Document 6521055

Copyright c Munksgaard 2001
Indoor Air 2001; 11: 217–222
http://journals.munksgaard.dk/indoorair
Printed in Denmark. All rights reserved
INDOOR AIR
ISSN 0905-6947
Why do Women Suffer from Sick Building Syndrome
more often than Men? – Subjective Higher Sensitivity
versus Objective Causes
S. BRASCHE1*, M. BULLINGER2, M. MORFELD2, H. J. GEBHARDT3 AND W. BISCHOF1
Received for review 31 January 2000. Accepted for publication 10 October 2000.
Abstract Office workers often report so-called sick building syndrome (SBS) symptoms affecting the skin, mucous membranes
and nervous system. The recurring higher prevalence of SBS in
women was investigated using questionnaire and ergonomic data
from the German ProKlimA-Project. The hypothesis that working
conditions and job characteristics for women are inferior to those
of men was tested for groups of risk factors. Finally, gender-specific multiple logistic regression models were compared. It was
found that 44.3% of women (nΩ888) and 26.2% of men (nΩ576)
suffer SBS with significant differences between men and women
for many variables. Considering sub-groups – supposing the
same circumstances in psycho-social and work-related conditions – gender-specific SBS prevalence rates differ as for the
whole sample, e.g. 35.9% of women with the most favourable job
characteristic suffer SBS (men: 19.4%), 53.0% of women with the
most unfavourable job characteristic suffer SBS (men: 33.3%).
These results show that women suffer more SBS than men independent of personal, most work-related and building factors.
Multiple logistic models define self-reported acute illness, job satisfaction, software quality and job characteristics as significant
gender-independent risk factors. Number of persons/room, selfreported allergy and smoking are characteristic female risk factors. Age is a significant risk factor only in men.
Key words Sick building syndrome; Prevalence rate; Gender;
Working conditions.
Practical Implications
The paper is focused on the exploration of the well-known
gender difference in complaints suffered in office buildings.
The hypothesis that different working conditions, job characteristics and demographic factors cause the higher level of
complaints by women cannot be confirmed. Women seem to
be more sensitive not only regarding the indoor environment
but also concerning work-related and psycho-social factors.
Therefore both the design of women’s work places and the
assessment of complaints should take into consideration this
globally higher sensitivity.
C Indoor Air (2001)
Introduction
Employees, especially in air-conditioned office buildings, often report a complex list of complaints relating
to skin, mucous membranes and the nervous system –
the so called sick building syndrome (SBS) (Levy &
Maroni, 1992). The syndrome itself has been identified
in type and extent in several studies, the aetiology of
the syndrome is still under discussion (Stenberg, 1994).
As a step towards a hypothesis relating to the aetiology, a variety of impact factors ranging from building-related factors over air quality factors to psychosocial and work-related factors have been explored. Female gender was found to be one of the powerful impact factors in many SBS studies (Skov et al., 1989;
Stenberg et al., 1990; Sundell, 1996; Jaakkola et al.,
1991).
That women are more likely to report impairments
is a long-standing epidemiological finding especially
in psychological research (Rodin & Ickovics, 1990). Differences were found between men and women in education level, working conditions, job characteristics
and other psycho-social factors influencing SBS-prevalence in a positive or negative way (Stenberg & Wall,
1995; Bullinger et al., 1999). Are these differences really
the cause of the gender difference in SBS? The simultaneously measured data of the German interdisciplinary ProKlimA-Project (Bischof et al., 1999) make it
possible to investigate this interesting problem and to
compare subjective as well as objective risk factors on
SBS in men and women.
1
Friedrich-Schiller-University Jena, Institute of Occupational, Social and Environmental Medicine, Department of Indoor Climatology Erfurt, GustavFreytag-Str. 1, D-99096 Erfurt, Germany, 2Department for Medical Psychology, University of Hamburg, Hamburg, Germany, 3Institute ASER e.V., Wuppertal, Germany, *Author to whom correspondence should be addressed.
