Linked Life Data

7869077

Source:http://linkedlifedata.com/resource/pubmed/id/7869077

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1995-3-30
pubmed:abstractText
Antioxidant vitamin intake (C,E and carotene) is assessed from a food frequency questionnaire applied to 10,359 middle-aged men and women participating in the Scottish Heart Health Study. Logistic regression analysis is then used to quantify the relationship between antioxidant vitamin consumption and prevalent coronary heart disease (CHD), analysing diagnosed and undiagnosed cases separately. For men, there is a protective effect of all three antioxidants, before and after adjustment for a comprehensive set of confounding variables. For women the picture is less clear, only vitamin C is negatively associated with CHD, but the effect is removed by adjustment. The logistic regression model is also used to determine classification rules for deciding whether or not an individual has CHD. The classification error rates using the antioxidants are found to be very similar to those found using smoking, blood pressure and serum total cholesterol as classification variables. Significant interactions are found for the antioxidants with smoking, cholesterol and age. It is concluded that antioxidant vitamin intake protects against CHD for men. Logistic regression analysis is compared with discriminant analysis, and is found to have important advantages as an epidemiological tool.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0895-4356
pubmed:author
pubmed:issnType
Print
pubmed:volume
48
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
307-16
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
An investigation of the relationship between antioxidant vitamin intake and coronary heart disease in men and women using logistic regression analysis.
pubmed:affiliation
Department of Applied Statistics, University of Reading, England.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't