IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp13055.html
   My bibliography  Save this paper

The Impact of BMI on Mental Health: Further Evidence from Genetic Markers

Author

Listed:
  • Amin, Vikesh

    (Central Michigan University)

  • Flores, Carlos A.

    (California Polytechnic State University)

  • Flores-Lagunes, Alfonso

    (Syracuse University)

Abstract

We estimate the effect of BMI on mental health for young adults and elderly individuals using data from the National Longitudinal Study of Adolescent Health and the Health & Retirement Study. To tackle confounding due to unobserved factors, we exploit variation in a polygenic score (PGS) for BMI within two complementary econometric methods that differ in the assumptions they employ. First, we use the BMI PGS as an IV and adjust for PGSs for other factors (depression and educational attainment) that may invalidate this IV. We find a large statistically significant effect of BMI on mental health for the elderly: a 5 kg/m2 increase in BMI (a difference equivalent to moving from overweight to obese) increases the probability of depression by 29%. In contrast, for young adults the IV estimates are statistically and economically insignificant. We show that IV estimates likely have to be interpreted as identifying a weighted average of effects of BMI on mental health mostly for compliers on the upper quantiles of the BMI distribution. Second, we use the BMI PGS as an "imperfect" IV and estimate an upper bound on the average treatment effect for the population. The estimated upper bounds reinforce the conclusions from the IV estimates.

Suggested Citation

  • Amin, Vikesh & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2020. "The Impact of BMI on Mental Health: Further Evidence from Genetic Markers," IZA Discussion Papers 13055, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13055
    as

    Download full text from publisher

    File URL: http://ftp.iza.org/dp13055.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bonanno, Alessandro & Bimbo, Francesco & Cleary, Rebecca & Castellari, Elena, 2018. "Food labels and adult BMI in Italy – An unconditional quantile regression approach," Food Policy, Elsevier, vol. 74(C), pages 199-211.
    2. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    3. Flores, Carlos A. & Flores-Lagunes, Alfonso, 2009. "Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment under Unconfoundedness," IZA Discussion Papers 4237, Institute of Labor Economics (IZA).
    4. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    5. Thomas A. DiPrete & Casper A. P. Burik & Philipp D. Koellinger, 2018. "Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(22), pages 4970-4979, May.
    6. Petri Böckerman & John Cawley & Jutta Viinikainen & Terho Lehtimäki & Suvi Rovio & Ilkka Seppälä & Jaakko Pehkonen & Olli Raitakari, 2019. "The effect of weight on labor market outcomes: An application of genetic instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 65-77, January.
    7. Brunello, Giorgio & D'Hombres, Beatrice, 2007. "Does body weight affect wages?: Evidence from Europe," Economics & Human Biology, Elsevier, vol. 5(1), pages 1-19, March.
    8. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, vol. 81(2), pages 667-737, March.
    9. Greve, Jane, 2008. "Obesity and labor market outcomes in Denmark," Economics & Human Biology, Elsevier, vol. 6(3), pages 350-362, December.
    10. Anna Zajacova & Sarah Burgard, 2013. "Healthier, Wealthier, and Wiser: A Demonstration of Compositional Changes in Aging Cohorts Due to Selective Mortality," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(3), pages 311-324, June.
    11. Janet Currie & Enrico Moretti, 2003. "Mother's Education and the Intergenerational Transmission of Human Capital: Evidence from College Openings," The Quarterly Journal of Economics, Oxford University Press, vol. 118(4), pages 1495-1532.
    12. Christine Himes, 2000. "Obesity, disease, and functional limitation in later life," Demography, Springer;Population Association of America (PAA), vol. 37(1), pages 73-82, February.
    13. Willage, Barton, 2018. "The effect of weight on mental health: New evidence using genetic IVs," Journal of Health Economics, Elsevier, vol. 57(C), pages 113-130.
    14. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    15. Wehby, George L. & Courtemanche, Charles J., 2012. "The heterogeneity of the cigarette price effect on body mass index," Journal of Health Economics, Elsevier, vol. 31(5), pages 719-729.
    16. von Hinke, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2016. "Genetic markers as instrumental variables," Journal of Health Economics, Elsevier, vol. 45(C), pages 131-148.
    17. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    18. Morris, Stephen, 2007. "The impact of obesity on employment," Labour Economics, Elsevier, vol. 14(3), pages 413-433, June.
    19. Hyungserk Ha & Chirok Han & Beomsoo Kim, 2017. "Can Obesity Cause Depression? Using Pseudo Panel Analysis," Discussion Paper Series 1701, Institute of Economic Research, Korea University.
    20. Euna Han & Lisa M. Powell, 2013. "Fast Food Prices And Adult Body Weight Outcomes: Evidence Based On Longitudinal Quantile Regression Models," Contemporary Economic Policy, Western Economic Association International, vol. 31(3), pages 528-536, July.
    21. Puhl, R.M. & Heuer, C.A., 2010. "Obesity stigma: Important considerations for public health," American Journal of Public Health, American Public Health Association, vol. 100(6), pages 1019-1028.
    22. Magnus Johannesson & David I. Laibson & Sarah E. Medland & Michelle N. Meyer & Joseph K. Pickrell & Tõnu Esko & Robert F. Krueger & Jonathan P. Beauchamp & Philipp D. Koellinger & Daniel J. Benjamin &, 2016. "Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses," Post-Print hal-02017373, HAL.
    23. Carpenter, K.M. & Hasin, D.S. & Allison, D.B. & Faith, M.S., 2000. "Relationships between obesity and DSM-IV major depressive disorder, suicide ideation, and suicide attempts: Results from a general population study," American Journal of Public Health, American Public Health Association, vol. 90(2), pages 251-257.
    24. Huber, Martin, 2019. "A review of causal mediation analysis for assessing direct and indirect treatment effects," FSES Working Papers 500, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    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. Barone, Adriana & Barra, Cristian, 2019. "Weight status and mental health in Italy: Evidence from EHIS2 microdata," MPRA Paper 96703, University Library of Munich, Germany.

