Biomedical subjects

Garrett M Fitzmaurice

Publications and source records attributed to Garrett M Fitzmaurice.

4 recordsLinked to original sources

PubMed2003

Family disruption in childhood and risk of adult depression.

OBJECTIVE: The authors examined the risk that family disruption and low socioeconomic status in early childhood confer on the onset of major depression in adulthood. METHOD: Participants were 1,104 offspring of mothers enrolled during pregnancy in the Providence, R.I., site of the National Collaborative Perinatal Project. Measures of childhood family disruption and socioeconomic status were obtained before birth and at age 7. Structured diagnostic interviews were used to assess respondents' lifetime history of major depressive episode between the ages of 18 and 39. Survival analysis was used to identify childhood risks for depression onset. RESULTS: Parental divorce in early childhood was associated with a higher lifetime risk of depression among subjects whose mothers did not remarry as well as among subjects whose mothers remarried. These effects were more pronounced when accompanied by high levels of parental conflict. Independent of the respondents' adult socioeconomic status, low socioeconomic status in childhood predicted an elevated risk of depression. CONCLUSIONS: Family disruption and low socioeconomic status in early childhood increase the long-term risk for major depression. Reducing childhood disadvantages may be one avenue for prevention of depression. Identification of modifiable pathways linking aspects of the early childhood environment to adult mental health is needed to mitigate the long-term consequences of childhood disadvantage.

Adolescent↗

PubMed2002

Parameter estimation in longitudinal studies with outcome-dependent follow-up.

In many observational studies, individuals are measured repeatedly over time, although not necessarily at a set of prespecified occasions. Instead, individuals may be measured at irregular intervals, with those having a history of poorer health outcomes being measured with somewhat greater frequency and regularity; i.e., those individuals with poorer health outcomes may have more frequent follow-up measurements and the intervals between their repeated measurements may be shorter. In this article, we consider estimation of regression parameters in models for longitudinal data where the follow-up times are not fixed by design but can depend on previous outcomes. In particular, we focus on general linear models for longitudinal data where the repeated measures are assumed to have a multivariate Gaussian distribution. We consider assumptions regarding the follow-up time process that result in the likelihood function separating into two components: one for the follow-up time process, the other for the outcome process. The practical implication of this separation is that the former process can be ignored when making likelihood-based inferences about the latter; i.e., maximum likelihood (ML) estimation of the regression parameters relating the mean of the longitudinal outcomes to covariates does not require that a model for the distribution of follow-up times be specified. As a result, standard statistical software, e.g., SAS PROC MIXED (Littell et al., 1996, SAS System for Mixed Models), can be used to analyze the data. However, we also demonstrate that misspecification of the model for the covariance among the repeated measures will, in general, result in regression parameter estimates that are biased. Furthermore, results of a simulation study indicate that the potential bias due to misspecification of the covariance can be quite considerable in this setting. Finally, we illustrate these results using data from a longitudinal observational study (Lipshultz et al., 1995, New England Journal of Medicine 332, 1738-1743) that explored the cardiotoxic effects of doxorubicin chemotherapy for the treatment of acute lymphoblastic leukemia in children.

Adolescent↗

PubMed2002

A pattern-mixture model for longitudinal binary responses with nonignorable nonresponse.

Longitudinal studies frequently incur outcome-related nonresponse. In this article, we discuss a likelihood-based method for analyzing repeated binary responses when the mechanism leading to missing response data depends on unobserved responses. We describe a pattern-mixture model for the joint distribution of the vector of binary responses and the indicators of nonresponse patterns. Specifically, we propose an extension of the multivariate logistic model to handle nonignorable nonresponse. This method yields estimates of the mean parameters under a variety of assumptions regarding the distribution of the unobserved responses. Because these models make unverifiable identifying assumptions, we recommended conducting sensitivity analyses that provide a range of inferences, each of which is valid under different assumptions for nonresponse. The methodology is illustrated using data from a longitudinal study of obesity in children.

Adolescent↗

PubMed2002

Socioeconomic status in childhood and the lifetime risk of major depression.

BACKGROUND: Major depression occurs more frequently among people of lower socioeconomic status (SES) and among females. Although the focus of considerable investigation, the development of SES and sex differences in depression remains to be fully explained. In this study, we test the hypotheses that low childhood SES predicts an increased risk of adult depression and contributes to a higher risk of depression among females. METHODS: Participants were 1132 adult offspring of mothers enrolled in the Providence, Rhode Island site of the US National Collaborative Perinatal Project between 1959 and 1966. Childhood SES, indexed by parental occupation, was assessed at the time of participants' birth and seventh year. A lifetime history and age at onset of major depressive episode were ascertained via structured interviews according to diagnostic criteria. Survival analyses were used to model the likelihood of first depression onset as a function of childhood SES. RESULTS: Participants from lower SES backgrounds had nearly a twofold increase in risk for major depression compared to those from the highest SES background independent of childhood sociodemographic factors, family history of mental illness, and adult SES. Analyses of sex differences in the effect of childhood SES on adult depression provided modest support for the hypothesis that childhood SES contributes to adult sex differences in depression. CONCLUSIONS: Low SES in childhood is related to a higher risk of major depression in adults. Social inequalities in depression likely originate early in life. Further research is needed to identify the pathways linking childhood conditions to SES differences in the incidence of major depression.

Adult↗