Impact of pre-existing subclinical depressive symptoms on the mental health of older adults during the COVID-19-related confinements.

doi:10.21203/rs.3.rs-5157163/v1

The COVID-19 pandemic significantly challenged mental health of populations worldwide. We aimed to assess changes in mental health of cognitively unimpaired (CU) older adults with pre-existing subclinical depressive symptoms during pandemic-related confinements, and the factors that could modulate these changes. CU older adults with (DepS, n=53) and without (NoDepS, n=47) pre-existing subclinical depressive symptoms (defined using the Geriatric Depression Scale at baseline) from the Age-Well randomized controlled trial (NCT02977819) were included – for whom data at baseline, post-intervention visits and during the two national confinements were available. The 18-month meditation or non-native language training intervention was completed before the pandemic. DepS, compared to NoDepS, had higher levels of depressive and anxiety symptoms at all assessments, including confinements. DepS had a greater increase in anxiety than NoDepS between the two confinements, and this increase was associated with greater ruminative brooding at baseline, but was not moderated by meditation practice. Pre-existing subclinical depressive symptoms in older adults contribute to mental health deterioration during confinements, with rumination being the main factor involved – stressing the need to treat these symptoms.

Psychiatry

Depressive symptoms

Anxiety symptoms

Older adults

COVID-19 pandemic

Meditation

The COVID-19 pandemic has required the implementation of unprecedented confinement and social/physical distancing measures, which have significantly affected societies, especially their mental health and well-being^1,2. Older adults were at greater risk for severe complications after COVID-19 infection, and thus were more exposed to virus-related stressors and more likely to be isolated¹. Despite this vulnerability, early reports showed that anxiety and depressive symptoms were less prevalent in older adults than in younger adults during the pandemic^3–6 – although a significant increase in these symptoms was also reported in older adults^5,7,8. Focusing research on this specific population is all the more relevant as the increase in psychoaffective symptoms, even at a subclinical level, as well as the living conditions to which they were exposed (i.e., social isolation, reduced physical and cognitive activity), are known to have major consequences in older adulthood, such as an increased risk of comorbidities, clinical anxiety and depressive disorders, cognitive decline and dementia^9–18. Moreover, in a previous study, we showed in two independent samples that cognitively unimpaired (CU) older adults with subclinical depressive symptoms had lower brain integrity, including hippocampal atrophy¹⁹ – strengthening the need to consider subclinical depressive symptoms as relevant in older adults, and even more in the context of the COVID-19 pandemic. Individuals with a pre-existing clinical depressive disorder have been found to be at greater risk of mental health deterioration during the confinements^20–23; however, little is known about those with a subclinical level of depressive symptoms. In this context, it seems crucial to better characterize older adults who could be most vulnerable to mental health deterioration during the confinements, and the underlying mechanisms, in order to promote appropriate care/intervention for these individuals if similar situations recur. Among non-pharmacological interventions, mental training through meditation practice^24,25 – targeting emotional and attentional regulation and stress reduction – might notably address this need.

Our goal was to assess changes in mental health across the COVID-19-related confinements in CU older adults with pre-existing subclinical depressive symptoms, compared to those without pre-existing symptoms. We also aimed to investigate the underlying psychological mechanisms (i.e., ruminative brooding and/or worry) that may predict mental health deterioration. Finally, we also evaluated whether an 18-month meditation intervention completed before the pandemic – compared to active and passive control groups – moderated the mental health changes between participants with and without pre-existing depressive symptoms during the pandemic confinements. We hypothesized that CU older adults with pre-existing subclinical depressive symptoms would have lower psychoaffective health (i.e., higher depressive and anxiety symptoms) – compared to those without pre-existing symptoms – across the pandemic confinements, and that this poorer mental health could be associated with negative psychological processes (i.e., ruminative brooding and/or worry) and moderated by meditation practice before the pandemic.

