Symptoms burden of long COVID on the individual with pre-existing depression: A longitudinal cohort study

doi:10.21203/rs.3.rs-5294140/v1

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Symptoms burden of long COVID on the individual with pre-existing depression: A longitudinal cohort study

https://doi.org/10.21203/rs.3.rs-5294140/v1

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Background

Mental health is receiving increasing attention in the field of long COVID. This study aims to compare the differences in long COVID symptoms between individuals with pre-existing depression and those without and assess the impact of pre-existing depression on the risk of long COVID and on the number of symptoms.

Methods

Data were from the Survey of Health, Ageing and Retirement in Europe (SHARE), participants aged 50 and older. Pre-existing depression was assessed by the EURO-D scale (October 2019-March 2020). Long COVID symptoms were reported by participants (June/August 2020 - June/August 2021). We compared the differences in long COVID symptoms among individuals with pre-existing depression and those without pre-existing depression with the Chi-squared test. P values from all tests were corrected using the Holm-Bonferroni correction. A multilevel (random intercept) hurdle negative binomial model was employed to assess the impact of pre-existing depression on the risk of long COVID and the number of symptoms and to explore effect modification by age, gender, and physical diseases.

Results

Of the 2063 participants who contracted COVID-19 (mean [SD] age, 68.0[8.5] years; 1259(61%) women. A higher number of individuals with pre-existing depression reported headache (32.2% vs 25.9%; P value = 0.027), body aches/joint pain (38.5% vs 29.4%; P value < 0.001), and confusion(10.6% vs 7.6%;P value < 0.01) than those without pre-existing depression. Pre-existing depression did not have a statistically significant impact on the risk of long COVID (adjusted OR = 1.00; 95% CI = 0.78–1.26). Among individuals reporting long COVID symptoms, Pre-existing depression was significantly related to the number of symptoms associated with long COVID (adjusted RR = 1.16; 95% CI = 1.07–1.25). The effect of pre-existing depression on the number of symptoms is moderated by the comorbid physical conditions.

Conclusions

This suggests a complex interplay between pre-existing depression and physical health, highlighting the importance of considering mental health factors in the management of long COVID patients.

Depression

COVID-19

Older adults

Long-term impacts

Long COVID, also referred to as post-COVID-19 condition, has emerged as a significant public health concern. According to the World Health Organization (WHO), long COVID occurs in individuals with a history of probable or confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, usually three months after the onset of COVID-19, with symptoms lasting at least two months and not attributable to an alternative diagnosis[1]. It is estimated that at least 10% of those infected with SARS-CoV-2 experience long COVID, presenting over 200 symptoms and impacting multiple organ systems[2]. Common symptoms include fatigue, headache, body aches/ joint pain, confusion, and generally impact everyday functioning[3–10].

Pre-existing mental disorders have become significant contributors to the global health burden. Depression is one of the most prevalent mental disorders, affecting approximately 3.8% of the global population before the pandemic[11]. Depression is associated with inflammation and immune dysregulation, potentially increasing the risk of developing long COVID after contracting COVID-19[10, 12–14].

Previous research has suggested that pre-existing depression is likely linked to certain long COVID symptoms, including chronic fatigue and persistent brain fog[12, 15]. It implies that individuals with pre-existing depression may experience different long COVID symptoms from those without pre-existing depression. Individuals with pre-existing depression also may experience a higher burden of symptoms after contracting COVID-19. However, this topic is still lacking in the current research regarding long COVID[16].

In this study, we aimed compare the differences in long COVID symptoms between individuals with and without pre-existing depression. We also assess the impact of pre-existing depression on the risk of long COVID and the number of symptoms experienced. Furthermore, we also explore effect modification by age, gender and physical diseases. By focusing on this specific population, we seek to clarify the role of pre-existing depression in the long COVID, contributing valuable insights to the ongoing discourse surrounding post-COVID-19 condition and mental health.

Study design and participants

We analyzed a unique panel database, the Survey of Health, Ageing and Retirement in Europe (SHARE), which serves as a valuable resource for studying the health and socio-economic implications of the pandemic on individuals aged 50 and older[17]. The survey data across countries was collected with a standardised sampling design and survey questionnaire.

