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ORIGINAL ARTICLE
Is work engagement related to work ability beyond working
conditions and lifestyle factors?
Auli Airila •Jari Hakanen •Anne Punakallio •
Sirpa Lusa •Ritva Luukkonen
Received: 1 September 2011 / Accepted: 6 January 2012 / Published online: 21 January 2012
ÓSpringer-Verlag 2012
Abstract
Purpose To examine the associations of age, lifestyle and
work-related factors, and particularly work engagement
with the work ability index (WAI) and its sub-dimensions.
Methods Step-wise regression analysis with a sample of
Finnish firefighters (n=403) was used. The outcome
variables were the WAI and its six sub-dimensions. The
independent variables consisted of age, lifestyle variables
(alcohol consumption, BMI, smoking, physical exercise,
and sleep problems), working conditions (job demands,
physical workload, supervisory relations, and task resour-
ces), and work engagement. The outcome variables and all
the variables related to lifestyle, working conditions, and
work engagement were measured in 2009. Work ability at
baseline 10 years earlier was adjusted for in the models.
Results Work engagement, age, physical exercise, sleep
problems, and physical workload were associated with the
WAI. All independent variables, except BMI and alcohol
consumption, were associated with at least one sub-dimen-
sion of the WAI after controlling the baseline WAI. Lifestyle
variables, working conditions, and work engagement were
more strongly related to the subjective WAI sub-dimensions
than to the two more objective WAI sub-dimensions.
Conclusions Work engagement was significantly associ-
ated with work ability even after adjusting for various
factors, indicating its importance in promoting work
ability. Other key factors for good work ability were fre-
quent exercise, good sleep, non-smoking, low job demands,
low physical workload, and high task resources. More
specifically, this study suggests that in maintaining work
ability, it is valuable not only to promote lifestyle factors or
working conditions, but also to enhance employees’ posi-
tive state of work engagement.
Keywords Work ability Work engagement
Job demands Job resources Lifestyle factors
Firefighters
Introduction
Maintaining and improving the work ability of employees is
important for increasing productivity and preventing early
exit from work life. Particularly in high-demand jobs, such
as firefighting, good work ability is a precondition to cope
with demanding tasks in diverse work conditions (e.g.,
Beaton et al. 1998; Bos et al. 2004; Lusa et al. 2006). In fact,
previous studies have indicated that poor work ability is
related to reduced productivity at work (van den Berg et al.
2010), increased sickness absence (Ahlstrom et al. 2010;
Kujala et al. 2006), and early retirement (Feldt et al. 2009;
Liira et al. 2000). Individual characteristics and work-
related risk factors have been extensively examined as
antecedents of work ability (for a review, see van den Berg
et al. 2009). However, the motivational aspects of human
resources—such as work engagement—have not been
studied with the same intensity, despite the fact that they are
considered essential factors related to work ability (van den
Berg et al. 2009). Therefore, there is a need to identify not
only the possible causes of decreased work ability but also
the factors that may actually improve work ability.
A. Airila
Department of Social Research, University of Helsinki,
Helsinki, Finland
A. Airila (&)J. Hakanen A. Punakallio S. Lusa
R. Luukkonen
Finnish Institute of Occupational Health, Work Organizations,
Topeliuksenkatu 41 a A, 00250 Helsinki, Finland
e-mail: auli.airila@ttl.fi
123
Int Arch Occup Environ Health (2012) 85:915–925
DOI 10.1007/s00420-012-0732-1
Work ability and its antecedents
Work ability refers to workers’ ability to carry out their
work in relation to the demands of the work, and their
health and mental resources (Ilmarinen et al. 1997). As
such, impaired work ability is believed to result from an
imbalance between job demands and individual resources.
Therefore, work characteristics, such as working conditions
and job demands, are key determinants of work ability. In
addition, individual resources, namely health and func-
tional capacity; knowledge and skills; and values, attitudes
and motivation, are related to work ability (Tuomi et al.
2001). Empirically, for example, age, alcohol consumption,
obesity, work demands, and physical workload have found
to be associated with decreased work ability among rep-
resentative samples of working population (e.g., Ilmarinen
et al. 1997), in health care (e.g., Fischer et al. 2006;
Pohjonen 2001), and among municipal workers (e.g.,
Tuomi et al. 1991a,b). In addition, work-related injuries—
which are frequent among firefighters (Poplin et al.
2011)—have been found to be related to work ability (e.g.,
Lusa et al. 2011).
