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Assets, stressors, and symptoms of persistent depression over the first year of the COVID-19 pandemic

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The coronavirus disease 2019 (COVID-19) pandemic has been accompanied by an increase in depression in U.S. adults. Previous literature suggests that having assets may protect against depression. Using a nationally representative longitudinal panel survey of U.S. adults studied in March and April 2020 and in March and April 2021, we found that (i) 20.3% of U.S. adults reported symptoms of persistent depression in Spring 2020 and Spring 2021, (ii) having more assets was associated with lower symptoms of persistent depression, with financial assets-household income and savings-most strongly associated, and (iii) while having assets appeared to protect persons-in particular those without stressors-from symptoms of persistent depression over the COVID-19 pandemic, having assets did not appear to reduce the effects of job loss, financial difficulties, or relationship stress on symptoms of persistent depression. Efforts to reduce population depression should consider the role played by assets in shaping risk of symptoms of persistent depression.
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Ettman et al., Sci. Adv. 8, eabm9737 (2022) 2 March 2022
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CORONAVIRUS
Assets, stressors, and symptoms of persistent
depression over the first year of the
COVID-19 pandemic
Catherine K. Ettman1,2*, Gregory H. Cohen1, Salma M. Abdalla1, Ludovic Trinquart1,3,4,
Brian C. Castrucci5, Rachel H. Bork5, Melissa A. Clark2, Ira B. Wilson2,
Patrick M. Vivier2,6, Sandro Galea1
The coronavirus disease 2019 (COVID-19) pandemic has been accompanied by an increase in depression in U.S.
adults. Previous literature suggests that having assets may protect against depression. Using a nationally repre-
sentative longitudinal panel survey of U.S. adults studied in March and April 2020 and in March and April 2021, we
found that (i) 20.3% of U.S. adults reported symptoms of persistent depression in Spring 2020 and Spring 2021,
(ii) having more assets was associated with lower symptoms of persistent depression, with financial assets—
household income and savings—most strongly associated, and (iii) while having assets appeared to protect
persons—in particular those without stressors—from symptoms of persistent depression over the COVID-19 pan-
demic, having assets did not appear to reduce the effects of job loss, financial difficulties, or relationship stress on
symptoms of persistent depression. Efforts to reduce population depression should consider the role played by
assets in shaping risk of symptoms of persistent depression.
INTRODUCTION
The first year of the coronavirus disease 2019 (COVID-19) pan-
demic presented unprecedented challenges for population mental
health. The threat and fear of a new devastating infectious disease
(1), millions of deaths globally, and unprecedented reductions in
social interactions were each stressors that could be expected to in-
fluence mental health. In addition, the efforts to mitigate the pandem-
ic were accompanied by an economic downturn that contributed to
poor mental health (25). An increase in poor mental health at the
start of the COVID-19 pandemic relative to before it has been doc-
umented across multiple studies. Daly etal. (6) reported an increase
in symptoms of depression from 8.7% in 2017 to 2018 to 14.4% in
April 2020 using the Patient Health Questionnaire-2 (PHQ-2) screener
for depressive symptoms. Czeisler etal. (7) documented a popula-
tion prevalence of 24.3% for symptoms of depressive disorder in
June 2020 also using the PHQ-2. Using the nine-question PHQ-9,
Ettman etal. (8) reported an increase in elevated symptoms of prob-
able depression from 8.5% in 2017 to 2018 to 27.8% in March and
April 2020, suggesting a potential threefold increase in symptoms
of probable depression at the start of the COVID-19 pandemic.
McGinty etal. (9) measured symptoms of serious psychological dis-
tress using the Kessler 6 Psychological Distress Scale and documented
in an increase from 3.9% in 2018 to 13.6% in April 2020, suggesting
a 3.5-fold increase in symptoms of psychological distress. While the
increase in depression at the onset of the pandemic may not have
been unexpected given what we knew about the risks for depression
before the pandemic, depression remained high through the end of
2020 as the COVID-19 pandemic continued (10). Vahratian etal. (10)
reported a continued increase in symptoms of depressive disorder
from 24.5% in August 2020 to 30.2% in December 2020. Ettman etal.
(11) reported that 32.8% of U.S. adults reported elevated symptoms
of probable depression in March and April 2021.
The continued high prevalence of depression is unusual. In the
aftermath of other mass traumatic events, population mental health
improved in the months that followed the large-scale trauma. For
example, after an initial increase, population depression decreased
substantially in the first six months after Hurricane Ike (12), the 1999
Mexico floods (13), and the September 11th attacks (13,14). The
chronic and continued exposure to the COVID-19 pandemic through-
out 2020 may have resulted in the observed persistence of high levels
of depression over time at the population level during the pandemic.
Comparison with population mental health following the last pan-
demic of similar scale, namely, the 1918 Flu Pandemic, is challenging,
given advances in the field on mental health screening instruments
and classification of conditions. Even so, publication from the time
suggested that while around one-fourth of cases at a Boston-based
hospital showed depression at any time, it was not chronic or per-
sistent when present (15). Persistent depression among individuals
(that is, unrelenting depression, or depression expressed by the same
person across multiple times) is particularly concerning given its po-
tential for ongoing health and economic consequences in popula-
tions (16). It was estimated that depression cost the United States
over $210 billion in 2010 including absenteeism (missed work), pre-
senteeism (underproduction while at work), and costs for treatment,
among others (17). The economic toll of depression could be con-
siderably larger with an increased prevalence of the population re-
porting symptoms of depression.
The role of assets may be essential to understanding the per-
sistently high burden of depression in the population during the
COVID-19 pandemic. Assets can protect against poor mental health,
as noted before the COVID-19 pandemic (1820). In particular, fi-
nancial assets, physical assets, and social assets may all protect against
depression (19,21). For example, having family savings was associated
1Boston University School of Public Health, Boston, MA, USA. 2Brown University
School of Public Health, Providence, RI, USA. 3Institute for Clinical Research and
Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USA. 4Tufts
Clinical and Translational Science Institute, Tufts University, Boston, Massachu-
setts, USA. 5de Beaumont Foundation, Bethesda, MD, USA. 6Hassenfeld Child
Health Innovation Institute, Providence, RI, USA.
*Corresponding author. Email: cettman@bu.edu
Copyright © 2022
The Authors, some
rights reserved;
exclusive licensee
American Association
for the Advancement
of Science. No claim to
original U.S. Government
Works. Distributed
under a Creative
Commons Attribution
License 4.0 (CC BY).
Ettman et al., Sci. Adv. 8, eabm9737 (2022) 2 March 2022
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with 150% greater odds of symptoms of depression relative to not
having family savings in 2015 to 2016 (18). Beyond just having family
savings, owning a home was also associated with lower odds of symp-
toms of depression: Homeowners without savings had 2.15 times
the odds of symptoms of depression relative to homeowners with
$5000in family savings, and home renters without family savings
had 3.65 times the odds of symptoms of depression relative to home
renters with home savings (20). The association of assets with prob-
able depression is so strong that it may, in fact, account for much of
the difference in population-level depression between racial-ethnic
groups (19). Having more assets was associated with a lower preva-
lence of probable depression at the start of COVID-19, including in
the face of stressors (22). It is possible that having access to assets may
also protect persons against persistent or chronic depression over
time. We do not know the prevalence of symptoms of persistent de-
pression, nor do we know the factors associated with greater risk for
symptoms of persistent depression following exposure to stressors
after the presence of the COVID-19 pandemic for 1 year.
Therefore, in this work, we aimed to understand the following:
(i) the population prevalence of symptoms of persistent depression
at two time points, 1 year apart, during the COVID-19 pandemic;
(ii) the relative influence of particular types of assets on symptoms
of persistent depression over that time; and (iii) whether having
assets reduced the effect of stressors on symptoms of persistent de-
pression over the course of the COVID-19 pandemic. This paper
addresses gaps in the literature by using a nationally representative,
longitudinal panel study to measure symptoms of persistent depres-
sion 1 year into the COVID-19 pandemic, measuring symptoms of
persistent depression in March and April 2020 and in March and
April 2021in U.S. adults. We use detailed assets and stressor expo-
sures measured at the start of the COVID-19 pandemic to predict
symptoms of persistent depression 1 year later.
