Occupational Medicine 2013;63:38–44 Advance Access publication 8 November 2012 doi:10.1093/occmed/kqs188
Subjective health complaints and psychosocial work environment among university personnel B. E. Moen1, G. Wieslander2, J. V. Bakke3 and D. Norbäck2 University of Bergen, Department of Public Health and Primary Health Care, Bergen, Norway, 2Uppsala University, Department of Occupational and Environmental Medicine, Uppsala, Sweden, 3Norwegian University of Science and Technology, Trondheim and the Norwegian Labour Inspection Authority, Gjøvik, Norway.
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Correspondence to: B. E. Moen, Department of Public Health and Primary Health Care, University of Bergen, Kalfarveien 31, NO-5020 Bergen, Norway. Tel: +47 55586112; fax: +47 55586105; e-mail:
[email protected] Background Questionnaires are often used to study health problems in working populations. An association between self-reported symptoms and psychosocial strain has been suggested, but results from such studies are difficult to interpret, as a gender difference might be present. The knowledge in this area is not clear. Aims
To compare the prevalence of subjective health symptoms and their relation to psychosocial work strain among men and women in different age groups, all working as university staff.
Methods
A cross-sectional survey was carried out among university personnel. The questionnaire included a subjective health complaint inventory consisting of 29 items about subjective somatic and psychological symptoms experienced during the last 30 days and psychosocial work factors. Regression analyses were performed.
Results
In total, 172 (86%) of 201 eligible employees participated. Women had a higher prevalence of musculoskeletal symptoms than men. Significant differences were found between the genders for headaches, neck pain and arm pain. There was a significant relationship between musculoskeletal symptoms and work strain for both genders. This was found for both men and women below 40 years and among men above the age of 40. No significant difference was found between genders regarding pseudoneurological, gastrointestinal, allergic and flu-like symptoms.
Conclusions More female than male university personnel reported musculoskeletal symptoms. The musculoskeletal symptoms were associated with high work strain in both genders, but, for women, this was limited to employees under the age of 40. The cause of this gender difference is unknown. Key words
Gender; musculoskeletal; psychosocial work strain; subjective health complaints; university; work environment.
Introduction Psychosocial work factors have been known for many years to be related to various health complaints, especially psychosomatic disorders [1,2]. High levels of work demands and low work control, also called ‘high occupational strain’, have been related to several negative effects on health, such as heart disease and increased mortality [3,4], anxiety, depression and other types of mental distress [5,6]. High occupational strain can also affect and contribute to the prevalence of musculoskeletal disorders and symptoms [7,8]. Questionnaires are often used to obtain information about self-reported health and perceived working
conditions among employees in workplaces. Both occupational health personnel and researchers use surveys of this kind, and a large number of questionnaires have been developed for risk evaluation and for occupational research [9]. The information obtained can be important in connection with the planning of preventive measures in workplaces, thus, enabling health problems to be detected at an early stage. The Subjective Health Complaints (SHC) Inventory measures the occurrence of both somatic and psychological symptoms [10]. It is sensitive to health complaints with minimal or no clinical findings and should be useful in working populations that are expected to be relatively healthy. It has been suggested that women tend to report a
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B. E. Moen Et Al.: Subjective Health Complaints and Psychosocial Work Environment
higher occurrence of symptoms than men when using both this instrument and similar questionnaires. This has been shown both in studies of general populations and in studies of working populations [11,12], and the gender differences have been most significant for musculoskeletal and pseudoneurological symptoms. It has been debated whether these findings are correct, however. The observed gender differences could be a reflection of a general excess of psychosomatic symptoms among women and could also be related to differences in working conditions and social roles between the genders [13]. More knowledge is needed in order to achieve a better interpretation of gender differences in studies using instruments where SHC are obtained [14], for instance in occupational health and public health studies. Using a population of university staff in a study of gender differences in SHC reduces the problem of differences in physical strain at work. Office work and work in lecture rooms are the main activities of this group of employees. In this kind of population, the ergonomic working conditions are more or less the same for both genders. To our knowledge, university personnel have not been studied before in relation to SHC. Our null hypothesis is that there is no gender difference in SHC among university personnel. Since self-reported psychosocial work factors may influence the results, we also wished to study the association between these factors and SHC. As SHC may increase with age, we also included the age factor. The aim of this study was to compare the prevalence of SHC and their relationship to psychosocial work strain among men and women in different age groups, all working as university staff.
