Skip to main content

Advertisement

SpringerLink
Log in

Body weight, mental health capital, and academic achievement

  • Published:
Review of Economics of the Household Aims and scope Submit manuscript

Abstract

Although obese students are more likely to exhibit the symptoms of depression than their slimmer counterparts and often do poorly in school, it is not clear whether these associations are spurious or causal in nature. Drawing on data from the National Longitudinal Study of Adolescent Health, we use an instrumental variables (IV) approach to distinguish between these hypotheses. IV estimates suggest that body weight leads to decreased self-esteem and increased depressive symptomatology among female, but not male, respondents. In addition, we find that body weight is negatively related to female academic achievement. Finally, we explore the degree to which the relationship between body weight and female academic achievement is explained by psychological wellbeing. We find that psychological wellbeing accounts for up to 30 % of this relationship.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. See Mallory et al. (1989), Rodriguez et al. (2002), Must and Anderson (2003), Hannon et al. (2005), Trent et al. (2005), and Tauman and Gozal (2006) for more information on adolescent obesity and asthma, menstrual abnormalities, sleep apnea, and type 2 diabetes. Among adults, obesity is associated with a wider set of pathologies including stroke, heart disease, and some types of cancer (World Health Organization 2000). See Oliver (2006) for an iconoclastic view of the relationship between obesity and health.

  2. See also Renman et al. (2007) and Swallen et al. (2005). Renman et al. (2007) matched 58 obese adolescents with 58 non-obese peers. They found no differences in self-esteem between the two groups. Swallen et al. (2005) used data from the first wave of the Add Health to examine the relationship between body weight and psychological wellbeing. These authors found that overweight and obese 12–14-year-olds were more likely to be depressed and more likely to have low self-esteem than their counterparts with BMIs in the normal range. However, they found no evidence to suggest that being overweight or obese was related to the psychological wellbeing of older adolescents.

  3. Using data from the Early Childhood Longitudinal Study-Kindergarten (ECLS-K), Zavodny (2013) found that BMI is negatively related to teacher assessment of student academic performance, but is essentially unrelated to standardized test scores. Zavodny interprets these findings as evidence that teachers may discriminate against overweight pupils.

  4. It should be noted, however, that a number of previous studies have found that the association between body weight and psychological wellbeing is at least as strong among males as among females (Swallen et al. 2005; Schieman et al. 2007; Cortese et al. 2009).

  5. Also see Eide et al. (2010), who found that being overweight was positively associated with male math and reading test scores. Crosnoe (2007) and Falkner et al. (2001) provide further evidence that overweight females suffer academically.

  6. Also see Datar et al. (2004) who found little evidence of a relationship between test scores and body weight. Fletcher and Lehrer (2009) found that weight status was not a good predictor of years of schooling completed.

  7. The initial Add Health data collection effort yielded information on over 20,000 respondents ages 11 through 21, approximately 17 % of whom had a participating biological sibling. Ninety-five percent of Add Health respondents were between the ages of 13 and 18 at the time of the baseline survey. See Harris et al. (2008) for more information on the Add Health data and how they were collected.

  8. The two missing items from the Adolescent Health questionnaire were “my sleep was restless,” and “I had crying spells.”

  9. See, for example, Goodman and Capitman (2000) and Hallfors et al. (2004 ).

  10. Sabia (2007) used a self-reported contemporaneous measure of grade point average in his study.

  11. Neither High School Diploma nor College Completion measure the quality of education received. As noted by Fletcher.

  12. See Kuczmarski et al (2002) for a discussion of these age- and gender-specific weight and BMI distributions.

  13. See Sabia (2007, p. 879) and Cawley (2004, p. 455) for a discussion of this issue. Wave II of the Add Health includes both measured and self-reported height and weight. In estimates not presented here, but available upon request, we find that self-reported and measured height and weight measures in the Add Health produce qualitatively similar findings to those presented below. Random measurement error (unrelated to psychological wellbeing or education) could lead to attenuation bias in OLS models but not the IV models described below.

