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Are associations between socio-economic characteristics and exposure to air pollution a question of study area size? An example from Scania, Sweden

Stroh, Emilie LU ; Oudin, Anna LU ; Gustafsson, Susanna LU ; Pilesjö, Petter LU ; Harrie, Lars LU ; Strömberg, Ulf LU and Jakobsson, Kristina LU (2005) In International Journal of Health Geographics 4(30).
Abstract
BACKGROUND: Numerous studies have shown that exposure to air pollutants in the area of residence and the socio-economic status of an individual may be related. Therefore, when conducting an epidemiological study on the health effect of air pollution, socio-economy may act as a confounding factor. In this paper we examine to what extent socio-economic status and concentrations of NO2 in the county/region of Scania, southern Sweden, are associated and if such associations between these factors differ when studying them at county or city level. To perform this study we used high-resolution census data and modelled the annual exposure to NO2 using an emission database, a dispersion modelling program and a geographical information system (GIS).... (More)
BACKGROUND: Numerous studies have shown that exposure to air pollutants in the area of residence and the socio-economic status of an individual may be related. Therefore, when conducting an epidemiological study on the health effect of air pollution, socio-economy may act as a confounding factor. In this paper we examine to what extent socio-economic status and concentrations of NO2 in the county/region of Scania, southern Sweden, are associated and if such associations between these factors differ when studying them at county or city level. To perform this study we used high-resolution census data and modelled the annual exposure to NO2 using an emission database, a dispersion modelling program and a geographical information system (GIS). RESULTS: The results from this study confirm that socio-economic status and the levels of NO2 in the area of residence are associated in some cities. The associations vary considerably between cities within the same county (Scania). Even for cities of similar sizes and population bases the associations observed are different. Studying the cities together or separately yields contradictory results, especially when education is used as a socio-economic indicator. CONCLUSION: Four conclusions have been drawn from the results of this study. 1) Adjusting for socio-economy is important when investigating the health effects of air pollution. 2) The county of Scania seems to be heterogeneous regarding the association between air pollution and socio-economy. 3) The relationship between air pollution and socio-economy differs in the five cities included in our study, depending on whether they are analysed separately or together. It is therefore inadvisable to determine and analyse associations between socio-economy and exposure to air pollutants on county level. This study indicates that the size and choice of study area is of great importance. 4) The selection of socio-economic indices (in this study: country of birth and education level) is important. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
International Journal of Health Geographics
volume
4
issue
30
publisher
BioMed Central
external identifiers
  • pmid:16288656
  • scopus:28544435619
ISSN
1476-072X
DOI
10.1186/1476-072X-4-30
language
English
LU publication?
yes
id
ddd05b23-6ce2-4326-aedf-4c1438908b3d (old id 1132974)
date added to LUP
2008-06-25 15:46:02
date last changed
2017-11-12 03:59:22
@article{ddd05b23-6ce2-4326-aedf-4c1438908b3d,
  abstract     = {BACKGROUND: Numerous studies have shown that exposure to air pollutants in the area of residence and the socio-economic status of an individual may be related. Therefore, when conducting an epidemiological study on the health effect of air pollution, socio-economy may act as a confounding factor. In this paper we examine to what extent socio-economic status and concentrations of NO2 in the county/region of Scania, southern Sweden, are associated and if such associations between these factors differ when studying them at county or city level. To perform this study we used high-resolution census data and modelled the annual exposure to NO2 using an emission database, a dispersion modelling program and a geographical information system (GIS). RESULTS: The results from this study confirm that socio-economic status and the levels of NO2 in the area of residence are associated in some cities. The associations vary considerably between cities within the same county (Scania). Even for cities of similar sizes and population bases the associations observed are different. Studying the cities together or separately yields contradictory results, especially when education is used as a socio-economic indicator. CONCLUSION: Four conclusions have been drawn from the results of this study. 1) Adjusting for socio-economy is important when investigating the health effects of air pollution. 2) The county of Scania seems to be heterogeneous regarding the association between air pollution and socio-economy. 3) The relationship between air pollution and socio-economy differs in the five cities included in our study, depending on whether they are analysed separately or together. It is therefore inadvisable to determine and analyse associations between socio-economy and exposure to air pollutants on county level. This study indicates that the size and choice of study area is of great importance. 4) The selection of socio-economic indices (in this study: country of birth and education level) is important.},
  author       = {Stroh, Emilie and Oudin, Anna and Gustafsson, Susanna and Pilesjö, Petter and Harrie, Lars and Strömberg, Ulf and Jakobsson, Kristina},
  issn         = {1476-072X},
  language     = {eng},
  number       = {30},
  publisher    = {BioMed Central},
  series       = {International Journal of Health Geographics},
  title        = {Are associations between socio-economic characteristics and exposure to air pollution a question of study area size? An example from Scania, Sweden},
  url          = {http://dx.doi.org/10.1186/1476-072X-4-30},
  volume       = {4},
  year         = {2005},
}