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O R I G I N A L A R T I C L E

Demands, skill discretion, decision authority and social climateat work as determinants of major depression in a 3-year follow-up

study

Andres Fandino-Losada Yvonne Forsell

Ingvar Lundberg

Received: 13 July 2011 / Accepted: 18 June 2012/ Published online: 4 July 2012

Springer-Verlag 2012

Abstract

Purpose The psychosocial work environment may be adeterminant of the development and course of depressive

disorders, but the literature shows inconsistent findings.

Thus, the aim of this study is to determine longitudinal

effects of the job demandscontrolsupport model

(JDCSM) variables on the occurrence of major depression

among working men and women from the general

population.

Methods The sample comprised 4,710 working women

and men living in Stockholm, who answered the same

questionnaire twice, 3 years apart, who were not depressed

during the first wave and had the same job in both waves.

The questionnaire included JDCSM variables (demands,

skill discretion, decision authority and social climate) and

other co-variables (income, education, occupational group,

social support, help and small children at home, living with

an adult and depressive symptoms at time 1; and negative

life events at time 2). Multiple logistic regressions were run

to calculate odds ratios of having major depression at time

2, after adjustment for other JDCSM variables and co-

variables.

Results Among women, inadequate work social climate

was the only significant risk indicator for major depression.Surprisingly, among men, high job demands and low skill

discretion appeared as protective factors against major

depression.

Conclusions The results showed a strong relationship

between inadequate social climate and major depression

among women, while there were no certain effects for the

remaining exposure variables. Among men, few cases of

major depression hampered well-founded conclusions

regarding our findings of low job demands and high skill

discretion as related to major depression.

Keywords Major depression

Psychosocial factors

Work environment Demandscontrolsupport

Population survey Follow-up

Introduction

The psychosocial work environment can be an important

determinant of the development and course of depressive

disorders (for reviews, see Stansfeld and Candy 2006;

Bonde2008; Netterstrm et al.2008). There are different

models to describe this environment, but the job demands

control(support) model (JDCSM) has been the most

influential since its appearance in the late 1970s. The

JDCSM involves two logical and easily understandable

concepts: job demands and job control (or decision lati-

tude). Job demands refer to task requirements and work

load. Job control refers to individuals ability to control

their work activities. Furthermore, Karasek emphasised

that both demands and control determine the psychological

strain at work, and job strain was defined as the combi-

nation of high demands and low control (Karasek 1979).

A. Fandino-Losada (&) Y. Forsell

Division of Public Health Epidemiology, Department of PublicHealth Sciences, Karolinska Institutet, Norrbacka, Plan 7,

Karolinska Hospital, 171 73 Stockholm, Sweden

e-mail: [email protected]; [email protected]

A. Fandino-Losada

School of Public Health/CISALVA Institute,

Universidad del Valle, Cali, Colombia

I. Lundberg

Department of Medical Sciences,

Occupational and Environmental Medicine,

Uppsala Universitet, Uppsala, Sweden

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DOI 10.1007/s00420-012-0791-3


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A third dimension was later added to the model: social

support at work. It is defined as the support received from

colleagues and supervisors at work, which hypothetically

buffers the effect of job strain situations on health out-

comes (Johnson and Hall1988; Johnson et al.1989). Thus,

the last model is called the job demandscontrolsupport

model (JDCSM).

The literature shows inconsistent results regarding therole of JDCSM variables as determinants of psychiatric

disorders, among other reasons because most studies have

been cross-sectional (van der Doef and Maes 1999; de

Lange et al. 2005). Longitudinal studies are necessary,

although not necessarily sufficient, to study causal rela-

tionships (Ahola and Hakanen 2007). In a pioneering

review, Stansfeld and Candy (2006) performed a meta-

analysis of 11 longitudinal studies on psychosocial occu-

pational exposures as determinants of psychological distress,

depression and anxiety.

Specifically for major depression, results from original

longitudinal studies are also inconsistent: some authorshave found that only job demands were determinants of

depressive disorders (Plaisier et al.2007), and others have

found decision latitude (or its components) as the unique

risk factor (Griffin et al.2002; Rugulies et al.2006; Clays

et al.2007; Joensuu et al.2010); other studies indicate that

both job demands and control are independent determi-

nants of the development of depressive disorders or

depressive symptoms (Paterniti et al.2002). Additionally,

social support at work has appeared as a direct and inde-

pendent determinant of depressive symptoms or depressive

disorders in several longitudinal studies (Niedhammer et al.

1998; Ylipaavalniemi et al. 2005; Griffin et al. 2007;

Stoetzer et al.2009). Two recent systematic reviews have

tried to consolidate findings from longitudinal studies

(Bonde 2008; Netterstrm et al. 2008), but only Bonde

calculated averaged odds ratios by meta-analysis. Both

reviews agreed on that high demands, low job social sup-

port and high job strain appeared more consistently as

moderate risk factors for depression, while results regard-

ing job control were contradictory. In any case, both groups

of authors acknowledged the heterogeneity of JDCSM

measures used by the original studies selected into each

review. Moreover, these systematic reviews are based on

small number of papers per JDCSM dimension, that is,

between 2 and 5 papers.

Although longitudinal studies imply progress in the

study of psychosocial determinants of depressive disorders,

a number of methodological problems remain: first, most

follow-up studies have been performed in specific occu-

pations (e.g. nurses, civil servants, hospital employees,

forest industry employees) (Bourbonnais et al. 1999;

Stansfeld et al.1999; Ylipaavalniemi et al.2005; Joensuu

et al.2010). Although studies on these groups could have

high internal validity and power, their conclusions may be

difficult to extrapolate to other working groups (Bourbon-

nais et al.1999; Joensuu et al.2010). Thus, research also

focuses on the psychosocial work situation in the general

population (Rugulies et al.2006; Magnusson Hanson et al.

2009; Stoetzer et al.2009; Wang et al.2009).

Second, rather few studies have assessed major

depression by using more exact measures such as physi-cians diagnoses, hospital admission diagnoses or vali-

dated lay-administered diagnostic algorithms. In contrast,

most longitudinal studies have used scales of general

depressive symptoms as a proxy for diagnoses, with the

disadvantage of having lower sensitivity and specificity in

the assessment of the health outcome (e.g. de Lange et al.

2002; Paterniti et al. 2002; Clays et al. 2007; Andrea

et al. 2009).

