Literature DB >> 33255224

Se Status Prediction by Food Intake as Compared to Circulating Biomarkers in a West Algerian Population.

Moussa Belhadj1, Latifa Sarra Kazi Tani1,2, Nouria Dennouni Medjati1, Yahia Harek1, Majda Dali Sahi1, Qian Sun3, Raban Heller3, Ammaria Behar1, Laurent Charlet2, Lutz Schomburg3.   

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.

Entities:  

Keywords:  food intake; glutathione peroxidase 3; monitoring; predictive model; selenium; selenoprotein P

Mesh:

Substances:

Year:  2020        PMID: 33255224      PMCID: PMC7760749          DOI: 10.3390/nu12123599

Source DB:  PubMed          Journal:  Nutrients        ISSN: 2072-6643            Impact factor:   5.717


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