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Nordic Journal of Psychiatry
ISSN: 0803-9488 (Print) 1502-4725 (Online) Journal homepage:
https://www.tandfonline.com/loi/ipsc20
Gender differences in healthcare management ofdepression:
aspects of sick leave and treatmentwith psychoactive drugs in a
Swedish setting
Per Lytsy, Johan Hallqvist, Kristina Alexanderson & Annika
Åhs
To cite this article: Per Lytsy, Johan Hallqvist, Kristina
Alexanderson & Annika Åhs (2019)Gender differences in
healthcare management of depression: aspects of sick leave and
treatmentwith psychoactive drugs in a Swedish setting, Nordic
Journal of Psychiatry, 73:7, 441-450,
DOI:10.1080/08039488.2019.1649723
To link to this article:
https://doi.org/10.1080/08039488.2019.1649723
© 2019 The Author(s). Published by InformaUK Limited, trading as
Taylor & FrancisGroup.
Published online: 12 Aug 2019.
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ARTICLE
Gender differences in healthcare management of depression:
aspects of sickleave and treatment with psychoactive drugs in a
Swedish setting
Per Lytsya,b , Johan Hallqvistb, Kristina Alexandersona and
Annika Åhsb
aDepartment of Clinical Neuroscience, Division of Insurance
Medicine, Karolinska Institutet, Stockholm, Sweden; bDepartment of
PublicHealth and Caring Sciences, University of Uppsala, Uppsala,
Sweden
ABSTRACTPurpose: To investigate whether women and men diagnosed
with depressive disorder were managedequally in terms of being
sick-leave certified and being prescribed psychoactive
drugs.Materials and methods: Data from all patients diagnosed with
depression during 2010–2015 inUppsala county, Sweden (n¼ 19 448)
were used to investigate associations between gender andissued
sick-leave certificate, prescriptions of anti-depressants,
anxiolytics, hypnotics and sedatives, andcognitive behavioral
psychotherapy referrals, at different time points up till 180days
after diagnosis.Results: At diagnosis date, 50.1% were prescribed
antidepressants; 14.2% anxiolytics; 13.3% hypnoticsor sedatives.
Corresponding proportion regarding issue of sick-leave certificate
among working aged(18–64 years) was 16.6%. Men had higher odds than
women of being prescribed antidepressants (OR1.16; 95% CI
1.09–1.24); anxiolytics (1.10; 95% CI 1.02–1.21), hypnotics and
sedatives (OR 1.09; 95% CI1.00–1.19) and lower odds (among those
aged 18–64 years) of being sick-leave certified (OR 0.90; 95%CI
0.82-0.98) in adjusted regression models. There were subtle changes
in ORs for outcomes at 3- and6-month follow-up periods.Conclusions:
Men had somewhat higher odds of being prescribed psychoactive drugs
and slightlylower odds of being sick-leave certified as compared to
women at date when diagnosed with depres-sion. The absolute
differences were, however, small and the overall conclusion is that
women andmen with current diagnosed depressive episode/recurrent
depressive disorder are generally managedlikewise regarding sick
leave and psychoactive treatment.
ARTICLE HISTORYReceived 21 January 2019Revised 24 June
2019Accepted 23 July 2019
KEYWORDSDepression; sick leave;anxiolytics; hypnotics
andsedatives; antidepressants
Introduction
Depression is a leading cause of burden of disease, associ-ated
with suffering and disability for the individual as well aswith
high costs for the society [1]. The estimated life-timerisk of
developing depression is estimated to be around 10%[2] but the rate
varies across countries [3]. Depression com-monly occurs together
with different kinds of comorbidity,such as anxiety, substance
abuse, and also somatic disease,adding to the total burden of
disease [4–6] and concurrentuse of other drug classes [7].
Both depression and other mental disorders, e.g.
anxietydisorders, affect more women than men [5,8]. In Sweden,where
this study was conducted, women are also more likelyto be sickness
absent due to mental diagnoses, such asdepressive episode [9,10].
The life-time prevalence of adepression is almost twice as high in
women than in men[11,12], and the prevalence gender ratio for
depression,based on data from all healthcare appointments in
primaryhealthcare during 2011 in Stockholm, Sweden, was 2.3
[13].The reasons for the gender gap in the development
andprevalence of depression are multifaceted and are believed
to result from a complex interaction of biologic and
psycho-logical factors, social determinants, and factors
associatedwith healthcare organization and practices
[11,12,14,15].
The main treatment options for depression involve
bothpsychotherapies and pharmaceuticals [16]. Regarding
antide-pressants, some studies suggest that women respond betterto
SSRIs (selective serotonin inhibitors) than men, althoughthe
results are not clear [17–20]. There are also inconsistentresults
for tricyclic antidepressants, where some studies havefound no
gender difference in treatment response [21,22],whereas others
suggest that men respond better [17], how-ever, a difference not
considered clinically relevant [23].There is no clear evidence that
women and men respond dif-ferently to psychotherapy [24,25]. In
summary, there is someresearch suggesting that men and women may
respond dif-ferently to psychotropic drugs and psychotherapy, but
theevidence is not convincing enough to translate into
gender-differentiated treatment guidelines.
There are, nevertheless, indications of factual gender
differ-ences in the treatment of depression in clinical practice
inSweden. Data from the National Prescribed Drug Register showthat
women are dispensed almost twice as much
CONTACT Per Lytsy [email protected] Division of Insurance
Medicine, Department of Clinical Neuroscience, Karolinska
Institutet, Stockholm SE-17177,Sweden� 2019 The Author(s).