Brasche, Bullinger, Morfeld, Gebhardt and Bischof
Table 1 Gender-related differences in SBS and in personal, work
place-related and job-related variables
Women
n
%
Men
n
p
%
SBS
yes
no
393 44.3
495 55.7
151 26.2
426 73.8 0.001
age
⬍31 years
31–40 years
41–50 years
⬎50 years
316
285
189
96
95
177
185
120
school
education
⬍10 years
166 18.9
10 year graduation 418 47.6
university entrance 295 33.6
qualification
73 12.7
192 33.5
309 53.8 0.001
professional
education
no
skilled labour
technical school/
master
university degree
27 3.2
520 60.9
134 15.7
21 3.7
201 35.6
100 17.7
173 20.3
243 43.0 0.001
acute
illness
yes
no
127 14.8
728 85.2
94 17.1
457 82.9 0.267
self reported
allergy
yes
no
340 38.3
548 61.7
164 28.4
414 71.6 0.001
physical
complaints
(Zerssen)
without
borderline
pathologic
691 80.0
87 10.1
86 9.9
498 87.5
42 7.4
29 5.1 0.001
external
locus of
control
low
middle
high
414 48.0
388 45.0
60 7.0
263 46.1
278 48.7
30 5.3 0.238
smoking
cigarettes
yes
no
238 27.0
645 73.0
132 23.0
442 77.0 0.090
job
satisfaction
satisfied
unsatisfied
631 71.1
257 28.9
412 71.3
166 28.7 0.927
airconditioned
yes
no
502 56.5
386 43.5
350 60.5
228 39.5 0.127
windows can yes
be opened
no
627 72.2
241 27.8
406 71.9
159 28.1 0.877
enough
natural light
659 75.1
219 24.9
496 86.4
78 13.6 0.001
working with no
computer
⬍4 h
⬎4 h
237 28.4
230 27.6
367 44.0
165 31.3
119 22.6
243 46.1 0.112
software
quality
no computer
good software
poor software
237 26.7
560 63.1
91 10.3
165 28.6
360 62.3
53 9.2 0.641
number of
persons
per room
1
2–4
5–6
7–10
⬎10
63
346
187
152
122
42
167
140
144
73
yes
no
35.7
32.2
21.3
10.8
7.2
39.8
21.5
17.5
14.0
16.5
30.7
32.1
20.8 0.001
7.4
29.5
24.7
25.4
12.9 0.001
equipment of good
work place
middle
poor
415 47.7
372 42.8
83 9.5
268 47.4
269 47.5
29 5.1 0.006
job
1 (very good)
characteristics 2
3
4 (not so good)
142
360
160
181
206 38.2
253 46.9
47 8.7
33 6.1 0.001
16.8
42.7
19.0
21.5
Methods
Between 1995 and 1998, 14 German office buildings were
surveyed. The measuring and questioning procedure in
218
selected rooms of the buildings (phase 2) involving 888
women and 576 men comprised:
– a self-administered questionnaire including among
others the sensory perception module which consists of
9 to 11 items pertaining to 6 different sub-scales, questions relating to job satisfaction, allergies, acute illness
and to psycho-social and demographic factors (Bullinger et al., 1993)
– ergonomic investigation of job characteristics and conditions and the ergonomic design of the work place
(Gebhardt et al., 1999)
– evaluation of building-related and room-related factors
and of the air-conditioning-systems
– measurement of physical, biological and chemical variables in rooms (not included in this analysis)
– medical examinations (not included in this analysis).
All these investigations took place in a 5-day period in
each building.
Following the hypothesis that working conditions
and job characteristics of women in office buildings are
worse and more unfavourable than those of men, important personal risk factors, variables of the working
conditions and the job characteristics are presented separately for men and women. The next step examines
prevalence rates of SBS (based on the sensory perception module of the questionnaire and defined as at least
2 sub-scales having at least 3 items ‘‘minor annoying’’
or more). Finally, multiple logistic regression models for
men and women are compared. Statistical software
SAS, Rel. 6.12 was used for the calculation of multiple
logistic regression models (OR) and the chi-square tests.
Results
Gender-Related Differences in SBS and in Personal,
Work Place-Related and Job-Related Factors
In our sub-sample a high gender-related difference in
prevalence rates was found. On the ‘‘complaints-side’’
44.3% of the women and 26.2% of the men suffer from
SBS. On the ‘‘factor-side‘‘, several significant differences were found. In the mean, men are older and
more highly educated than women. Women more often
report allergy and physical complaints and are more
frequently cigarette smokers (only tendency) than men.
