IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0122963.html
   My bibliography  Save this article

Association between an Internet-Based Measure of Area Racism and Black Mortality

Author

Listed:
  • David H Chae
  • Sean Clouston
  • Mark L Hatzenbuehler
  • Michael R Kramer
  • Hannah L F Cooper
  • Sacoby M Wilson
  • Seth I Stephens-Davidowitz
  • Robert S Gold
  • Bruce G Link

Abstract

Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the “N-word” in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004–2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health.

Suggested Citation

  • David H Chae & Sean Clouston & Mark L Hatzenbuehler & Michael R Kramer & Hannah L F Cooper & Sacoby M Wilson & Seth I Stephens-Davidowitz & Robert S Gold & Bruce G Link, 2015. "Association between an Internet-Based Measure of Area Racism and Black Mortality," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-12, April.
    • Handle: RePEc:plo:pone00:0122963
    DOI: 10.1371/journal.pone.0122963
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0122963
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0122963&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0122963?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
    ---><---

    References listed on IDEAS

    as
    1. James Kau & Donald Keenan & Henry Munneke, 2012. "Racial Discrimination and Mortgage Lending," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 289-304, August.
    2. Stephens-Davidowitz, Seth, 2014. "The cost of racial animus on a black candidate: Evidence using Google search data," Journal of Public Economics, Elsevier, vol. 118(C), pages 26-40.
    3. Geronimus, A.T. & Hicken, M. & Keene, D. & Bound, J., 2006. ""Weathering" and age patterns of allostatic load scores among blacks and whites in the United States," American Journal of Public Health, American Public Health Association, vol. 96(5), pages 826-833.
    4. Christopher P. Scheitle, 2011. "Google's Insights for Search: A Note Evaluating the Use of Search Engine Data in Social Research," Social Science Quarterly, Southwestern Social Science Association, vol. 92(1), pages 285-295, March.
    5. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    6. Darity Jr., W.A., 2003. "Employment discrimination, segregation, and health," American Journal of Public Health, American Public Health Association, vol. 93(2), pages 226-231.
    7. Cunningham, Timothy J. & Seeman, Teresa E. & Kawachi, Ichiro & Gortmaker, Steven L. & Jacobs, David R. & Kiefe, Catarina I. & Berkman, Lisa F., 2012. "Racial/ethnic and gender differences in the association between self-reported experiences of racial/ethnic discrimination and inflammation in the CARDIA cohort of 4 US communities," Social Science & Medicine, Elsevier, vol. 75(5), pages 922-931.
    8. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    9. Dinwiddie, Gniesha Y. & Gaskin, Darrell J. & Chan, Kitty S. & Norrington, Janette & McCleary, Rachel, 2013. "Residential segregation, geographic proximity and type of services used: Evidence for racial/ethnic disparities in mental health," Social Science & Medicine, Elsevier, vol. 80(C), pages 67-75.
    10. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    11. Nancy Krieger & Pamela D Waterman & Anna Kosheleva & Jarvis T Chen & Dana R Carney & Kevin W Smith & Gary G Bennett & David R Williams & Elmer Freeman & Beverley Russell & Gisele Thornhill & Kristin M, 2011. "Exposing Racial Discrimination: Implicit & Explicit Measures–The My Body, My Story Study of 1005 US-Born Black & White Community Health Center Members," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-24, November.
    12. Chae, David H. & Lincoln, Karen D. & Adler, Nancy E. & Syme, S. Leonard, 2010. "Do experiences of racial discrimination predict cardiovascular disease among African American men? The moderating role of internalized negative racial group attitudes," Social Science & Medicine, Elsevier, vol. 71(6), pages 1182-1188, September.
    13. Rick L. Williams, 2000. "A Note on Robust Variance Estimation for Cluster-Correlated Data," Biometrics, The International Biometric Society, vol. 56(2), pages 645-646, June.
    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. Mauro Caselli & Paolo Falco & Babak Somekh, 2024. "Inside the NBA Bubble: how Black players performed better without fans," Journal of Population Economics, Springer;European Society for Population Economics, vol. 37(2), pages 1-20, June.
    2. Duncan, Dustin T. & Cook, Stephanie H. & Wood, Erica P. & Regan, Seann D. & Chaix, Basile & Tian, Yijun & Chunara, Rumi, 2023. "Structural racism and homophobia evaluated through social media sentiment combined with activity spaces and associations with mental health among young sexual minority men," Social Science & Medicine, Elsevier, vol. 320(C).
    3. Isoya, Hidehito & Yamada, Hiroyuki, 2021. "Hidden internet-based measure of discrimination and mental health of Black people," Social Science & Medicine, Elsevier, vol. 273(C).
    4. Ahmadi, Iman & Habel, Johannes & Jia, Miaolei & Wei, Sarah, 2022. "Consumer stockpiling under the impact of a global disaster: The evolution of affective and cognitive motives," Journal of Business Research, Elsevier, vol. 142(C), pages 56-71.
    5. Splan, Eric D. & Magerman, Adam B. & Forbes, Chad E., 2021. "Associations of regional racial attitudes with chronic illness in the United States," Social Science & Medicine, Elsevier, vol. 281(C).
    6. Bertrand, Jérémie & Weill, Laurent, 2021. "Do algorithms discriminate against African Americans in lending?," Economic Modelling, Elsevier, vol. 104(C).
    7. Park, Hyun Joon & Francisco, Sara Chari & Pang, M. Rosemary & Peng, Lulu & Chi, Guangqing, 2023. "Exposure to anti-Black Lives Matter movement and obesity of the Black population," Social Science & Medicine, Elsevier, vol. 316(C).
    8. HwaJung Choi & Robert Schoeni & Hongwei Xu & Adriana Reyes & Deena Thomas, 2021. "Proximity to mother over the life course in the United States: Overall patterns and racial differences," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(23), pages 769-806.
    9. Chen, Shanting & Mallory, Allen B., 2021. "The effect of racial discrimination on mental and physical health: A propensity score weighting approach," Social Science & Medicine, Elsevier, vol. 285(C).
    10. Dhammika Dharmapala & Aziz Huq, 2024. "Imputing Unreported Hate Crimes Using Google Search Data," CESifo Working Paper Series 11245, CESifo.
    11. Ewens, Michael & Gupta, Arpit & Howell, Sabrina, 2021. "Local Journalism under Private Equity Ownership," SocArXiv 6ynf4_v1, Center for Open Science.
    12. Anderson, D. Mark & Crost, Benjamin & Rees, Daniel I., 2020. "Do economic downturns fuel racial animus?," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 9-18.
    13. Justin T. Huang & Masha Krupenkin & David Rothschild & Julia Lee Cunningham, 2023. "The cost of anti-Asian racism during the COVID-19 pandemic," Nature Human Behaviour, Nature, vol. 7(5), pages 682-695, May.
    14. Clouston, Sean A.P. & Rubin, Marcie S. & Chae, David H. & Freese, Jeremy & Nemesure, Barbara & Link, Bruce G., 2017. "Fundamental causes of accelerated declines in colorectal cancer mortality: Modeling multiple ways that disadvantage influences mortality risk," Social Science & Medicine, Elsevier, vol. 187(C), pages 1-10.