Published by Informa UK Limited, trading as Taylor & Francis
Group.This is an Open Access article distributed under the terms of
the Creative Commons Attribution-NonCommercial-NoDerivatives
License (http://creativecommons.org/licenses/by-nc-nd/4.0/),which
permits non-commercial re-use, distribution, and reproduction in
any medium, provided the original work is properly cited, and is
not altered, transformed, or built upon inany way.
NORDIC JOURNAL OF PSYCHIATRY2019, VOL. 73, NO. 7,
441–450https://doi.org/10.1080/08039488.2019.1649723
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-
antidepressants than men [26]. Such results do, however,
notaccount for the gender differences in prevalence of
depression.
It is also known that women have more healthcare visits[27],
which possibly contributes to higher depression rates.More women
use psychotropic drugs, and women are morelikely than men to use
pharmaceuticals with an abusepotential, also after adjusting for
diagnosis, demographicfactors, health status, and health insurance
[28]. There areseveral other factors that may contribute to
differences inprescription, dispensing, and drug utilization, such
as gen-der differences for the preference of psychological
versuspharmacological treatment [29].
Since the 1980s, sickness absence due to mental diagno-ses has
been one of the most common reason for sick leavein Sweden as well
as in many other countries [30–32]. Suchdata also show a clear
gender gap, with about twice as highsick-leave rates for women as
compared to men [33,34].
The aim of this study was to explore potential genderdifferences
in the management of patients with currentdiagnosed depression,
regarding sick-leave certification, pre-scribed medication
(antidepressants, anxiolytics, and hyp-notic and sedatives), and
referral to psychotherapy.
Materials and methods
Study design and sample
This study used register data from individuals diagnosedwith
depression during 2010–2015 in Uppsala County (about340,000
inhabitants) and collects various data from each indi-vidual
12months prior and until 180 days after case identifi-cation (date
of diagnosis). Although this study has alongitudinal approach in
the collection of the outcomemeasures, the analyses have a
cross-sectional design.
Patients were identified using a database consisting ofdata (no
full text) from the electronic medical files record sys-tem
‘Cosmic’. Labeled data, corresponding to the variablesdescribed
below, were extracted using Microsoft SQL Server/SAP
BusinessObjects BI product suite, concealing informationabout the
identity of individuals also for the researcher per-forming the
task. Once all data had been obtained, the accur-acy of the data
was validated against the Cosmic medical filesfor a few random
cases, by a person not part of the researchteam and working under
law of confidentiality. The validationprocedure was performed to
ascertain that the data obtainedfrom the data base corresponded to
the exact same informa-tion in the full text electronic medical
files. The Cosmic sys-tem is used in both primary and secondary
healthcare byvirtually all healthcare providers in Uppsala County
(at thetime with the exception of one private general
practitionerand ten private psychiatrists, whose patient visits are
not rep-resented in the data, covering maximum 5% of the
patients).The sample is considered as to a high-degree
representhealthcare provided within Uppsala County.
The sample
There were two inclusion criteria. The first was havingreceived
a depression diagnosis (IDC 10 F32/F33) during the
study period. The F32/F33 code encompasses current depres-sive
episode and recurrent depressive disorder, respectively,where
additional code characters could further specify sever-ity or
subtype [35]. The second inclusion criterion was nothaving been
diagnosed with an F32/F32 diagnosis within a12-month period prior
to case identification (wash-outperiod). Thus, a case was
considered being a reasonably newdepressive episode, but does not
rule out having been diag-nosed with a depression diagnosis prior
the 12-monthperiod. To avoid bias, an individual could only become
acase once.
The total sample consisted of 20,227 individuals.
Peoplediagnosed with bipolar disorder (ICD-10 F31, n¼ 543);
severedepression with psychotic symptoms (ICD 10 F32.3/F33.3,n¼
215), or both (n¼ 22) at either the date of diagnosis orduring the
future 6 months were excluded because the man-agement of these
disorders are likely to substantially differfrom other types of
depressive disorders. After exclusion, thetotal sample consisted of
19,448 individuals.
Variables and management of data
Baseline data assessed at the date of diagnosis (T0),
includedinformation about gender, age, and subtype of
F32/F33-diag-nosis as well as whether the depression diagnosis was
set asmain diagnosis or not. Other information collected at T0
waswhether any of the following comorbidity diagnoses (includ-ing
subtypes) was registered the same day: anxiety disorders(F41);
obsessive-compulsive disorders (F42); reaction tosevere stress and
adjustment disorders (F43); or any mentaland behavioral disorders
due to use of alcohol (F10).Individuals with one or more concurrent
F41, F42, or F43diagnoses were considered having psychiatric
comorbidity.Psychiatric comorbidity was also measured during
follow-ups, to be controlled for in the regression models.
Dataabout number of visits to physicians and other
healthcareprofessionals during follow-up was also collected. It was
notpossible to collect data about sick leave and treatment statusat
a time point just before case identification.
Other information collected for each individual was thetotal
number of healthcare visits 12months before the dateof diagnosis,
and whether the visit at the time of diagnosisoccurred in primary
or secondary healthcare and whether itoccurred at an in- or
outpatient healthcare visit. Data at T0was also collected on
assessments of depressive depth usingMADRS score [36] and alcohol
usage using AUDIT score [37],however, with low overall coverage for
these variables.
