Linked Life Data

11980099

Source:http://linkedlifedata.com/resource/pubmed/id/11980099

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2002-4-30
pubmed:abstractText
The aim was to develop a multiple logistic regression model to identify multi-family houses with an increase of sick building syndrome (SBS). In Stockholm, 609 multi-family buildings with 14,235 dwellings were selected by stratified random sampling. The response rate was 77%. Multiple logistic regression analysis was applied, adjusting for ownership of the building, building age and size, age, gender, and atopy. Females, subjects with allergy, those above 65 yr, and those in new buildings reported significantly more SBS. Subjects owning their own building reported less SBS, but the relationship between ownership and building age was strong. A regression model, including factors with a high explanatory value was developed. According to the model, 5% of all buildings built before 1961, 13% of those built 1976-1984, and 15% of those built 1985-1990 would have significantly more SBS than expected. In conclusion, SBS is related to personal factors, building age, and ownership of the building. To identify multi-family buildings with more SBS than expected, it is necessary to adjust for ownership and population characteristics.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0905-6947
pubmed:author
pubmed:issnType
Print
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
101-10
pubmed:dateRevised
2009-9-29
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Development of a multiple regression model to identify multi-family residential buildings with a high prevalence of sick building syndrome (SBS).
pubmed:affiliation
Stockholm Office of Research and Statistics, Stockholm, Sweden. karin.engvall@bepe.a.se
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't