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Background. Shift work is characterized by employees working outside the standard hours of 7:00 am to 6:00 pm. Because shift work includes night work, the normal sleep-wake cycle (circadian rhythm) is disrupted, with potential consequences for shift workers' physical and mental health.Objectives. To assess the pooled effects of shift work on mental health and to evaluate whether these differ in men and women.Search Methods. We searched PubMed, Scopus, and Web of Science databases for peer-reviewed or government reports published up to August 2018Selection Criteria. To be included, studies had to be longitudinal or case-control studies of shift work exposure associated with adverse mental health outcomes. For subanalyses, we grouped these outcomes as anxiety symptoms, depressive symptoms, or general poor mental health symptoms.Data Collection and Analysis. We followed the Meta-Analysis of Observational Studies in Epidemiology Group guidelines. We extracted adjusted risk estimates for each study to calculate pooled effect sizes (ESs) using random effect models and metaregression analysis to explore sources of heterogeneity.Main Results. We included 7 longitudinal studies, with 28 431 unique participants. Shift work was associated with increased overall risk of adverse mental health outcomes combined (ES = 1.28; 95% confidence interval [CI] = 1.02, 1.62; I2 = 70.6%) and specifically for depressive symptoms (ES = 1.33; 95% CI = 1.02, 1.74; I2 = 31.5%). Gender differences explained more than 90% of heterogeneity, with female shift workers more likely to experience depressive symptoms than female non-shift workers (odds ratio = 1.73; 95% CI = 1.39, 2.14).Authors' Conclusions. To our knowledge, this is the first meta-analysis to investigate the pooled effects of shift work on the risk of poor mental health, including subanalyses by type of poor mental health and gender. Shift workers, particularly women, are at increased risk for poor mental health, particularly depressive symptoms.Public Health Implications. Depression accounts for 4.3% of the global burden of disease and incidence, with mental disorders worldwide predicted to cost US $16.3 million by 2030. With 1 in 5 people in the United States and Europe doing shift work, and the increased risk of poor mental health among shift workers, shift work industries are a priority context for reducing this burden. Workplace health promotion programs and policies are needed to minimize shift workers' risk of poor mental health. (Am J Public Health. Published online ahead of print September 19, 2019: e1-e8. doi:10.2105/AJPH.2019.305278).
Content may be subject to copyright.
Shift Work and Poor Mental Health: A
Meta-Analysis of Longitudinal Studies
Luciana Torquati, PhD, Gregore I. Mielke, PhD, Wendy J. Brown, PhD, Nicola W. Burton, PhD, and Tracy L. Kolbe-Alexander, PhD
Background. Shift work is characterized by employees working
outside the standard hours of 7:00 AM to 6:00 PM. Because shift work
includes night work, the normal sleepwake cycle (circadian rhythm) is
disrupted, with potential consequences for shift workersphysical and
mental health.
Objectives. To assess the pooled effects of shift work on mental health
and to evaluate whether these differ in men and women.
Search Methods. We searched PubMed, Scopus, and Web of Science
databases for peer-reviewed or government reports published up to
August 2018
Selection Criteria. To be included, studies had to be longitudinal or case
control studies of shift work exposure associated with adverse mental
health outcomes. For subanalyses, we grouped these outcomes as anxiety
symptoms, depressive symptoms, or general poor mental health
symptoms.
Data Collection and Analysis. We followed the Meta-Analysis of Ob-
servational Studies in Epidemiology Group guidelines. We extracted ad-
justed risk estimates for each study to calculate pooled effect sizes (ESs)
using random effect models and metaregression analysis to explore
sources of heterogeneity.
Main Results. We included 7 longitudinal studies, with 28 431 unique
participants. Shift work was associated with increased overall risk of
adverse mental health outcomes combined (ES = 1.28; 95% condence
interval [CI] = 1.02, 1.62; I
2
= 70.6%) and specically for depressive
symptoms (ES = 1.33; 95% CI = 1.02, 1.74; I
2
= 31.5%). Gender differences
explained more than 90% of heterogeneity, with female shift workers
more likely to experience depressive symptoms than female nonshift
workers (odds ratio = 1.73; 95% CI = 1.39, 2.14).
AuthorsConclusions. To our knowledge, this is the rst meta-analysis to
investigate the pooled effects of shift work on the risk of poor mental
health, including subanalyses by type of poor mental health and gender.
Shift workers, particularly women, are at increased risk for poor mental
health, particularly depressive symptoms.
Public Health Implications. Depression accounts for 4.3% of the global
burden of disease and incidence, with mental disorders worldwide predicted
to cost US $16.3 million by 2030. With 1 in 5 people in the United States and
Europe doing shift work, and the increased risk of poor mental health among
shift workers, shift work industries are a priority context for reducing this
burden. Workplace health promotion programs and policies are needed
to minimize shift workersrisk of poor mental health. (Am J Public Health.
2019;109:e13e20. doi:10.2105/AJPH.2019.305278)
PLAIN-LANGUAGE SUMMARY
Many industries, such as transportation,
health care, and hospitality, depend on em-
ployees working outside standard 7:00 AM to
6:00 PM hours. Altering normal sleeping hours
can affect shift workersphysical and mental
health. We analyzed data from 28 431 unique
participants in studies that compared mental
health outcomes in nonshift versus shift
workers. Compared to nonshift workers,
shift workers had a 30% higher risk of poor
mental health and depression. Interestingly,
women shift workers had a 70% higher risk of
depression compared to women working day
shifts. Poor mental health costs millions of
dollars to health care systems and can affect
peoples ability to work and have good quality
of life. It is important to have programs and
policies that can minimize shift workersrisk
of poor mental health.
November 2019, Vol 109, No. 11 AJPH Torquati et al. Peer Reviewed Systematic Review e13
AJPH OPEN-THEMED RESEARCH
Shift work is characterized by alternating
and rotating morning, afternoon, and
night shifts, with employees often working
outside the standard hours of 7:00 AM to 6:00
PM.
1
About 20% of the working population in
the United States, Australia, and Europe are
engaged in this work pattern.
2,3
Given service
and production demands, industries in the
transportation, hospitality, manufacturing,
and health care sectors depend on shift work.
3
Because shift work includes night work, the
normal sleepwake cycle (circadian rhythm)
is disrupted, with potential consequences for
shift workersphysical and mental health.
4,5
Altered sleep patterns owing to shift work
have been associated with irritability, de-
pressed mood, anxiety, and nervousness.
6,7
Sleeping at odd times of the day together with
shift schedules create challenges for main-
taining healthy worklife balance in shift
workers, as opportunities for family, social,
and leisure activities are constrained.
8,9
This
may lead to social isolation and contribute
to poor mental health in this occupational
group.
8
Mental disorders accounted for
14.4% of the total global burden of disease in
2017
10
and are estimated to cost the health
system billions of dollars.
11
Cross-sectional studies have suggested a
positive association between shift work and
poor mental health.
12
In a large cohort study
of Dutch employees, Driesen et al. reported
that shift workers were twice as likely to
report depressed mood as were those working
day-only shifts (odds ratio [OR] = 2.05; 95%
condence interval [CI] = 1.52, 2.77).
12
Similarly, Lee et al. found that Korean nurses
who worked shifts had 1.5 times greater odds
of experiencing higher severity of depressive
symptoms than did nonshift workers
(OR = 1.52; CI = 1.38, 1.67).
