Young Adult Unemployment and Later Depression and Anxiety: Does Childhood Neighborhood Matter?
Young adulthood represents a developmental period with disproportionately heightened risk of losing a job. Young adult unemployment has been linked to increased mental health problems, at least in the short term. However, their possible long-term impacts, often referred as “scarring effects,” have been understudied, possibly underestimating the magnitude of mental health burden that young adult unemployment generates. This longitudinal study examined whether duration of unemployment during young adulthood is associated with later mental health disorders, after accounting for mental and behavioral health problems in childhood. Furthermore, the current study investigated whether childhood neighborhood characteristics affect this association and if so, in what specific functional ways. Data were drawn from a longitudinal study of developmental outcomes in a community sample in Seattle. Data collection began in 1985 when study participants were elementary students and involved yearly assessments in childhood and adolescence (ages 10–16) and then biennial or triennial assessments (ages 18–39; N = 677 at age 39; 47% European American, 26% African American, 22% Asian American, and 5% Native American; 49% female). The current study findings suggest that duration of unemployment across young adulthood increased mental health problems at age 39, regardless of gender. Childhood neighborhood characteristics, particularly their positive aspect, exerted independent impacts on adult mental health problems beyond unemployment experiences across young adulthood. The current findings indicate a needed shift in service profiles for unemployed young adults—a comprehensive approach that not only facilitates reemployment but also addresses mental health needs to help them to cope with job loss. Further, the present study findings suggest that childhood neighborhoods, particularly positive features such as positive neighborhood involvement, may represent concrete and malleable prevention targets that can curb mental health problems early in life.
KeywordsMental health Unemployment Scarring effects Life course Young adulthood Perceived neighborhood characteristics in childhood
We would like to extend our gratitude to SSDP study participants for their continued contribution to the study.
J.O.L. originated the study, performed the statistical analyses, guided additional data analyses, led the writing of the article, and coordinated drafting of the manuscript among co-authors; T.M.J. contributed to data preparation for analyses, drafted the method and result sections, and created tables; Y.Y. contributed to literature search; D.A.H. provided expertise in the conceptualization of neighborhood impacts; J.P.Y. contextualized findings in different cultural contexts; R.K. contributed to the conceptualization of the study, the data collection, and the interpretation of findings. In addition, all authors have been involved in drafting the manuscript and revising it critically for important intellectual content. All authors read and approved the final manuscript.
This study was supported by grants R01DA033956, 1R01DA024411, and 1R01DA009679 from National Institute on Drug Abuse. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the funding agency. The funding agency played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit this article for publication.
Data sharing and declaration
This manuscript’s data will not be deposited.
Compliance with Ethical Standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All study procedures were approved by the Human Subjects Review Committee of the University of Washington.
Informed consent was obtained from all participants included in the study.
- Achenbach, T. M. (1991). CBCL 4-18: YSR and TRF Profiles. Burlington, VT: University of Vermont Press.Google Scholar
- Achenbach, T. M., & Edelbrock, C. (1983). Manual for the Child Behavior Checklist and Revised Child Behavior Profile. Burlington, VT: University of Vermont Press.Google Scholar
- American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th edn.). Washington, DC: Author.Google Scholar
- Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. Thousand Oaks, CA: Sage.Google Scholar
- Bronfenbrenner, U., & Morris, P. A. (1998). The ecology of developmental processes. In R. Lerner (Ed.), Handbook of child psychology: 1. Theoretical models of human development. 5th ed. (pp. 992–1028). New York, NY: Wiley.Google Scholar
- Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996a). Behavioral observations at age 3 years predict adult psychiatric disorders: longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53, 1033–1039. https://doi.org/10.1001/archpsyc.1996.01830110071009.CrossRefGoogle Scholar
- Caspi, A., Moffitt, T. E., Thornton, A., Freedman, D., Amell, J. W., Harrington, H., & Silva, P. A. (1996b). The life history calendar: a research and clinical assessment method for collecting retrospective event-history data. International Journal of Methods in Psychiatric Research, 6, 101–114. https://doi.org/10.1002/(sici)1234-988x(199607)6:2<101::aid-mpr156>3.3.co;2-e.CrossRefGoogle Scholar
- Catalano, R., Goldman-Mellor, S., Saxton, K., Margerison-Zilko, C., Subbaraman, M., LeWinn, K., & Anderson, E. (2011). The health effects of economic decline. Annual Review of Public Health, 32, 431–450. https://doi.org/10.1146/annurev-publhealth-031210-101146.CrossRefGoogle Scholar
- Center for Behavioral Health Statistics and Quality (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15-4927, NSDUH Series H-50). https://www.samhsa.gov/data/sites/default/files/NSDUH-FRR1-2014/NSDUH-FRR1-2014.pdf
- Daly, M., & Delaney, L. (2013). The scarring effect of unemployment throughout adulthood on psychological distress at age 50: estimates controlling for early adulthood distress and childhood psychological factors. Social Science & Medicine, 80, 19–23. https://doi.org/10.1016/j.socscimed.2012.12.008.CrossRefGoogle Scholar
- Dooley, D., & Prause, J. (2004). The social costs of underemployment.. New York, NY: Cambridge University Press.Google Scholar
- Echeverria, S., Diez-Roux, A. V., Shea, S., Borrell, L. N., & Jackson, S. (2008). Associations of neighborhood problems and neighborhood social cohesion with mental health and health behaviors: the multi-ethnic study of atherosclerosis. Health and Place, 14, 853–865. https://doi.org/10.1016/j.healthplace.2008.01.004.CrossRefGoogle Scholar
- Edwards, K. A., & Hertel-Fernandez, A. (2010). The kids aren’t alright: a labor market analysis of young workers. Washington, DC: Economic Policy Institute.Google Scholar
- Fortin, N. M. (2015). Gender role attitudes and women’s labor market participation: opting-out, AIDS, and the persistent appeal of housewifery. Annals of Economics and Statistics, 117/118, 379–401. https://doi.org/10.15609/annaeconstat2009.117-118.379.CrossRefGoogle Scholar
- Frasquilho, D., de Matos, M. G., Marques, A., Gaspar, T., & Caldas-de-Almeida, J. M. (2016). Distress and unemployment: the related economic and noneconomic factors in a sample of unemployed adults. International Journal of Public Health, 61, 821–828. https://doi.org/10.1007/s00038-016-0806-z.CrossRefGoogle Scholar
- Hammarström, A., Gustafsson, P. E., Strandh, M., Virtanen, P., & Janlert, U. (2011). It’s no surprise! Men are not hit more than women by the health consequences of unemployment in the Northern Swedish Cohort. Scandinavian Journal of Public Health, 39, 187–193. https://doi.org/10.1177/1403494810394906.CrossRefGoogle Scholar
- Hawkins, J. D., Oesterle, S., Brown, E. C., Abbott, R. D., & Catalano, R. F. (2014). Youth problem behaviors 8 years after implementing the communities that care prevention system: a community-randomized trial. JAMA Pediatrics, 168, 122–129. https://doi.org/10.1001/jamapediatrics.2013.4009.CrossRefGoogle Scholar
- Hawkins, J. D., Smith, B. H., Hill, K. G., Kosterman, R., Catalano, R. F., & Abbott, R. D. (2003). Understanding and preventing crime and violence: Findings from the Seattle Social Development Project. In T. P. Thornberry & M. D. Krohn (Eds.), Taking stock of delinquency: an overview of findings from contemporary longitudinal studies (pp. 255–312). New York, NY: Kluwer Academic/Plenum.CrossRefGoogle Scholar
- Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. Thousand Oaks: Sage.Google Scholar
