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Sick and depressed? The causal impact of a diabetes diagnosis on depression

Author

Listed:
  • Alessio Gaggero

    (University of Granada)

  • Joan Gil

    (Universitat de Barcelona)

  • Dolores Jiménez-Rubio

    (University of Granada)

  • Eugenio Zucchelli

    (Universidad Autónoma de Madrid (UAM)
    Lancaster University
    IZA)

Abstract

Background There is sparse evidence on the impact of health information on mental health as well as on the mechanisms governing this relationship. We estimate the causal impact of health information on mental health via the effect of a diabetes diagnosis on depression. Methods We employ a fuzzy regression discontinuity design (RDD) exploiting the exogenous cut-off value of a biomarker used to diagnose type-2 diabetes (glycated haemoglobin, HbA1c) and information on psycometrically validated measures of diagnosed clinical depression drawn from rich administrative longitudinal individual-level data from a large municipality in Spain. This approach allows estimating the causal impact of a type-2 diabetes diagnosis on clinica ldepression. Results We find that overall a type-2 diabetes diagnosis increases the probability of becoming depressed, however this effect appears to be driven mostly by women, and in particular those who are relatively younger and obese. Results also appear to differ by changes in lifestyle induced by the diabetes diagnosis: while women who did not lose weight are more likely to develop depression, men who did lose weight present a reduced probability of being depressed. Results are robust to alternative parametric and non-parametric specifications and placebo tests. Conclusions The study provides novel empirical evidence on the causal impact of health information on mental health, shedding light on gender-based differences in such effects and potential mechanisms through changes in lifestyle behaviours.

Suggested Citation

  • Alessio Gaggero & Joan Gil & Dolores Jiménez-Rubio & Eugenio Zucchelli, 2023. "Sick and depressed? The causal impact of a diabetes diagnosis on depression," Health Economics Review, Springer, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:spr:hecrev:v:13:y:2023:i:1:d:10.1186_s13561-023-00451-w
    DOI: 10.1186/s13561-023-00451-w
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    1. Gaggero, Alessio & Gil, Joan & Jiménez-Rubio, Dolores & Zucchelli, Eugenio, 2022. "Does health information affect lifestyle behaviours? The impact of a diabetes diagnosis," Social Science & Medicine, Elsevier, vol. 314(C).
    2. Gaggero, A. & Gil, J. & Jiménez-Rubio, D. & Zucchelli, E., 2021. "Health information and lifestyle behaviours: the impact of a diabetes diagnosis," Health, Econometrics and Data Group (HEDG) Working Papers 21/02, HEDG, c/o Department of Economics, University of York.
    3. Kim, Hyuncheol Bryant & Lee, Suejin A. & Lim, Wilfredo, 2019. "Knowing is not half the battle: Impacts of information from the National Health Screening Program in Korea," Journal of Health Economics, Elsevier, vol. 65(C), pages 1-14.
    4. 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.
    5. Jutta Roosen & Stéphan Marette & Sandrine Blanchemanche & Philippe Verger, 2009. "Does Health Information Matter for Modifying Consumption? A Field Experiment Measuring the Impact of Risk Information on Fish Consumption," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 2-20.
    6. Iizuka, Toshiaki & Nishiyama, Katsuhiko & Chen, Brian & Eggleston, Karen, 2021. "False alarm? Estimating the marginal value of health signals," Journal of Public Economics, Elsevier, vol. 195(C).
    7. Paul Frijters & David W. Johnston & Michael A. Shields, 2014. "The Effect Of Mental Health On Employment: Evidence From Australian Panel Data," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1058-1071, September.
    8. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    9. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    10. Nathan Kettlewell, 2020. "Policy Choice and Product Bundling in a Complicated Health Insurance Market: Do People Get It Right?," Journal of Human Resources, University of Wisconsin Press, vol. 55(2), pages 566-610.
    11. Seuring, Till & Serneels, Pieter & Suhrcke, Marc & Bachmann, Max, 2020. "Diabetes, employment and behavioural risk factors in China: Marginal structural models versus fixed effects models," Economics & Human Biology, Elsevier, vol. 39(C).
    12. Gaggero, Alessio, 2020. "The effect of type 2 diabetes diagnosis in the elderly," Economics & Human Biology, Elsevier, vol. 37(C).
    13. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    14. Grossman, Michael, 1972. "On the Concept of Health Capital and the Demand for Health," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 223-255, March-Apr.
    15. Cawley, John & Ruhm, Christopher J., 2011. "The Economics of Risky Health Behaviors," Handbook of Health Economics, in: Mark V. Pauly & Thomas G. Mcguire & Pedro P. Barros (ed.), Handbook of Health Economics, volume 2, chapter 0, pages 95-199, Elsevier.
    16. Saurabh Bhargava & George Loewenstein & Justin Sydnor, 2017. "Choose to Lose: Health Plan Choices from a Menu with Dominated Option," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1319-1372.
    17. Deborah J. Brown & Lee F. Schrader, 1990. "Cholesterol Information and Shell Egg Consumption," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(3), pages 548-555.
    18. Fichera, Eleonora & von Hinke, Stephanie, 2020. "The response to nutritional labels: Evidence from a quasi-experiment," Journal of Health Economics, Elsevier, vol. 72(C).
    19. Zhao, Meng & Konishi, Yoshifumi & Glewwe, Paul, 2013. "Does information on health status lead to a healthier lifestyle? Evidence from China on the effect of hypertension diagnosis on food consumption," Journal of Health Economics, Elsevier, vol. 32(2), pages 367-385.
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    More about this item

    Keywords

    Diabetes; Depression; Fuzzy regression discontinuity design; Administrative longitudinal data; Lifestyle changes;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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