Participants and study design

We included CU older adults from the Age-Well randomized controlled trial of the Medit-Ageing European project, sponsored by the French National Institute of Health and Medical Research (INSERM). The design of the trial has been fully described elsewhere^26,27. Participants were recruited from the general population. Main eligibility criteria included being: a native French speaker, aged at least 65 years, retired for at least one year, educated for at least 7 years and showing performance within the normal range for their age and educational level on standardized cognitive tests (see Tables 1 and 2 in the Age-Well protocol paper²⁶ for details). Participants had no evidence of a major neurological or psychiatric disorder, chronic disease or acute unstable illness, history of cerebrovascular disease, and no current or recent medication that may interfere with cognitive functioning (including antidepressants and anxiolytics). Notably, the absence of major depression was assessed using a clinician-administered questionnaire, the Montgomery-Åsberg Depression Rating Scale (MADRS)²⁸, with a cut-off value of 6 (participants with MADRS > 6 were excluded). All participants provided written informed consent prior to the examinations, and the Age-Well randomized clinical trial was approved by the ethics committee (Comité de Protection des Personnes Nord-Ouest III, Caen, France; trial registration number: EudraCT: 2016-002441-36; date of first registration: 30/11/2016; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819).

Table 1

**Participants’ characteristics and between-group comparisons for each visit.**
Age-Well Cohort (n = 100)	NoDepS Group (n = 47)	DepS Group (n = 53)	Between-group comparisons
Age-Well Cohort (n = 100)	NoDepS Group (n = 47)	DepS Group (n = 53)	p-value	T, F or χ² value	Mean difference [95% CI]
Baseline
Demographic data
Sex, Female, n (%)	23 (49)	36 (68)	0.09^a	2.97
Age, years (Range)	70.26 ± 4.20 (65–84)	68.34 ± 3.02 (65–77)	0.01^b	-2.64	-1.92 [-3.36 to -0.48]
Education, years (Range)	13.28 ± 3.08 (7–22)	13.32 ± 3.03 (7–20)	0.94^b	0.07	0.04 [-1.17 to 1.26]
Global cognition
MMSE (Range)	29.06 ± 0.92 (26–30)	29.13 ± 1.14 (26–30)	0.75^b	0.33	0.07 [-0.35 to 0.48]
Psychoaffective variables
GDS (Range)	0.00 ± 0.00 (0–0)	2.23 ± 1.87 (1–11)	NA
STAI-A (Range)	26.21 ± 4.92 (20–42)	29.19 ± 6.12 (20–46)	0.013^c	6.36	2.95 [0.63 to 5.27]
Psychological processes
RRS brooding (Range)	7.53 ± 2.01 (5–15)	8.83 ± 2.52 (5–16)	0.014^c	6.23	1.22 [0.25 to 2.18]
PSWQ (Range)	38.85 ± 10.20 (20–58)	45.08 ± 12.75 (24–70)	0.019^c	5.65	5.82 [0.96 to 10.69]
Post-intervention
Psychoaffective variables
GDS (Range)	1.00 ± 1.23 (0–4)	2.28 ± 2.03 (0–8)	< 0.001^c	12.05	1.28 [0.55 to 2.01]
STAI-A (Range)	26.49 ± 6.36 (20–51)	30.13 ± 6.78 (20–53)	0.011^c	6.75	3.67 [0.87 to 6.48]
Confinement 1
Psychoaffective variables
DASS Depression (Range)	2.36 ± 3.10 (0–12)	4.87 ± 5.46 (0–25)	0.008^c	7.37	2.65 [0.71 to 4.59]
STAI-A (Range)	32.32 ± 7.65 (20–54)	37.23 ± 10.52 (20–67)	0.026^c	5.09	4.53 [0.54 to 8.52]
Confinement 2
Psychoaffective variables
DASS Depression (Range)	3.68 ± 5.33 (0–20)	7.42 ± 7.36 (0–35)	0.013^c	6.37	3.51 [0.75 to 6.26]
STAI-A (Range)	32.55 ± 10.24 (20–61)	40.38 ± 11.44 (20–64)	0.002^c	10.41	7.56 [2.91 to 12.21]
Data are presented as mean ± standard deviation of participants, unless otherwise indicated. Between-group differences were assessed using ^a χ² tests for categorical variables, ^b Student’s t-tests or ^c ANCOVA adjusted for age, sex and education (as well as intervention group for post-intervention and confinements time points) for continuous variables. Values in bold correspond to significant p-values (p < 0.05) and values in italic correspond to trends (0.05 < p < 0.1). N, Sample size; NoDepS, Group without pre-existing subclinical depressive symptoms; DepS, Group with pre-existing subclinical depressive symptoms; MMSE, Mini-Mental State Examination; GDS, Geriatric Depression Scale; STAI-A, State-Trait Anxiety Inventory form Y-A; DASS Depression, Depression Anxiety and Stress Scale – Depression subscale; RRS brooding, Rumination Response Scale – Brooding subscale; PSWQ, Penn State Worry Questionnaire; NA, Not applicable.