Also the working conditions of women and men are
different. Proportionately more men than women work
at naturally lighted places. Evaluation of the work
place equipment gives more favourable scores for men
than women. Work places of men, more often than
women, are found in large offices with 5 and more persons. Last but not least, men are characterised by much
better job characteristics than women. No significant
differences were found concerning self-reported acute
illness, external locus of control, job satisfaction, airconditioning system, locked windows, working with
computers and software quality (Table 1).
Gender-related SBS prevalence
Gender-Related SBS Prevalence Rates According to
Personal, Work Place-Related and Job-Related
Factors
If gender differences in personal, work place-related or
job-related variables are the cause of the gender dependence in SBS-prevalence rates, persons with the
same personal background / working under the same
conditions should have similar prevalence rates – independent of gender. So the prevalence rates of women
and men related to the items of all impact variables
were compared (Table 2).
At a first glance, Table 2 shows many significant
differences between women and men – following the
well known pattern of significantly higher prevalence
rates in women than in men. However, the trends in
SBS prevalence for most of the variables (school education, acute illness, self-reported allergy, physical
complaints, external locus of control, job satisfaction,
air conditioning system, locked windows, natural
light at the work place and software quality) are
similar for both women and men. Lower educated
employees, persons suffering from acute illness and/
or from an allergy and people reporting low job satisfaction show higher prevalence rates. SBS prevalence rates and external locus of control increase proportionally. Air-conditioned rooms, locked windows,
lack of natural light at the work place and poor software quality also have an unfavourable influence on
the SBS prevalence rate. These results are valid for
women and men in a similar manner but, concerning
SBS-complaints, women react more extremely than
men.
Only women show clear trends in SBS prevalence
rates relating to professional education, number of persons per room and job characteristics. This means that
women characterised by low professional education
and unfavourable job characteristics report more frequent SBS-complaints. An interesting result is the fact
that women working in one person offices have a very
high SBS prevalence rate (57.1%) and women working
in 2–4 person offices have the lowest prevalence rate
(38.2%) related to this variable. From this point, the
prevalence rate increases proportionally to the number
of persons per room reaching 50% in rooms with more
than 10 persons. Inverse trends in SBS prevalence rates
of women and men were found to relate to smoking
behaviour and time spent on computer-work. For
women cigarette smoking is a risk factor, not so for
men. Women working longer than 4 h with computers
are characterised by the highest prevalence rate (49.6%)
related to this variable, men show the lowest prevalence rate (20.7%) under the same circumstances
(Table 2).
Table 2 Gender-related SBS prevalence rates (PR) according to
personal, work place-related and job-related impact factors
Women
n
all
PR
(%)
Men
n
p
PR
(%)
888 44.3
578 26.2 0.001
316
285
189
96
95
177
185
120
age
⬍31 years
31–40 years
41–50 years
⬎50 years
school
education
⬍10 years
166 45.2
10 year graduation 418 44.7
university entrance 295 43.7
qualification
73 27.4 0.010
192 27.2 0.001
309 24.6 0.001
professional
education
no
skilled labour
technical school/
master
university degree