We constructed a new cohort using Wave 8 of the SHARE study (conducted from October 2019 to March 2020) and the SHARE Corona Survey (June to August 2021). This cohort includes participants from the baseline survey of Wave 8, which measured depression, as well as participants aged 50 and older who took part in the SHARE Corona Survey in 2021, totaling 32,003 participants. Among them, 2,579 individuals had experienced COVID-19 infection. Of these, 130 (5.04%) had incomplete primary information. Ultimately, our study includes a final sample of 2,449 participants with complete data., of which 1611 had a positive test for the SARS-CoV-2 virus and 452 experienced symptoms that they attributed to the COVID-19 illness but were not tested. Further details can be found in Supplementary Figure S1.

This report follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guidelines[18].

Measurement of depression

In this study, participants with depression were defined as having a depression symptom score above established cut-off points, which were assessed with the EURO-D mental health scale. It determines the presence of negative affect and somatic symptoms on a scale from 0 (the lowest level of depression) to 12 (the highest), which covers 12 items (depression, pessimism, wishing death, guilt, sleep, interest, irritability, appetite, fatigue, concentration, enjoyment, and tearfulness).

Clinically significant depression is defined as an EURO-D score of 4 or higher, based on validation work conducted among older adults.

We employed the recommended thresholds(EURO-D scored ≥ 4) to identify participants with depression. The measurement of the EURO-D scores was conducted before the outbreak of the pandemic (October 2019 to March 2020). Although the EURO-D score does not provide a definitive diagnosis of depression such as in the DSM-IV or ICD-10, this cut-off score shows good predictive performance.

Long COVID

Participants were asked whether they had experienced any long-term or lingering effects that they attributed to their COVID-19 illness. They were presented with a list of nine symptoms, including fatigue, cough, congestion, shortness of breath, loss of taste or smell, headache, body aches/joint pain, chest or abdominal pain, diarrhea, nausea, confusion, or any other symptoms.

To quantify the extent of symptoms, a count variable was created ranging from 0 (indicating no symptoms) to 9 (representing the maximum number of symptoms). Participants were considered to have long COVID, if they reported one or more of these symptoms during the 12-month follow-up after COVID-19 infection (from June/August 2020 to June/August 2021).

Covariates

Covariates in this study included sociodemographic indicators (gender, age, level of education, living arrangement, work situation, and economic status), body mass index (BMI, mass in kg divided by square of height in meters), smoking history, seven chronic conditions (history of heart attack, high blood pressure or hypertension, stroke or cerebral vascular disease, diabetes or high blood sugar, chronic lung disease, cancer, and chronic kidney disease), and number of chronic conditions. All covariates were collected during Wave 8 of the SHARE (fielded in October 2019-March 2020) or SHARE Corona Survey 1 (June-August 2020)

Gender was measured as a dichotomous variable indicating male or female, and age was classified into two groups (50–79 years and ≥ 80 years). Education level was categorised into three groups according to the International Standard Classification of Education 1997: low education (ISCED-97 levels 0–2), medium education (ISCED-97 levels 3–4), and high education (ISCED-97 levels 5–6). Living arrangements are measured by whether an individual lives with a partner or spouse. Work situations encompassed two groups before the pandemic (not employed VS employed). Economic status was assessed as a binary variable and included two categories: difficulty making ends meet and easily making ends meet at the outbreak of the pandemic (October 2019 to March 2020). BMI was categorised into two groups (< 30 and ≥ 30). Smoking history refers to participants who had a record of smoking cigarettes, cigars, cigarillos, or a pipe daily for at least one year. Chronic conditions were diagnosed by medical doctors or specialists and reported by self or proxy- participants on follow-up questionnaires.

Statistical analyses

Descriptive data for baseline characteristics of participants are presented as mean (standard deviations, SD) values or frequencies (percentage), as appropriate. Chi-squared test used to compare the baseline characteristics. We compared the frequencies and proportions of 9 long COVID symptoms between participants with pre-existing depression and those without pre-existing depression with Chi-squared test. The significance level was a priori at P < 0.05, with P values from all tests being corrected using the Holm-Bonferroni correction[19].

