Relating sick building symptoms to environmental conditions and worker characteristics

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2 Scopus citations

Abstract

Recent concern has centered on "sick buildings" in which there has been an unusually high percentage of health complaints by the building's occupants. Typically, these symptoms are thought to be tied to indoor air quality characteristics, such as high levels of respirable particles or volatiles, thermal conditions, etc. In addition, recent studies have drawn connections between "sick building syndrome" (SBS) symptoms and non-environmental variables, i.e., personal and occupational factors. This paper presents a brief review of a study by Hedge et al. (1995) and additional analyses of their data. In a study of 27 air-conditioned office buildings, Hedge et' al. measured nine indoor environmental conditions at various locations within each building and concurrently questioned workers on sixteen SBS symptoms and a number of other personal factors. The additional analyses presented in this paper attempt to draw formal statistical connections between SBS symptoms and both personal worker characteristics and indoor air pollutants simultaneously. The analyses were based on symptom severity response variables whic include information not only on the frequency with which an individual experienced a symptom, but also on how much the symptom disrupted the individual's work. Results from sixteen linear mixed effects models indicate that significant predictors are primarily personal and occupational in nature rather than environmental. For a number of the symptoms, additional variability attributable to buildings exists. However, any physical explanation of this variability remains unclear.

Original languageEnglish (US)
Pages (from-to)172-179
Number of pages8
JournalIndoor Air
Volume8
Issue number3
DOIs
StatePublished - 1998
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Building and Construction
  • Public Health, Environmental and Occupational Health

Keywords

  • Indoor air quality
  • Linear mixed models
  • Occupational health
  • Work-related illness

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