ArticleBMC medical research methodology2023
Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report.
Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Burden of severe asthma in Italy: Patients treated with versus eligible for monoclonal antibodies in a large real-world study.The Journal of international medical research · 2026Article
- Prevalence and associated factors of asthma and COPD among adults in Iran based on the 2021 STEPS survey.Scientific reports · 2025Article
- Personal care product use and risk of adult-onset asthma: Prospective cohort analyses of U.S. Women from the Sister Study.Environment international · 2025Article
- Healthcare claims and health interview survey data for chronic disease surveillance: agreement and comparative validity of prevalence indicators for 20 chronic conditions in a general population sample in France.European journal of public health · 2025Article
- Work Stressors and Asthma in Female and Male US Workers: Findings From the National Health Interview Survey.American journal of industrial medicine · 2025Article
- Asthma and the risk of cardiac events among patients with long QT syndrome after age 40.Heart rhythm O2 · 2025Article
- Association between asthma and periodontitis: A case-control analysis of risk factors, related medications, and allergic responses.Journal of periodontal research · 2025Article
- Ketamine as an Adjunct Therapy in Acute Severe Asthma: An In-Depth Review of Efficacy and Clinical Implications.Cureus · 2024Review
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Authors and funding
5 authors at 5 institutions in 1 country.
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Abstract
backgroundStudies 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.
methodsWe 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.
resultsApplying 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).
conclusionsThese 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.
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