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Birth weight, neonatal care, and infant mortality: Evidence from macrosomic babies

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  • Brilli, Ylenia
  • Restrepo, Brandon J.

Abstract

This study demonstrates that rule-of-thumb health treatment decision-making exists when assigning medical care to macrosomic newborns with an extremely high birth weight and estimates the short-run health return to neonatal care for infants at the high end of the birth weight distribution. Using a regression discontinuity design, we find that infants born with a birth weight above 5000 grams have a 2 percentage-point higher probability of admission to a neonatal intensive care unit and a 1 percentage-point higher probability of antibiotics receipt, compared to infants with a birth weight below 5000 grams. We also find that being born above the 5000-gram cutoff has a mortality-reducing effect: infants with a birth weight larger than 5000 grams face a 0.15 percentage-point lower risk of mortality in the first week and a 0.20 percentage-point lower risk of mortality in the first month, compared to their counterparts with a birth weight below 5000 grams. We do not find any evidence of changes in health treatments and mortality at macrosomic cutoffs lower than 5000 grams, which is consistent with the idea that such treatment decisions are guided by the higher expected morbidity and mortality risk associated with infants weighing more than 5000 grams.

Suggested Citation

  • Brilli, Ylenia & Restrepo, Brandon J., 2020. "Birth weight, neonatal care, and infant mortality: Evidence from macrosomic babies," Economics & Human Biology, Elsevier, vol. 37(C).
  • Handle: RePEc:eee:ehbiol:v:37:y:2020:i:c:s1570677x19300930
    DOI: 10.1016/j.ehb.2019.100825
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    1. Alan I. Barreca & Jason M. Lindo & Glen R. Waddell, 2016. "Heaping-Induced Bias In Regression-Discontinuity Designs," Economic Inquiry, Western Economic Association International, vol. 54(1), pages 268-293, January.
    2. Jürges, Hendrik & Köberlein, Juliane, 2015. "What explains DRG upcoding in neonatology? The roles of financial incentives and infant health," Journal of Health Economics, Elsevier, vol. 43(C), pages 13-26.
    3. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    4. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    5. Douglas Almond & Joseph J. Doyle & Amanda E. Kowalski & Heidi Williams, 2010. "Estimating Marginal Returns to Medical Care: Evidence from At-risk Newborns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(2), pages 591-634.
    6. Andrew Gelman & Guido Imbens, 2019. "Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 447-456, July.
    7. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    8. Reif, Simon & Wichert, Sebastian & Wuppermann, Amelie, 2018. "Is it good to be too light? Birth weight thresholds in hospital reimbursement systems," Journal of Health Economics, Elsevier, vol. 59(C), pages 1-25.
    9. Michal Kolesár & Christoph Rothe, 2018. "Inference in Regression Discontinuity Designs with a Discrete Running Variable," American Economic Review, American Economic Association, vol. 108(8), pages 2277-2304, August.
    10. Cutler David M. & Meara Ellen, 2000. "The Technology of Birth: Is It Worth It?," Forum for Health Economics & Policy, De Gruyter, vol. 3(1), pages 1-37, January.
    11. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    12. Prashant Bharadwaj & Katrine Vellesen L?ken & Christopher Neilson, 2013. "Early Life Health Interventions and Academic Achievement," American Economic Review, American Economic Association, vol. 103(5), pages 1862-1891, August.
    13. David M. Cutler & Ellen Meara, 2000. "The Technology of Birth: Is It Worth It?," NBER Chapters, in: Frontiers in Health Policy Research, Volume 3, pages 33-68, National Bureau of Economic Research, Inc.
    14. Brigham R. Frandsen, 2017. "Party Bias in Union Representation Elections: Testing for Manipulation in the Regression Discontinuity Design when the Running Variable is Discrete," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 281-315, Emerald Group Publishing Limited.
    15. Daysal, N. Meltem & Trandafir, Mircea & van Ewijk, Reyn, 2019. "Low-risk isn’t no-risk: Perinatal treatments and the health of low-income newborns," Journal of Health Economics, Elsevier, vol. 64(C), pages 55-67.
    16. N. Meltem Daysal & Marianne Simonsen & Mircea Trandafir & Sanni Breining, 2022. "Spillover Effects of Early-Life Medical Interventions," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 1-16, March.
    17. Choi, Jin-young & Lee, Myoung-jae, 2019. "Twins are more different than commonly believed, but made less different by compensating behaviors," Economics & Human Biology, Elsevier, vol. 35(C), pages 18-31.
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    More about this item

    Keywords

    Birth weight; Macrosomia; Health care; Medical inputs; Infants; Mortality;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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