  14. In addition to these controls, the vector X i included a set of indicators for missing values for each of the control variables. However, the findings presented below are robust to (1) restricting the sample to those respondents with non-missing information on each of the control variables, and (2) using a mean imputation method to fill in missing values of the control variables. For female respondents, we include a control for ever having been pregnant. There is evidence that parental education and family structure are associated with body weight. See, for instance, Kemptner and Marcus (2013 ).

  15. BMI of the respondent’s biological is available for respondents whose biological sibling was interviewed by the Add Health at Wave I. The second instrument is based on an item in the parental survey, which was usually completed by the respondent’s biological mother. The parent was asked, “[d]oes the adolescent’s biological mother now have [the health problem] of obesity?” The respondent’s mother was coded as being obese if this question was answered in the affirmative. A total of 3,467 respondents had non-missing information on their own body weight, their sibling’s body weight, and their biological mother’s obesity status.

  16. We note that the relationship between psychological wellbeing and academic performance is potentially bidirectional. However, our purpose is not to estimate the causal effect of psychological wellbeing on academic performance. Rather, it is to examine whether psychological wellbeing mediates the relationship between body weight and academic performance. The estimates of the relationship between psychological wellbeing and academic performance presented bellow should not be interpreted causally.

  17. Because the IV sample represents approximately 20 percent of all Add Health respondents, we explored the degree to which selection into this sample might produce non-representative estimates. Specifically, we estimated a probit model of the probability of being in the IV sample found that, among female respondents, neither BMI nor psychological wellbeing predicted this probability. Moreover, there were no statistically significant differences in family background or a wide set of individual characteristics. The only differences we found were that female respondents who were part of the IV sample tended to come from larger families (by construction, given that respondents had to have a sibling to be part of the IV sample), were less likely to be Asian, and were more likely to come from rural, non-Eastern parts of the United States. For males, the correlates were similar, although the IV sample was composed of individuals of slightly lower body weight than those in the OLS sample.

  18. The literature on exercise and adolescent mental health is briefly summarized by Rees and Sabia (2010). See Kakizaki et al. (2008) for a review of the literature on personality and obesity.

  19. In unreported results available upon request, we conduct gender-specific IV analyses by race and ethnicity. We find that the adverse psychological effects of adolescent bodyweight are strongest for white women and, depending on the specification, for Hispanic women. For black women, however, there is little evidence of a causal link.

  20. This third instrument is based on an item in the parental survey, which was usually completed by the respondent’s biological mother. The parent was asked, “[d]oes the adolescent’s biological father now have [the health problem] of obesity?” The respondent’s mother was coded as being obese if this question was answered in the affirmative.

  21. It should be noted that one concern with using the biological mother’s own reported obesity status as an instrument is that it could be correlated with unobserved attitudes related to mental health (or schooling). Therefore, we experimented with using sibling BMI as the sole instrument. TSLS estimates of the effect of body weight on academic achievement using sibling BMI as an instrument are qualitatively and quantitatively similar to the results reported in Table 5A and 7A.

  22. By focusing on the contemporaneous (i.e., cross-sectional) relationship between body weight and psychological wellbeing, our approach avoids modeling the complex long-run interactions between bodyweight, psychological wellbeing, and academic achievement. It should be noted however, that body weight at Wave I is highly correlated with body weight at Wave IV. In fact, less than 2 percent of respondents who were overweight at Wave I were in the healthy weight category at Wave IV. In unreported results available upon request, we estimate the relationship between Wave I body weight (in pounds) and Wave IV academic achievement controlling for Wave IV body weight (in pounds) for female respondents. The OLS and TSLS results still provide evidence of a negative relationship between Wave I body weight and academic achievement. However, these estimates are considerably smaller than those reported in the Table 7A perhaps because Wave I body weight is so closely tied to Wave IV body weight. A large number of studies have examined the long-run impact of academic achievement on body weight. See, for example, Fletcher and Frisvold (2014 ).