Third, psychosocial work factors have been addressed by

using different conceptual approaches, although the concept

of work stress lies behind them in most studies (Stansfeld

and Candy2006). This situation does not allow easy com-parisons between different studies or generalisation of study

findings. Some studies have used shorter forms of the

JDCSM scales (Shields2006; Wang et al.2009), and others

have developed their own scales (Tokuyama et al. 2003;

Ylipaavalniemi et al.2005; Rugulies et al.2006; Joensuu

et al.2010). Furthermore, a combined index was created in

a study (Wang2005), which did not gauge the orthogonal

dimensions originally proposed by the JDCSM (Karasek

and Theorell1990).

Finally, most longitudinal studies of the JDCSM and

depressive disorders have used a dichotomic approach to

operationalise the JDCSM scales, that is, a cut-off point

was selected and then the scale was dichotomised by

splitting scores into high and low categories (Stansfeld and

Candy 2006). In his seminal study, Karasek proposed a

median split methodology to create the dichotomic cate-

gories (Karasek1979), which has been followed by most

researches (Wang 2004; Rugulies et al. 2006; Virtanen

et al.2007). However, to identify doseresponse effects of

JDCSM variables, it is necessary to use finer exposure

categories. Accordingly, some cross-sectional studies have

addressed this issue by using scale tertiles (Shields2006)

or scale quartiles (Michelsen and Bildt2003), although the

longitudinal studies lack this methodological approach

(Blackmore et al. 2007; Bonde 2008; Netterstrm et al.

2008).

Hence, the aims of this study are as follows:

To determine the longitudinal effects of job demands,

skill discretion, decision authority and social climate

(support) at work on the occurrence of major depres-

sion (assessed by a diagnostic algorithm) among

working men and women from the general population.

592 Int Arch Occup Environ Health (2013) 86:591605

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To test the dose response of the job demandscontrol

support model (JDCSM) components on risk of major

depression over time.

We hypothesise that high job demands, inadequate skill

discretion, inadequate decision authority and inadequate

social climate at work are risk factors for the occurrence of

major depression among working men and women.

Methods

Population and sample

The study sample was drawn from the PART studya

longitudinal study of mental health, work and relations

ongoing in Stockholm County, Sweden. The study popu-

lation at wave 1 included 19,744 individuals aged

2064 years registered in the county and randomly selected

from the county council register. The ethical committee atthe Karolinska Institutet, Stockholm, approved the study,

and informed consents were obtained from all participants.

Wave 1 (19982000)

(Time 1: T1). Subjects in the intended population sample

received a questionnaire by mail, and 10,443 individuals

responded (53 % of the intended sample). An extensive

non-response analysis was done by using available official

registers. Participation was related to female gender, higher

age, higher income and education, being born in the Nordic

countries, and having no psychiatric diagnosis in the hos-pital discharge register or in the early retirement register.

Associations between age, gender, income, country of

origin and inpatient hospital care due to psychiatric diag-

nosis were calculated for participants and non-participants

separately. The odds ratios (ORs) for these associations

were very similar among participants and non-participants

(Lundberg et al.2005).

Wave 2 (20012003)

(Time 2: T2). All participants from the first wave received a

second, almost identical, questionnaire 3 years later. The

participation rate at the follow-up phase (T2) was 83 %

(n = 8,622). Attrition in the second phase was associated

with thesame conditions as in the first phase, but associations

between putative risk factors and major depression, deter-

mined at T1, were the same in both the T2-participant and

T2-non-participant subsamples (Bergman et al. 2010).

Additionally, participants diagnosed with major depression

at time 1 had a higher probability of non-participationat time

2 (OR = 1.6; 95 % confidence interval (CI) = 1.12.4).

Study sample in the present study

For this study, only participants who were working at T1

(employed and self-employed) and who continued in the

same job at T2 were selected, that is, 4,710 subjects

(55.3 % from the T2 sample), and among them, 244 per-

sons were excluded because they fulfilled the case criteria

for major depression at T1 according to the MDI algorithm(see measures below), that is, 5 % of the remaining sample.

Additionally, one case was excluded because there was no

information about his/her depressive status at T2. Finally,

our study sample included 4,427 subjects (51 % from the

T2 sample), 2,415 women and 2,012 men.

Measures and instruments

Exposure variables

Inadequate social climate at work is a scale measuring

social support at work, extracted from the SwedishDemandControlSupport Questionnaire (DCSQ) (Sanne

et al.2005), which did not cover instrumental support at the

time of the first PART data collection (Hallstrom et al.

2003) and was oriented towards the atmosphere at the

worksite (Theorell and Karasek 1996; Landsbergis et al.

2000). The social climate scale has six questions: There is

a calm and pleasant atmosphere at my work place; There

is good sense of fellowship; My workmates support

me; If I have a bad day, my colleagues understand it;

I have a good relationship with my superiors; I have a

good relationship with my workmates. The four response

alternatives were Perfectly true, True, Not true andNot true at all for all questions, using a Likert scale (14

points), adding up items into the scale score (624 points)

with higher scores indicating lower social climate. Validity

studies show that this scale explained 72 % of the variance

in a total index of social support originally containing 15

items (Ahlberg-Hulten et al. 1995) with an adequate

solution in principal component analyses and a satisfactory

internal consistency, that is, Cronbachs alpha= 0.83

(Sanne et al.2005). In the present study, the scale showed a

Cronbachs alpha of 0.86 at T1.

Also the DCSQ, which is a translation/adaptation of

Karaseks demanddecision latitude questionnaire (Theorell

and Karasek1996; Landsbergis et al. 2000), was used to

assess psychological demands, skill discretion and decision

authority (Karasek and Theorell 1990; Karasek 1979).

There were five questions on job psychological demands

and six on job control (four questions on skill discretion

and two questions on decision authority). The questions on

psychological demands concerned requirements to work

very fast, to work very hard, to do an excessive amount of

work, to have enough time to get the job done and to have

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conflicting demands at work. Cronbachs alpha for the job

demands scale at T1 was 0.74. The four questions on skill

discretion concerned requirements to learn new things:

whether skills were required, whether creativity was

required and whether the work was monotonous or vari-

able. Cronbachs alpha for the skill discretion scale at T1

was 0.66. The two questions on decision authority con-

cerned freedom to decide what should be done and howthe job should be done. Cronbachs alpha for decision

authority scale at T1 was 0.77. The last two scales were

reversed for the analyses; thus, they expressed inadequate

job skill discretion and inadequat e job decision author-

ity. Cronbachs alpha for the job control scale at T1 was

0.73.

