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The Simultaneous Effects of Socioeconomic Disadvantage and Child Health on Children’s Cognitive Development

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Demography

Abstract

Family socioeconomic status (SES) and child health are so strongly related that scholars have speculated child health to be an important pathway through which a cycle of poverty is reproduced across generations. Despite increasing recognition that SES and health work reciprocally and dynamically over the life course to produce inequality, research has yet to address how these two pathways simultaneously shape children’s development. Using longitudinal data from the Fragile Families and Child Wellbeing Study and marginal structural models, we ask three questions: (1) how does the reciprocal relationship between socioeconomic disadvantage and child health affect estimates of each circumstance on children’s cognitive development?; (2) how do their respective effects vary with age?; and (3) do family SES and child health have differential effects on cognitive development across population subgroups? The results show that the negative effects of socioeconomic disadvantage and poor health are insensitive to their reciprocal relationships over time. We find divergent effects of socioeconomic disadvantage and poor health on children’s cognitive trajectories, with a widening pattern for family SES effects and a leveling-off pattern for child health effects. Finally, the effects of socioeconomic disadvantage are similar across all racial/ethnic groups, while the effects of child health are largely driven by white children. We discuss theoretical and policy implications of these findings for future research.

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Notes

  1. Researchers have also identified collider stratification bias as potentially arising with this approach (Morgan and Winship 2007; Pearl 2009). Suppose that unobserved factors influence time-varying child health and the outcome but not the treatment (i.e., time-varying exposure to socioeconomic disadvantage). Conditioning on child health generates an unnecessary correlation between its common causes—socioeconomic disadvantage and unobserved factors—even under the assumption of no unobserved heterogeneity of the treatment effect. Because unobserved factors also affect the outcome, conditioning on child health makes it impossible to distinguish the effects of socioeconomic disadvantage from those of unobserved factors.

  2. For example, the Early Childhood Longitudinal Study-Birth Cohort tracks children from birth only through kindergarten entry. The National Longitudinal Survey of Youth 1979 (NLSY79) Children and Young Adults collects information on children born only to NLSY79 mothers.

  3. Given our analytic strategy described later, we exclude mother-child pairs lost to follow-up from the analysis. They consist of those who permanently dropped out of the survey and those who left the survey but rejoined later. To address this issue of whole-wave missingness, we incorporate censoring weights in our marginal structural models.

  4. The analysis examines only those children whose cognitive achievement test is conducted in English because of its incompatibility with that in Spanish (Dunn and Dunn 1997). For this reason, the respondents contribute an average of 2.3 person-years to our panel data.

  5. For the Year 1 measure of child mental health, we use the Emotionality, Activity, and Sociability Temperament Survey for children as the CBCL scales are available from Year 3 on (Mathieson and Tambs 1999).

  6. We specify our models such that the quartile measures of socioeconomic disadvantage and child health are linearly linked to children’s cognitive development. In a supplementary analysis (results available upon request), we test whether the associations should be specified to be nonlinear by introducing quadratic terms in the models, and reject the nonlinear specification.

  7. Given the research design of the FFCWS, family structure at baseline refers only to a mother’s relationship with her child’s biological father.

  8. Weights are truncated at the first and ninety-ninth percentiles to avert disproportionate influence from outlying observations (Cole and Hernán 2008).

  9. If our MSMs are correctly specified, in expectation, the distributions of stabilized IPT, censoring, and final weights should be centered on values close to 1, have small variance, and be symmetric (Hernán et al. 2002). As shown in Table S3 (Online Resource 1), all three weights meet these conditions. They have a mean close to 1, are highly clustered around the mean, and are only slightly skewed to the right. Furthermore, Tables S4 and S5 (also in Online Resource 1) document that the IPT weighting achieves covariate balance, suggesting that socioeconomic disadvantage and poor health are largely independent of observed time-constant and time-varying covariates in the IPT weighted data.

  10. For the purpose of consistency, the analysis incorporates censoring weights into all models.

  11. Supplemental analysis (not shown) indicates that the effect of poor health at age 5 is mostly driven by children who transition to formal schooling.

  12. Descriptive evidence also supports divergent age-specific patterns of socioeconomic disadvantage and poor health. Nearly one-fourth of children (24 %) experience long-term exposure to the highest level of socioeconomic disadvantage (being on the fourth quartile at least two of three time points), whereas only one-eighth (13 %) do so with respect to poor health.