13
Longitudinal
studies have, however, provided conicting
results. Some studies have found increased
risks of anxiety and depression in shift
workers,
14,15
whereas others found that shift
workers had better psychological well-being
and general mental health than did nonshift
workers.
16,17
The contradictory ndings
from these studies may be explained by dif-
ferences in occupations, industry sectors, and
the context of shift work in different
countries.
Tolerance to shift work is dened as the
ability to adapt to it without adverse health
effects. This may explain individual
differences in responses to shift work expo-
sure,
18
as well as gender differences. A recent
systematic review of data from 60 studies of
several occupations in 23 countries has shown
that male shift workers had better sleep and
less fatigue than did female shift workers.
18
A
prospective study of working conditions in
the general Swedish population has shown
that female shift workers had a higher risk of
low psychological well-being than did male
shift workers (risk ratio [RR] = 1.60; 95%
CI = 1.00, 2.80).
17
By contrast, Bara and
Arber
15
reported that male night workers in
the United Kingdom had higher risks of poor
mental health (OR = 2.58; 95% CI = 1.22,
5.48) and anxiety or depression (OR = 6.08;
95% CI = 2.06, 17.92) than did their female
counterparts (OR = 1.06; 95% CI = 0.49,
2.27 and 1.69; 95% CI = 0.60, 4.76, re-
spectively). Given these ndings, the associ-
ations between shift work and the risk of poor
mental health in men and women are unclear.
Therefore, we assessed the pooled effects of
shift work exposure on mental health and in
specic outcomes and evaluated whether
these differ in men and women.
METHODS
We followed the framework proposed by
the Meta-Analysis of Observational Studies in
Epidemiology group
19
for design, research
strategy, analysis, and reporting. We searched
peer-reviewed publications in 3 major data-
bases: PubMed, Scopus, and Web of Science.
We performed all searches using title or ab-
stract and keywords elds combining shift
work and mental health terms, with publi-
cation up to August 2018. The search terms
we used to identify studies with adverse
mental health outcomes were based on a
previous publication on optimal strategies
to retrieve mental health content in
MEDLINE
20
and included truncated
wildcard terms such as depress*,”“anxi*,
psychol*,and stress*and other key words
including mental health,”“mental distress,
and mental OR psychological well-being.
We used hierarchical MeSH (Medical Subject
Headings) terms in the PubMed database to
optimize inclusion of a range of adverse mental
health outcomes (i.e., mental health[mh];
emotions[mh]; mental disorders[mh]).
Shift work search terms were similar to those
used in a previous systematic review on shift
work and metabolic risk factors
21
:shift work
OR shiftworkOR irregular hoursOR
rotating shiftOR rotating hours.A
complete list of all search term combinations
used in each database is available on request.
Referencelistsoftheincludedarticleswerealso
scanned for relevant studies and for systematic
reviews on shift work and mental health.
Two authors (L. T. and T. L. K.-A.)
scanned titles and abstracts independently to
determine whether each article met the fol-
lowing inclusion criteria:
1. was a prospective cohort or casecontrol
study;
2. included a measure of shift work dened as
either night shift, irregular work, rota-
tional work, or a combination of these;
3. provided an estimate of risk of an adverse
mental health outcome that was assessed
via self-report using a validated scale score,
reported as diagnosed by a professional as
mental illness (e.g., anxiety, clinical de-
pression), or both
22
;
4. described shift work as the main exposure
and had an independent referent group;
5. was written in English; and
6. was a peer-reviewed journal article or
government report.
We excluded studies if shift work expo-
sure was a secondary factor to insomnia,
family or social conict, or similar outcomes.
For example, we excluded studies of job strain
ABOUT THE AUTHORS
Luciana Torquati is with Sport and Health Sciences, University of Exeter, Exeter, UK. Luciana Torquati, Gregore I. Mielke,
Wendy J. Brown, and Tracy L. Kolbe-Alexander are with the Centre for Research in Exercise, Physical Activity, and Health,
University of Queensland, Brisbane, Australia. Nicola W. Burton is with the School of Applied Psychology, Griffith
University, Mt Gravatt, Australia. Tracy L. Kolbe-Alexander is with the School of Health & Well-Being, University of
Southern Queensland, Ipswich, Australia.
Correspondence should be sent to Dr. Luciana Torquati, Sport and Health Sciences, University of Exeter, St Lukes campus, EX1
2LU Exeter, UK (e-mail: l.torquati@exeter.ac.uk). Reprints can be ordered at http://www.ajph.org by cl icking the Reprintslink.
This article was accepted July 10, 2019.
doi: 10.2105/AJPH.2019.305278
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e14 Systematic Review Peer Reviewed Torquati et al. AJPH November 2019, Vol 109, No. 11
or relationships at work and similar exposures.
We did not exclude any studies based on year
of publication.
After selecting potentially eligible studies
based on title or abstract, we performed a
full-text scan. Disagreement on study in-
clusion arose for 2 studies, which analyzed
data from the same cohort, but with differ-
ent outcomes.
7,23
These were resolved by
consulting with a third reviewer to reach
consensus, which was to include the
study with the most recent analysis.
7
After
full-text review, 7 articles met all the selection
criteria; their data were included in the
meta-analysis.
Data Extraction
Two authors independently extracted
data from each included study. This in-
cluded information on author and year,
study design, follow-up duration and
years, sample size, participantsage and
gender, industry in which participants
worked and cohort name (if ongoing
cohort study), denition and assessment
of shift work, duration of exposure to
shift work (if reported), adverse mental
health outcome, and variables used in the
adjusted model for risk estimate. Risk es-
timates were extracted for both crude and
adjusted models of OR, RR, or hazard
ratio (HR). We included these in the an-
alyses if they were measured using vali-
datedtoolsandwerespecictothe
outcome reported (e.g., General Health
Questionnaire used to identify poor
mental health).
Risk of Bias Assessment
We used a tool from a previous
meta-analysis on shift workersrisk
of poor physical health outcomes
24
to
assess the risk of bias in the included
studies in our meta-analysis. Two authors
(L. T. and T. L. K.-A.) independently
assessed the following major domains
of bias:
dexposure denition,
dexposure assessment,
dreliability of assessments,
dconfounding, and
danalysis methods (research-specic bias).
The tool also considered the following
minor domains of bias:
dblinding of assessors,
dattrition,
dselective reporting,
dfunding, and
dconict of interest.
We rated each criterion as high, low, or
unclear risk of bias, as described in Appendix I.
Based on these ratings, we classied studies as
low (if all major domains and >2 minor
domains scored low risk), moderate (if 4
major domains and 2 minor domains scored
low risk), or high risk (if <4 major domains
scored low risk) of bias.
Data Management and Statistical
Analyses
We extracted ORs, RRs, and HRs from
each study as a measure of risk estimates,
including their respective SEs or 95% CIs.
The reference group we used in all studies was
nonshift workers, dened as those workers
either not doing rotational shifts with night
shift included or those who worked only day
shifts (7:00 AM6:00 PM). For each study, we
extracted those estimates with the highest
level of adjustment for covariates. When
studies calculated the risk estimates for men
and women separately, we included 2 in-
dependent estimates in the meta-analysis. For
studies with analyses of subgroups based on
years of shift work, we included data from
cumulative groups wherever possible. If a
study included more than 1 type of work
schedule (e.g., rotational shifts or permanent
night shift), we extracted risk estimates for
both groups. We created 4 groups of adverse
mental health outcomes for the analyses. A
combined group included all the outcomes
(overall effect), and for the subanalyses we
divided this into 3 mutually exclusive groups
reecting the type of outcome: depressive
symptoms, anxiety symptoms, and general
poor mental health symptoms.
