Perceived health and indoor environmental quality in green-certified and non-green buildings in a public organization in Taiwan.

摘要

The current study is the first to empirically investigate the effects of green-certified buildings on human resource outcomes. This observational study uses survey data to compare self-reported health symptoms (HS) and satisfaction with indoor environmental quality (IEQS) for two intact groups of male employees working for the same public sector employer in Taiwan: one group works in certified green building (n=211), and the other works in two non-green buildings (n=161).;Using multiple regression analysis, this study found strong empirical support for 3 of 4 research hypotheses. First, study participants in the green building had IEQS scores 32.3% higher on average (p 0.001) than those in the non-green buildings, controlling for general building satisfaction (GBS) and average weekly hours worked in the building (HRs). The observed effect size for the difference in the adjusted mean IEQS scores is 4.62, a very large effect as defined by Cohen. Thus this effect of the green building on IEQS is both statistically significant and substantively important.;Second, employees in the green building had HS scores 7.50 points (or 15.9%) higher, on average, than those in the non-green buildings controlling for GBS, HRs, job satisfaction (JS), age (AGE), and psychological demands of work (PSD) (p 0.001). The effect size for the estimated difference in adjusted HS means is 2.26, a large effect.;Strong empirical support was also found for the third research hypothesis using an alternative specification of the model for HS in which IEQS is added as a control variable. On average, a one point increase in IEQS is associated with a 0.19 point increase in HS, controlling for GB, JS, AGE, PSD, GBS, and HRs (p 0.001). The effect size for IEQS is 0.56, a large effect as defined by Cohen and Cohen for continuous explanatory variables in regression analysis.;The fourth research hypothesis was not empirically supported by the data. Depending on the specification of the model for HS, the effect of JS on HS is either negligible (explains less than 1% of the variance in HS) and not significant or negligible, significant, and the wrong sign (negative).