Cargando…
Spatial epidemiology of diabetes: Methods and insights
Diabetes mellitus (DM) is a growing epidemic with global proportions. It is estimated that in 2019, 463 million adults aged 20-79 years were living with DM. The latest evidence shows that DM continues to be a significant global health challenge and is likely to continue to grow substantially in the...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311478/ https://www.ncbi.nlm.nih.gov/pubmed/34326953 http://dx.doi.org/10.4239/wjd.v12.i7.1042 |
_version_ | 1783728963996090368 |
---|---|
author | Cuadros, Diego F Li, Jingjing Musuka, Godfrey Awad, Susanne F |
author_facet | Cuadros, Diego F Li, Jingjing Musuka, Godfrey Awad, Susanne F |
author_sort | Cuadros, Diego F |
collection | PubMed |
description | Diabetes mellitus (DM) is a growing epidemic with global proportions. It is estimated that in 2019, 463 million adults aged 20-79 years were living with DM. The latest evidence shows that DM continues to be a significant global health challenge and is likely to continue to grow substantially in the next decades, which would have major implications for healthcare expenditures, particularly in developing countries. Hence, new conceptual and methodological approaches to tackle the epidemic are long overdue. Spatial epidemiology has been a successful approach to control infectious disease epidemics like malaria and human immunodeficiency virus. The implementation of this approach has been expanded to include the study of non-communicable diseases like cancer and cardiovascular diseases. In this review, we discussed the implementation and use of spatial epidemiology and Geographic Information Systems to the study of DM. We reviewed several spatial methods used to understand the spatial structure of the disease and identify the potential geographical drivers of the spatial distribution of DM. Finally, we discussed the use of spatial epidemiology on the design and implementation of geographically targeted prevention and treatment interventions against DM. |
format | Online Article Text |
id | pubmed-8311478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-83114782021-07-28 Spatial epidemiology of diabetes: Methods and insights Cuadros, Diego F Li, Jingjing Musuka, Godfrey Awad, Susanne F World J Diabetes Review Diabetes mellitus (DM) is a growing epidemic with global proportions. It is estimated that in 2019, 463 million adults aged 20-79 years were living with DM. The latest evidence shows that DM continues to be a significant global health challenge and is likely to continue to grow substantially in the next decades, which would have major implications for healthcare expenditures, particularly in developing countries. Hence, new conceptual and methodological approaches to tackle the epidemic are long overdue. Spatial epidemiology has been a successful approach to control infectious disease epidemics like malaria and human immunodeficiency virus. The implementation of this approach has been expanded to include the study of non-communicable diseases like cancer and cardiovascular diseases. In this review, we discussed the implementation and use of spatial epidemiology and Geographic Information Systems to the study of DM. We reviewed several spatial methods used to understand the spatial structure of the disease and identify the potential geographical drivers of the spatial distribution of DM. Finally, we discussed the use of spatial epidemiology on the design and implementation of geographically targeted prevention and treatment interventions against DM. Baishideng Publishing Group Inc 2021-07-15 2021-07-15 /pmc/articles/PMC8311478/ /pubmed/34326953 http://dx.doi.org/10.4239/wjd.v12.i7.1042 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Review Cuadros, Diego F Li, Jingjing Musuka, Godfrey Awad, Susanne F Spatial epidemiology of diabetes: Methods and insights |
title | Spatial epidemiology of diabetes: Methods and insights |
title_full | Spatial epidemiology of diabetes: Methods and insights |
title_fullStr | Spatial epidemiology of diabetes: Methods and insights |
title_full_unstemmed | Spatial epidemiology of diabetes: Methods and insights |
title_short | Spatial epidemiology of diabetes: Methods and insights |
title_sort | spatial epidemiology of diabetes: methods and insights |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311478/ https://www.ncbi.nlm.nih.gov/pubmed/34326953 http://dx.doi.org/10.4239/wjd.v12.i7.1042 |
work_keys_str_mv | AT cuadrosdiegof spatialepidemiologyofdiabetesmethodsandinsights AT lijingjing spatialepidemiologyofdiabetesmethodsandinsights AT musukagodfrey spatialepidemiologyofdiabetesmethodsandinsights AT awadsusannef spatialepidemiologyofdiabetesmethodsandinsights |