Evaluation of Risk Factors for Chronic Obstructive Pulmonary Disease in the Middle-Aged and Elderly Rural Population of Northeast China Using Logistic Regression and Principal Component Analysis

Rui Wang,1– 4 Wei Zhang,1– 3 Yuanyuan Li,1– 3 Yuting Jiang,1– 3 Hongqi Feng,1– 3 Yang Du,1– 3 Zhe Jiao,1– 3 Li Lan,4 Xiaona Liu,1– 3 Bingyun Li,1– 3 Chang Liu,1– 3 Xingbo Gu,5 Fang Chu,1– 3 Yuncheng Shen,1– 3 Chenpeng Zhu,1– 3 Xinhua Shao,1– 3 Simeng Tong,1– 3 Dianjun Sun1– 3 1Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, 150081, People’s Republic of China; 2National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, 150081, People’s Republic of China; 3Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, 150081, People’s Republic of China; 4Harbin Center for Disease Control and Prevention, Harbin, 150056, People’s Republic of China; 5Department of Biostatistics, School of Public Health, Hainan Medical University, Haikou, 571199, People’s Republic of ChinaCorrespondence: Dianjun Sun, Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Baojian Road 157, Harbin, Heilongjiang Province, 150081, People’s Republic of China, Tel +86-13313685318, Fax +86 45186612695, Email hrbmusdj@163.comPurpose: To investigate the environmental, immune, and inflammatory factors associated with chronic obstructive pulmonary disease (COPD) in middle-aged and older Chinese individuals.Patients and Methods: A community-based case–control study was conducted among 471 patients with COPD and 485 controls. The information on COPD of the participants was collected through face-to-face interviews, and serum samples were measured at the laboratory. The main risk factors for COPD were analyzed using principal component analysis (PCA) and logistic regression.Results: Nine hundred and fifty-six respondents were included in the analysis. The results of the PCA-logistic regression analysis showed significant differences in the environmental factors, medical history, and serum C-reactive protein (CRP) levels between patients and controls. COPD was markedly more usual in those with smoking index > 200 (OR, 1.42; 95% CI, 1.28– 1.57); exposure to outdoor straw burning (OR, 1.64; 95% CI, 1.47– 1.83); use of coal, wood, and straw indoors (OR, 2.31; 95% CI, 1.92– 2.78); history of respiratory disease and coronary heart disease (OR, 3.58; 95% CI, 3.12– 4.10), congestive heart failure (OR, 1.23; 95% CI, 1.09– 1.38), and cerebrovascular disease (OR, 1.15; 95% CI,1.02– 1.31); and higher serum level of CRP (OR, 1.20; 95% CI, 1.11– 1.30). Compared to the logistic regression analysis, PCA logistic regression analysis identified more important risk factors for COPD.Conclusion: PCA-logistic regression analysis was first utilized to explore the influencing factors among rural residents in Northeast China Environmental aged 40 years and above, it was found that environmental factors, medical history, and serum CRP levels mainly affected the prevalence of COPD.Keywords: chronic obstructive pulmonary disease, collinearity, principal component, logistic regression