge@mcgill.ca.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Campins</LastName><ForeName>Magda</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Servei de Medicina Preventiva i Epidemiologia, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Passeig Vall d'Hebron 119-129, Barcelona 08035, Spain.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>02</Month><Day>16</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Prev Med</MedlineTA><NlmUniqueID>0322116</NlmUniqueID><ISSNLinking>0091-7435</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D007252">Influenza Vaccines</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015331" MajorTopicYN="N">Cohort Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007252" MajorTopicYN="N">Influenza Vaccines</DescriptorName><QualifierName UI="Q000627" MajorTopicYN="Y">therapeutic use</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032541" MajorTopicYN="Y">Mass Vaccination</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011247" MajorTopicYN="N">Pregnancy</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011262" MajorTopicYN="Y">Pregnancy Trimester, Second</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011263" MajorTopicYN="Y">Pregnancy Trimester, Third</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D037841" MajorTopicYN="N">Pregnant Women</DescriptorName><QualifierName UI="Q000523" MajorTopicYN="Y">psychology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013030" MajorTopicYN="N">Spain</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013997" MajorTopicYN="N">Time Factors</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Cox model</Keyword><Keyword MajorTopicYN="N">Gestational age</Keyword><Keyword MajorTopicYN="N">Influenza</Keyword><Keyword MajorTopicYN="N">Mass vaccination</Keyword><Keyword MajorTopicYN="N">Pregnancy</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>10</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2017</Year><Month>01</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>02</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>2</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>4</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>2</Month><Day>21</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">28216380</ArticleId><ArticleId IdType="pii">S0091-7435(17)30058-0</ArticleId><ArticleId IdType="doi">10.1016/j.ypmed.2017.02.010</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Canada</li><li>Espagne</li></country><region><li>Catalogne</li><li>Québec</li></region><settlement><li>Montréal</li></settlement><orgName><li>Université McGill</li></orgName></list><tree><country name="Canada"><noRegion><name sortKey="Vilca, Luz Maria" sort="Vilca, Luz Maria" uniqKey="Vilca L" first="Luz Maria" last="Vilca">Luz Maria Vilca</name></noRegion><name sortKey="Buckeridge, David" sort="Buckeridge, David" uniqKey="Buckeridge D" first="David" last="Buckeridge">David Buckeridge</name><name sortKey="Verma, Aman" sort="Verma, Aman" uniqKey="Verma A" first="Aman" last="Verma">Aman Verma</name></country><country name="Espagne"><region name="Catalogne"><name sortKey="Campins, Magda" sort="Campins, Magda" uniqKey="Campins M" first="Magda" last="Campins">Magda Campins</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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