240 research outputs found

    Stepfamily Relationship Quality and Stepchildren’s Depression in Adolescence and Adulthood

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    Before reaching adulthood, one third of all youth in the United States will reside in a stepfamily household—a familial context marked by distinct challenges. Relatively few studies have explored family processes that promote youth adjustment in stepfamilies, and even fewer studies have examined these links across adolescence, emerging adulthood, and beyond. To address these gaps, we use a nationally representative sample of 758 adolescent stepchildren to examine the concurrent and long-term influence of mother–child, stepfather–child, nonresident father–child, and stepcouple relationship quality on stepchildren’s depression across three stages of development: adolescence, emerging adulthood, and young adulthood. Results from longitudinal structural equation modeling indicate that higher quality mother–child and stepfather–child relationships are directly associated with reductions in depression during adolescence and indirectly associated with reductions in depression during emerging and young adulthood via prior levels of depression; higher quality stepcouple relationships are directly associated with reductions in depression during emerging and young adulthood

    A Longitudinal Analysis of Stepfamily Relationship Quality and Adolescent Physical Health

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    Approximately one third of youth are estimated to live with a biological parent and stepparent before reaching adulthood. Additional research is warranted whereby stepfamily processes are identified that drive variation in youth adjustment, particularly physical health. We examined stepfather–child, mother–child, and stepcouple relationship quality as predictors of levels and changes in adolescent physical health over time. We used a nationally representative sample of 1,233 adolescents living in biological mother–stepfather families from waves I (1994–1995) and II (1996) of the National Longitudinal Study of Adolescent to Adult Health. We incorporated measures of stepfather–child, mother–child, and stepcouple relationship quality, as well as adolescent reports of 10 physical health symptoms at waves I and II. Structural equation modeling was used to examine associations between wave I stepfamily relationships and adolescent physical symptoms at waves I and II. We used a zero-inflated negative binomial model to establish the validity of wave II adolescent physical symptoms as a predictor of an index of diagnosed chronic illnesses by wave IV (ages 26–32 years).Stepfather–child and mother–child relationship quality were negatively correlated with concurrent levels of adolescent physical symptoms. Stepfather–child relationship quality was negatively associated with change in adolescent physical symptoms over time. Adolescents with higher levels of physical symptoms at wave II were more likely to report chronic illnesses by adulthood. Stepfather–child relationship quality is a robust predictor of adolescent physical health throughout adolescence and is linked to chronic illness diagnoses in young adulthood. Future research should explore further the mechanisms that underlie this association

    The Add Health Study: Design and Accomplishments

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    This document was prepared to be used by those interested in a ready reference for the design features and accomplishments of Add Health (the National Longitudinal Study of Adolescent Health). It provides a summary of features incorporated in the first fifteen years of completed work on the Add Health Study. The reader is referred to our web site (www.cpc.unc.edu/addhealth) for additional information, and for availability of data. Parts of this document may be incorporated into other documents for grant applications, papers for publication, or public presentations, without further permission. This document will be useful for those planning to use existing Add Health data

    Polygenic Scores (PGSs) in the National Longitudinal Study of Adolescent to Adult Health (Add Health) – Release 2

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    Research has shown that many outcomes of interest in the health, behavioral, and social sciences are influenced by genetics (Domingue et al. 2016; Plomin et al. 2016; Turkheimer 2000). For most human traits/behaviors, commonly referred to as phenotypes in genetic literature, it appears that the genetic influence on the phenotype is highly polygenic; i.e., there is no single gene that can account for the association between genetic variance and the outcome. Instead, the influence of genetics on the phenotype is due to many small associations spread across single-nucleotide polymorphisms (SNPs, pronounced snips) (Chabris et al. 2015). Polygenic Scores allow researchers to avoid the methodological complexities of including hundreds, thousands, and possibly millions, of covariates in their analyses by condensing, into a single measure, the associations between individual SNPs and the phenotype of interest (Plomin, Haworth, and Davis 2009)

    Polygenic Scores (PGSs) in the National Longitudinal Study of Adolescent to Adult Health (Add Health) – Release 1