Table 2

**Post-hoc statistical summary of the changes in anxiety and depressive symptoms within the groups across time points and between groups for each time point.**
	Within-group changes across time points			Between-group comparisons for each time point	Overall Interaction effect
	NoDepS	DepS		DepS versus NoDepS	Time x Group
	Estimate (SE) P	Estimate (SE) P		Estimate (SE) P	P
Anxiety symptoms (STAI-A)					0.024
Baseline to Post-intervention	0.40 (1.26) 0.989	0.98 (1.20) 0.845	Baseline	2.92 (1.71) 0.090
Baseline to C1	6.25 (1.33) < .0001	8.10 (1.26) < .0001	Post-intervention	3.51 (1.71) 0.042
Baseline to C2	6.49 (1.38) < .0001	11.25 (1.31) < .0001	C1	4.76 (1.72) 0.006
Post-intervention to C1	5.86 (1.23) < .0001	7.11 (1.16) < .0001	C2	7.68 (1.72) < .0001
Post-intervention to C2	6.10 (1.26) < .0001	10.27 (1.19) < .0001
C1 to C2	0.24 (1.23) 0.997	3.16 (1.16) 0.035
Depressive symptoms (DASS Depression)					0.201
C1 to C2	1.33 (0.71) 0.063	2.56 (0.67) 0.0002	C1	2.50 (1.17) 0.035
			C2	3.74 (1.18) 0.002
Linear mixed-effect models were adjusted for age, sex, education and intervention group, with a statistical significance set to p < 0.05. Post-hoc analyses comparing the estimated marginal means were adjusted for multiple comparisons. For within-group changes, positive estimate values represent an increase in anxiety and/or depressive symptoms across time. For between-group comparisons, positive estimate values represent higher anxiety and/or depressive symptoms in the DepS group compared to the NoDepS group for each time points. Values in bold correspond to significant p-values (p < 0.05) and values in italic correspond to trends (0.05 < p < 0.1). NoDepS, Group without pre-existing subclinical depressive symptoms; DepS, Group with pre-existing subclinical depressive symptoms; P, p-value; SE, Standard Error; STAI-A, State-Trait Anxiety Inventory form Y-A; DASS Depression, Depression Anxiety and Stress Scale – Depression subscale; C1, Confinement 1; C2, Confinement 2.

Out of 157 participants who attended a screening visit, 137 were randomly assigned to three groups: one group with a meditation training (intervention group), one group with a structurally matched non-native language training (English learning = active control group), and one group with no intervention (passive control group). The 18-month intervention period started just after randomization, and participants had a post-intervention visit at the end of the intervention^26,27. Two participants were excluded from all secondary analyses by the Trial Steering Committee for not meeting eligibility criteria (i.e., history of head trauma and amyotrophic lateral sclerosis diagnosis during the intervention period [with a likely subclinical state at inclusion]). One non-study related death (i.e., myocardial infarction) was reported during the intervention period before the post-intervention visit (data not included), and one participant revealed to have not followed their allocated arm (randomized to no intervention but attended non-native language training, he was therefore analyzed within the non-native language training arm). Baseline, interventions and post-intervention visits were all completed before the COVID-19 pandemic (between 22th November 2016 and 6th February 2020).

Participants then completed the COVID-19 follow-up assessments, which corresponded to the first (C1, from 17th March to 11th May 2020, date for sending out online questionnaires: 22th April 2020) and the second (C2, from 30th October to 15th December 2020, date for sending out online questionnaires: 23th November 2020) national confinement periods that occurred in France during the pandemic. Thirty-four participants who did not complete the first and/or second confinement assessments were excluded from our analyses. A total of 100 participants were therefore included (See Fig. 1 for the detailed inclusion process).

Assessment of subclinical depressive symptoms and classification of participants at baseline

In this study, we were specifically interested in the presence of pre-existing subclinical depressive symptoms before the onset of the COVID-19 pandemic – which was assessed using the 15-item version of the Geriatric Depression Scale (GDS) during the Age-Well baseline visit. This self-reported binary response questionnaire ranges from 0 to 15, with a higher score indicating more depressive symptoms^29,30. As in our previous study¹⁹, we split participants into having subclinical depressive symptoms (DepS; GDS > 0, n = 53) or not (NoDepS; GDS = 0, n = 47) based on GDS scores at baseline. Of note, the GDS was also administered at the post-intervention visit, but not at the COVID-19 follow-up assessments.

