In this study, a model with four latent linear growth trajectory classes best captured heterogeneity in the 10-year course of young men’s depressive symptoms from early adolescence to the mid 20’s. The four classes were labeled based on the fitted mean growth curve within each group as (a) high-persistent, (b) high-decreasing, (c) moderate-decreasing, and (d) very low. Consistent with our hypothesis, this finding indicates that there may be heterogeneous subgroups of young men who follow unique trajectories of depressive symptoms from early adolescence through young adulthood. Differences among the three lowest classes in trajectory parameters seemed largely quantitative rather than qualitative. As the level of depressive symptoms over time increased across these groups, the young men showed more variability in levels of depressive symptoms, both within and across time, and more tendency for the levels of symptoms to decrease (i.e., improve). The high-persistent group, however, departed from this pattern. Although the high-persistent class did have the highest time-specific variability, the young men in this class maintained their symptom levels over time, showed no significant variability around slope (i.e., direction of change over time), and showed no association between initial level and change over time. In addition, in the high-persistent class there was a small autoregressive effect indicating some effect of depressive symptoms in the prior period on current levels of symptoms. These findings suggest that the lowest three classes differ from each other in degrees of depressive symptoms and show some recovery from early adolescent symptom levels over time. In contrast, the high-persistent class differed in a qualitative way from the other three classes; not only did they show a higher average level of depressive symptoms, but the high average level was stable over time.
A marked positive relation was found between the mean level and the variability of the depressive symptoms that departs from the standard growth curve model. It could be this feature that was largely responsible for the superior fit of the four-class model, despite the lack of qualitative differences among the three lower classes. It is also possible that psychometric properties of the CES-D partially accounted for the fact that a four-class model fit better than three- or two-class models, as floor effects, skewness, and outliers are departures from normality that can create classes (Bauer & Curran, 2003
; Muthén, 2003
). However, they were not extreme in these data. Thus, particularly given that the episodic nature of depressive symptoms is well known, the patterns found are likely to be characteristic of longitudinal differences in experiences of depressive symptoms over time, rather than a psychometric artifact of the data.
The probability of a lifetime diagnosis of depression was strongly related to latent class membership, and the high-persistent group had the highest rate. The persistently high average level of depressive symptoms for the high-persistent group and the high time-specific variance, which indicates an episodic pattern for the individuals in the group, suggests an underdiagnosis of lifetime cases at ages 25–26 years. Although it is possible that there can be relatively high symptom severity without meeting the diagnostic criteria, this could also either be due to issues with the DSM-IV diagnostic system or the CIDI interview. It is likely that at least part of the discrepancy is due to poor retrospective recall. It has been suggested that lay-administered diagnostic interviews such as the DIS or CIDI tend to underestimate prevalence rates (Eaton, Neufeld, Chen, & Cai, 2000
; Murphy, Monson, Laird, Sobol, & Leighton, 2000
). It is also possible that others in the group may meet diagnostic criteria for a depressive disorder in the future. The high-decreasing group also had a relatively high rate of diagnosis of depressive disorders, suggesting that they also deserve attention regarding prevention. Although they did decrease in symptoms levels over time, they were still at an elevated level of depressive symptoms at age 24 years, relative to the two lower groups.5
Future studies should look into the timing of onset of the diagnoses for these two elevated trajectory classes and try to map out course characteristics of symptoms before and after the onset.
One of the unexpected findings was the small proportion of the sample in the very low group (only 5.8%) and the relatively high proportion in the high-persistent group (24.2%). Typically, men are thought to have low rates of depressive symptoms compared to women, but these findings suggest that there is a substantial subgroup of young men who suffer from high rates of recurring symptoms. It could be that the prevalence of high and persistent symptoms is higher for at-risk men than for an unselected group. This is likely given that several family risk factors were associated with membership in the high-persistent trajectory group.
