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related events are strong predictors of trajectories of growth
in depressive symptoms over a 6-year interval. In contrast,
trajectories of stable or decreasing stress are associated with
trajectories of decline in depressive symptoms.
which more accurately capture stress experience—would be
desirable. As mentioned before, our measures were trun-
cated both in terms of failing to provide a count of each type
of event between waves and in terms of failing to cover the
entire interval between waves of data collection. Nonethe-
less, we have argued that these effects should have only
negatively biased the relationship between stress and de-
pression.
The relationship between stressors and depression has
been a major research issue for more than three decades. It
may be tempting to assume that we already know all that we
need to about this relationship. This article has attempted to
demonstrate that on both theoretical (i.e., incomplete atten-
tion to stress exposure) and statistical grounds there is more
to be learned.
One of the reasons that patterns of change are highlighted
so clearly using latent growth curve analysis is the explicit
attention to heterogeneity provided by the construction of
individual trajectories. As expected, we observed wide vari-
ation in trajectories of both loss-related events and depres-
sive symptoms, with stability, increases, and decreases well
represented in the sample. Indeed, growth in events was ex-
perienced by a minority of sample members, albeit a size-
able minority (approximately 40%). Using latent growth
curve analysis, however, we were able to test the hypothesis
that growth in loss events over time will be associated with
increases in depressive symptoms. Thus, we did not simply
test the hypothesis that increases in both loss-related events
and depression are typical of the older population. Rather,
we also tested the hypothesis that those persons who experi-
ence increases in loss-related events will be at increased risk
for increases in depressive symptoms.
Although not the primary focus of this article, the effects
of the covariates on trajectories of depression are of interest.
The results indicated that all of the covariates except age
and race were significantly related to the intercept of the tra-
jectory of depressive symptoms, but only functional impair-
ment was significantly associated with the slope of the tra-
jectory. The relationships between the covariates and the
intercept are comparable to observations in previous cross-
sectional and short-term longitudinal studies: Women report
higher levels of depressive symptoms, as do the those with
lower levels or education, higher numbers of chronic ill-
nesses, and higher levels of functional impairment. In con-
trast, all the covariates but one were unrelated to the slope
of the trajectory of depressive symptoms. Thus, for exam-
ple, with the effects of loss-related events statistically con-
trolled, women were no more likely than men to exhibit tra-
jectories of increasing numbers of depressive symptoms
over time. The single covariate significantly related to the
slope of the depression trajectory was functional impair-
ment, and its effect was negative (i.e., high levels of impair-
ment were associated with decreasing depression symptoms
over time). This finding is contrary to the usual expectation
that functional impairment will increase the risk of depres-
sion. But other explanations are possible—for example, this
may represent a form of regression toward the mean or it
may be that individuals adjust to their impairments over
time, reducing psychological distress.
Acknowledgments
The research on which this article is based was performed pursuant to
Contract Number N01-AG-1-2102 with the National Institute on Aging, in
support of the Established Populations for Epidemiologic Studies of the
Elderly (Duke University). This research was supported by a Glaxo-
Wellcome Long-Term Care Research Award granted the first author, and
the first author was also supported by National Institute on Aging Grant
T32 AG00139. We thank the editor and the anonymous reviewers for their
comments on the article.
Address correspondence to Scott M. Lynch, Department of Sociology,
Princeton University, Princeton, NJ 08544. E-mail: slynch@princeton.edu
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