We used risk estimates to calculate the
pooled effect size (ES) using random effects
models to assess the association between
shift work and overall risk of adverse mental
health outcomes combined (overall effect).
We chose this approach because, unlike
xed-effect models, random effect models
assume that the shift work effect might vary
between studies as well as participants in each
study.
25
We rst conducted an overall effect
analysis, including all estimates in a non-
exposure versus exposure meta-analysis, with
shift work as the exposure group. We then
conducted 2 subgroup analyses: (1) by type of
adverse mental health outcomes (depressive
symptoms, anxiety symptoms, general poor
mental health symptoms), and (2) by gender
to assess the risk of adverse mental health
outcomes combined.
We used the I
2
test to assess heterogeneity.
To assess robustness of data and potential
sources of heterogeneity, we conducted
sensitivity analyses using univariate metare-
gression. Variables included in the sensitivity
analyses were type of poor mental health
outcome (depressive symptoms, anxiety
symptoms, general poor mental health
symptoms); gender; exposure denition (low
or high risk of bias); industry or occupation
(nursing, other); follow-up (£1 year, >1
year); risk of bias (moderate, high); average
age of the cohort (£35 vs >35 years); sample
size (<1000, >1000); and tool used to
measure outcomes (General Health Ques-
tionnaire, other). We used funnel plots and
the Egger test to evaluate publication bias. We
conducted all analyses using Stata version 12.1
(StataCorp, College Station, TX).
RESULTS
The results of the systematic review are
shown in Figure 1. We retrieved 1902 articles
and, after removing duplicates, reviewed
639 by title and abstract and 51 by full text. Of
the eligible studies, we did not include 2
studies because of data format (continuous
data),
16,26
which resulted in 7 studies being
included in the meta-analysis. These articles
included 14 separate estimates of the associ-
ation between shift work and adverse
mental health outcomes.
Study Characteristics
Study characteristics are summarized in
Table 1. All studies were prospective cohort
studies, 3 had a follow-up of 1 year or less, and
4 had a follow-up of between 2 and 10 years.
The latter studies had larger sample sizes than
did those with 1 year or less follow-up
AJPH OPEN-THEMED RESEARCH
November 2019, Vol 109, No. 11 AJPH Torquati et al. Peer Reviewed Systematic Review e15
(n = 371582 vs 4209765, respectively).
15,17,27,28
Most of the studies (n = 4) measured gen-
eral poor mental health symptoms
using the 12-question General Health
Questionnaire.
14,15,17,26
One study also used
theNottinghamLifeQuality Questionnaire,
but to avoid duplication of estimates, we in-
cluded only the general poor mental health
symptoms estimate dened with the General
Health Questionnaire.
17
One study used
the 28-item General Health Questionnaire
and depression subscales to dene cases of
combined anxiety and depressive symptoms.
The remaining studies used either the
Hospital Anxiety and Depression scale to
dene cases of anxiety and depressive
symptoms
29
or a self-reported checklist from
the Health and Work Productivity Ques-
tionnaire for cases of depressive symptoms.
27
We excluded 1 risk estimate from the anal-
ysis because the authors measured symptoms
of anxiety and depression together using a
single self-reported question.
13
The average
age of participants in the studies was 39.7
years, with a range of 18 to 60 years.
Risk of Bias Assessment
The risk of bias was high in more than half
the studies and moderate in the remaining
studies (Table A, available as a supplement to
the online version of this article at http://
www.ajph.org). Exposure assessment (e.g.,
using self-report) and attrition (lost to
follow-up >20%) were the 2 domains with a
high risk of bias in the majority of the studies.
Three studies scored a high risk of bias for
exposure denition. No studies reported on
the blinding of assessors or researchers un-
dertaking the studies. As this aspect is not
relevant to the included studiesdesign, we
deemed the risk of bias unclear for this item.
Denition and Measure of
Exposure to Shift Work
Six studies used self-report to measure shift
work exposure, and 1 used company rec-
ords.
30
Studies dened shift work differently,
with most using a work pattern consisting
of rotations between morning, afternoon,
and night shifts or between day and night
shifts.
14,2730
Two studies considered work-
ing nights as shift work, but without a specic
pattern denition (e.g., frequency of night
shifts).
15,17
Effect of Shift Work on Mental
Health Outcomes
The results of the meta-analysis for the
association between shift work and adverse
mental health outcomes (combined and by
type) are shown in Figure 2. The pooled ES
shows shift workers had a higher risk of ad-
verse mental health outcomes combined than
those who did not do shift work (ES = 1.28;
95% CI = 1.02, 1.62). However, there was
substantial heterogeneity among studies
(I
2
= 70.6%). In the subanalysis by type
of adverse mental health outcome, shift
work was associated with 33% higher risk
of depressive symptoms (ES = 1.33; 95%
CI = 1.02, 1.74). The risk of anxiety
symptoms and general poor mental health
symptoms was higher in shift workers than
in nonshift workers; however, these asso-
ciations were not statistically signicant
(ES = 1.20; 95% CI = 0.85, 1.69 and ES =
1.18; 95% CI = 0.72,1.91, respectively).
In the subgroup analysis in Figure 3, female
shift workers were at higher risk for combined
adverse mental health outcomes (ES = 1.78;
95% CI =1.39, 2.14) than were female non
shift workers. However, this was not the case
for male shift workers (ES = 1.14; 95% CI =
0.49, 2.65).
Sensitivity Analysis
Results of the sensitivity analysis are shown
in Table B (available as a supplement to the
online version of this article at http://
www.ajph.org). The metaregression results
show that gender and overall risk of bias could
explain 90.00% and 0.61% of the heteroge-
neity of results. The rest of the factors mea-
sured resulted in a negative I
2
, which can be
interpreted as zero.
31
When the pooled effect
size included estimates from women only, the
effect of shift work was higher in female shift
workers than in female nonshift workers
(ES = 1.73; 95% CI = 1.39, 2.14). But this was
not the case for male shift workers (ES = 1.25;
95% CI = 0.49, 2.65). The pooled effect sizes
were signicant for depressive symptoms,
studies with low risk of bias in the exposure
denition, studies of nurses, studies with large
1902 retrieved
n
=
1263 duplicates
n
=
639 reviewed by
title/abstract
n
=
51 reviewed by
full text
n
=
588 excluded
Not shift workers
=
86
Not longitudinal design
=
28
No specic mental health outcome
=
192
No shift work and mental health–specic
=
133
Sleep/circadian rhythm–related
=
149
7 articles included
in meta-analysis
n
=
44 excluded
Cross-sectional data
=
15
Shift work not main exposure factor
=
16
Repetition from previous cohort study
=
4
Data format/no control
=
9
FIGURE 1Flow Diagram of Literature Search and Selection of Studies: United States, 2018
AJPH OPEN-THEMED RESEARCH
e16 Systematic Review Peer Reviewed Torquati et al. AJPH November 2019, Vol 109, No. 11
sample size (>1000), and studies with mod-
erate overall risk of bias.