Outcome variable

Major depression was assessed by the Major Depression

Inventory (MDI) algorithm (Bech et al. 1997; Bech and

Wermuth 1998). Validity studies for the MDI have beenperformed in population-based settings in Sweden (Forsell

2005), as well as in clinical settings in European countries

(Bech et al.2001; Olsen et al.2003; Cuijpers et al.2007).

The sensitivity of MDI was 0.78 and the specificity was

0.78 in a study based on the first PART data collection

(Forsell 2005). The MDI scale includes DSM-IV criteria

for major depression; each symptom must have been

present more than 2 weeks, using a six-point intensity

Likert scale (from not at all to all the time). The MDI

can be used as a diagnostic instrument in which the items

are dichotomised to indicate the presence or absence of

each symptom following a diagnostic algorithm, but it can

also be used as a continuous scale of depressive symptoms

(ranging from 0 to 50 points). This scale had a Cronbachs

alpha of 0.92 at T1 and 0.92 at T2 in the study sample. The

outcome measure was defined as the point prevalence of

major depression assessed by the MDI algorithm at the

follow-up (T2).

Confounders

In this study, the following variables were selected as

potential confounders in multivariable regression models,

because they have been associated with both depressive

disorders and psychosocial work factors in several studies:

age, living without another adult, little help with household

chores, small children at home, education level, income

level, occupational groups, inadequate availability of social

attachment (as a continuous score), depressive symptoms at

baseline (T1), also as a continuous score and the number of

potentially negative life events at T2 (Muntaner et al.1998;

Griffin et al.2002; Michelsen and Bildt2003; Mitchell et al.

2003; Bonde2008; Choi and Marks2008; Netterstrm et al.

2008; Virtanen et al. 2008; Kaikkonen et al. 2009;

Vanroelen et al.2010). Small children were defined as those

younger than 7 years of age. Education was divided into

three levels depending on years of completed studies:

compulsory school (B9 years), uncompleted upper sec-

ondary school (1011 years) and completed upper second-

ary school or more (C12 years). Income was divided into

four levels: 149 K SEK or less (thousands of SwedishCrowns), 150199 K SEK, 200299 K SEK, 300 K SEK or

more (1 & 9.33 SEK). Occupational groups were defined

according to the first level of classification in the Nordic

Standard Occupational Classification (NSOC) of 1989

(Statistiska centralbyran1989) and still valid in 19982000

(T1), which originally consists of 12 main groups. These

were reclassified into 7 groups due to small numbers in

some NSOC groups: unskilled manual (blue collar) work-

ers, skilled manual (blue collar) workers, lower non-manual

(white collar) workers, middle non-manual (white collar)

workers, higher non-manual (white collar) workers, self-

employed professionals and entrepreneurs. Availability ofattachment in the social network was assessed with three

questions from a Swedish modification of the Interview

Schedule for Social Interaction (ISSI) (Henderson et al.

1980; Unden and Orth-Gomer1984); each question used a

four-point Likert scale (1= completely true to 4= not at

all), and they were added up in a single score; the higher the

score, the worse the social attachment. Cronbachs alpha for

the inadequate availability of the social attachment scale at

T1 was 0.75. Depressive symptoms at baseline were

assessed by the Major Depression InventoryMDI (Bech

et al. 1997; Bech and Wermuth 1998)as a continuous

score ranging from 0 to 50 points, with a Cronbachs alpha

of 0.92. A list of 22 potentially negative life events (e.g.

divorce, death of a child) was provided in the questionnaire

(Hallstrom et al.2003), and each respondent stated whether

they occurred or not during the last 12 months before filling

the questionnaire at T2. The number of potentially negative

life events was categorised in the analyses as none, one,

two, and three or more events.

Statistical analyses

In this paper, the JDSCM scales on job demands, inade-

quate job skill discretion, inadequate job decision authority

and inadequate work social climate were split by cut-off

points defined by scale-specific quartiles obtained from the

current study sample, that is, subjects without major

depression at T1 according to the MDI algorithm and who

had the same job at both waves. Thus, sample distribution

quartiles, independently for each JDCSM variable, were

used for defining the exposure groups (i.e. exposure cate-

gories grouping scores of JDCSM scales). Due to the

limited number of scale points, the scales could not be


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divided into exact medians or quartiles. The true percent-

ages by intended quartiles and median are shown in

Tables1, 2, 3 and 4. Median split exposure groups were

defined merging the two lowest (Q1 and Q2) and the two

highest (Q3 and Q4), respectively. The quartile and median

cut-off scores for defining the JDCSM exposure groups are

shown in Tables1, 2 and 3 for the quartile splits and

Table4 for the median splits. The JDCSM quartilesresulted in percentages different to the theoretical 25 % in

each one, given the empirical distribution of scales scores;

for example, for job demands, a 12-point score was not

only the 25th percentile but also the 35th percentile. There

were not significant differences in cut-offs between women

and men for the JDCSM dimensions; thus, the same divi-

sions were used for generating the exposure categories in

Tables1 (womens results) and 2 (mens results).

Nearly eleven per cent (10.64 %) of the subjects records

had at least one variable with missing values; thus, the

regression imputation method (Raghunathan2004; Donders

et al.2006; Groves et al.2009) was used to complete themissing values in exposure variables and confounders before

running the regression models. For testing the robustness of

results from these models, all regressions were repeated

without imputed values. Initially, cross-tabulations and sin-

gle-regression analyses were done to explore associations

between the outcome variable and exposures and con-

founders using the crude data (Tables1, 2). Then, regression

analyses followed this sequence: firstly, exposure categories

(quartiles of JDCSM variables) were used in block enter

logistic regressions, starting with the simplest logistic

regression models (only one JDCSM variable) with occur-

rence of major depression at T2 as the outcome, using the

lowest quartile as the reference group for each variable.

