Depression is more than feeling blue and transitorily losing the capacity to experience pleasure. Depression syndromes are highly prevalent in later life, and last longer than in other periods of life. Almost one in three older people may show clinical levels of depressive symptoms in the UK. Clinically relevant depression symptom episodes in old age are related to devastating consequences (e.g., increased risk of mortality, higher disability, reduced quality of life), even from earliest stages (e.g., subclinical conditions). Little is known about the relationship between symptom course and health-related outcomes. The search for person-specific symptom trajectories may help identify at-risk profiles, thus uncovering potential targets for treatment.

Many factors deserve consideration when depression course being studied. Sex constitutes a biological condition highly connected with depression symptom manifestation. Why do women fall into depression more frequently than men? Probably this is due to sexually-mediated biological processes (e.g., estradiol releasing patterns) and social influence that may put women at higher risk for developing depression problems. Moreover, women often show more heightened courses of depression symptoms over time. Unfortunately, little is known about the sex-specific trajectories of depression symptoms and their related impact on daily living, health and quality of life.

This study aimed at depicting the longitudinal trajectories of depression symptoms in older men and women, with a special interest in identifying heterogeneous trajectories of symptoms. Moreover, we intended to uncover the sociodemographic and health-related profile that featured each symptom trajectory. Finally, we were interested in examining how symptom trajectories may predict health-related outcomes two years later (i.e., quality of life, satisfaction with life and daily living functioning).

To do so, we used data from the English Longitudinal Study of Ageing (ELSA). The ELSA constitutes an excellent cohort study on ageing, relied on surveying British older adults every two years since 2002. The study aims at collecting information across multiple domains (socioeconomic, environmental, health-related, etc.). More concretely, data from 8317 older adults (46.02% men), aged between 65-90 years, were used in our study. None of these participants showed dementia diagnosis and responded by themselves the ELSA survey across waves.

Depressive symptoms were assessed over an 8-year follow-up (from 2002-2010, across five waves), by means of the Center for Epidemiologic Studies Depression Scale, 8-item version (CES-D 8). Moreover, information on time-varying (self-reported health across waves, amount of morbid conditions, feelings of loneliness, sensory function course) and time invariant depression concomitants (education level, household income, history of psychiatric problems in adulthood and age of retirement) were collected.

The identification of sex-specific symptom trajectories relied on robust structural equation modelling. Also, the relationships between symptom trajectory membership and concomitants were examined. Finally, generalised linear regression was used to examine how symptom trajectory membership may predict health-related outcomes at wave 6 (2012). The CASP-19 (the composite score) was used to measure quality of life. The instrument works quite well in old population and shows adequate psychometric properties. More concretely, we found satisfactory reliability levels within our sample (Cronbach’s α = .89).

As a result, we uncovered three heterogeneous trajectories of depression symptoms in men and women. For both sexes, we identified a low-symptom trajectory class (covering more than 77% of men and 68% of women, respectively), with minimal symptom levels over time; a subclinical-symptom trajectory (over 17% of men and 21% of women, respectively), featured by increasing levels of symptoms, that surpassed the cut-off point of clinical meaningfulness over time; and a chronic-symptom trajectory (6% of men and 11% of women), featured by heightened levels of symptoms over time. Sex-related differences were revealed in terms of higher proportion of women showing subclinical and chronic-symptom trajectories in comparison to men. For both sexes, the chronic-symptom trajectory was associated with increasing course of hearing difficulties and the history of psychiatric problems. The subclinical-symptom trajectory was featured by a higher increase in visual difficulties over time. Also, some sex-specific relationships were found: higher amount of morbid conditions in women with subclinical-symptom trajectory; and higher multimorbidity and loneliness feelings in men with chronic-symptom trajectory.

Finally, trajectory class predicted the health-related outcomes in the follow-up. More concretely, individuals with a chronic-symptom trajectory showed the lowest levels of quality of life and satisfaction with life, and the highest levels of disability. Surprisingly, individuals showing a subclinical-symptom trajectory also manifested poorer health-related outcomes than individuals in the normative trajectory class.

Our study constitutes a flexible, but robust approach to study depression symptom dynamics over time and its concomitants. We aimed at providing some evidence to raise awareness of personalised medicine (by means of identifying person-specific trajectories) and its usefulness in geriatric sciences. Moreover, we would like to highlight that depression should be tackled even from its earliest states (subclinical symptom trajectories also showed decreased quality of life) in order to tackle its devastating impact.

Manuscript published in: De la Torre-luque A, De la Fuente J, Prina M, Sanchez-Niubo A, Haro JM, Ayuso-Mateos JL. Long-term trajectories of depressive symptoms in old age: Relationships with sociodemographic and health-related factors. J Affect Disord. 2019;246(November 2018):329-337. doi:10.1016/j.jad.2018.12.122

Guest blog by Alejandro de la Torre Luque, Centre for Biomedical Research in Mental Health (CIBERSAM), Department of Psychiatry. Universidad Autonoma de Madrid, Spain: alejandro.delatorre@uam.es