27 66.7
520 56.0
134 38.8
21 23.8 0.003
201 28.4 0.001
100 21.2 0.004
173 39.9
243 24.7 0.001
acute
illness
yes
no
127 63.8
728 40.9
94 45.7 0.008
457 21.7 0.001
self reported
allergy
yes
no
340 54.4
548 38.0
164 28.8 0.001
414 25.1 0.001
physical
complaints
(Zerssen)
without
borderline
pathologic
691 34.4
87 72.4
86 91.9
498 19.5 0.001
42 66.7 0.502
29 79.3 0.065
external
locus of
control
low
middle
high
414 43.2
388 44.3
60 51.7
263 21.7 0.001
278 29.5 0.001
30 33.3 0.100
smoking
cigarettes
yes
no
238 53.4
645 40.9
132 22.9 0.001
442 27.4 0.001
job
satisfaction
satisfied
unsatisfied
631 40.7
257 52.9
412 21.6 0.001
166 37.6 0.002
airconditioned
yes
no
502 48.4
386 38.9
350 27.8 0.001
228 23.7 0.001
windows can yes
be opened
no
627 42.9
241 48.6
406 22.7 0.001
159 34.6 0.006
enough
natural light
659 41.4
219 52.1
496 24.2 0.001
78 38.5 0.039
working with no
computer
⬍4 h
⬎4 h
237 44.7
230 36.5
367 49.6
165 30.9 0.005
119 31.9 0.394
243 20.7 0.001
software
quality
no computer
good software
poor software
237 44.7
560 41.4
91 60.4
165 30.9 0.005
360 22.8 0.001
53 34.0 0.002
number of
persons
per room
1
2–4
5–6
7–10
⬎10
63
346
187
152
122
42
167
140
144
73
yes
no
47.8
43.5
41.8
40.6
57.1
38.2
47.1
46.7
50.0
27.4
23.9
22.2
35.0
26.2
21.6
31.4
23.8
30.1
0.001
0.001
0.001
0.396
0.002
0.001
0.004
0.001
0.007
equipment of good
work place
middle
poor
415 43.4
372 46.8
83 41.0
268 27.0 0.001
269 26.0 0.001
29 17.2 0.021
job
1 (very good)
characteristics 2
3
4 (not so good)
142
360
160
181
206
253
47
33
35.9
42.8
48.1
53.0
19.4
32.1
19.2
33.3
0.001
0.008
0.001
0.037
Gender Typical Risk Factor Models for SBS
The multiple logistic regression models were calculated for women (f) and men (m) and the whole popu-
219
Brasche, Bullinger, Morfeld, Gebhardt and Bischof
Table 3 Impacts on SBS – Odds Ratios (OR) and 5%-Confidence Intervals (CI) of multiple logistic models for women, men and total
Women
nΩ756
Men
nΩ491
Total
nΩ1247
OR (5%-CI)
OR (5%-CI)
OR (5%-CI)
sex
female
age
⬍31 years
31–40 years
41–50 years
⬎50 years
1.19 (0.76–1.86)
1.20 (0.77–1.87)
1
1.02 (0.56–1.87)
2.06 (1.03–4.13)
1.46 (0.80–2.67)
1
2.36 (1.25–4.48)
1.42 (0.99–2.04)
1.30 (0.92–1.83)
1
1.49 (0.97–2.27)
professional
education
no
skilled labour
technical school
university
2.02 (0.75–5.47)
0.96 (0.62–1.50)
0.86 (0.50–1.48)
1
0.70 (0.16–3.03)
1.18 (0.70–1.99)
0.59 (0.29–1.18)
1
1.27 (0.61–2.65)
1.01 (0.73–1.40)
0.82 (0.55–1.25)
1
acute illness
yes
2.55 (1.62–4.00)
3.58 (2.05–6.26)
2.95 (2.10–4.15)
self rep. allergy
yes
1.79 (1.30–2.47)
1.26 (0.76–2.07)
1.59 (1.22–2.07)
external
locus of
control
low
middle
high
1
0.99 (0.51–1.95)
0.81 (0.59–1.13)
1
1.35 (0.47–3.87)
1.62 (1.02–2.59)
1
1.14 (0.66–1.97)
1.04 (0.80–1.34)
job satisfaction
unsatisfied
1.69 (1.19–2.38)
2.71 (1.64–4.47)
1.93 (1.46–2.55)
smoking cigarettes
yes
1.56 (1.11–2.21)
0.82 (0.47–1.42)
1.25 (0.94–1.66)
air-conditioned
yes
1.23 (0.84–1.79)
0.99 (0.61–1.65)
1.19 (0.89–1.59)
software
quality
no computer
good software
poor software
1.18 (0.82–1.70)
1
2.13 (1.26–3.60)
1.89 (1.08–3.28)
1
2.47 (1.12–5.42)
1.30 (0.97–1.75)
1
2.09 (1.36–3.21)
number of
persons
per room
1
2–4
5–6
7–10
⬎10
2.30 (1.22–4.35)
1
1.55 (1.01–2.40)
1.13 (0.69–1.85)
1.54 (0.89–2.67)
1.28 (0.51–3.21)
1
1.25 (0.66–2.37)
0.86 (0.44–1.70)
0.96 (0.44–2.09)
1.87 (1.12–3.10)
1
1.40 (0.99–1.99)
0.99 (0.67–1.47)
1.34 (0.87–2.06)
job
characteristics
1 (very good)
2
3
4 (not so good)
1
1.62 (1.01–2.58)
1.97 (1.13–3.44)
2.46 (1.40–4.34)
1
1.91 (1.13–3.22)
0.91 (0.37–2.23)
2.55 (0.97–6.70)
1
1.67 (1.19–2.34)
1.66 (1.07–2.56)
2.41 (1.53–3.80)
2.14 (1.60–2.86)
boldΩsignificant (p⬍0.05)
lation (total) including most of the variables. All
models contain the same variables for calculation
(Table 3).
