Air pollution and risk of respiratory and cardiovascular hospitalizations in the most populous city in Vietnam

Abstract

Air pollution has become an alarming issue in Vietnam recently; however, there was only one study so far on the effects of ambient air pollution on population health. Our study aimed to investigate the short-term effects of air pollutants including PM10, NO2, SO2, and O3 on respiratory and cardiovascular hospitalizations in Ho Chi Minh City (HCMC), the largest city in Vietnam. Data on hospitalization from the two largest hospitals in HCMC and daily records of PM10, NO2, SO2, O3 and meteorological data were collected from February 2004 to December 2007. A time-series regression analysis with distributed lag model was applied for data analysis. Changes in levels of NO2 and PM10 were strongly associated with hospital admissions for both respiratory and cardiovascular diseases (CVD); whereas levels of SO2 were only moderately associated with respiratory and CVD hospital admissions and O3 concentration was not associated with any of them. For a 10μg/m(3) increase of each air pollutant, the risk of respiratory admissions increased from 0.7% to 8% while the risk of CVD admissions increased from 0.5% to 4%. Females were found to be more sensitive than males to exposure to air pollutants in regard to respiratory diseases. In regard to CVD, females (RR, 1.04, 95% CI, 1.01-1.07) had a slightly higher risk of admissions than males (RR, 1.03, 95% CI, 1-1.06) to exposure to NO2. In contrast, males (RR, 1.007, 95%CI, 1-1.01) had a higher risk of admission than females (RR, 1.004, 95%CI, 1.001-1.007) to exposure to PM10. People in the age group of 5-65year-olds had a slightly higher risk of admissions caused by air pollutants than the elderly (65+years old) except for a significant effect of PM10 on the risk of cardiovascular admissions was found for the elderly only.

Associations of short-term exposure to air pollution with respiratory hospital admissions in Arak, Iran

“…Also other studies from China such as, Zhang et al’s study from Beijing, [1], Tao et al’s study from Lanzhou [20], and Liu et al’s study from Jinan [22], reported that an increase of 10 μg/m 3 of SO 2 corresponded to a 35%, 0.5% and 1.2% increase of respiratory diseases hospitalizations, respectively. Another study done by Phung et al from Vietnam also found that SO 2 was positively associated with the number of respiratory hospital admissions [36]. The mean annual concentration of SO 2 in most of the mentioned studies that reported significant association between SO 2 levels and respiratory hospital admissions, were higher than the present study.…”

“…A study done by Wilson et al from Europe in 2005 reported that increases in O 3 , was not positively associated with the number of all respiratory hospitalizations in Portland and Manchester, UK [19]. Another study done by Phung et al investigated air pollution and the risk of respiratory and cardiovascular hospitalizations in Vietnam and did not show any significant association between O 3 and respiratory hospitalizations [36]. Also Fung et al study in 2005 in Ontario, Canada did not find any association between O 3 and respiratory diseases admissions either [6].…”

“…This study used Generalized Linear Models (GLM) and Distributed Lag Models (DLM) within the family of Poisson distribution [35, 36], (Eq.1). We checked Poisson regression assumptions and because of its over dispersion we use quasi-Poisson regression models.…”

“…The Distributed Lag Model was used for lags up to 7 days (0–7 days), in order to evaluate the delayed effect of air pollutants [1, 36]. In order to control for seasonality and long-term trend in the data, a flexible spline function of time with 7 degrees of freedom (df) per year was used [35].…”

“…This variable shows the time interval from the previous holiday in days. Finally, we provide separate models for each pollutant, to reduce potential co-linearity between them [36]. The final model was described as below, (Eq.…”