Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates

Detalhes bibliográficos
Autor(a) principal: Kislaya, Irina
Data de Publicação: 2021
Outros Autores: Leite, Andreia, Perelman, Julian, Machado, Ausenda, Torres, Ana Rita, Tolonen, Hanna, Nunes, Baltazar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/133201
Resumo: Funding Information: The authors are grateful to all the professionals that were involved in the INSEF and INS2014 fieldwork and to all the INSEF and the INS2014 participants. Funding Information: No specific funding was received for this study. The Portuguese National Health Examination Survey 2013–2017 (INSEF) was developed as part of the Pre-defined project of the Public Health Initiatives Program, “Improvement of epidemiological health information to support public health decision and management in Portugal. Towards reduced inequalities, improved health, and bilateral cooperation”, that benefits from a 1.500.000€ Grant from Iceland, Liechtenstein and Norway, through the EEA Grants. Publisher Copyright: © 2021, The Author(s).
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spelling Combining self-reported and objectively measured survey data to improve hypertension prevalence estimatesPortuguese experienceBias correctionHypertensionMIMEMisclassification errorMultiple imputationSelf-reportsSurveyPublic Health, Environmental and Occupational HealthSDG 3 - Good Health and Well-beingFunding Information: The authors are grateful to all the professionals that were involved in the INSEF and INS2014 fieldwork and to all the INSEF and the INS2014 participants. Funding Information: No specific funding was received for this study. The Portuguese National Health Examination Survey 2013–2017 (INSEF) was developed as part of the Pre-defined project of the Public Health Initiatives Program, “Improvement of epidemiological health information to support public health decision and management in Portugal. Towards reduced inequalities, improved health, and bilateral cooperation”, that benefits from a 1.500.000€ Grant from Iceland, Liechtenstein and Norway, through the EEA Grants. Publisher Copyright: © 2021, The Author(s).Background: Accurate data on hypertension is essential to inform decision-making. Hypertension prevalence may be underestimated by population-based surveys due to misclassification of health status by participants. Therefore, adjustment for misclassification bias is required when relying on self-reports. This study aims to quantify misclassification bias in self-reported hypertension prevalence and prevalence ratios in the Portuguese component of the European Health Interview Survey (INS2014), and illustrate application of multiple imputation (MIME) for bias correction using measured high blood pressure data from the first Portuguese health examination survey (INSEF). Methods: We assumed that objectively measured hypertension status was missing for INS2014 participants (n = 13,937) and imputed it using INSEF (n = 4910) as auxiliary data. Self-reported, objectively measured and MIME-corrected hypertension prevalence and prevalence ratios (PR) by sex, age group and education were estimated. Bias in self-reported and MIME-corrected estimates were computed using objectively measured INSEF data as a gold-standard. Results: Self-reported INS2014 data underestimated hypertension prevalence in all population subgroups, with misclassification bias ranging from 5.2 to 18.6 percentage points (pp). After MIME-correction, prevalence estimates increased and became closer to objectively measured ones, with bias reduction to 0 pp - 5.7 pp. Compared to objectively measured INSEF, self-reported INS2014 data considerably underestimated prevalence ratio by sex (PR = 0.8, 95CI = [0.7, 0.9] vs. PR = 1.2, 95CI = [1.1, 1.4]). MIME successfully corrected direction of association with sex in bivariate (PR = 1.1, 95CI = [1.0, 1.3]) and multivariate analyses (PR = 1.2, 95CI = [1.0, 1.3]). Misclassification bias in hypertension prevalence ratios by education and age group were less pronounced and did not require correction in multivariate analyses. Conclusions: Our results highlight the importance of misclassification bias analysis in self-reported hypertension. Multiple imputation is a feasible approach to adjust for misclassification bias in prevalence estimates and exposure-outcomes associations in survey data.Comprehensive Health Research Centre (CHRC) - Pólo ENSPCentro de Investigação em Saúde Pública (CISP/PHRC)Escola Nacional de Saúde Pública (ENSP)RUNKislaya, IrinaLeite, AndreiaPerelman, JulianMachado, AusendaTorres, Ana RitaTolonen, HannaNunes, Baltazar2022-02-18T23:19:25Z2021-122021-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/133201eng0778-7367PURE: 41837483https://doi.org/10.1186/s13690-021-00562-yinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:11:55Zoai:run.unl.pt:10362/133201Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:47:44.907990Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
Portuguese experience
title Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
spellingShingle Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
Kislaya, Irina
Bias correction
Hypertension
MIME
Misclassification error
Multiple imputation
Self-reports
Survey
Public Health, Environmental and Occupational Health
SDG 3 - Good Health and Well-being
title_short Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
title_full Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
title_fullStr Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
title_full_unstemmed Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
title_sort Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates
author Kislaya, Irina
author_facet Kislaya, Irina
Leite, Andreia
Perelman, Julian
Machado, Ausenda
Torres, Ana Rita
Tolonen, Hanna
Nunes, Baltazar
author_role author
author2 Leite, Andreia
Perelman, Julian
Machado, Ausenda
Torres, Ana Rita
Tolonen, Hanna
Nunes, Baltazar
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Comprehensive Health Research Centre (CHRC) - Pólo ENSP
Centro de Investigação em Saúde Pública (CISP/PHRC)
Escola Nacional de Saúde Pública (ENSP)
RUN
dc.contributor.author.fl_str_mv Kislaya, Irina
Leite, Andreia
Perelman, Julian
Machado, Ausenda
Torres, Ana Rita
Tolonen, Hanna
Nunes, Baltazar
dc.subject.por.fl_str_mv Bias correction
Hypertension
MIME
Misclassification error
Multiple imputation
Self-reports
Survey
Public Health, Environmental and Occupational Health
SDG 3 - Good Health and Well-being
topic Bias correction
Hypertension
MIME
Misclassification error
Multiple imputation
Self-reports
Survey
Public Health, Environmental and Occupational Health
SDG 3 - Good Health and Well-being
description Funding Information: The authors are grateful to all the professionals that were involved in the INSEF and INS2014 fieldwork and to all the INSEF and the INS2014 participants. Funding Information: No specific funding was received for this study. The Portuguese National Health Examination Survey 2013–2017 (INSEF) was developed as part of the Pre-defined project of the Public Health Initiatives Program, “Improvement of epidemiological health information to support public health decision and management in Portugal. Towards reduced inequalities, improved health, and bilateral cooperation”, that benefits from a 1.500.000€ Grant from Iceland, Liechtenstein and Norway, through the EEA Grants. Publisher Copyright: © 2021, The Author(s).
publishDate 2021
dc.date.none.fl_str_mv 2021-12
2021-12-01T00:00:00Z
2022-02-18T23:19:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/133201
url http://hdl.handle.net/10362/133201
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0778-7367
PURE: 41837483
https://doi.org/10.1186/s13690-021-00562-y
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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