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Dietary Intake Estimates and Urinary Cadmium Levels in Danish Postmenopausal Women

BACKGROUND: Cadmium is a known carcinogen that can disrupt endocrine signalling. Cigarette smoking and food are the most common routes of non-occupational exposure to cadmium. Cadmium accumulates in the kidney and can be measured in urine, making urine cadmium (U-Cd) a biomarker of long-term exposur...

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Detalles Bibliográficos
Autores principales: Vacchi-Suzzi, Caterina, Eriksen, Kirsten T., Levine, Keith, McElroy, Jane, Tjønneland, Anne, Raaschou-Nielsen, Ole, Harrington, James M., Meliker, Jaymie R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577120/
https://www.ncbi.nlm.nih.gov/pubmed/26390122
http://dx.doi.org/10.1371/journal.pone.0138784
Descripción
Sumario:BACKGROUND: Cadmium is a known carcinogen that can disrupt endocrine signalling. Cigarette smoking and food are the most common routes of non-occupational exposure to cadmium. Cadmium accumulates in the kidney and can be measured in urine, making urine cadmium (U-Cd) a biomarker of long-term exposure. However dietary-cadmium (D-Cd) intake estimates are often used as surrogate indicator of cadmium exposure in non-smoking subjects. It is therefore important to investigate the concordance between D-Cd estimates obtained with Food Frequency Questionnaires and U-Cd. METHODS: U-Cd levels were compared with estimated dietary-cadmium (D-Cd) intake in 1764 post-menopausal women from the Danish Diet, Cancer and Health cohort. For each participant, a food frequency questionnaire, and measures of cadmium content in standard recipes were used to judge the daily intake of cadmium, normalized by daily caloric intake. Cadmium was measured by ICP-MS in spot urine sampled at baseline and normalized by urinary creatinine. Information on diet, socio-demographics and smoking were self-reported at baseline. RESULTS: Linear regressions between U-Cd and D-Cd alone revealed minimal but significant positive correlation in never smokers (R(2) = 0.0076, β = 1.5% increase per 1 ng Cd kcal(-1), p = 0.0085, n = 782), and negative correlation in current smokers (R(2) = 0.0184, β = 7.1% decrease per 1 ng Cd kcal(-1) change, p = 0.0006, n = 584). In the full study population, most of the variability in U-Cd was explained by smoking status (R(2) = 0.2450, n = 1764). A forward selection model revealed that the strongest predictors of U-Cd were age in never smokers (Δ R(2) = 0.04), smoking duration in former smokers (Δ R(2) = 0.06) and pack-years in current smokers (Δ R(2) = 0.07). Food items that contributed to U-Cd were leafy vegetables and soy-based products, but explained very little of the variance in U-Cd. CONCLUSIONS: Dietary-Cd intake estimated from food frequency questionnaires correlates only minimally with U-Cd biomarker, and its use as a Cd exposure indicator may be of limited utility in epidemiologic studies.