Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis

Author:

Virtanen Marianna12ORCID,Heikkilä Katriina13,Vahtera Jussi4ORCID,Kivimäki Mika567,Halonen Jaana I38,Alexanderson Kristina1,Rautiainen Simo9,Lallukka Tea15ORCID,Mittendorfer-Rutz Ellenor1

Affiliation:

1. Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet , Stockholm, Sweden

2. School of Educational Sciences and Psychology, University of Eastern Finland , Joensuu, Finland

3. Finnish Institute for Health and Welfare , Helsinki, Finland

4. Department of Public Health, University of Turku and Turku University Hospital , Turku, Finland

5. Clinicum, Department of Public Health, University of Helsinki , Helsinki, Finland

6. Department of Epidemiology and Public Health, University College London , London, UK

7. Finnish Institute of Occupational Health , Helsinki, Finland

8. Department of Psychology, Stockholm University , Stockholm, Sweden

9. Faculty of Social Sciences and Business Sciences, Karelian Institute, University of Eastern Finland , Joensuu, Finland

Abstract

Abstract Background To characterize geospatial patterning of disadvantage in Sweden, we examined whether municipal-level indicators of socioeconomic disadvantage and disability pension (DP) rate were clustered, whether the different geospatial clusters were overlapping and whether the findings were similar among women and men. Methods Administrative national data from all 290 Swedish municipalities were used to determine the prevalence of DP and socioeconomic disadvantage [poverty, long-term unemployment, income inequality (GINI Index) and income inequality between women and men]. Geospatial cold spots (clusters of municipalities with a DP/socioeconomic disadvantage prevalence lower than the nationwide prevalence) and hot spots (clusters of municipalities with a DP/socioeconomic disadvantage higher than the nationwide prevalence) were identified, and whether a hot spot was overlapping with another hot spot and a cold spot overlapping with another cold spot were analysed using the Getis-Ord Gi statistics. Results Among women and men, cold spots of DP were most consistently located in the Stockholm area. Hot spots of DP were found in the mid-south Sweden, characterized by mid-sized urban centres in rural territories. High DP rate and socioeconomic disadvantage were overlapping, except for income inequality. Clusters of gender income inequality and women’s high DP rate were observed in mid-south Sweden. Conclusion DP and socioeconomic disadvantage are not randomly distributed in Sweden. Geospatial analyses revealed clusters of municipalities with high risk of both DP and socioeconomic disadvantage in certain areas and low risk in other areas. Further research is needed to identify preventive actions to decrease regional inequalities in work capacity.

Funder

Swedish Research Council for Health, Working Life and Welfare

Swedish Research Council

NordForsk

Academy of Finland

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health

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