References

  • BeLue, R., Francis, L. A., & Colaco, B. (2009). Mental health problems and overweight in a nationally representative sample of adolescents: Effects of race and ethnicity. Pediatrics, 23(2), 697–702.

    Article  Google Scholar 

  • Betts, J. R., & Morrell, D. (1999). The determinants of undergraduate grade point average: The relative importance of family background, high school resources, and peer group effects. Journal of Human Resources, 34(2), 268–293.

    Article  Google Scholar 

  • Brunello, G., & D’Hombres, B. (2007). Does body weight affect wages? Evidence from Europe. Economics and Human Biology, 5(1), 1–19.

    Article  Google Scholar 

  • Card, D. (1999). The causal effect of education on earnings. In O. Ashenfelter, & D. Card (Eds.) Handbook of labor economics 3A (Chapter 30). Oxford: Elsevier.

  • Carpenter, K. M., Hasin, D. D., 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, 90(2), 251–257.

    Article  Google Scholar 

  • Cawley, J. (2004). The impact of obesity on wages. Journal of Human Resources, 39(2), 452–474.

    Google Scholar 

  • Cawley, J., Markowitz, S., & Tauras, J. (2004). Lighting up and slimming down: The effects of body weight and cigarette prices on adolescent smoking initiation. Journal of Health Economics, 23(2), 293–311.

    Article  Google Scholar 

  • Cawley, J., & Meyerhoefer, C. (2012). The Medical Costs of Obesity: An Instrumental Variables Approach. Journal of Health Economics, 31(1), 219–230.

    Article  Google Scholar 

  • Comuzzie, A. G., & Allison, D. B. (1998). The search for human obesity genes. Science, 280(5368), 1374–1377.

    Article  Google Scholar 

  • Cortese, S., Falissard, B., Angriman, M., Pigaiani, Y., Banzato, C., Bogoni, G., et al. (2009). The relationship between body size and depression symptoms in adolescents. The Journal of Pediatrics, 154(1), 86–90.

    Article  Google Scholar 

  • Cramer, P., & Steinwert, T. (1998). Thin is good, fat is bad: How early does it begin? Journal of Applied Developmental Psychology, 19(3), 429–451.

    Article  Google Scholar 

  • Crosnoe, R. (2007). Obesity and education. Sociology of Education, 80(3), 241–260.

    Article  Google Scholar 

  • Datar, A., Sturm, R., & Magnabosco, J. L. (2004). Childhood overweight and academic performance: National study of kindergartners and first-graders. Obesity Research, 12(1), 58–68.

    Article  Google Scholar 

  • Ding, W., Lehrer, S. F., Niels Rosenquist, J., & Audrain-McGovern, J. (2009). The impact of poor health on academic performance: New evidence using genetic markers. Journal of Health Economics, 28(3), 578–597.

    Article  Google Scholar 

  • Duncan, B., & Rees, D. I. (2005). The effect of smoking on depressive symptomatology: A reexamination of the data from the national longitudinal study of adolescent health. American Journal of Epidemiology, 162(5), 461–470.

    Article  Google Scholar 

  • Eide, E. R., Showalter, M. H., & Goldhaber, D. D. (2010). “The relation between children’s health and academic achievement. Children and Youth Services Review, 32(Bo. 2), 231–238.

    Article  Google Scholar 

  • Eisenberg, M. E., Neumark-Sztainer, D., & Story, M. (2003). Associations of weight-based teasing and emotional well-being among adolescents. Archives of Pediatrics and Adolescent Medicine, 157(8), 733–738.

    Article  Google Scholar 

  • 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), 33–42.

    Article  Google Scholar 

  • Fletcher, J. M. (2008). Adolescent depression: Diagnosis, treatment, and educational attainment. Health Economics, 17(11), 1215–1235.