    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. Chae, David H. & Clouston, Sean & Martz, Connor D. & Hatzenbuehler, Mark L. & Cooper, Hannah L.F. & Turpin, Rodman & Stephens-Davidowitz, Seth & Kramer, Michael R., 2018. "Area racism and birth outcomes among Blacks in the United States," Social Science & Medicine, Elsevier, vol. 199(C), pages 49-55.
    2. Kristina Gligorić & Arnaud Chiolero & Emre Kıcıman & Ryen W. White & Robert West, 2022. "Population-scale dietary interests during the COVID-19 pandemic," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Abay,Kibrom A. & Hirfrfot,Kibrom Tafere & Woldemichael,Andinet, 2020. "Winners and Losers from COVID-19 : Global Evidence from Google Search," Policy Research Working Paper Series 9268, The World Bank.
    4. Junzhao Ma & Dewi Tojib & Yelena Tsarenko, 2022. "Sex Robots: Are We Ready for Them? An Exploration of the Psychological Mechanisms Underlying People’s Receptiveness of Sex Robots," Journal of Business Ethics, Springer, vol. 178(4), pages 1091-1107, July.
    5. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    6. Stephens-Davidowitz, Seth, 2014. "The cost of racial animus on a black candidate: Evidence using Google search data," Journal of Public Economics, Elsevier, vol. 118(C), pages 26-40.
    7. Colen, Cynthia G. & Ramey, David M. & Cooksey, Elizabeth C. & Williams, David R., 2018. "Racial disparities in health among nonpoor African Americans and Hispanics: The role of acute and chronic discrimination," Social Science & Medicine, Elsevier, vol. 199(C), pages 167-180.
    8. Siddiqi, Arjumand & Jones, Marcella K. & Bruce, Donald J. & Erwin, Paul C., 2016. "Do racial inequities in infant mortality correspond to variations in societal conditions? A study of state-level income inequality in the U.S., 1992–2007," Social Science & Medicine, Elsevier, vol. 164(C), pages 49-58.
    9. Ma, Junzhao & Seenivasan, Satheesh & Yan, Bingyu, 2020. "Media influences on consumption trends: Effects of the film Food, Inc. on organic food sales in the U.S," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 320-335.
    10. Sansone, Dario, 2019. "Pink work: Same-sex marriage, employment and discrimination," Journal of Public Economics, Elsevier, vol. 180(C).
    11. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
    12. Jesse T. Richman & Ryan J. Roberts, 2023. "Assessing Spurious Correlations in Big Search Data," Forecasting, MDPI, vol. 5(1), pages 1-12, February.
    13. Grechyna, Daryna, 2025. "Raising awareness of climate change: Nature, activists, politicians?," Ecological Economics, Elsevier, vol. 227(C).
    14. Yangkun Huang & Xiaoping Xu & Sini Su, 2021. "Diverging from News Media: An Exploratory Study on the Changing Dynamics between Media and Public Attention on Cancer in China from 2011–2020," IJERPH, MDPI, vol. 18(16), pages 1-13, August.
    15. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    16. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    17. Breithaupt, Patrick & Kesler, Reinhold & Niebel, Thomas & Rammer, Christian, 2020. "Intangible capital indicators based on web scraping of social media," ZEW Discussion Papers 20-046, ZEW - Leibniz Centre for European Economic Research.
    18. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022. "Does online salience predict charitable giving? Evidence from SMS text donations," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 134-149.
    19. Yann Algan & Fabrice Murtin & Elizabeth Beasley & Kazuhito Higa & Claudia Senik, 2019. "Well-being through the lens of the internet," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-23, January.
    20. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0122963. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.