Some individuals (n¼ 53) were at T0 diagnosed with morethan one
F32 and/or F33 diagnoses, with or without subclassification. This
was managed the following way: F32 andF33 diagnoses, without
further sub classification, weretogether with F32.9 or F33.9
(‘unspecified’) subclassificationrecategorized as F32 and F33
‘Unspecified’, respectively. If anindividual had both an F32.X and
a F33.X diagnosis at T0(n¼ 26), then the F33.X diagnosis was
considered as themain. If an individual had two diagnoses (n¼ 27),
both ineither the F32 or the F33 domain, then the more severe
orspecified diagnosis were considered as the main.
442 P. LYTSY ET AL.
-
Other variables assessed during follow-up periods werewhether a
patient was diagnosed with bipolar disorder ordepression with
psychotic symptoms (reasons for exclusion).
The main independent variable was gender which wasinvestigated
in regards to the following outcomes for differ-ent time periods
until 180 days after diagnosis of depression.
� Whether a sick-leave certificate had been issued at leastonce
(y/n) in the designated outcome period. There wasno data on grade
or duration of sick leave.
� Whether one or more prescriptions of the following
medi-cations were issued at least once in the designated out-come
period:� antidepressants (ATC class N06A, yes/no)� anxiolytics (ATC
class N05B, yes/no)� hypnotics and sedatives (ATC N05C, yes/no)
� Whether the individual had been refereed to
cognitivebehavioral psychotherapy (CBT) within the
rehabilitation-guarantee program (rehabiliteringsgarantin), which
wasan incentive program during 2008–2015 aiming toincrease CBT
treatment in patients with depressive andstress-related disorders
in working age. Not all healthcare-givers were eligible for
reimbursement from that incen-tive program, thus the outcome does
not comprise allCBT therapy given in the county.
Outcomes were measured during four different periods:the day of
diagnosis (T0) and days 1–89 (T1), days 90–180(T2), and the first 6
months, days 0–180 (T0 þ T1 þ T2).
Analysis
The main analyses investigated associations between genderand
the outcomes of (1) whether a sick-leave certificate wasissued;
having received a prescription of (2) antidepressants,(3)
anxiolytics, or (4) hypnotics or sedatives; (5) havingreceived a
CBT referral within the rehabilitation-guaranteeprogram.
Associations were tested at the four time perspec-tives using
multiple logistic regressions presenting results ascrude and
adjusted odds ratios (OR) with 95% confidenceintervals (CI).
Outcomes 1 and 5 (whether a sick-leave certifi-cate was issued and
having been referred to CBT) were onlyassessed in individuals of
working age (18–64 years), whereasthe other outcomes were assessed
in all adults (>18 years),total group (7–97 years) and according
to predefined agegroups, being
-
was 29.9 for receiving a sick-leave certificate, 66.6%
forreceiving a prescription of antidepressants, 22.8% for
receiv-ing a prescription of anxiolytics, and 23.7% for receiving
aprescription of hypnotics and sedatives. There were generallysmall
differences in proportions in regards to gender withina given age
group, whereas there were larger differences inthe outcomes between
age groups (Table 3). Among allpatients, 74.2% (women 74.0%, men
74.6%) were prescribedsome type of psychoactive drug during the
total follow-upperiod of 180 days (not shown in table).
Regression models
In the fully adjusted logistic regressions, men in working
age,as compared to women, had an OR of 0.90 (95% CI0.82–0.98) for
sick-leave certification at the date of diagnosis.The corresponding
numbers for receiving a prescription ofantidepressants in the adult
age population was OR 1.16(95% CI 1.09–1.24); for receiving a
prescription of anxiolytics:OR 1.10 (95% CI 1.02–1.21), and for
having received a pre-scription for hypnotics and sedatives: OR
1.09 (95% CI1.00–1.19). The corresponding numbers for the total
follow-up period (180 days) was an OR of 0.94 (95% CI 0.87–1.01)for
men as compared to women in working age for beingsick-leave
certified, and in the adult population an OR of1.17 (95% CI
1.10–1.26) for having received a prescription ofantidepressants; OR
1.03 (95% CI 0.96–1.11) for havingreceived a prescription of
anxiolytics and an OR of 1.15 (95%CI 1.07–1.24) for having received
a prescription for hypnoticsand sedatives.
None of the patients were referred to CBT at the date
ofdiagnosis, but during follow-up there were no gender differ-ences
in those qualifying for such referrals (Table 4).
Some results of covariates included in the adjusted mod-els are
worth noting. Having a severe depression sub classifi-cation and
having other psychiatric comorbidity were factorsseparately
associated with having higher odds of being sick-leave certified at
the date of diagnosis; OR 1.40 (95% CI1.10–1.79) and OR 1.40 (95%
CI 1.25–1.58), respectively.These findings remained and were more
pronounced wheninvestigating odds of sick-leave certification
within the first180 days (not shown).
Discussion
The aim of this study was to explore gender differences inthe
management of depression in both primary and second-ary healthcare.
The main result showed no large gender dif-ferences in sick-leave
certification at the date of diagnosisnor during the following 6
months. The regression analysessuggest that men had somewhat lesser
risk of being sick-leave certified than women, however, the
difference wassmall and not consistent over follow-up time and
differentage groups. Thus, the results imply that women and
menlargely were treated likewise in terms of being sick-leave
cer-tified when diagnosed with depression.
The same seems to be true also for psychoactive
drugprescriptions, where there were small absolute differences
inissued prescriptions for antidepressants, anxiolytics, and
hyp-notics and sedatives.
