IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12276-d685607.html
   My bibliography  Save this article

Trends and Inequalities in the Incidence of Acute Myocardial Infarction among Beijing Townships, 2007–2018

Author

Listed:
  • Jie Chang

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Qiuju Deng

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Moning Guo

    (Beijing Municipal Health Commission Information Center, Beijing 100034, China)

  • Majid Ezzati

    (Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
    MRC Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
    Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London W2 1PG, UK
    Regional Institute for Population Studies, University of Ghana, Accra P.O. Box LG 96, Ghana)

  • Jill Baumgartner

    (Institute for Health and Social Policy & Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1G1, Canada)

  • Honor Bixby

    (Institute for Health and Social Policy & Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1G1, Canada)

  • Queenie Chan

    (Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
    MRC Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK)

  • Dong Zhao

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Feng Lu

    (Beijing Municipal Health Commission Information Center, Beijing 100034, China)

  • Piaopiao Hu

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Yuwei Su

    (School of Urban Design, Wuhan University, Wuhan 430072, China
    School of Architecture, Tsinghua University, Beijing 100084, China)

  • Jiayi Sun

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Ying Long

    (Key Laboratory of Eco Planning & Green Building, Ministry of Education, Beijing 100084, China
    School of Architecture and Hang Lung Center for Real Estate, Tsinghua University, Beijing 100084, China)

  • Jing Liu

    (Department of Epidemiology, Beijing An Zhen Hospital, Capital Medical University, Beijing 100029, China
    Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
    National Clinical Research Center of Cardiovascular Diseases, Beijing 100029, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

Abstract

Acute myocardial infarction (AMI) poses a serious disease burden in China, but studies on small-area characteristics of AMI incidence are lacking. We therefore examined temporal trends and geographic variations in AMI incidence at the township level in Beijing. In this cross-sectional analysis, 259,830 AMI events during 2007–2018 from the Beijing Cardiovascular Disease Surveillance System were included. We estimated AMI incidence for 307 consistent townships during consecutive 3-year periods with a Bayesian spatial model. From 2007 to 2018, the median AMI incidence in townships increased from 216.3 to 231.6 per 100,000, with a greater relative increase in young and middle-aged males (35–49 years: 54.2%; 50–64 years: 33.2%). The most pronounced increases in the relative inequalities was observed among young residents (2.1 to 2.8 for males and 2.8 to 3.4 for females). Townships with high rates and larger relative increases were primarily located in Beijing’s northeastern and southwestern peri-urban areas. However, large increases among young and middle-aged males were observed throughout peri-urban areas. AMI incidence and their changes over time varied substantially at the township level in Beijing, especially among young adults. Targeted mitigation strategies are required for high-risk populations and areas to reduce health disparities across Beijing.

Suggested Citation

  • Jie Chang & Qiuju Deng & Moning Guo & Majid Ezzati & Jill Baumgartner & Honor Bixby & Queenie Chan & Dong Zhao & Feng Lu & Piaopiao Hu & Yuwei Su & Jiayi Sun & Ying Long & Jing Liu, 2021. "Trends and Inequalities in the Incidence of Acute Myocardial Infarction among Beijing Townships, 2007–2018," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12276-:d:685607
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12276/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/23/12276/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    Full references (including those not matched with items on IDEAS)

    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. Katie Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
    2. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    3. Shreosi Sanyal & Thierry Rochereau & Cara Nichole Maesano & Laure Com-Ruelle & Isabella Annesi-Maesano, 2018. "Long-Term Effect of Outdoor Air Pollution on Mortality and Morbidity: A 12-Year Follow-Up Study for Metropolitan France," IJERPH, MDPI, vol. 15(11), pages 1-8, November.
    4. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    5. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    6. Vanessa Santos-Sánchez & Juan Antonio Córdoba-Doña & Javier García-Pérez & Antonio Escolar-Pujolar & Lucia Pozzi & Rebeca Ramis, 2020. "Cancer Mortality and Deprivation in the Proximity of Polluting Industrial Facilities in an Industrial Region of Spain," IJERPH, MDPI, vol. 17(6), pages 1-15, March.
    7. Berti, Patrizia & Dreassi, Emanuela & Rigo, Pietro, 2014. "Compatibility results for conditional distributions," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 190-203.
    8. Louise Choo & Stephen G. Walker, 2008. "A new approach to investigating spatial variations of disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 395-405, April.
    9. Young‐Geun Choi & Lawrence P. Hanrahan & Derek Norton & Ying‐Qi Zhao, 2022. "Simultaneous spatial smoothing and outlier detection using penalized regression, with application to childhood obesity surveillance from electronic health records," Biometrics, The International Biometric Society, vol. 78(1), pages 324-336, March.
    10. Zhengyi Zhou & David S. Matteson & Dawn B. Woodard & Shane G. Henderson & Athanasios C. Micheas, 2015. "A Spatio-Temporal Point Process Model for Ambulance Demand," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 6-15, March.
    11. Eric C. Tassone & Marie Lynn Miranda & Alan E. Gelfand, 2010. "Disaggregated spatial modelling for areal unit categorical data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 175-190, January.
    12. Junming Li & Xiulan Han & Xiao Li & Jianping Yang & Xuejiao Li, 2018. "Spatiotemporal Patterns of Ground Monitored PM 2.5 Concentrations in China in Recent Years," IJERPH, MDPI, vol. 15(1), pages 1-15, January.
    13. Sanjay Chaudhuri & Debashis Mondal & Teng Yin, 2017. "Hamiltonian Monte Carlo sampling in Bayesian empirical likelihood computation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 293-320, January.
    14. Dolores Catelan & Annibale Biggeri & Corrado Lagazio, 2009. "On the clustering term in ecological analysis: how do different prior specifications affect results?," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 49-61, March.
    15. Massimo Bilancia & Giacomo Demarinis, 2014. "Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 71-94, March.
    16. Douglas R. M. Azevedo & Marcos O. Prates & Dipankar Bandyopadhyay, 2021. "MSPOCK: Alleviating Spatial Confounding in Multivariate Disease Mapping Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 464-491, September.
    17. Edgar Santos‐Fernandez & Erin E. Peterson & Julie Vercelloni & Em Rushworth & Kerrie Mengersen, 2021. "Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 147-173, January.
    18. Ying C. MacNab, 2018. "Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 497-541, September.
    19. Jonathan Wakefield & Taylor Okonek & Jon Pedersen, 2020. "Small Area Estimation for Disease Prevalence Mapping," International Statistical Review, International Statistical Institute, vol. 88(2), pages 398-418, August.
    20. Julien Riou & Anthony Hauser & Anna Fesser & Christian L. Althaus & Matthias Egger & Garyfallos Konstantinoudis, 2023. "Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland," Nature Communications, Nature, vol. 14(1), pages 1-9, 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:18:y:2021:i:23:p:12276-:d:685607. 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.