Investigation of "Sick" Residential and Workplace Buildings using a Computerized/Web-Based Occupant Health Survey Instrument

Speaker(s): 
Date: 
September 15, 2005 - 12:00pm
Location: 
Bldg. 90

Epidemiological investigation of occupants of a residential or non-industrial workplace building (or building complex) is a well-established, public health method used to identify and measure the nature, distribution, and cause of occupational or environmental illness related to indoor air quality (IAQ) problems or concerns. Such an investigation is particularly useful where disease-exposure associations have not been clearly established and multiple environmental and human factors may be implicated or considered. --The ”sick building syndrome” has been recognized world-wide for over 30 years, and continues to be one of the most common IAQ-related occupant health problems.  Although it has been the subject of numerous epidemiological investigations, it remains one of the most difficult to define in terms of its symptoms and causation.  Other recognized diseases such as asthma have also been increasingly associated with IAQ-related environmental agents, conditions and problems, including moisture, mold, building materials and by-products, ventilation, and various allergens.  --To better understand and quantify the nature, extent, distribution, and building-relatedness of occupant illness in problem buildings with specific or poorly characterized occupant health complaints or IAQ problems, and their relationship of occupant health conditions to putative indoor environmental contaminants or factors, innovative, sophisticated investigational tools and methods are needed to conduct comprehensive, accurate, and cost-effective epidemiological investigations.  --A highly reliable, software-based (stand-alone and web-based) technology for the customized collection of complex occupant health symptom data among a cohort of occupants of any workplace or residential building is described.  Unique design features and analysis methods in the software are employed to minimize sources of bias, confounding, and effect modification. The data are analyzed in comparison to a control population using multivariate statistical methods to identify and quantify the building-relatedness, determinants and distribution of occupants' illness.  --The results of a case study is presented to highlight the power and utility of this new methodology, and its implications for diagnosing, treating, and preventing a significant amount of indoor air quality-related health complaints.  Potential research and field applications of this technology in both problem and non-problem buildings are discussed.

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