Work ability is often measured using the work ability
index (WAI) consisting of seven dimensions on the phys-
ical and mental demands of work, health, and individual
resources (Tuomi et al. 1998). Although several studies
using the WAI have been published, only few studies (e.g.,
Alavinia et al. 2009; Pohjonen 2001; van den Berg et al.
2010) have investigated the potential antecedents of the
different sub-dimensions of the WAI. Hence, it is not yet
clear to which sub-dimensions of work ability individual or
work-related factors relate to, or what the role of different
dimensions within the total score of the WAI is (see also
Feldt et al. 2009). However, knowledge on the relation-
ships between the sub-dimensions of the WAI and indi-
vidual and work characteristics are essential in order to
improve work ability and apply properly focused inter-
ventions in workplaces.
Work engagement
As noted, although positive feelings and motivation at
work influence work ability, this aspect has received sur-
prisingly little research attention. One such affective-
motivational concept is work engagement, which has
emerged as a positive psychological construct of occupa-
tional health to measure positive work-related state of mind
(Bakker et al. 2008). Work engagement is a positive, ful-
filling, affective-motivational state of work-related well-
being, characterized by vigor, dedication, and absorption
(Schaufeli et al. 2002). Vigor refers to high levels of energy
and mental resilience while working; dedication is char-
acterized by being strongly involved in one’s work and
experiencing a sense of significance and enthusiasm; and
absorption refers to being fully concentrated and happily
engrossed in one’s work.
The motivational power of work engagement has proved
to be important in work life both among blue- and white-
collar workers, such as home-care employees (Schaufeli
and Bakker 2004), hotel receptionists (Salanova et al.
2005), managers (Feldt et al. 2009), and teachers (Hakanen
et al. 2006). For example, the high energy of employees
and their concentration on work tasks have been linked to
job performance (Halbesleben 2010) and organizational
commitment (Hakanen et al. 2008). In addition, a three-
year cross-lagged panel study among Finnish dentists
(Hakanen et al. 2011) showed positive reciprocal effects
over time (so called gain spirals) between work engage-
ment and work–family enrichment, indicating that positive
affects at work may enhance positive appraisals of work
and enrich home life. Thus, for example, in fire and rescue
services, these positive outcomes of work engagement may
be valuable for both the individual firefighters and the
whole organization in the form of better health and
increased intention to stay on at work for longer. In fact,
some studies suggest a positive association between work
engagement and health (e.g., Hakanen and Lindbohm
2008; Parzefall and Hakanen 2010; Seppa
¨la
¨et al. in press).
In contrast, little is known about the relationship between
work engagement and work ability.
Research questions
The central aim of the present study among Finnish fire-
fighters was to examine whether work engagement, as a
motivational well-being concept, is associated with work
ability, after adjusting for age, lifestyle and work-related
factors, and the baseline work ability 10 years earlier.
Consequently, the research questions were as follows:
(i) Are age, lifestyle factors, and working conditions
associated with the WAI?; (ii) Does work engagement
relate to the WAI even after adjusting for age, lifestyle
factors, and working conditions?; and (iii) Are age, life-
style factors, working conditions, and particularly work
engagement associated with the different sub-dimensions
of the WAI?
Methods
Participants and procedure
The data consists of a questionnaire study among Finnish
firefighters conducted in 1999 (baseline WAI was measured)
and 2009 (other variables of the present study were
916 Int Arch Occup Environ Health (2012) 85:915–925
123
measured). The study focused on both the physical and
mental conditions of fire and rescue work, and the well-being
of professional firefighters. A 10-year interval between data
collections was based on practical decisions and financial
arrangements and could not be influenced by the researchers.
In 1999, 1,124 questionnaires were posted, and 72%
(n=794) returned the questionnaire. In the follow-up
10 years later, 68% (n=721) returned the questionnaire.
The research process is reported in detail elsewhere (Lusa
et al. 2006,2011). The study was approved by the Ethics
Committee of the HUS Hospital District and was performed
according to the Helsinki Declaration. Each subject gave
written informed consent before participation.
Work ability index
Work ability was measured twice (in 1999 and 2009) by
the WAI questionnaire (Tuomi et al. 1998) that is the most
widely used questionnaire, and a validated measure of
work ability (van den Berg et al. 2009). Furthermore, sat-
isfactory test–retest reliability of the index has been
observed (de Zwart et al. 2002). The index consists of
seven dimensions, namely: (1) the subjective estimation of
current work ability compared with lifetime best (0–10
points); (2) subjective work ability in relation to job
demands (2–10 points); (3) the number of current diseases
diagnosed by a physician (1–7 points); (4) the subjective
estimation of work impairment due to diseases (1-6 points);
(5) sick leave during the past year (1–5 points); (6) own
prognosis of work ability 2 years from now (1, 4 or 7
points); and (7) psychological resources (1–4 points). The
WAI index ranges from 7 to 49 points, and a higher score
indicates better work ability. In this study, we used the
continuous sum score of the WAI. In addition, the sub-
dimensions of the WAI were used as separate dependent
variables. Furthermore, in our study models, the impact of
baseline WAI and its sub-dimensions 10 years earlier in
1999 were controlled for.
