title: Small-area spatio-temporal analyses of participation rates in the mammography screening program in the city of Dortmund (NW Germany).
abstract: BACKGROUND
  The population-based mammography screening program (MSP) was implemented by the end of 2005 in Germany, and all women between 50 and 69 years are actively invited to a free biennial screening examination. However, despite the expected benefits, the overall participation rates range only between 50 and 55%. There is also increasing evidence that belonging to a vulnerable population, such as ethnic minorities or low income groups, is associated with a decreased likelihood of participating in screening programs. This study aimed to analyze in more detail the intra-urban variation of MSP uptake at the neighborhood level (i.e. statistical districts) for the city of Dortmund in northwest Germany and to identify demographic and socioeconomic risk factors that contribute to non-response to screening invitations.
  
  
  METHODS
  The numbers of participants by statistical district were aggregated over the three periods 2007/2008, 2009/2010, and 2011/2012. Participation rates were calculated as numbers of participants per female resident population averaged over each 2-year period. Bayesian hierarchical spatial models extended with a temporal and spatio-temporal interaction effect were used to analyze the participation rates applying integrated nested Laplace approximations (INLA). The model included explanatory covariates taken from the atlas of social structure of Dortmund.
  
  
  RESULTS
  Generally, participation rates rose for all districts over the time periods. However, participation was persistently lowest in the inner city of Dortmund. Multivariable regression analysis showed that migrant status and long-term unemployment were associated with significant increases of non-attendance in the MSP.
  
  
  CONCLUSIONS
  Low income groups and immigrant populations are clustered in the inner city of Dortmund and the observed spatial pattern of persistently low participation in the city center is likely linked to the underlying socioeconomic gradient. This corresponds with the findings of the ecological regression analysis manifesting socioeconomically deprived neighborhoods as risk factors for low attendance in the MSP. Spatio-temporal surveillance of participation in cancer screening programs may be used to identify spatial inequalities in screening uptake and plan spatially focused interventions.
authors.affiliation: Institute of Epidemiology and Social Medicine, Medical Faculty, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1 D3, D 48149, Münster, Germany. dorothea.lemke@uni-muenster.de.|Institute for Geoinformatics, Geosciences Faculty, Westfälische Wilhelms-Universität Münster, Münster, Germany. dorothea.lemke@uni-muenster.de.
authors.forename: Dorothea
authors.initials: D
authors.lastname: Lemke
authors.affiliation: Reference Center for the Mammography Screening Program, University Hospital, Westfälische Wilhelms-Universität Münster, Münster, Germany. berkemeyer@referenzzentrum-ms.de.
authors.forename: Shoma
authors.initials: S
authors.lastname: Berkemeyer
authors.affiliation: Epidemiological Cancer Registry North Rhine-Westphalia, Münster, Germany. Volkmar.Mattauch@krebsregister.nrw.de.
authors.forename: Volkmar
authors.initials: V
authors.lastname: Mattauch
authors.affiliation: Epidemiological Cancer Registry North Rhine-Westphalia, Münster, Germany. Oliver.Heidinger@krebsregister.nrw.de.
authors.forename: Oliver
authors.initials: O
authors.lastname: Heidinger
authors.affiliation: Institute for Geoinformatics, Geosciences Faculty, Westfälische Wilhelms-Universität Münster, Münster, Germany. edzer.pebesma@uni-muenster.de.
authors.forename: Edzer
authors.initials: E
authors.lastname: Pebesma
authors.affiliation: Institute of Epidemiology and Social Medicine, Medical Faculty, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1 D3, D 48149, Münster, Germany. hense@uni-muenster.de.|Epidemiological Cancer Registry North Rhine-Westphalia, Münster, Germany. hense@uni-muenster.de.
authors.forename: Hans-Werner
authors.initials: HW
authors.lastname: Hense
mesh_terms: D001499:Bayes Theorem; D055088:Early Detection of Cancer / Q000706:statistics & numerical data*; D005260:Female; D005858:Germany; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D010358:Patient Participation / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012307:Risk Factors; D017062:Small-Area Analysis; D012959:Socioeconomic Factors; D062211:Spatio-Temporal Analysis