Asset Details
Do you wish to reserve the book?
Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis
Do you wish to request the book?
Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Clustering of disability pension and socioeconomic disadvantage in Sweden: a geospatial analysis
2022
Overview
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.