RESULTS
Table1 shows the prevalence of symptoms of persistent depression
by gender, age, and race/ethnicity. Twenty percent of U.S. adults re-
ported symptoms of persistent depression, reporting elevated symp-
toms of probable depression in both March and April 2020 and March
and April 2021. Among women, 24.8% reported symptoms of per-
sistent depression and among men, 15.4% reported symptoms of
persistent depression (P<0.01). Persons ages 18 to 39 years reported
the highest prevalence of symptoms of persistent depression (26.8%)
relative to persons ages 40 to 59 years (20.7%) and persons ages
60 years and older (10.2%) (P<0.01). We found no evidence of
differences in the prevalence of symptoms of persistent depression
across race/ethnicity.
Figure1 shows a visual representation of the prevalence of symp-
toms of persistent depression by three types of assets, which are de-
scribed in greater detail in Materials and Methods: financial assets,
physical assets, and social assets. Financial assets include household
income and household savings; physical assets include homeowner-
ship; and social assets include educational attainment and marital
status, as published previously (19). The graph shows that as each
asset type increased, the prevalence of persistent depression decreased.
While persons with more social assets reported lower prevalence of
Table 1. Symptoms of persistent depression in March and April 2020 (T1) and March and April 2021 (T2) by gender, age, and race/ethnicity. Note: T1
demographic characteristics reported. Other race includes multiple races and non-Hispanic Asian race. Column percentages provided for total; row percentages
provided for persistent depression. Symptoms of persistent depression defined as presence of PHQ-9 score of 10 or greater at T1 and T2. n unweighted,
% weighted using T2 survey weights. P value reflects the two-sided 2 test between persistent depression and all other categories (people with no
depression, depression only at T1, or depression only at T2). P values <0.05 suggest significance in differences between persistent depression and all other
categories by demographic characteristics.
Total Symptoms of persistent
depression All other categories
n%n%n%P value
Total 1139 208 20.3 931 79.7
Gender 0.008
Female 563 51.8 130 24.8 433 75.2
Male 576 48.2 78 15.4 498 84.6
Age <0.001
18–39 years 458 40.3 102 26.8 356 73.2
40–59 years 380 32.0 76 20.7 304 79.3
≥60 years 301 27.7 30 10.2 271 89.8
Race/ethnicity 0.602
Black, non-
Hispanic 95 11.9 13 16.2 82 83.8
Hispanic, any race
or races 186 16.4 39 23.9 147 76.1
White, non-
Hispanic 773 63.1 139 20.7 634 79.3
Other race,
non-Hispanic 85 8.6 17 15.8 68 84.2
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depression than persons with fewer social assets, the spread between
the groups was greatest between high- and low-asset holders for fi-
nancial assets and physical assets. Persistent depression was highest
among persons with low household income, with 40.9% of persons
with $0 to $19,999 and 9.5% of persons with $75,000 or more in an-
nual household income reporting persistent depression (P<0.01).
Thirty-one percent of persons with less than $5000in household
savings relative to 13.2% of persons with $5000 or more in household
savings reported persistent depression (P<0.01). Twenty-five percent
of home renters and 16.3% of homeowners reported persistent de-
pression (P<0.01). More than 25% percent of persons without a high
school degree reported persistent depression, while 11.9% of persons
with a college degree or higher reported persistent depression. Persons
who were not married reported a higher prevalence of persistent de-
pression than persons who were married; 28% of persons who had
never married and 28% of those who were living with a partner versus
13.2% of persons who were married reported persistent depression.
Table2 shows the odds of symptoms of persistent depression by
financial assets (income and savings), physical assets (homeowner-
ship), and social assets (education and marital status). Persons with
a household income of $0 to $19,999 relative to $75,000 or more
had 6.8 times the odds of symptoms of persistent depression, ad-
justing for demographic characteristics (model 2). Persons with less
than relative to more than $5000in household savings had 2.7 times
the odds of symptoms of persistent depression when adjusting for
demographics (model 3). Persons with a high school degree or grad-
uate equivalency degree/general educational diploma (GED) had
2.9 times the odds of symptoms of persistent depression as persons
with a college degree or more (model 5). Persons who were never
married had 2.1 times the odds and persons who were widowed,
divorced, or separated had 2.0 times the odds of symptoms of per-
sistent depression as persons who were married, when controlling
for demographics (model 6). Model 7 shows the adjusted odds of
symptoms of persistent depression, adjusting for all assets (which
are correlated with each other; see table S1) and demographic char-
acteristics. When adjusting for financial, physical, and social assets
at the same time, having a household income of $0 to $19,999 rela-
tive to $75,000 or more was associated with 3.5 times the odds of
symptoms of persistent depression and having household savings of
less than $5000 was associated with 1.7 times the odds of symptoms
of persistent depression.
Figure2 shows the predicted probability of symptoms of per-
sistent depression adjusted for demographic characteristics and for
the interaction of job loss, financial difficulties, and relationship prob-
lems with each asset type. Assets did not appear to reduce the effect
of job loss, financial difficulties, or relationship problems on symp-
toms of persistent depression. Assets were, however, associated with
lower symptoms of persistent depression among persons who did not
report stressors. In particular, persons who had more than $5000in
savings and did not report job loss had substantially lower symptoms
of persistent depression than persons who had less than $5000in
savings and did not report job loss; similarly, persons with $5000 or
more in savings and did not report relationship problems had sub-
stantially lower symptoms of persistent depression than their coun-
terparts with less than $5000in savings.
Table S1 shows the correlation of assets with each another, and
table S2 shows the prevalence of symptoms of persistent depression
by financial assets, physical assets, and social assets. Table S3 shows
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
$0
-
$19,999
$20,000
-
$44,999
$45,000
-
$74,000
≥$75,000
$0
-
$4999
≥$5000
Occupied without payment
Rented for cash
Homeowner
Less than high school graduat
e
High school grad or GED
Some college
College grad or more
Living with partner
Never married
Widowed, divorced, separated
Married
Income
Savings
Homeownership
Education
Marital status
Financial assets Physical assets Social assets
Prevalence of persistent depression symptoms
Fig. 1. Prevalence of symptoms of persistent depression in March and April 2021 (T2) by financial assets, physical assets, and social assets in March and April 2020
(T1). Note: T1 assets reported. Symptoms of persistent depression defined as presence of PHQ-9 score of 10 or greater at T1 and T2. GED, graduate equivalency degree/
general educational diploma. Percentages weighted using T2 survey weights.
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the adjusted predicted probabilities and 95% confidence intervals
(CIs) for all interaction pairs. Table S4 shows the results of likeli-
hood ratio tests for the interaction between each stressor (job loss,
financial problems, and relationship problems) and each asset type.
At the 0.05 level of significance, there was evidence of interaction
between savings and job loss and between savings and relationship
problems on symptoms of persistent depression. Figure S1 shows the
unadjusted, unweighted prevalence of symptoms of persistent de-
pression across each stressor and asset type combination.
DISCUSSION
In a nationally representative longitudinal panel study of U.S. adults
1 year into the COVID-19 pandemic, we describe three main findings:
(i) 20.3% of surveyed U.S. adults reported symptoms of depression
in both March and April 2020 and March and April 2021; (ii) finan-
cial assets, physical assets, and social assets were each associated with
a lower likelihood of symptoms of persistent depression 1 year into
the COVID-19 pandemic, with the strongest associations among fi-
nancial assets; and (iii) persons with fewer assets and more stressors
in March and April 2020 were more likely to report symptoms of per-
sistent depression 1 year later, in March and April 2021, controlling
for gender, race/ethnicity, age, and household size. Having assets was
particularly important for reducing symptoms of persistent depres-
sion 1 year into the COVID-19 pandemic in the absence of stressors.
People who experienced stressors had greater symptoms of persistent
depression than persons who did not. Persons with lowest risk of
symptoms of persistent depression in Spring 2021 were those with
high assets in Spring 2020 and no exposure to job loss, financial dif-
ficulties, or relationship problems.
Table 2. Odds ratios of symptoms of persistent depression in March and April 2021 (T2) by assets in March and April 2020 (T1). Note: Odds radio (OR),
adjusted odds ratios (aOR), and 95% confidence interval (CI) presented. Model 1: unadjusted. Models 2 to 6: adjusted for household income, household savings,
homeownership, education, or marital status, respectively, and gender, age, race/ethnicity, and household size. Model 7: multivariable model adjusted for
gender, age, race/ethnicity, household size, and all assets (household income, household savings, homeownership, education, and marital status). Symptoms of
persistent depression defined as presence of the PHQ-9 score of 10 or greater at T1 and T2. Data weighted using T2 survey weights. Ref, reference.
