Linked Life Data

14756842

Source:http://linkedlifedata.com/resource/pubmed/id/14756842

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2004-2-3
pubmed:abstractText
In this study, we were able to separate buildings with high and low prevalence of sick building syndrome (SBS) using principal component analysis. The prevalence of SBS was defined by the presence of at least one typical skin, mucosal and general (headache and fatigue) symptom. Data from the Swedish Office Illness Study describing the presence and level of chemical compounds in outdoor, supply, and room air, respectively, were evaluated together with information about the buildings in six models. When all data were included the most complex model was able to separate 71% of the high prevalence buildings from the low prevalence buildings. The most important variable that separates the high prevalence buildings from the low prevalence buildings was a more frequent occurrence or a higher concentration of compounds with shorter retention time in the high prevalence buildings. Elevated relative humidity in supply and room air and higher levels of total volatile organic compounds in outdoor and supply air were more common in high prevalence buildings. Ten building variables also contributed to the separation of the two classes of low and high prevalence buildings.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0905-6947
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
16-23
pubmed:dateRevised
2009-9-29
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Class separation of buildings with high and low prevalence of SBS by principal component analysis.
pubmed:affiliation
Department of Chemistry, Environmental Chemistry, Umeå University, Umeå, Sweden.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't