The outcomes in this study were assessed for three differ-ent
time perspectives, the date of diagnosis, and during thesubsequent
3 and 6 months, respectively. At the date ofdiagnosis, it is
reasonable to assume that outcomes are dir-ect consequences of the
health situation resulting in thedepressive disorder diagnosis,
most likely carried out by thesame physician. This is not
necessarily the case for the longertime periods. The reasons for
including longer periods wasthat consequences of having depression
(such as receivingtreatments or a sick-leave certificate) may occur
after the daywhen the diagnosis is set. There is, furthermore, a
complexityin healthcare seeking behavior and healthcare
utilizationthat, beyond the clinical condition and its progression,
willaffect how the condition is managed. Factors such as
localorganization of healthcare, availability of resources,
referralroutines, and the physician’s knowledge as well as
thepatient’s own preferences, may affect where and by
whichphysician a diagnosis is set and whom later will treat andcare
for the patient. In Sweden, it is common that patientswith newly
developed and uncomplicated depressive epi-sodes are managed within
primary healthcare, whereaspatients with complex, recurrent, or
severe conditions morecommonly are referred to specialists in
psychiatry.Depending on the severity of the condition, a
psychiatristmay then refer the patient back, with a diagnosis and
treat-ment recommendations, or the psychiatrist might ‘keep’
thepatient if considered warranted. A physician might, further,want
to see how a condition develops before initiating
Table 2. Distribution of characteristics in the study
population, by gender andtotal, at the date of the incident
diagnosis of depressive episode (F32/F33) in2010–2015.
Women Men Totaln¼ 12,469 n¼ 6979 n¼ 19,448
Age, mean years (SD) 41.7 (20.3) 40.7 (19.4) 41. 3 (19.9)Age
groups, yearsYounger than 18 8.1 (1014) 7.2 (506) 7.8 (1520)18–29
27.5 (3429) 30.0 (2087) 28.4 (5516)30–64 48.5 (6049) 49.1 (3426)
48.7 (9475)65 and older 15.9 (1977) 13.8 (960) 15.1 (2937)
Depression-a as main diagnosis 75.3 (9388) 74.4 (5191) 75.0
(14,579)Severe episode of depressiona¶
(F32.2/F33.2)3.5 (437) 4.2 (296) 3.7 (722)
Anxiety diagnosis (F41)disorders
10.5 (1312) 9.3 (649) 10.0 (1962)
OCD diagnosis (F42) 1.2 (143) 1.2 (81) 1.2 (224)Stress diagnoses
(F43) 4.9 (610) 4.3 (299) 4.7 (909)Psychiatric comorbidity
(F41, F42 or F43)15.5 (1932) 14.1 (984) 15.0 (2916)
Alcohol diagnosis (F10) 0.6 (69) 2.0 (138) 1.1 (207)MADRS-S
(mean, n) 23.9 (1311) 24.1 (810) 24.0 (2121)AUDIT (mean, n) 15.5
(313) 18.0 (221) 16.5 (534)Number of healthcare visits last
year (SD)4.4 (6.4) 2.9 (6.1) 3.9 (6.3)
Primary healthcare diagnosis 65.5 (8172) 56.7 (3955) 62.4
(12,127)Secondary healthcare diagnoses
(i.e. psychiatry)34.5 (4297) 43.3 (3024) 37.6 (7321)
Inpatient healthcare 2.8 (346) 4.7 (325) 3.4 (671)Outpatient
healthcare 97.2 (12,123) 95.3 (6654) 96.6 (18,777)
Percentages and n for subgroups in brackets, if not otherwise
stated.aDepressive episode F32 or recurrent depressive disorder
F33.SD: standard deviation; MADRS-S¼Montgomery-Åsberg Depression
RatingScale (range 0–54); AUDIT Alcohol Use Disorders
Identification Test(range 0–40).
444 P. LYTSY ET AL.
-
Table3.
Prop
ortio
nsof
patientshaving
been
sick-leavecertified,p
rescrib
edantid
epressants
(N06A),anxiolytics(N05B),h
ypno
ticsandsedatives
(H&S,N05C),and
referred
toCo
gnitive
behavioral
therapy(CBT)with
inthe
rehabilitation-gu
aranteeprog
ram,arespectively,by
sex,agegrou
ps,and
diffe
rent
timeperspectives
afterbeingdiagno
sedwith
depressive
episod
e(F32/F33,d
ay0)
durin
g2010–2015.
Day
ofdiagno
sis(Day
¼0)
Days1–89
Days90–180
Days0–180
WM
Tot
WM
Tot
WM
Tot
WM
Tot
Agegrou
psn¼12,469
n¼6979
n¼19,448
n¼12,469
n¼6979
n¼19,448
n¼12,469
n¼6979
n¼19,448
n¼12,469
n¼6979
n¼19,448
Sick-leavecertificate
Totalb
17.6
14.9
16.6
15.8
14.8
15.4
11.6
10.0
11.0
31.0
27.8
29.9
(1668)
(821)
(2489)
(1499)
(813)
(2312)
(1099)
(555)
(1654)
(2947)
(1530)
(4477)
Sick-leavecertificate
18–29
11.4
10.5
11.0
11.7
11.6
11.6
8.0
8.2
8.0
22.6
22.5
22.6
(392)
(220)
(612)
(401)
(242)
(643)
(273)
(170)
(443)
(774)
(470)
(1244)
Sick-leavecertificate
30–64
21.1
17.5
19.8
18.2
16.7
17.6
13.7
11.2
12.8
35.9
30.9
34.1
(1276)
(601)
(1877)
(1098)
(571)
(1669)
(826)
(385)
(1211)
(2173)
(1060)
(3233)
Antid
ep.
