Major Depression before and during the Covid-19 pandemic – a population-based study among Swedish adults

doi:10.21203/rs.3.rs-2190150/v1

Purpose: To determine and compare the prevalence of depression and depressive symptoms in 2010 and 2021 in an adult population living in Stockholm at start of participation, Sweden, and study the possible impact of the Covid-19 pandemic.

Methods: Data were used from 2010 (n=6,641) and 2021 (n=8,863) based on a longitudinal population-based study with the aim to study risk and protective factors for mental health. Self-reported depression was assessed using Major Depression Inventory and in 2021 questions on effects of the Covid-19 pandemic were added. Prevalence was calculated and presented with 95% confidence intervals.

Results: Depression and depressive symptoms had increased in 2021 compared with 2010. The highest prevalence was found in women and in the youngest age-group. There was no difference after adjusting for Covid-19 infection in any of the age-groups. Women who experienced life changes related to the pandemic situation had higher rates of depression as well as those who lost their job during the pandemic.

Conclusion: During the Covid-19 pandemic, it seems both depression and depressive symptoms become more common. However, we did not find support for a direct effect related to a Covid-19 infection but our results suggest that part of the increase may be due to secondary social and economic consequences of the pandemic.

Depression

Depressive symptoms

Prevalence

Covid-19

population-based study

Many well-known risk factors for depression increase during a pandemic, both due to actual infections and to imposed restrictions of everyday life. Postinfectious reactions, financial insecurity, job stress and decreased social network are amongst them. These stressors, and the degree they affect people, are most likely different in different countries, groups, and individuals.

Many studies, including several systematic reviews and meta-analyses, have recently been published showing an increased rate of depressive symptoms, as well as depression, during the Covid-19 pandemic. The pooled prevalence of depression has varied greatly between studies; from 16 to 45%. The highest rate was found in a meta-analysis only including patients (n = 5,153) suffering from Covid-19, the lowest were reported in a study mixing many different study samples (n = 189,159) [1, 2]. A systematic review and meta-analysis including 68 cross-sectional studies (n = 288,830) from 19 countries, reported a higher risk among women. Other associated factors were younger age, living in rural areas and having lower socio-economic status. However, a substantial heterogeneity for most of the associations were found [3].

In general, most of the studies are from China most likely since the outbreak started there. Additionally, most of the studies used the Patient Health Questionnaire (PHQ-9) as measure of depressive symptoms and depression diagnosis was defined using cut-off scores. Most of the studies focus on direct effects of Covid-19 infection on the individuals but there are also studies of the effects of the lockdowns. A meta-analysis including 25 studies (n = 72,004) specifically focusing on the effects of lockdowns reported that the psychological impact was small in magnitude and highly heterogeneous, suggesting nonuniform detrimental effects on mental health and that most people were psychologically resilient [4].

Concerning the effects of how the stringency of lockdowns affects the prevalence of depressive symptoms a meta-analysis reported that the prevalence of clinically significant depressive symptoms was significantly lower in countries where governments implemented stringent (the Oxford COVID-19 Government Response Index) policies more promptly [5]. However, again here most of the included studies were from China. There were two included Swedish studies, one which included only elite athletes [6] and the other one was a cross-sectional study (n = 1,212) of persons recruited online using PHQ-9 as depression measure showing a prevalence of 30%. There were no gender differences, and poor self-rated health, and previous history of mental health problems were associated with depression [7].

In summary, several studies have been done showing high rates of depression during the pandemic. However, most of the studies have been limited to PHQ-9 and to a Chinese context. Since a validation of PHQ-9 using a structured clinical interview in a primary care population revealed that a PHQ-9 score of 10 or higher had good sensitivity but poor specificity in detecting major depression [8].

Diagnosis of depression according to DSM-5 is made assessing the presence of five out of nine symptoms and either sadness or loss of interest are mandatory to fulfill the criteria. Previous studies are also silent regarding if specific depressive symptoms have increased. Restrictions imposed on daily life might for example increase sleeping problems and restlessness due to reduced possibilities for physical activity or fear of infection.

The present study used Major Depression Inventory (MDI) to determine the rates of depression and depressive symptoms in an adult population living in Stockholm, Sweden, at the time of recruitment, in 2021 comparing with similar data from 2010.

