Prevalence, Associate Factors, and Disease Awareness of Chronic Obstructive Pulmonary Disease: A Large-Scale...

Chronic obstructive pulmonary disease (COPD) represents a significant global health burden with substantial morbidity and mortality worldwide. While smoking remains the predominant associate factor, emerging evidence suggests biomass fuel exposure and other environmental factors contribute significantly to disease development. Large-scale epidemiological studies are essential to identify modifiable associate factors and inform evidence-based prevention strategies.

We conducted a cluster-sampling cross-sectional survey of 65,680 participants aged 35-75 years during Jan 2023 to Dec 2024, to investigate COPD prevalence and associated associate factors in Tianjin, China. COPD diagnosis was established using post-bronchodilator spirometry with FEV1/FVC<70% as the diagnostic criterion. Comprehensive associate factor assessment included demographic variables (age, gender), anthropometric measures (BMI), smoking status (never, current, former), biomass fuel use for cooking or heating, and chronic cough symptoms. Statistical analysis employed univariate comparisons and multivariate logistic regression modeling to identify independent associate factors, calculating odds ratios (OR) with 95% confidence intervals (CI).

The overall COPD prevalence was 7.9% (5,160/65,680 participants) with significant demographic variations. Mean participant age was 54.5±10.9 years, with 41.6% male representation. Multivariate logistic regression identified several independent associate factors: advancing age (OR=1.049, 95% CI: 1.046-1.052, P<0.001), male gender (OR=1.402, 95% CI: 1.312-1.499, P<0.001), current smoking (OR=1.560, 95% CI: 1.445-1.684, P<0.001), former smoking (OR=1.460, 95% CI: 1.306-1.631, P<0.001), and biomass fuel use (OR=1.470, 95% CI: 1.317-1.641, P<0.001). BMI and chronic cough showed no significant associations in the multivariate model.

This large-scale epidemiological study confirms a substantial COPD burden with multiple modifiable associate factors. Beyond traditional smoking risks, biomass fuel exposure emerges as a significant independent predictor, highlighting the importance of environmental interventions. These findings support comprehensive prevention strategies targeting smoking cessation and clean energy initiatives, particularly for high-risk populations including older males and those with environmental exposures.