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International Journal of Health Economics and Management
Published in: International Journal of Health Economics and Management 2/2022

01-06-2022 | Obesity | Research article

Temporary and persistent overweight and long-term labor market outcomes

Authors: Liisa T. Laine, Ari Hyytinen

Published in: International Journal of Health Economics and Management | Issue 2/2022

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Abstract

We study how the duration of being overweight earlier in life is related to subsequent long-term labor market outcomes. Our data on fraternal and identical twins born and raised in the same household contain weight measurements of the twins during their early adulthood measured in 1975, 1981, and 1990 and is linked to register-based administrative data on the earnings and employment from 1990 to 2009. When combined, these data enable an empirical strategy that controls for the family environment and genes shared by twins. We find that being persistently overweight during early adulthood is negatively associated with long-term earnings for both women and men. We find that for women, the association is driven by a decrease in labor market-attachment, whereas for men, the association is driven by lower annual earnings.
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Footnotes
1
Extensive literature has used within-sibling variation to study, for instance, the effects of education on economic outcomes in different contexts (Griliches, 1979; Altonji and Dunn, 1996; Aaronson, 1998; Sacerdote, 2007; Abramitzky et al., 2012). Specifically, our approach is related to Behrman and Rosenzweig (2002) and Behrman et al. (1996) who estimate the returns to education using twin-data.
 
2
The age range in our study is slightly wider than in prior literature: Han et al. (2011) study the effect of adolescent BMI on education and occupation. The cohorts in Chen (2012) are teens (age 16), young adults (age 23), and adults (age 33). In Pinkston (2017) ages vary between 16–30.
 
3
Record linkages of the cohort study data conform to the Finnish Data Protection Act and were originally approved by the ethical committee of the Department of Public Health, University of Helsinki (Kaprio et al., 1979). All the data work of this paper was carried out at Statistics Finland, following its terms and conditions of confidentiality.
 
4
We acknowledge that the number of twin pairs is relatively small. However, the problem and the possible consequences of small sample size, for example on the power of the study, are shared by all studies using twin data.
 
5
As discussed below, these commonly used thresholds (in research and clinical work) are obviously proxies of excess body weight and have their limitations (see below). Anyhow, we use the official cutoffs determined by WHO for transparency instead of relying more "ad hoc" measures.
 
6
Figure A1 plots the local polynomial regressions of each long-term outcome on BMI (average over time) and Figure A2 plots twin-differenced local polynomial regressions of each long-term outcome on twin-differenced BMI (average over time). The former provide support for our use of BMI = 25 as the threshold for being overweight.
 
7
Our education variable refers to the number of years in school, which is based on information on achieved degrees and standard degree times.
 
8
It is unlikely that our results are explained by children only. For example, Finland universal health coverage and all individuals are insured by the National Health Insurance scheme. All pregnant women also attend regular well-child visits prior and after labor. It is also likely that the existing family leave policies Finland alleviate the effects of children on labor market outcomes.
 
9
The descriptive nature of our study is also in line with the interpretation of BMI being a proxy of different factors that can be associated with long-term labor market outcomes.
 