Assessment of psychoaffective health across time

Depressive symptoms during pandemic-related confinements

During the confinements, self-reported depressive symptoms were obtained from the full 42-item Depression Anxiety and Stress Scale (DASS)³¹, with scores from the 14-item depression subscale (scores range from 0 to 42). Each item is rated on a 4-point Likert-type scale, ranging from 0 (Did not apply to me at all - Never) to 3 (Applied to me very much, or most of the time – Almost always). Higher scores indicate greater depressive symptoms. This scale was not administered at baseline, nor post-intervention.

Anxiety symptoms before and during pandemic-related confinements

For all assessments, self-reported state anxiety symptoms were obtained from the 20-item Spielberger State-Trait Anxiety Inventory form Y-A (STAI-A) (scores range from 20 to 80)³². Each item is rated on a 4-point Likert-type scale, ranging from 1 (No) to 4 (Yes), to indicate the extent to which the respondent felt that way at the time of the evaluation. Higher scores indicate greater anxiety symptoms. At baseline and post-intervention follow-up visits, we used the mean of the STAI-A scores reported before the magnetic resonance imaging (MRI) examinations (n = 2) and during the first neuropsychological session.

Assessment of negative psychological processes at baseline

Ruminative brooding

Self-reported ruminative brooding (i.e., repetitive passive and judgmental thoughts about one’s mood) was obtained from the 5-item brooding subscale (scores range from 5 to 20) of the 22-item Rumination Response Scale (RRS)³³. Each item is rated on a 4-point Likert-type scale, ranging from 1 (almost never) to 4 (almost always). Higher scores indicate greater ruminative brooding. One participant had no available data for this questionnaire.

Worry

Self-reported worry was obtained from the 16-item Penn State Worry Questionnaire (PSWQ) (scores range from 16 to 80)³⁴. Each item is rated on a 5-point Likert-type scale, ranging from 1 (Very typical of me) to 5 (Not at all typical of me). Higher scores indicate greater worry.

Statistical analyses

Between-group comparisons at baseline, post-intervention and COVID-19 follow-up assessments

Group differences between participants with and without pre-existing subclinical depressive symptoms for demographic and global cognitive functioning at baseline were assessed using Student’s t-tests for continuous variables and χ² tests for categorical variables, with statistical significance set to p < 0.05. Between-group differences in depressive and anxiety symptoms at each time-point, as well as baseline differences in ruminative brooding and worry, were assessed using analyses of covariance (ANCOVA) corrected for age, sex and education, as well as intervention group for post-intervention and confinement assessments, with statistical significance set to p < 0.05.

Impact of COVID-19 confinements on psychoaffective health of participants with and without pre-existing subclinical depressive symptoms: longitudinal analyses

Longitudinal data were analyzed using linear mixed-effect models (with the lme4 package³⁵ in RStudio version 1.4.1106) to evaluate the change in depressive and anxiety symptoms across assessments between participants with and without pre-existing subclinical depressive symptoms.

As depressive symptoms were not assessed with the DASS scale before the confinements, only the impact of the confinement repetition (i.e., no comparison with pre-COVID-19 scores) on depressive symptoms between participants with and without pre-existing depressive symptoms was assessed.

Longitudinal models included all main effects, as well as the interaction between Time (categorical variable, i.e., C1 and C2 for depressive symptoms or Baseline, Post-intervention, C1 and C2 for anxiety symptoms) and Group of participants (categorical variable, i.e., DepS versus NoDepS) and were adjusted for age, sex, education and intervention group (i.e., meditation training, non-native language training and no intervention). Post-hoc analyses comparing the estimated marginal means using the emmeans package³⁶ in RStudio were adjusted for multiple comparisons. The significance level was set at p < 0.05 for all statistical analyses.

Participants’ characteristics at baseline and post-intervention follow-up visits

Demographic data, cognitive performance and psychoaffective variables for each group, as well as between-group differences, are reported in Table 1.

Participants with subclinical depressive symptoms were younger and tended to have a higher proportion of women compared to participants without symptoms. The two groups did not differ in any other demographic or cognitive variables.

