Vadu Rural Health Program, KEM Hospital Research Centre (KEMHRC), Pune, India.
Faculty of Medicine, University of Malaya (UM), Kuala Lumpur, Malaysia.
J Glob Health. 2021 Oct 30;11:04065. doi: 10.7189/jogh.11.04065. eCollection 2021.
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).
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.
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.
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.
我们之前的范围综述揭示了慢性呼吸道疾病人群调查中的局限性和不一致性。根据这一综述，我们在四个南亚和东南亚中低收入国家（LMICs）试点了一项成年人横断面调查，以评估调查的可行性，并确定预测哮喘或慢性阻塞性肺疾病（COPD）的变量。
我们使用 BOLD-1 问卷的相关翻译，并增加了来自 ECRHS-II 的额外问题，对亚组进行了肺量测定和安排专科临床复查以确认诊断。我们使用随机抽样，在四个 LMIC 的五个地点试点了一项社区为基础的调查，并注意到进行调查的任何实际障碍。三位临床医生独立使用问卷、肺量测定和专科审查的信息，并就临床诊断达成共识。我们使用套索回归来确定预测临床诊断的变量，并尝试开发一种用于检测哮喘和 COPD 的算法。
在 508 名参与者中，55.9%报告有一个或多个慢性呼吸道症状。哮喘的患病率为 16.3%；COPD 为 4.5%；“其他慢性呼吸道疾病”为 3.0%。基于共识分类（n=483 份完整记录），“过去 12 个月有喘息”和“醒来时感觉紧绷”是哮喘最强的预测因素。对于 COPD，年龄和肺量测定结果是最强的预测因素。实际挑战包括后勤问题（参与者招募；研究人员安全）；由于当地方言而导致的问题误解；以及在现场保证高质量的肺量测定。
在人群调查中检测哮喘依赖于症状和病史。相比之下，肺量测定和年龄是 COPD 的最佳预测因素。需要解决后勤、语言和肺量测定相关的挑战。