These regression models were called Model 0, that is, the

unadjusted ones. Afterwards, multiple logistic regressions

were run to calculate the ORs of having the outcome (i.e.

major depression) at follow-up (T2) for each psychosocial

work environment variable quartiles compared with the

reference quartile, adding the confounding variables in each

step. In this manner, Model 1 adjusted for all JDCSM vari-

ables (i.e. job demands, skill discretion, decision authority

and job social climate) and age. Model 2 included Model 1

variables and additionally adjusted for living alone status,

inadequate social availability (scale score), having little help

with household chores, having small children at home and

number of negative life events at T2. Model 3 included

Model 2 variables and additionally adjusted for education

level, income level and occupational groups. Model 4

included Model 3 variables and additionally adjusted for

depressive symptoms score (MDI) at T1.

Model 4 could be considered an over-adjusted regres-

sion model, because it is controversial whether a high level

of baseline depressive symptoms (T1) was a confounder or

an intermediate variable (Thielen et al.2011), but on the

other hand, directed acyclic graphs (DAGs) analysis

(Hernan et al.2002) showed that it was necessary to control

for depressive symptoms at T1 as a confounder, due to

relationships between peoples mood and self-assessment

of their psychosocial work environment (de Lange et al.

2005; Stansfeld and Candy2006). All described analyses

were done for mens and womens subsamples, separately.Among men, a median split approach for JDCSM variables

was used instead of the quartile approach, due to the small

number of cases among them. Supplementary analyses

were done among women using a median split approach in

order to compare their results with the median approach

among men. Collinearity among co-variables in regression

models was checked using variance inflation factors (VIFs)

(Belsley et al. 1980); no collinearity was found. Finally,

trends over quartiles of significant JDCSM variables were

explored with the trend Walds test and orthogonal poly-

nomial contrasts for linear, quadratic and cubic trends

(Szklo and Nieto 2007). Analyses were done by usingSTATA 11.2 (StataCorp2009).

Results

The point prevalence of major depression at the third year

follow-up (T2) was 3.77 % (95 % CI= 3.214.33 %),

being 5.63 % (95 % CI= 4.716.55 %) among women

and 1.54 % (95 % CI = 1.002.08 %) among men, based

on 136 cases among women and 31 cases among men.

Tables1and2describe the distribution of the JDCSM

variables andthe selected confounders among cases andnon-

cases for each gender (Tables1 and 2, respectively). Among

women, the cases tended to have higher job demands, lower

job skill discretion and lower job social climate, to receive

less help with household chores, to have lower education and

income levels,to belong to the unskilled manual (blue collar)

workers, to the lower non-manual (white collar) workers or

to theentrepreneurs, to be younger, to have lower availability

of social attachment, to have higher levels of depressive

symptoms at T1 and to have experienced more negative life

events (one, two or three or more categories) at T2 when

compared with controls (Table1). For men, the cases tended

to have lower job demands, lower job skill discretion, lower

job decision authority and lower job social climate, to live

without other adults, to receive less help with household

chores, to have lower income levels, to belong to the skilled

manual (blue collar) workers or to the lower non-manual

(white collar) workers, to have lower availability of social

attachment andto have higher levels of depressive symptoms

at T1 and to have experienced more negative lifeevents(one,

two or three or more categories) at T2 when compared with

the controls (Table2).


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Table 1 Crude associations between study variables at time 1 and major depression at time 2 for women

Exposure variables Depressed T2

N= 136

Non-depressed T2

N= 2,279

Crude ORs

Categorical variables T1 and T2 Na % Na % OR (95 % CI)

Job demands T1b

Lowest (512 points)c 39 29.6 850 37.7 1

Low (13 points) 20 15.2 310 13.8 1.41 (0.812.45)

High (1415 points) 32 24.2 539 23.9 1.29 (0.802.09)

Highest (1620 points) 41 31.1 555 24.6 1.61* (1.032.53)

Inadequate skill discretion T1b

Lowest (46 points)c 38 27.9 728 32.1 1

Low (7 points) 30 22.1 432 19.0 1.33 (0.812.18)

High (89 points) 34 25.0 739 32.6 0.88 (0.551.42)

Highest (1016 points) 34 25.0 370 16.3 1.76* (1.092.84)

Inadequate decision authority T1b

Lowest (2 points)c 39 28.7 693 30.5 1

Low (3 points) 18 13.2 483 21.2 0.66 (0.371.17)

High (4 points) 37 27.2 528 23.2 1.25 (0.781.98)

Highest (58 points) 42 30.9 572 25.1 1.30 (0.832.05)

Inadequate job social climate T1b

Lowest (69 points)c 22 17.2 760 35.4 1

Low (1011 points) 29 22.7 462 21.5 2.17** (1.233.82)

High (1213 points) 36 28.1 569 26.5 2.19** (1.273.76)

Highest (1423 points) 41 32.0 356 16.6 3.98*** (2.336.78)

Living without an adult T1d 37 27.2 630 27.7 0.98 (0.661.44)

Little help with house chores T1d 72 53.3 954 42.1 1.57* (1.112.23)

Small children at home T1d 31 22.8 393 17.3 1.41 (0.932.13)

Negative life events at T2

Nonec 10 7.3 760 33.4 1

One 25 18.4 678 29.8 2.80** (1.345.88)Two 28 20.6 439 19.3 4.85*** (2.3310.07)

Three or more 73 53.7 400 17.5 13.87*** (7.0827.16)

Education level T1

9 years or less 24 17.7 303 13.3 1.84* (1.113.04)

1011 years 62 45.6 813 35.7 1.77** (1.212.59)

12 years or morec 50 36.8 1159 51.0 1

Yearly income level T1

149 K SEK or less 15 11.0 153 6.7 2.05* (1.143.69)

150199 K SEK 18 13.2 255 11.2 1.48 (0.862.53)

200299 K SEK 39 28.7 526 23.1 1.55* (1.032.34)

300 K SEK or morec 64 47.1 1339 58.9 1

Occupational groups T1

Unskilled manual workers 18 14.1 243 11.2 1.87 (0.933.81)

Skilled manual workers 8 6.2 111 5.1 1.84 (0.764.44)

Lower non-manual workers 39 30.5 459 21.1 2.16* (1.173.99)

Middle non-manual workers 32 25.0 672 30.9 1.21 (0.652.27)

Higher non-manual workersc 15 11.7 382 17.6 1

Self-employed professionals 6 4.7 183 8.4 0.83 (0.322.19)

Entrepreneurs 10 7.8 121 5.6 2.10 (0.924.81)


