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). 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