IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v14y2016i1p3-d85946.html
   My bibliography  Save this article

Residential Proximity to Major Roadways and Risk of Type 2 Diabetes Mellitus: A Meta-Analysis

Author

Listed:
  • Zhiqing Zhao

    (Emergency Department, Maternal and Children Health’s Hospital of Tangshan, Tangshan 063000, China
    Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao 266003, China
    These authors contributed equally to this work.)

  • Faying Lin

    (Department of Medical Services, The Eighth Hospital of PLA, Shigatse 857000, China
    These authors contributed equally to this work.)

  • Bennett Wang

    (Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao 266003, China)

  • Yihai Cao

    (Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm 17177, Sweden)

  • Xu Hou

    (Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao 266003, China)

  • Yangang Wang

    (Department of Endocrinology, Affiliated Hospital of Qingdao University, Qingdao 266003, China)

Abstract

Research indicates that higher levels of traffic-related pollution exposure increase the risk of diabetes, but the association between road proximity and diabetes risk remains unclear. To assess and quantify the association between residential proximity to major roadways and type 2 diabetes, a systematic review and meta-analysis was performed. Embase, Medline, and Web of Science were searched for eligible studies. Using a random-effects meta-analysis, the summary relative risks (RRs) were calculated. Bayesian meta-analysis was also performed. Eight studies (6 cohort and 2 cross-sectional) with 158,576 participants were finally included. The summary unadjusted RR for type 2 diabetes associated with residential proximity to major roadways was 1.24 (95% confidence interval [CI]: 1.07–1.44, p = 0.001, I 2 = 48.1%). The summary adjusted RR of type 2 diabetes associated with residential proximity to major roadways was 1.12 (95% CI: 1.03–1.22, p = 0.01, I 2 = 17.9%). After excluding two cross-sectional studies, the summary results suggested that residential proximity to major roadways could increase type 2 diabetes risk (Adjusted RR = 1.13; 95% CI: 1.02–1.27, p = 0.025, I 2 = 36.6%). Bayesian meta-analysis showed that the unadjusted RR and adjusted RR of type 2 diabetes associated with residential proximity to major roadways were 1.22 (95% credibility interval: 1.06–1.55) and 1.13 (95% credibility interval: 1.01–1.31), respectively. The meta-analysis suggested that residential proximity to major roadways could significantly increase risk of type 2 diabetes, and it is an independent risk factor of type 2 diabetes. More well-designed studies are needed to further strengthen the evidence.