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Table3 describes the simple and adjusted logistic

regression results for study variables in relation to

occurrence of major depression at T2 among women. In

this manner, job demands (highest quartile, OR= 1.69,

95 % CI = 1.082.64) and lack of skill discretion at

work (highest quartile, OR= 1.7595 % CI = 1.092.83)

were significant predictors of major depression only in

the crude model (Model 0). When analysis was adjusted

for all JDCSM variables and age in Model 1, jobdemands and lack of job skill discretion effects were no

longer significant in that and subsequent models. Inade-

quate social climate at work appeared as a significant

determinant of major depression at T2 in all adjusted

models; furthermore, the effect was significant for all

quartiles (when compared with the lowest quartile as the

reference category). Indeed, the highest quartile of

inadequate social climate remained as that with the

highest OR in Model 3 (OR= 3.35; 95 % CI= 1.88

5.99), but in Model 4, its OR was the second highest after

the low quartile (OR= 2.09 for the latter vs. OR = 2.06

for the former). The trend analysis rendered a significantlinear trend (X2(1) = 4.31; p =0.038) over inadequate

social climate quartiles, but neither a quadratic nor a cubic

trend.

Analyses with non-imputed variables showed slightly

lower ORs (data not shown) compared with those in

Table3, and some ORs in non-imputed analyses were not

statistically significant, although close to be significant

(p\ 0.10). Supplementary analyses for median splits of

JDCSM variables, using the same model definitions as

above, were done for women. Only inadequate social cli-

mate over the median was significant as a risk factor for

major depression occurrence in some adjusted models (1and 2) with ORs ranging from 1.94 (95 % CI = 1.352.81)

to 1.52 (95 % CI = 1.032.23). In the fully adjusted model

(which included depressive symptoms at T1), inadequate

social climate was not significant (p = 0.20). Since the

median split did not show any significant association, we

kept the quartiles split of inadequate social climate. We

found that the three upper quartiles showed similar ORs in

Model 4, which were all significantly higher than the first

quartile (see Table3).

Table4 describes the crude and adjusted logistic

regression results among men by using the median split

approach for the JDCSM. Due to the few cases among

men, no JDCSM variable was significant in the crude

model (Model 0), but when analysis was adjusted for all

JDCSM variables and age in Model 1, high job demands

and low social climate at work appeared as a significant

protective factor (OR= 0.41; 95 % CI = 0.190.88) and

as a risk factor for major depression (OR = 2.37; 95 %CI = 1.125.02), respectively. Furthermore, high job

demands remained as a protective factor in subsequent

models, which included more confounders (OR Model

3 = 0.23; 95 % CI= 0.090.57; OR Model 4 = 0.24;

95 % CI = 0.100.60). In contrast, the social climate at

work effect was no longer significant in models including

more confounders (Models 2 to 4). On the other hand, low

skill discretion appeared as a protective factor against

major depression in Model 3 (OR= 0.30; 95 %

CI = 0.110.79) and Model 4 (OR = 0.32; 95 %

CI = 0.110.90). Additionally, analyses with non-imputed

variables showed significant and very similar ORs com-pared to those in Table4(data not shown).

Discussion

The literature shows inconsistent results for the longitudi-

nal relationships between JDCSM variables and depressive

disorders, but two recent meta-analyses and a system-

atic review (Stansfeld and Candy 2006; Bonde 2008;

Netterstrm et al.2008) showed coherent results on high

job demands and low occupational social support as risk

factors for subsequent major depressive disorders or mentalillness occurrence. In contrast, these reviews showed con-

tradictory results regarding job control, or its components,

as risk or protective factors for major depression. The

findings about major depression in these reviews were

based on small number of papers for each JDCSM

dimension. In our study, the findings regarding inadequate

job social climate are in line with the current evidence and

show that, in particular, a good social climate seems pro-

tective against major depression among women, but our

Table 1 continued

Continuous variables T1 Mean SD Mean SD OR (95 % CI)

Age 40.43 10.54 42.58 10.95 0.98* (0.971.00)

Inadequate social availability 4.72 1.81 4.02 1.28 1.34*** (1.211.48)

Depressive symptoms score 10.82 6.76 5.50 5.26 1.14*** (1.111.17)

OR odds ratio, CI confidence interval, SD standard deviation Significance level at p\ 0.10; * Significance level at p\ 0.05; ** Significance level at p\0.01; *** Significance level at p\0.001a

Nbefore imputation of missing values, b quartiles split, c reference category, d the reference category is No


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Table 2 Crude associations between study variables at time 1 and major depression at time 2 for men

Exposure variables Depressed T2

N= 31

Non-depressed T2

N= 1,981

Crude ORs

Categorical variables T1 and T2 Na % Na % OR (95 % CI)

Job demands T1b

Lowest (512 points)c 16 53.3 722 36.7 1

Low (13 points) 4 13.3 273 13.9 0.66 (0.222.00)

High (1415 points) 3 10.0 546 27.7 0.25* (0.070.86)

Highest (1620 points) 7 23.3 428 21.7 0.74 (0.301.81)

Inadequate skill discretion T1b

Lowest (46 points)c 14 45.2 819 41.6 1

Low (7 points) 6 19.4 372 18.9 0.94 (0.362.47)

High (89 points) 3 9.7 566 28.7 0.31 (0.091.08)

Highest (1016 points) 8 25.8 213 10.8 2.20 (0.915.31)

Inadequate decision authority T1b

Lowest (2 points)c 7 22.6 782 39.5 1

Low (3 points) 9 29.0 466 23.5 2.16 (0.805.83)

High (4 points) 5 16.1 407 20.6 1.37 (0.434.35)

Highest (58 points) 10 32.3 325 16.4 3.44* (1.309.11)

Inadequate job social climate T1b

Lowest (69 points)c 7 24.1 611 34.5 1

Low (1011 points) 5 17.2 429 24.2 1.02 (0.323.23)

High (1213 points) 6 20.7 470 26.6 1.11 (0.373.34)

Highest (1423 points) 11 37.9 260 14.7 3.69** (1.429.63)

Living without an adult T1d 13 41.9 450 22.8 2.45* (1.195.04)

Little help with house chores T1d 21 70.0 873 44.3 2.93** (1.346.44)

Small children at home T1d 9 29.0 343 17.4 1.94 (0.894.26)

Negative life events at T2

Nonec 1 3.3 753 38.0 1

One 6 20.0 575 29.1 7.86

(0.9465.45)Two 6 20.0 360 18.2 12.55* (1.51104.63)