- Hultman, B., & Hemlin, S. (2008). Self-rated quality of life among the young unemployed and the young in work in northern Sweden. Work, 30, 461–472.Google Scholar
- Lee, J. O., Jones, T. M., Kosterman, R., Rhew, I. C., Lovasi, G. S., Hill, K. G., & Hawkins, J. D. (2017). The association of unemployment from age 21 to 33 with substance use disorder symptoms at age 39: the role of childhood neighborhood characteristics. Drug and Alcohol Dependence, 174, 1–8. https://doi.org/10.1016/j.drugalcdep.2017.01.005.CrossRefGoogle Scholar
- Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2013). Long-term neighborhood effects on low-income families: Evidence from moving to opportunity. American Economic Review, 103, 226–231. https://doi.org/10.1257/aer.103.3.226.CrossRefGoogle Scholar
- Monteiro, N. M., Balogun, S. K., & Oratile, K. N. (2014). Managing stress: The influence of gender, age and emotion regulation on coping among university students in Botswana. International Journal of Adolescence and Youth, 19, 153–173. https://doi.org/10.1080/02673843.2014.908784.CrossRefGoogle Scholar
- Moore, T. H. M., Kapur, N., Hawton, K., Richards, A., Metcalfe, C., & Gunnell, D. (2017). Interventions to reduce the impact of unemployment and economic hardship on mental health in the general population: A systematic review. Psychological Medicine, 47, 1062–1084. https://doi.org/10.1017/s0033291716002944.CrossRefGoogle Scholar
- Muthén, L. K., & Muthén, B. O. (2015). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
- Newman, D. L., Moffitt, T. E., Caspi, A., Magdol, L., Silva, P. A., & Stanton, W. R. (1996). Psychiatric disorder in a birth cohort of young adults: prevalence, comorbidity, clinical significance, and new case incidence from ages 11 to 21. Journal of Consulting and Clinical Psychology, 64, 552–562. https://doi.org/10.1037//0022-006x.64.3.552.CrossRefGoogle Scholar
- Nieuwenhuis, J., van Ham, M., Yu, R. Q., Branje, S., Meeus, W., & Hooimeijer, P. (2017). Being poorer than the rest of the neighborhood: relative deprivation and problem behavior of youth. Journal of Youth and Adolescence, 46, 1891–1904. https://doi.org/10.1007/s10964-017-0668-6.CrossRefGoogle Scholar
- Oesterle, S. (2013). Pathways to young adulthood and preventive interventions targeting young adults.. Washington, DC: National Academies Press.Google Scholar
- Reinherz, H. Z., Giaconia, R. M., Hauf, A. M. C., Wasserman, M. S., & Paradis, A. D. (2000). General and specific childhood risk factors for depression and drug disorders by early adulthood. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 223–231. https://doi.org/10.1097/00004583-200002000-00023.CrossRefGoogle Scholar
- Robins, L., Helzer, J. E., Croghan, J., Williams, J. B. W., & Spitzer, R. L. (1981). NIMH Diagnostic Interview Schedule (Version III). Rockville: National Institute of Mental Health.Google Scholar
- Sareen, J., Afifi, T. O., McMillan, K. A., & Asmundson, G. J. G. (2011). Relationship between household income and mental disorders: findings from a population-based longitudinal study. Archives of General Psychiatry, 68, 419–427. https://doi.org/10.1001/archgenpsychiatry.2011.15.CrossRefGoogle Scholar
- Sroufe, L. A. (2007). The place of development in developmental psychopathology. In M. A. S. (Ed.) Multilevel dynamics in developmental psychopathology: the Minnesota Symposia on Child Psychology (Vol. 34, pp. 285–299). Mahwah: Lawrence Erlbaum. .Google Scholar
- Taylor, P., Parker, K., Kochhar, R., Fry, R., Funk, C., Patten, E., & Motel, S. (2012). Young, underemployed and optimistic: coming of age, slowly, in a tough economy. Washington, DC: Pew Research Center.Google Scholar
- Wanberg, C. R. (2012). The individual experience of unemployment. Annual Review of Psychology, 63, 369–396. https://doi.org/10.1146/annurev-psych-120710-100500.CrossRefGoogle Scholar
- Yoshihama, M., Gillespie, B., Hammock, A. C., Belli, R. F., & Tolman, R. M. (2005). Does the life history calendar method facilitate the recall of intimate partner violence? Comparison of two methods of data collection. Social Work Research, 29, 151–163. https://doi.org/10.1093/swr/29.3.151.CrossRefGoogle Scholar