DISCUSSION
To our knowledge, this is the rst meta-
analysis to investigate the pooled effects of
shift work on the risk of poor mental health,
including subanalyses by type of poor mental
health and gender. The results show that shift
work was associated with an increased overall
risk of adverse mental health outcomes
combined. Specically, the risk of depressive
symptoms was 33% higher in shift workers
than in nonshift workers. Gender differences
explained more than 90% of heterogeneity,
with female shift workers more likely to
experience depressive symptoms than female
nonshift workers (OR = 1.73; 95% CI =
1.39, 2.14).
Our results are comparable with a previous
meta-analysis that investigated depression risk
in shift workers.
32
Lee et al.
32
reported a
RR = 1.43 (95% CI = 1.24, 1.64), which is
similar to our pooled estimate for depressive
symptoms (ES = 1.33; 95% CI = 1.02, 1.74).
Another review and meta-analysis of longi-
tudinal studies found that most studies re-
ported an increased risk of depression with
night work, but the pooled effect size was not
signicant (ES =1.42; 95% CI= 0.92, 2.19).
33
Our study adds to previous literature by
showing that shift workersrisk is higher for
adverse mental health outcomes combined,
not just depression, and this risk might differ
between men and women.
Although our study did not specically
assess positive mental health outcomes, our
ndings of an increased risk of symptoms
related to depression and poor mental health
outcomes seem to contrast with those of
Nabe-Niesen et al.,
16
who found that Danish
shift workers had better mental health and
vitality than did day workers. These differ-
ences might be because the study had a
younger participant sample, the study had
shorter follow-up and exposure to shift work,
and the participants had more control over
working times. Subgroup analysis in the other
study showed that shift workers with low
control of planning working hours scored the
lowest on mental health (frequency of feeling
nervous, blue, happy) and vitality scales
(frequency of feeling energetic, worn out,
tired).
16
Although not assessed in our study, low job
control has previously been demonstrated to
have a negative effect on mental health.
34,35
This suggests a mediating role for work-
related factors in the shift work and mental
health relationship. Two recent meta-
analyses have reported that specic work-
related factors such as job strain, low decision
latitude, and low social support were associ-
ated with higher risk of poor mental health in
the working population.
36,37
These factors
are common characteristics of shift work and
could contribute to the risk of adverse mental
health outcomes.
38
Interestingly, one study
showed that shift work was not associated
with poor mental health after adjustment for
psychosocial working conditions.
27
Previous studies have shown that tolerance
to different work stressors (e.g., job insecurity,
lifework balance) differs by gender, with
lower tolerance associated with higher in-
cidence of major depressive disorders in
women than in men.
39
This might explain the
higher pooled effect size observed for general
poor mental health in women than in the
overall effects in our subgroup analysis
(ES = 1.73 vs 1.28). Our ndings are com-
parable to other research reporting increased
odds for depressive symptoms in female shift
workers than in female nonshift workers
(OR = 1.52; 95% CI = 1.38, 1.67).
13
Cross-
sectional analysis from a large Dutch cohort
study also reported higher odds of depressed
mood in female shift workers than in their day
shift counterparts (OR = 5.96; 95%
CI = 2.83, 12.56). This was higher than the
odds reported for male shift compared with
TABLE 1Characteristics of the Studies Included in the Meta-Analysis of Effects of Shift Work Exposure on Mental Health and Male-Female
Differences: United States, 2018
Study Design
Follow-
Up
Type of Adverse Mental
Health Outcome Tool Used Case Denition
Sample
Size Age, Years
a
Gender
Occupational
Group
Lin et al.
14
Cohort study 1 y General poor mental
health symptoms
GHQ-12 Score >4 1360 29.9 (2045) Female Nurses
Bara and
Arber
15
Cohort study 8 y General poor mental
health symptoms
GHQ-12 Score >4 9765 2173 Female and
male
Not
specied
Bildt and
Michelsen
17
Cohort study 4 y General poor mental
health symptoms
GHQ-12 Score >75th percentile 420 4663 Female and
male
Not
specied
Driesen
et al.
27
Cohort study 10 y Depressive symptoms Self-report HPQ
checklist
Current/past treatment
of depressive disorder
8178 40.1 (8.0) Female and
male
Not
specied
De Raeve
et al.
28
Cohort study 2 y General poor mental
health symptoms
GHQ-12 Score >4 6828 41.72 (8.70) Female and
male
Not
specied
Berthelsen
et al.
29
Cohort study 1 y Anxiety and depressive
symptoms
HADS-14 Score >8 in respective
scales
1582 30 (2160) Female and
male
Nurses
Poole
et al.
30
Cohort study 6 mo Anxiety and depressive
symptoms
GHQ-28 anxiety and
depression scales
Score >4 in respective
scales
298 35 (1860) Female and
male
Factory
employees
Note. GHQ = General Health Questionnaire; HADS = Hospital Anxiety and Depression Scale; HPQ = Health and Work Performance Questionnaire.
a
Average age at baseline, or the highest mean when the study presented the population in stratied groups, with SD or range presented in parentheses.
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November 2019, Vol 109, No. 11 AJPH Torquati et al. Peer Reviewed Systematic Review e17
nonshift workers (OR = 2.05; 95% CI =
1.52, 2.77).
12
Such ndings suggest that
female shift workers are at higher risk for
adverse mental health outcomes than are male
shift workers.
The higher risk of depression in female
than male shift workers may be partly
explained by the higher risk of depression
among women than men in the general
population.
40
This increased vulnerability
has been attributed to gender differences in
physiological stress responses, biological load
and hormones, interpersonal orientation,
rumination and internalization of difculties,
and exposure to other adversity (e.g., re-
lationship violence, discrimination).
40
Future
research on the effects of shift work on mental
health outcomes could include measures of
other relevant factors, such as alcohol abuse
and aggression, that are more prevalent
among men than women.
These results suggest that employers should
consider strategies for reducing the mental
health burden on shift workers, such as giving
more control and exibility over shift sched-
ules, reducing job strain, and providing more
social support at work. Workplace policies,
programs, and practices could promote
awareness of associated risks and protective
factors and enable access to mental health
services without stigmatization. Depression
accounts for 4.3% of the global burden of
disease and incidence,
41
with mental disorders
worldwide predicted to cost US $16.3 million
by 2030.
42
Untreated mental health condi-
tions are costly to workplaces in terms of ab-
senteeism, presenteeism, and compensation
claims. With 1 in 5 people inthe United States
and Europe doing shift work,
2,3
and the in-
creased risk of poor mental health among shift
workers, shift work industries are a priority
context for reducing this burden.
Strengths and Limitations
The strengths of this study include our
use of comprehensive search terms, with a
combination of keywords that has previously
been shown to be appropriate in maximizing
retrieval of studies on shift work and poor
mental health.
20,43
We also used large
Overall (I2
=
70.6%; P
<
.001)
Bildt and Michelsen17
Bara and Arber15
Poole et al.30
Poole et al.30
Bildt and Michelsen17
Poor general mental health symptoms
Bildt and Michelsen17
Driesen et al.27
Anxiety symptoms
Driesen et al.27
De Raeve et al.28
Bildt and Michelsen17
Study
Subtotal (I2
=
85.6%; P
<
.001)
Lin et al.14
Depressive symptoms
Subtotal (I2
=
0.0%; P
>
.99)
Bethelsen et al.29
Bethelsen et al.29
Subtotal (I2
=
31.5%; P
=
.199)
Bara and Arber15
Male
Male
Male & Female
Male & Female
Male
Female
Female
Male
Male & Female
Female
Gender
Female
Male & Female
Male & Female
Female
1.28 (1.02, 1.62)
2.20 (0.96, 5.02)
2.58 (1.22, 5.47)
0.94 (0.63, 1.41)
1.20 (0.77, 1.88)
0.20 (0.07, 0.57)
1.20 (0.85, 1.69)
1.60 (0.96, 2.68)
1.63 (1.05, 2.54)
1.16 (0.81, 1.66)
0.90 (0.77, 1.06)
2.40 (1.00, 5.78)
ES (95% CI)
1.18 (0.72, 1.91)
1.91 (1.39, 2.63)
1.20 (0.71, 2.02)
1.20 (0.56, 2.57)
1.33 (1.02, 1.74)
1.06 (0.49, 2.28)
100.00
4.81
5.36
8.82
8.33
3.55
15.86
7.59
8.39
%
9.41
11.40
4.44
Weight
42.97
9.83
7.53
5.29
41.17
5.24
.5 1 2 3
Note. ES = effect size.
