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The longitudinal course of late-life depression remains under-studied.
Aims
To describe transitions along the depression continuum in old age and to identify factors associated with specific transition patterns.
Method
We analysed 15-year longitudinal data on 2745 dementia-free persons aged 60+ from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression (minor and major) was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; subsyndromal depression (SSD) was operationalised as the presence of ≥2 symptoms without depression. Multistate survival models were used to map depression transitions, including death, and to examine the association of psychosocial (social network, connection and support), lifestyle (smoking, alcohol consumption and physical activity) and clinical (somatic disease count) factors with transition patterns.
Results
Over the follow-up, 19.1% had ≥1 transitions across depressive states, while 6.5% had ≥2. Each additional somatic disease was associated with a higher hazard of progression from no depression (No Dep) to SSD (hazard ratio 1.09; 1.07–1.10) and depression (Dep) (hazard ratio 1.06; 1.04–1.08), but also with a lower recovery (HRSSD−No Dep 0.95; 0.93–0.97 [where ‘HR’ refers to ‘hazard ratio’]; HRDep−No Dep 0.96; 0.93–0.99). Physical activity was associated with an increased hazard of recovery to no depression from SSD (hazard ratio 1.49; 1.28–1.73) and depression (hazard ratio 1.20; 1.00–1.44), while a richer social network was associated with both higher recovery from (HRSSD−No Dep 1.44; 1.26–1.66; HRDep−No Dep 1.51; 1.34–1.71) and lower progression hazards to a worse depressive state (HRNo Dep−SSD 0.81; 0.70–0.94; HRNo Dep−Dep 0.58; 0.46–0.73; HRSSD−Dep 0.66; 0.44–0.98).
Conclusions
Older people may present with heterogeneous depressive trajectories. Targeting the accumulation of somatic diseases and enhancing social interactions may be appropriate for both depression prevention and burden reduction, while promoting physical activity may primarily benefit recovery from depressive disorders.
Co-occurring somatic diseases exhibit complex clinical profiles, which can differentially impact the development of late-life depression. Within a community-based cohort, we aimed to explore the association between somatic disease burden, both in terms of the number of diseases and their patterns, and the incidence of depression in older people.
Methods
We analysed longitudinal data of depression- and dementia-free individuals aged 60+ years from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression diagnoses were clinically ascertained following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision over a 15-year follow-up. Somatic disease burden was assessed at baseline through a comprehensive list of chronic diseases obtained by combining information from clinical examinations, medication reviews and national registers and operationalized as (i) disease count and (ii) patterns of co-occurring diseases from latent class analysis. The association of somatic disease burden with depression incidence was investigated using Cox models, accounting for sociodemographic, lifestyle and clinical factors.
Results
The analytical sample comprised 2904 people (mean age, 73.2 [standard deviation (SD), 10.5]; female, 63.1%). Over the follow-up (mean length, 9.6 years [SD, 4 years]), 225 depression cases were detected. Each additional disease was associated with the occurrence of any depression in a dose–response manner (hazard ratio [HR], 1.16; 95% confidence interval [CI]: 1.08, 1.24). As for disease patterns, individuals presenting with sensory/anaemia (HR, 1.91; 95% CI: 1.03, 3.53), thyroid/musculoskeletal (HR, 1.90; 95% CI: 1.06, 3.39) and cardiometabolic (HR, 2.77; 95% CI: 1.40, 5.46) patterns exhibited with higher depression hazards, compared to those without 2+ diseases (multimorbidity). In the subsample of multimorbid individuals (85%), only the cardiometabolic pattern remained associated with a higher depression hazard compared to the unspecific pattern (HR, 1.71; 95% CI: 1.02, 2.84).
Conclusions
Both number and patterns of co-occurring somatic diseases are associated with an increased risk of late-life depression. Mental health should be closely monitored among older adults with high somatic burden, especially if affected by cardiometabolic multimorbidity.