Another somewhat unexpected finding was that there was no adolescent onset trajectory class. This may be partly because the model was estimated over 10 years to the mid 20s rather than just over the adolescent period. In addition, variation around the intercept and slope was allowed within groups; thus, some boys with increasing patterns of symptoms were accommodated within the groups. Studies have suggested that adolescents are at greater risk for depressive symptoms as they experience multiple developmental challenges (e.g., Petersen, Sirigiani, & Kennedy, 1991
). However, adolescent onset of depressive symptoms appears to be more prevalent for adolescent girls than for boys (e.g., Cyranowski, Frank, Young, & Shear, 2000
), perhaps because girls are either more likely to be exposed to stressful environments or are more sensitive to such stressors (Compas & Wagner, 1991
; Ge et al., 1994
). It is also possible that there is a subgroup of men who develop depressive symptoms in their late 20’s or early 30’s, and the present study did not extend to this age period. As there are only a few long-term research studies that have followed men into adulthood, it is difficult to know just when men are particularly vulnerable to the development of depressive symptoms. This issue definitely warrants further investigation.
Consistent with the general hypothesis, it was found that some early risk factors predicted only class membership, some predicted only growth within class, and some predicted both. However, the hypothesis that contextual and parental risk factors would predict class membership and individual risk factors would predict change within class over time was only partially supported. Parental transitions and family income predicted only class membership and not growth within classes. Young men’s childhood antisocial behavior and paternal antisocial behavior predicted only growth within classes. Academic achievement, parental depressive symptoms, childhood depressive symptoms, and negative life events predicted class membership and growth within classes. It is possible that paternal antisocial behavior and parents’ depressive symptoms are closely related to interpersonal contexts within which parents’ psychopathology influences their children through poor parenting and poor interactional skills. In addition, poor academic skills, early onset of depressive symptoms, and the experience of multiple negative life events in childhood appear to exert strong influence on the longitudinal course of depressive symptoms for all of the trajectory groups.
In general, risk factors from childhood predicted initial status positively and slope negatively, indicating that the young men showed some recovery over time from the effects of these risk factors, perhaps either due to distance in time from the risk factor (e.g., negative life events), an improvement in the level of the risk factors, or due to decreased exposure to the risk factor. For example, it is normative for youth to spend less time with parents as they mature; thus, parental risk factors may become less influential. Risk factors in childhood may also become less salient with age. Boys who experienced depressive symptoms due to poor academic achievement may later experience success in a manual job that does not require those skills. The only significant exception to the pattern of prediction from risk factors to higher levels of initial status and to some recovery over time was that childhood depressive symptoms predicted some increase over time for the very low class.
An important finding of the study is that four of the significant predictors of depressive trajectory membership uniquely discriminated the high-persistent group from the other three groups, including parental transitions, childhood academic achievement problems, parents’ depressive symptoms, and negative life events. On the other hand, family income and childhood depressive symptoms primarily discriminated the very low from the high-persistent group. Most notably, these two predictors failed to discriminate the moderate-decreasing and the high-decreasing group from the high-persistent group. Thus, the class prediction results strongly support a qualitative distinction between the high-persistent group and the other three trajectory groups. The findings also suggest that the very low class may be qualitatively different from the other classes, although the small size of the very low group, the modest significance levels of the effects, and the lack of qualitative differences in the trajectories themselves make this a tentative finding. These findings strongly suggest that mechanisms related to the development of such symptoms should be understood with respect to different lifetime trajectories.
Results for the multivariate prediction models indicated that only three predictors uniquely contributed to class discrimination, namely parents’ depressive symptoms, negative life events, and childhood depressive symptoms. The former two uniquely discriminated the high-persistent class from the other three classes, but the latter discriminated the high-persistent from the very low class and the moderate-decreasing class only. The latter two factors also predicted initial status or change within classes. The effects of childhood depressive symptoms on slope interacted with latent class, such that it positively and significantly predicted growth for the low group but negatively and significantly predicted growth in the other three classes. Although many studies have consistently indicated strong associations of these factors with the continuity of depressive symptoms in young adulthood (Harrington, Rutter, & Fombonne,1996
), most of the studies were based on a variable-centered approach and consequently were unable to address differential vulnerability to risk factors for individuals with different depressive trajectories. The unique aspect of the present study is that findings showed more specific prediction effects associated with the development of depressive symptoms in young men.