Because of the large amount of missing data (n=199)
in estimated work impairment due to diseases (sub-
dimension 4), this item was excluded from the analyses.
The high number of drop-outs in this particular item is
explained, at least partly, by technical reasons: the question
was divided into two columns in the questionnaire and
situated after a question concerning different types of
cancer rather than directly after other diseases included in
the WAI questionnaire. Thus, the total WAI score was
calculated without sub-dimension 4. Therefore, the slightly
modified WAI index in the present study had a range from
6 to 43 points. However, the correlation between the total
WAI score and the modified index was extremely high:
0.99 both in 1999 and 2009. Cronbach’s alphas for the
modified WAI were 0.70 in 1999 and 0.78 in 2009.
Lifestyle variables
Alcohol consumption, body mass index (BMI), smoking,
physical exercise, and sleep problems were studied as
indicative of lifestyle. Alcohol consumption was measured
using a single-item question on the frequency of alcohol
consumption with an eight-point scale (1 =never,
8=daily or almost daily). BMI was calculated by dividing
body weight (kilograms) by the square of body height
(meters). Smoking habits were elicited using a dichoto-
mous (yes–no) question on current smoking. Physical
exercise was assessed through a single-item question on the
frequency of leisure-time exercise activity, using a three-
point scale (1 =not at all, 2 =occasionally, 3 =fre-
quently). Finally, a four-item scale of sleep problems was
derived from the Basic Nordic Sleep Questionnaire
(Partinen and Gislason 1995): difficulties in falling asleep
during the past 3 months; sleeping well during the past
3 months; awaking too early in the morning and not being
able to fall back asleep during the past 3 months; and
extreme tiredness during daytime. All the items were rated
on a five-point scale (1 =not at all, 5 =daily/almost
daily) except sleeping well, which was measured with a
three-point scale (1 =well, 3 =moderately, 5 =poorly).
Cronbach’s alpha was 0.79.
Working conditions
We measured working conditions with four scales: physical
workload, job demands, supervisory relations, and task
resources. Physical workload was measured using four
items adapted from Viikari-Juntura et al. (1996). Physical
workload was covered by questions on the frequency of
working in four difficult work postures: (i) working on
one’s knees, crouched, or crawling; (ii) postures in which
the back is bent; (iii) postures in which the back is twisted;
and (iv) working with hand or hands over neck–shoulder
level. All items were rated on a four-point scale (for
example, 1 =not at all, 4 =over an hour during the shift).
Cronbach’s alpha was 0.79. Job demands (e.g., Tuomi et al.
1991b) consisted of three items: excessive demands of the
job; responsibility of the job; and fear of failure and mis-
takes at work. Items were rated on a five-point scale
(0 =not at all, 4 =very much). Cronbach’s alpha was
0.75. Supervisory relations and task resources were adapted
from the Occupational Stress Questionnaire (Elo et al.
1992). Supervisory relations were elicited using five items
covering supervisory support, supervisory control, and
relationships between employees and supervisors. Task
resources included three items: decision making on issues
concerning one’s tasks; being able to use one’s knowledge
and skills at work; and feedback on success in work tasks.
Both supervisory relations and task resources were rated on
Int Arch Occup Environ Health (2012) 85:915–925 917
123
a five-point scale (1 =not at all/practically never,
5=very much). Cronbach’s alphas were 0.84 for super-
visory relations and 0.72 for task resources.
Work engagement
Work engagement was measured by using the Finnish
translation of the short version of the Utrecht Work
Engagement Scale, the UWES-9 (Hakanen 2009; Schaufeli
et al. 2006) that is the most widely used and validated mea-
sure for work engagement (Bakker et al. 2008), consisting of
nine items. The instrument has three sub-scales: vigor (e.g.,
‘‘At my work, I feel bursting with energy’’), dedication (e.g.,
‘‘My job inspires me’’), and absorption (e.g., ‘‘I am immersed
in my work’’). Each of the sub-dimensions was assessed
using three items. The items were rated on a seven-point
frequency-based scale (0 =never, 6 =daily). The scale
was highly reliable (Cronbach’s alpha =0.95).