Rapid societal changes occurred during the course of the 20th century. Previous literature has found an increase in depression over time for younger and middle- aged populations. Among older adults, the prevalence of major depression has been found to be stable over time, while for the milder forms, the findings are limited by the largely non-representative nature of analyzed samples. Given the dramatic secular changes in several factors linked to old-age depression, a careful examination of depressive symptom burden and prevalence of depression in representative cohorts of similarly-aged older adults separated in time is required.
Methods:
We will analyze data on 2,041 older adults from the Swedish National Study on Aging and Care in Kungsholmen. Separate individuals, aged 60 and 81 years were assessed with a Comprehensive Psychopathological Rating Scale (CPRS) during detailed clinical examinations, separated in time by 15 years (2001 vs. 2016). Information on 21 depressive symptoms, is subsequently combined into diagnoses of major depression (presence of at least one core symptom [low mood and/or loss of interest], and at least five out of the nine symptoms); minor depression (presence of at least one core symptom, and two to four symptoms in total), and subsyndromal depression (presence of at least two symptoms in the absence of any other depression diagnoses). Psychosocial (loneliness, bereavement), behavioral (alcohol consumption, smoking), and functional factors (impairments in activities of daily living) are used as potential explanatory factors for any observed cohort differences in symptom burden or prevalence of depression.
Results:
For the 60-year old age-group, comparison of symptom burden and diagnostic status will be done across 739 participants assessed in 2001 and 677 people assessed in 2013. For the 81-year old age- group, comparisons will involve 236 people assessed in 2001, 194 people assessed in 2010, and 195 people assessed in 2016.
Conclusion:
Preliminary results are expected by March, once data entry and cleaning are completed. We hypothesize that the burden of depressive symptoms and the prevalence of depression will be lower in later born cohorts and that explanatory factors may account for some of the cohort effect.
Social health (SH) markers, including marital status, contact frequency, network size, and social support, have been linked with increased cognitive capability. However, the underlying mechanisms remain poorly understood. We aim to investigate whether depression symptoms and inflammatory biomarkers mediate associations between SH and cognitive outcomes.
Methods:
We used data from waves 1-9 of the English Longitudinal Study of Ageing, involving 7,136 participants aged 50 or older at baseline. First, we examined associations between SH (wave 1) and depression and inflammatory biomarkers (C-reactive protein (CRP) and fibrinogen) (wave 2) using linear regression models. Second, we tested associations between a) SH and b) depression and inflammation with subsequent standardised verbal fluency and memory in wave 3 and change between waves 3-9, indexed using slopes derived from multilevel models. We adjusted for age, sex, socio-economic position, cardiovascular disease, basic and instrumental activities of daily living, health behaviours, and baseline depression symptoms and cognition. We will also conduct causal mediation analysis.
Results:
All SH markers, except contact frequency, were associated with lower subsequent depression, but not inflammatory biomarkers. Greater contact frequency (e.g. once-twice a week vs <once per year: β=0.18 [0.01, 0.36]) and less negative support (β=0.02 [0.00, 0.03]) were associated with higher verbal fluency. Larger network size (>6 people vs none: β=0.007SD/year [0.001, 0.012]), less negative (β=0.001SD/year [0.001, 0.002]) and more positive support (β=0.001SD/year [0.000, 0.001]) were linked with slower memory decline, and more positive support predicted slower verbal fluency decline (β=0.001SD/year [0.000, 0.001]). Depression symptoms were associated with lower memory and verbal fluency, and faster memory decline (β=-0.001SD/year [-0.001, -0.000]) and verbal fluency (β=-0.001SD/year [-0.001, -0.000]). CRP was associated with lower verbal fluency (β=-0.02 [-0.04, 0.00]), whereas fibrinogen was linked with faster memory decline (β=-0.001SD/year [-0.003, -0.000]).
Conclusion:
Depression symptoms and SH showed associations with subsequent cognitive capability and change. SH was linked with lower depression, but not inflammatory biomarkers. Findings highlight the potential for depression to underpin associations between SH and cognition, a pathway which we will test using causal mediation analysis. We will also examine whether findings replicate in the Swedish National Study of Aging and Care in Kungsholmen.
