The impact of the synergistic effect of SO2 and PM2.5/PM10 on obstructive lung disease in subtropical Taiwan

Abstract

Background: Chronic Obstructive lung diseases (COPD) are complex conditions influenced by various environmental, lifestyle, and genetic factors. Ambient air pollution has been identified as a potential risk factor, causing 4.2 million deaths worldwide in 2016, accounting for 25% of all COPD-related deaths and 26% of all respiratory infection-related deaths. This study aims to evaluate the associations among chronic lung diseases, air pollution, and meteorological factors.

Methods: This cross-sectional study obtained data from the Taiwan Biobank and Taiwan Air Quality Monitoring Database. We defined obstructive lung disease as patients with FEV1/FVC < 70%. Descriptive analysis between spirometry groups was performed using one-way ANOVA and the chi-square or Fisher's exact test. A generalized additive model (GAM) was used to evaluate the relationship between SO₂ and PM_2.5/PM₁₀ through equations and splines fitting.

Results: A total of 2,635 participants were enrolled. Regarding environmental factors, higher temperature, higher relative humidity, and lower rainfall were risk factors for obstructive lung disease. SO₂ was positively correlated with PM₁₀ and PM_2.5, with correlation coefficients of 0.53 (p < 0.0001) and 0.52 (p < 0.0001), respectively. Additionally, SO₂ modified the relative risk of obstructive impairment for both PM₁₀ [β coefficient (β) = 0.01, p = 0.0052] and PM_2.5 (β = 0.01, p = 0.0155). Further analysis per standard deviation (per SD) increase revealed that SO₂ also modified the relationship for both PM₁₀ (β = 0.11, p = 0.0052) and PM_2.5 (β = 0.09, p = 0.0155). Our GAM analysis showed a quadratic pattern for SO₂ (per SD) and PM₁₀ (per SD) in model 1, and a quadratic pattern for SO₂ (per SD) in model 2. Moreover, our findings confirmed synergistic effects among temperature, SO₂ and PM_2.5/PM₁₀, as demonstrated by the significant associations of bivariate (SO₂ vs. PM₁₀, SO₂ vs. PM_2.5) thin-plate smoothing splines in models 1 and 2 with obstructive impairment (p < 0.0001).

Conclusion: Our study showed high temperature, humidity, and low rainfall increased the risk of obstructive lung disease. Synergistic effects were observed among temperature, SO₂, and PM_2.5/PM₁₀. The impact of air pollutants on obstructive lung disease should consider these interactions.

Keywords: air pollutants; climate factors; generalized additive model; obstructive lung disease; synergistic effect.

Figure 1

Partial prediction of A) SO₂ (Per SD) and PM10 (Per SD) in model 1 and B) SO₂ (Per SD) and PM2.5 (Per SD) on the risk of obstructive impairment. A semiparametric model was performed by using the parametric effects of temperature (°C), relative humidity (%) and Rainfall (mm/day) as the linear part of the model. Obstructive impairment was associated with a quadratic pattern for the SO₂ (Per SD) and PM10 (Per SD) in model 1 and a quadratic pattern for the SO₂ (Per SD) but not PM2.5 (Per SD) in model 2.

Figure 2

Correlations between A) SO₂ (Per SD) and PM10 (Per SD) in model 1 and B) SO₂ (Per SD) and PM2.5 (Per SD) in model 2 of obstructive impairment were applied by the use of a generalized additive model (GAM), a smoothing spline nonparametric model. A semiparametric model was performed by using the parametric effects of temperature (°C), relative humidity (%) and Rainfall (mm/day) as the linear part of the model. The graphic suggests that there was an interaction, a diagonal pattern in model 1 and model 2, on the risk of obstructive impairment.