Data was based on a longitudinal population-based study of mental health, work, and relations: PART (In Swedish: Psykisk hälsa, Arbete och RelaTioner), among adult people living in the Stockholm County, Sweden at time of inclusion. So far four waves (w) have been conducted: 1998–2000 (w1), 2001–2003 (w2), 2010 (w3) and the most recent in 2021 (w4). At each wave, subjects who agreed to participate, answered a questionnaire sent by mail or administered online. The original study sample at baseline in 1998 included 19,742 adult individuals 20–64 years of age residing in the Stockholm County and randomly selected from the Total population register. 10 441 individuals responded at w1 (53%). Non-response analysis was performed using available official registers. Participation was related to female gender, higher age, higher income, and education, being born in the Nordic countries, and having no previous psychiatric diagnosis in the hospital discharge register or in the early retirement register [9]. All participants from the first wave received a second, almost identical questionnaire at w2 and the participation rate was 83%. Attrition in the second wave was associated with the same conditions as in the first wave. In w3 this was repeated (participation rate 61%) with the addition that 4,956 persons aged 20–30 was invited (participation rate = 22%). In w4, a similar procedure was used as in w3, and 10,158 individuals from w1 participants were invited (participation rate 73%) with an additional sample of 4,986 young adults aged 20–30 (participation rate 33%). The flowchart of the PART study participants is presented in Appendix (Fig. 1).

In this study, persons with available measurements on Major Depression Inventory (MDI) from wave 3 (n = 6,641) and wave 4 (n = 8,863) were included in the analysis. To study the covid-related effect, the analyses was restricted to participants in wave 4 with information on those related questions (n = 8,813). The ethical review board (case numbers: 2009/880 − 31, and 2021 − 00843) approved the study and informed consents were obtained from all participants.

Depression

Depression was assessed using the Major Depression Inventory (MDI) [10] following a diagnostic algorithm according to the DSM-4R and DSM-5 criteria. The scale includes a list of major depression symptoms according to the DSM-5 definition, using six-point intensity Likert scales (from “not at all” to “all the time”). A question on duration of symptoms was added in the questionnaire and only symptoms reported to have lasted at least 2 weeks were included. Validity studies of the MDI has been performed using the PART study and in clinical settings in European countries [11, 12, 13]. The sensitivity of MDI was 0.78 and the specificity was 0.78 based on the PART first wave [11].

Other variables

Age and sex were assessed based on information from the Total population register. Marital status (e.g., married/cohabitant, unmarried, divorced, and widowed) derived from the Longitudinal Integration Database for Health Insurance and Labour Market Studies (LISA) register based on the most recent status before the questionnaire was sent out (i.e. in December 2019). Other variables were assessed based on the questionnaire. Employment status was grouped into employed, retired/early retired, study, break from work or study (e.g. parental leave, and study leave), and other (e.g. jobless, and long-term sick leave). History of Covid-19 infection were self-reported. Covid related work changes were assessed using the responses to the following questions: “During the period from the beginning of the Covid-19 pandemic until now, did your work situation change in any way?” The participants were grouped into lost job, changed job, no change, not applicable based on their answers. The Covid-related change in private life was assessed based on the following question “During the past month, how much disturbance has the covid-19 pandemic caused in your daily life?” The answers included no disturbance, little disturbance, some disturbance, pretty much disturbance, and too much disturbance.

Statistical methods

The distribution of characteristics of the participants in w3 (2010) and w4 (2021) were compared using t-test for continuous variables, and chi-square test for categorical variables. The characteristics were presented by age, the prevalence of depression/individual symptoms were presented by age and sex. In addition, chi-square test was performed to compare the prevalence of individual symptoms between wave 3 and wave 4 for total participants and for men and women.

Linear regression and logistic regression were performed to compare the mean score of MDI and the prevalence of depression, respectively, between 2010 and 2021. Two models were presented: model 1 was adjusted for age, and if applicable, sex; model 2 was adjusted for age, marital status, employment status, covid infection, and if applicable, sex. For those aged 65 and above, generalized estimation equation was used to rule out the effect of repeated participation, in which a linear link was used for MDI score and logit link was used for depression. Statistical analyses were performed using IBM SPSS 28 for Windows (IBM SPSS Inc., Chicago, Illinois, USA).

