ReviewJournal of global health2021
Predictors for detecting chronic respiratory diseases in community surveys: A pilot cross-sectional survey in four South and South East Asian low- and middle-income countries.
Review in Journal of global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Associations of Dietary Patterns and Allergies With Asthma Among University Students in Bangladesh: A Cross-Sectional Study.Health science reports · 2026Article
- Prevalence and covariates of chronic respiratory disorders among middle-aged Bangladeshi people: A rural community-based study.Lung India : official organ of Indian Chest Society · 2025Article
- Optimising participation in a pulmonary rehabilitation programme for people living with chronic respiratory diseases in rural India: a feasibility study.Journal of global health · 2025Article
- Global trends and age-period-cohort effects of chronic respiratory disease mortality attributed to industrial gaseous pollutants from 1990 to 2021.Scientific reports · 2025Article
- Persons at High-Risk and Low-Risk for Chronic Obstructive Pulmonary Disease: Results from the BOLD Study in Iran.Tanaffos · 2025Article
- Identifying Existing Evidence to Potentially Develop a Machine Learning Diagnostic Algorithm for Cough in Primary Care Settings: Scoping Review.Journal of medical Internet research · 2023Article
- Global Burden of Asthma, and Its Impact on Specific Subgroups: Nasal Polyps, Allergic Rhinitis, Severe Asthma, Eosinophilic Asthma.Journal of asthma and allergy · 2023Article
Corrections and comments
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Authors and funding
24 authors at 7 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOur previous scoping review revealed limitations and inconsistencies in population surveys of chronic respiratory disease. Informed by this review, we piloted a cross-sectional survey of adults in four South/South-East Asian low-and middle-income countries (LMICs) to assess survey feasibility and identify variables that predicted asthma or chronic obstructive pulmonary disease (COPD).
methodsWe administered relevant translations of the BOLD-1 questionnaire with additional questions from ECRHS-II, performed spirometry and arranged specialist clinical review for a sub-group to confirm the diagnosis. Using random sampling, we piloted a community-based survey at five sites in four LMICs and noted any practical barriers to conducting the survey. Three clinicians independently used information from questionnaires, spirometry and specialist reviews, and reached consensus on a clinical diagnosis. We used lasso regression to identify variables that predicted the clinical diagnoses and attempted to develop an algorithm for detecting asthma and COPD.
resultsOf 508 participants, 55.9% reported one or more chronic respiratory symptoms. The prevalence of asthma was 16.3%; COPD 4.5%; and 'other chronic respiratory disease' 3.0%. Based on consensus categorisation (n = 483 complete records), "Wheezing in last 12 months" and "Waking up with a feeling of tightness" were the strongest predictors for asthma. For COPD, age and spirometry results were the strongest predictors. Practical challenges included logistics (participant recruitment; researcher safety); misinterpretation of questions due to local dialects; and assuring quality spirometry in the field.
conclusionDetecting asthma in population surveys relies on symptoms and history. In contrast, spirometry and age were the best predictors of COPD. Logistical, language and spirometry-related challenges need to be addressed.
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