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Conference Paper: The Associations between Exposures to Traffic and Mortality Risks in Hong Kong

TitleThe Associations between Exposures to Traffic and Mortality Risks in Hong Kong
Authors
Issue Date2013
PublisherThe Urban and Regional Information Systems Association (URISA.
Citation
The 4th GIS in Public Health Conference of Urban and Regional Information Systems Association (URISA), Miami, Florida, USA, 17-20 June 2013. In the Conference Program of the 4th GIS in Public Health Conference of URISA, 2013, p. 13-14 How to Cite?
AbstractBackground: Traffic is a main source of air pollution in Hong Kong. The associations between traffic related health effects have been 13 reported mostly for European and North America, but very few for densely populated urban environments in Asia. Objective: To assess traffic related health effects in the population of Hong Kong. Methods: Residential locations of persons who died during 2010 were documented in 209 Tertiary Planning Units (TPU) of Hong Kong. The 2010 Annual Average Daily Traffic (AADT) data were retrieved from traffic census reports. Three indicators of trafficrelated exposure by TPU were computed using ArcGIS (version 9.2): (i) Road Density (RD) = total length of roads divided by area; (ii) Traffic Density (TD) = RD times AADT; and (iii) Vehicle Density (VD) = AADT divided by area. They were further categorizing into three levels by tertile: low, middle and high. Poisson regression models of standardized mortality ratios were fitted with adjustment for ethnicity, marital status, education level, housing type and income. Results: The ranges of risk ratios (95% CI) of mortality for high or middle relative to low exposure level were: for all-nature causes 1.17 (1.13-1.21)-1.32(1.27-1.36), cardiovascular 1.16(1.09-1.23)- 1.27(1.19-1.37), respiratory 1.30(1.20-1.42)-1.44(1.33-1.56), and cancer 1.08(1.02-1.14)-1.28(1.20-1.36). The risk ratios were the highest for the middle level of TD or VD, but increased from middle to high level of RD. Conclusions: Traffic related exposures measured at the neighborhood levels are associated with mortality. Investigations at individual levels are necessary to account for confounding.
DescriptionPoster presentation
Persistent Identifierhttp://hdl.handle.net/10722/191050

 

DC FieldValueLanguage
dc.contributor.authorMa, Xen_US
dc.contributor.authorThach, TQen_US
dc.contributor.authorLai, PCen_US
dc.contributor.authorChau, YKen_US
dc.contributor.authorLai, HKen_US
dc.contributor.authorWong, CMen_US
dc.date.accessioned2013-09-17T16:12:58Z-
dc.date.available2013-09-17T16:12:58Z-
dc.date.issued2013en_US
dc.identifier.citationThe 4th GIS in Public Health Conference of Urban and Regional Information Systems Association (URISA), Miami, Florida, USA, 17-20 June 2013. In the Conference Program of the 4th GIS in Public Health Conference of URISA, 2013, p. 13-14en_US
dc.identifier.urihttp://hdl.handle.net/10722/191050-
dc.descriptionPoster presentation-
dc.description.abstractBackground: Traffic is a main source of air pollution in Hong Kong. The associations between traffic related health effects have been 13 reported mostly for European and North America, but very few for densely populated urban environments in Asia. Objective: To assess traffic related health effects in the population of Hong Kong. Methods: Residential locations of persons who died during 2010 were documented in 209 Tertiary Planning Units (TPU) of Hong Kong. The 2010 Annual Average Daily Traffic (AADT) data were retrieved from traffic census reports. Three indicators of trafficrelated exposure by TPU were computed using ArcGIS (version 9.2): (i) Road Density (RD) = total length of roads divided by area; (ii) Traffic Density (TD) = RD times AADT; and (iii) Vehicle Density (VD) = AADT divided by area. They were further categorizing into three levels by tertile: low, middle and high. Poisson regression models of standardized mortality ratios were fitted with adjustment for ethnicity, marital status, education level, housing type and income. Results: The ranges of risk ratios (95% CI) of mortality for high or middle relative to low exposure level were: for all-nature causes 1.17 (1.13-1.21)-1.32(1.27-1.36), cardiovascular 1.16(1.09-1.23)- 1.27(1.19-1.37), respiratory 1.30(1.20-1.42)-1.44(1.33-1.56), and cancer 1.08(1.02-1.14)-1.28(1.20-1.36). The risk ratios were the highest for the middle level of TD or VD, but increased from middle to high level of RD. Conclusions: Traffic related exposures measured at the neighborhood levels are associated with mortality. Investigations at individual levels are necessary to account for confounding.-
dc.languageengen_US
dc.publisherThe Urban and Regional Information Systems Association (URISA.-
dc.relation.ispartofGIS in Public Health Conference of Urban and Regional Information Systems Association, URISA 2013en_US
dc.titleThe Associations between Exposures to Traffic and Mortality Risks in Hong Kongen_US
dc.typeConference_Paperen_US
dc.identifier.emailThach, TQ: thach@hku.hken_US
dc.identifier.emailLai, PC: pclai@hku.hken_US
dc.identifier.emailLai, HK: hklai@graduate.hku.hken_US
dc.identifier.emailWong, CM: hrmrwcm@hku.hken_US
dc.identifier.authorityThach, TQ=rp00450en_US
dc.identifier.authorityLai, PC=rp00565en_US
dc.identifier.authorityLai, HK=rp01527en_US
dc.identifier.hkuros224476en_US
dc.identifier.spage13-
dc.identifier.epage14-
dc.publisher.placeUnited States-

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