IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v222y2019icp133-144.html
   My bibliography  Save this article

Socioeconomic determinants of pediatric asthma emergency department visits under regional economic development in western New York

Author

Listed:
  • Eum, Youngseob
  • Yoo, EunHye
  • Bowen, Elizabeth

Abstract

Although the links between asthma in children and physical environmental factors have been well established, the role of community-level socioeconomic status remains inconclusive. Consequently, little attention has been paid to the dynamic changes in the associations between socioeconomic status and asthma outcomes due to structural changes in the community, such as an influx of financial resources. This study examined the relationship between community-level socioeconomic status indicators and asthma-related emergency department utilization for school-aged children in 2011 and 2015, assessing the early impact of a large-scale regional economic development project in western New York, United States. Our analyses controlled for other community-level health risk factors, such as environmental exposure, and spatial correlation of the emergency department usage data. Results indicated that both median household income and health insurance coverage were key socioeconomic predictors of the children's asthma-related emergency department utilization over the study period. We also found that the risk of emergency department utilization for asthma decreased significantly in the area in which regional economic development projects were completed during the initial stage of the project. Through a comparison study we demonstrated that the spatial correlation present in asthma-related ED utilization improved model fit and corrected biases in the estimates. Although our findings suggest that improving the socioeconomic status of communities contributes to a reduction in emergency department utilization for pediatric asthma, more empirical studies are warranted for evaluating the comprehensive effects of regional economic development on public health.

