Linked Life Data

1397219

Source:http://linkedlifedata.com/resource/pubmed/id/1397219

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1992-11-23
pubmed:abstractText
Two population samples of men aged 46-65 years were examined for the measurement of some cardiovascular risk factors and followed up for 6.5 years. The two groups were: 1) 3338 men belonging to occupational groups examined in Rome (ROG) in 1979-81 and 2) 1543 men belonging to two demographic samples of rural areas located in northern and central Italy (IRA) examined in 1965. In men free from previous myocardial infarction the rate of fatal coronary events was 18.0 in the ROG group and 17.5 per 1000 in the IRA group. Five established risk factors (age, systolic blood pressure, serum cholesterol, cigarette consumption and body mass index) were used in a multivariate model for predicting coronary deaths. The coefficients of the multiple logistic function were similar in the two populations group. However, when the IRA coefficients were applied to the ROG factors, they predicted 43 events instead of 58 (under-estimation of 26%; p < 0.05), whereas the ROG coefficients predicted 31 events instead of 26 in the IRA sample (over-estimation of 19%; p = n.s.). A model which included the pool of the two populations and a dummy-variable for the identification of each of them, suggested that being a member of the ROG group is accompained, everything else being equal, by an extra risk of 26%.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0393-2990
pubmed:author
pubmed:issnType
Print
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
521-6
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
The prediction of coronary heart disease in different population samples.
pubmed:affiliation
Laboratory of Epidemiology and Biostatistics, Istituto Superiore di Sanità, Rome, Italy.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't