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. 2022 Oct 3;32(5):703-708.
doi: 10.1093/eurpub/ckac096.

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

Marianna Virtanen  1   2 , Katriina Heikkilä  1   3 , Jussi Vahtera  4 , Mika Kivimäki  5   6   7 , Jaana I Halonen  3   8 , Kristina Alexanderson  1 , Simo Rautiainen  9 , Tea Lallukka  1   5 , Ellenor Mittendorfer-Rutz  1
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Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis

Marianna Virtanen et al. Eur J Public Health. .

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.

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Figures

Figure 1
Figure 1
Cold and hot spots of the prevalence of disability pension among women (A) and men (B) and overlapping cold and hot spots of disability pension between women and men (C)
Figure 2
Figure 2
Cold and hot spots of socioeconomic disadvantage indicators across Swedish municipalities: poverty (A), long-term unemployment (B), income inequality by GINI Index (C) and gender income inequality (between women and men) (D)
See this image and copyright information in PMC

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