Usama Bilal1,2, Amy H Auchincloss3,4, Ana V Diez-Roux3,4. 1. Urban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, 7th floor, Philadelphia, PA, 19104, USA. ubilal@drexel.edu. 2. Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA. ubilal@drexel.edu. 3. Urban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, 7th floor, Philadelphia, PA, 19104, USA. 4. Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA.
Abstract
PURPOSE OF REVIEW: The objective of this review is to highlight the evidence on the association between contextual characteristics of residential environments and type 2 diabetes, to provide an overview of the methodological challenges and to outline potential topics for future research in this field. RECENT FINDINGS: The link between neighborhood socioeconomic status or deprivation and diabetes prevalence, incidence, and control is robust and has been replicated in numerous settings, including in experimental and quasi-experimental studies. The association between characteristics of the built environment that affect physical activity, other aspects of the built environment, and diabetes risk is robust. There is also evidence for an association between food environments and diabetes risk, but some conflicting results have emerged in this area. While the evidence base on the association of neighborhood socioeconomic status and built and physical environments and diabetes is large and robust, challenges remain related to confounding due to neighborhood selection. Moreover, we also outline five paths forward for future research on the role of neighborhood environments on diabetes.
PURPOSE OF REVIEW: The objective of this review is to highlight the evidence on the association between contextual characteristics of residential environments and type 2 diabetes, to provide an overview of the methodological challenges and to outline potential topics for future research in this field. RECENT FINDINGS: The link between neighborhood socioeconomic status or deprivation and diabetes prevalence, incidence, and control is robust and has been replicated in numerous settings, including in experimental and quasi-experimental studies. The association between characteristics of the built environment that affect physical activity, other aspects of the built environment, and diabetes risk is robust. There is also evidence for an association between food environments and diabetes risk, but some conflicting results have emerged in this area. While the evidence base on the association of neighborhood socioeconomic status and built and physical environments and diabetes is large and robust, challenges remain related to confounding due to neighborhood selection. Moreover, we also outline five paths forward for future research on the role of neighborhood environments on diabetes.
Entities:
Keywords:
Diabetes; Neighborhoods; Residential environments; Social epidemiology
Authors: Jens Ludwig; Lisa Sanbonmatsu; Lisa Gennetian; Emma Adam; Greg J Duncan; Lawrence F Katz; Ronald C Kessler; Jeffrey R Kling; Stacy Tessler Lindau; Robert C Whitaker; Thomas W McDade Journal: N Engl J Med Date: 2011-10-20 Impact factor: 91.245
Authors: Janelle Downing; Barbara Laraia; Hector Rodriguez; William H Dow; Nancy Adler; Dean Schillinger; E Margaret Warton; Andrew J Karter Journal: Am J Epidemiol Date: 2017-03-15 Impact factor: 4.897
Authors: Paul J Christine; Rebekah Young; Sara D Adar; Alain G Bertoni; Michele Heisler; Mercedes R Carnethon; Rodney A Hayward; Ana V Diez Roux Journal: Am J Prev Med Date: 2017-08 Impact factor: 5.043
Authors: G Müller; J Wellmann; S Hartwig; K H Greiser; S Moebus; K-H Jöckel; S Schipf; H Völzke; W Maier; C Meisinger; T Tamayo; W Rathmann; K Berger Journal: Diabet Med Date: 2014-12-30 Impact factor: 4.359
Authors: Manuel Franco; Usama Bilal; Pedro Orduñez; Mikhail Benet; Alain Morejón; Benjamín Caballero; Joan F Kennelly; Richard S Cooper Journal: BMJ Date: 2013-04-09
Authors: Bahman P Tabaei; Andrew G Rundle; Winfred Y Wu; Carol R Horowitz; Victoria Mayer; Daniel M Sheehan; Shadi Chamany Journal: Am J Epidemiol Date: 2018-04-01 Impact factor: 4.897
Authors: Alice M Dalton; Andrew P Jones; Stephen J Sharp; Andrew J M Cooper; Simon Griffin; Nicholas J Wareham Journal: BMC Public Health Date: 2016-11-18 Impact factor: 3.295
Authors: Joline W J Beulens; Maria G M Pinho; Taymara C Abreu; Nicole R den Braver; Thao M Lam; Anke Huss; Jelle Vlaanderen; Tabea Sonnenschein; Noreen Z Siddiqui; Zhendong Yuan; Jules Kerckhoffs; Alexandra Zhernakova; Milla F Brandao Gois; Roel C H Vermeulen Journal: Diabetologia Date: 2021-11-18 Impact factor: 10.122
Authors: Melissa N Poulsen; Brian S Schwartz; Joseph Dewalle; Cara Nordberg; Jonathan S Pollak; Jennifer Silva; Carla I Mercado; Deborah B Rolka; Karen Rae Siegel; Annemarie G Hirsch Journal: Landsc Urban Plan Date: 2021-05 Impact factor: 6.142
Authors: Carrie R Howell; Li Zhang; Nengjun Yi; Tapan Mehta; Andrea L Cherrington; W Timothy Garvey Journal: Obesity (Silver Spring) Date: 2022-05-25 Impact factor: 9.298
Authors: M Maya McDoom; Lisa A Cooper; Yea-Jen Hsu; Abhay Singh; Jamie Perin; Rachel L J Thornton Journal: J Gen Intern Med Date: 2020-02-10 Impact factor: 5.128
Authors: Deanna D Rumble; Katherine O'Neal; Demario S Overstreet; Terence M Penn; Pamela Jackson; Edwin N Aroke; Andrew M Sims; Annabel L King; Fariha N Hasan; Tammie L Quinn; D Leann Long; Robert E Sorge; Burel R Goodin Journal: J Behav Med Date: 2021-06-09