All the variables related to lifestyle, working conditions,
and work engagement were measured in 2009.
Data analysis
We used exploratory factor analysis (EFA) to examine
whether the different scales of working conditions could be
distinguished from each other. The EFA results supported
the distinctiveness of the four working condition scales,
namely job demands, physical workload, supervisory rela-
tions, and task resources. In this study, we used linear
regression analysis to examine whether lifestyle and work-
related factors and work engagement were related to the
WAI or its six sub-dimensions after the baseline WAI and the
sub-dimensions of the WAI 10 years earlier were controlled
for. Thus, we had totally 7 different models to analyze.
Variables were entered into the models in four steps. First,
the continuous variable WAI or the sub-dimension of the
WAI at baseline and age was added to the model. In the
second step, lifestyle variables were added and in the third
step, working conditions. Finally, in the fourth step, work
engagement was added to the model. A pvalue of\0.05 was
considered to be statistically significant. We checked for
multicollinearity and found no collinearity problems in our
data (see Myers 1990). All analyses were conducted using
PASW Statistics 18 for Windows.
Results
Characteristics of the study population
The study population consists of male firefighters who
had responded to the questionnaires in both in 1999 and
2009 and were still employed in 2009 (n=403). A total
of 148 of the respondents from 1999 did not answer in
2009. The drop-outs were older (mean value 39.9 vs.
38.5), had lower education (primary school education
28.6% vs. 18.4%), smoked more often (41% vs. 26%),
and had lower WAI (mean value 33.2 vs. 35.2), and their
medical condition was slightly weaker (mean value 3.9
vs. 4.0) than those who responded at both times, indi-
cating slightly better lifestyle and work ability among the
sample of this study. However, when we took account the
age difference by applying statistical models, there was
no difference between groups.
In 2009, the average age of the study population was
48.5 (range 35–62, SD =5.4). Of the participants, 80.9%
(n=321) had a primary or elementary school education
and 19.1% (n=76) a secondary school education. A large
majority (87.7%, n=315) had a firefighter qualification,
29.4% (n=105) had a sub-officer qualification, and 9.8%
(n=35) a fire chief qualification. Mean work experience
in fire and rescue services was 25.3 years (range 3–39,
SD =5.8). A large majority (84.3%, n=337) of the
participants did shift work.
Descriptive results
The means, standard deviations, and the Pearson correla-
tions of the study variables are presented in Table 1. All
variables, except alcohol consumption, were significantly
correlated with the total WAI score. More importantly,
work engagement was significantly related to the total WAI
score and all its sub-dimensions except number of diseases
(sub-dimension 3).
Antecedents of the total work ability index
Table 2shows the results of the stepwise regression
analyses related to total WAI. Age was negatively related
to WAI. The lifestyle variables included in step 2 sig-
nificantly improved the regression model. More specifi-
cally, sleep problems were negatively and physical
exercise positively related to work ability. In contrast,
alcohol consumption, BMI, and smoking were not related
to the total WAI score. Adding working conditions (step
3) to the model further significantly improved the
regression model. However, only physical workload was
significantly related to the WAI. Finally, after adjusting
for the WAI 10 years earlier, age, lifestyle variables, and
working conditions, work engagement was added to the
model (step 4). The results showed a positive relationship
between work engagement and work ability. The final
model explained 53% of the variance of the WAI. The
total variance of the model was 31.22 and the residual
variance 15.48.
