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Predictors of erythrocyte cadmium levels in 454 adults in Florence, Italy

Caini, Saverio; Bendinelli, Benedetta; Masala, Giovanna; Saieva, Calogero; Lundh, Thomas LU ; Kyrtopoulos, Soterios A. and Palli, Domenico (2018) In Science of the Total Environment 644. p.37-44
Abstract

Background: Cadmium bioaccumulates in the body and causes several adverse health effects. Understanding the primary sources of exposure is critical in order to implement effective prevention measures. Methods: We included 454 adults enrolled in the Florence cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) during 1992–98. At enrolment, information was collected on demographics, lifestyle and dietary habits using validated questionnaires; anthropometric measures were taken; and a blood sample was collected from each study participant. Information on the residential and occupational history prior to enrolment was reconstructed by phone interviews. Cadmium levels were measured in erythrocytes using... (More)

Background: Cadmium bioaccumulates in the body and causes several adverse health effects. Understanding the primary sources of exposure is critical in order to implement effective prevention measures. Methods: We included 454 adults enrolled in the Florence cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) during 1992–98. At enrolment, information was collected on demographics, lifestyle and dietary habits using validated questionnaires; anthropometric measures were taken; and a blood sample was collected from each study participant. Information on the residential and occupational history prior to enrolment was reconstructed by phone interviews. Cadmium levels were measured in erythrocytes using inductively coupled plasma-mass spectrometry. We used multiple linear regression models to investigate the main determinants of cadmium levels. Results: Median erythrocyte cadmium levels were 0.66 μg/L (inter-quartile range 0.43–1.07 μg/L). Cadmium levels were lowest in never smokers (0.50 μg/L) and highest in current smokers (1.38 μg/L). Smoking status and the number of pack-years were the strongest predictors of cadmium levels in multivariable analysis, together with erythrocyte levels of lead, and biking to work, while an inverse association emerged with consumption of red meat and dairy products and physical activity levels. Cadmium levels were higher among women than men (0.66 vs. 0.58 μg/L), and, among the former, positively associated with late menopause, nulliparity, and use of hormones for menopause. The predictors included in the multivariable model explained >40% of the variability in erythrocyte cadmium levels. Conclusions: Smoking was the most important determinant of erythrocyte cadmium levels, which were also affected by dietary habits, physical activity levels, biking, and (among women) hormone-related variables. Our results are important to inform public health actions aimed at reducing the impact of potentially modifiable sources of exposure to cadmium.

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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Cadmium, Diet, Lifestyle, Predictors
in
Science of the Total Environment
volume
644
pages
8 pages
publisher
Elsevier
external identifiers
  • scopus:85049320188
ISSN
0048-9697
DOI
10.1016/j.scitotenv.2018.06.347
language
English
LU publication?
no
id
bc57ba6d-055f-4a16-98c9-03514a47c9a8
date added to LUP
2018-07-12 12:38:15
date last changed
2018-07-13 03:00:04
@article{bc57ba6d-055f-4a16-98c9-03514a47c9a8,
  abstract     = {<p>Background: Cadmium bioaccumulates in the body and causes several adverse health effects. Understanding the primary sources of exposure is critical in order to implement effective prevention measures. Methods: We included 454 adults enrolled in the Florence cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) during 1992–98. At enrolment, information was collected on demographics, lifestyle and dietary habits using validated questionnaires; anthropometric measures were taken; and a blood sample was collected from each study participant. Information on the residential and occupational history prior to enrolment was reconstructed by phone interviews. Cadmium levels were measured in erythrocytes using inductively coupled plasma-mass spectrometry. We used multiple linear regression models to investigate the main determinants of cadmium levels. Results: Median erythrocyte cadmium levels were 0.66 μg/L (inter-quartile range 0.43–1.07 μg/L). Cadmium levels were lowest in never smokers (0.50 μg/L) and highest in current smokers (1.38 μg/L). Smoking status and the number of pack-years were the strongest predictors of cadmium levels in multivariable analysis, together with erythrocyte levels of lead, and biking to work, while an inverse association emerged with consumption of red meat and dairy products and physical activity levels. Cadmium levels were higher among women than men (0.66 vs. 0.58 μg/L), and, among the former, positively associated with late menopause, nulliparity, and use of hormones for menopause. The predictors included in the multivariable model explained &gt;40% of the variability in erythrocyte cadmium levels. Conclusions: Smoking was the most important determinant of erythrocyte cadmium levels, which were also affected by dietary habits, physical activity levels, biking, and (among women) hormone-related variables. Our results are important to inform public health actions aimed at reducing the impact of potentially modifiable sources of exposure to cadmium.</p>},
  author       = {Caini, Saverio and Bendinelli, Benedetta and Masala, Giovanna and Saieva, Calogero and Lundh, Thomas and Kyrtopoulos, Soterios A. and Palli, Domenico},
  issn         = {0048-9697},
  keyword      = {Cadmium,Diet,Lifestyle,Predictors},
  language     = {eng},
  month        = {12},
  pages        = {37--44},
  publisher    = {Elsevier},
  series       = {Science of the Total Environment},
  title        = {Predictors of erythrocyte cadmium levels in 454 adults in Florence, Italy},
  url          = {http://dx.doi.org/10.1016/j.scitotenv.2018.06.347},
  volume       = {644},
  year         = {2018},
}