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Background  The global burden of chronic obstructive pulmonary disease (COPD) disproportionately affects resource-limited settings such as sub-Saharan Africa (SSA), but population-based prevalence estimates in SSA are rare. We aimed to estimate the population prevalence of COPD and chronic respiratory symptoms in rural southwestern Uganda.    Methods  Adults at least 18 years of age who participated in a population-wide census in rural southwestern Uganda completed respiratory questionnaires and lung function testing with bronchodilator challenge at health screening events in June 2015. We defined COPD as post-bronchodilator forced expiratory volume in one second to forced vital capacity ratio less than the lower limit of normal. We fit multivariable linear and log binomial regression models to estimate correlates of abnormal lung function and respiratory symptoms, respectively. We included inverse probability of sampling weights in models to facilitate population-level estimates.    Results  Forty-six percent of census participants (843/1814) completed respiratory questionnaires and spirometry, of which 565 (67%) met acceptability standards. COPD and respiratory symptom population prevalence were 2% (95% confidence interval (CI)  = 1%-3%) and 30% (95% CI = 25%-36%), respectively. Respiratory symptoms were more prevalent and lung function was lower among women and ever-smokers ( P  < 0.05). HIV serostatus was associated with neither respiratory symptoms nor lung function.    Conclusions  COPD population prevalence was low despite prevalent respiratory symptoms. This work adds to the growing body of literature depicting lower-than-expected COPD prevalence estimates in SSA and raises questions about whether the high respiratory symptom burden in rural southwestern Uganda represents underlying structural lung disease not identified by screening spirometry.

journal of global health

Prevalence and correlates of chronic obstructive pulmonary disease and chronic respiratory symptoms in rural southwestern Uganda: a cross-sectional, population-based study