Abstract
BackgroundThe 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.MethodsThe 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.ResultsGenerally, 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.ConclusionLow 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.
Highlights
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
We suggest that small-area analyses may provide important insights into the processes and factors that are associated with low participation rates and that this may help to develop spatially focused approaches to improve the participation rates in disadvantaged neighborhoods
Despite rising overall MSP participation rates for the three periods from 48 % (2007/08) over 50 % (2009/10) to 54 % (2011/12) (Referenzzentrum MS), a concentration of statistical districts with low participation rates persisted in the inner city of Dortmund, while the outer districts had consistently higher participation rates (Fig. 2a–c)
Summary
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. Mammography screening is a procedure of secondary cancer prevention with an aim of detecting breast cancer in early stages where therapy is less invasive (e.g., breastconserving therapies instead of mastectomy), remaining lifespans are extended and, ideally, breast cancer mortality is reduced Despite these expected benefits and the free provision by all statutory health insurances, the overall participation rates range only between 50 and 55 % [1]. Population-based surveys demonstrate that significant gaps exist in screening mammography uptake across population subgroups [2] These differences are believed to substantially contribute to a higher prevalence of late stage breast cancer at diagnosis among vulnerable populations, including racial and ethnic minorities [3] and low-income groups [4, 5]. We suggest that small-area analyses may provide important insights into the processes and factors that are associated with low participation rates and that this may help to develop spatially focused approaches to improve the participation rates in disadvantaged neighborhoods
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