Individual differences in the timing of dementia have been attributed to cognitive reserve (CR), thought to reflect lifelong engagement in stimulating experiences, which provide resilience against brain pathology. In older adults, dementia and depression are closely related, and some studies have linked CR with depression risk in old age. It is unclear if different ways of operationalizing CR exhibit similar association with old-age depression. We examined the association of two measures of CR with depressive burden in older adults: activity-based CR, capturing engagement in stimulating activities using proxy variables, and residual-based CR, indicating residual variance in cognition, not explained by the brain status.
Methods:
We used data on 354 adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen, followed for 15 years. Residual-based reserve was computed from a regression predicting episodic memory with a brain-integrity index incorporating six structural neuroimaging markers (white- matter hyperintensities volume, whole-brain gray matter volume, hippocampal volume, lateral ventricular volume, lacunes, and perivascular spaces), age, and sex. Activity-based reserve incorporated education, work complexity, social network, and leisure activities. Depressive burden was captured over the follow- up with the Montgomery-Åsberg Depression Rating Scale and time until clinically relevant level of symptoms (>6) was modelled using Cox proportional hazard models.
Results:
Preliminary results indicate that, upon minimal adjustment (age, sex, brain integrity status), top tertiles (ref: bottom tertile) of both activity-based (HR: 0.77; 95% CI: 0.61-0.98) and residual-based CR (HR: 0.62; 95% CI: 0.44-0.98) were associated with a lower risk of depressive burden onset over 15 years. Upon further adjustment for anthropometrics, health behaviors, and chronic disease burden, the association of activity-based CR was attenuated, whereas residual-based CR preserved its effect on depressive burden (HR [fully adjusted model]: 0.59; 95% CI: 0.40-0.88). Next steps include evaluating the ability of reserve measures to attenuate the association of brain integrity with depressive burden using interaction analysis.
Conclusion:
Preliminary findings suggest that CR may be linked with depression development in older adults, although the association may vary depending on measurement of reserve. Association of activity- based reserve may be attributed to somatic disease pathways.
Depression evolves dynamically in old age. Studies of natural history of major depression in older adults suggest that 19–34% recover, 27%–32% remain chronically ill, and approximately 40% experience a fluctuating course. Another way of approaching depression from a longitudinal point of view is by adopting a symptom-based approach, that in addition to the evolution of clinically manifested diagnostic entities, also focuses on transitions involving subclinical/subsyndromal states, although few studies have attempted it. We examined psychosocial, behavioral, and clinical determinants of transitions across states that include no depression, subsyndromal-, and clinical depression.
Methods:
We used data on 3086 adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen, followed for 15 years. Markov-state transition models were used to capture transition patterns, as well as their associated determinants. Death and dropout constituted absorbing states. Depression was diagnosed in accordance with DSM-5; SSD was based on having at least 2 symptoms in the absence of DSM diagnosis. Determinants of transition patterns included index of social connections and support (i.e., psychosocial determinants); smoking, alcohol consumption, and physical activity (behavioral determinants); somatic disease burden and history of depression (clinical determinants).
Results:
At baseline, 10% of the study population exhibited clinically relevant levels of depressive symptoms. Over a 15-year period, a total of 11,489 transitions were observed. Preliminary results indicate that behavioral factors (primarily smoking) were mostly associated with transitions from no depression to clinical depression, as well as from clinical depression to death. Mostly the same pattern was seen for clinical determinants, although higher burden of chronic diseases and previous depression also increased the likelihood of transition from no depression to SSD. Notably, of high baseline values of social connection and support were found to: 1) lower the likelihood of transitioning from no depression to either SSD or clinical depression; 2) lower the likelihood of transitioning from SSD to clinical depression; and 3) increase the likelihood of transitioning from clinical depression to no depression.
Conclusion:
Clinical and behavioral factors are mostly implicated in lowering the occurrence of depression, whereas psychosocial factors may also be implicated in recovery.
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