918 Int Arch Occup Environ Health (2012) 85:915–925
123
Table 1 Range, means, standard deviations, and the Pearson correlations between the study variables (n=403)
Variables Range M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Independent variables 2009
1. Age 35–62 48.54 5.43 1.00
2. Alcohol consumption 1–8 5.75 1.71 .01 1.00
3. BMI 20.4–36.6 26.71 2.85 .11* .02 1.00
4. Smoking 0–1 0.22 0.41 -.02 .06 .02 1.00
5. Physical exercise 1–3 2.77 0.45 -.07 .03 -.20** -.07 1.00
6. Sleep problems 4–19 8.98 3.25 .07 .19** .04 -.04 -.05 1.00
7. Job demands 0–4 0.79 0.78 .07 .06 -.00 -.03 .08 .31** 1.00
8. Physical work load 1–3.75 1.87 0.56 .01 -.08 .02 -.05 .09 .13** .02 1.00
9. Supervisory relations 1–5 3.89 0.82 -.03 .00 -.08 .06 .07 -.15** -.32** .07 1.00
10. Task resources 1–5 3.29 0.69 .06 -.07 -.03 .03 -.07 -.25** -.24** -.08 .44** 1.00
11. Work engagement 0–6 3.73 1.42 .02 -.07 -.04 -.08 -.03 -.25** -.33** -.07 .38** .62** 1.00
Dependent variables 2009
12. WAI 11–42 30.48 5.57 -.33** -.07 -.15** -.10* .15** -.37** -.30** -.11* .19** .29** .41** 1.00
13. Current work ability 0–10 7.13 1.71 -.28** -.05 -.19** -.08 .21** -.29** -.26** -.07 .15** .18** .31** .84** 1.00
14. Work ability in
relation to job demands
3–10 7.55 1.35 -.21** -.10* -.07 -.08 .18** -.44** -.39** -.05 .16** .28** .42** .79** .72** 1.00
15. Number of diseases 1–7 3.42 1.70 .17** .01 .16** .07 -.11* .19** .08 .19** -.08 -.11* -.10 -.57** -.28** -.21** 1.00
16. Sick leave 1–5 2.34 1.11 .04 -.01 .07 .08 -.11* .19** .06 .16** -.07 -.16** -.16** -.53** -.35** -.30** .32** 1.00
17. Own prognosis of
work ability
1, 4, 7 6.09 1.56 -.42** -.05 -.10* -.04 .05 -.19** -.17** -.13** .09* .21** .23** .69** .54** .46** -.18** -.22** 1.00
18. Psychological
resources
1–4 3.12 0.72 -.04 -.08 -.06 -.09* .04 -.37** -.38** .01 .24** .29** .49** .52** .43** .51** .08 -.10* .28**
Number of diseases and sick leave are presented as reversed indicators of work ability, thus, higher value indicate more diseases, and higher frequency of sick leave
MMean, SD Standard deviation
** p\.01. * p\.05
Int Arch Occup Environ Health (2012) 85:915–925 919
123
Antecedents of the sub-dimensions
of the work ability index
As can be seen from Table 3, age was negatively related to
the two WAI sub-dimensions, namely current work ability
and own prognosis of work ability (sub-dimensions 1 and 6).
Of lifestyle variables, sleep problems and physical exercise
in particular were associated with the sub-dimensions of the
WAI: frequent sleep problems were negatively related to
current work ability, work ability in relations to job
demands, and psychological resources (sub-dimensions 1, 2,
and 7). In turn, frequent physical exercise was positively
associated with current work ability and work ability in
relation to job demands, and negatively with sick leaves
(sub-dimensions 1, 2, and 5). Smoking was negatively
related to work ability in relations to job demands (sub-
dimension 2). Finally, alcohol consumption and BMI were
not related to any of the measured WAI sub-dimensions.
Working conditions were associated with five sub-
dimensions of the WAI. More specifically, high job
demands were negatively related to work ability in relation
to job demands and psychological resources (sub-dimen-
sions 2 and 7). High physical workload in turn was posi-
tively associated with a higher frequency of diseases and
sick leaves (sub-dimension 3 and 5). In addition, task
resources were positively related to own prognosis of work
ability (sub-dimension 6), whereas supervisory relations
were not related to any of the sub-dimensions of the WAI.
Finally, in the fourth step, work engagement was added
to each model. As Table 3shows, work engagement was
positively related to three sub-dimensions of the WAI:
good current work ability (sub-dimension 1), good work
ability in relation to job demands (sub-dimension 2), and a
higher level of psychological resources (sub-dimension 7).
In contrast, work engagement was not related to the
number of diseases (sub-dimension 3), sick leaves (sub-
dimension 5), or own prognosis of work ability (sub-
dimension 6).
Of the different sub-dimensions, the highest explained
variances of the study models concerned work ability in
relation to job demands (48%) and psychological resources
(45%). In contrast, the lowest explained variances con-
cerned sick leave (20%) and number of diseases (24%).
Discussion
This study contributes to the work ability literature by
addressing two research needs raised in the field: we
focused on the thus far neglected role of motivation—here
work engagement—as an antecedent of the WAI (van den
Berg et al. 2009), and we investigated the antecedents of
different sub-dimensions of the WAI (Feldt et al. 2009). In
particular, we investigated whether work engagement, as a
motivational concept, is related to the work ability of
Finnish firefighters after controlling for age, lifestyle
variables, and working conditions, and work ability
10 years earlier. Our main results showed a positive rela-
tionship between work engagement and work ability after
adjusting for various factors that prior research (e.g., van
den Berg et al. 2009) has identified as significant predictors
of the WAI. In addition, in this study, the different sub-
dimensions of the WAI had partly different antecedents.