  13. Although the main goal of this study is to examine how the reciprocity between social causation and health selection processes affects children’s cognitive trajectory, unobserved confounding remains a concern. To address this issue, we estimate child fixed-effects models. By using within-child variation in exposures to socioeconomic and health disadvantages and cognitive achievement, these models account for selection bias due to unobserved time-constant characteristics. The results (see Table S7 in Online Resource 1) suggest that the age-specific patterns of socioeconomic disadvantage and child health effects are substantively similar to those reported here.

  14. We exclude other racial/ethnic groups because of their small sample sizes.

  15. Although we use IPT and censoring weights in the analysis, an additional examination that incorporates survey weights produces similar results (not shown). Our findings are therefore relevant to children growing up in large urban cities.

References

  • Achenbach, T. M., & Rescorla, L. A. (2000). Manuals for the ASEBA preschool forms and profiles. Burlington: Research Center for Children, Youth, and Families, University of Vermont.

    Google Scholar 

  • Adler, N. E., Boyce, T., Chesney, M. A., Cohen, S., Folkman, S., Kahn, R. L., & Syme, S. L. (1994). Socioeconomic status and health: The challenge of the gradient. American Psychologist, 49, 15–24.

    Article  Google Scholar 

  • Aizer, A., & Currie, J. (2014). The intergenerational transmission of inequality: Maternal disadvantage and health at birth. Science, 344, 856–861.

    Article  Google Scholar 

  • Allison, P. D. (2002). Missing data. Thousand Oaks, CA: Sage Publications.

    Book  Google Scholar 

  • Amato, P. R., & Keith, B. (1991). Parental divorce and the well-being of children: A meta-analysis. Psychological Bulletin, 110, 26–46.

    Article  Google Scholar 

  • Andersen, R. M., Mullner, R. M., & Cornelius, L. J. (1987). Black-white differences in health status: Methods or substance? Milbank Quarterly, 65, 72–99.

    Article  Google Scholar 

  • Bartley, M., & Plewis, I. (1997). Does health-selective mobility account for socioeconomic differences in health? Evidence from England and Wales, 1971 to 1991. Journal of Health and Social Behavior, 38, 376–386.

    Article  Google Scholar 

  • Boardman, J. D., Powers, D. A., Padilla, Y. C., & Hummer, R. A. (2002). Low birth weight, social factors, and developmental outcomes among children in the United States. Demography, 39, 353–368.

    Article  Google Scholar 

  • Bowles, S., & Gintis, H. (1976). Schooling in capitalist America. New York, NY: Basic Books.

    Google Scholar 

  • Busch, S. H., & Barry, C. L. (2007). Mental health disorders in childhood: Assessing the burden on families. Health Affairs, 26, 1088–1095.

    Article  Google Scholar 

  • Case, A., Fertig, A., & Paxson, C. (2005). The lasting impact of childhood health and circumstance. Journal of Health Economics, 24, 365–389.

    Article  Google Scholar 

  • Case, A., & Paxson, C. (2006). Children’s health and social mobility. Future of Children, 16(2), 151–173.

  • Chandola, T., Bartley, M., Sacker, A., Jenkinson, C., & Marmot, M. (2003). Health selection in the Whitehall II study, UK. Social Science & Medicine, 56, 2059–2072.

    Article  Google Scholar 

  • Cheadle, J. E., & Goosby, B. J. (2010). Birth weight, cognitive development, and life chances: A comparison of siblings from childhood into early adulthood. Social Science Research, 39, 570–584.

    Article  Google Scholar 

  • Cole, S. R., & Hernán, M. A. (2008). Constructing inverse probability of treatment weights for marginal structural models. American Journal of Epidemiology, 168, 656–664.

    Article  Google Scholar 

  • Conley, D., & Bennett, N. (2000). Is biology destiny? Birth weight and life chances. American Sociological Review, 65, 458–467.

    Article  Google Scholar 

  • Currie, J. (2005). Health disparities and gaps in school readiness. Future of Children, 15(1), 117–138.

  • Currie, J. (2009). Healthy, wealthy, and wise? Socioeconomic status, poor health in childhood, and human capital development. Journal of Economic Literature, 47, 87–122.

    Article  Google Scholar 

  • Dickman, S. J. (1990). Functional and dysfunctional impulsivity: Personality and cognitive correlates. Journal of Personality and Social Psychology, 58, 95–102.

    Article  Google Scholar 

  • DiPrete, T. A., & Jennings, J. L. (2012). Social and behavioral skills and the gender gap in early educational achievement. Social Science Research, 41, 1–15.

    Article  Google Scholar 

  • Donenberg, G., & Baker, B. L. (1993). The impact of young children with externalizing behaviors on their families. Journal of Abnormal Child Psychology, 21, 179–198.

