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Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries

BACKGROUND: Drug Use Disorder (DUD) is a major contributor to world-wide morbidity and mortality. The extensive national registers in Sweden provide the basis for a study of spatial and temporal patterns of DUD onset and recurrence in Sweden from 2001–2015. METHODS: To identify patterns of DUD over...

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Autores principales: Stewart, Kathleen, Kendler, Kenneth S., Westholm, Anton, Ohlsson, Henrik, Sundquist, Jan, Sundquist, Kristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906828/
https://www.ncbi.nlm.nih.gov/pubmed/36750781
http://dx.doi.org/10.1186/s12889-023-15149-1
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author Stewart, Kathleen
Kendler, Kenneth S.
Westholm, Anton
Ohlsson, Henrik
Sundquist, Jan
Sundquist, Kristina
author_facet Stewart, Kathleen
Kendler, Kenneth S.
Westholm, Anton
Ohlsson, Henrik
Sundquist, Jan
Sundquist, Kristina
author_sort Stewart, Kathleen
collection PubMed
description BACKGROUND: Drug Use Disorder (DUD) is a major contributor to world-wide morbidity and mortality. The extensive national registers in Sweden provide the basis for a study of spatial and temporal patterns of DUD onset and recurrence in Sweden from 2001–2015. METHODS: To identify patterns of DUD over space, time and gender for Swedish individuals aged 15–35, space–time clustering using SaTScan was applied. We used yearly information on residential locations in Demographic Statistical Areas (DeSO) for all of Sweden. The clustering analysis used a Poisson probability model and a null hypothesis that the expected number of cases in each DeSO was proportional to the population size of DeSOs. As SaTScan results can be unstable, steps were taken to determine stable clusters and to refine and optimize cluster size. Results for each gender-register combination were compared to the results of spatial clustering using Gi* statistics. The space–time scanning model was also run with an adjustment for neighborhood socioeconomic status to determine DUD prevalence as it relates to education, income, unemployment and receipt of social welfare. RESULTS: DUD prevalence increased over time. Males yielded more significant clusters than females for both criminal and medical registers. Female DUD prevalence rates increased over time, especially after 2012. Higher correlations in DUD rates existed across the two registers than across gender. Male clusters were present from 2004 onwards while female–criminal clusters appeared after 2007, and female–medical clusters not until 2010. By 2013, clusters existed for all gender–register combinations. Male–criminal clusters were concentrated in Stockholm, Göteborg and Malmö as were male and female-medical clusters. Neighborhood SES was more highly related to the distribution of criminal than medical DUD clusters. A persistent gap in core clusters was identified in Stockholm in an area with notably high SES. CONCLUSIONS: Persistent hotspots of DUD in Sweden were confirmed as well as new and emerging hotspots, especially in Stockholm, Göteborg and Malmö. Higher correlations existed in DUD rates across registers than across gender. The findings are useful for monitoring the current drug problem and for identifying drivers underlying patterns of spread and important causal pathways to DUD.
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spelling pubmed-99068282023-02-08 Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries Stewart, Kathleen Kendler, Kenneth S. Westholm, Anton Ohlsson, Henrik Sundquist, Jan Sundquist, Kristina BMC Public Health Research BACKGROUND: Drug Use Disorder (DUD) is a major contributor to world-wide morbidity and mortality. The extensive national registers in Sweden provide the basis for a study of spatial and temporal patterns of DUD onset and recurrence in Sweden from 2001–2015. METHODS: To identify patterns of DUD over space, time and gender for Swedish individuals aged 15–35, space–time clustering using SaTScan was applied. We used yearly information on residential locations in Demographic Statistical Areas (DeSO) for all of Sweden. The clustering analysis used a Poisson probability model and a null hypothesis that the expected number of cases in each DeSO was proportional to the population size of DeSOs. As SaTScan results can be unstable, steps were taken to determine stable clusters and to refine and optimize cluster size. Results for each gender-register combination were compared to the results of spatial clustering using Gi* statistics. The space–time scanning model was also run with an adjustment for neighborhood socioeconomic status to determine DUD prevalence as it relates to education, income, unemployment and receipt of social welfare. RESULTS: DUD prevalence increased over time. Males yielded more significant clusters than females for both criminal and medical registers. Female DUD prevalence rates increased over time, especially after 2012. Higher correlations in DUD rates existed across the two registers than across gender. Male clusters were present from 2004 onwards while female–criminal clusters appeared after 2007, and female–medical clusters not until 2010. By 2013, clusters existed for all gender–register combinations. Male–criminal clusters were concentrated in Stockholm, Göteborg and Malmö as were male and female-medical clusters. Neighborhood SES was more highly related to the distribution of criminal than medical DUD clusters. A persistent gap in core clusters was identified in Stockholm in an area with notably high SES. CONCLUSIONS: Persistent hotspots of DUD in Sweden were confirmed as well as new and emerging hotspots, especially in Stockholm, Göteborg and Malmö. Higher correlations existed in DUD rates across registers than across gender. The findings are useful for monitoring the current drug problem and for identifying drivers underlying patterns of spread and important causal pathways to DUD. BioMed Central 2023-02-07 /pmc/articles/PMC9906828/ /pubmed/36750781 http://dx.doi.org/10.1186/s12889-023-15149-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Stewart, Kathleen
Kendler, Kenneth S.
Westholm, Anton
Ohlsson, Henrik
Sundquist, Jan
Sundquist, Kristina
Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title_full Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title_fullStr Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title_full_unstemmed Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title_short Spatiotemporal patterns of drug use disorder in Sweden assessed using population-based registries
title_sort spatiotemporal patterns of drug use disorder in sweden assessed using population-based registries
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9906828/
https://www.ncbi.nlm.nih.gov/pubmed/36750781
http://dx.doi.org/10.1186/s12889-023-15149-1
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