    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. Aliaksandr Amialchuk & Kateryna Bornukova & Mir M. Ali, 2018. "Will a Decline in Smoking Increase Body Weights? Evidence from Belarus," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 44(2), pages 190-210, April.
    2. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    3. Kedagni, Desire, 2018. "Identifying Treatment Effects in the Presence of Confounded Types," ISU General Staff Papers 201809110700001056, Iowa State University, Department of Economics.
    4. Christina Hansen Edwards & Johan Håkon Bjørngaard & Jonas Minet Kinge, 2021. "The relationship between body mass index and income: Using genetic variants from HUNT as instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1933-1949, August.
    5. Kedagni, Desire, 2021. "Identifying treatment effects in the presence of confounded types," ISU General Staff Papers 202106050700001056, Iowa State University, Department of Economics.
    6. Kim, Tae Hyun & Han, Euna, 2015. "Impact of body mass on job quality," Economics & Human Biology, Elsevier, vol. 17(C), pages 75-85.
    7. Jun Wang & Qihui Chen & Gang Chen & Yingxiang Li & Guoshu Kong & Chen Zhu, 2020. "What is creating the height premium? New evidence from a Mendelian randomization analysis in China," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
    8. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    9. MORIKAWA Masayuki, 2018. "Smoking, Obesity, and Labor Market Outcomes: Evidence from Japan," Discussion papers 18023, Research Institute of Economy, Trade and Industry (RIETI).
    10. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    11. Asgeirsdottir, Tinna Laufey, 2011. "Do body weight and gender shape the work force? The case of Iceland," Economics & Human Biology, Elsevier, vol. 9(2), pages 148-156, March.
    12. Raymundo M. Campos-Vazquez & Roy Nuñez, 2019. "Obesity and labor market outcomes in Mexico/Obesidad y el mercado de trabajo en México," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 34(2), pages 159-196.
    13. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    14. Tinna Laufey Ásgeirsdóttir & Harpa H. Berndsen & Bryndís Þ. Guðmundsdóttir & Bryndís A. Gunnarsdóttir & Hugrún J. Halldórsdóttir, 2016. "The effect of obesity, alcohol misuse and smoking on employment and hours worked: evidence from the Icelandic economic collapse," Review of Economics of the Household, Springer, vol. 14(2), pages 313-335, June.
    15. Chu, Filmer & Ohinmaa, Arto, 2016. "The obesity penalty in the labor market using longitudinal Canadian data," Economics & Human Biology, Elsevier, vol. 23(C), pages 10-17.
    16. Konstantinos Eleftheriou & George Athanasiou & Periklis Kougoulis, 2013. "Labour market, obesity and public policy considerations," Economics Bulletin, AccessEcon, vol. 33(1), pages 783-793.
    17. Joseph Sabia & Daniel Rees, 2015. "Body weight, mental health capital, and academic achievement," Review of Economics of the Household, Springer, vol. 13(3), pages 653-684, September.
    18. Vira Semenova, 2020. "Better Lee Bounds," Papers 2008.12720, arXiv.org.
    19. Johansson, Edvard & Böckerman, Petri & Kiiskinen, Urpo & Heliövaara, Markku, 2009. "Obesity and labour market success in Finland: The difference between having a high BMI and being fat," Economics & Human Biology, Elsevier, vol. 7(1), pages 36-45, March.
    20. Sif Jónsdóttir & Tinna Ásgeirsdóttir, 2014. "The effect of job loss on body weight during an economic collapse," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(6), pages 567-576, July.

    More about this item

    Keywords

    BMI; depression; genetics; instrumental variables;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:iza:izadps:dp13055. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.