N06A
Total
49.2
51.8
50.1
38.2
39.6
38.7
26.6
24.1
25.7
65.9
68.0
66.6
(6138)
(3612)
(9750)
(4770)
(2763)
(7533)
(3310)
(1685)
(4995)
(8213)
(4743)
(12956)
Antid
ep.
N06A
<18
22.3
25.7
23.4
(356)
43.6
41.9
43.0
31.8
29.2
31.0
53.2
53.8
53.4
(226)
(130)
(442)
(212)
(654)
(323)
(148)
(471)
(540)
(272)
(812)
Antid
ep.N
06A
18–29
48.8
51.4
49.8
42.8
41.3
42.2
29.0
26.1
27.9
66.4
68.8
67.3
(1678)
(1072)
(2750)
(1466)
(863)
(2329)
(1631)
(545)
(1538)
(2275)
(1435)
(3710)
Antid
ep.N
06A
30–64
52.7
54.9
53.5
38.1
40.1
38.8
27.0
23.4
25.7
68.4
70.3
69.1
(3189)
(1883)
(5072)
(2306)
(1374)
(3680)
(1631)
(803)
(2434)
(4138)
(2404)
(6546)
Antid
ep.N
06A
>65
52.8
51.8
53.5
28.1
32.7
29.6
18.4
19.7
18.8
63.7
65.4
64.3
(1045)
(527)
(1572)
(556)
(314)
(870)
(363)
(189)
(552)
(1260)
(628)
(1888)
AnxiolyticsN05B
Total
13.9
14.9
14.2
13.2
12.4
12.9
8.3
7.4
8.0
22.8
22.7
22.8
(1730)
(1037)
(2767)
(1646)
(868)
(2514)
(1033)
(520)
(1553)
(2848)
(1584)
(4432)
AnxiolyticsN05B
<18
5.6
3.4
4.9
9.4
6.1
8.3
5.9
3.4
5.1
13.2
8.7
11.7
(57)
(17)
(74)
(95)
(31)
(126)
(60)
(17)
(77)
(134)
(44)
(178)
AnxiolyticsN05B
18–29
15.3
15.1
15.2
14.4
11.7
13.4
7.7
5.9
7.0
25.6
23.0
24.6
(524)
(316)
(840)
(495)
(244)
(739)
(265)
(123)
(388)
(877)
(479)
(1356)
AnxiolyticsN05B
30–64
15.3
17.1
15.9
13.1
13.8
13.3
8.4
8.7
8.5
23.6
25.2
24.2
(923)
(586)
(1509)
(791)
(477)
(1262)
(597)
(298)
(805)
(1429)
(865)
(2294)
AnxiolyticsN05B
>65
11.4
12.3
11.7
13.4
12.7
13.2
10.2
8.5
9.6
20.6
20.4
20.6
(226)
(118)
(344)
(265)
(122)
(387)
(201)
(82)
(283)
(408)
(196)
(604)
H&S
NO5C
Total
12.9
14.0
13.3
15.1
16.7
15.7
11.6
11.3
11.5
23.0
25.0
23.7
(1610)
(976)
(2586)
(1886)
(1165)
(3051)
(1442)
(787)
(2229)
(2867)
(1741)
(4608)
H&S
NO5C
<18
9.6
8.1
9.1
18.0
16.0
17.3
12.4
10.0
11.6
22.9
20.0
21.9
(97)
(41)
(138)
(182)
(81)
(263)
(126)
(51)
(177)
(232)
(101)
(333)
H&S
NO5C
18–29
9.7
11.8
10.5
12.4
13.9
13.0
8.6
9.3
8.9
18.3
21.0
19.3
(333)
(246)
(579)
(426)
(289)
(715)
(295)
(195)
(490)
(628)
(439)
(1067)
H&S
NO5C
30–64
15.0
16.5
15.5
15.7
18.4
16.6
11.9
12.0
12.0
24.7
28.2
26.0
(907)
(565)
(1472)
(949)
(629)
(1578)
(721)
(413)
(1134)
(1496)
(968)
(2464)
H&S
NO5C
>65
13.8
12.9
13.5
16.6
17.3
16.8
15.2
11.3
14.6
25.8
24.3
25.3
(273)
(124)
(397)
(329)
(166)
(495)
(300)
(128)
(428)
(511)
(233)
(744)
CBT
Total
00
12.0
1.8
2.0
1.4
1.4
1.4
3.4
3.2
3.3
(195)
(103)
(298)
(135)
(76)
(211)
(324)
(178)
(502)
CBT
18–29
00
02.4
1.9
2.2
2.1
1.5
1.8
4.4
3.4
4.0
(82)
(40)
(122)
(71)
(31)
(102)
(149)
(70)
(219)
CBT
30–64
00
01.9
1.8
1.9
1.1
1.3
1.2
2.9
3.2
3.0
(113)
(63)
(176)
(64)
(45)
(109)
(175)
(108)
(283)
Sick-leavecertificate
issued
byph
ysician,
Antid
ep.:antid
epressants;C
BT:cog
nitiveBehavioral
therapy;H&S:Hypno
ticsandsedatives.
a The
rehabilitation-gu
aranteeprog
ram
was
ereimbu
rsem
entsystem
forCB
Treferrals.Itdo
esno
treflect
thetotaln
umberof
CBTreferrals.
bRestrictedto
patientsof
working
age;18–64years(n¼14,991).
NORDIC JOURNAL OF PSYCHIATRY 445
-
Table4.