Three or more 17 56.7 291 14.7 43.99*** (5.83332.05)

Education level T1

9 years or less 5 16.1 236 11.9 1.49 (0.534.22)

1011 years 13 41.9 827 41.8 1.11 (0.512.40)

12 years or morec 13 41.9 915 46.3 1

Yearly income level T1

149 K SEK or less 2 6.5 90 4.6 2.75 (0.6012.61)

150199 K SEK 5 16.1 142 7.2 4.36** (1.4912.73)

200299 K SEK 13 41.9 383 19.4 4.21*** (1.879.46)

300 K SEK or morec 11 35.5 1363 68.9 1

Occupational groups T1

Unskilled manual workers 3 10.0 197 10.2 2.17 (0.4310.86)

Skilled manual workers 5 16.7 203 10.5 3.51 (0.8314.85)

Lower non-manual workers 5 16.7 182 9.4 3.92 (0.93-16.57)

Middle non-manual workers 7 23.3 412 21.4 2.42 (0.629.44)

Higher non-manual workersc 3 10.0 428 22.2 1

Self-employed professionals 4 13.3 264 13.7 2.16 (0.489.73)

Entrepreneurs 3 10.0 243 12.6 1.76 (0.358.79)


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findings regarding job demands and skill discretion among

men are opposite to recent reviews, that is, high job

demands appeared as a protective factor for major

depression occurrence and skill discretion appeared as a

factor that increased the occurrence of major depression.

The fact that high job demands among men appeared as

a protective factor against major depression in the adjusted

models was not expected, although the finding was con-

sistent in analyses with and without imputation. We have

found one nested casecontrol study derived from the

Table 3 Adjusted multiple logistic regression models for major depression at T2 among women

Outcome: major

depression at T2

Model 0 Model 1 Model 2 Model 3 Model 4

Quartiles split of OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI)

Job Demands T1a

Lowest (512 points)b 1 1 1 1 1

Low (13 points) 1.41 (0.812.46) 1.36 (0.772.40) 1.23 (0.682.21) 1.21 (0.672.20) 1.23 (0.672.26)

High (1415 points) 1.33 (0.832.14) 1.21 (0.741.98) 1.01 (0.601.68) 0.99 (0.591.67) 0.94 (0.551.59)

Highest (1620 points) 1.69* (1.082.64) 1.33 (0.832.13) 1.19 (0.731.94) 1.31 (0.792.15) 1.07 (0.641.79)

Inadequate skill discretion T1a


Low (7 points) 1.29 (0.782.12) 1.29 (0.782.14) 1.28 (0.762.16) 1.18 (0.692.02) 1.13 (0.651.95)

High (89 points) 0.88 (0.551.42) 0.86 (0.531.42) 0.79 (0.471.32) 0.63 (0.371.08) 0.65 (0.371.13)

Highest (1016 points) 1.75* (1.092.83) 1.63 (0.962.77) 1.57 (0.912.74) 1.12 (0.612.05) 1.12 (0.602.10)

Inadequate decision authority T1a


Low (3 points) 0.65 (0.371.15) 0.57 (0.321.01) 0.58 (0.321.05) 0.61 (0.331.11) 0.63 (0.341.17)

High (4 points) 1.23 (0.771.95) 1.00 (0.621.62) 1.08 (0.651.78) 1.05 (0.621.76) 1.02 (0.601.76)

Highest (58 points) 1.25 (0.801.97) 0.79 (0.481.31) 0.82 (0.491.38) 0.75 (0.441.30) 0.74 (0.421.30)Inadequate job social climate T1a


Low (1011 points) 2.32** (1.334.05) 2.35** (1.344.14) 1.97* (1.103.52) 2.08* (1.153.75) 2.09* (1.153.81)

High (1213 points) 2.42*** (1.424.13) 2.41** (1.404.16) 1.92* (1.093.38) 2.08* (1.183.68) 1.85* (1.033.31)

Highest (1423 points) 4.19*** (2.477.11) 3.84*** (2.206.71) 2.55** (1.424.56) 2.78*** (1.535.06) 2.06* (1.103.83)

Model 0: Simple logistic regression, that is, unadjusted by each other JDCSM variable

Model 1: Adjusted for each other JDCSM variables (i.e. job demands, skill discretion, decision authority and job social climate) and age at T1

Model 2: Model 1 and additionally adjusting for living alone status, inadequate social availability (scale score), having little help with home

chores and having small children at home at T1, and negative life events at T2

Model 3: Model 2 and additionally adjusting for education level, income level and occupational groups at T1

Model 4: Model 3 and additionally adjusting for score of depressive symptoms (MDI) at T1

OR odds ratio, CI confidence interval Significance level at p\ 0.10; * Significance level at p\ 0.05; ** Significance level at p\0.01; *** Significance level at p\0.001a quartiles split, b reference category

Table 2 continued

Continuous variables T1 Mean SD Mean SD OR (95 % CI)

Age 40.65 8.60 43.18 11.00 0.98 (0.951.01)

Inadequate social availability 5.45 2.20 4.39 1.55 1.37*** (1.151.62)

Depressive symptoms score 12.03 5.43 4.18 4.45 1.23*** (1.171.29)

OR odds ratio, CI confidence interval, SD standard deviation Significance level at p\ 0.10; * Significance level at p\ 0.05; ** Significance level at p\0.01; *** Significance level at p\0.001a

Nbefore imputation of missing values, b quartiles split, c reference category, d the reference category is No


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Danish Work Environment Cohort Study (DWECS) that

showed a significant protective effect of high demands on

depressive disorders among men, but the authors did not

offer a plausible explanation for their findings (Wieclawet al.2008). Additionally, we found no association between

high job demands and major depression among women.

This is in accordance with several previous studies where

high psychological demands were not related to depression

among women (Clumeck et al.2009; Virtanen et al.2010;

Thielen et al.2011). We lack explanations for these find-

ings, and further investigation is warranted. Furthermore,

we stratified the mens analyses by three major occupa-

tional groups (blue-collar workers, white-collar workers

and other workers) in order to test the robustness of this

protective effect among different occupational groups.

Thus, the OR of high job demands remained significantlyprotective only in the blue-collar strata (data not shown);

however, the ORs for high job demands in the other two

strata were also below unity.