Suggested Citation

  • Eum, Youngseob & Yoo, EunHye & Bowen, Elizabeth, 2019. "Socioeconomic determinants of pediatric asthma emergency department visits under regional economic development in western New York," Social Science & Medicine, Elsevier, vol. 222(C), pages 133-144.
    • Handle: RePEc:eee:socmed:v:222:y:2019:i:c:p:133-144
    DOI: 10.1016/j.socscimed.2019.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953619300012
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2019.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chagas, André L.S. & Azzoni, Carlos R. & Almeida, Alexandre N., 2016. "A spatial difference-in-differences analysis of the impact of sugarcane production on respiratory diseases," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 24-36.
    2. 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.
    3. Gabe, Jonathan & Bury, Michael & Ramsay, Rosemary, 2002. "Living with asthma: the experiences of young people at home and at school," Social Science & Medicine, Elsevier, vol. 55(9), pages 1619-1633, November.
    4. Dubé, Jean & Legros, Diègo & Thériault, Marius & Des Rosiers, François, 2014. "A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 24-40.
    5. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    6. Miller, Sarah, 2012. "The effect of insurance on emergency room visits: An analysis of the 2006 Massachusetts health reform," Journal of Public Economics, Elsevier, vol. 96(11), pages 893-908.
    7. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).
    8. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    9. Crouse, Dan L. & Ross, Nancy A. & Goldberg, Mark S., 2009. "Double burden of deprivation and high concentrations of ambient air pollution at the neighbourhood scale in Montreal, Canada," Social Science & Medicine, Elsevier, vol. 69(6), pages 971-981, September.
    10. Bowen, Elizabeth A. & Miller, Berg & Barman-Adhikari, Anamika & Fallin, Kyla & Zuchlewski, Dale, 2017. "Emerging adult homelessness in geographic perspective: A view from the Rust Belt," Children and Youth Services Review, Elsevier, vol. 73(C), pages 213-219.
    11. Veronica J. Berrocal & Alan E. Gelfand & David M. Holland, 2012. "Space-Time Data fusion Under Error in Computer Model Output: An Application to Modeling Air Quality," Biometrics, The International Biometric Society, vol. 68(3), pages 837-848, September.
    12. Bhan, N. & Kawachi, I. & Glymour, M.M. & Subramanian, S.V., 2015. "Time trends in racial and ethnic disparities in asthma prevalence in the United States from the Behavioral Risk Factor Surveillance System (BRFSS) study (1999-2011)," American Journal of Public Health, American Public Health Association, vol. 105(6), pages 1269-1275.
    13. Shankardass, Ketan & McConnell, Rob S. & Milam, Joel & Berhane, Kiros & Tatalovich, Zaria & Wilson, John P. & Jerrett, Michael, 2007. "The association between contextual socioeconomic factors and prevalent asthma in a cohort of Southern California school children," Social Science & Medicine, Elsevier, vol. 65(8), pages 1792-1806, October.
    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. Chen, Yewen & Chang, Xiaohui & Luo, Fangzhi & Huang, Hui, 2023. "Additive dynamic models for correcting numerical model outputs," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    2. Bardaka, Eleni & Delgado, Michael S. & Florax, Raymond J.G.M., 2018. "Causal identification of transit-induced gentrification and spatial spillover effects: The case of the Denver light rail," Journal of Transport Geography, Elsevier, vol. 71(C), pages 15-31.
    3. Bardaka, Eleni & Delgado, Michael S. & Florax, Raymond J.G.M., 2019. "A spatial multiple treatment/multiple outcome difference-in-differences model with an application to urban rail infrastructure and gentrification," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 325-345.
    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. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    6. 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.
    7. 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.
    8. Bondo, Kristin J. & Rosenberry, Christopher S. & Stainbrook, David & Walter, W. David, 2024. "Comparing risk of chronic wasting disease occurrence using Bayesian hierarchical spatial models and different surveillance types," Ecological Modelling, Elsevier, vol. 493(C).
    9. 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.
    10. Isabel Martínez-Pérez & Verónica González-Iglesias & Valentín Rodríguez Suárez & Ana Fernández-Somoano, 2021. "Spatial Distribution of Hospitalizations for Ischemic Heart Diseases in the Central Region of Asturias, Spain," IJERPH, MDPI, vol. 18(23), pages 1-10, November.
    11. Johnson, Blair T. & Sisti, Anthony & Bernstein, Mary & Chen, Kun & Hennessy, Emily A. & Acabchuk, Rebecca L. & Matos, Michaela, 2021. "Community-level factors and incidence of gun violence in the United States, 2014–2017," Social Science & Medicine, Elsevier, vol. 280(C).
    12. Maike Tahden & Juliane Manitz & Klaus Baumgardt & Gerhard Fell & Thomas Kneib & Guido Hegasy, 2016. "Epidemiological and Ecological Characterization of the EHEC O104:H4 Outbreak in Hamburg, Germany, 2011," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-19, October.
    13. Zhang, Yaoyu & Liu, Jin & Wang, Bo, 2022. "The impact of High-Speed Rails on urban expansion: An investigation using an SDID with dynamic effects method," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    14. Radka Jersakova & James Lomax & James Hetherington & Brieuc Lehmann & George Nicholson & Mark Briers & Chris Holmes, 2022. "Bayesian imputation of COVID‐19 positive test counts for nowcasting under reporting lag," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 834-860, August.
    15. Darren J. Mayne & Geoffrey G. Morgan & Bin B. Jalaludin & Adrian E. Bauman, 2018. "Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia," IJERPH, MDPI, vol. 15(2), pages 1-24, February.
    16. Aparicio, Genoveva & Camacho, Maximo & Maté-Sánchez-Val, Mariluz, 2024. "Quantifying the impact: Are coastal areas impoverished by marine pollution?," Ecological Economics, Elsevier, vol. 221(C).
    17. Ferreira, Marco A.R. & Porter, Erica M. & Franck, Christopher T., 2021. "Fast and scalable computations for Gaussian hierarchical models with intrinsic conditional autoregressive spatial random effects," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
    18. Faustin Habyarimana & Temesgen Zewotir & Shaun Ramroop, 2017. "Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda," IJERPH, MDPI, vol. 14(6), pages 1-15, June.
    19. Medina-Olivares, Victor & Calabrese, Raffaella & Dong, Yizhe & Shi, Baofeng, 2022. "Spatial dependence in microfinance credit default," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1071-1085.
    20. Diao, Mi & Leonard, Delon & Sing, Tien Foo, 2017. "Spatial-difference-in-differences models for impact of new mass rapid transit line on private housing values," Regional Science and Urban Economics, Elsevier, vol. 67(C), pages 64-77.

    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:eee:socmed:v:222:y:2019:i:c:p:133-144. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.