Studies on health effects of air pollution often use daily mean concentration to estimate exposure while ignoring daily variations. This study examined the health effects of daily variation of PM2.5. We calculated daily mean and standard deviations of PM2.5 in Hong Kong between 1998 and 2011. We used a generalized additive model to estimate the association between respiratory mortality and daily mean and variation of PM2.5, as well as their interaction. We controlled for potential confounders, including temporal trends, day of the week, meteorological factors, and gaseous air pollutants. Both daily mean and standard deviation of PM2.5 were significantly associated with mortalities from overall respiratory diseases and pneumonia. Each 10 μg/m(3) increment in daily mean concentration at lag 2 day was associated with a 0.61% (95% CI: 0.19%, 1.03%) increase in overall respiratory mortality and a 0.67% (95% CI: 0.14%, 1.21%) increase in pneumonia mortality. And a 10 μg/m(3) increase in standard deviation at lag 1 day corresponded to a 1.40% (95% CI: 0.35%, 2.46%) increase in overall respiratory mortality, and a 1.80% (95% CI: 0.46%, 3.16%) increase in pneumonia mortality. We also observed a positive but non-significant synergistic interaction between daily mean and variation on respiratory mortality and pneumonia mortality. However, we did not find any significant association with mortality from chronic obstructive pulmonary diseases. Our study suggests that, besides mean concentration, the standard deviation of PM2.5 might be one potential predictor of respiratory mortality in Hong Kong, and should be considered when assessing the respiratory effects of PM2.5.
Keywords: Fine particulate matter air pollution; Respiratory mortality; Standard deviation; Time series study.
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