FIGURE 2Effect of Exposure to Shift Work by Adverse Mental Health Outcomes and Combined Outcomes (Overall Effect): United States,
2018
AJPH OPEN-THEMED RESEARCH
e18 Systematic Review Peer Reviewed Torquati et al. AJPH November 2019, Vol 109, No. 11
databases, conducted by hand searches in
reference lists of relevant articles, and con-
tacted authors for data to optimize the data.
The exclusion of 2 studies
16,26
because of data
format (continuous instead of categorical)
remains a potential limitation; however, it is
unlikely that this decision would have sig-
nicantly changed our ndings. One study
26
had a very small sample size (n = 60) and
reported similar ndings to our study,
whereas the other
16
reported both negative
and positive associations between shift work
and mental health and vitality. The ndings
from these studies are similar to those reported
in other included studies,
17
and earlier in the
discussion we explored possible reasons for
the differences in associations.
We conducted sensitivity analyses on the
effects of gender; however, we could not do
this for other personality traits or job-related
factors. This information was not available in
the included studies. We conducted sensi-
tivity analysis on participantsoccupation
using a dichotomy of nursing versus other,
but the lack of occupation information in
most studies limited our ability to explore
potential moderating effects of specicoc-
cupations. Given the large body of literature
on these factors, these variables should be
considered in future meta-analyses as me-
diators of overall pooled effect size. To en-
hance specicity, we grouped estimates into
3 types of adverse mental health outcomes
(i.e., anxiety symptoms, depression symp-
toms, general poor mental health symptoms)
and used a dichotomy of present versus not
present.
We acknowledge that this could be per-
ceived as a simplistic approach and that the
measures used in the included studies were
sometimes very basic (e.g., 1 question item to
dene clinical depression) and used cutoff scores
to identify the presence or absence of adverse
mental health outcomes. This approach would
be insufcient for diagnostic purposes. We
have,therefore,usedlanguageaboutsymp-
tomsrather than diagnoses and excluded es-
timates of anxiety and depression assessed with
asinglequestion.
13
Future studies of the effects
of shift work on adverse mental health outcomes
could include subanalyses to assess the effects
of gender differences in job-related factors.
Conclusions
Shift workers are at increased risk for
poor mental health and, more specically,
symptoms related to depression; this is par-
ticularly true for female shift workers.
Workplace health promotion programs and
Overall (I2
=
70.6%; P
<
.001)
Male & Female
Study
Bildt and Michelsen17
Bildt and Michelsen17
Bildt and Michelsen17
Subtotal (I2
=
0.0%; P
=
.624)
Bethelsen et al.29
Lin et al.14
Driesen et al.27
Female
Subtotal (I2
=
0.0%; P
=
.622)
Bildt and Michelsen17
De Raeve et al.28
Bethelsen et al.29
Poole et al.30
Poole et al.30
Subtotal (I2
=
82.8%; P
=
.001)
Bara and Arber15
Driesen et al.27
Bara and Arber15
Male
Depressive symptoms
Outcome
Depressive symptoms
Poor general mental health symptoms
Depressive symptoms
Poor general mental health symptoms
Depressive symptoms
Depressive symptoms
Poor general mental health symptoms
Poor general mental health symptoms
Poor general mental health symptoms
Anxiety symptoms
Anxiety symptoms
Depressive symptoms
Poor general mental health symptoms
1.28 (1.02, 1.62)
2.20 (0.96, 5.02)
ES (95% CI)
2.40 (1.00, 5.78)
0.20 (0.07, 0.57)
0.95 (0.83, 1.09)
1.20 (0.56, 2.57)
1.91 (1.39, 2.63)
1.16 (0.81, 1.66)
1.63 (1.05, 2.54)
2.58 (1.22, 5.47)
1.73 (1.39, 2.14)
1.60 (0.96, 2.68)
0.90 (0.77, 1.06)
1.20 (0.71, 2.02)
1.20 (0.77, 1.88)
0.94 (0.63, 1.41)
1.14 (0.49, 2.65)
1.06 (0.49, 2.28)
100.00
4.81
Weight
4.44
3.55
41.37
5.29
9.83
9.41
8.39
5.36
35.50
7.59
11.40
7.53
8.33
8.82
23.13
5.24
%
.5 1 2 3
Note. ES = effect size.
FIGURE 3Effect of Shift Work on Adverse Mental Health Outcomes (Overall Effect), by Gender: United States, 2018
AJPH OPEN-THEMED RESEARCH
November 2019, Vol 109, No. 11 AJPH Torquati et al. Peer Reviewed Systematic Review e19
policies are needed to minimize shift workers
risk of poor mental health.
CONTRIBUTORS
L. Torquati conducted the searches and drafted the re-
view. L. Torquati and G. I. Mielke contributed to data
design, analysis, and interpretation. G. I. Miel ke, W.J.
Brown, N. W. Burton, and T. L. Kolbe-Alexande r
contributed to the interpretation of data and revision of
data analysis and content. T. L. Kolbe-Alexander con-
tributed to the conception of the study. All authors ap-
proved the nal version to be published.
ACKNOWLEDGMENTS
The authors would like to thank the following authors
who kindly replied to our request for further data in an
effort to include as many eligible studies as possible: I.J.
Kant, Nicole W. H. Jansen, Amanda Cooklin, Ralph
Mistlberger, Eirunn Thun, John Violanti, Sandra
West, Margot Shields, and Marianna Virtanen.
CONFLICTS OF INTEREST
The authors declare no conict of interests or nancial
conicts.
HUMAN PARTICIPANT PROTECTION
No protocol approval was necessary because no human
participants were involved in this study.
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... A previous meta-analysis of longitudinal studies included a sensitivity analysis for the effect of gender on mental health in nurses (22). However, the authors did not analyze the characteristics associated with shift work because this information was not available (22). ...
... A previous meta-analysis of longitudinal studies included a sensitivity analysis for the effect of gender on mental health in nurses (22). However, the authors did not analyze the characteristics associated with shift work because this information was not available (22). To fully explore the mechanisms by which shift work might influence mental health, it is necessary to consider specific characteristics of the working environment (e.g., fixed/permanent shifts, number of night shifts worked, start times, and the speed and direction of shift rotation) (23). ...
... In the present study, shift nurses were 1.54 and 1.36 times more likely to have greater levels of depression and anxiety, respectively, compared with non-shift nurses. A metaanalysis of longitudinal data showed that shift work enhanced the overall risk of adverse mental health outcomes (e.g., depression and anxiety) by 28% among 28,431 participants (22). Lee et al. also found that Korean nurses who engaged in shift work were 1.5 times more likely to experience more severe depressive symptoms in comparison with non-shift workers (25). ...