Methods A cross-sectional study was carried out among university personnel in four university buildings, where an indoor air study had been carried out. The houses had been refurbished from apartment houses to serve as offices and lecture rooms for the university in the period 1994– 2000. There had been problems related to the indoor climate in two of these buildings after the refurbishment. The employees had reported discomfort at work due to an unpleasant odour in some parts of the buildings, and they had reported increasing respiratory symptoms to the occupational health service. All the employees of these two houses were moved to other buildings for some months in 1999–2000. In this period, these two houses had been further redecorated and equipped with mechanical supply and exhaust ventilation, and some moisture damages of the buildings was repaired. Improvements had been verified by air microbiology. The indoor parameters measured were similar and within the recommended values for all four buildings at the time of
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our study [15]. The gender distribution of the employees from the two renovated buildings was the same as for the employees in the other two buildings. All employees, PhD students and master students working in these buildings during the study period were invited to participate and were given both oral and written information about the study. The participants gave their written informed consent. The study was carried out from February to March 2004. Two reminders were given. The participants completed a questionnaire themselves, answering questions about gender, age, years of education, academic position at the university (yes/no), daily working hours, current smoking (yes/no) and number of cigarettes smoked daily. Questions about work demands (six items), control (five items) and social support (six items) in the past 3 months were based on the Swedish Demand–Control–Support Questionnaire [16]. Each item was scored on a four-point scale: ‘Yes, often’ = 1, ‘Yes sometimes’ = 2, ‘No, seldom’ = 3 and ‘No, almost never’ = 4 [17]. The scores were totalled, yielding subscale scores from 5 to 20 for demands and latitude, and from 6 to 24 for support. The three indexes were mathematically converted into values in the range of 0.00–1.00 by first subtracting the number of items included from each score and then dividing by the same number. Work demands and control were combined as the factor ‘strain’ (demands divided by control), resulting in a range of 0.00–1.40. SHC were measured using the SHC Inventory [10], which consists of 29 items about subjective somatic and psychological complaints experienced during the last 30 days and uses a four-point scale (0 = no complaints, 1 = some, 2 = much, 3 = severe complaints). The version of the SHC inventory used [10] was developed from the original Ursin health inventory [18,19]. This SHC version has five subscales that were developed by a factor analysis [10]. Musculoskeletal symptoms consisted of eight items (headaches, neck pain, upper back pain, low back pain, arm pain, shoulder pain, migraine and leg pain), giving a maximum score of 24. Pseudoneurological symptoms consisted of seven items (palpitation, heat flushes, sleep problems, tiredness, dizziness, anxiety and depression), giving a maximum score of 21. Gastrointestinal symptoms consisted of seven items (heartburn, stomach discomfort, ulcer/non-ulcer dyspepsia, stomach pain, gas discomfort, diarrhoea and constipation), giving a maximum score of 21. Allergy consisted of five items (asthma, breathing difficulties, eczema, allergy, chest pain), giving a maximum score of 15. Flu consisted of two items (colds/flu, cough), giving a maximum score of six. If there were scores on a minimum of 50% of the items within one subscale, the mean values of the other items in that scale for that individual were imputed. If there were more than 50% missing values within a subscale, the subscale was considered to be missing for that individual. Groups were compared using t-tests for continuous variables and chi-square tests for categorical variables.
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A linear regression model was used to analyse the relationship between different symptom group scores and gender, adjusting for education and working hours. The population was stratified by age using two groups: below and above 40 years old. This was the mean age for women, and, when using this cut-off point, the groups were of similar size. The gender differences for individual items were analysed by categorizing each item into score zero or above, using logistic regression analyses and adjusting for age, education and working hours, as these factors were different for males and females in the present population. In addition, we adjusted for work location in a house with previous indoor air problems (yes/no). The relationship between different symptom group scores and work strain among university personnel was analysed and stratified by gender, using a linear regression model and adjusting for education and working hours. Odds ratios and 95% confidence intervals were calculated. The statistical significance level was set to P