A description of the study population in 2010 and 2021 can be seen in Table 1.

Table 1

Demographic characteristics of study participants in 2010 and 2021 by age.
Characteristics	2010 (n = 6641)						2021 (n = 8863)
Characteristics	Age 20–29	Age 30–39	Age 40–49	Age 50–59	Age 60–64	Age ≥ 65	Age 20–29	Age 30–39	Age 40–49	Age 50–59	Age 60–64	Age ≥ 65
Female, n (%)	625 (66.2)	610 (61.7)	758 (61.9)	722 (60.3)	415 (56.3)	866 (55.9)	799 (59.3)	514 (66.4)	614 (59.3)	1020 (57.9)	428 (56.9)	1800 (56.4)
Marital status^, n (%)
Married/cohabitant	82 (8.7)	442 (44.7)	640 (52.3)	639 (53.4)	445 (60.4)	931 (60.1)	51 (3.8)	238 (30.7)	614 (59.3)	984 (55.9)	388 (51.6)	1788 (56.0)
Unmarried	850 (90.0)	506 (51.2)	430 (35.1)	271 (22.6)	124 (16.8)	122 (7.9)	1268 (94.1)	506 (65.4)	304 (29.3)	501 (28.4)	185 (24.6)	409 (12.8)
Divorced	11 (1.2)	40 (4.0)	149 (12.2)	269 (22.6)	138 (18.7)	339 (21.9)	3 (0.2)	24 (3.1)	110 (10.6)	259 (14.7)	164 (21.8)	631 (19.8)
Widowed	1 (0.1)	1 (0.1)	5 (0.4)	18 (1.5)	30 (4.1)	158 (10.2)	0 (0.0)	0 (0.0)	4 (0.4)	16 (0.9)	14 (1.9)	363 (11.4)
Missing	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	25 (1.9)*	6 (0.8)*	4 (0.4)*	1 (0.1)*	1 (0.1)*	2 (0.1)*
Employment status, n (%)
Employed	423 (44.8)	663 (67.0)	912 (74.5)	789 (65.9)	388 (52.6)	129 (8.3)	634 (47.1)	525 (67.8)	870 (84.0)	1430 (81.2)	484 (64.4)	175 (5.5)
Leave of absence from work or study	37 (3.9)	94 (9.5)	47 (3.8)	19 (1.6)	12 (1.6)	2 (0.1)	36 (2.7)	81 (10.5)	34 (3.3)	40 (2.3)	17 (2.3)	9 (0.3)
Studying	279 (29.6)	41 (4.1)	25 (2.0)	10 (0.8)	0 (0.0)	-	398 (29.5)	56 (7.2)	21 (2.0)	24 (1.4)	5 (0.7)	-
Retired/early retired	0 (0.0)	3 (0.3)	19 (1.6)	55 (4.6)	135 (18.3)	1232 (79.5)	13 (1.0)	5 (0.6)	9 (0.9)	31 (1.8)	106 (14.1)	2769 (86.7)
Other	150 (15.9)	94 (9.5)	92 (7.5)	109 (9.1)	94 (12.8)	123 (7.9)	133 (9.9)	49 (6.3)	34 (3.3)	81 (4.6)	66 (8.8)	75 (2.3)
Missing	55 (5.8)	94 (9.5)	129 (10.5)	215 (18.0)	108 (14.7)	64 (4.1)	33 (9.9)	58 (7.5)	68 (6.6)	155 (8.8)	74 (9.8)	165 (5.2)
*Not available in the LISA register 2019.

Depressive symptoms according to MDI-score increased in 2021 compared to 2010, in all age groups, except for those ≥65 years, as well as in both genders, see table 2. The highest mean scores were found in the youngest age-group. Prevalence of Major depression increased in the younger age groups, but not as much as depressive symptoms, see table 3. An increase was also seen amongst those ≥ 65 years. A description of the β coefficients and ORs can be seen in supplementary table 1 (The trend in MDI score and prevalence of major depression over time).

