Linked Life Data

12396999

Source:http://linkedlifedata.com/resource/pubmed/id/12396999

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
9
pubmed:dateCreated
2002-10-24
pubmed:abstractText
The impact of cigarette smoking on various diseases is studied frequently in epidemiology. However, there is no consensus on how to model different aspects of smoking history. The aim of this investigation was to elucidate the impact of several decisions that must be made when modeling smoking variables. The authors used data on lung cancer from a case-control study undertaken in Montreal, Quebec, Canada, in 1979-1985. The roles of smoking status, intensity, duration, cigarette-years, age at initiation, and time since cessation were investigated using time-dependent variables in an adaptation of Cox's model to case-control data. The authors reached four conclusions. 1) The estimated hazard ratios for current and ex-smokers depend strongly on how long subjects are required to not have smoked to be considered "ex-smokers." 2) When the aim is to estimate the effect of continuous smoking variables, a simple approach can be used (and is proposed) to separate the qualitative difference between never and ever smokers from the quantitative effect of smoking. 3) Using intensity and duration as separate variables may lead to a better model fit than using their product (cigarette-years). 4) When estimating the effects of time since cessation or age at initiation, it is still useful to use cigarette-years, because it reduces multicollinearity.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0002-9262
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
156
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
813-23
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Modeling smoking history: a comparison of different approaches.
pubmed:affiliation
Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't