Literature
Aaronson, D. (1998). Using sibling data to estimate the impact of neighborhoods on children’s educational outcomes. The Journal of Human Resources, 33(4), 915–946.
Abramitzky, R., Boustan, L. P., & Eriksson, K. (2012). Europe’s tired, poor, huddled masses: Self-selection and economic outcomes in the age of mass migration. American Economic Review, 102(5), 1832–1856.
Altonji, J. G., & Dunn, T. A. (1996). Using siblings to estimate the effect of school quality on wages. The Review of Economics and Statistics, 78(4), 665–671.CrossRef
Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton: Princeton University Press.
Averett, S. (2011). Labor market consequences: Employment, wages, disability and absenteeism. In J. Cawley (Ed.), The Oxford Handbook of the Social Science of Obesity, Volume 1 of Oxford Handbooks (pp. 531–552). Oxford: Oxford University Press.
Averett, S., & Korenman, S. (1996). The economic reality of beauty myth. Journal of Human Resources, 31(2), 304–330.CrossRef
Baum, C., & Ford, W. (2004). The wage effects of obesity: A longitudinal study. Health Economics, 13, 885–899.PubMedCrossRef
Behrman, J., & Rosenzweig, M. (2001). The returns to increasing body weight. PIER Working Paper 01(052).
Behrman, J., & Rosenzweig, M. (2002). Does increasing women’s schooling raise the schooling of the next generation? American Economic Review, 92(1), 323–334.
Behrman, J., Rosenzweig, M., & Taubman, P. (1996). College choice and wages: Estimates using data on female twins. The Review of Economics and Statistics, 78(4), 672–685.CrossRef
Benjamin, D., Cesarini, D., Chabris, C. F., Glaeser, E. L., Laibson, D., Guonason, V., Harris, T. B., Launer, L. J., Purcell, S., Smith, A. V., Johannesson, M., Magnusson, P. K., Beauchamp, J. P., Christakis, N. A., Atwood, C. S., Hebert, B., Freese, J., Hauser, R. M., Hauser, T. S., & Lichtenstein, P. (2012). The promises and pitfalls of genoeconomics. Annual Review of Economics, 4(1), 627–662.PubMedPubMedCentralCrossRef
Böckerman, P., Cawley, J., Viinikainen, J., Lehtimäki, T., Rovio, S., Seppälä, I., et al. (2018). The effect of weight on labor market outcomes: An application of genetic instrumental variables. Health Economics.,.
Brown, C., & Routon, P. W. (2018). On the distributional and evolutionary nature of the obesity wage penalty. Economics & Human Biology, 28, 160–172.CrossRef
Brunello, G., & Beatrice, D. (2007). Does body weight affect wages?: Evidence from Europe. Economics & Human Biology, 5(1), 1–19.CrossRef
Burkhauser, R. V., & Cawley, J. (2008). Beyond BMI: The value of more accurate measures of fatness and obesity in social science research. Journal of Health Economics, 27(2), 519–529.PubMedCrossRef
Caliendo, M., & Gehrsitz, M. (2016). Obesity and the labor market: A fresh look at the weight penalty. Economics & Human Biology, 23, 209–225.CrossRef
Caliendo, M., & Lee, W.-S. (2013). Fat chance obesity and the transition from unemployment to employment. Economics & Human Biology, 11(2), 121–133.CrossRef
Campos-Vazquez, R. M., & Gonzalez, E. (2020). Obesity and hiring discrimination. Economics & Human Biology, 37, 100850.CrossRef
Cawley, J. (2004). The impact of obesity on wages. The Journal of Human Resources, 39(2), 451–474.CrossRef
Cawley, J. (2015). An economy of scales: A selective review of obesity’s economic causes, consequences, and solutions. Journal of Health Economics, 43, 244–268.
Cawley, J., & Meyerhoefer, C. (2012). The medical care costs of obesity: An instrumental variables approach. Journal of Health Economics, 31(1), 219–230.PubMedCrossRef
Datar, A. (2017). The more the heavier? Family size and childhood obesity in the U.S. Social Science & Medicine, 180, 143–151.CrossRef
Falkner, N. H., Neumark-Sztainer, D., Story, M., Jeffery, R. W., Beuhring, T., & Resnick, M. D. (2001). Social, educational, and psychological correlates of weight status in adolescents. Obesity Research, 9(1), 32–42.PubMedCrossRef
Farooqi, I. S., & O’Rahilly, S. (2007). Genetic factors in human obesity. Obesity Reviews, 8, 37–40.
Florin, T. A., Shults, J., & Stettler, N. (2011). Perception of overweight is associated with poor academic performance in us adolescents. Journal of School Health, 81(11), 663–670.CrossRef
Gregory, C. A., & Ruhm, C. J. (2011). Where does the wage penalty bite?, pp. 315 – 347. University of Chicago Press.
