dc.contributor.author
Belhadj, Moussa
dc.contributor.author
Kazi Tani, Latifa Sarra
dc.contributor.author
Dennouni Medjati, Nouria
dc.contributor.author
Harek, Yahia
dc.contributor.author
Dali Sahi, Majda
dc.contributor.author
Sun, Qian
dc.contributor.author
Heller, Raban
dc.contributor.author
Behar, Ammaria
dc.contributor.author
Charlet, Laurent
dc.contributor.author
Schomburg, Lutz
dc.date.accessioned
2021-01-13T13:54:52Z
dc.date.available
2021-01-13T13:54:52Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/29007
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-28757
dc.description.abstract
Algeria is the largest country in Africa, located close to the Mediterranean coastal area, where nutrients consumption varies widely. Local data on selenium composition of foods are not available. We postulated a close correlation between selenium status predictions from food consumption analysis with a quantitative analysis of circulating biomarkers of selenium status. Population characteristics were recorded from 158 participants and dietary selenium intake was calculated by 24-h recall. The average total plasma selenium was 92.4 ± 18.5 µg/L and the mean of selenium intake was 62.7 µg/day. The selenoprotein P concentration was 5.5 ± 2.0 mg/L and glutathione peroxidase 3 activity was 247.3 ± 41.5 U/L. A direct comparison of the dietary-derived selenium status to the circulating selenium biomarkers showed no significant interrelation. Based on absolute intakes of meat, potato and eggs, a model was deduced that outperforms the intake composition-based prediction from all food components significantly (DeLong's test, p = 0.029), yielding an area under the curve of 82%. Selenium status prediction from food intake remains a challenge. Imprecision of survey method or information on nutrient composition makes extrapolating selenium intake from food data providing incorrect insights into the nutritional status of a given population, and laboratory analyses are needed for reliable information.
en
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
predictive model
en
dc.subject
selenoprotein P
en
dc.subject
glutathione peroxidase 3
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
Se Status Prediction by Food Intake as Compared to Circulating Biomarkers in a West Algerian Population
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
3599
dcterms.bibliographicCitation.doi
10.3390/nu12123599
dcterms.bibliographicCitation.journaltitle
Nutrients
dcterms.bibliographicCitation.number
12
dcterms.bibliographicCitation.originalpublishername
MDPI AG
dcterms.bibliographicCitation.volume
12
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
33255224
dcterms.isPartOf.eissn
2072-6643