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7
OR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI)
Household income
$0–$19,999 6.6 (3.5–12.2) 6.8 (3.7–12.6) 3.5 (1.6–7.6)
$20,000–$44,999 2.6 (1.5–4.6) 2.7 (1.5–4.9) 1.7 (0.9–3.3)
$45,000–$74,999 1.8 (1.0–3.4) 1.8 (1.0–3.2) 1.3 (0.7–2.4)
≥$75,000 Ref Ref
Household savings
$0–$4999 3.0 (1.9–4.7) 2.7 (1.7–4.2) 1.7 (1.0–2.8)
≥$5000 Ref
Homeownership
Occupied without
payment 3.7 (1.1–2.6) 3.1 (1.3–7.5) 0.9 (0.5–1.5)
Rented for cash 1.7 (1.4–9.9) 1.4 (0.9–2.3) 1.6 (0.6–4.2)
Homeowner Ref
Education
Less than high
school
graduate
2.5 (1.0–6.6) 2.6 (1.0–6.6) 1.1 (0.4–2.8)
High school
graduate or
GED
2.7 (1.6–4.5) 2.9 (1.7–5.1) 1.6 (0.8–3.0)
Some college 2.2 (1.4–3.4) 2.2 (1.4–3.5) 1.6 (0.9–2.6)
College graduate or more Ref
Marital status
Living with
partner 2.7 (1.3–5.5) 2.0 (1.0–4.0) 1.4 (0.7–2.9)
Never married 2.5 (1.5–4.2) 2.1 (1.3–3.5) 1.5 (0.8–2.7)
Widowed,
divorced,
separated
2.0 (1.2–3.2) 2.0 (1.2–3.5) 1.5 (0.8–2.7)
Married
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These findings are consistent with some but not all other studies
that have reported a consistently high prevalence of symptoms of de-
pression during the COVID-19 pandemic in population-level longi-
tudinal cohorts. Most of the studies published to date on longitudinal
cohorts have been conducted outside of the United States, in Australia,
Austria, and the United Kingdom, among others. Czeisler etal. (23)
found an unchanged prevalence of probable depression in the Australian
population in April 2020 and September 2020. However, Australia
Fig. 2. Predicted probability of symptoms of persistent depression in March and April 2021 (T2) by stressors and assets in March and April 2020 (T1). Note: T1
stressors and assets reported. Symptoms of persistent depression defined as presence of the PHQ-9 score of 10 or greater at T1 and T2. Models adjusted for gender, age,
race/ethnicity, and household size. Unweighted.
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maintained its lockdown during the two survey periods, unlike the
United States, whose COVID-19 restriction policies were largely being
lifted around the timing of the COVID-19 and Life stressors Impact
on Mental Health and Well-being (CLIMB) Time 2 (T2) survey. In
Austria, which did lift its lockdown policies before the CLIMB T2
collection, Pieh etal. (24) found no significant change in probable de-
pression between April 2020 and September 2020; they found that
18.3 and 19.7% of the sample reported PHQ-9 scores of 10 or greater
at T1 and T2, respectively. Several studies conducted on longitudi-
nal cohorts in the United Kingdom reported that depressive symp-
toms improved after the initial start of the COVID-19 pandemic.
Fancourt etal. (25) and Pierce etal. (26) reported that depressive
symptoms improved from the start of the COVID-19 pandemic and
August 2020 and October 2020, respectively. However, these studies
were conducted during summer months, which may have been con-
founded by seasonal effects resulting in improved affect. In addition,
a requirement that participants provide at least three repeated mea-
sures (i.e., participants had to respond to at least three of the weekly
surveys between 23 March 2020 and 9 August 2020 to be included
in the sample) in the study by Fancourt etal. may be susceptible to
survivorship bias (27), which could lead to an underreporting of
adverse mental health symptoms at the population level. Given that
the CLIMB survey had a response rate of 81.1% at T2, our data may
be less susceptible to survivorship bias.
Within the United States, there are few studies that have longitu-
dinally followed populations during the COVID-19 pandemic. While
several studies compared adult depressive symptoms relative to the
start of the COVID-19 pandemic (6,28,29), none to our knowledge
has reported on persistent depression (presence of repeatedly report-
ing probable depression in the same persons) reported out as far as
April 2021. Of the longitudinal studies conducted at the start of the
COVID-19 pandemic, findings suggested no change or a slight de-
cline in depressive symptoms during the first half of 2020 (3033). For
example, Shuster etal. (32) found that anxiety and depressive symp-
toms declined after the initial weeks of COVID-19, measured be-
tween April 2020 and June 2020. Their study differs from ours in that
the population was not representative of U.S. adults, captured a
10-week span (relative to our 12-month comparison), and may have
seen a decline in depressive symptoms due to loss to follow-up of
persons with depression and seasonal effects, with affect improv-
ing during summer months. Our findings were consistent with theirs
in that they reported that female gender, younger age, and lower
household income were associated with increased depression across
time. They also found that worsening economic situation due to
COVID-19 was associated with increased depression over time (32).
The most recent longitudinal study of which we are aware measured
depressive symptoms over the previous 7 days using the PHQ-2 with
the last reporting period being from 20 January to 1 February 2021
(10). While the authors used an abbreviated form of the PHQ-9 and
did not capture detailed asset or stressor information, they reported
an increase in the percentage of adults with recent symptoms of
an anxiety or depressive disorder (10), with 30.2% of U.S. adults
reporting symptoms of a depressive disorder as of January and
February 2021 (relative to our finding that 20.3% of U.S. adults re-
ported symptoms of depressive disorder at both March and April 2020
and March and April 2021). According to the Centers for Disease
Control National Center for Health Statistics Household Pulse
Survey, which used the shorter-form PHQ-2, 24.7% of U.S. adults
reported symptoms of depressive disorder between 17 March and
29 March 2021, which closely aligned with our survey collection at
T2 (34).
Our findings were consistent with other studies that have ad-
dressed the stressors of job loss, financial strain, and relationship
conflict during COVID-19. In a cross-sectional study conducted in
April 2020, McDowell etal. (35) reported an increase in symptoms of
depression among persons who reported job loss. Hertz-Palmor etal.
(36) assessed relations between financial strain and depressive symp-
toms in March and April 2020 and 1 month later in samples in the
United States and Israel. They found that income loss and financial
strain were associated with exacerbated depressive symptoms in their
1-month follow-up sample. Lee etal. (37) studied relationship con-
flict during COVID-19 from March and April 2020 and found that
in the weeks studied, relationship conflict increased. Although their
findings did not show a significant association between relationship
conflict and depressive symptoms, this may have been due to limita-
tions in sample size (N=291) (37). Nonetheless, these studies show
early evidence that exposure to stressors during the COVID-19 pan-
demic was associated with depressive symptoms.
Our findings that having more assets was associated with lower
depression are novel in the context of COVID-19, even if consistent
with studies conducted after other traumatic and stressful events. For
example, Gallo etal. (38) found that persistent depression lowered
over time following involuntary job loss but remained highest among
low-wealth persons. Tracy etal. (39) found that low–socioeconomic
status persons were more likely to report depressive symptoms fol-
lowing Hurricane Ike. Thus, although the conditions of COVID-19
were unique, these findings provide support for the notion that eco-
nomic conditions can buffer the effects of stressors on depression.
The COVID-19 pandemic in particular was unique in its wide-
ranging scope, its ongoing nature, and the economic inequities that
it produced (40). As a result, persistent depression may be higher
1 year into the COVID-19 pandemic than that documented after other
large-scale events.