Bivariate
andmultivariablelogisticregression
spresentin
god
dratio
s(OR)
with
95%
confidence
intervals(CI)formen,as
comparedto
wom
en,tohave
received
atleaston
cea(1)sick-leavecertificate,(2)
pre-
scrip
tionof
antid
epressants
(N06A),anxiolytics(N05B),or
hypn
oticsandsedatives
(N05C)
and(3)having
been
refereed
tocogn
itive
behavioral
therapy(CBT)aby
agegrou
psat
diffe
rent
timeperio
dsafterbeingdiag-
nosedwith
depressive
episod
e(F32/F33,d
ay0)
durin
g2010–2015.
Sick-leavecertificate
day0
Sick-leavecertificate
days
1–89
Sick-leavecertificate
days
90–180
Sick-leavecertificate
days
0–180
Agegrou
p(years)
n(total
19447)
Gender
(wom
enref)
ORcrud
e(95%
CI)
ORfullmod
elb
(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
elb
(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
elb
(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
elb
(95%
CI)
18–64
14,991
Men
0.82
0.90
0.92
1.00
0.85
0.94
0.85
0.94
(0.75–0.90)
(0.82–0.98)
(0.84–1.01)
(0.91–1.10)
(0.77–0.95)
(0.84–1.05)
(0.79–0.92)
(0.87–1.01)
18–29
5516
Men
0.91
1.04
0.99
1.10
1.03
1.21
1.00
1.13
(0.77–1.09)
(0.87–1.25)
(0.84–1.17)
(0.93–1.32)
(0.84–1.25)
(0.98–1.48)
(0.88–1.14)
(0.99–1.30)
30–64
9475
Men
0.80
0.85
0.90
0.95
0.80
0.86
0.79
0.86
(0.71–0.89)
(0.76–0.95)
(0.81–1.01)
(0.86–1.08)
(0.70–0.91)
(0.75–0.98)
(0.73–0.87)
(0.79–0.95)
Prescriptio
nof
antid
epressants
(N06A)
day0
Prescriptio
nof
antid
epressants
(N06A)
days
1–89
Prescriptio
nof
antid
epressants
(N06A)
days
90–180
Prescriptio
nof
antid
epressants
(N06A)
days
1–180
Agegrou
pn
Gender
(wom
enref)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
7–97
19447
Men
1.11
1.19
1.06
1.09
0.88
0.90
1.10
1.18
(1.04–1.17)
(1.12–1.26)
(1.00–1.12)
(1.03–1.16)
(0.82–0.94)
(0.84–0.97)
(1.03–1.17)
(1.10–1.25)
18–97
17928
Men
1.09
1.16
1.07
1.10
0.88
0.90
1.10
1.17
(1.03–1.16)
(1.09–1.24)
(1.01–1.14)
(1.03–1.18)
(0.82–0.95)
(0.84–0.97)
(1.03–1.18)
(1.10–1.26)
<18
1529
Men
1.21
1.30
0.94
1.00
0.88
0.97
1.02
1.13
(0.94–1.54)
(1.01–1.68)
(0.75–1.16)
(0.80–1.25)
(0.70–1.12)
(0.76–1.23)
(0.82–1.26)
(0.91–1.42)
18–29
5516
Men
1.10
1.13
0.94
1.01
0.87
0.93
1.12
1.19
(0.99–1.23)
(1.01–1.26)
(0.84–1.05)
(0.90–1.13)
(0.77–0.98)
(0.81–1.05)
(0.99–1.25)
(1.05–1.34)
30–64
9475
Men
1.09
1.17
1.09
1.13
0.83
0.86
1.09
1.16
(1.01–1.19)
(1.07–1.28)
(1.00–1.18)
(1.04-1.23)
(0.75–0.91)
(0.78–0.95)
(1.00–1.20)
(1.06–1.28)
>65
2937
Men
1.09
1.14
1.24
1.23
1.09
1.09
1.08
1.12
(0.93–1.27)
(0.97–1.34)
(1.05–1.47)
(1.03–1.45)
(0.89–1.32)
(0.89–1.33)
(0.92–1.27)
(0.94–1.33)
Prescriptio
nof
anxiolytics
N05Bday0
Prescriptio
nanxiolytics
N05Bdays
1–89
Prescriptio
nanxiolytics
N05Bdays
90–180
Prescriptio
nanxiolytics
N05Bdays
1–180
Agegrou
pn
Gender
(wom
enref)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
7–97
19,447
Men
1.08
1.11
0.93
0.98
0.89
0.95
0.99
1.04
(1.00–1.18)
(1.03–1.21)
(0.86–1.02)
(0.89–1.07)
(0.80–0.99)
(0.85–1.06)
(0.92–1.06)
(0.97–1.12)
18–97
17,928
Men
1.09
1.10
0.94
0.98
0.91
0.96
1.01
1.03
(1.00–1.19)
(1.02–1.21)
(0.87–1.04)
(0.89–1.07)
(0.81–1.02)
(0.86–1.08)
(0.94–1.08)
(0.96–1.11)
<18
1529
Men
0.58
0.61
0.63
0.68
0.55
0.59
0.63
0.71
(0.34–1.01)
(0.35–1.07)
(0.41–0.96)
(0.45–1.05)
(0.32–0.96)
(0.33–1.03)
(0.44–0.90)
(0.49–1.03)
18–29
5516
Men
0.99
1.02
0.78
0.84
0.75
0.83
0.86
0.92
(0.85–1.15)
(0.87–1.20)
(0.67–0.92)
(0.71–0.99)
(0.60–0.93)
(0.66–1.04)
(0.76–0.98)
(0.80–1.04)
30–64
9475
Men
1.15
1.14
1.06
1.07
1.04
1.04
1.09
1.10
(1.02–1.28)
(1.02–1.28)
(0.94–1.20)
(0.94–1.21)
(0.90–1.21)
(0.89–1.22)
(0.99–1.20)
(1.00–1.22)
>65
2937
Men
1.09
1.07
0.94
0.91
0.83
0.82
0.99
0.96
(0.86–1.38)
(0.84–1.36)
(0.75–1.18)
(0.71–1.15)
(0.63–1.08)
(0.63–1.10)
(0.82–1.19)
(0.79–1.18)
(continued)