Griliches, Z. (1979). Sibling models and data in economics: Beginnings of a survey. Journal of Political Economy, 87(5), S37–S64.CrossRef
Gwozdz, W., Sousa-Poza, A., Reisch, L. A., Bammann, K., Eiben, G., Kourides, Y., Kovacs, E., Lauria, F., Konstabel, K., Santaliestra-Pasias, A. M., Vyncke, K., & Pigeot, I. (2015). Peer effects on obesity in a sample of European children. IZA Discussion Papers 9051, Institute for the Study of Labor (IZA).
Han, E., Norton, E. C., & Powell, L. M. (2011). Direct and indirect effects of body weight on adult wages. Economics & Human Biology, 9(4), 381–392.CrossRef
Han, E., Norton, E. C., & Stearns, S. C. (2009). Weight and wages: Fat versus lean paychecks. Health Economics, 18(5), 535–548.PubMedCrossRef
Heckman, J. J. (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312(5782), 1900–1902.PubMedCrossRef
Hyytinen, A., Ilmakunnas, P., & Toivanen, O. (2013). The return-to-entrepreneurship puzzle. Labour Economics, 20, 57–67.CrossRef
Hyytinen, A., & Lahtonen, J. (2013). The effect of physical activity on long-term income. Social Science & Medicine, 96, 129–137.CrossRef
Jenq, C., Pan, J., & Theseira, W. (2015). Beauty, weight, and skin color in charitable giving. Journal of Economic Behavior & Organization, 119, 234–253.CrossRef
Kaprio, J., Artimo, M, Sarna, S., & Rantasalo, I. (1979). The Finnish twin registry: Baseline characteristics. section i: Materials methods, representativeness and results for variables special to twin studies. Kansanterveystieteen julkaisuja, M.
Kristjansson, L. A., Sigfusdottir, I. D., & Allegrante, J. P. (2010). Health behavior and academic achievement among adolescents: The relative contribution of dietary habits, physical activity, body mass index, and self-esteem. Health Education & Behavior, 37(1), 51–64.CrossRef
Mobius, M. M., & Rosenblat, T. S. (2006). Why beauty matters. The American Economic Review, 96(1), 222–235.CrossRef
Morris, S. (2007). The impact of obesity on employment. Labour Economics, 14(3), 413–433.CrossRef
Pinkston, J. C. (2017). The dynamic effects of obesity on the wages of young workers. Economics & Human Biology, 27, 154–166.CrossRef
Price, J., & Swigert, J. (2012). Within-family variation in obesity. Economics & Human Biology, 10(4), 333–339.CrossRef
Puhl, R., & Brownell, K. D. (2001). Bias, discrimination, and obesity. Obesity Research, 9(12), 788–805.PubMedCrossRef
Rooth, D.-O. (2009). Obesity, attractiveness, and differential treatment in hiring: A field experiment. Journal of Human Resources, 44(3), 710–735.CrossRef
Sabia, J. J., & Rees, D. I. (2012). Body weight and wages: Evidence from Add Health. Economics & Human Biology, 10(1), 14–19.
Sacerdote, B. (2007). How large are the effects from changes in family environment? A study of Korean American adoptees. The Quarterly Journal of Economics, 122(1), 119–157.CrossRef
Sargent, J., & Blanchflower, D. (1994). Obesity and stature in adolescence and earnings in young adulthood: Analysis of a British birth cohort. Archives of Pediatrics & Adolescent Medicine, 148(7), 681–687.CrossRef
Segal, N. L., & Allison, D. B. (2002). Twins and virtual twins: Bases of relative body weight revisited. International Journal of Obesity and Related Disorders, 26(4), 437–441.CrossRef
Silventoinen, K., Jelenkovic, A., Sund, R., Honda, C., Aaltonen, S., Yokoyama, Y., Tarnoki, A. D., Tarnoki, D. L., Ning, F., Ji, F., et al. (2015). The codatwins project: The cohort description of collaborative project of development of anthropometrical measures in twins to study macro-environmental variation in genetic and environmental effects on anthropometric traits. Twin Research and Human Genetics, 18(4), 348–360.PubMedPubMedCentralCrossRef
Yang, W., Kelly, T., & He, J. (2007). Genetic epidemiology of obesity. Epidemiologic Reviews, 29(1), 49–61.PubMedCrossRef
Zwijnenburg, P. J., Meijers-Heijboer, H., & Boomsma, D. I. (2010). Identical but not the same: The value of discordant monozygotic twins in genetic research. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 153B(6)
Metadata
Title
Temporary and persistent overweight and long-term labor market outcomes
Authors
Liisa T. Laine
Ari Hyytinen
Publication date
01-06-2022
Publisher
Springer US
Published in
International Journal of Health Economics and Management / Issue 2/2022
Print ISSN: 2199-9023
Electronic ISSN: 2199-9031
DOI
https://doi.org/10.1007/s10754-021-09315-4

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