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    Research has shown that many outcomes of interest in the health, behavioral, and social sciences are influenced by genetics (Domingue et al. 2016; Plomin et al. 2016; Turkheimer 2000). For most human traits/behaviors, commonly referred to as phenotypes, it appears that the genetic influence on the phenotype is highly polygenic; i.e., there is no single gene that can account for the association between genetic variance and the outcome. Instead, the influence of genetics on the phenotype appears to be due to many small associations across thousands, and possibly millions, of individual single-nucleotide polymorphisms (SNPs, pronounced snips) (Chabris et al. 2015). Polygenic Scores allow researchers to avoid the methodological complexities of including thousands, or millions, of covariates in their analyses by condensing, into a single measure, the associations between individual SNPs and the phenotype of interest (Plomin, Haworth, and Davis 2009)

    Construction of Wave V Biomarker Weight

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    This document provides a brief overview of how the biomarker sample was constructed. It also reports some statistical results of the biomarker weight

    Gender and Health Behavior Clustering among U.S. Young Adults

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    U.S. trends in population health suggest alarming disparities among young adults who are less healthy across most measureable domains than their counterparts in other high-income countries; these international comparisons are particularly troubling for women. To deepen our understanding of gender disparities in health and underlying behavioral contributions, we document gender-specific clusters of health behavior among U.S. young adults using nationally representative data from the National Longitudinal Study of Adolescent to Adult Health. We find high levels of poor health behavior, but especially among men; 40 percent of men clustered into a group characterized by unhealthy behavior (e.g., poor diet, no exercise, substance use), compared to only 22 percent of women. Additionally, women tend to age out of unhealthy behaviors in young adulthood more than men. Further, we uncover gender differences in the extent to which sociodemographic position and adolescent contexts inform health behavior clustering. For example, college education was more protective for men, whereas marital status was equally protective across gender. Parental drinking mattered for health behavior clustering among men, whereas peer drinking mattered for clustering among women. We discuss these results in the context of declining female advantage in U.S. health and changing young adult social and health contexts

    Household Financial Assets Inequity and Health Disparities Among Young Adults: Evidence from the National Longitudinal Study of Adolescent to Adult Health

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    Introduction: Research has established a strong relationship between financial resources and health outcomes. Yet, little is known about the effects of assets disparities on health outcomes, especially during the critical period when adolescents transition to adults. Methods: Using data from the National Longitudinal Study of Adolescent to Adult Health (n = 10,861), this study investigated the relationships between three household total assets value groups (low, moderate, and high assets) and three net worth groups (negative, neutral, and positive) on young adults’ general health, obese, and depression. Results: Both assets and debts were related to young adults’ health status, young adults with more assets and positive net worth have higher probability to report a better level of both general health and depression. Young adult’s obesity was found to be associated with net worth but not with assets. Conclusions and Implications: Our work connects health promotion with poverty alleviation to address the challenge of health disparity. A better understanding of different forms of financial resources (e.g., income, assets, and debts) and their dynamic relationships with health outcomes will contribute to developing effective asset-based interventions for promoting health status. Particularly, current policy and practice should consider the importance of resolving and clearing debt

    Impact of maternal and paternal preconception health on birth outcomes using prospective couples’ data in Add Health

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    Retrospective studies of preconception health have demonstrated that parents’ health conditions and behaviors can impact a newborn’s birth outcomes and, subsequently, future health status. This study sought to examine the impact of preconception health, measured prospectively, among both mothers and fathers, on two important birth outcomes: birthweight and gestational age

    Marriage and Health in the Transition to Adulthood: Evidence for African Americans in the Add Health Study

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    This paper examines the relationship between early marriage (before age 26), cohabitation, and health for African Americans and whites during the transition to adulthood using the National Longitudinal Study of Adolescent Health (Add Health). We examine three categories of health outcomes relevant to young adulthood: physical health, mental health, and health risk behaviors. Lagged dependent variable models are used to examine the health effects of early marriage and cohabitation accounting for potential health selection into unions. Our results indicate that early marriage by young adults does not have protective effects for African Americans, and finds more negative effects for African American men than women. There are mixed results for whites with some protective effects of marriage for binge drinking. Early marriage for both African Americans and whites is associated with increased Body Mass Index (BMI). Cohabitation is uniformly associated with negative health outcomes for all race and sex groups
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