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Background Although shift work is the foundation of the provision of 24-h continuous care in hospitals, it can negatively impact mental health in hospital workers such as nurses. Despite the connection between mental health and overall health, little is known about the effect of shift work-related factors on mental health in this population. Objectives We investigated the effect of scheduling practices, physical and psychological characteristics related to shift work, and personal habits during shift work on depression and anxiety among nurses. Methods In this multi-center cross-sectional study, 11,061 nurses from 20 hospitals in the Shandong Province of China completed an online survey between December 2020 and February 2022. Multivariate ordered logistic regression analysis was performed to examine shift-related factors associated with depression and anxiety in the study population. Results The completion rate of all nurses' questionnaires was 83.00% ( n = 9,181). Among the 9,181 respondents, 66.20% ( n = 6,078) were shift nurses. Depression and anxiety were found in 58.82 and 62.08% of shift nurses, respectively, and these rates were influenced by fatigue during shift work, psychological stress before/during/after night shifts, feeling of being refreshed after resting before/after night shifts, using sleep medication before/after night shifts, physical discomfort during night shifts, busyness during night shifts, food intake during shift work, working > 40 h/week during shift work, and sleep quality before/after night shifts. Conclusions Depression and anxiety in shift nurses may be addressed by reducing their workload, sources of stress during night shifts, and facilitating rest and relaxation.
... 3 Several previous studies have described structural and functional brain changes in shift workers. 4,5 Simulated night shift work reportedly changed the pattern of brain protein synthesis in a rat study. 6 To the best of our knowledge, no study has yet reported white matter changes in shift workers. ...
... Shift workers have an increased risk of chronic disease, including type 2 diabetes, hypertension, cardiovascular disease, selected cancers and all-cause mortality, compared to their day worker counterparts (Gu et al. 2015;Knutsson and Kempe 2014;Manohar et al. 2017;Moreno et al. 2019;Torquati et al. 2018;Wang et al. 2015). Shift work is typically defined as working outside the usual 6 am to 6 pm working day, and often involves some component of night work (Kecklund and Axelsson 2016;Torquati et al. 2019). Being awake for long periods at night predisposes individuals to a variety of biological and social factors which impacts on their ability to engage in adequate physical activity and achieve good sleep health (i.e. a duration, quality and timing of sleep that leaves a person feeling refreshed during the day) (Buysse 2014;Neil-Sztramko et al. 2014). ...
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... A metaanalysis of longitudinal studies indicated that shift work is associated with worse mental health, specifically depressive symptoms. This conclusion is consistent with another metaanalysis showing that night shift work is related to an increased risk of depression (Lee et al., 2017;Torquati et al., 2019). The night shift workers are exposed to long-term artificial light at night, which may lead to chronic desynchronization of their circadian rhythm. ...
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The circadian rhythm is crucial for physiological and behavioral functions. Chronotype, which represents individual preferences for activity and performance, is associated with human health issues, particularly psychiatric disorders. This narrative review, which focuses on the relationship between chronotype and mental disorders, provides an insight into the potential mechanism. Recent evidence indicates that (1) the evening chronotype is a risk factor for depressive disorders and substance use disorders, whereas the morning chronotype is a protective factor. (2) Evening chronotype individuals with bipolar disorder tend to have more severe symptoms and comorbidities. (3) The evening chronotype is only related to anxiety symptoms. (4) The relationship between chronotype and schizophrenia remains unclear, despite increasing evidence on their link. (5) The evening chronotype is significantly associated with eating disorders, with the majority of studies have focused on binge eating disorders. Furthermore, the underlying mechanisms or influence factors are described in detail, including clock genes, brain characteristics, neuroendocrinology, the light/dark cycle, social factors, psychological factors, and sleep disorders. These findings provide the latest evidence on chronotypes and psychiatric disorders and serve as a valuable reference for researchers.
... This is especially relevant for shift workers, who are regularly required to be awake and active during the dark period of the day and who subsequently sleep or rest during the light part of the day. Such rest-activity patterns are associated with an increased risk of for example insomnia or shift work disorder [6][7][8], cardiovascular disease [9,10], cancer [11][12][13][14], gastrointestinal disorders [15], metabolic disturbances [16], diabetes [17][18][19], and impaired reproductive health [20][21][22] as well having adverse effects on mental health [4,23,24] and the work-life balance [25]. ...
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Background Blue-depleted light environments (BDLEs) may result in beneficial health outcomes for hospital inpatients in some cases. However, less is known about the effects on hospital staff working shifts. This study aimed to explore the effects of a BDLE compared with a standard hospital light environment (STLE) in a naturalistic setting on nurses’ functioning during shifts and sleep patterns between shifts. Methods Twenty-five nurses recruited from St. Olavs Hospital in Trondheim, Norway, completed 14 days of actigraphy recordings and self-reported assessments of sleep (e.g., total sleep time/sleep efficiency) and functioning while working shifts (e.g., mood, stress levels/caffeine use) in two different light environments. Additionally, participants were asked to complete several scales and questionnaires to assess the symptoms of medical conditions and mental health conditions and the side effects associated with each light environment. Results A multilevel fixed-effects regression model showed a within-subject increase in subjective sleepiness (by 17%) during evening shifts in the BDLE compared with the STLE ( p = .034; Cohen’s d = 0.49) and an 0.2 increase in number of caffeinated beverages during nightshifts in the STLE compared with the BDLE ( p = .027; Cohen’s d = 0.37). There were no significant differences on any sleep measures (either based on sleep diary data or actigraphy recordings) nor on self-reported levels of stress or mood across the two conditions. Exploratory between-group analyses of questionnaire data showed that there were no significant differences except that nurses working in the BDLE reported perceiving the lighting as warmer ( p = .009) and more relaxing ( p = .023) than nurses working in the STLE. Conclusions Overall, there was little evidence that the change in the light environment had any negative impact on nurses’ sleep and function, despite some indication of increased evening sleepiness in the BDLE. We recommend further investigations on this topic before BDLEs are implemented as standard solutions in healthcare institutions and propose specific suggestions for designing future large-scale trials and cohort studies. Trial registration The study was registered before data collection was completed on the ISRCTN website ( ISRCTN21603406 ).
... Working outside the normal daytime working hours can cause a disturbance of the individuals' endogenous circadian rhythm, which is believed to be an important contributor to the detrimental effects of shift work [2,4]. Studies on shift work have found associations with health problems such as certain cancers and cardiovascular diseases [5,6], diabetes [7], gastro-intestinal problems [8], and impaired mental health [9], as well as more acute problems related to sleep and stress [2,10]. Shift systems that cause the greatest disruption of the biological rhythm and sleep-in particular night shifts, early morning shifts (starts before 06:00 a.m.) and quick returns (i.e., 11 h or less between two consecutive shifts)-are associated with the largest negative effects on health and sleep [11][12][13][14]. ...
