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Educational attainment and cardiovascular disease in the United States: A quasi-experimental instrumental variables analysis

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  • Rita Hamad
  • Thu T Nguyen
  • Jay Bhattacharya
  • M Maria Glymour
  • David H Rehkopf

Abstract

Background: There is ongoing debate about whether education or socioeconomic status (SES) should be inputs into cardiovascular disease (CVD) prediction algorithms and clinical risk adjustment models. It is also unclear whether intervening on education will affect CVD, in part because there is controversy regarding whether education is a determinant of CVD or merely correlated due to confounding or reverse causation. We took advantage of a natural experiment to estimate the population-level effects of educational attainment on CVD and related risk factors. Methods and findings: We took advantage of variation in United States state-level compulsory schooling laws (CSLs), a natural experiment that was associated with geographic and temporal differences in the minimum number of years that children were required to attend school. We linked census data on educational attainment (N = approximately 5.4 million) during childhood with outcomes in adulthood, using cohort data from the 1992–2012 waves of the Health and Retirement Study (HRS; N = 30,853) and serial cross-sectional data from 1971–2012 waves of the National Health and Nutrition Examination Survey (NHANES; N = 44,732). We examined self-reported CVD outcomes and related risk factors, as well as relevant serum biomarkers. Using instrumental variables (IV) analysis, we found that increased educational attainment was associated with reduced smoking (HRS β −0.036, 95%CI: −0.06, −0.02, p

Suggested Citation

  • Rita Hamad & Thu T Nguyen & Jay Bhattacharya & M Maria Glymour & David H Rehkopf, 2019. "Educational attainment and cardiovascular disease in the United States: A quasi-experimental instrumental variables analysis," PLOS Medicine, Public Library of Science, vol. 16(6), pages 1-19, June.
  • Handle: RePEc:plo:pmed00:1002834
    DOI: 10.1371/journal.pmed.1002834
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    Cited by:

    1. Artur Nagapetyan & Alexander Drozd & Dmitry Subbotovsky, 2023. "How to Determine the Optimal Number of Cardiologists in a Region?," Mathematics, MDPI, vol. 11(21), pages 1-23, October.
    2. Park, Hansol & Kim, Taehoon & Kim, Jinho, 2023. "Longitudinal pathways from adolescent depressive symptoms to cardiovascular disease risk in adulthood," Social Science & Medicine, Elsevier, vol. 318(C).

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