A multilevel (random intercept) hurdle negative binomial model was employed to assessed the impact of pre-existing depression on the risk of long COVID and on the number of symptoms. Among all participants, the average number of symptoms is 2.25, with a variance of 4.32, which implies that the count data is excessively discrete (variance greater than the mean), subject to the assumption of a negative binomial distribution. Country variance was used as a random effect in the model to capture potential differences.

The model is structured in two parts: the zero part estimates the probability of an individual reporting zero symptoms. In contrast, the count part is the count of occurrences given that the event has occurred [20, 21]. In our study, the event refers to long COVID symptoms.

Further, to explore effect modification[22] by age, gender and number of physical diseases, the effect of pre-existing depression was assessed in subgroups of age (50–69, 70+), gender (man, women) and number of physical diseases (< 2, 2+).

Adjusted rate ratios (aOR) with 95% CIs for the risk of long COVID and adjusted rate ratios (aRR) with 95% CIs for the level of symptoms were calculated in the binary model and the count model, respectively.

A multilevel (random intercept) hurdle negative binomial model was conducted using the “mixed_model” function in the GLMMadaptive package in R (version 4.3.2)[23]. All P values were from 2-sided tests and results were deemed statistically significant at P < 0.05.

Of the 2063 participants who contracted COVID-19 (mean [SD] age, 68.0[8.5] years), 1259(61%) women, and 603 (29.2%) had a pre-existing depression (Table 1).

Table 1

Descriptive statistics for study participants
Characters	Participants, No. (%)/ mean (SD)			P value
Characters	All Participants	Without depression	With depression	P value
All	2063	1460 (70.8)	603 (29.2)
Female	1259 (61%)	821 (56.2%)	438 (72.6%)	< 0.0001
Age, mean (SD), years	68.0(8.5)	67.5 (8.1)	69.1 (9.3)	< 0.0001
Living with a partner or spouse(ca8)	1442 (69.9%)	1066 (73%)	376 (62.4%)	< 0.0001
Level of education				< 0.0001
Low	577 (28%)	365 (25%)	212 (35.2%)
Mid	1040 (50.4%)	755 (51.7%)	285 (47.3%)
High	446 (21.6%)	340 (23.3%)	106 (17.6%)
Economic status(ca8)				< 0.0001
Easily	1314 (63.7%)	987 (67.6%)	327 (54.2%)
Difficulty	749 (36.3%)	473 (32.4%)	276 (45.8%)
Employed(ca8)	596 (28.9%)	456 (31.2%)	140 (23.2%)	0.0003
BMI (≥ 30)	639 (31%)	443 (30.3%)	196 (32.5%)	0.36
Smoking history	781 (37.9%)	556 (38.1%)	225 (37.3%)	0.78
N of physical disease				< 0.0001
< 2	928(44.98%)	730(50.0%)	198(32.8%)
2+	1135(55.02%)	730 (50%)	405 (67.2%)

The proportion of females was higher among participants with pre-existing depression than among participants without pre-existing depression (72.6% vs 56.2%; P < 0.0001). Participants with pre-existing depression were older than those without (mean [SD], 69.1 [9.3] vs 67.5 [8.1] years; P < 0.0001) and had a higher number of physical diseases (mean [SD], 2.5 [SD = 1.8] vs 1.7 [SD = 1.5]; P < 0.0001). In addition, a greater proportion of participants with pre-existing depression than those without pre-existing depression included those without living with a partner or spouse, lower levels of education, more difficult family economic situations, and unemployed status (Table 1).

The most frequent symptoms among all participants were followed by fatigue (50.4%), cough/congestion/shortness of breath (36.5%), and body aches/joint pain (32.0%).

A higher number of individuals with pre-existing depression reported headache (32.2% vs 25.9%; P value = 0.027), body aches/joint pain (38.5% vs 29.4%; P value < 0.001), and confusion(10.6% vs 7.6%;P value < 0.01) than those without pre-existing depression (Fig. 1).

Pre-existing depression did not have a statistically significant impact on the risk of long COVID (at least one long COVID symptom) (adjusted OR = 1.00; 95% CI = 0.78–1.26), after adjusting for sociodemographic characteristics, BMI, smoking, and number of physical diseases (Table 2).