    Article  Google Scholar 

  • Duncan, G. J., Yeung, W. J., Brooks-Gunn, J., & Smith, J. R. (1998). How much does childhood poverty affect the life chances of children? American Sociological Review, 63, 406–423.

    Article  Google Scholar 

  • Duncan, G. J., Ziol-Guest, K., & Kalil, A. (2010). Early-childhood poverty and adult attainment, behavior, and health. Child Development, 81, 306–325.

    Article  Google Scholar 

  • Dunn, L. M., & Dunn, L. M. (1997). Examiner’s manual for the Peabody Picture Vocabulary Test. Circle Pines, MN: American Guidance Services.

    Google Scholar 

  • Elder, G. H. (1994). Time, human agency, and social change: Perspectives on the life course. Social Psychological Quarterly, 57, 4–15.

    Article  Google Scholar 

  • Elder, G. H. (1998). The life course and human development. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology, Volume 1: Theoretical models of human development (pp. 939–991). New York, NY: John Wiley.

    Google Scholar 

  • Farkas, G. (2003). Cognitive skills and noncognitive traits and behaviors in stratification processes. Annual Review of Sociology, 29, 541–562.

    Article  Google Scholar 

  • Ferraro, K. F., & Farmer, M. M. (1996). Double jeopardy to health hypothesis for African Americans: Analysis and critique. Journal of Health and Social Behavior, 37, 27–43.

    Article  Google Scholar 

  • Ferraro, K. F., & Kelly-Moore, J. A. (2003). Cumulative disadvantage and health: Long-term consequences of obesity? American Sociological Review, 68, 707–729.

    Article  Google Scholar 

  • Ferraro, K. F., & Shippee, T. P. (2009). Aging and cumulative inequality: How does inequality get under the skin? Gerontologist, 49, 333–343.

    Article  Google Scholar 

  • Ferraro, K. F., Shippee, T. P., & Schafer, M. H. (2009). Cumulative inequality theory for research on aging and the life course. In V. L. Bengtson, M. Silverstein, N. M. Putney, & D. Gans (Eds.), Handbook of theories of aging (pp. 413–433). New York, NY: Springer.

    Google Scholar 

  • Finch, B. K. (2003). Early origins of the gradient: The relationship between socioeconomic status and infant mortality in the United States. Demography, 40, 675–699.

    Article  Google Scholar 

  • Finch, B. K., Hummer, R. A., Reindl, M., & Vega, W. A. (2002). Validity of self-rated health among Latino(a)s. American Journal of Epidemiology, 155, 755–759.

    Article  Google Scholar 

  • Garbarski, D. (2014). The interplay between child and maternal Health: Reciprocal relationships and cumulative disadvantage during childhood and adolescence. Journal of Health and Social Behavior, 55, 91–106.

    Article  Google Scholar 

  • Hall, M., & Farkas, G. (2011). Adolescent cognitive skills, attitudinal/behavioral traits, and career wages. Social Forces, 89, 1261–1285.

    Article  Google Scholar 

  • Hass, S. A. (2006). Health selection and the process of social stratification: The effect of childhood health on socioeconomic attainment. Journal of Health and Social Behavior, 47, 339–354.

    Article  Google Scholar 

  • Heckman, J. (2007). The economics, technology, and neuroscience of human capability formation. Proceedings of the National Academy of Sciences, 104, 13250–13255.

  • Hernán, M. Á., Brumback, B., & Robins, J. M. (2002). Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures. Statistics in Medicine, 21, 1689–1709.

    Article  Google Scholar 

  • Hogan, D., Msall, M. E., Goldscheider, F. K., Shandra, C. L., & Avery, R. C. (2012). Family consequences of children’s disabilities. New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Hsin, A. (2012). Is biology destiny? Birth weight and differential parental treatment. Demography, 49, 1385–1405.

    Article  Google Scholar 

  • Iceland, J. (2013). Poverty in America: A handbook. Los Angeles: University of California Press.

    Google Scholar 

  • Idler, E. L., & Kasl, S. V. (1995). Self-ratings of health: Do they also predict change in functional ability? Journal of Gerontology, Series B: Social Sciences, 508, S344–S353.

    Article  Google Scholar 

  • Jackson, M. I. (2009). Understanding links between adolescent health and educational attainment. Demography, 46, 671–694.

    Article  Google Scholar 

  • Jackson, M. I. (2010). A life course perspective on child health, cognition and occupational skill qualifications in adulthood: Evidence from a British cohort. Social Forces, 89, 89–116.

    Article  Google Scholar 

  • Jackson, M. I. (2015). Cumulative inequality in child health and academic achievement. Journal of Health and Social Behavior, 56, 262–280.