This study has three main limitations. First, the PHQ-9, which
was used to assess symptoms of probable depression at each time
point, is a depression screener, which does not replace the gold stan-
dard of clinical diagnosis. However, given a sensitivity and specificity
of 88% relative to clinical diagnosis, the PHQ-9 is the best available
measure that allows large-scale assessments to provide estimates of
symptoms of depression consistent with probable depression at the
national level across time (41). Using the PHQ-9 allowed us to esti-
mate the burden of depression at the population level at the begin-
ning of the pandemic, setting a baseline for symptoms of persistent
depression, which was defined as presence of probable depression at
T1 and T2. The study was not designed to measure continuous prob-
able depression throughout the 12-month follow-up period but rather
to measure presence of probable depression at both T1 and T2. Sec-
ond, similar to all longitudinal studies following the same persons
over time, we experienced some loss to follow-up at T2. However,
with 81.1% of respondents replying at T2, we had a relatively high
response rate, particularly given potential for survey response fatigue
during the COVID-19 pandemic. It is possible that nonresponders at
T2 had a higher prevalence of depression at T2 than responders (27),
suggesting that the documented symptoms of persistent depression
presented may represent an underestimate of the prevalence of prob-
able depression at T2 and therefore symptoms of persistent depres-
sion. Survey weights accounting for nonresponse at T2 were used,
allaying these concerns. Third, our sample size may have limited our
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ability to detect significant associations in the interactive effects
of assets in protecting against persistent depression across stressor
groups. However, that we were able to detect significant associa-
tions in the interactions of savings with relationship problems and
job loss speaks to the magnitude of these stressors on poor men-
tal health.
We found a high prevalence of persistent depression across a na-
tionally representative group of U.S. adults measured longitudinally
after 1 year of follow-up during the COVID-19 pandemic through
April 2021. Our results highlight the importance of assets as a po-
tential protective mechanism against ongoing probable depression.
Exposure to stressors and having fewer assets were both associated
with greater persistent depression 12 months into the COVID-19 pan-
demic. While assets did not appear to reduce the effect of stressors
on persistent depression, having more assets and not experiencing
stressors was associated with significantly less persistent depression
than having fewer assets. These findings highlight the deleterious
effect of stressors on mental health and the potential protective ef-
fect of assets against the COVID-19 pandemic in the absence of re-
ported job loss, financial problems, and relationship stressors.
Given the high prevalence of depression in U.S. adults 1 year into
the COVID-19 pandemic, with one in five surveyed U.S. adults screen-
ing positive for symptoms of probable depression both in March
and April 2020 and in March and April 2021, finding multiple ways
to address and mitigate the burden of poor mental health will be
critical. These findings suggest that interventions to shore up eco-
nomic contexts that people live in, in particular bolstering financial
assets and reducing stressors, may serve to lessen persistent depres-
sion over time. Efforts to improve the economic status of low-asset
populations may lead to improved mental health.
MATERIALS AND METHODS
Experimental design
This study used a nationally representative sample of U.S. residents
ages 18 years and older followed longitudinally over 1 year of the
COVID-19 pandemic. Participants were surveyed in March and
April 2020 (T1) and in March and April 2021 (T2) as part of the CLIMB
study (11). Participants were drawn from the AmeriSpeak panel, which
is a nationally representative standing panel whose sampling frame
covered 97% of U.S. households and used a two-stage probability-
based sample design to recruit members. The AmeriSpeak panel has
a household response rate of 34.2% (42). Participants provided con-
sent at induction into the AmeriSpeak panel and at the beginning
of each CLIMB survey. Participants were contacted over email and
over the telephone if they did not respond to email outreach. The
CLIMB survey completion rate for participants at T1 was 64.3% (8),
and among those participants, the response rate at T2 was 81.1% (11).
Details on sampling, demographics, and characteristics can be found
in other published work (8,11,22,43). The final analytic sample in
this paper included 1139 participants who responded to all depres-
sion questions at T1 and T2. Forty-four persons were removed from
the analysis because they did not respond to all depression questions
at T1 and/or T2. The participants who were not included in the anal-
ysis because of missing depression values did not differ significantly
across gender, race/ethnicity, marital status, age, education, or house-
hold income status from participants who were included in the anal-
ysis. Survey weights accounted for nonresponse at T1 and at T2 and
aligned the sample with the U.S. adult population according to
the 2010 U.S. Census (1) using the following variables: age, gender,
Census Division, race/ethnicity, education, housing type, and house-
hold phone status. The institutional review boards at NORC at the
University of Chicago and Boston University approved this study.
Key covariates
Symptoms of persistent depression
Participants completed the PHQ-9, a validated screening tool for
depression at both T1 and T2. The PHQ-9 is a nine-item screening
tool measuring probable depression based on the DSM-IV: Diag-
nostic and Statistical Manual of Mental Disorders, fourth edition.
Participants responded to nine questions about their affect over the
last 2 weeks; responses were tallied for corresponding scores ranging
from 0 to 27. Using a PHQ-9 score of 10 or greater has a sensitivity
of 88% and a specificity of 88% when tested against clinical diag-
nosis of depression (41). Having symptoms of persistent depression
was defined as the presence of a PHQ-9 score of 10 or greater at both
T1 and T2. We compared persons with persistent depression to all
others in the sample, given the increased burden of poor mental
health for persons reporting probable depression chronically across
multiple time points (16). Because the PHQ-9 is a screening tool, it
cannot replace official diagnosis of depression by a clinician (44).
Throughout this paper, symptoms of persistent depression refer to
the presence of elevated symptoms of probable depression in both
March and April 2020 and March and April 2021 as indicated by a
PHQ-9 score of 10 or greater at both times. This definition differs
from persistent depressive disorder, reflecting the DSM-5 concepts
of dysthymia and chronic major depression, which would be diag-
nosed by a clinician (45). Here, symptoms of persistent depression
reflect the presence of elevated symptoms of probable depression at
two points one year apart during the COVID-19 pandemic.
Assets
To consider the role different types of assets, assets were grouped into
three categories: financial assets, physical assets, and social assets,
as previously published (19). Financial assets included household
income and household savings. Household income was defined as
a categorical variable: $0 to $19,999, $20,000 to $44,999, $45,000 to
$74,999, and≥$75,000 (11), with categories divided roughly at the
interquartile range. To determine household savings, participants
were asked to list total money in all types of accounts, including “cash,
savings, or checking accounts, stocks, bonds, mutual funds, retirement
funds (such as pensions, IRAs, 401Ks, etc.), and certificates of deposit”
as consistent with national surveys (18). A binary variable was then
created: $0 to $4999 or $5000 or more, as used previously (8,11,22).
Physical assets referred to homeownership, which was defined as a
categorical variable: homeowner, rented for cash, and occupied with-
out payment of cash rent (11). Social assets included educational
attainment and marital status. Educational attainment was defined
as a categorical variable: less than high school graduate, high
school graduate or GED, some college, including vocational/tech
school, and college graduate or more (11). Marital status was
defined as a categorical variable: married; widowed, divorced, or
separated; never married; and living with partner (11). Assets at T1
were reported.
Demographic characteristics
Key demographic characteristics include gender (female/male), age
category (18 to 39 years, 40 to 59 years, and 60 years or older), race/
ethnicity (Hispanic, non-Hispanic black, non-Hispanic white, and
Ettman et al., Sci. Adv. 8, eabm9737 (2022) 2 March 2022
SCIENCE ADVANCES | RESEARCH ARTICLE
8 of 9
other race, including non-Hispanic Asian and multiple races), and
household size (continuous variable, capped at 7).
Stressors
To examine the role of assets in protecting against persistent de-
pression, including in the face of stressors, we selected three stressors
as examples of COVID-19–induced stressors experienced during
the pandemic. We also aimed to understand whether assets modified
the relation between stressors and persistent depression. We used
three stressors that were highly associated with probable depression
and, therefore, were candidates for potential effect measure modi-
fication. Job loss, financial difficulties, and relationship problems
were each defined as a binary variable in response to the following
question: “Have any of the following affected your life as a result of
the coronavirus or COVID-19 outbreak?” Responses included the
following: “losing a job,” “having financial problems,” and “family
or relationship problems (for example, with your spouse or kids).”
Stressors at T1 were reported.
Statistical analysis
First, we calculated the prevalence of symptoms of persistent de-
pression by gender, age, and race/ethnicity. Prevalence measures of
symptoms of persistent depression were weighted unless otherwise
noted. We used complex probability weights to account for nonre-
sponse at T1 and T2 and to align with the U.S. adult population; the
survey weights allowed for estimates to represent the U.S. national
adult population (11). We conducted two-tailed 2 analyses to measure
the difference in distribution of symptoms of persistent depression
across groups. Significance was set at P<0.05. Demographic and
asset variables at T1 were used to predict symptoms of persistent
depression across time. Second, we calculated the weighted preva-
lence and odds along with their 95% CIs of symptoms of persistent
depression across financial assets, physical assets, and social assets.