Table 2

Trend in the score of major depression inventory 2010–2021.
Age groups (years)	Total				Male				Female
	Mean (SD)		Coefficient (95% CI)^*		Mean (SD)		Coefficient (95% CI)^*		Mean (SD)		Coefficient (95% CI)^*
	2010	2021	Model 1	Model 2	2010	2021	Model 1	Model 2	2010	2021	Model 1	Model 2
Total	6.8 (8.0)	8.8 (9.4)	2.67 (2.45–2.89)	2.26 (1.97–2.54)	5.6 (7.0)	7.4 (8.6)	2.28 (1.63–1.96)	1.72 (1.30–2.14)	7.6 (8.5)	9.8 (9.7)	2.94 (2.64–3.24)	2.60 (2.22–2.99)
20–29	10.8 (9.6)	14.6 (11.1)	4.11 (3.24–4.97)	4.04 (3.11–4.97)	8.3 (8.1)	12.6 (10.4)	4.30 (2.97–5.64)	4.32 (2.89–5.76)	12.0 (10.1)	16.0 (11.3)	4.01 (2.89–5.14)	3.86 (2.65–5.08)
30–39	7.3 (7.6)	11.3 (9.7)	3.80 (2.98–4.61)	3.60 (2.71–4.50)	6.4 (6.7)	10.1 (8.8)	3.49 (2.26–4.71)	2.97 (1.60–4.34)	7.8 (8.1)	12.0 (10.1)	3.98 (2.90–5.05)	3.92 (2.74–5.09)
40–49	6.7 (7.4)	8.9 (8.9)	2.33 (1.66–3.01)	2.15 (1.41–2.89)	5.8 (6.8)	6.9 (7.6)	1.10 (0.14–2.07)	1.14 (0.12–2.16)	7.3 (7.7)	10.4 (9.4)	3.12 (2.21–4.04)	2.85 (1.82–3.88)
50–59	6.9 (8.3)	7.8 (8.6)	0.89 (0.27–1.51)	1.03 (0.37–1.69)	6.1 (7.7)	6.6 (8.0)	0.45 (-0.45-1.36)	0.43 (-0.54-1.40)	7.5 (8.7)	8.7 (8.9)	1.19 (0.35–2.03)	1.43 (0.54–2.33)
60–64	5.4 (7.0)	6.8 (7.8)	1.38 (0.63–2.13)	1.14 (0.34–1.94)	4.5 (6.1)	5.8 (6.8)	1.36 (0.36–2.36)	1.33 (0.23–2.43)	6.2 (7.5)	7.6 (8.5)	1.40 (0.32–2.49)	1.13 (-0.003-2.26)
≥65	4.8 (6.6)	6.7 (8.1)	1.39 (0.92–1.86)	0.89 (-0.08-1.85)	4.0 (5.8)	5.8 (7.7)	1.33 (0.67–1.99)	1.00 (-0.20-2.19)	5.3 (7.1)	7.4 (8.3)	1.42 (0.76–2.08)	0.79 (-0.68-2.27)
CI, confidence interval.
^*Coefficient (95% confidence interval) was presented from linear regression, except that GEE model was used for total participants and those aged 65 and above due to repeated participation. The score in 2010 was considered as reference. Model 1 was adjusted for age, and sex if applicable. Model 2 was adjusted for age, marital status, employment status, covid infection, and sex, if applicable.