    Article  Google Scholar 

  • Jonsson, J. J. O. (2010). Child well-being and intergenerational inequality. Child Indicators Research, 3, 1–10.

    Article  Google Scholar 

  • Kadushin, C. (1964). Social class and the experience of ill health. Sociological Inquiry, 35, 67–80.

    Article  Google Scholar 

  • Kerckhoff, A. C., Haney, L. B., & Glennie, E. (2001). System effects on educational achievement: A British–American comparison. Social Science Research, 30, 497–528.

    Article  Google Scholar 

  • Kessler, R. C., Andrews, G., Mroczek, D., Ustun, B., & Wittchen, H.-U. (1998). The World Health Organization Composite International Diagnostic Interview short-form (CIDI-SF). International Journal of Methods in Psychiatric Research, 7, 171–185.

  • Kröger, H., Pakpahan, E., & Hoffmann, R. (2015). What causes health inequality? A systematic review on the relative importance of social causation and health selection. European Journal of Public Health, 25, 951–960.

    Article  Google Scholar 

  • Lee, D. (2014). Age trajectories of poverty during childhood and high school graduation. Sociological Science, 1, 344–365.

    Article  Google Scholar 

  • Lichter, D. T., Parisi, D., & Toquino, M. C. (2012). The geography of exclusion: Race, segregation, and concentrated poverty. Social Problems, 59, 364–388.

    Article  Google Scholar 

  • Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 35, 80–94.

    Article  Google Scholar 

  • Lynch, S. M. (2006). Explaining life course and cohort variation in the relationship between education and health: The role of income. Journal of Health and Social Behavior, 47, 324–338.

    Article  Google Scholar 

  • Magnuson, K., Waldfogel, J., & Washbrook, E. (2012). SES gradients in skills during the school years. In J. Ermisch, M. Jäntti, & T. M. Smeeding (Eds.), From parents to children: The intergenerational transmission of advantage (pp. 235–261). New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Masters, R. K., Hummer, R. A., & Powers, D. A. (2012). Educational differences in U.S. adult mortality: A cohort perspective. American Sociological Review, 77, 548–572.

    Article  Google Scholar 

  • Mathieson, K. S., & Tambs, K. (1999). The EAS temperament questionnaire: Factor structure, age trends, reliability, and stability in a Norwegian sample. Journal of Child Psychology and Psychiatry, 40, 431–439.

    Article  Google Scholar 

  • McLeod, J. D., & Fettes, D. L. (2007). Trajectories of failure: The educational careers of children with mental health problems. American Journal of Sociology, 113, 653–701.

    Article  Google Scholar 

  • McLeod, J. D., & Shanahan, M. J. (1993). Poverty, parenting and children’s mental health. American Sociological Review, 58, 351–366.

    Article  Google Scholar 

  • McLeod, J. D., & Shanahan, M. J. (1996). Trajectories of poverty and children’s mental health. Journal of Health and Social Behavior, 37, 207–220.

    Article  Google Scholar 

  • McLoyd, V. C., Cauce, A. M., Takeuchi, D., & Wilson, L. (2000). Marital processes and parental socialization in families of color: A decade review of research. Journal of Marriage and the Family, 62, 1070–1093.

    Article  Google Scholar 

  • Miech, R. A., Caspi, A., Moffitt, T. E., Wright, B. R. E., & Silva, P. A. (1999). Low socioeconomic status and mental disorders: A longitudinal study of selection and causation during young adulthood. American Journal of Sociology, 104, 1096–1131.

    Article  Google Scholar 

  • Miech, R. A., Pampel, F., Kim, J., & Rogers, R. G. (2011). The enduring association between education and mortality: The role of widening and narrowing disparities. American Sociological Review, 76, 913–934.

    Article  Google Scholar 

  • Morgan, S. L., & Winship, C. (2007). Counterfactuals and causal inference: Methods and principles for social research. New York, NY: Cambridge University Press.

    Book  Google Scholar 

  • Mulatu, M. S., & Schooler, C. (2002). Causal connections between socio-economic status and health: Reciprocal effects and mediating mechanisms. Journal of Health and Social Behavior, 43, 22–41.

    Article  Google Scholar 

  • Noonan, K., Reichman, N. E., & Corman, H. (2005). New fathers’ labor supply: Does child health matter? Social Science Quarterly, 86, 1399–1417.

    Article  Google Scholar 

  • Palloni, A. (2006). Reproducing inequalities: Luck, wallets, and the enduring effects of childhood health. Demography, 43, 587–615.