Model 1 reported the unadjusted odds of symptoms of persistent de-
pression by each asset; thus, model 1 showed the bivariable relation
between symptoms of persistent depression and each asset, unad-
justed for any other variable. Models 2 through 6 reported the odds
of symptoms of persistent depression by each asset type, adjusting
for demographic characteristics of age, gender, race/ethnicity, and
household size (to account for sharing of assets within a household).
Thus, models 2 to 6 show the adjusted odds of symptoms of per-
sistent depression adjusting for age, gender, race/ethnicity, and house-
hold size, along with household income (model 2), household savings
(model 3), homeownership (model 4), education (model 5), and
marital status (model 6), respectively. Model 7 adjusted for all assets
and demographic characteristics together. Third, we assessed the
effect modification of assets on the relation between stressors and
symptoms of persistent depression and tested for interaction. To do
this, we estimated the predicted probability of symptoms of per-
sistent depression by the stressors of job loss, financial difficulties,
and relationship problems across each asset type, adjusting for de-
mographic characteristics and for the interaction of each asset with
each stressor. We used the margins command in STATA to calculate
the predicted probabilities of the interaction term combinations.
To estimate the predicted probabilities of symptoms of persistent
depression on interaction pairs, we used unweighted regres-
sion models in our margin commands, as consistent with recom-
mendations in the literature (46, 47) and reported unweighted
probabilities across interaction pairs for relevant comparison.
We graphed the predicted probabilities in a figure with 15 panels
representing each of the five asset and three stressor category
combinations.
A correlation table across different asset types is listed in table S1,
and a table with symptoms of persistent depression by asset types
and corresponding P value is listed in table S2. A table with predicted
probabilities and corresponding 95% CIs is listed in table 3. We con-
ducted maximum likelihood ratio tests to measure the difference
between each interaction term model and the relevant nested model
with only main terms; we determined significance of the interaction
terms using a P value cutoff of 0.05. Last, we calculated the prevalence
of symptoms of persistent depression by interaction group catego-
ries to understand the direction of the associations. Maximum like-
lihood ratio test results and unadjusted prevalence of symptoms of
persistent depression by asset and stressor groups are listed in table
S4 and fig. S1, respectively. Use of survey weights is described in
respective note of each figure and table. Analyses were conducted in
STATA 16.1.
SUPPLEMENTARY MATERIALS
Supplementary material for this article is available at https://science.org/doi/10.1126/
sciadv.abm9737
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Acknowledgments: We thank L. Sullivan for consulting on the methods used in this study.
Funding: Funding for T1 of the CLIMB survey came from the Rockefeller Foundation-Boston
University 3-D Commission grant number 2019 HTH 024 (S.G.). Funding for T2 of the CLIMB
survey came from the de Beaumont Foundation grant AGMT DTD 11/16/2020 (S.G.). Research
reported in this publication was supported by the National Institute on Minority Health and
Health Disparities of the National Institutes of Health under award number F31MD017133
(C.K.E.). The content is solely the responsibility of the authors and does not necessarily
represent the official views of the National Institutes of Health. Author contributions:
Conceptualization: C.K.E., P.M.V., and S.G. Data curation: S.G. and C.K.E. Formal analysis: C.K.E.
and L.T. Funding acquisition: C.K.E., S.G., B.C.C., R.H.B., and S.M.A. Methodology: C.K.E., P.M.V.,
S.G., L.T., I.W., and M.A.C. Supervision: S.G. and P.M.V. Writing–original draft: C.K.E. Writing–
review and editing: C.K.E., G.H.C., S.M.A., L.T., B.C.C., R.H.B., M.A.C., I.W., P.M.V., and S.G.
Competing interests: The authors declare that they have no competing interests. Data and
materials availability: All data needed to evaluate the conclusions in the paper are
present in the paper and/or the Supplementary Materials.
Submitted 31 October 2021
Accepted 6 January 2022
Published 2 March 2022
10.1126/sciadv.abm9737
... Inability to pay bills and lack of cash reserves increase risk of anxiety symptoms (7). Conversely, having more financial resources (e.g., income and savings) may buffer against risk of mental health difficulties (8,9). ...
... Data on income before taxes and gross financial assets from population-based registries were also included, as financial resources such as income and savings have been found to reduce risk of symptoms of common mental disorders like depression (8,9) These were household-based metrics and computed for the entire household if a person lived with others, further taking into account the familial economic situation. Financial assets included bank deposits, shares in equity funds, bonds, stocks, and market funds (37). ...
... Similarity in edges was high across networks estimated separately in each sample, supporting the appropriateness of combining data to maximize the accuracy of the model estimation (correlations ranged from = 0.970 to = 0.976). assessed diagnoses) to diverse financial challenges, such as lower income and insufficient cash reserves (1,3,7), job loss and unemployment (2,4), financial strain (6), and lower family savings and financial assets (8,9). The interrelatedness of financial factors and their symptom-level relationships revealed in our network analysis supports the notion that financial adversity is complex and multidimensional (15). ...
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Financial adversity increases the risk of common mental disorders. However, few studieshave assessed how multiple financial factors are related to individual symptoms of anxietyand depression. We applied a network approach to examine associations between objectiveregister-based and self-reported financial indicators, and symptoms of anxiety and depressionacross 49,750 randomly sampled Norwegian adults. Almost all measured symptoms wereassociated with at least one financial hardship or protective variable. Depressive symptomswere more strongly linked to financial difficulties compared to anxiety symptoms.Hopelessness was a key symptom tying financial factors to mental health adversities and wasassociated with greater financial dissatisfaction, inability to afford to keep one’s home warm,and unemployment. Experiencing sudden fear was linked with inability to afford healthyfood. Our findings point to the importance of financial factors, including those linked to basiclife circumstances, for population mental health and unravel granular associations withsymptoms of anxiety and depression.
... Participants include adults ages 18 years and older who completed at least two waves of the COVID- 19 and Life Stressors Impact on Mental Health and Well-being study (CLIMB) [16,19,32,39]. Wave 1 of the survey was administered March 31, 2020 -April 13, 2020 (T1), Wave 2 was administered March 23, 2021 -April 19, 2021 (T2), and Wave 3 was administered March 22, 2022-April 19, 2022. ...
... Survey weights were created to account for non-response, survey selection, and demographics that when applied made the sample representative of the U.S. More information on the CLIMB sample can be found in previous writing [16,17,32]. The final analytic sample for this paper included 1,271 participants. ...
... Within the financial asset groupings, the low income-low savings group reported the highest levels of probable depression at every time point and the high income-high savings group reported the lowest levels of probable depression at every time point. These findings were consistent with the literature that shows that socio-economic indicators were associated with worse mental health during the COVID-19 pandemic [18,19,32,57]. In an analysis of Household Pulse data from April 2020 to May 2021, Lee and Singh found that persons with income less than $25,000 had 2.3 times the odds of serious depression compared to persons with income of more than $200,000 [20]. ...
Article
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The prevalence of depression in U.S. adults during the COVID-19 pandemic has been high overall and particularly high among persons with fewer assets. Building on previous work on assets and mental health, we document the burden of depression in groups based on income and savings during the first two years of the COVID-19 pandemic. Using a nationally representative, longitudinal panel study of U.S. adults (N = 1,271) collected in April-May 2020 (T1), April-May 2021 (T2), and April-May 2022 (T3), we estimated the adjusted odds of reporting probable depression at any time during the COVID-19 pandemic with generalized estimating equations (GEE). We explored probable depression—defined as a score of ≥10 on the Patient Health Questionnaire-9 (PHQ-9)—by four asset groups, defined by median income (≥65,000)andsavings(65,000) and savings (≥20,000) categories. The prevalence of probable depression was consistently high in Spring 2020, Spring 2021, and Spring 2022 with 27.9% of U.S. adults reporting probable depression in Spring 2022. We found that there were four distinct asset groups that experienced different depression trajectories over the COVID-19 pandemic. Low income-low savings asset groups had the highest level of probable depression across time, reporting 3.7 times the odds (95% CI: 2.6, 5.3) of probable depression at any time relative to high income-high savings asset groups. While probable depression stayed relatively stable across time for most groups, the low income-low savings group reported significantly higher levels of probable depression at T2, compared to T1, and the high income-low savings group reported significantly higher levels of probable depression at T3 than T1. The weighted average of probable depression across time was 42.9% for low income-low savings groups, 24.3% for high income-low savings groups, 19.4% for low income-high savings groups, and 14.0% for high income-high savings groups. Efforts to ameliorate both savings and income may be necessary to mitigate the mental health consequences of pandemics.