Participants with subclinical depressive symptoms at baseline had higher anxiety, ruminative brooding and worry levels compared to participants without subclinical depressive symptoms. At the post-intervention follow-up visit, participants with pre-existing subclinical depressive symptoms had higher depressive and anxiety symptoms compared to those without pre-existing symptoms (Table 1).

Between-group differences in psychoaffective variables during confinements

Participants with pre-existing subclinical depressive symptoms had higher anxiety and depressive symptoms during the first and the second confinement compared to those without pre-existing subclinical depressive symptoms (Table 1).

Longitudinal analyses

Firstly, we found a main effect of Time (all time points considered) and Group (DepS versus NoDepS) on anxiety symptoms (p < 0.001 and p = 0.005, respectively), as well as an interaction between Time and Group (p = 0.024) (Fig. 2 and Table 2). Post-hoc analyses showed that higher anxiety symptoms were observed during the confinements (C1 and C2) compared to the baseline and post-intervention visits (all between-time points comparisons, p < 0.0001) regardless of the group of participants (DepS versus NoDepS). Moreover, the DepS group reported higher anxiety symptoms at all time points compared to the NoDepS group, except at baseline where only a trend was observed in this model (Baseline, p = 0.090; post-intervention, p = 0.042; C1, p = 0.006; C2, p < 0.0001). Lastly, anxiety symptoms increased in the second confinement (C2) compared to the first confinement (C1) in the DepS group (p = 0.035) but not in the NoDepS group (p = 0.997).

Secondly, we found a main effect of Time (C1 versus C2) and Group (DepS versus NoDepS) on depressive symptoms (p = 0.0001 and p = 0.033, respectively), with no interaction between Time and Group (p = 0.201) (Fig. 3 and Table 2). Post-hoc analyses showed that higher depressive symptoms were observed during the second confinement (C2) compared to the first one (C1) in the DepS group (p = 0.0002) and tended to be higher in the NoDepS group (0.063). Moreover, the DepS group had higher depressive symptoms than the NoDepS group in the first and the second confinement (p = 0.035 and p = 0.002, respectively).

Complementary analyses: factors associated with greater anxiety increase from confinement 1 to confinement 2 in participants with pre-existing subclinical depressive symptoms

As we found that the increase in anxiety symptoms from the first to the second confinement was higher in the DepS than in the NoDepS group, we performed additional analyses to assess i) whether we could identify pre-existing negative psychological processes (i.e., ruminative brooding and/or worry) that would be associated with this disproportionate anxiety increase; and ii) whether the meditation training intervention completed before the pandemic (in the context of the Age-Well randomized control trial) moderated this effect. For these analyses, the change in anxiety symptoms between the first and the second confinement was expressed as a percentage increase and was calculated as follows: [((C2 score – C1 score) / C1 score) x100].

Multiple linear regression models were performed to assess the association between the percentage increase in anxiety symptoms between the first and the second confinements and both baseline ruminative brooding and worry in the DepS group – adjusted for age, sex, education and intervention group.

An ANCOVA was performed to assess the effect of the intervention group (completed before the COVID-19 pandemic) on the change in anxiety symptoms in the DepS group (Meditation training, n = 23; Non-native language training, n = 15 and No intervention, n = 15) – adjusted for age, sex and education.

In the DepS group, we found that higher baseline ruminative brooding was positively associated with the percentage increase in anxiety symptoms between the first and the second confinement (β = 3.772 p = 0.001) (Fig. 4). Worry at baseline was not associated with this increase in anxiety symptoms with confinement repetition in the DepS group (β = 0.326 p = 0.189).

In the DepS group, no significant main effect of the intervention group was observed regarding the change in anxiety symptoms with confinement repetition (F = 2.298 p = 0.112) (Fig. 5).

This study showed that CU older adults with pre-existing subclinical depressive symptoms had lower mental health during the COVID-19-related confinements, with higher levels of depressive and anxiety symptoms. More specifically, anxiety symptoms increased with confinement repetition only in participants with pre-exiting subclinical depressive symptoms, and this increase was associated with higher levels of ruminative brooding at baseline. Finally, meditation training before the pandemic did not moderate the change in anxiety symptoms over the pandemic confinements.

