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Validation of an Index for Functionally Important Respiratory Symptoms among Adults in the Nationally Representative Population Assessment of Tobacco and Health Study, 2014-2016.

Michael J HalenarJames D SargentKathryn C EdwardsSteven WoloshinLisa SchwartzJennifer EmondSusanne TanskiJohn P PierceKristie A TaylorKristin LautenMaciej Lukasz GoniewiczRaymond S NiauraGabriella AnicYanling ChenPriscilla Callahan-LyonLisa D GardnerTheresa ThekkudanNicolette BorekHeather L KimmelKenneth Michael CummingsAndrew HylandMary F Brunette
Published in: International journal of environmental research and public health (2021)
The purpose of this study is to validate the seven-item wheezing module from the International Study of Asthma and Allergies in Children (ISAAC) in the nationally representative Population Assessment of Tobacco and Health Study. Adult participants with complete Wave 2-3 data were selected, including those with asthma but excluding those with COPD and other respiratory diseases (n = 16,295). We created a nine-point respiratory symptom index from the ISAAC questions, assessed the reliability of the index, and examined associations with self-reported asthma diagnosis. Threshold values were assessed for association with functional outcomes. The weighted prevalence for one or more respiratory symptom was 18.0% (SE = 0.5) for adults without asthma, 70.1% (SE = 1.3) for those with lifetime asthma, 75.7% (SE = 3.7) for adults with past-year asthma not on medications, and 92.6% (SE = 1.6) for those on medications. Cronbach's alpha for the respiratory symptom index was 0.86. Index scores of ≥2 or ≥3 yielded functionally important respiratory symptom prevalence of 7-10%, adequate sensitivity and specificity for identifying asthma, and consistent independent associations with all functional outcomes and tobacco use variables. Respiratory symptom index scores of ≥2 or ≥3 are indicative of functionally important respiratory symptoms and could be used to assess the relationship between tobacco use and respiratory health.
Keyphrases
  • chronic obstructive pulmonary disease
  • lung function
  • healthcare
  • public health
  • allergic rhinitis
  • respiratory tract
  • machine learning
  • risk assessment
  • air pollution
  • health information
  • physical activity
  • deep learning