Agarwal, Dhiraj and Hanafi, Nik Sherina and Khoo, Ee Ming and Parker, Richard A. and Ghorpade, Deesha and Salvi, Sundeep and Abu Bakar, Ahmad Ihsan and Chinna, Karuthan and Das, Deepa and Habib, Monsur and Hussein, Norita and Isaac, Rita and Islam, Mohammad Shahidul and Khan, Mohsin Saeed and Liew, Su May and Pang, Yong Kek and Paul, Biswajit and Saha, Samir K. and Wong, Li Ping and Yusuf, Osman M. and Yusuf, Shahida O. and Juvekar, Sanjay and Pinnock, Hilary and Collaboration, RESPIRE (2021) 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. Journal of Global Health, 11. ISSN 2047-2978, DOI https://doi.org/10.7189/jogh.11.04065.
Full text not available from this repository.Abstract
Our 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). Methods We 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. Results Of 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. Conclusion Detecting 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.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Burden;COPD;Strategies;Spirometry;Disorders |
| Subjects: | R Medicine R Medicine > RA Public aspects of medicine R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 31 Oct 2022 00:43 |
| Last Modified: | 31 Oct 2022 00:43 |
| URI: | http://eprints.um.edu.my/id/eprint/35378 |
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