Air Quality, Atmosphere & Health

, Volume 10, Issue 9, pp 1139–1149 | Cite as

Using spatio-temporal land use regression models to address spatial variation in air pollution concentrations in time series studies

  • Konstantina Dimakopoulou
  • Alexandros Gryparis
  • Klea KatsouyanniEmail author


Time series studies are used to assess the effects of short-term exposures to PM10 and NO2 on mortality using an integrated pollutant series taken to characterize exposure over a large area. We propose using spatio-temporal land use regression (LUR) models by smaller geographical sectors within an area of interest to account for spatial variability in these studies. Based on model-estimated time series, we conducted a case-crossover analysis for each sub-sector within two larger areas of interest (Athens and Thessaloniki, Greece) separately to investigate heterogeneity and provide combined results if appropriate. As sensitivity analysis, we compared the case-crossover method to classical time series analysis and also to using fixed site measurements only. For PM10 exposures in Athens, we found consistent adverse effects which were larger when using spatio-temporal LUR modeled concentrations (total mortality RR 2.55 and 95% CI − 0.30 to 5.39) compared to measurements (RR 0.36 and 95% CI − 0.21 to 0.93). For NO2, we found a similar magnitude in the effects, when using measurements from fixed sites (RR 0.81 and 95% CI 0.39 to 1.22) and modeled levels (RR 0.71 and 95% CI 0.14 to 1.28). Analysis by geographical sector did not add information over a unified analysis for the whole area. The effect estimates using classical Poisson regression time series yielded consistently smaller size effects compared to the case-crossover method. Our analysis demonstrates the potential of using spatio-temporal models in time series analysis for short-term air pollution effects to account for spatial variability in addition to the temporal.


Air pollution Spatio-temporal models Short-term health effects PM10 NO2 


Funding information

The work has been co-funded by the European Commission and the Greek government by the National Strategic Reference Framework 2007–2013 Contract Ref: MAPHEAT/SH3_3518.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11869_2017_500_MOESM1_ESM.docx (181 kb)
ESM 1 (DOCX 180 kb)


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Hygiene, Epidemiology, and Medical Statistics Medical SchoolNational and Kapodistrian UniversityAthensGreece
  2. 2.Department of Primary Care & Public Health Sciences and MRC-PHE Centre for Environment and HealthKing’s College LondonLondonUK
  3. 3.Department of Hygiene, Epidemiology, and Medical StatisticsUniversity of Athens Medical SchoolAthensGreece
  4. 4.Department of Primary Care & Public Health Sciences and Environmental Research GroupKing’s College LondonLondonUK

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