The higher level of anxiety in older adults with subclinical depressive symptoms compared to those without depressive symptoms, both before and during the pandemic, is consistent with studies showing that anxiety symptoms are frequently observed in patients with late-life depression^37,38. Moreover, the pandemic had an effect on anxiety symptoms in all individuals, but those with pre-existing subclinical depressive symptoms were more affected by its duration – since their anxiety symptoms increased with the repetition of confinements. This result could reflect the fact that these individuals tended to dwell on past negative events (e.g. of the first confinement), which amplified their anxiety during the second confinement. These results indicate that older adults with pre-existing subclinical depressive symptoms were less resilient to the multiple stressors experienced during the pandemic compared to individuals without pre-existing symptoms – consistent with what has been previously reported in clinical mental disorders^20–23. Older adults with subclinical depressive symptoms thus represent a population highly vulnerable to mental health deterioration. As the presence of depressive symptoms, even at subclinical levels, could have deleterious consequences in older adults (i.e., increased risk of clinical depressive disorder, comorbidity including anxiety symptoms, mortality and dementia)^9–14,39, there is a need to monitor and treat these depressive symptoms in this population.

Ruminative brooding was associated with increased anxiety symptoms from the first to the second confinement, making it an important psychological process to target through mental health interventions in individuals at risk of depression. Higher levels of ruminative brooding were already present in individuals with subclinical depressive symptoms at baseline, which is consistent with previous works highlighting that rumination is frequently experienced by patients with clinical depressive disorder and is thought to play a role in the depressive symptomatology⁴⁰. Indeed, higher levels of rumination have been linked to the onset, severity and duration of depressive episodes, as well as an increased risk of relapse in depressive patients in remission^40–42. Interestingly, the brain substrates of subclinical depressive symptoms identified in our previous study¹⁹ involved regions of the default mode network (DMN) (i.e., the precuneus/cingulate posterior, medial prefrontal and temporoparietal cortex and the hippocampus), which is also associated with rumination processes^43,44. Changes in this network’s activation and functional connectivity have been observed in late-life depression and are thought to be associated with a dysregulation of mental content in favor of negative thoughts and ruminations⁴⁵.

In young and middle-aged adults, meditation-based interventions have been shown to reduce depressive and anxiety symptoms in individuals with^46–48 or without^49,50 mental disorders – making it a promising practice for improving mental health. While preliminary research in older adults showed encouraging results indicating a similar impact of meditation on psychoaffective symptoms^24,51–56, the results need to be confirmed as the studies are scarce and had limitations (i.e., small sample size, short duration of intervention, lack of active and/or passive control groups). Although our study addressed some of these limitations, the 18-month meditation intervention that was completed before the pandemic did not mitigate the pandemic’s impact on the anxiety symptoms of these older adults. Given that only 23 participants with subclinical depressive symptoms underwent the meditation training, the sample may have been too small to detect an effect, or that it would have been necessary to maintain meditation practice in a more formal way during confinement (e.g., guided lessons with an instructor) to really benefit from its effects. In addition, our population was enriched with healthy, highly educated and very active participants, which may also limit the potential for intervention-related improvements in mental health. Further investigations are needed to better understand whether and how psychological interventions could moderate the influence of major stressors, such as the pandemic and the associated confinement, on mental health in older adults.

The main strength of the study was to provide a greater insight on mental health during the COVID-19 pandemic and its determinants in a well-characterized sample of CU older adults with and without subclinical depressive symptoms. Repeated longitudinal assessments allowed us to follow the evolution of mental health before and during the pandemic, as well as to evaluate the effect of baseline psychological processes and meditation practice via a randomized controlled trial design. However, the use of self-report questionnaires for assessing psychoaffective factors is a limitation; as it is subjective, the measure could be biased by demand characteristics, awareness and introspective ability. Yet, we previously found a link between subclinical depressive symptoms assessed using the same questionnaire (GDS; with the same cut-off value used to split participants) and neurodegeneration biomarkers, both in our sample and in a completely independent sample (ADNI), which suggests that this measure is relatively reliable¹⁹. Furthermore, the fact that depressive symptoms were not evaluated with the same questionnaire before and during the confinements prevented us from assessing the direct impact of confinements on depressive symptoms.

