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Family Structure, Community Context, and Adolescent Problem Behaviors

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Abstract

A number of models have been proposed to explain the relationship between family structure and adolescent problem behaviors, including several that consider parent-child relations, family income, stress, and residential mobility. However, studies have not explored whether the different types of communities within which families reside affect the association between family structure and problem behaviors. A community context model also suggests that the relationship between family structure and problem behaviors may be conditioned by community characteristics. The results of a multilevel regression model that used data from the National Educational Longitudinal Study (NELS; n = 10,286) indicated that adolescents from homes with a recently divorced mother, a mother and stepfather, a single mother, or a single father reported more problem behaviors regardless of the community context. Moreover, adolescents living in communities with a high proportion of impoverished residents, female headed households, or jobless males reported more problem behaviors irrespective of family structure.

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Notes

  1. It is normally not sufficient to use cross-sectional data to examine the processes that link family or community characteristics to adolescent behaviors. Longitudinal data are better suited for sorting out predictor and outcome variables, as well as for examining changes in family structure or community of residence. Unfortunately, NELS, even though it provided the best available data for examining family structure and community characteristics at the national-level, did not furnish suitable longitudinal data because (a) the waves were at least two years apart, (b) the problem behavior items were not consistent across the waves, and (c) it was not possible to match zipcode-level data with the data from 12th grade respondents. Since some students changed residences between 10th and 12th grade, it was not feasible to use the zipcode-level data for longitudinal data analysis. Hence, I relied on the 10th grade sample only and recommend that subsequent research attempt to confirm or dispute the results using longitudinal data.

  2. There are about 51,000 census tracts in the U.S. and about 20,000 zipcodes that are used. The zipcode-level file was constructed by the National Opinion Research Center for the National Center for Educational Statistics. Although census tracts may be preferable, studies using national-level data have begun to use zipcode or county-level data (e.g., Ainsworth, 2002; Arora and Cason, 1998), recognizing implicitly that sampling schemes typically provide too few observations per census tract for modeling purposes.

  3. Although one would prefer to have more respondents sampled per community unit, power analyses of multilevel models suggest that having a large number of level-2 (community) units is more important than the number of level-1 units (respondents) for producing unbiased and efficient estimates (Cohen, 1998).

  4. Whether a divorce had occurred in the past two years was based on a question that asked resident parents whether they had gone through a divorce since the 1988 interview. I also considered changes in stepparent families. However, a preliminary analysis indicated no significant differences between mother-stepfather families in terms of timing of remarriage, so only one group was used to specify mother-stepfather families. To be consistent, it would also have been preferable to create a recent divorce measure for father only families. However, several empirical models indicated that there were too few father only families to justify such a step.

  5. The NELS questions did not ask respondents to distinguish between resident and nonresident parents when asking about supervision or attachment. One might assume that most respondents referred to resident parents when answering these questions, but there is no way to ensure that such an assumption is valid. Hence, there may be an unknown degree of measurement error in the supervision and attachment items.

  6. I also estimated models that included only the family structure and the community-level variables, as well as their cross-level interactions, but found that this did not affect the results of or the conclusions based on the models shown in the results section.

  7. Another practical constraint due to the sparse within-unit sample sizes is whether the model is estimable with all seven random coefficients in one model. To check this, the random coefficients were entered piecemeal and then a final model was estimated with all of the significant random components in one model. Only the random components of the coefficients associated with father only, father-stepmother, and other family types were noticeably different from zero, with only two significantly so. Therefore, the coefficients associated with mother only (both types) and mother-stepfather families were specified as fixed in the analysis. The MCMC validation exercise described in the analysis plan substantiated this decision.

  8. A substantial amount of research has been conducted to determine the best approaches for analyzing multilevel data. An MCMC-Gibbs sampler method with diffuse priors has been recommended to validate models (Browne, Draper, Goldstein, and Rasbash, 2002). MCMC using a Bayesian approach by way of a resampling procedure (similar to a bootstrap) reduces the potential biases in standard errors and makes chance findings less likely. Mathematical details are provided in Gilks et al. (1996). I allowed 5,000 iterations of the Gibbs sampler to validate the models.

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Acknowledgments

Support for this research was provided by Grant 11293 from the National Institute on Drug Abuse. An earlier version of this paper was presented at the 2002 annual meeting of the American Society of Criminology, Chicago, IL. I thank the following people for advice and assistance on earlier drafts of this paper: Mikaela Dufur, Steve Bahr, Wayne Osgood, Ralph Brown, Bob Johnson, and three anonymous reviewers.

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  1. Department of Sociology, Brigham Young University, 2039 JFSB, Provo, UT, 84602, USA

    John P. Hoffmann

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Hoffmann, J.P. Family Structure, Community Context, and Adolescent Problem Behaviors. J Youth Adolescence 35, 867–880 (2006). https://doi.org/10.1007/s10964-006-9078-x

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