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Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden

OBJECTIVE: Investigating demographic and socioeconomic factors as intersecting rather than as separate dimensions may improve our understanding of the heterogeneous distribution of type 2 diabetes in the population. However, this complexity has scarcely been investigated and we still do not know the...

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Autores principales: Wemrell, Maria, Bennet, Louise, Merlo, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861116/
https://www.ncbi.nlm.nih.gov/pubmed/31798898
http://dx.doi.org/10.1136/bmjdrc-2019-000749
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author Wemrell, Maria
Bennet, Louise
Merlo, Juan
author_facet Wemrell, Maria
Bennet, Louise
Merlo, Juan
author_sort Wemrell, Maria
collection PubMed
description OBJECTIVE: Investigating demographic and socioeconomic factors as intersecting rather than as separate dimensions may improve our understanding of the heterogeneous distribution of type 2 diabetes in the population. However, this complexity has scarcely been investigated and we still do not know the accuracy of these factors for predicting type 2 diabetes. Improved understanding of the demographic and socioeconomic disparities predicting type 2 diabetes risk in the population would contribute to more precise and effective public health interventions. RESEARCH DESIGN AND METHODS: We analyzed the risk of type 2 diabetes among 4 334 030 individuals aged 40–84 years who by 2010 had resided in Sweden for at least 5 years. We stratified the study population into 120 strata defined by categories of age, gender, income, education, and immigration status. We calculated measures of absolute risk (prevalence) and relative risk (prevalence ratio), and quantified the discriminatory accuracy of the information for predicting type 2 diabetes in the population. RESULTS: The distribution of type 2 diabetes risk in the population was highly heterogeneous. For instance, immigrated men aged 70–79 years with low educational achievement and low income had a risk around 32 times higher than native women aged 40–49 years with high income and high educational achievement (ie, 17.6% vs 0.5%). The discriminatory accuracy of the information was acceptable. CONCLUSION: A more detailed, intersectional mapping of socioeconomic and demographic distribution of type 2 diabetes can assist in public health management aiming to reduce the prevalence of the disease.
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spelling pubmed-68611162019-12-03 Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden Wemrell, Maria Bennet, Louise Merlo, Juan BMJ Open Diabetes Res Care Epidemiology/Health Services Research OBJECTIVE: Investigating demographic and socioeconomic factors as intersecting rather than as separate dimensions may improve our understanding of the heterogeneous distribution of type 2 diabetes in the population. However, this complexity has scarcely been investigated and we still do not know the accuracy of these factors for predicting type 2 diabetes. Improved understanding of the demographic and socioeconomic disparities predicting type 2 diabetes risk in the population would contribute to more precise and effective public health interventions. RESEARCH DESIGN AND METHODS: We analyzed the risk of type 2 diabetes among 4 334 030 individuals aged 40–84 years who by 2010 had resided in Sweden for at least 5 years. We stratified the study population into 120 strata defined by categories of age, gender, income, education, and immigration status. We calculated measures of absolute risk (prevalence) and relative risk (prevalence ratio), and quantified the discriminatory accuracy of the information for predicting type 2 diabetes in the population. RESULTS: The distribution of type 2 diabetes risk in the population was highly heterogeneous. For instance, immigrated men aged 70–79 years with low educational achievement and low income had a risk around 32 times higher than native women aged 40–49 years with high income and high educational achievement (ie, 17.6% vs 0.5%). The discriminatory accuracy of the information was acceptable. CONCLUSION: A more detailed, intersectional mapping of socioeconomic and demographic distribution of type 2 diabetes can assist in public health management aiming to reduce the prevalence of the disease. BMJ Publishing Group 2019-11-07 /pmc/articles/PMC6861116/ /pubmed/31798898 http://dx.doi.org/10.1136/bmjdrc-2019-000749 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Epidemiology/Health Services Research
Wemrell, Maria
Bennet, Louise
Merlo, Juan
Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title_full Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title_fullStr Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title_full_unstemmed Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title_short Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden
title_sort understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in sweden
topic Epidemiology/Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861116/
https://www.ncbi.nlm.nih.gov/pubmed/31798898
http://dx.doi.org/10.1136/bmjdrc-2019-000749
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