Methods: We analyzed data from the fourth Korean National Health and Nutrition Examination Survey and National Health Insurance claims in 2007-2012. Subjects who were 19 years old and more and had forced expiratory volume in 1 second (FEV1) ≥ 60% predicted and a ratio of FEV1 to forced vital capacity (FVC) < 0.7 were included. K-means clustering was performed to explore subtypes. For clustering analysis, six key input variables, age, body mass index (BMI), FEV1% predicted, the presence or absence of self-reported wheezing, smoking status, and pack-years of smoking were selected.
Results: Among a total of 2,140 subjects, five subgroups identified through k-means clustering include putative “near-normal (n=232)”, “asthmatic (n=392)”, “COPD (n=37)”, “asthma-overlap (n=893)” and “COPD-overlap (n=586)” subtypes. Among five subgropus, near-normal subgroup showed the oldest mean age (72±7 years) and the highest FEV1 (102±8% predicted), and asthmatic subgroup was the youngest (46±9 years). Asthma-overlap subgroup had the lowest FEV1 (77±9% predicted). COPD and COPD-overlap subgroups were male-predominant (100% and 98%, respectively) and all current or ex-smokers. When applying the lower limit of normal FEV1/FVC as a criterion for airway obstruction, asthma group showed the highest prevalence of airway obstruction. While COPD, asthma-overlap and COPD-overlap subgroups showed high prescription rate of respiratory medicine, asthmatic subgroup had the lowest prescription rate despite the highest proportion of self-reported wheezing. Except asthmatic subgroup, comorbidities such as hypertension, diabetes mellitus, hyperlipidemia and coronary artery disease were frequently observed. Although COPD subgroup represents only 2% of total subjects, they showed the highest mean medical cost and health utilization, comprising 5% of the total cost. When calculating a ratio of total medical expense to household income, mean ratio was the highest in COPD subgroup.
Conclusion: Subjects with mild to moderate airflow limitation exhibited clinical and epidemiological heterogeneity. Each subgroup may have a different level of demand for health resources.