Table 2

Zero symptoms and average of symptoms for participants, n = 2063
	Zero symptoms, n (%)			P	_adjOR (95%CI)	Average symptoms	P	_adjRR (95%CI)
	0	1		P	_adjOR (95%CI)	Average symptoms	P	_adjRR (95%CI)
All	557(27.0%)	1506(73.0%)				3.08
Depression
No	404 (27.7%)	1056 (72.3%)	Ref		1	2.98	Ref	1
Yes	153 (25.4%)	450 (74.6%)	0.97		0.98(0.77, 1.24)	3.33	0.0005	1.16(1.07, 1.26)
Gender
Man	245 (30.5%)	559 (69.5%)	Ref		1	3.04	Ref	1
Female	312 (24.8%)	947 (75.2%)	0.032		0.79(0.64, 0.99)	3.10	0.54	0.99(0.91, 1.08)
Age group
50–69	345 (27.3%)	921 (72.7%)	Ref		1	3.20	Ref	1
70+	212 (26.6%)	585 (73.4%)	0.32		1.01(0.79, 1.29)	2.89	< 0.0001	0.85(0.78, 0.93)
N of physical disease
< 2	308 (30.5%)	620 (69.5%)	Ref			2.98	Ref
2+	249 (21.9%)	886 (78.1%)	< 0.0001		0.60(0.48, 0.75)	3.15	0.33	1.04(0.96, 1.13)

Furthermore, among individuals reporting long COVID symptoms, individuals with pre-existing depression reported a greater number of long COVID symptoms compared to those without pre-existing (3.33 vs 2.98). Pre-existing depression was significantly related to the number of symptoms associated with long COVID, after adjusting for sociodemographic characteristics, BMI, smoking, and number of physical diseases (adjusted RR = 1.16; 95% CI = 1.07–1.25) (Table 2).

Table 3 represents the result of the assessment of effect modification by age, gender, and number of physical diseases in a stratified analysis. the effect of pre-existing depression was consistent in the subgroup of age (50–69, 70+) and gender (man, female). Pre-existing depression was significantly related to the number of symptoms associated with long COVID in two and more than two physical disease groups (adjusted RR = 1.19; 95% CI = 1.07–1.31), but not in less than two physical disease groups (adjusted RR = 1.09; 95% CI = 0.95, 1.26).

Table 3

The effect modification by age, gender, and number of physical diseases
	0 symptom		Average symptoms
	P	OR (95%CI)	P	RR (95%CI)
Gender
Man	0.26	1.17(0.87, 1.56)	0.031	1.18(1.02, 1.37)
Female	0.32	0.79(0.51, 1.20)	0.005	1.15(1.04, 1.27)
Age group
50–69	0.81	0.96(0.70, 1.32)	0.05	1.11(1.00, 1.23)
70+	0.46	1.16(0.79,1.69)	0.006	1.21(1.06, 1.39)
N of physical disease
< 2	0.38	0.85(0.58, 1.23)	0.21	1.09(0.95, 1.26)
2+	0.45	1.13(0.82, 1.56)	0.0009	1.19(1.07, 1.31)

In this study, we compare the differences in long COVID symptoms between individuals with pre-existing depression and those without and assess the effect of pre-existing depression on the risk of long COVID and on the number of symptoms. A higher number of individuals with pre-existing depression reported headache, body aches/joint pain, and confusion than those without pre-existing depression. Pre-existing depression did not have a statistically significant impact on the risk of long COVID. Among individuals reporting long COVID symptoms, individuals with pre-existing depression had a 16% increased risk of experiencing an additional symptom. The effect of pre-existing depression on the number of symptoms is moderated by the number of physical diseases.

We identified headache, body aches/joint pain, and confusion were significantly more prevalent among individuals with pre-existing depression than those without pre-existing depression. Depression is associated with a complex interplay between chronic pain and inflammatory processes[24], which may also explain the observation of increased symptoms of headaches or body aches/joint pain in individuals with depression. People may develop confusion (a kind of symptom of brain fog) after a COVID-19 infection[15]. Previous evidence showed depression as the strongest predictor of persistent brain fog at 1-year follow-up in patients who contracted COVID-19[15]. A systematic review also suggested that previous psychiatric diagnoses were risk factors for the development of psychiatric symptoms in patients with long COVID[25].