The nature of the mechanism through which parents’ depressive symptoms, men’s childhood depressive symptoms, and negative life events operate to predict trajectory membership and longitudinal changes within each trajectory remain unclear. Parental depressive symptoms are known as significant risk factors for their children’s longer-term vulnerability to high levels of similar symptoms (e.g., Downey & Coyne, 1990
). However, to what extent this effect is due to direct genetic effects, to direct learning, or to some mediated effect, such as through a poor parent-child relationship, cannot be answered from our study. Replication and extension of the findings of the present study to samples representative of populations with differing characteristics is necessary. Given the nature of the present sample (i.e., at-risk for antisocial behavior), generalizability of the findings might be limited. Using the CES-D, Garrison et al. (1990)
reported mean levels of 11.66 through 13.98 for White male high school students. The overall mean levels of the present sample over the 10 years (from 7.71. to 11.33) are somewhat lower than that of Garrison et al’s. However, few studies have examined depressive symptoms of adolescent males through young adulthood, therefore, it is difficult to evaluate the present findings with respect to other studies in terms of relative levels of depressive symptoms over an extended time. Furthermore, it is likely that the number and pattern of depressive trajectories identified in the study were limited because of the relatively small sample size, although Sampson, Laub, and Eggleston (2004)
found that estimates of the number of classes tended to stabilize at an N
of around 200. Future studies should try to extend to culturally and ethnically diverse samples as well as to women. In addition, the depressive trajectory in the present study started at ages 14-15 years and did not include childhood, an important period for the development of depressive symptoms. Extension to younger ages would provide a more complete picture of the developmental course of men’s depressive symptoms. Future studies are also encouraged to use a variety of different measures of depressive symptoms.
The present study did not test any specific theory regarding the associations of stress to depressive symptoms. However, findings from our study can be used to refine the extant theories. It is possible to test different diathesis-stress models for different subgroups. Some of the diatheses could be unique to some groups, some could be common across two or more subgroups, and the same could be true for the stressors. Such an effort can also help clinicians to identify individuals at different levels of risk and accordingly to develop treatment programs. Lastly, the study did not include any time-varying covariates, such as negative life events or social support. Certainly early risk factors cannot fully explain the longitudinal course of men’s depressive symptoms. It is possible that the youths’ subsequent experiences during adolescence and young adulthood are uniquely related to trajectory membership and growth within each group. Proximal time-varying factors would enhance our understandings of the developmental courses of depressive symptoms.
It is possible that some of the parental influences on the men’s depressive symptoms could have been underestimated because of the way the parental predictors were constructed in this study. Indicators for parents’ depressive symptoms were taken from a self-reported measure of depressive symptoms (e.g., CES-D) assessed at three waves rather than from lifetime diagnostic interviews. Therefore, the actual level of parental depressive symptoms and its association with the men’s depressive symptoms may have been underestimated.
Despite these limitations, this study is the first, to our knowledge, to study diverse longitudinal trajectories of depressive symptoms and to examine childhood risk factors predicting the class membership as well as within class development. Harrington and colleagues (Harrington et al., 1996
) called for a need to examine whether there are subgroups of individuals that have particularly strong continuities into adulthood. However, because of the lack of efforts to differentiate distinctive depressive trajectories, particularly for men, little is known about prototypical subgroups of individuals with similar trajectories. The present study represents a potentially important first step toward identification of subgroups of individuals who follow similar trajectories of depressive symptoms. The fact that there are multiple depressive trajectory subgroups and that different factors are related to the trajectory membership and growth within each class calls for the need to further refine our theories as well as treatment programs. Researchers and clinicians should be aware of the possibility that individuals with depressive symptoms are developmentally heterogeneous. Ignoring this issue could obscure important differences among individuals, which then can render ineffective design of prevention or intervention programs. It is our belief that findings from the study provide interesting insight for future study that can improve the current knowledge on the long-term depressive trajectories. An important next step includes the examination of differential outcomes for each trajectory.