Overall, our study highlights that CU older adults with subclinical depressive symptoms were particularly vulnerable to the mental health effects of the COVID-19 pandemic and its repeated confinements. More particularly, pre-existing subclinical depressive symptoms were associated with lower mental health during the COVID-19-related confinements, including higher levels of depressive and anxiety symptoms, and an increase in anxiety symptoms with the repetition of confinements. This increase was associated with higher ruminative brooding at baseline but was not moderated by meditation training before the pandemic. Future planning to manage mental health in older adults with subclinical depressive symptoms, especially during stressful events such as the pandemic, needs prioritization and could involve interventions targeting these psychoaffective factors and their determinants to limit their negative consequences.

Availability of data and materials

Data and code are made available on request following a formal data sharing agreement and approval by the consortium and executive committee (https://silversantestudy.eu/2020/09/25/data-sharing). The Material can be mobilized, under the conditions and modalities defined in the Medit-Ageing Charter by any research team belonging to an Academic, for carrying out a scientific research project relating to the scientific theme of mental health and well-being in older people. The Material may also be mobilized by non-academic third parties, under conditions, in particular financial, which will be established by separate agreement between Inserm and by the said third party. Data sharing policies described in the Medit-Ageing charter are in compliance with our ethics approval and guidelines from our funding body.

Data statement

The data has been presented orally at the GREPACO conference (May 22-23, 2023, Louvain-la-Neuve, Belgium).

Author contributions

Dr Chételat had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: ET, NLM, GC. Acquisition, analysis, or interpretation of data: ET, JG, LP, MD, OH, FM, SF, DV, VDLS, GP, NLM, GC. Drafting of the manuscript: ET. Critical revision of the manuscript for important intellectual content: ET, JG, LP, MD, OH, FM, SF, DV, VDLS, GP, NLM, GC. Statistical analysis: ET. Obtained funding: ET, GP, NLM, GC. Administrative, technical, or material support: FM, SV, DV, GP. Supervision: NLM, GC. Other–Principal investigators: GC, VDLS (MD, principal investigator).

Acknowledgments

We acknowledge A. Cognet, V. Le Franc, C. Gaubert, G. Le Du, MSc, T. Jorand, M. Botton, MSc, A. Joret Philippe, MSc, S. Egret, MSc, P. Lacheray, MSc, J. Lebahar, PhD, C. Tomadesso, PhD, I. Moulinet, PhD, S. Réhel, PhD, H. Espérou, MD, PhD, E. Frison, MD, PhD, and the Cyceron MRI-PET staff members for their help with recruitment and data acquisition or administrative support. We also acknowledge the Euclid team, the sponsor (INSERM) and all the participants of the study for their contribution.

Fundings

The Age-Well randomized clinical trial is part of the Medit-Ageing project and is funded through the European Union’s Horizon 2020 Research and Innovation Program (grant 667696), Institut National de la Santé et de la Recherche Médicale, Région Normandie, and Fondation MMA des Entrepreneurs du Futur.

Disclosures

Dr Touron reported grants from French Ministry of Higher Education and Research (PhD grant). Dr Gonneaud was supported by a Young Researcher Grant from the Fondation Alzheimer and Fondation de France. Dr Poisnel, Dr Marchant and Dr Chételat reported grants from European Union’s Horizon 2020 Research and Innovation Program under grant agreement No 667696 during the conduct of the study. Dr Chételat reported grants, personal fees and nonfinancial support from Institut National de la Santé et de la Recherche Médicale (INSERM); personal fees from Fondation Entrepreneurs MMA, grants and personal fees from Fondation Alzheimer, grants from Région Normandie, grants from Fondation Recherche Alzheimer, grants from Association France Alzheimer, outside the submitted work. No other disclosures were reported.

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The authors declare potential competing interests as follows: Dr Touron reported grants from French Ministry of Higher Education and Research (PhD grant). Dr Gonneaud was supported by a Young Researcher Grant from the Fondation Alzheimer and Fondation de France. Dr Poisnel, Dr Marchant and Dr Chételat reported grants from European Union’s Horizon 2020 Research and Innovation Program under grant agreement No 667696 during the conduct of the study. Dr Chételat reported grants, personal fees and nonfinancial support from Institut National de la Santé et de la Recherche Médicale (INSERM); personal fees from Fondation Entrepreneurs MMA, grants and personal fees from Fondation Alzheimer, grants from Région Normandie, grants from Fondation Recherche Alzheimer, grants from Association France Alzheimer, outside the submitted work. No other disclosures were reported.

Impact of pre-existing subclinical depressive symptoms on the mental health of older adults during the COVID-19-related confinements.

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Abstract

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Introduction

Materials and methods