Linked Life Data

8328001

Source:http://linkedlifedata.com/resource/pubmed/id/8328001

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2-3
pubmed:dateCreated
1993-8-6
pubmed:abstractText
The dose-response relationship for environmental cadmium exposure was assessed using logistic regression analysis. The prevalence of metallothioneinuria was employed as a response variable, while age and total cadmium intake, calculated from the average cadmium concentration in rice and duration of residence in the cadmium-polluted area, were used as explanatory variables. The target population comprised of 1843 cadmium-exposed and 240 non-exposed inhabitants of Ishikawa, Japan. The individuals were divided into 96 subgroups by sex, age (4 categories), cadmium concentrations in rice (3 categories) and length of residence in the polluted area (4 categories). Only total cadmium intake had a significant association with the prevalence of metallothioneinuria. In the non-exposed subjects total cadmium intakes corresponding to 2.5% prevalence of metallothioneinuria were calculated. Based on metallothionein levels expressed as either microgram/l urine or microgram/g creatinine, the total intakes were: 2.221 or 2.207 g in men and 2.365 or 0.319 g in women, respectively. Most of these values were similar to those reported by us previously, employing simple regression analysis. It is concluded, therefore, that a maximum allowable intake of about 2 g cadmium is a reasonable estimate for preventing the cadmium-induced renal dysfunction.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0300-483X
pubmed:author
pubmed:issnType
Print
pubmed:day
11
pubmed:volume
80
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
207-15
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
Dose-response relationship between total cadmium intake and metallothioneinuria using logistic regression analysis.
pubmed:affiliation
Department of Pharmacology and Toxicology, University of Rhode Island, Kingston 02881-0809.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.