... On the other hand, at younger ages, the relative changes in point estimates for the stressor effects reverse, and the confidence intervals expand. For example, at no days socializing in person and daily socializing in person, each additional stressor was associated with 0. 78 The patterns of online socialization were even less resolved. For females at age 25, the stressors were associated with .52 (95% CI [0.06, 0.99]) and .46 ...
... The prevalence and intensity of depression abruptly increased among populations worldwide during the early phase of the COVID-19 pandemic [26,[74][75][76][77][78]. The upsurge at the start of the pandemic followed years of gradual escalation of depression [79], particularly among adolescents and young adults [12,80]. ...
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Substantial increases in depression at the outset of the pandemic were previously reported in NCANDA, a longitudinal sample of adolescents and young adults. The current NCANDA study examined depression symptoms before and during the COVID-19 pandemic. It evaluated the influence of stressors and social behavior (e.g., in-person and online socializing) with linear mixed effects models. A strong, positive association between COVID-19-related stressors and depression symptoms was observed. The frequency of in-person socializing did not account for the totality of the changes in depression observed during the early COVID-19 pandemic. It may be that pandemic-related stressors counteracted the benefits of in-person interactions during the early stages of the COVID-19 pandemic. Future studies can continue to elucidate the interactions among psychosocial, genetic, and behavioral factors contributing to depression symptoms in the unprecedented context of the COVID-19 pandemic.
... The initial shock in depressive symptom levels distinguishing this second group from the consistently resilient group was related to increased financial and occupational worries at the onset of the pandemic and older age, with improvement in symptomatology related to more frequent engagement in physical activity. This is in line with previous findings identifying that financial assets protect against persistent depressive symptomatology during the present pandemic [40,41]. The initial shock displayed by older aged individuals may have been related to greater infection fears, previously related to depressive symptomatology [42], and possibly explained by the greater risk of severe illness and mortality in these adults [43,44]. ...
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Despite the presence of individual differences in the depressive symptom change in adults during the COVID-19 pandemic, most studies have investigated population-level changes in depression during the first year of the pandemic. This longitudinal repeated-measurement study obtained 39,259 observations from 4,361 adults assessed nine times over a 24-month period in Norway (March 2020 to March 2022). Using a Latent Change Score Mixture Model to investigate differential change patterns in depressive symptoms, five profiles were identified. Most adults revealed a consistently resilient (42.52%) or predominantly resilient pattern differentiated by an initial shock in symptomatology (13.17%). Another group exhibited consistently high depressive adversities (8.5%). One group showed mild deterioration with small increases in depressive symptomatology compared to onset levels (29.04%), and a second strong deterioration group exhibited clinically severe levels of gained symptoms over time (6.77%). Both deteriorating depressive symptom change patterns predicted the presence of a psychiatric diagnosis and treatment seeking at the end of the study period. Together, the absence of a preexisting psychiatric diagnosis at the onset of the pandemic and severe symptom increases during, combined with reports of psychiatric treatment seeking and diagnosis at the end of the study period, indicated that the strongly deteriorating subgroup represents an additional and newly emerged group of adults struggling with depressive problems. Factors related to general adverse change (lower education levels, lone residence), initial shocks prior to recovery (frequent information seeking, financial and occupational concerns), and resilience and recovery (older age, being in a relationship, physical activity) were identified. Binge drinking and belonging to an ethnic minority were influential predictors of the strongly deteriorating group. All major change patterns in depressive symptoms occurred during the first 3 months of the pandemic, suggesting this period represents a window of sensitivity for the development of long-lasting depressive states versus patterns of recovery and resilience. These findings call for increased vigilance of psychiatric symptoms during the initial phases of infectious disease outbreaks and highlight a specific target period for the implementation of preventive measures.
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Background Insomnia, depression, anxiety, and stigma are prevalent and often coexist in patients with Tuberculosis (TB), potentially exacerbating one another. However, the complex intrinsic associations among these four disorders remain unclear, particularly concerning the role of stigma in relation to the other disorders. Methods A cross-sectional study was conducted at West China Hospital and the Fourth People’s Hospital of Guangxi from November 2023 to June 2024. The levels of insomnia, depression, anxiety, and stigma among TB patients were assessed using the Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the TB-Related Stigma Scale (TRSS). Network analysis was used to identify the central and bridge symptoms and explore the role of stigma within the insomnia-depression-anxiety-stigma network. Results PHQ1 (anhedonia), GAD1 (nervousness), GAD5 (restlessness), and PHQ3 (sleep problems) are central to the network. Bridge symptoms, including PHQ3 (sleep problems), PSQI5 (sleep disturbances), and GAD5 (restlessness) link the depression, insomnia, and anxiety communities. TRSS1 (family’s negative perception) of the stigma community exhibited the highest betweenness and second highest bridge betweenness in the network, highlighting the mediating role of family support across insomnia and psychological symptoms. Additionally, the global strength invariance test indicates that gender, age and education level do not significantly impact the network structure. Conclusion Depression (anhedonia and sleep problems) and anxiety (nervousness and restlessness) are the primary concerns requiring intervention in TB patients. In addition, sleep problems act as a bridge in the overall network. Stigma, particularly negative perceptions from family, may play a crucial mediating role in sustaining the entire symptom network. Consequently, these symptoms could represent potential targets for intervention.
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Financial, material, and social assets are core drivers of access to salutary resources. However, there is a paucity of research about how non-income financial assets shape mental health. We explore the relation of financial assets with symptoms of depression and of anxiety using a nationally representative, longitudinal survey of U.S. adults fielded annually from 2020 to 2023 (n = 1,296 unique participants). We used multivariable logistic regression models to estimate the association of financial assets and financial stress separately and together with symptoms of depression (PHQ-9 > 9), anxiety (GAD-7 > 9), and their co-occurrence, controlling for demographic indicators and year fixed effects. We found, first, that adults with <5,000inaccruedfinancialassetsreportedovertwotimestheoddsofpositivescreenfordepression,anxiety,andcooccurringdepressionandanxiety,respectively,asadultswith5,000 in accrued financial assets reported over two times the odds of positive screen for depression, anxiety, and co-occurring depression and anxiety, respectively, as adults with ≥100,000 in financial assets. Second, when controlling for accrued financial assets, annual household income was not associated with symptoms of anxiety. Third, the gap in positive screen for depression between household financial assets groups stayed consistent and did not differ significantly over the study period. Annual income alone does not capture the influence of all financial assets on mental health.
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The burden of generalized anxiety disorder (GAD) accrued disproportionately over the COVID-19 pandemic to low-resource populations. Using a longitudinal, nationally representative study of U.S. adults, we used generalized estimating equations (GEE) to estimate the burden of positive screen for GAD (GAD-7 ≥10) over time. The final sample included 1270 adults ≥18 who completed the CLIMB (COVID-19 and Life Stressors Impact on Mental Health and Well-being) study, collected in Spring 2020, 2021, and 2022. The national prevalence of positive screen for GAD decreased from 24.4% in 2020 to 21.3% in 2022 (p<0.05). Across the COVID-19 pandemic, factors associated with increased odds of positive screen for GAD were: lower income (OR:2.06 [95%CI: 1.17,3.63] for ≤19,999relativeto19,999 relative to ≥75,000), younger age (OR:2.55 [95% CI:1.67,3.89] for ages 18-39 relative to ≥60 years), and having contracted COVID-19 (OR:1.54 [95%CI:1.12,2.14]). Experiencing stressors was associated with 14% increased odds of positive screen for GAD for each additional stressor. The 2020 stressors most strongly associated with positive screen for GAD in 2022 were job loss and difficulties paying rent. Efforts to address the stressors affecting groups with the highest burden of anxiety post-pandemic may help to mitigate poor mental health exacerbated during the COVID-19 pandemic.