Table 3

Prevalence of major depression in 2010 compared to 2021 in total participants and by age and sex
Age groups (years)	Total				Male				Female
	No. cases (%)		Odds ratio (95% CI)^*		No. cases (%)		Odds ratio (95% CI)^*		No. cases (%)		Odds ratio (95% CI)^*
	2010	2021	Model 1	Model 2	2010	2021	Model 1	Model 2	2010	2021	Model 1	Model 2
Total	314 (4.7)	605 (6.8)	1.67 (1.47–1.90)	1.43 (1.22–1.67)	70 (2.6)	182 (4.9)	2.09 (1.60–2.74)	1.66 (1.21–2.28)	244 (6.1)	423 (8.2)	1.54 (1.33–1.79)	1.36 (1.13–1.63)
20–29	98 (10.4)	211(15.7)	1.68 (1.30–2.18)	1.63 (1.24–2.15)	16 (5.0)	64 (11.7)	2.49 (1.41–4.39)	2.33 (1.29–4.22)	82 (13.1)	147 (18.4)	1.50 (1.12–2.01)	1.48 (1.08–2.02)
30–39	51 (5.2)	67 (8.7)	1.60 (1.09–2.35)	1.54 (1.02–2.33)	11 (2.9)	19 (7.3)	2.41 (1.11–5.23)	2.61 (1.14–5.96)	40 (6.6)	48 (9.3)	1.39 (0.90–2.16)	1.29 (0.80–2.09)
40–49	43 (3.5)	64 (6.2)	1.84 (1.23–2.75)	1.87 (1.21–2.90)	8 (1.7)	14 (3.3)	2.01 (0.82–4.91)	2.00 (0.77–5.17)	35 (4.6)	50 (8.1)	1.80 (1.15–2.83)	1.87 (1.14–3.07)
50–59	62 (5.2)	92 (5.2)	1.02 (0.73–1.42)	1.10 (0.77–1.57)	17 (3.6)	27 (3.6)	1.02 (0.55–1.88)	1.21 (0.62–2.36)	45 (6.2)	65 (6.4)	1.02 (0.69–1.52)	1.08 (0.71–1.65)
60–64	24 (3.3)	26 (3.5)	1.06 (0.60–1.86)	1.05 (0.58–1.92)	7 (2.2)	7 (2.2)	1.00 (0.34–2.88)	0.79 (0.24–2.62)	17 (4.1)	19 (4.4)	1.09 (0.56–2.13)	1.17 (0.58–2.37)
≥65	36 (2.3)	145 (4.5)	1.85 (1.24–2.76)	1.91 (1.28–2.86)	11 (1.6)	51 (3.7)	2.11 (1.04–4.25)	2.13 (1.06–4.30)	25 (2.9)	94 (5.2)	1.72 (1.06–2.81)	1.80 (1.10–2.94)
CI, confidence interval.
^*Odds ratio (95% confidence interval) was presented from logistic regression, except that GEE model was used for total participants and those aged 65 and above due to repeated participation. The prevalence in 2010 was considered as reference. Model 1 was adjusted for age, and sex if applicable. Model 2 was adjusted for age, marital status, employment status, covid infection, and sex, if applicable.

Analysis of the symptoms included in MDI, all increased except “feeling low” in females, see supplementary table 1.

No differences in prevalence were found for depression in those reporting having experienced Covid-19 infections compared to those that did not. However, a higher prevalence was associated with reporting Covid-related life changes in women and those reporting to have lost their job, see table 4.

Table 4

The association of covid-19 infections and covid-19 related work and private life changes with Major depression, odds ratio (OR) and 95% confidence interval (95% CI), (n = 9 414).
	No. of participants	Major depression in 2021
	No. of participants	No. of cases	OR (95% CI)^*
Covid-19 infection
Total
No	7377	500	Ref
Yes	1436	101	0.86 (0.68–1.08)
Males
No	3092	158	Ref
Yes	579	22	0.65 (0.41–1.03)
Females
No	4285	342	Ref
Yes	857	79	0.95 (0.73–1.24)
Covid-related work change^b
Total
No change	4524	230	Ref
Lost job	903	102	1.87 (1.46–2.41)
Changed job	670	53	1.05 (0.77–1.45)
Not applicable (not working)	2336	179	2.02 (1.64–2.50)
Men
No change	2006	76	Ref
Lost job	377	26	1.49 (0.93–2.39)
Changed job	252	9	0.61 (0.30–1.25)
Not applicable (not working)	919	61	2.32 (1.62–3.33)
Women
No change	2518	154	Ref
Lost job	526	76	2.06 (1.53–2.78)
Changed job	418	44	1.24 (0.86–1.78)
Not applicable (not working)	1417	118	1.90 (1.46–2.46)
Covid-related disturbance in private life^b
Total
No	1059	61	Ref
Little	2850	125	0.76 (0.55–1.05)
Some	1253	114	1.46 (1.05–2.03)
Pretty much	2705	166	1.02 (0.75–1.39)
Too much	925	128	2.46 (1.78–3.41)
Men
No disturbance	543	32	Ref
Little disturbance	1283	44	0.62 (0.39-1.00)
Some disturbance	521	27	0.83 (0.49–1.42)
Pretty much disturbance	1010	44	0.75 (0.46–1.20)
Too much disturbance	308	29	1.66 (0.97–2.84)
Women
No disturbance	516	29	Ref
Little disturbance	1567	81	0.94 (0.60–1.47)
Some disturbance	732	87	2.08 (1.34–3.24)
Pretty much disturbance	1695	122	1.33 (0.87–2.04)
Too much disturbance	617	99	3.30 (2.12–5.12)
^*Adjusted for age, marital status, employment status, and sex, if applicable.