We found contradictory findings regarding job control

components (i.e. skill discretion and decision authority)

when the results of adjusted models were compared

between genders. Among women, inadequate skill discre-

tion appeared as a risk factor for the occurrence of major

depression, but only in the crude model. The opposite

occurred among men; inadequate skill discretion appeared

as a protective factor in adjusted models (3 and 4).

Moreover, the literature reports inconsistent findings rela-

ted to decision latitude or job control appearing as aprotective factor in some studies, as a risk factor in others

and without significant results in others, in samples of

either gender or samples of both genders included. In

systematic reviews, job control or its components showed

contradictory findings (Bonde 2008; Netterstrm et al.

2008). These reviews showed that decision latitude was

addressed only as a whole dimension in the cited studies,

that is, its components (skill discretion and decision

authority) were not individually scrutinised. Uniquely, two

recent longitudinal studies addressed decision authority as

a separate scale (Magnusson Hanson et al.2009; Joensuu

et al.2010) with contradictory findings between studies: inthe former, high decision authority appeared as a protective

factor against depression, and in the latter, it resulted as a

risk factor.

Additionally, only the Finnish Still Working Study

(Joensuu et al.2010) addressed skill discretion as a sepa-

rate scale, showing a protective effect on depression

occurrence. In contrast, the DWECS study showed non-

significant results for possibilities for development, a

scale conceptually related to skill discretion (Rugulies et al.

Table 4 Adjusted multiple logistic regression models for major depression at T2 among men

Outcome: major

depression at T2

Model 0 Model 1 Model 2 Model 3 Model 4

Median split of: OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI) OR (95 % CI)

Job demands T1a

Low (513 points)b 1 1 1 1 1

High (1420 points) 0.49

(0.231.04) 0.41* (0.190.88) 0.33** (0.140.73) 0.23** (0.090.57) 0.24** (0.100.60)Inadequate skill discretion T1a

Low (47 points)b 1 1 1 1 1

High (816 points) 0.84 (0.401.76) 0.58 (0.271.27) 0.50 (0.221.15) 0.30* (0.110.79) 0.32* (0.110.90)

Inadequate decision authority T1a

Low (23 points)b 1 1 1 1 1

High (48 points) 1.60 (0.793.25) 1.44 (0.683.08) 1.20 (0.532.72) 0.91 (0.372.27) 0.82 (0.322.07)

Inadequate job social climate T1a

Low (611 points)b 1 1 1 1 1

High (1223 points) 2.03 (0.994.16) 2.37* (1.125.02) 1.84 (0.814.18) 1.54 (0.633.78) 1.40 (0.563.48)

Model 0: Simple logistic regression, that is, unadjusted by each other JDCSM variable

Model 1: Adjusted for each other JDCSM variables (i.e. job demands, skill discretion, decision authority and job social climate) and age at T1

Model 2: Model 1 and additionally adjusting for living alone status, inadequate social availability (scale score), having little help with home

chores and having small children at home at T1, and negative life events at T2

Model 3: Model 2 and additionally adjusting for education level, income level and occupational groups at T1

Model 4: Model 3 and additionally adjusting for score of depressive symptoms (MDI) at T1

OR odds ratio, CI confidence interval Significance level at p\ 0.10; * Significance level at p\ 0.05; ** Significance level at p\0.01; *** Significance level at p\0.001a Median split, b reference category


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2006). Adding more empirical evidence to this contro-

versy, we found a protective effect of inadequate skill

discretion on the occurrence of major depression, but only

among men. Such findings have been obtained before

(Kawakami et al. 1995; Kondo et al. 2006). A possible

explanation for these peculiar results is that using skills has

become more of a demand when work intensity increases

(Joensuu et al.2010). Furthermore, we stratified the mensanalyses by three major occupational groups (blue-collar

workers, white-collar workers and other workers) in order

to test the robustness of this protective effect among dif-

ferent occupational groups. Thus, the OR of low skill

discretion remained significantly protective only in the

blue-collar strata (data not shown); however, the ORs for

low skill discretion in the other two strata were also below

unity. Additionally, our findings strongly suggest that skill

discretion and decision authority should be addressed

separately in future studies about the psychosocial work

environment.

Finally, inadequate social climate at work appeared as apredictor of major depression only among women, and it

remained significant over different adjusted models. Trend

analyses showed a significant linear trend over the quartiles

of inadequate social climate with the reference category

significantly lower than the upper three categories. Our

results confirm findings about inadequate social climate as

a risk factor for depressive disorders in other longitudinal

studies (Bonde2008; Sinokki et al.2009), but our gender-

specific findings were opposite to those reported in the

literature, where inadequate social support at work was a

stronger risk factor among men than among women

(Griffin et al.2002; Shields2006; Netterstrm et al.2008)

or only significant among men, when the outcome was use

of antidepressant medication (Thielen et al. 2011). The

limited number of men with major depression in our

sample (only 31 subjects) should have implied a low power

to detect significant relationships. Additionally, our mea-

sure of social climate did not cover instrumental social

support. It is possible that inadequate social climate could

have a stronger relation with major depression among

women than among men while inadequate instrumental

social support, which we have not measured, could be more

related to major depression among men.

Limitations of the study

First, our sample of working individuals was plausibly

comprised by individuals healthier in terms of their phys-

ical and mental health than those unemployed or not in the

labour market (i.e. the healthy worker effect), which is in

line with the patterns of participation in both waves of the

PART study (Lundberg et al.2005; Bergman et al.2010);

thus, the occurrence of major depression in our study was

lower compared to some other studies (for reviews, see

Stansfeld and Candy2006; Bonde2008; Netterstrm et al.

2008). Additionally, conclusions about the relationship

between JDCSM variables and major depression in this

study should be interpreted with caution because our

sample included only subjects who remained in the same

job over the two study waves. Subjects who were not

included in this sample may have changed jobs or havebecome unemployed due to work stress problems (Haahr

et al.2007) or depressive disorders (Lerner et al. 2004).

In contrast, persons who remained in the same job over

two waves could have done so because of interesting and

challenging work (Stansfeld et al.2008). To assess these

alternative explanations, we did supplementary analyses:

there were no differences in the prevalence of major

depression at T2 between people who had the same job in

both waves and people who left their T1 job (3.77 vs.