Suggested Citation

  • Zhiqing Zhao & Faying Lin & Bennett Wang & Yihai Cao & Xu Hou & Yangang Wang, 2016. "Residential Proximity to Major Roadways and Risk of Type 2 Diabetes Mellitus: A Meta-Analysis," IJERPH, MDPI, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:gam:jijerp:v:14:y:2016:i:1:p:3-:d:85946
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/14/1/3/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/14/1/3/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lindsay J. Underhill & Sonali Bose & D’Ann L. Williams & Karina M. Romero & Gary Malpartida & Patrick N. Breysse & Elizabeth M. Klasen & Juan M. Combe & William Checkley & Nadia N. Hansel, 2015. "Association of Roadway Proximity with Indoor Air Pollution in a Peri-Urban Community in Lima, Peru," IJERPH, MDPI, vol. 12(10), pages 1-16, October.
    2. Stuart Batterman & Rajiv Ganguly & Paul Harbin, 2015. "High Resolution Spatial and Temporal Mapping of Traffic-Related Air Pollutants," IJERPH, MDPI, vol. 12(4), pages 1-21, April.
    3. Julian P. T. Higgins & Simon G. Thompson & David J. Spiegelhalter, 2009. "A re‐evaluation of random‐effects meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 137-159, January.
    4. Anne M. Weaver & Gregory A. Wellenius & Wen-Chih Wu & DeMarc A. Hickson & Masoor Kamalesh & Yi Wang, 2016. "Residential Proximity to Major Roadways Is Not Associated with Cardiac Function in African Americans: Results from the Jackson Heart Study," IJERPH, MDPI, vol. 13(6), pages 1-12, June.
    5. A. E. Ades & G. Lu & J. P. T. Higgins, 2005. "The Interpretation of Random-Effects Meta-Analysis in Decision Models," Medical Decision Making, , vol. 25(6), pages 646-654, November.
    6. Ettore Bidoli & Marilena Pappagallo & Silvia Birri & Luisa Frova & Loris Zanier & Diego Serraino, 2016. "Residential Proximity to Major Roadways and Lung Cancer Mortality. Italy, 1990–2010: An Observational Study," IJERPH, MDPI, vol. 13(2), pages 1-9, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tashi Dendup & Xiaoqi Feng & Stephanie Clingan & Thomas Astell-Burt, 2018. "Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review," IJERPH, MDPI, vol. 15(1), pages 1-25, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bodnar, Olha & Eriksson, Viktor, 2021. "Bayesian model selection: Application to adjustment of fundamental physical constants," Working Papers 2021:7, Örebro University, School of Business.
    2. Yeojin Chung & Sophia Rabe-Hesketh & Vincent Dorie & Andrew Gelman & Jingchen Liu, 2013. "A Nondegenerate Penalized Likelihood Estimator for Variance Parameters in Multilevel Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 685-709, October.
    3. Sofia Dias & Alex J. Sutton & Nicky J. Welton & A. E. Ades, 2013. "Evidence Synthesis for Decision Making 3," Medical Decision Making, , vol. 33(5), pages 618-640, July.
    4. Amanda Kvarven & Eirik Strømland & Conny Wollbrant & David Andersson & Magnus Johannesson & Gustav Tinghög & Daniel Västfjäll & Kristian Ove R. Myrseth, 2020. "The intuitive cooperation hypothesis revisited: a meta-analytic examination of effect size and between-study heterogeneity," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 6(1), pages 26-42, June.
    5. Xiaowei Gong & Boyun Yuan & Yadong Yuan, 2022. "Incidence and prognostic value of pulmonary embolism in COVID-19: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-16, March.
    6. Nelson, Jon Paul, 2020. "Fixed-effect versus random-effects meta-analysis in economics: A study of pass-through rates for alcohol beverage excise taxes," Economics Discussion Papers 2020-1, Kiel Institute for the World Economy (IfW Kiel).
    7. Ibrahim Y. Tawbe, 2023. "Environmental disclosure programs and birth weight: a meta- analysis," Working Papers 2023-02, CRESE.
    8. Fanjie Meng & Xiangpo Pan & Wenzhen Tong, 2018. "Rifampicin versus streptomycin for brucellosis treatment in humans: A meta-analysis of randomized controlled trials," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-12, February.
    9. Biao Zhou & Gao Feng Feng Cai & Hua Kun Kun Lv & Shuang Fei Fei Xu & Zheng Ting Ting Wang & Zheng Gang Gang Jiang & Chong Gao Gao Hu & Yong Di Di Chen, 2019. "Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users—Findings from a Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 16(13), pages 1-17, July.
    10. Alberto Aiolfi & Emanuele Asti & Emanuele Rausa & Giulia Bonavina & Gianluca Bonitta & Luigi Bonavina, 2018. "Use of C-reactive protein for the early prediction of anastomotic leak after esophagectomy: Systematic review and Bayesian meta-analysis," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-13, December.
    11. Shijie Ren & Jeremy E. Oakley & John W. Stevens, 2018. "Incorporating Genuine Prior Information about Between-Study Heterogeneity in Random Effects Pairwise and Network Meta-analyses," Medical Decision Making, , vol. 38(4), pages 531-542, May.
    12. Dusan Jandacka & Daniela Durcanska, 2021. "Seasonal Variation, Chemical Composition, and PMF-Derived Sources Identification of Traffic-Related PM 1 , PM 2.5 , and PM 2.5–10 in the Air Quality Management Region of Žilina, Slovakia," IJERPH, MDPI, vol. 18(19), pages 1-23, September.
    13. Ajaree Rayanakorn & Hooi-Leng Ser & Priyia Pusparajah & Kok-Gan Chan & Bey Hing Goh & Tahir Mehmood Khan & Surasak Saokaew & Shaun Wen Huey Lee & Learn-Han Lee, 2020. "Comparative efficacy of antibiotic(s) alone or in combination of corticosteroids in adults with acute bacterial meningitis: A systematic review and network meta-analysis," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-17, May.
    14. Tomáš Havránek, 2009. "Rose Effect and the Euro: The Magic is Gone," Working Papers IES 2009/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2009.
    15. Ratko Peric & Zoran Nikolovski & Marco Meucci & Philippe Tadger & Carlo Ferri Marini & Francisco José Amaro-Gahete, 2022. "A Systematic Review and Meta-Analysis on the Association and Differences between Aerobic Threshold and Point of Optimal Fat Oxidation," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    16. Nelson Gouveia, 2016. "Addressing Environmental Health Inequalities," IJERPH, MDPI, vol. 13(9), pages 1-3, August.
    17. Cebiroglu, Gökhan & Hautsch, Nikolaus & Walsh, Christopher, 2019. "Revisiting the stealth trading hypothesis: Does time-varying liquidity explain the size-effect?," CFS Working Paper Series 625, Center for Financial Studies (CFS).
    18. Bijing Mao & Yafei Li & Zhimin Zhang & Chuan Chen & Yuanyuan Chen & Chenchen Ding & Lin Lei & Jian Li & Mei Jiang & Dong Wang & Ge Wang, 2015. "One-Carbon Metabolic Factors and Risk of Renal Cell Cancer: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-10, October.
    19. Richard A Hubner & Richard D Riley & Lucinda J Billingham & Sanjay Popat, 2011. "Excision Repair Cross-Complementation Group 1 (ERCC1) Status and Lung Cancer Outcomes: A Meta-Analysis of Published Studies and Recommendations," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-10, October.
    20. Shefali Liyanage & Kiran Saqib & Amber Fozia Khan & Tijhiana Rose Thobani & Wang-Choi Tang & Cameron B. Chiarot & Bara’ Abdallah AlShurman & Zahid Ahmad Butt, 2021. "Prevalence of Anxiety in University Students during the COVID-19 Pandemic: A Systematic Review," IJERPH, MDPI, vol. 19(1), pages 1-13, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:14:y:2016:i:1:p:3-:d:85946. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.