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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
Article

Abstract

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.

Keywords

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

Notes

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)

References

  1. Alessandrini ER, Faustini A, Chiusolo M, Stafoggia M, Gandini M, Demaria M, Antonelli A, Arena P, Biggeri A, Canova C, Casale G, Cernigliaro A, Garrone E, Gherardi B, Gianicolo EA, Giannini S, Iuzzolino C, Lauriola P, Mariottini M, Pasetto P, Randi G, Ranzi A, Santoro M, Selle V, Serinelli M, Stivanello E, Tominz R, Vigotti MA, Zauli-Sajani S, Forastiere F, Cadum E, Gruppocollaborativo EpiAir2 (2013) Air pollution and mortality in twenty-five Italian cities: results of the EpiAir2 Project. Epidemiol Prev 37:220–229Google Scholar
  2. Analitis A, Katsouyanni K, Dimakopoulou K, Samoli E, Nikoloulopoulos AK, Petasakis Y, Touloumi G, Schwartz J, Anderson HR, Cambra K, Forastiere F, Zmirou D, Vonk JM, Clancy L, Kriz B, Bobvos J, Pekkanen J (2006 Mar) Short-term effects of ambient particles on cardiovascular and respiratory mortality. Epidemiology 17(2):230–233CrossRefGoogle Scholar
  3. Avlund K, Damsgaard MT, Schroll M (2001) Tiredness as determinant of subsequent use of health and social services among nondisabled elderly people. J Aging Health 13(2):267–286CrossRefGoogle Scholar
  4. Basagaña X, Aguilera I, Rivera M, Agis D, Foraster M, Marrugat J, Elosua R, Künzli N (2013 Oct 15) Measurement error in epidemiologic studies of air pollution based on land-use regression models. Am J Epidemiol 178(8):1342–1346CrossRefGoogle Scholar
  5. Berkey CS, Hoaglin DC, Mosteller F et al (1995) A random-effects regression model for metaanalysis. Stat Med 14:395–411CrossRefGoogle Scholar
  6. Diggle PJ (1990) Time series: a biostatistical introduction. Clarendon Press, OxfordGoogle Scholar
  7. Dionisio KL, Baxter LK, Burke J, Özkaynak H (2016) The importance of the exposure metric in air pollution epidemiology studies: when does it matter, and why? Air Qual Atmos Health 9:495–502CrossRefGoogle Scholar
  8. ESRI (2011) ArcGIS desktop: release 10. Redlands, CA: Environmental Systems Research InstituteGoogle Scholar
  9. ESRI (2016) ArcGIS desktop: release 10.3. Redlands, CA: Environmental Systems Research Institute. http://desktop.arcgis.com/en/arcmap/10.3/tools/data-management-toolbox/create-random-points.htm (Retrieved on 27 March 2017)
  10. Gryparis A, Dimakopoulou K, Pedeli X, Katsouyanni K (2014) Spatio-temporal semiparametric models for NO2 and PM10 concentration levels in Athens, Greece. Sci Total Environ 479–480:21–30Google Scholar
  11. Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558CrossRefGoogle Scholar
  12. Hoek G, Beelen R, de Hoogh K, Vienneau D, Gulliver J, Fischer P, Briggs D (2008) A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmos Environ 42:7561–7578CrossRefGoogle Scholar
  13. Kinney PL, Aggarwal M, Northridge ME, Janssen NA, Shepard P (2000) Airborne concentrations of PM2.5 and diesel exhaust particles on Harlem sidewalks: a community-based pilot study. Environ Health Perspect 108:213–218Google Scholar
  14. Kunzli N, Jerrett M, Mack WJ, Beckerman B, LaBree L, Gilliland F et al (2005) Ambient air pollution and atherosclerosis in Los Angeles. Environ Health Perspect 113(2):201–206CrossRefGoogle Scholar
  15. Laden F, Neas LM, Dockery DW, Schwartz J (2000) Association of fine particulate matter from different sources with daily mortality in six U.S. cities. Environ Health Perspect 108:941–947CrossRefGoogle Scholar
  16. Lu Y, Symons JM, Geyh AS, Zeger SL (2008) An approach to checking case-crossover analyses based on equivalence with time-series methods. Epidemiology 19:169–175CrossRefGoogle Scholar
  17. Maynard D, Coull BA, Gryparis A, Schwartz J (2007) Mortality risk associated with short-term exposure to traffic particles and sulfates. Environ Health Perspect 115(5):751–755CrossRefGoogle Scholar
  18. Miller KA, Siscovick DS, Sheppard L, Shepherd K, Sullivan JH, Anderson GL et al (2007) Long-term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med 356:447–458CrossRefGoogle Scholar
  19. Milojevic A, Armstrong BG, Gasparrini A, Bohnenstengel SI, Barratt B, Wilkinson P. Methods to Estimate Acclimatization to the Urban Heat Island Effects on Heat- and Cold-Related Mortality. Environ Health Perspect. 2016 Feb 9. [Epub ahead of print]Google Scholar
  20. Perrakis K, Gryparis A, Schwartz J, Le Tertre A, Katsouyanni K, Forastiere F, Stafoggia M, Samoli E (2014) Controlling for seasonal patterns and time varying confounders in time-series epidemiological models: a simulation study. Stat Med 33(28):4904–4918CrossRefGoogle Scholar
  21. Pope CA III, Dockery DW, Schwartz J (1995) Review of epidemiological evidence of health effects of particulate air pollution. InhalnToxicol 7:1–18Google Scholar
  22. Puett RC, Hart JE, Schwartz J, Hu FB, Liese AD, Laden F (2011) Are particulate matter exposures associated with risk of type 2 diabetes? Environ Health Perspect 119(3):384–389CrossRefGoogle Scholar
  23. Samoli E, Aga E, Touloumi G, Nisiotis K, Forsberg B, Lefranc A, Pekkanen J, Wojtyniak B, Schindler C, Niciu E, Brunstein R, DodicFikfak M, Schwartz J, Katsouyanni K (2006) Short-term effects of nitrogen dioxide on mortality: an analysis within the APHEA project. EurRespir J 27(6):1129–1138CrossRefGoogle Scholar
  24. Samoli E, Kougea E, Kassomenos P, Analitis A, Klea K (2011) Does the presence of desert dust modify the effect of PM10 on mortality in Athens, Greece? Sci Total Environ 409(11):2049–2054CrossRefGoogle Scholar
  25. Sheppard L, Burnett RT, Szpiro AA, Kim SY, Jerrett M, Pope CA III, Brunekreef B (2012) Confounding and exposure measurement error in air pollution epidemiology. Air Qual Atmos Health 5:203–216CrossRefGoogle Scholar
  26. Simoni M, Baldacci S, Maio S, Cerrai S, Sarno G, Viegi G (2015) Adverse effects of outdoor pollution in the elderly. J Thorac Dis 7(1):34–45Google Scholar
  27. Touloumi G, Katsouyanni K, Zmirou D, Schwartz J, Spix C, Ponce de Leon A, Tobias A, Quenel P, Rabczenco D, Bacharova L, Bisanti L, Vonk JM, Ponka A (1997) Short term effects of ambient oxidants exposure on mortality: a combined analysis within the APHEA project. Am J Epidemiol 146:177–185CrossRefGoogle Scholar
  28. Whitaker HJ, Hocine MN, Farrington CP (2007) On case-crossover methods for environmental time series data. Environmetrics 18:157–171CrossRefGoogle Scholar

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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