As expected, acute illness is highly significant for reported SBS-complaints, affecting men (m: ORΩ3.6)
more than women (f: ORΩ2.6). No job satisfaction (f:
ORΩ1.7; m: ORΩ2.7), poor software quality (f: ORΩ
2.1; m: ORΩ2.5) and unfavourable job characteristics
(f: ORΩ2.5; m: ORΩ2.6) are risk factors related to SBS
in both women and men. But except for ‘‘job characteristics’’ men show higher Odds Ratios than women.
Overall, SBS-complaints are significantly higher for females (adjusted: ORΩ2.1; crude: ORΩ2.2). Typical female risk factors are a private office (one-person room)
(ORΩ2.3), a self-reported allergy (ORΩ1.8) and cigarette smoking (ORΩ1.6). An external locus of control
(ORΩ1.6) and being younger than 31 years (ORΩ2.1)
or older than 50 years (ORΩ2.4) are risk factors only
for men.
Discussion
Fig. 1 Theoretical model of SBS genesis
220
The analysis presented is a continuation of the analysis
of Bullinger et al. (1999) using a sub-group of employees surveyed extensively. The results of Bullinger
et al. are based on a questionnaire and some buildingrelated information, with the great advantage that, because all available employees (4,596) of the 14 office
Gender-related SBS prevalence
buildings were included, the risk of selection bias is
avoided. A disadvantage is that nearly all data are selfreported and are subject to the same psychological
mechanism as SBS-complaints. The present analysis includes variables of the work place and job characteristics recorded in an objective manner.
Gender differences were found in the objective variables, e.g. in the job characteristics and work place ergonomy. Similar results were presented by Stenberg &
Wall (1995). In Table 2 prevalence rates for women and
men related to the items of all the included variables
are shown. In most cases women are characterised by
higher prevalence rates than men under the same circumstances. Women and men show similar trends influencing SBS by the variables school education, selfreported acute illness, self-reported allergy, physical
complaints, external locus of control, job satisfaction,
air-conditioning system, locked windows, natural light
at the work place and software quality. Many of these
variables were also identified in other studies (Skov et
al., 1989; Whitley et al., 1995; Hedge et al., 1996; Sundell, 1996; Norbäck & Edling, 1991) and in the general
multivariate analysis of this project (Brasche et al.,
1999).
As a result, the gender difference in SBS-prevalence
cannot be explained by different working conditions,
different job characteristics and the indicated demographic and psycho-social factors in general. Stenberg & Wall drew the same conclusions from their investigation (Stenberg & Wall, 1995).
The classification of complaints relating to SBS as
symptoms of ‘‘Mass Hysteria’’ – women being more
prone to Mass Psychogenic Illness (MPI) than men – is
a very extreme and provocative hypothesis (Rothman & Weintraub, 1995). Kreiss comments that this diagnosis is ‘‘no longer acceptable or common’’ and refers to explicit diagnostic criteria for MPI such as explosive onset, transmission by sight and sound and
hyperventilation (Kreiss, 1989) which are absent in the
case of SBS. A theoretical approach regarding the route
from a ‘‘sick building’’ to the conscious perception of
‘‘building symptoms’’ to complaints is preferred (Bauer et al., 1992). The physical and psychic disposition on
the one hand and work- and/or job-related factors on
the other hand are considered possible risk factors on
the perception of the indoor environment and directly
on the pathogenesis of complaints (Figure 1).
Acknowledgement
ProKlimA-Project was supported by the program
‘‘Work, Environment and Health’’ of the German Ministry of Education, Science, Research and Technology.
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