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Background: This study aimed to investigate whether different types of changes in the work schedule of nurses working rotating shifts during the COVID-19 pandemic were associated with sleep duration, sleep quality, and turnover intention. Methods: Cross-sectional questionnaire data from 694 nurses participating in the SUrvey of Shift work, Sleep and Health (SUSSH) were collected between the first and the second wave of the COVID-19 pandemic in Norway. A total of 89.9% were female, and mean age was 44.6 years (SD = 8.6 years). Changes in the shift work schedule related to the pandemic comprised reports of more long workdays (>8 h), less days off between work periods, more night shifts, more quick returns (i.e., 11 h or less between two consecutive shifts), more day shifts, and more evening shifts compared to no change in the respective shift characteristics. Change in sleep duration, sleep quality, and turnover intention as well as demographics were also assessed. Logistic regression analyses were performed to investigate whether changes in the specific work schedules were associated with sleep duration, sleep quality, and turnover intention, controlling for sex, age, cohabitation, children living in household, percentage of full time equivalent and other changes in the work schedule. Results: A total of 17% reported experiencing one or more changes in their work schedule during the pandemic. Experiencing any change in the work schedule predicted worse sleep quality (OR = 2.68, p < 0.001), reduced sleep duration (OR = 4.56, p < 0.001), and higher turnover intention (OR = 1.96, p = 0.006) compared to experiencing no change in work schedule. Among the specific changes in work schedules, experiencing an increase in quick returns had the highest odds ratio for worse sleep quality (OR = 10.34, p = 0.007) and higher turnover intention (OR = 8.49, p = 0.014) compared to those who reported no change in quick returns. Nurses experiencing an increase in long workdays were more likely to report higher turnover intention (OR = 4.37, p = 0.003) compared to those experiencing no change in long workdays. Conclusions: Change in work schedule related to the pandemic was associated with worse sleep quality, reduced sleep duration, and higher turnover intention. Increase in quick returns emerged as especially problematic in terms of sleep quality and turnover intention, along with long workdays, which were associated with higher turnover intention.
... Shift work is especially widespread in the healthcare sector with about 40% of the employees being engaged in such schedules [2]. Shift work has been associated with a range of adverse health effects, including cardiovascular disease [3], cancers [4,5], diabetes [6], gastrointestinal disorders [7], sleep disturbances [8], and impaired mental health [9]. In addition, shift work represents a risk factor for accidents and injuries [10]. ...
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Background Shift work, i.e., non-standard work hours, has been associated with both short- and long-term sickness absence. However, findings are inconsistent and inconclusive. Thus far, no comprehensive meta-analytic synthesis on the relationship between shift work and sickness absence has been published. The aims of the planned systematic review and meta-analysis are (1) to establish whether shift work is associated with sickness absence, (2) to determine if specific shift work characteristics relate to sickness absence (e.g., length and frequency of spells), and (3) to identify moderating factors affecting the relationship between shift work and sickness absence. Methods Eligible studies will be identified using a predefined search strategy in several electronic databases (MEDLINE, Web of Science, PsychInfo, EMBASE, and ProQuest) and comprise peer-reviewed papers reporting original empirical findings on the association between shift work and sickness absence. Mainly observational studies with cross-sectional, prospective, or retrospective research design and case-control studies will be included. Risk of bias will be assessed using an adapted checklist previously employed to evaluate studies on sickness absence. To carry out the meta-analytic synthesis, a random effects meta-analysis will be conducted using the Comprehensive Meta-Analysis software. The review and meta-analysis will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Heterogeneity will be evaluated by Cochran’s Q test and the I ² statistics. Discussion The review and meta-analysis will be the first to conduct a meta-analytic synthesis of the evidence on the association between exposure to shift work and sickness absence, as well as identify relevant moderators affecting the relationship between shift work and sickness absence. Aggregation of the existing evidence will improve the knowledge on the association between shift work and sickness absence. Such knowledge can be used to guide scheduling of shift work to promote work schedules that are less detrimental to health and contribute to reduced sickness absence and higher work- and leisure-time productivity. Systematic review registration PROSPERO CRD42022301200
... Formal workers may not be as protected as we would expect, diminishing the differences between formal and informal workers. Workers at formal jobs may also be exposed to other work-related risk factors for poor mental health, such as an increased number of working hours, unpaid overtime, poor job security, poor satisfaction with one's work culture and a feeling of a lack of support, low income, shift work, and night work [48,49]. Moreover, the provision of mental health services represents less than 1% of government health spending in low-and middle-income countries, and rates of availability and uptake for mental health services remain very low [50]. ...
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The aim of this study is to estimate the association between employment conditions and mental health status in the working population of Iberoamerica. In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 13 countries. A sample of 180,260 workers was analyzed. Informality was assessed by social security, health affiliation, or contract holding. Mental health was assessed using several instruments. We used Poisson regression models to estimate the contribution of informality to poor mental health by sex and country, adjusted by sociodemographic and work-related characteristics. Then, we performed a meta-analysis pooling of aggregate data using a random-effects inverse-variance model. Workers in informal employments showed a higher adjusted prevalence ratio (aPR) of poor mental health than those in formal employment in Peru (aPR men 1.5 [95% confidence intervals 1.16; 1.93]), Spain (aPR men 2.2 [1.01; 4.78]) and Mexico (aPR men 1.24 [1.04; 1.47]; women 1.39 [1.18; 1.64]). Overall estimates showed that workers in informal employment have a higher prevalence of poor mental health than formal workers, with it being 1.19 times higher (aPR 1.19 [1.02; 1.39]) among men, and 1.11 times higher prevalence among women (aPR 1.11 [1.00; 1.23]). Addressing informal employment could contribute to improving workers’ mental health.
... [19,20] Shift work was associated with an increased risk of adverse mental health outcomes in general, and depressive symptoms in particular. [21] Resident physicians who were on call more than 6 times a month had significantly poorer sleep quality and higher anxiety and depression scores compared to other colleagues. [22] It is well known that patients with IBS often have symptoms such Table 2 The quality assessment for the included articles. ...
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Background: The possible association between shift work with irritable bowel syndrome (IBS) and functional dyspepsia (FD) remains controversial. The purpose of the study is to conduct a meta-analysis to explore the potential association between shift work with IBS/FD. Methods: We searched relevant observational studies on Medline (PubMed) and Embase until June 30, 2021. Two different investigators extracted data and assessed the quality of each study independently. The meta-analysis was used to evaluate the pooled odds risk (OR) between shift work and IBS/FD. Results: Eight studies were included ultimately. Shift workers were more likely to suffer from IBS. The OR of shift work was 1.81 (95% confidence interval 1.42; 2.32) with low heterogeneity (P < .05, I2 = 0%) for IBS. However, no evidence of the association was observed between shift work and the risk of FD. The OR of shift work was 0.87 (95% confidence interval 0.62; 1.23) (P > .05) for FD. Conclusions: There was a positive association between shift work and IBS. The prevalence of IBS was 81% higher among shift workers than among non-shift workers. Shift work was probably a risk factor for IBS. The low heterogeneity supports the reliability of the results. However, there was no significant association between shift work and FD. The strength of the evidence was limited and further prospective cohort studies were needed.
