Stressful Life Events and Depression among Adolescent Twin Pairs

Abstract

Using the twin pairs sample from the National Longitudinal Study of Adolescent Health, we estimate bivariate Cholesky models for the influence of stressful life events (SLEs) on depressive symptoms. We show that depressive symptoms and dependent SLEs (events influenced by an individual's behavior) are both moderately heritable . We find no evidence for the heritability of independent SLEs. Results from the bivariate Cholesky model suggest that roughly one-half of the correlation between depression and dependent SLEs is due to common genetic factors. Our findings suggest that attempts to characterize the causal effect of SLEs on mental health should limit their list of SLEs to those that are outside of the control of the individual.

Acknowledgments

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill and funded by grant P01HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health Web site (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. Additional funding was provided by the following three NICHD grants: K01HD50336, R01HD060726, and R21HD051146.

Notes

¹Detailed information about the Add Health study design can be found in Harris et al. (2009), and readers are encouraged to visit the following website: http://www.cpc.unc.edu/projects/addhealth.

²We are aware that using researcher judgment to classify SLEs is not a perfect method. The personal beliefs of any researcher may influence whether they think specific life events are exogenous or brought upon oneself by the respondent. For this reason, we relied heavily on past research with one adjustment.

³The parameter tests from these models provide the following information: (1) the best-fitting model indicates whether genetic or environmental influences or both are important sources of variation for each trait; (2) the models decompose environmental influences into shared and nonshared sources and indicate whether both sources are needed to fully characterize environmental influences; and (3) most important, they describe the extent to which the observed covariation between the two traits is due to environmental or genetic covariation. Specifically, the path coefficients described in Figure 1, in combination with information about the variance of each trait and their covariance, can be used to identify the source of the variation that is unique to each trait and that which is shared. The equation describes this relatively simple element-by-element conversion. The solution to this equation provides standardized estimates for the heritability of SLEs , the heritability of depressive symptoms , and the proportion of the covariance between depression and SLEs that is due to common additive genetic influences (rA). A common summary statistic of the genetic covariation is the genetic correlation coefficient (r_g), which is given as . Taken as a function of the univariate heritabilties of the two traits , the standardized genetic correlation summarizes the proportion of the phenotypic correlation that is due to shared genetic influences.

⁴Because of the relatively low phenotypic correlation, the confidence interval for the standardized solution contains the value of zero. Simulations were used to obtain the following empirical 95 percent confidence interval for the genetic correlation coefficient [r _g = .15(−.06, .38)]. Though this estimate is statistically significant at the p < .10 level, we nevertheless suggests caution when interpreting the parameter estimate for the proportion of shared genetic covariance between dependent stressful life events and depressive symptoms.