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Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report
BACKGROUND: Studies have suggested that agreement between administrative health data and self-report for asthma status ranges from fair to good, but few studies benefited from administrative health data over a long period. We aimed to (1) evaluate agreement between asthma status ascertained in admin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486089/ https://www.ncbi.nlm.nih.gov/pubmed/37679673 http://dx.doi.org/10.1186/s12874-023-02011-6 |
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author | Rousseau, Marie-Claude Conus, Florence El-Zein, Mariam Benedetti, Andrea Parent, Marie-Elise |
author_facet | Rousseau, Marie-Claude Conus, Florence El-Zein, Mariam Benedetti, Andrea Parent, Marie-Elise |
author_sort | Rousseau, Marie-Claude |
collection | PubMed |
description | BACKGROUND: Studies have suggested that agreement between administrative health data and self-report for asthma status ranges from fair to good, but few studies benefited from administrative health data over a long period. We aimed to (1) evaluate agreement between asthma status ascertained in administrative health data covering a period of 30 years and from self-report, and (2) identify determinants of agreement between the two sources. METHODS: We used administrative health data (1983–2012) from the Quebec Birth Cohort on Immunity and Health, which included 81,496 individuals born in the province of Quebec, Canada, in 1974. Additional information, including self-reported asthma, was collected by telephone interview with 1643 participants in 2012. By design, half of them had childhood asthma based on health services utilization. Results were weighted according to the inverse of the sampling probabilities. Five algorithms were applied to administrative health data (having ≥ 2 physician claims over a 1-, 2-, 3-, 5-, or 30-year interval or ≥ 1 hospitalization), to enable comparisons with previous studies. We estimated the proportion of overall agreement and Kappa, between asthma status derived from algorithms and self-reports. We used logistic regression to identify factors associated with agreement. RESULTS: Applying the five algorithms, the prevalence of asthma ranged from 49 to 55% among the 1643 participants. At interview (mean age = 37 years), 49% and 47% of participants respectively reported ever having asthma and asthma diagnosed by a physician. Proportions of agreement between administrative health data and self-report ranged from 88 to 91%, with Kappas ranging from 0.57 (95% CI: 0.52–0.63) to 0.67 (95% CI: 0.62–0.72); the highest values were obtained with the [≥ 2 physician claims over a 30-year interval or ≥ 1 hospitalization] algorithm. Having sought health services for allergic diseases other than asthma was related to lower agreement (Odds ratio = 0.41; 95% CI: 0.25–0.65 comparing ≥ 1 health services to none). CONCLUSIONS: These findings indicate good agreement between asthma status defined from administrative health data and self-report. Agreement was higher than previously observed, which may be due to the 30-year lookback window in administrative data. Our findings support using both administrative health data and self-report in population-based epidemiological studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-02011-6. |
format | Online Article Text |
id | pubmed-10486089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104860892023-09-09 Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report Rousseau, Marie-Claude Conus, Florence El-Zein, Mariam Benedetti, Andrea Parent, Marie-Elise BMC Med Res Methodol Research BACKGROUND: Studies have suggested that agreement between administrative health data and self-report for asthma status ranges from fair to good, but few studies benefited from administrative health data over a long period. We aimed to (1) evaluate agreement between asthma status ascertained in administrative health data covering a period of 30 years and from self-report, and (2) identify determinants of agreement between the two sources. METHODS: We used administrative health data (1983–2012) from the Quebec Birth Cohort on Immunity and Health, which included 81,496 individuals born in the province of Quebec, Canada, in 1974. Additional information, including self-reported asthma, was collected by telephone interview with 1643 participants in 2012. By design, half of them had childhood asthma based on health services utilization. Results were weighted according to the inverse of the sampling probabilities. Five algorithms were applied to administrative health data (having ≥ 2 physician claims over a 1-, 2-, 3-, 5-, or 30-year interval or ≥ 1 hospitalization), to enable comparisons with previous studies. We estimated the proportion of overall agreement and Kappa, between asthma status derived from algorithms and self-reports. We used logistic regression to identify factors associated with agreement. RESULTS: Applying the five algorithms, the prevalence of asthma ranged from 49 to 55% among the 1643 participants. At interview (mean age = 37 years), 49% and 47% of participants respectively reported ever having asthma and asthma diagnosed by a physician. Proportions of agreement between administrative health data and self-report ranged from 88 to 91%, with Kappas ranging from 0.57 (95% CI: 0.52–0.63) to 0.67 (95% CI: 0.62–0.72); the highest values were obtained with the [≥ 2 physician claims over a 30-year interval or ≥ 1 hospitalization] algorithm. Having sought health services for allergic diseases other than asthma was related to lower agreement (Odds ratio = 0.41; 95% CI: 0.25–0.65 comparing ≥ 1 health services to none). CONCLUSIONS: These findings indicate good agreement between asthma status defined from administrative health data and self-report. Agreement was higher than previously observed, which may be due to the 30-year lookback window in administrative data. Our findings support using both administrative health data and self-report in population-based epidemiological studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-02011-6. BioMed Central 2023-09-07 /pmc/articles/PMC10486089/ /pubmed/37679673 http://dx.doi.org/10.1186/s12874-023-02011-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Rousseau, Marie-Claude Conus, Florence El-Zein, Mariam Benedetti, Andrea Parent, Marie-Elise Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title | Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title_full | Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title_fullStr | Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title_full_unstemmed | Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title_short | Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
title_sort | ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486089/ https://www.ncbi.nlm.nih.gov/pubmed/37679673 http://dx.doi.org/10.1186/s12874-023-02011-6 |
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