4.54 %, Fishers exact test p = 0.12). Also, we made

regression analyses using the sample of people who did not

have the same job at T2, but no significant results werefound for any JDCSM variable neither among women nor

among men (data not shown). Finally, we have tested

independently each item of the job demands scale (some

items could be related to interesting and challenging work)

among persons with the same job, but non-significant

results were found for such items in models adjusted by

JDCSM and other co-variables; thus, no single job demands

item was significantly related to the study outcome.

Second, in this study, the measurements of exposures

and outcome cannot be considered completely independent

because they were both obtained through self-reports

(Rugulies et al.2006; Bonde2008). This dependence could

spuriously have increased the odds ratios due to the

triviality trap or bias due to common method (Kris-

tensen1996; Kasl1998). Thus, we have tried to control the

common method bias in two ways: firstly, we removed

from the study sample individuals who met the criteria for

major depression, because individuals with major depres-

sion could have negatively assessed their work environ-

ment (de Lange et al.2005). Secondly, we have measured

the work exposures and the major depression outcome

3 years apart. Moreover, the level of baseline depressive

symptoms was adjusted for in the regression analyses.

However, of course there might be non-measured fac-

tors, such as personality and social desirability, which

could have affected our results via the common method

bias mechanism. Two papers exploring this issue showed

that the associations between depressive symptoms and

psychosocial work factors were not biased by personality

factors (Paterniti et al. 2002; Jurado et al. 2005). The

depressive symptoms are part of several personality dis-

orders; thus, controlling for the former would also partially

control for the latter.


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Finally, we have no incidence estimates given that our

population was examined twice over a 3-year lag. Thereby,

we could have lost incident cases appearing and disap-

pearing between the two data collection times. This fact

could reduce the study power, but it would hardly affect

our point prevalence estimates and the exposureoutcome

relationships.

Strengths of the study

In the literature, there are rather few longitudinal and

population-based studies about the influence of psychoso-

cial work environment factors on major depression. The

advantage of population studies is that they allow including

a broader range of psychosocial work factors in comparison

with occupational sample studies where the extent of

demandscontrolsupport arrangements is limited to the

organisation boundaries. But population studies imply

logistic limitations, which make it more difficult to prop-

erly assess the outcome (i.e. major depression) and theputative determinants (i.e. psychosocial work environment

variables).

Our study has several strengths compared to other pop-

ulation studies: first, the four psychosocial work dimensions

(demands, decision authority, skill discretion and social

climate) were assessed by specific state-of-the-art scales

originated from Karasek and Theorells work (Karasek

1979; Karasek and Theorell1990; Johnson and Hall1988;

Karasek et al. 1998) instead of using summary scales for

each or a composite index for all JDCSM factors (e.g. job

stress index or job strain quotient). Our approach also

allowed an individual assessment of each psychosocial

work environment dimension, yielding independent con-

clusions about demands, decision authority, skill discretion

and social climate at work. In the literature, only Joensuu

et al. study analysed the four Karasek JDCSM dimensions

individually, although it was a study about a specific pop-

ulation: private sector industrial employees (Joensuu et al.

2010). Our study sought to contribute to the understanding

of psychosocial work environment factors as determinants

of major depression in the general working population by

using the four JDCSM dimensions individually.

Second, we utilised a sample of subjects working in the

same job at both waves (T1 and T2); thus, it allowed

having an assessment of psychosocial work exposure

variables that should be more stable (over 3 years) and

more accurate compared to other follow-up studies, where

working conditions should have changed over the follow-

up (Stansfeld and Candy 2006; Bonde2008; Netterstrm

et al.2008).

Finally, usually previous studies applied a dichotomised

split approach for psychosocial work variables, which

could bring statistical modelling problems when the

behaviour of the phenomenon is complex (Theorell and

Karasek1996; Altman and Royston2006). Then, analyses

using more categories are warranted. Conversely, a con-

tinuous scale approach could be very useful for determin-

ing doseresponse effects, and indeed, this method has

been used in some studies (Plaisier et al. 2007; Virtanen

et al.2007; Magnusson Hanson et al.2009), but it implies

that a linear relationship exists between the predictors andthe outcome variable (MacCallum et al. 2002). Thereby,

split analysis using a number of ordered categories based

on scale threshold criteria (e.g. quartiles) seems a good

alternative in the middle of dichotomic and continuous

approaches. Hence, we utilised quartile cut-off points for

the JDCSM variables (i.e. the 25th, 50th and 75th sample

percentiles) in the analyses of the womens subsample.

Conclusions

The results showed that a good work social climate wasprotective against major depression among women. How-

ever, there were no clear effects of other JDCSM exposure

variables among women. Among men, high job demands

and low skill discretion appeared as protective factors

against major depression; both are novel and controversial

findings considering the recent literature reviews. Thus,

more studies are warranted to disentangle such relation-

ships. Finally, decision authority and skill discretion

seemed to have opposite effects on the occurrence of major

depression; therefore, they should be addressed separately

in future studies about the psychosocial work environment.

Acknowledgments The authors thank the PART project grant

providers: the Swedish Medical Research Council, the Swedish

Council for Working Life and Social Research and the Stockholm

County Council (Grant number VR K2007-61X-20381-01-3). The

PhD student support was provided by the COLFUTURO Foundation

(Colombia), the ERACOL academic exchange programme (Erasmus

Mundus External CooperationEurope) and Universidad del Valle

(Colombia). We also wish to thank Professor Tores Theorell for

valuable suggestions during the development of the study, Peeter

Fredlund and Michael Lundberg for statistical advice and the

Reviewers for suggestions for improving the manuscript.

Conflict of interest The authors declare that they have no conflict

of interest.

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C o p y r i g h t o f I n t e r n a t i o n a l A r c h i v e s o f O c c u p a t i o n a l & E n v i r o n m e n t a l H e a l t h i s t h e p r o p e r t y

o f S p r i n g e r S c i e n c e & B u s i n e s s M e d i a B . V . a n d i t s c o n t e n t m a y n o t b e c o p i e d o r e m a i l e d t o

m u l t i p l e s i t e s o r p o s t e d t o a l i s t s e r v w i t h o u t t h e c o p y r i g h t h o l d e r ' s e x p r e s s w r i t t e n p e r m i s s i o n .

H o w e v e r , u s e r s m a y p r i n t , d o w n l o a d , o r e m a i l a r t i c l e s f o r i n d i v i d u a l u s e .

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