    Article  Google Scholar 

  • Fletcher, J. M. (2010). Adolescent depression and educational attainment: Evidence from sibling fixed effects. Health Economics, 19(7), 855–871.

    Article  Google Scholar 

  • Fletcher, J. M., & Frisvold, D. E. (2014). The long run health returns to college quality. Review of Economics of the Household, 12(2), 295–325.

    Article  Google Scholar 

  • Fletcher, J. M., & Lehrer, F. L. (2009). The effects of adolescent health on educational outcomes: Causal evidence using genetic lotteries between siblings. Forum for Health Economics and Policy, 12, 2. http://www.bepress.com/fhep/12/2/8.

  • Franklin, J., Denyer, G., Steinbeck, K. S., Caterson, I. D., & Hill, A. J. (2006). Obesity and risk of low self-esteem: A statewide survey of Australian children. Pediatrics, 118(6), 2481–2487.

    Article  Google Scholar 

  • Frederick, D. A., Forbes, G. B., Grigorian, K. E., & Jarcho, J. M. (2007). The UCLA body project I: Gender and ethnic differences in self-objectification and body satisfaction among 2,206 undergraduates. Sex Roles, 57(5–6), 317–327.

    Article  Google Scholar 

  • French, M. T., Jenny, F. H., & Philip, K. R. (2011). What you do in high school matters: The effects of high school GPA on educational attainment and labor market earnings in adulthood. Working paper, University of Miami, Miami, FL.

  • Goodman, E., & Capitman, J. (2000). Depressive symptoms and cigarette smoking among teens. Pediatrics, 105(4), 748–755.

    Article  Google Scholar 

  • Grilo, C. M., & Pogue-Geile, M. F. (1991). The nature of environmental influences on weight and obesity: A behavioral genetic analysis. Psychological Bulletin, 110(3), 520–537.

    Article  Google Scholar 

  • Hallfors, D. D., Waller, M. W., Ford, C. A., Halpern, C. T., Brodish, P., & Iritani, B. (2004). Adolescent depression and suicide risk: Association with sex and drug behavior. American Journal of Preventative Medicine, 27(3), 224–231.

    Google Scholar 

  • Hannon, T. S., Rao, G., & Arslanian, S. A. (2005). Childhood obesity and type 2 diabetes mellitus. Pediatrics, 116(2), 473–480.

    Article  Google Scholar 

  • Harris, K. M., Halpern, C. T., Entzel, P., Tabor, J., Bearman P. S., & Udry, J. R. (2008). The national longitudinal study of adolescent health: Research design [WWW document]. http://www.cpc.unc.edu/projects/addhealth/design.

  • Heckman, J. J., & Pinto, R. (2013). Econometric mediation analysis: Identifying the sources of treatment effects from experimentally estimated production technologies with unmeasured and mismeasured inputs. National Bureau of economic research working paper no. 19314.

  • Heo, M., Pietrobelli, A., Fontaine, K. R., Sirey, J. A., & Faith, M. S. (2006). Depressive mood and obesity in US adults: Comparison and moderation by sex, age, and race. International Journal of Obesity, 30(3), 513–519.

    Article  Google Scholar 

  • Imbens, G. W., & Angrist, J. D. (1994). Identification and estimation of local average treatment effects. Econometrica, 62(2), 467–475.

    Article  Google Scholar 

  • Istvan, J., Zavela, K., & Weidner, G. (1992). Body weight and psychological distress in NHANES I. International Journal of Obesity and Related Metabolic Disorders, 16(12), 999–1003.

    Google Scholar 

  • Janssen, I., Craig, W. M., Boyce, W. F., & Pickett, W. (2004). Associations between overweight and obesity with bullying behaviors in school-aged children. Pediatrics, 113(5), 1187–1194.

    Article  Google Scholar 

  • Kaestner, R., & Grossman, M. (2009). Effects of weight on children’s educational achievement. Economics of Education Review, 28(6), 651–661.