Article
Objectives: Shiftworkers routinely obtain inadequate sleep, which has major health consequences. Sleep hygiene describes a range of behaviours, lifestyle and environmental factors that can improve sleep. To date, limited research has examined sleep hygiene in shiftworkers. This study aimed to assess the sociodemographic and behavioural correlates of sleep hygiene knowledge and engagement with sleep hygiene practices in Australian shiftworkers. Study design: An online, cross-sectional survey. Setting and participants: Australian adults from across multiple industries (n=588) who work shift work. Measures: The online survey included questions regarding sleep hygiene knowledge and questions from modified versions of the Pittsburgh Sleep Quality Index and Sleep Hygiene Index. Results: Of the 588 participants, 52.9% reported having heard of 'sleep hygiene'. Of these participants, 77.5% reported understanding the term moderately, extremely or very well. Engagement with each sleep hygiene practice was varied. Common sleep hygiene practices were controlling the bedroom environment (eg, a cool, dark and quiet bedroom). Less common practices were avoiding light as bedtime approaches. Logistic regressions revealed that shiftworkers who had heard of sleep hygiene were more likely to engage in sleep hygiene practices and had better sleep quality compared with those who had not heard of sleep hygiene. Increased engagement in sleep hygiene practices did not predict the likelihood of individuals reporting better sleep quality. Conclusions: Shiftworkers demonstrated varied knowledge, understanding and engagement with individual sleep hygiene practices. Future research should focus on the development of sleep hygiene interventions that accommodate the unique challenges of shift work to optimise sleep.
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Objectives The aim of this review was to assess the risk of cardiovascular disease (CVD) events associated with shift work and determine if there is a dose-response relationship in this association. Method Electronic databases (PubMed, Scopus, and Web of Science) were searched for cohort or case-control control study designs in any population, reporting exposure to shift work as the main contributing factor to estimate CVD risk. For each study, adjusted relative risk (RR) ratios and 95% confidence intervals (CI) were extracted, and used to calculate the pooled RR using random-effect models. Meta-regression analysis was conducted to explore potential heterogeneity sources. Potential non-linear dose-response relationships were examined using fractional polynomial models. Results We included 21 studies with a total of 173 010 unique participants. The majority of the studies were ranked low-to-moderate risk of bias. The risk of any CVD event was 17% higher among shift workers than day workers. The risk of coronary heart disease (CHD) morbidity was 26% higher (1.26, 95% CI 1.10-1.43, I 2= 48.0%). Sub-group analysis showed an almost 20% higher risk of CVD and CHD mortality among shift workers than those who did not work shifts (1.22, 95% CI 1.09-1.37, I 2= 0% and 1.18, 95% CI 1.06-1.32 I 2=0%; respectively). After the first five years of shift work, there was a 7.1% increase in risk of CVD events for every additional five years of exposure (95% CI 1.05-1.10). Heterogeneity of the pooled effect size (ES) estimates was high (I 2=67%), and meta-regression analysis showed that sample size explained 7.7% of this. Conclusions The association between shift work and CVD risk is non-linear and seems to appear only after the first five years of exposure. As shift work remains crucial for meeting production and service demands across many industries, policies and initiatives are needed to reduce shift workers' CVD risk.
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This study estimates fatal and nonfatal disease burden among Indigenous Australians in 2011 and compares it with non-Indigenous Australians. The study found that there were 284 years lost per 1000 people because of premature death or living with ill health. Most of the disease burden was from chronic diseases (64%), particularly mental and substance-use disorders, injuries, cardiovascular diseases, cancer and respiratory diseases. The burden of disease was higher among males (54%) than females (46%) and higher for fatal (53%) than for nonfatal burden (47%). The disease groups with the highest burden varied by age group, with mental and substance-use disorders and injuries being the largest disease groups among those aged 5–44 years, and cardiovascular disease and cancer becoming more prominent among those aged 45 and older. Large disparities existed between Indigenous and non-Indigenous Australians, with the total burden being 2.3 times the non-Indigenous rates, fatal burden being 2.7 times and nonfatal burden being 2 times.
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This study aimed to assess whether night shift work is associated with the risk of depression by using a meta-analysis of observational studies. We searched PubMed and EMBASE in August, 2016 to locate eligible studies and investigated the association between night shift work and the risk of depression, reporting outcome measures with adjusted odds ratios (ORs) or relative risks (RRs) and 95% confidence intervals (CIs). In the meta-analysis of a total of 11 observational studies with 9 cross-sectional study, 1 longitudinal study, and 1 cohort study, night shift work was significantly associated with an increased risk of depression (OR/RR, 1.43; 95% CI, 1.24-1.64; I² = 78.0%). Also, subgroup meta-analyses by gender, night shift work duration, type of occupation, continent, and type of publication showed that night shift work was consistently associated with the increased risk of depression. The current meta-analysis suggests that night shift work is associated with the increased risk of depression. However, further large prospective cohort studies are needed to confirm this association.
Article
Background: Reported associations between shiftwork and health have largely been based on occupation-specific, or single sex studies that might not be generalizable to the entire working population. The objective of this study was to investigate whether shiftwork was independently associated with obesity, diabetes, poor sleep and well-being in a large, UK general population cohort. Methods: Participants of the UK Biobank study who were employed at the time of assessment were included. Exposure variables were self-reported shiftwork (any shiftwork and night shiftwork); and outcomes were objectively measured obesity, inflammation and physical activity and self-reported lifestyle, sleep and well-being variables, including mental health. Results: Shiftwork was reported by 17% of the 277168 employed participants. Shiftworkers were more likely to be male, socioeconomically deprived and smokers, and to have higher levels of physical activity. Univariately, and following adjustment for lifestyle and work-related confounders, shiftworkers were more likely to be obese, depressed, to report disturbed sleep, and to have neurotic traits. Shiftwork was independently associated with multiple indicators of poor health and wellbeing, despite higher physical activity, and even in shiftworkers that did not work nights. Shiftwork is an emerging social factor that contributes to disease in the urban environment across the working population.
Article
Women are about twice as likely as are men to develop depression during their lifetime. This Series paper summarises evidence regarding the epidemiology on gender differences in prevalence, incidence, and course of depression, and factors possibly explaining the gender gap. Gender-related subtypes of depression are suggested to exist, of which the developmental subtype has the strongest potential to contribute to the gender gap. Limited evidence exists for risk factors to be specifically linked to depression. Future research could profit from a transdiagnostic perspective, permitting the differentiation of specific susceptibilities from those predicting general psychopathologies within and across the internalising and externalising spectra. An integration of the Research Domain Criteria framework will allow examination of gender differences in core psychological functions, within the context of developmental transitions and environmental settings. Monitoring of changing socioeconomic and cultural trends in factors contributing to the gender gap will be important, as well as the influence of these trends on changes in symptom expression across psychopathologies in men and women.
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Context Although the metabolic health effects of shift work have been extensively studied, a systematic synthesis of the available research is lacking. This review aimed to systematically summarize the available evidence of longitudinal studies linking shift work with metabolic risk factors. Evidence acquisition A systematic literature search was performed in 2015. Studies were included if (1) they had a longitudinal design; (2) shift work was studied as the exposure; and (3) the outcome involved a metabolic risk factor, including anthropometric, blood glucose, blood lipid, or blood pressure measures. Evidence synthesis Eligible studies were assessed for their methodologic quality in 2015. A best-evidence synthesis was used to draw conclusions per outcome. Thirty-nine articles describing 22 studies were included. Strong evidence was found for a relation between shift work and increased body weight/BMI, risk for overweight, and impaired glucose tolerance. For the remaining outcomes, there was insufficient evidence. Conclusions Shift work seems to be associated with body weight gain, risk for overweight, and impaired glucose tolerance. Overall, lack of high–methodologic quality studies and inconsistency in findings led to insufficient evidence in assessing the relation between shift work and other metabolic risk factors. To strengthen the evidence, more high-quality longitudinal studies that provide more information on the shift work schedule (e.g., frequency of night shifts, duration in years) are needed. Further, research to the (mediating) role of lifestyle behaviors in the health effects of shift work is recommended, as this may offer potential for preventive strategies.