Work engagement and work ability
Despite the growing evidence on the positive consequences
of work engagement for organizational outcomes (e.g.,
Hakanen et al. 2008; Salanova et al. 2005), there is still
scarce research on the health- and work ability-enhancing
potential of work engagement. Our results indicated that
the positive state of work engagement consisting of vigor,
dedication, and absorption was significantly associated
with work ability. In fact, work engagement was related
both to the total score of the WAI and to its three sub-
dimensions even after adjusting for various individual and
organizational characteristics. More specifically, our study
showed that a motivated and energetic worker, who
Table 2 Associations of age, life-style variables, working conditions,
and work engagement with work ability index (WAI) in 2009
(n=403)
Explanatory
variables
Work ability index
b 95% CI DR
2
R
2
Step 1 .39*** .39
WAI 1999 .53 0.36 to 0.70
Age -.14 -0.26 to -0.03
Step 2: Lifestyle variables .09*** .48
Alcohol consumption -.01 -0.38 to 0.35
BMI -.16 -0.38 to 0.06
Smoking -1.38 -2.79 to 0.04
Physical exercise 1.74 0.43 to 3.04
Sleep problems -.28 -0.46 to -0.10
Step 3: Working conditions .04** .52
Job demands -.73 -1.51 to 0.06
Physical workload -1.32 -2.40 to -0.23
Supervisory relations -.01 -0.80 to 0.78
Task resources .32 -0.81 to 1.44
Step 4: Work engagement .01* .53
Work engagement .61 0.09 to 1.13
bunstandardized beta-coefficient from the final step; CI confidence
interval; DR
2
change in explanation rate; R
2
explanation rate
*p\.05. ** p\.01. *** p\.001
920 Int Arch Occup Environ Health (2012) 85:915–925
123
Table 3 Associations of lifestyle variables, working conditions and work engagement with different WAI sub-dimensions (n=403)
Explanatory variables Work ability sub-dimensions
Current work ability Work ability in
relation to job demands
Number of diseases Sick leave Own prognosis
of work ability
Psychological
resources
b 95% CI b 95% CI b 95% CI b 95% CI b 95% CI b 95% CI
Step 1
WAI dimension 1999 0.30 0.12 to 0.48 0.31 0.18 to 0.43 0.48 0.30 to 0.67 0.26 0.12 to 0.40 0.45 0.12 to 0.79 0.21 0.10 to 0.33
Age -0.04 -0.08 to -0.01 -0.02 -0.04 to 0.01 0.02 -0.03 to 0.06 -0.01 -0.03 to 0.02 -0.11 -0.14 to -0.07 0.00 -0.01 to 0.02
Step 2: Lifestyle variables
Alcohol consumption -0.07 -0.18 to 0.05 0.01 -0.07 to 0.09 -0.05 -0.20 to 0.11 -0.03 -0.11 to 0.05 -0.06 -0.16 to 0.05 -0.04 -0.08 to 0.01
BMI -0.05 -0.12 to 0.02 -0.02 -0.07 to 0.03 0.08 -0.01 to 0.16 -0.01 -0.06 to 0.04 -0.06 -0.13 to 0.00 -0.01 -0.04 to 0.02
Smoking -0.36 -0.82 to 0.09 -0.32 -0.64 to -0.01 0.54 -0.04 to 1.12 0.26 -0.07 to 0.59 -0.31 -0.74 to 0.11 -0.10 -0.29 to 0.08
Physical exercise 0.58 0.14 to 1.03 0.40 0.10 to 0.71 -0.49 -1.03 to 0.06 -0.51 -0.82 to -0.19 0.07 -0.33 to 0.48 0.11 -0.07 to 0.28
Sleep problems -0.07 -0.13 to -0.02 -0.10 -0.15 to -0.06 0.07 -0.01 to 0.14 0.03 -0.01 to 0.07 -0.04 -0.09 to 0.02 -0.05 -0.07 to -0.02
Step 3: Working conditions
Job demands -0.25 -0.52 to 0.02 -0.24 -0.43 to -0.05 0.05 -0.28 to 0.38 0.08 -0.12 to 0.27 -0.08 -0.33 to 0.17 -0.15 -0.26 to -0.04
Physical workload -0.33 -0.67 to 0.02 0.01 -0.24 to 0.25 0.53 0.09 to 0.97 0.34 0.09 to 0.60 -0.17 -0.49 to 0.15 -0.02 -0.16 to 0.12
Supervisory relations -0.01 -0.26 to 0.25 -0.10 -0.28 to 0.08 -0.12 -0.44 to 0.21 -0.05 -0.23 to 0.14 -0.15 -0.38 to 0.09 0.06 -0.04 to 0.17
Task resources -0.06 -0.42 to 0.31 0.04 -0.21 to 0.30 0.18 -0.29 to 0.64 -0.05 -0.31 to 0.21 0.34 0.01 to 0.68 -0.06 -0.20 to 0.09
Step 4: Work engagement
Work engagement 0.25 0.08 to 0.41 0.25 0.14 to 0.37 0.00 -0.21 to 0.22 -0.04 -0.16 to 0.09 0.08 -0.08 to 0.23 0.18 0.12 to 0.25
bunstandardized beta-coefficient from the final step; CI confidence interval
Int Arch Occup Environ Health (2012) 85:915–925 921
123
strongly identifies with his/her work, has better work
ability than his/her less engaged co-worker. This finding is
in line with a study of Finnish teachers (Hakanen et al.