In the present study Major Depression and depressive symptoms were more common (45% increase) in 2021 compared with 2010. The highest prevalence was found in the youngest age-group years and in women all in agreement with previous studies.

Older adults are at higher risk for severe infection and death due to Covid-19, but they have also been found to have lower risk of post-traumatic symptoms suggesting a higher resilience towards stress [14]. Other studies have also shown a lower risk of depression in this age group during the pandemic [15]. We found no relation between being infected by Covid-19 and higher rates of depression. Since its most likely that most of the persons in this sample did not have a severe infection, it is not possible to compare with studies using hospitalized samples. However, higher rates of depression were associated with women who experienced disturbances in their private life related to the pandemic situation. Higher rates were also found in those who lost their job during the pandemic. Thus, some of the increase might be due to secondary social and economic consequences of the pandemic.

A report in Lancet 2021 by the Covid-19 Mental Disorders Collaborators estimated an additional 53.2 million (44.8 to 62.9) cases of Major depressive disorder globally (an increase of 27.6% [25.1 to 30.3]) due to the Covid-19 pandemic [16]. The meta-analysis included 46 studies from around the world. Most of the included studies used symptom scales, which was considered using a bias correction. This bias correction assumes that the predictive validity of the symptom scales remained the same pre-pandemic and mid-pandemic. They also concluded that some of the symptoms might be reactive to the situation and not a part of a disorder.

However, there is evidence of an increasing trend of depression even before Covid-19 pandemic. A recent review by Moreno-Agostino concluded that this increase is not due to methodological changes within or across studies [17]. They excluded studies with different sampling procedures or depression assessments across time points. The study also highlights the absence of research on the changes in incidence of depression over time using the same sampling methods and depression assessments across time points.

The 45% increase of depression seen in the present study was mainly driven by the younger persons (20–39 years) but also partly explained by an increased prevalence in the elderly. Although the prevalence was higher among women the relative increase was higher among men. One explanation could be that it is not being a woman rather the expression of femininity that increases the risk [18]. Acknowledging and expressing the feminine side might be more accepted in recent years. Depression might have different expression in women and men and rating scales might capture the feminine rather than the masculine expression [19].

There is a possibility that the high numbers reported in the studies included in the Lancet review will decrease after the pandemic. Well-being theories suggests that because of genetic and personality predispositional factors, subjective well-being is stable over the long term [20, 21]. Thus the 45% increase might be explained both by a pandemic related effect and a time-trend.

Strength of our study include the population-based, longitudinal design and use of validated assessment of depression, which is rare in the Covid context. Several limitations must also be acknowledged, oneThis might affect the external validitu being the non-participation rate. Participation might be related to Covid-19 infection as well as depressive symptoms, causing an underestimation. During the pandemic restrictions in Sweden have been relying partly on recommendations since trust in the government is high (67% in 2020- data from OECD). This might affect the external validity.

However, a recent review and meta-analysis including 36 studies comparing pre and peri-Covid-19 data on anxiety and depression reported that age, status as a medical provider, race, or region of origin, had no impact on elevated levels of symptoms during the pandemic implying that the results could be applicable even in other settings [22].

In summary, the increase in prevalence of depression in 2021 compared to 2010 could be due to the overall increasing rates of depression in society but we cannot rule out an effect of the pandemic either.

Acknowledgements

Financial support was obtained from Forte - the Swedish Research Council for Health, Working Life and Welfare (case number:2020-02766).

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No competing interests reported.

Appendix.docx

Major Depression before and during the Covid-19 pandemic – a population-based study among Swedish adults

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Version 1

Abstract

Introduction

Methods

Depression

Other variables

Statistical methods

Results

Discussion

Declarations

References

Additional Declarations

Supplementary Files

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Version 1