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The influence of individual and contextual psychosocial work factors on the perception of the indoor environment at work: a multilevel analysis

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Abstract

Purpose

The aims of this study was to investigate the role of the psychosocial work environment—at the individual level as well as the workplace level—in explaining the variability in the employees’ perception of the indoor environment.

Methods

The perception of the indoor environment was surveyed by questionnaires among 3,281 employees in 39 randomly selected workplaces. Multilevel logistic regression analyses included individual-level and workplace-level covariates to examine the effect of context. Associations between psychosocial risk factors at the workplace level and the employees’ perception of the indoor environment was calculated as the interval odds ratios while between-workplace variations were quantified by intraclass correlations and median odds ratios.

Results

We found moderate differences between the workplaces in the perception of the indoor environment, but large differences between individuals in the same building indicating that some occupants of a building do perceive problems in the indoor environment even in the absence of a general indoor air problem in the workplace. The type of organisation accounted for some of the variation in perceived indoor environment. Psychosocial work environment factors at the individual level, but not at the workplace-level, were associated with the individual perception of the indoor environment. In addition, an increased tendency to report symptoms was strongly associated with complaints about the indoor environment suggesting bias due to a tendency to “over-report”.

Conclusion

In studies investigating “sick buildings” contextual factors may be important. Multilevel analyses should be used in future research within workplaces where clustering could be expected.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

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Correspondence to Charlotte Brauer.

Appendix

Appendix

The interval odds ratio (IOR-80)

The IOR-80 describes the effect of the workplace-level risk factor. Consider all possible pairs of persons with similar individual covariates, in which one person works in a workplace with a low value of the aggregate workplace risk factor and the other in a workplace with a high value of the same aggregate workplace risk factor. For all possible pairs the OR is computed and we obtain a distribution of the OR. The IOR-80 is defined as the interval centred on the median of the distribution that comprises 80% of the values of the OR. If the interval contains the value 1, it indicates that the workplace risk factor does not account for a substantial amount of the variation between the workplaces.

The lower and the upper bounds of the IOR were computed with the following formula (Larsen and Merlo 2005; Merlo et al. 2006):

$$ \begin{gathered} {\text{IOR}}_{\text{lower}} = \exp \left[ {\beta + \sqrt {\left( {2 \times {\text{V}}_{\text{A}} } \right)} \times \left( { - 1.2816} \right)} \right] \hfill \\ {\text{IOR}}_{\text{upper}} = \exp \left[ {\beta + \sqrt {\left( {2 \times {\text{V}}_{\text{A}} } \right)} \times 1.2816} \right] \hfill \\ \end{gathered} $$

where β is the regression coefficient for the workplace-level variable, VA is the workplace-level variance, and the values −1.2816 and +1.2816 are the 10th and 90th percentiles of the normal distribution with mean 0 and variance 1.

The intraclass correlation coefficient (ICC)

The ICC is a measure of clustering often used in multilevel linear regression which gives information about the proportion of total variance in the outcome that is attributable to the area level as for instance a workplace level (Merlo et al. 2005). A high ICC indicates clustering and suggests that the workplaces are very important in understanding individual differences in outcome. Conversely, an ICC of 0 suggests that the workplace context is irrelevant in understanding individual differences in outcome. It is computed as ICC = VA/(VA + VI) where VA is the area-level variance and VI is the individual level variance (Merlo et al. 2005, 2006). In multilevel linear regression both the area-level variance and the individual level variance are expressed on the same scale, but in multilevel logistic regression these variances are not directly comparable as the area-level variance is on the logistic scale and the individual level variance is on the probability scale. Snijders and Bosker have described a method to compute the ICC in the case of logistic regression (Snijders and Bosker 1999). This method converts the individual level variance from the probability scale to the logistic scale before computing the ICC which then can be calculated with the following formula that was used in the present study:

$$ {\text{ICC}} = {{{\text{V}}_{\text{A}} } \mathord{\left/ {\vphantom {{{\text{V}}_{\text{A}} } {\left( {{\text{V}}_{\text{A}} + {{\pi^{2} } \mathord{\left/ {\vphantom {{\pi^{2} } 3}} \right. \kern-\nulldelimiterspace} 3}} \right)}}} \right. \kern-\nulldelimiterspace} {\left( {{\text{V}}_{\text{A}} + {{\pi^{2} } \mathord{\left/ {\vphantom {{\pi^{2} } 3}} \right. \kern-\nulldelimiterspace} 3}} \right)}} $$

where VA is the workplace-level variance.

In the text the intraclass correlation coefficient refers to the variances in the empty model while residual intraclass correlation coefficient refers to the variances in the models which control for the effect of explanatory variables (Snijders and Bosker 1999).

The median odds ratio (MOR)

The MOR is also a measure of clustering (Larsen and Merlo 2005; Merlo et al. 2006). Considering all possible pairs of persons with similar individual covariates but working in different workplaces, the OR of all these pairs can be computed yielding a distribution of the OR. The MOR is defined as the median value of this distribution. It corresponds to the increased risk that (in median) a person would have, if moving to another workplace with a higher risk. If MOR is equal to 1, there is no workplace variance.

The MOR was computed in the following way:

$$ {\text{MOR}} = \exp \left[ {\sqrt {\left( {2 \times {\text{V}}_{\text{A}} } \right)} \times 0.6745} \right] $$

where VA is the workplace-level variance, and 0.6745 is the 75th percentile of the cumulative distribution function of the normal distribution with mean 0 and variance 1.

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Brauer, C., Mikkelsen, S. The influence of individual and contextual psychosocial work factors on the perception of the indoor environment at work: a multilevel analysis. Int Arch Occup Environ Health 83, 639–651 (2010). https://doi.org/10.1007/s00420-010-0511-9

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