2006) in which work engagement was positively related to
one-item self-rated work ability. The idea of the dark side
of engagement, which suggests that being highly engaged
can also have detrimental consequences for the individual
(Bakker et al. 2011), was not supported in our study.
We also showed that work engagement was related to
the sub-dimensions of the WAI that can be characterized as
subjective estimations of one’s work ability, namely cur-
rent work ability, work ability in relation to job demands,
and psychological resources. On the contrary, no signifi-
cant association was found between work engagement and
the more health-related dimensions of the WAI, such as
number of diseases and sick leave. Obviously, work
engagement may not be related to diseases diagnosed by a
physician. As regards sick leaves, one study found that
among Dutch managers, work engagement predicted
absence frequency but not absence duration (Schaufeli
et al. 2009). The WAI instrument does not differentiate
between frequency and duration of sick leaves, but simply
measures the number of absence days. This may explain
why in our study we did not find an association between
work engagement and sick leaves.
Age, lifestyle factors, and work ability
This study supported age-related diversity in work ability,
as older age was negatively related to work ability. In a
similar vein, older age has been associated with poorer
WAI in several follow-up studies (e.g., Ilmarinen et al.
1997; Tuomi et al. 2004). More importantly, prior studies
among firefighters (Punakallio et al. 2004) have reported
that the WAI decreases with age. However, contrary to
expectations and earlier findings (e.g., Pohjonen 2001), in
our study, age was not associated with work ability in
relation to job demands (WAI sub-dimension 2). Age was
negatively associated only with the sub-dimensions of
current work ability, and own prognosis of work ability.
The non-significant results suggest that older age does not
necessarily decrease the mental resources of firefighters.
Similarly, Lusa et al. (2006) found that age was not
strongly associated with perceived mental strain among
firefighters.
Of lifestyle factors, sleep problems and lack of exercise
in leisure time were strongly, and smoking to a lesser
extent, associated with the WAI. Sleep problems and
smoking indicated poorer, whereas physical exercise was
related to better WAI. These results are in line with several
previous studies that have examined the relationship
between lifestyle factors and work ability (e.g., Camerino
et al. 2008; Fischer et al. 2006; Lusa et al. 2002; Tuomi
et al. 2004). However, in contrast to earlier findings (e.g.,
Fischer et al. 2006; Kaleta et al. 2006), neither alcohol
consumption nor BMI was related to the WAI. The null
association between alcohol consumption and the WAI
may be, at least partly, explained by the healthy worker
effect, that is, heavy drinkers with low work ability may
have dropped out of the sample. As regards BMI, one
explanation for the non-significant association may be the
presence of other lifestyle risk factors in the multivariable
models, which diminish the association with BMI.
Working conditions and work ability
Our results indicated that working conditions, particularly
physical workload and job demands, and to a lesser extent
also task resources, were related to work ability. Specifi-
cally, difficult work postures negatively associated with
work ability among the firefighters. This result is in line
with prior findings that have indicated a positive relation-
ship between high physical workload and decreased work
ability (Ilmarinen et al. 1997; Pohjonen 2001; Tuomi et al.
1991a,b). In addition, our finding on the association
between job demands and the WAI is consistent with
several previous studies (e.g., Tuomi et al. 1997,2001).
Furthermore, our result on the positive association between
task resources and the WAI has also been previously
reported (Tuomi et al. 2004). However, it should be noted
that in our study, task resources only related to one sub-
dimension (own prognosis of work ability) of the WAI.
