Air pollution and hemorrhagic fever with renal syndrome in South Korea: An ecological correlation study

Seung Seok Han, Sunhee Kim, Yunhee Choi, Suhnggwon Kim, Yon Su Kim

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13 Scopus citations

Abstract

Background: The effects of air pollution on the respiratory and cardiovascular systems, and the resulting impacts on public health, have been widely studied. However, little is known about the effect of air pollution on the occurrence of hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease. In this study, we evaluated the correlation between air pollution and HFRS incidence from 2001 to 2010, and estimated the significance of the correlation under the effect of climate variables. Methods. We obtained data regarding HFRS, particulate matter smaller than 10 μm (PM10) as an index of air pollution, and climate variables including temperature, humidity, and precipitation from the national database of South Korea. Poisson regression models were established to predict the number of HFRS cases using air pollution and climate variables with different time lags. We then compared the ability of the climate model and the combined climate and air pollution model to predict the occurrence of HFRS. Results: The correlations between PM 10 and HFRS were significant in univariate analyses, although the direction of the correlations changed according to the time lags. In multivariate analyses of adjusted climate variables, the effects of PM 10 with time lags were different. However, PM10 without time lags was selected in the final model for predicting HFRS cases. The model that combined climate and PM10 data was a better predictor of HFRS cases than the model that used only climate data, for both the study period and the year 2011. Conclusions: This is the first report to document an association between HFRS and PM10 level.

Original languageEnglish
Article number347
JournalBMC Public Health
Volume13
Issue number1
DOIs
StatePublished - 2013

Keywords

  • Air pollution
  • Hantavirus
  • Hemorrhagic fever with renal syndrome
  • Infection
  • Particulate matter

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