Impact of haze and air pollution-related hazards on hospital admissions in Guangzhou, China
Authors: Zhang, Z; Wang, J; Chen, L; Chen, X; Sun, G; Zhong, N; Kan, H; Lu, W
Environmental Science and Pollution Research 21:4236-4244.
HERO ID: 2214248
Guangzhou is a metropolitan in south China with unique pollutants and geographic location. Unlike those . . .
Guangzhou is a metropolitan in south China with unique pollutants and geographic location. Unlike those in western countries and the rest of China, the appearance of haze in Guangzhou is often (about 278 days per year on average of 4 years). Little is known about the influence of these hazes on health. In this study, we investigated whether short-term exposures to haze and air pollution are associated with hospital admissions in Guangzhou. The relationships between haze, air pollution, and daily hospital admissions during 2008-2011 were assessed using generalized additive model. Studies were categorized by gender, age, season, lag, and disease category. In haze episodes, an increase in air pollutant emissions corresponded to 3.46 (95 % CI, 1.67, 5.27) increase in excessive risk (ER) of total hospital admissions at lag 1, 11.42 (95 % CI, 4.32, 18.99) and 11.57 (95 % CI, 4.38, 19.26) increases in ERs of cardiovascular illnesses at lags 2 and 4 days, respectively. As to total hospital admissions, an increase in NO2 was associated with a 0.73 (95 % CI, 0.11, 1.35) and a 0.28 (95 % CI, 0.11, 0.46) increases in ERs at lag 5 and lag 05, respectively. For respiratory illnesses, increases in NO2 was associated with a 1.94 (95 % CI, 0.50, 3.40) increase in ER at lag 0, especially among chronic obstructive pulmonary disease. Haze (at lag1) and air pollution (for NO2 at lag 5 and for SO2 at lag3) both presented more drastic effects on the 19 to 64 years old and in the females. Together, we demonstrated that haze pollution was associated with total and cardiovascular illnesses. NO2 was the sole pollutant with the largest risk of hospital admissions for total and respiratory diseases in both single- and multi-pollutant models.