Trajectories of Depressive Symptoms in Old Age

This research study by Chui, Gerstorf, Hoppmann, and Luszcz (2015) integrated changes
related to age, pathology, and mortality to examine the Trajectories of depressive symptoms in
old age. Life in the old age is faced with different challenges in the well-being of an individual.
The researcher in this study extends that propositions drawn from the well-being paradox in
ageing using data collected for about fifteen years. Basically, the goal of the researcher was to
examine age- related trajectories of depressive symptoms in association with mortality in old and
very old age, considering pathology-related changes in order to extend and qualify the previous
findings in regards to the well-being paradox of old age.
The Australian Longitudinal Study of ageing collected data based on depressive
symptoms from participants that were old to those that were very old. The researcher in this
study avoided using life-threatening conditions and mainly focused on the relationships between
diagnosis of arthritis, changes in depressive symptoms and mortality.
The researcher’s hypotheses included: first, depressive symptoms would rise from young
to old as well as oldest to old. Secondly, increases that are related to age in depressive symptoms
would be associated with arthritis incidences. Thirdly, changes related to age in depressive
symptoms would be important predictors of death. The specific hypothesis was that increase
related to age in level and slope of depressive symptoms would be associated with increased
risks of mortality. According to the results of decreasing gender differences in depressive
symptoms from young to old age and old to old age from a longitudinal sample (Barefoot et al.,
2001), the researcher hypothesized that women would show a higher levels of depressive

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symptoms than men. Gender differences in depressive symptoms were hypothesized to be
smaller in oldest to old age than in young to old-aged adults.
Baltes et al (2006) points out that people experience developmental change which
involves gains and losses, that is, as one ages, losses in functional capacity increase while gains
decrease. However, it is paradoxical that studies indicate that well-being stability takes pace as
people age. Reports indicate increased life satisfaction in older adults between 62 and 95 years.
Positive effects were reported to stabilize from the young to middle ages (15-90 years).
There is evidence that old age causes depressive symptoms. Differences in the
composition of the sample however indicate that the trajectory of age-related symptoms among
the old people remains inconclusive. Socio-emotional selectivity as well as wisdom may be the
protecting some older adults from depressive symptoms at old age.
Also, age-related changes in chronic health conditions as well as disabilities may be the
cause of the association between depressive symptoms and age. The condition used in this study,
arthritis, increases with age.
The sample used by the researcher was from data obtained from ALSA. The participants
were randomly selected from South Australian Electoral roll, which contains almost all the
citizens in Australia. A sample of 54% of 2,087 individuals over the age of 65 years were found
to have arthritis. Among the 22 chronic health conditions, these individuals who had arthritis
reported that pain was the most severe. Past research indicated that the higher the depressive
symptoms, the higher the intensity of chronic pain. In selecting the sample, individuals who had
arthritis for about 10 years were considered.

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A total of 1,477 eligible people took part in Wave 1in 1992. Among those who
participated also were the spouses to the participants as long as they were aged 65 years and
above and the correspondents who were above 70 years. All the participants resulted in a sample
of 2,087 older adults aged between 64.9 years and 103.5 years.
The measures relevant to this study were collected on five occasions since September
1992 to June 2008. The survival status of the participants was based on death as on the February
of 2012, during which 1,721 participants (82.46) were dead. Apart from survival status, more
measures included the depressive symptoms, covariates and arthritis diagnosis.
According to Rizopoulos (2012), joint modeling of longitudinal change and survival
allows the simultaneous estimation of longitudinal and survival information. Both the survival
and longitudinal sub models are treated in order to specify the joint model. For successful
examination of the association between depressive symptoms that are age related on mortality,
chronological age represented the developmental time.
In the analysis, the researcher also examined the effects of Gender, Gender times Age
interaction as well as quadratic effect of age. The above joint modelling of longitudinal as well
as survival sub models required parametric models. In this study, the commonly used
nonparametric Cox survival model could not have been used. Weibull survival model was used
because it works best for parametric models for survival functions (Therneau & Grambsch,
2000). Basically, the joint model was useful in providing the age-related trajectory of depressive
symptoms
Before the joint models of survival data and longitudinal data were fitted, the multilevel
models were tested in order to examine the functional form of longitudinal trajectory. The

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quadratic and linear effects for age, gender as well as Age X Gender interaction effects were
examined. Also, all control variables, including living arrangement, education, marital status,
illness burden and cognitive functioning were entered in this model.
The results of the best fitting model indicated that depressive symptoms increased with
age, that is, a10 = 0.09, t (2605) = 4.85, p < .001. The results of women indicated that they
reported more depressive symptoms than their men, that is, a10= 2.47, t(2023) = 4.51, p < .001.
The effects of gender and age were interpreted in the context of ‘Gender X Age’ interaction,
a11= -0.13, t(2605) = -3.90, p < .001. In order to determine the effects of gender, age and
arthritis on depressive symptoms, additional preliminary analysis were performed. Participants
with a current arthritis diagnosis indicated more depressive symptoms, that is, a20 = 0.55, z =
3.02, p < .01.
The results implied that individuals who reported more depressive symptoms may be
likely to engage in behaviors that are unhealthy and they have less support socially thereby
leading to higher mortality risks.
This study was purposed to examine age-related trajectories of depressive symptoms in
association with mortality in old and very old age, considering pathology-related changes in
order to extend and qualify the previous findings in regards to the well-being paradox in the old
age.
This study indicated that: Depressive symptoms increased from young age to old age and
from oldest age to old, in contrast to propositions of the well-being paradox. It also showed that
depressive symptom levels were associated with arthritis diagnosis, that is, there was a higher
level of depressive symptoms for individuals with arthritis than for individuals who do not have

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arthritis. The study also indicated that the level of depressive symptoms as well as the change in
depressive symptoms were associated mortality, thereby suggesting emotional functioning that
worsens as death approaches. Lastly, the study showed that the significant interaction of ‘Age X
Gender’ on depressive symptoms indicated that depressive symptoms increase with age and there
was a more pronounced increase in men than in women.
The research study suggests there is better emotional well-being in men than in women in
young to old age whereas in very old age depressive symptoms increase among men by first
reducing and later reversing the gender difference. In conclusion, the findings of this research
study suggest that changes in depressive symptoms at an old age are related to pathology, age
and mortality.
In this research study strengths and contributions lie in the study findings which are
generalized to the population concerning the required information. The research has also utilized
standardized approaches that allow it to be replicated in various areas, with time more findings
can be produced for comparisons. The findings of this research can be generalized because data
was based on random samples of sufficient size.

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References

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Barefoot, J. C., Mortensen, E. L., Helms, M. J., Avlund, K., & Schroll, M. (2001). A
longitudinal study of gender differences in depressive symp- toms from age 50
to 80. Psychology and Aging, 16, 342–345. http://dx.doi.org/10.1037/0882-
7974.16.2.342
Chui, H., Gerstorf, D., Hoppmann, C., & Luszcz, M. (2015). Trajectories of depressive
symptoms in old age: Integrating age-, pathology-, and mortality-related changes.
Psychology And Aging, 30(4), 940-951. http://dx.doi.org/10.1037/pag0000054
Rizopoulos, D. (2012). Joint models for longitudinal and time-to-event data: With
applications in R. Boca Raton, FL: Chapman and Hall/CRC.
http://dx.doi.org/10.1201/b12208
Therneau, T. M., & Grambsch, P. M. (2000). Modeling survival data: Extending the
Cox model. New York, NY: Springer. http://dx.doi.org/ 10.1007/978-1-4757-
3294-8