446 P. LYTSY ET AL.
-
Prescriptio
nof
hypn
oticsand
sedatives
(NO5C)day0
Prescriptio
nof
hypn
oticsand
sedatives
(NO5C)days
1–89
Prescriptio
nof
hypn
oticsand
sedatives
(NO5C)days
90–180
Prescriptio
nof
hypn
oticsand
sedatives
(NO5C)days
1–180
Agegrou
pn
Gender
(wom
enref)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORCrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
7–97
19,447
men
1.10
1.09
1.12
1.15
0.97
1.01
1.11
1.13
(1.01–1.19)
(1.00–1.19)
(1.04–1.22)
(1.06–1.24)
(0.89–1.07)
(0.92–1.11)
(1.03–1.19)
(1.05–1.21)
18–97
17,927
men
1.10
1.09
1.15
1.18
0.99
1.03
1.14
1.15
(1.02–1.21)
(1.00–1.19)
(1.06–1.25)
(1.08–1.28)
(0.90–1.09)
(0.94–1.14)
(1.06–1.22)
(1.07–1.24)
<18
1529
men
0.83
0.91
0.87
0.93
0.79
0.84
0.84
0.92
(0.57–1.22)
(0.62–1.35)
(0.65–1.16)
(0.69–1.25)
(0.56–1.11)
(0.58–1.19)
(0.65–1.09)
(0.70–1.21)
18–29
5516
men
1.24
1.24
1.13
1.18
1.09
1.19
1.19
1.16
(1.04–1.47)
(1.04–1.49)
(0.97–1.33)
(1.01–1.40)
(0.91–1.32)
(0.98–1.45)
(1.04–1.36)
(1.06–1.28)
30–64
9475
men
1.12
1.06
1.21
1.19
1.01
1.00
1.20
1.16
(1.00–1.26)
(0.95–1.20)
(1.08–1.35)
(1.06–1.34)
(0.89–1.15)
(0.88–1.14)
(1.09–1.32)
(1.06–1.28)
>65
2937
men
0.93
0.90
1.05
1.03
0.86
0.87
0.92
0.90
(0.74–1.16)
(0.71–1.13)
(0.85–1.29)
(0.84–1.27)
(0.69–1.07)
(0.70–1.10)
(0.77–1.10)
(0.75–1.08)
CBTreferral
day0
CBTreferral
days
1–89
CBTreferral
days
90–180
CBTreferral
days
1–180
Agegrou
pn
Gender
(wom
enref)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
ORcrud
e(95%
CI)
ORfullmod
el(95%
CI)
18–64
14991
Men
nana
0.91
1.00
0.98
1.00
0.94
1.00
(0.72–1.15)
(0.78–1.28)
(0.73–1.28)
(0.75–1.33)
(0.78–1.13)
(0.83–1.21)
18–29
5516
Men
nana
0.80
0.84
0.71
0.72
0.76
0.78
(0.54–1.17)
(0.57–1.24)
(0.47–1.09)
(0.46–1.10)
(0.57–1.02)
(0.59–1.06)
30–64
9475
Men
Na
na0.98
1.11
1.24
1.27
1.09
1.18
(0.72–1.34)
(0.81–1.52)
(0.85–1.83)
(0.86–1.88)
(0.86–1.39)
(0.92–1.52)
a Referralswith
therehabilitation-gu
aranteeprog
ram
was
areimbu
rsem
entsystem
forCB
Treferrals.Itdo
esno
treflect
thetotaln
umberof
CBTreferrals.
bFullmultivariate
mod
eladjusted
forage,
numberof
healthcare
visits
previous
year,having
severe
depression
orno
t,othercurrentpsychiatric
comorbidity,andwhether
thevisitwhendiagno
sedwas
inaprimaryor
second
aryhealthcare
setting.
NORDIC JOURNAL OF PSYCHIATRY 447
-
treatment or issuing a sick-leave certificate, and a
patientmight want to consider a treatment option some time
beforeaccepting it. We, thus, believe it was relevant to assess
thestudied outcomes also over time. The potential drawback ofthis
approach is that we cannot be sure that the depressivedisorder
directly contributes to a specific outcome thatoccurs during a
period of time. This mainly concerns thesick-leave outcome in the
analyses, since it is possible to besick-leave certified for other
diagnoses than depression. Ifwomen and men are as likely to be
sickness certified orother diagnoses during follow-up, this will
not affect ourmain analysis, which assesses gender differences.
Less than two thirds (62.4%) of the population were diag-nosed
in primary healthcare. This seems to be a low figureconsidering
that most healthcare is delivered by generalpractitioners, and it
might reflect referral routines as well pri-mary healthcare’s known
low sensitivity to identify clinicallydepressed patients [38].
