Cuadros DF, Li J, Musuka G, Awad SF. Spatial epidemiology of diabetes: Methods and insights. World J Diabetes 2021; 12(7): 1042-1056 [PMID: 34326953 DOI: 10.4239/wjd.v12.i7.1042]
Corresponding Author of This Article
Diego F Cuadros, PhD, Assistant Professor, Geography and Geographic Information Systems, University of Cincinnati, 2600 Clifton Ave, Cincinnati, OH 45221, United States. diego.cuadros@uc.edu
Research Domain of This Article
Public, Environmental & Occupational Health
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Diabetes. Jul 15, 2021; 12(7): 1042-1056 Published online Jul 15, 2021. doi: 10.4239/wjd.v12.i7.1042
Spatial epidemiology of diabetes: Methods and insights
Diego F Cuadros, Jingjing Li, Godfrey Musuka, Susanne F Awad
Diego F Cuadros, Geography and Geographic Information Systems, University of Cincinnati, Cincinnati, OH 45221, United States
Jingjing Li, Urban Health Collaborative, Drexel University, Philadelphia, PA 19104, United States.
Godfrey Musuka, ICAP, Columbia University, Harare 00000, Zimbabwe
Susanne F Awad, Infectious Disease Epidemiology Group, Weill Cornell Medicine – Qatar, Cornell University, Doha 24144, Qatar
Susanne F Awad, World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine – Qatar, Cornell University, Doha 24144, Qatar
Susanne F Awad, Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10044, United States
Author contributions: Cuadros DF, Li J, Musuka G, and Awad SF designed the research study; Cuadros DF, Li J, and Awad SF performed the literature search; Cuadros DF, and Li JJ Generated the figure maps; Cuadros DF wrote the first draft of the manuscript; Li JJ, Musuka G, and Awad SF helped writing the final version of the manuscript; all authors have read and approved the final manuscript.
Conflict-of-interest statement: No conflict of interest to report.
Open-Access: 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. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Diego F Cuadros, PhD, Assistant Professor, Geography and Geographic Information Systems, University of Cincinnati, 2600 Clifton Ave, Cincinnati, OH 45221, United States. diego.cuadros@uc.edu
Received: February 10, 2021 Peer-review started: February 10, 2021 First decision: April 20, 2021 Revised: May 7, 2021 Accepted: June 4, 2021 Article in press: June 4, 2021 Published online: July 15, 2021 Processing time: 152 Days and 3.5 Hours
Core Tip
Core Tip: With more than 400 million people having diabetes mellitus (DM), this disease emerges as one of the biggest public health challenges of our current times. However, one of the most significant public health advances in the study of DM is the demonstration that it can be prevented by the implementation of effective interventions targeting the factors that exacerbate the risk of the disease. Spatially informed tailored strategies that allocate resources in the high-risk areas where the most vulnerable populations reside would be an effective approach aimed to control and reduce the burden of the disease. Spatially explicit community-level policy interventions would offer great promise in effectively addressing the obesogenic and diabetogenic environment aimed to control the global DM epidemic.