    Article  Google Scholar 

  • Kakizaki, M., Kuriyama, S., Sato, Y., Shimazu, T., Matsuda-Ohmori, K., Nakaya, N., et al. (2008). Personality and body mass index: A cross-sectional analysis from the Miyagi Cohort study. Journal of Psychosomatic Research, 64(1), 71–80.

    Article  Google Scholar 

  • Kemptner, Daniel, & Marcus, Jan. (2013). Spillover effects of maternal education on child’s health and health behavior. Review of Economics of the Household, 11(1), 29–52.

    Article  Google Scholar 

  • Kuczmarski, R. J., Ogden, C. L., Guo, S. S., Grummer-Strawn, L. M., Flegal, K. M., Mei, Z., et al. (2002). 2000 CDC growth charts for the United States: Methods and development. Vital and Health Statistics, 11(246), 1–190.

    Google Scholar 

  • Latner, J. D., Stunkard, A. J., & Terence Wilson, G. (2005). Stigmatized students: Age, sex, and ethnicity effects in the stigmatization of obesity. Obesity, 13(7), 1226–1231.

    Article  Google Scholar 

  • Lee, C., & Orazem, P. F. (2010). High school employment, school performance, and college entry. Economics of Education Review, 29(1), 29–39.

    Article  Google Scholar 

  • Madsen, K. A., Weedn, A. E., & Crawford, P. B. (2010). Disparities in peaks, plateaus, and declines in prevalence of high BMI among adolescents. Pediatrics, 126(3), 434–442.

    Article  Google Scholar 

  • Mallory, G. B., Fiser, Debra H., & Jackson, Rithea. (1989). Sleep-associated breathing disorders in morbidly obese children and adolescents. The Journal of Pediatrics, 115(6), 892–897.

    Article  Google Scholar 

  • Markowitz, S., Friedman, M. A., & Arent, S. M. (2008). Understanding the relation between obesity and depression: Causal mechanisms and implications for treatment. Clinical Psychology: Science and Practice, 15(1), 1–20.

    Google Scholar 

  • Must, A., & Anderson, S. E. (2003). Effects of obesity on morbidity in children and adolescents. Nutrition in Clinical Care, 6(1), 4–12.

    Google Scholar 

  • Neumark-Sztainer, D., & Eisenberg, M. (2005). Weight bias in a teen’s world. In K. D. Brownell, R. Puhl, M. B. Schwartz, & R. Rudd (Eds.), Weight bias: Nature, consequences, and remedies (pp. 68–79). New York: The Guildford Press.

    Google Scholar 

  • Neumark-Sztainer, D., Story, M., & Harris, T. (1999). Beliefs and attitudes about obesity among teachers and school health care providers working with adolescents. Journal of Nutrition Education, 31(1), 3–9.

    Article  Google Scholar 

  • Norton, E. C., & Han, E. (2008). Genetic information, obesity, and labor market outcomes. Health Economics, 17(9), 1089–1104.

    Article  Google Scholar 

  • Ogden, C. L., & Carroll, M. D. (2010). Prevalence of obesity among children and adolescents: United States, trends 1963–1965 through 2007–2008. Washington DC: National Center for Health Statistics. http://www.cdc.gov/nchs/data/hestat/obesity_child_07_08/obesity_child_07_08.htm.

  • Ogden, C. L., Carroll, M. D., Curtin, L. R., Lamb, M. M., & Flegal, K. M. (2010). Prevalence of high body mass index in US children and adolescents, 2007–2008. Journal of the American Medical Association, 303(3), 242–249.

    Article  Google Scholar 

  • Oliver, J. E. (2006). The politics of pathology: How obesity became an epidemic disease. Perspectives in Biology and Medicine, 49(4), 611–627.