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Psychiatric epidemiology has led to substantial progress in our understanding of the causes of mental health disorders. The increasing sophistication of etiologic psychiatric research has been accompanied by a greater focus on the biological and genetic causes of psychiatric disorders, to some extent diverging from field’s early focus on the burden of poor mental health due to a breadth of social and economic conditions. We argue that the moment is ripe for advancing a mental health epidemiology that can reconnect the field to these earlier—and still central—concerns while retaining the strengths of psychiatric epidemiology. Embracing 5 considerations can help advance the evolving field of mental health epidemiology. First, conceptually, an ambitious vision for the future of the field necessitates investment in refining our definitions and methodologies. Second, there is a need for a renewed focus on the macrosocial determinants of mental health. Third, a deeper engagement with mental health inequities should be central to our scholarship. Fourth, the field would benefit from a more deliberate assessment of the mechanisms leading to adverse mental health outcomes, which can then be used to inform novel interventions. Finally, realizing this future is contingent upon a wholesale commitment to studying population mental health globally. This article is part of a Special Collection on Mental Health.
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Background The COVID-19 pandemic and its consequences have been associated with an increase in poor population mental health. We assessed how depressive symptoms changed among U.S. adults over the course of the COVID-19 pandemic and identified the key risk factors for these symptoms. Methods Longitudinal panel study of a nationally representative group of U.S. adults ages 18 years and older surveyed in March-April 2020 (Time 1; N=1441) and March-April 2021 (Time 2; N=1161) in the COVID-19 and Life Stressors Impact on Mental Health and Well-being study (CLIMB). The Patient Health Questionnaire-9 (PHQ-9) was used to define elevated depressive symptoms (cut-off ≥10) and depressive symptoms score (0-27). Findings The prevalence of elevated depressive symptoms persisted from 27.8% in 2020 (95% CI: 24.9, 30.9) to 32.8% in 2021 (95% CI: 29.1, 36.8). Over time, the central drivers of depressive symptoms were low household income, not being married, and experiencing multiple stressors during the COVID-19 pandemic. The odds ratio of elevated depressive symptoms for low income relative to high income persons increased from 2.3 (95% CI: 1.2, 4.2) in 2020 to 7.0 (95% CI: 3.7, 13.3) in 2021. Fewer people reported experiencing 4 or more COVID-19 stressors in 2021 than in 2020 (47.5% in 2020 vs 37.1% in 2021), but the odds ratio of elevated depressive symptoms associated with 4 or more stressors relative to 1 stressor or less increased from 1.9 (95% CI: 1.2, 3.1) in 2020 to 5.4 (95% CI: 3.2, 9.2) in 2021. Interpretation The burden of depressive symptoms in the U.S. adult population increased over the course of the COVID-19 pandemic. Mental health gaps grew between populations with different assets and stressor experiences during the COVID-19 pandemic. Funding CLIMB Time 1 was sponsored by the Rockefeller Foundation-Boston University 3-D Commission. CLIMB Time 2 was sponsored by the de Beaumont Foundation.
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Crises such as the COVID-19 pandemic are known to exacerbate depression and anxiety, though their temporal trajectories remain under-investigated. The present study aims to investigate fluctuations in depression and anxiety using the COVID-19 pandemic as a model crisis. A total of 1512 adults living in the United States enrolled in this online study beginning April 2, 2020 and were assessed weekly for 10 weeks (until June 4, 2020). We measured depression and anxiety using the Zung Self-Rating Depression scale and State-Trait Anxiety Inventory (state subscale), respectively, along with demographic and COVID-related surveys. Linear mixed-effects models were used to examine factors contributing to longitudinal changes in depression and anxiety. We found that depression and anxiety levels were high in early April, but declined over time. Being female, younger age, lower-income, and previous psychiatric diagnosis correlated with higher overall levels of anxiety and depression; being married additionally correlated with lower overall levels of depression, but not anxiety. Importantly, worsening of COVID-related economic impact and increase in projected pandemic duration exacerbated both depression and anxiety over time. Finally, increasing levels of informedness correlated with decreasing levels of depression, while increased COVID-19 severity (i.e., 7-day change in cases) and social media use were positively associated with anxiety over time. These findings not only provide evidence for overall emotional adaptation during the initial weeks of the pandemic, but also provide insight into overlapping, yet distinct, factors contributing to depression and anxiety throughout the first wave of the pandemic.
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Objective To document the prevalence of anxiety disorders in the USA during the COVID-19 pandemic. Design A cross-sectional analysis. Setting A nationally representative sample in the USA between 31 March and 13 April 2020. Participants 1450 English-speaking adult participants in the AmeriSpeak Panel. AmeriSpeak is a probability-based panel designed to be representative of households in the USA. Main outcome measures Prevalence of probable generalised anxiety disorder (GAD) using the GAD-7 and post-traumatic stress symptoms (PTSS) using the four-item PTSD (post-traumatic stress disorder) checklist. Both outcomes were stratified by demographics and COVID-19-related stressors. Results The majority of participants were female (51.8%), non-Hispanic white (62.9%) and reported a household saving of $5000 or more. Those between 18 and 29 years old were the largest age group (38.1%) compared with 40–59 years (32.0%) and 60 years or more (29.9%). The prevalence of probable GAD was 10.9% (95% CI 9.1% to 13.2%) and the prevalence of PTSS was 21.7% (95% CI 19.1% to 24.6%). Among participants reporting five or more COVID-19-related stressors, the prevalence of probable GAD was 20.5% (95% CI 16.1% to 25.8%) and the prevalence of PTSS was 35.7% (95% CI 30.2% to 41.6%). Experiencing five or more COVID-19-related stressors was a predictor of both probable GAD (OR=4.5, 95% CI 2.3 to 8.8) and PTSS (OR=3.3, 95% CI 2.1 to 5.1). Conclusions The prevalence of probable anxiety disorders in the USA, as the COVID-19 pandemic and policies implemented to tackle it unfolded, is higher than estimates reported prior to the pandemic and estimates reported following other mass traumatic events. Exposure to COVID-19-related stressors is associated with higher prevalence of both probable GAD and PTSS, highlighting the role these stressors play in increasing the risk of developing anxiety disorders in the USA. Mitigation and recovery policies should take into account the mental health toll the pandemic had on the USA population.
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Aims Markedly elevated adverse mental health symptoms were widely observed early in the coronavirus disease-2019 (COVID-19) pandemic. Unlike the U.S., where cross-sectional data indicate anxiety and depression symptoms have remained elevated, such symptoms reportedly declined in the U.K., according to analysis of repeated measures from a large-scale longitudinal study. However, nearly 40% of U.K. respondents (those who did not complete multiple follow-up surveys) were excluded from analysis, suggesting that survivorship bias might partially explain this discrepancy. We therefore sought to assess survivorship bias among participants in our longitudinal survey study as part of The COVID-19 Outbreak Public Evaluation (COPE) Initiative. Methods Survivorship bias was assessed in 4039 U.S. respondents who completed surveys including the assessment of mental health as part of The COPE Initiative in April 2020 and were invited to complete follow-up surveys. Participants completed validated screening instruments for symptoms of anxiety, depression and insomnia. Survivorship bias was assessed for (1) demographic differences in follow-up survey participation, (2) differences in initial adverse mental health symptom prevalence adjusted for demographic factors and (3) differences in follow-up survey participation based on mental health experiences adjusted for demographic factors. Results Adjusting for demographics, individuals who completed only one or two out of four surveys had significantly higher prevalence of anxiety and depression symptoms in April 2020 (e.g. one-survey v . four-survey, anxiety symptoms, adjusted prevalence ratio [aPR]: 1.30, 95% confidence interval [CI]: 1.08–1.55, p = 0.0045; depression symptoms, aPR: 1.43, 95% CI: 1.17–1.75, p = 0.00052). Moreover, individuals who experienced incident anxiety or depression symptoms had significantly higher adjusted odds of not completing follow-up surveys (adjusted odds ratio [aOR]: 1.68, 95% CI: 1.22–2.31, p = 0.0015, aOR: 1.56, 95% CI: 1.15–2.12, p = 0.0046, respectively). Conclusions Our findings reveal significant survivorship bias among longitudinal survey respondents, indicating that restricting analytic samples to only respondents who provide repeated assessments in longitudinal survey studies could lead to overly optimistic interpretations of mental health trends over time. Cross-sectional or planned missing data designs may provide more accurate estimates of population-level adverse mental health symptom prevalence than longitudinal surveys.