We did not find pre-existing depression has a statistically significant impact on the risk of long COVID compared to those without pre-existing depression. That is to say, individuals who contracted COVID-19 might have a similar risk of long COVID, regardless of depression status. Yet, some previous studies suggested that pre-existing depression was associated with the risk of long COVID (at least had long COVID symptoms)[12, 14].

Among individuals reporting long COVID symptoms, we found that pre-existing depression was associated with a 16% increased risk of experiencing an additional symptom. In line with a prospective study based on predominantly female cohorts, which also revealed that individuals with probable depression reported a greater number of symptoms of long COVID (mean [SD] symptoms = 3.4 [2.1] VS no depression, mean [SD] symptoms = 2.5 [1.7])[10].

We also found the effect of pre-existing depression on the number of symptoms is moderated by the number of physical diseases. Individuals with pre-existing depression with two and more than two physical diseases are likely to have a higher number of symptoms than those with less than two physical diseases. Previous study suggested that multimorbidity was associated with a higher number of symptoms[26]. The question of whether this increase in risk is distributed uniformly across individuals remains an area of investigation. Our study addresses this research gap, revealing that the risk is more pronounced in populations with a history of depression.

First, this study has inherent limitations due to its observational design, which means that it can only establish associations but not causation. Although efforts were made to control for confounding factors, there may still be residual confounding that could influence the observed relationships between variables. Second, the data used in this study relied on self-reported information, which introduces the possibility of recall bias and misclassification. Finally, depression was measured using a validated scale among older adults rather than clinical diagnoses, while this scale has been widely used and validated in previous research.

The study indicated that individuals with pre-existing depression experienced more frequent symptoms including headache, body aches/joint pain, and confusion, and have a higher disease burden of long COVID when infected with COVID-19. The effect of pre-existing depression on the number of symptoms also is moderated by the comorbid physical conditions. This suggests a complex interplay between pre-existing depression and physical health, highlighting the importance of considering mental health factors in the management of long COVID patients.

COVID-19: Coronavirus disease 2019

SARS-CoV-2: Severe acute respiratory syndrome coronavirus

BMI: Body mass index

ARR: Adjusted risk ratio

AOR: Adjusted odds ratio

CIs: Confidence intervals

Acknowledgments

None.

Author Contributions

WG acquired funding for this study. WG conceived the research idea, designed and supervised the study. XH conducted the literature search and performed data collection, management, and analysis. XH drafted the manuscript. WG directed the study and critically revised the manuscript. All authors had full access to all the data in the study and verified the data. WG had final responsibility for the decision to submit for publication.

Funding

This work was supported by the Senior Talent Startup Fund of Nanchang University. The funding source did not influence data collection, study design, or interpretation of findings.

Data Availability

This study used publicly available longitudinal survey data from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Ethics approval and consent to participate

The SHARE project is subject to continuous ethics reviewed by both the primary ethics committees (University of Mannheim and Max Planck Society, Germany) and national ethics committees in the participating countries. The reviews covered all aspects of the project, including study design and the informed consent. The reviews confirmed the project to be compliant with the relevant legal norms and that the project and its procedures agree with international ethical standards. The owner of the SHARE study is the “Survey of Health, Ageing and Retirement in Europe – European Research Infrastructure Consortium (SHARE-ERIC)”. After registration, individuals with a scientific background may use the data within the framework of 'scientific-use files.' The secondary analysis conducted here did not require further ethical approval. More information about the ethical approval can be found on the SHARE project webpage [http://www.share-project.org/].

Clinical trial number

Not applicable.

Consent for publication

Not applicable.

Competing interests

All the authors had no any personal, financial, commercial, or academic conflicts of interest separately.

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No competing interests reported.

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Symptoms burden of long COVID on the individual with pre-existing depression: A longitudinal cohort study

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Background

Data and Methods

Study design and participants

Measurement of depression

Long COVID

Covariates

Statistical analyses

Results

Discussion

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Conclusions

Abbreviations

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