    Article  Google Scholar 

  • Palloni, A., Milesi, C., White, R., & Turner, A. (2009). Early childhood health, reproduction of economic inequalities and the persistence of health and mortality differentials. Social Science & Medicine, 68, 1574–1582.

    Article  Google Scholar 

  • Pearl, J. (2009). Causality: Models, reasoning, and inference. New York, NY: Cambridge University Press.

    Book  Google Scholar 

  • Powers, E. T. (2001). New estimates of the impact of child disability on maternal employment. American Economic Review, 91(2), 135–139.

  • Powers, E. T. (2003). Children’s health and maternal work activity: Estimates under alternative disability definitions. Journal of Human Resources, 38, 522–556.

    Article  Google Scholar 

  • Reichman, N. E., Corman, H., & Noonan, K. (2004). Effects of child health on parents’ relationship status. Demography, 41, 569–584.

    Article  Google Scholar 

  • Reichman, N. E., Teitler, J., Garfinkel, I., & McLanahan, S. (2001). Fragile Families: Sample and design. Children and Youth Services Review, 23, 303–326.

  • Robins, J. M. (1999). Association, causation, and marginal structural models. Synthese, 121, 151–179.

    Article  Google Scholar 

  • Robins, J. M., Hernán, M. Á., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11, 550–560.

    Article  Google Scholar 

  • Royston, P. (2005). Multiple imputation of missing values: Update. Stata Journal, 5, 188–201.

    Google Scholar 

  • Shonkoff, J. P., & Phillips, D. (2000). From neurons to neighborhood: The science of early childhood development. Washington, DC: National Academies Press.

    Google Scholar 

  • Smith, T. E. (1997). Differences between black and white students in the effects of parental separation on school grades. Journal of Divorce and Remarriage, 27, 25–42.

    Article  Google Scholar 

  • Stabile, M., & Allin, S. (2012). The economic costs of childhood disability. Future of Children, 22(1), 65–96.

  • Thomas, D., & Frankenberg, E. (2002). Health, nutrition and economic prosperity: A microeconomic perspective. Bulletin of the World Health Organization, 80, 106–113.

    Google Scholar 

  • Torche, F. (2011). The effect of maternal stress on birth outcomes: Exploiting a natural experiment. Demography, 48, 1473–1491.

    Article  Google Scholar 

  • Vaughan, E. L., Feinn, R., Bernard, S., Brereton, M., & Kaufman, J. S. (2013). Relationships between child emotional and behavioral symptoms and caregiver strain and parenting stress. Journal of Family Issues, 34, 534–556.

    Article  Google Scholar 

  • von Hippel, P. T. (2007). Regression with missing Ys: An improved strategy for analyzing multiply imputed data. Sociological Methodology, 37, 83–117.

    Article  Google Scholar 

  • Wagmiller, R. L., Lennon, M. C., Kuang, L., Alberti, P. M., & Aber, J. L. (2006). The dynamics of economic disadvantage and children’s life chances. American Sociological Review, 71, 847–866.

    Article  Google Scholar 

  • Warren, J. R. (2009). Socioeconomic status and health across the life course: A test of the social causation and health selection hypotheses. Social Forces, 87, 2125–2153.

    Article  Google Scholar 

  • Weschler, D. (1981). Wechsler adult intelligence scale-revised. New York, NY: The Psychological Corporation.

    Google Scholar 

  • Williams, D. R., Mohammed, S. A., Leavell, J., & Collins, C. (2010). Race, socioeconomic status, and health: Complexities, ongoing challenges, and research opportunities. Annals of the New York Academy of Sciences, 1186, 69–101.

    Article  Google Scholar 

  • Young, R., & Johnson, D. R. (2015). Handling missing values in longitudinal panel data with multiple imputation. Journal of Marriage and Family, 77, 277–294.

    Article  Google Scholar 

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Acknowledgments

Both authors contributed equally to the article. An earlier version of this article was presented at the 2015 meeting of the RC28 of ISA in Philadelphia. We gratefully acknowledge the Demography Editors and reviewers, Larry Wu, Florencia Torche, Mike Hout, and Paula England for their valuable feedback on earlier drafts of this article. This research was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A3A2044496).

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  1. Department of Sociology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea, 03722

    Dohoon Lee

  2. Department of Sociology, Brown University, Box 1916, Providence, RI, 02912, USA

    Margot Jackson

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Lee, D., Jackson, M. The Simultaneous Effects of Socioeconomic Disadvantage and Child Health on Children’s Cognitive Development. Demography 54, 1845–1871 (2017). https://doi.org/10.1007/s13524-017-0605-z

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