Another reason, contributing towhere patients seek care, is that
people in Uppsala have thepossibility to seek secondary healthcare
directly, by self-refer-rals. Such referrals are considered by
medical specialists andthe individual is then either welcomed or
directed to anadequate care level.
The strengths of this study include the high coveragecommunity
sampling method with no attrition, coveringalmost all healthcare
given. It is further a strength that it waspossible to control for
comorbidity and number of healthcarevisits, since these factors are
likely to be associated with theoutcomes. The main limitations of
the study include themany potential factors that might affect the
management ofdepression and that this study has not been able to
controlfor. The covariates used in this study were limited to
thoseaccessible within the search terms of the database.
Thedenominator of all outcome proportions are all patients, notthe
patients at risk of the outcome. It was not possible todetermine if
the patients already were on sick leave ortreated with any
psycho-active drug at the time of outcomemeasurement. Nor was it
possible to control whether partici-pants moved out of the county
or sought healthcare else-where during follow-up. For these
reasons, proportions andrates of the outcomes are believed to be
somewhat underes-timated. We tried to alleviate these problems by
using awash-out period and by the adjustment of accessible
covari-ates. The washout period for having a F32/F33 diagnosis
was12months, but since an individual only could be includedonce
this means that some individuals had washout periodslonger than
12months. We tested gender differences in man-agement for
depression for five different outcomes, but alsoperformed many
subgroups analyses, which increases therisk of false positive
findings. Thus, we suggest the results ofthe regression analyses to
be viewed in terms of over alltrends.
The adjusted analyses controlled for having severedepression. It
would have been desirable to adjust fordepression severity using
MADRS-S estimates, however, thismeasure was only assessed in 10.9%
of the cases; consideredtoo few to be included in the fully
adjusted regressionmodels, reducing the overall study sample. The
averages
MADRS-scores assessed, nevertheless, did not differ
signifi-cantly between women and men (Table 1).
The fact that a higher proportion of men in all agesreceived
prescriptions in all three categories of psychoactivedrugs in this
study is notable. It is known that women ingeneral are prescribed
more psychoactive drugs than men.The Swedish Board of Health and
Welfare provides statisticsof all dispensed prescribed drugs and it
is possible to investi-gate gender differences in this database
[39]. When usingthese statistics: antidepressants, anxiolytics, and
hypnoticsand sedatives (as daily day doses/1000 inhabitants)
andrestricting data to the years of this study (2010–2015),
theaverage women-to-men ratio was 1.86 for antidepressants,1.39 for
anxiolytics, and 1.69 for hypnotics and sedatives.These figures
indicate that women consume more psycho-active drugs. However,
according to the results in this study,this is not because women
are more likely to receive pre-scriptions at the time of diagnosis
or in the followingmonths. Instead, the reasons seem to be that
more womenthan men are diagnosed with depression, a finding that
wasalso apparent in the present study where almost two thirdsof the
cases in the study population were women. The find-ings in this
study, thus, do not support the idea that womenand men are treated
differently regarding sick-leave certifica-tion or medication. On
the contrary, although there weresmall differences, the main
pattern regarding sick leave andtreatment seemed to be gender
neutral.
Conclusion
In conclusion, there were small differences in proportions ofmen
and women who were sick-leave certified or
prescribedantidepressants, anxiolytics, or hypnotics and sedatives
atthe date diagnosed with depression as well as during the
fol-lowing 6months. Men had, compared to women, somewhatlower odds
of being sick-leave certified and somewhathigher odds of receiving
prescriptions of psychoactive drugsthe same day they were
diagnosed; however, the overallconclusion is that women and men
diagnosed with depres-sion generally seems to be treated in equal
ways regardingthe here studied aspects.
Acknowledgements
The authors are much grateful to Mats Norman and Mats Bystr€om
forhelp with the planning and execution of the extraction of
data.
Disclosure statement
No potential conflict of interest was reported by the
authors.
Funding
This work was supported by research grants from the Uppsala
AcademicHospital (no grant number, for the first author).
448 P. LYTSY ET AL.
-
Notes on contributors
Per Lytsy, MD PhD is specialised in social medicine. He does
research atthe Department of Clinical Neuroscience, Karolinska
Institutet and holdsa position the Swedish Agency for Health
Technology Assessment andAssessment of Social Services (SBU). His
research interests involveresearch methodology, mental and public
health and insurancemedicine.
Johan Hallqvist, MD PhD, senior professor in preventive medicine
andformer head of Department of Public Health and Caring Sciences
atUppsala University. His research interest involves research
methodology,social epidemiology and health policy.
Kristina Alexanderson, PhD, professor of social insurance, has
>300 ori-ginal international peer-reviewed publications. Her
research focus is onhealth and sickness absence, in general and
regarding specific diagnosesand life situations. She uses both
epidemiological and qualitative analyt-ical methods and has
established large population-based research data-bases. Extensive
international collaborations.
Annika Åhs, PhD, is a clinical psychologist and researcher. The
mainfields of her research interest are predictors of health and
health careutilization in relation to employment status. She works
as a clinicalpsychologist in psychiatry.
ORCID
Per Lytsy http://orcid.org/0000-0003-1949-6299
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450 P. LYTSY ET AL.
http://www.socialstyrelsen.se/statistik/statistikdatabas/lakemedelhttp://www.socialstyrelsen.se/statistik/statistikdatabas/lakemedel
AbstractIntroductionMaterials and methodsStudy design and
sampleThe sampleVariables and management of dataAnalysisEthics
ResultsRegression models
DiscussionConclusionAcknowledgementsDisclosure statementNotes on
contributorsReferences