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The novel coronavirus disease (COVID-19) has repeatedly been reported to impair mental health. This longitudinal study evaluated mental health at the emergence of the COVID-19 pandemic (t1) and 6 months later (t2) in Austria. Indicators of mental health were depression (PHQ-9), anxiety (GAD-7), sleep quality (ISI), perceived stress (PSS-10), as well as quality of life (WHO-QOL BREF) and well-being (WHO-5). In total, N = 437 individuals participated in both surveys (52.9% women). The number of participants with clinically relevant depressive, anxiety, or insomnia symptoms did not differ statistically significantly between t1 and t2 (p ≥ 0.48). The prevalence of moderate or severe (clinically relevant) (1) depressive symptoms changed from 18.3% to 19.7% (p = 0.48), (2) anxiety symptoms from 16.5 to 15.6% (p = 0.67), and insomnia from 14.6 to 15.6% (p = 0.69) from t1 to t2. Bonferroni-corrected t-tests showed that the stress level (PSS-10) decreased, and well-being (WHO-5) increased. However, effect sizes do not seem to be clinically relevant (Cohen‘s d < 0.2). Results suggest that detrimental health consequences of the COVID-19 pandemic persisted several months after its outbreak and the end of the lockdown measures, respectively. Regarding well-being and stress, there is a slight trend toward improvement.
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The spread of disease and increase in deaths during large outbreaks of transmissible diseases is often associated with fear and grief (1). Social restrictions, limits on operating nonessential businesses, and other measures to reduce pandemic-related mortality and morbidity can lead to isolation and unemployment or underemployment, further increasing the risk for mental health problems (2). To rapidly monitor changes in mental health status and access to care during the COVID-19 pandemic, CDC partnered with the U.S. Census Bureau to conduct the Household Pulse Survey (HPS). This report describes trends in the percentage of adults with symptoms of an anxiety disorder or a depressive disorder and those who sought mental health services. During August 19, 2020-February 1, 2021, the percentage of adults with symptoms of an anxiety or a depressive disorder during the past 7 days increased significantly (from 36.4% to 41.5%), as did the percentage reporting that they needed but did not receive mental health counseling or therapy during the past 4 weeks (from 9.2% to 11.7%). Increases were largest among adults aged 18-29 years and among those with less than a high school education. HPS data can be used in near real time to evaluate the impact of strategies that address mental health status and care of adults during the COVID-19 pandemic and to guide interventions for groups that are disproportionately affected.
Article
The COVID-19 pandemic has been associated with mental health consequences due to direct (i.e., SARS-CoV-2 infection, potentially due to neuronal or astrocytic infection, microvascular, or inflammatory mechanisms) and indirect (i.e., social and economic impacts of COVID-19 prevention measures) mechanisms. Investigation of mental health in a region with one of the longest lockdowns and lowest COVID-19 prevalence globally (Victoria, Australia) allowed for evaluation of mental health in the absence of direct pandemic mental health consequences. Surveys were administered during 15-24 September 2020 to Victorian residents aged ≥18 years for The COVID-19 Outbreak Public Evaluation (COPE) Initiative. Responses were compared cross-sectionally with April-2020 data, and longitudinally among respondents who completed both surveys. Multivariable Poisson regressions were used to estimate prevalence ratios for adverse mental health symptoms, substance use, and suicidal ideation adjusted for demographics, sleep, and behaviours (e.g., screen-time, outdoor-time). In September-2020, among 1157 Victorians, one-third reported anxiety or depressive disorder symptoms, one-fifth reported suicidal ideation, and one-tenth reported having seriously considered suicide within 30 days. Young adults, unpaid caregivers, those with disabilities, and those with pre-existing psychiatric or sleep conditions showed increased prevalence of adverse mental health symptoms. Prevalence of symptoms of burnout, anxiety, and depressive disorder were unchanged between April-2020 and September-2020. Persistently common experiences of adverse mental health symptoms despite low SARS-CoV-2 prevalence during prolonged lockdown highlight the urgent need for mental health support services.
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Background : COVID-19 pandemic has major ramifications for global health and economy, with growing concerns about economic recession and implications for mental health. Here we investigated the associations between pandemic-related income loss with financial strain and mental health trajectories over a 1-month course, in two independent cohorts. Methods : Two independent studies were conducted in the U.S and in Israel at the beginning of the outbreak (March-April 2020, T1; study I: N = 2,904, study II: N = 1,267) and at a 1-month follow-up (T2; study I: N = 1,318, study II: N = 241). Mixed-effects models were applied to assess associations among COVID-19-related income loss, financial strain, and pandemic-related worries about health, with anxiety and depression, controlling for multiple covariates including pre-COVID-19 income. Results : In both studies, income loss and financial strain were associated with greater depressive symptoms at T1, above and beyond T1 anxiety, worries about health, and pre-COVID-19 income. Worsening of income loss was associated with exacerbation of depression at T2 in both studies. Worsening of subjective financial strain was associated with exacerbation of depression at T2 in one study (US). Conclusions : Income loss and financial strain were uniquely associated with depressive symptoms and their exacerbation over time, above and beyond pandemic-related anxiety. In times when a myriad of stressors are affecting mental health worldwide, our findings reveal specific links between the economic impact of COVID-19 and psychiatric outcomes.
Article
Background The mental health of the UK population declined at the onset of the COVID-19 pandemic. Convenience sample surveys indicate that recovery began soon after. Using a probability sample, we tracked mental health during the pandemic to characterise mental health trajectories and identify predictors of deterioration. Methods This study was a secondary analysis of five waves of the UK Household Longitudinal Study (a large, national, probability-based survey that has been collecting data continuously since January, 2009) from late April to early October, 2020 and pre-pandemic data taken from 2018–19. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). We used latent class mixed models to identify discrete mental health trajectories and fixed-effects regression to identify predictors of change in mental health. Findings Mental health was assessed in 19 763 adults (≥16 years; 11 477 [58·1%] women and 8287 [41·9%] men; 3453 [17·5%] participants from minority ethnic groups). Mean population mental health deteriorated with the onset of the pandemic and did not begin improving until July, 2020. Latent class analysis identified five distinct mental health trajectories up to October 2020. Most individuals in the population had either consistently good (7437 [39·3%] participants) or consistently very good (7623 [37·5%] participants) mental health across the first 6 months of the pandemic. A recovering group (1727 [12·0%] participants) showed worsened mental health during the initial shock of the pandemic and then returned to around pre-pandemic levels of mental health by October, 2020. The two remaining groups were characterised by poor mental health throughout the observation period; for one group, (523 [4·1%] participants) there was an initial worsening in mental health that was sustained with highly elevated scores. The other group (1011 [7·0%] participants) had little initial acute deterioration in their mental health, but reported a steady and sustained decline in mental health over time. These last two groups were more likely to have pre-existing mental or physical ill-health, to live in deprived neighbourhoods, and be of Asian, Black or mixed ethnicity. Infection with SARS-CoV-2, local lockdown, and financial difficulties all predicted a subsequent deterioration in mental health. Interpretation Between April and October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. Around one in nine individuals had deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions, or infection with SARS-CoV-2 might benefit most from early intervention.
Article
This study uses a risk and resilience framework to examine short-term self-reported changes in relationship conflict early in the COVID-19 pandemic (March and April 2020). Longitudinal data from U.S. adults in a romantic relationship ( N = 291) were collected via three waves of an online survey. Participants self-reported anxiety, depression, increased alcohol use, and dyadic coping since the pandemic. Relationship conflict variables included whether the participant reported that they and their partner “had disagreements related to the Coronavirus,” “had more disagreements than usual,” “had more verbal fights than usual,” and “had more physical fights than usual” in the past two weeks. Analyses controlled for sociodemographic characteristics as well as days spent in lockdown and employment change due to COVID-19. Results indicated that couples’ disagreement and verbal fighting scores increased from Time 1 to Time 2, but disagreements related to COVID-19 and physical fighting did not. Couples with higher levels of dyadic coping reported fewer fights and disagreements on average. However, dyadic coping did not buffer participants from increases in relationship conflict. Increased alcohol use since the pandemic was positively associated with disagreements related to COVID-19, disagreement scores, and verbal fighting scores. More days spent in lockdown was associated with increases in disagreements related to COVID-19. The conditions created by COVID-19 may contribute to worsening relationship conflict, even among couples who start with high levels of dyadic coping. Depression and alcohol use may contribute to poorer relationship quality during the pandemic. There is need for enhanced intervention and mental health supports to mitigate the potential effects of the pandemic on couples’ relationship functioning.