    Article  Google Scholar 

  • Onyike, C. U., Crum, R. M., Lee, H. B., Lyketsos, C. G., & Eaton, W. W. (2003). Is obesity associated with major depression? Results from the third national health and nutrition examination survey. American Journal of Epidemiology, 158(12), 1139–1147.

    Article  Google Scholar 

  • Pesa, J. A., Syre, T. R., & Jones, E. (2000). Psychosocial differences associated with body weight among female adolescents: The importance of body image. Journal of Adolescent Health, 26(5), 330–337.

    Article  Google Scholar 

  • Puhl, R., & Brownell, K. D. (2001). Bias, discrimination, and obesity. Obesity Research, 9(12), 788–805.

    Article  Google Scholar 

  • Puhl, R. M., & Latner, J. D. (2007). Stigma, obesity, and the health of the nation’s children. Psychological Bulletin, 133(4), 557–580.

    Article  Google Scholar 

  • Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401.

    Article  Google Scholar 

  • Rees, D. I., & Sabia, J. J. (2010). Exercise and adolescent mental health: New evidence from longitudinal data. Journal of Mental Health Policy and Economics, 13(1), 13–25.

    Google Scholar 

  • Renman, C., Engstrom, I., Silfverdal, S.-A., & Aman, J. (2007). Mental health and psychosocial characteristics in adolescent obesity: A population-based case–control study. Acta Paediatrica, 88(9), 998–1003.

    Article  Google Scholar 

  • Roberts, R. E., Lewinsohn, P. M., & Seeley, J. R. (1991). Screening for adolescent depression: A comparison of depression scales. Journal of the American Academy of Child and Adolescent Psychiatry, 30, 58–66.

    Article  Google Scholar 

  • Rodriguez, M. A., Winkleby, M. A., Ahn, D., Sundquist, J., & Kraemer, H. C. (2002). Identification of population subgroups of children and adolescents with high asthma prevalence: Findings from the third national health and nutrition examination survey. Archives of Pediatrics and Adolescent Medicine, 156(3), 269–275.

    Article  Google Scholar 

  • Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Sabia, J. J. (2007). The effect of adolescent body weight on adolescent academic performance. Southern Economic Journal, 73(4), 871–900.

    Google Scholar 

  • Sacerdote, B. (2007). How large are the effects from changes in family environment? A study of Korean American adoptees. Quarterly Journal of Economics, 122(1), 119–157.

    Article  Google Scholar 

  • Schieman, S., McMullen, T., & Swan, M. (2007). Relative body weight and psychological distress in late life observations of gender and race comparisons. Journal of Aging and Health, 19(2), 286–312.

    Article  Google Scholar 

  • Scholder, S. H. K., Smith, G. D., Lawlor, D. A., Propper, C., & Windmeijer, F. (2010). Genetic markers as instrumental variables: An application to child fat mass and academic achievement. Working paper no. 10/229, Centre for Market and Public Organisation, Bristol Institute of Public Affairs, University of Bristol.

  • Sira, N., & Ballard, S. M. (2011). Gender differences in body satisfaction: An examination of familial and individual level variables. Family Science Review, 16(1), 57–73.

    Google Scholar 

  • Smith, G. D., Sterne, J. A. C., Fraser, A., Tynelius, P., Lawlor, D. A., & Rasmussen, F. (2009). The association between BMI and mortality using offspring BMI as an indicator of own BMI: Large intergenerational mortality study. British Medical Journal, 339, b5403.

    Google Scholar 

  • Staiger, D., & Stock, J. H. (1997). Instrumental variables regression with weak instruments. Econometrica, 65(3), 557–586.

    Article  Google Scholar 

  • Stradmeijer, M., Bosch, J., Koops, W., & Seidell, J. (2000). Family functioning and psychosocial adjustment in overweight youngsters. International Journal of Eating Disorders, 27(1), 110–114.