In the current study, supervisory relations were not
related to work ability. Previous studies have found mixed
evidence on the role of supervisory support in work ability
and health (e.g., Boxer and Wild 1993; Sugimura and
The
´riault 2010; Tuomi et al. 1997). In fact, the importance
of supervisors in the work of firefighters may be different
compared with other occupations. The working community
of firefighters is compact and coherent, and the relation-
ships between co-workers are important and highly valued
(Pillai and Williams 2004). In addition, working in 24-hour
shifts strengthens the relationship between co-workers who
mainly operate in closely coordinated teams, which may, in
turn, lessen the importance of the supervisor.
Sub-dimensions of work ability
In this study, in addition to examining the total WAI score,
we also focused on its sub-dimensions, in order to identify
the antecedents of each sub-dimension of the WAI. This
knowledge may be helpful in focusing and planning
workplace interventions aimed at better work ability
among employees. Our results showed that lifestyle factors,
working conditions, and work engagement were more
strongly related to the more subjective dimensions of work
922 Int Arch Occup Environ Health (2012) 85:915–925
123
ability (sub-dimensions 1, 2, 6, and 7) than to the two more
objective dimensions, namely number of diseases (sub-
dimension 3) and sick leave (sub-dimension 5). Similarly,
in their study on construction workers, Alavinia et al.
(2009) found that work-related risk factors were more
strongly associated with the work ability sub-dimensions
(1 and 2) than with the health-related sub-dimensions (3, 4,
and 5). In fact, recently, it has been suggested that the one-
factor model of work ability should be dismissed (Martus
et al. 2010) and replaced by a two-dimensional instrument
covering subjectively estimated work ability and objective
health status. Future studies should further investigate the
dimensionality of the WAI and the importance of the dif-
ferent sub-dimensions within the total score. Practically,
our results suggest that by improving lifestyle and the
work-related factors included in this study, it may be
possible to improve at least the more subjective estimates
of the WAI.
Limitations and future research
Our study has some limitations that should be acknowl-
edged. First, the study was based on self-report measures,
which may cause systematic measurement errors (common
methods variance). However, we controlled for baseline
work ability in our study, which assumingly diminished the
risk of common method bias (Doty and Glick 1998).
Nevertheless, including more objective measures of life-
style and work-related factors in future studies on work
ability would strengthen the study design. Second, like
lifestyle and other work-related variables, work engage-
ment was only measured once, and therefore, our analysis
was cross-sectional and therefore no causality between
work ability and engagement can be determined. However,
the study design allowed us to adjust work ability at the
baseline (1999), and even after this, the relationships
between independent variables and outcome variables were
significant. We suggest that in the future, the effect of work
engagement on work ability should be studied using a
longitudinal full-panel design. Third, the present study
focused on one profession only, firefighters, which may
potentially threaten the generalizability of our findings.
Nevertheless, although some caution is needed, we believe
that the results can also be extended to other occupational
sectors, because similar evidence of the positive impact of
work engagement exists in various occupation sectors and
countries (e.g., Hakanen et al. 2006; Salanova and Schau-
feli 2008). In addition, as the positive effect of work
engagement on several dimensions of the WAI was robust
even in a highly physically demanding job as firefighting,
we assume that the same effect is also plausible in other
occupational sectors. Moreover, there was not a consider-
able ‘‘healthy worker’’ effect in our sample as the mean for
the current work ability (range, 0–10) among the partici-
pants (7.1) was lower than among Finnish male employees
in general (8.4; Perkio
¨-Ma
¨kela
¨et al. 2010). However, it
would be interesting to conduct a similar study using a
heterogeneous sample of employees that would also enable
to examine the role of socio-economic status in WAI.
Conclusions
The findings of the current study contribute to the existing
research on work ability by adding a motivational, work-
related well-being concept of work engagement as a
potentially important antecedent of work ability and its
sub-dimensions. This study showed that work engagement
may play an important role in promoting work ability. In
addition to work engagement, other key factors in the good
work ability of firefighters were good sleep, frequent
exercise, not too high physical workload and job demands,
and good task resources. Thus, not only promoting lifestyle
factors or working conditions but also fostering a positive
and motivational state of work engagement (e.g., via
increasing job autonomy and feedback) is likely to be
valuable in maintaining work ability, and in turn, dimin-
ishing the risk of work disability and early exit from work.
Acknowledgments This study was supported by grants from the
Fire Protection Fund, Finland, and the Emergency Services College,
Kuopio, Finland.
Conflict of interest The authors declare that they have no conflict
of interest.
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