    Article  Google Scholar 

  • Stunkard, A. J., Sorensen, T. I. A., Hanis, C., Teasdale, T. W., Chakraborty, R., Schull, W. J., et al. (1986). An adoption study of human obesity. New England Journal of Medicine, 314(4), 193–196.

    Article  Google Scholar 

  • Swallen, K. C., Reither, E. N., Haas, S., & Meier, A. M. (2005). Overweight, obesity, and health-related quality of life among adolescents: The national longitudinal study of adolescent health. Pediatrics, 115(2), 340–347.

    Article  Google Scholar 

  • Tauman, R., & Gozal, David. (2006). Obesity and Obstructive Sleep Apnea in Children. Paediatric respiratory reviews, 7(4), 247–259.

    Article  Google Scholar 

  • Tiggemann, Marika, & Anesbury, Tracy. (2000). Negative Stereotyping of Obesity in Children: The Role of Controllability Beliefs. Journal of Applied Social Psychology, 30(9), 1977–1993.

    Article  Google Scholar 

  • Tiggemann, M., & Wilson-Barrett, E. (1998). Children’s Figure Ratings: Relationship to Self-Esteem and Negative Stereotyping. International Journal of Eating Disorders, 23(1), 83–88.

    Article  Google Scholar 

  • Trent, M., Bryn Austin, S., Rich, M., & Gordon, C. M. (2005). Overweight status of adolescent girls with polycystic ovary syndrome: Body mass index as mediator of quality of life. Ambulatory Pediatrics, 5(2), 107–111.

    Article  Google Scholar 

  • Vogler, G. P., Sorensen, T. I. A., Stunkard, A. J., Srinivasan, M. R., & Rao, D. C. (1995). Influences of genes and shared family environment on adult body mass index assessed in an adoption study by a comprehensive path model. International Journal of Obesity, 19(1), 40–45.

    Google Scholar 

  • Wang, J., Iannotti, R. J., & Luk, J. W. (2010). Bullying victimization among underweight and overweight U.S. youth: Differential associations for boys and girls. Journal of Adolescent Health, 47(1), 99–101.

    Article  Google Scholar 

  • Wardle, J., Carnell, S., Haworth, C. M. A., & Plomin, R. (2008). Evidence for a strong genetic influence on childhood adiposity despite the force of the obesogenic environment. American Journal of Clinical Nutrition, 87(2), 398–404.

    Google Scholar 

  • World Health Organization. (2000). Obesity: Preventing and managing the global epidemic. Technical report series, no. 894. WHO, Geneva.

  • Zavodny, M. (2013). Does weight affect children’s test scores and teacher assessments differently? Economics of Education Review, 34, 135–145.

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank participants at the 2010 Southern Economic Association meetings for useful comments and suggestions on an earlier draft of this paper. This research uses data from the National Longitudinal Study of Adolescent Health, designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris, and funded by a Grant P01-HD31921 from the National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data files from the National Longitudinal Study of Adolescent Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 27516-2524 (http://www.cpc.unc.edu/addhealth/contract.html).

Author information

Authors and Affiliations

  1. Department of Economics, San Diego State University, 5500 Campanile Drive, San Diego, CA, 92182-4485, USA

    Joseph J. Sabia

  2. Department of Economics, University of Colorado Denver, Campus Box 181, Denver, CO, 80217-3364, USA

    Daniel I. Rees

Authors
  1. Joseph J. Sabia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel I. Rees
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joseph J. Sabia.

Appendix

Appendix

See Tables 11 and 12.

Table 11 Descriptive statistics for outcomes and key independent variables by gender for sample used to estimate Eq. (1)
Full size table
Table 12 Descriptive statistics for outcomes and key independent variables by gender for sample used to estimate Eq. (2)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sabia, J.J., Rees, D.I. Body weight, mental health capital, and academic achievement. Rev Econ Household 13, 653–684 (2015). https://doi.org/10.1007/s11150-014-9272-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11150-014-9272-7

Keywords

JEL Classification

Search

Navigation