Polyphenol-rich tea decreases iron absorption from fortified wheat bread in Senegalese mother–child pairs and bioavailability of ferrous fumarate is sharply lower in children

The World Health Organization recommends serum ferritin concentrations as the best indicator of iron deficiency (ID). Unfortunately, ferritin increases with infections; hence, the prevalence of ID is underestimated. The objective was to estimate the increase in ferritin in 32 studies of apparently healthy persons by using 2 acute-phase proteins (APPs), C-reactive protein (CRP) and alpha(1)-acid glycoprotein (AGP), individually and in combination, and to calculate factors to remove the influence of inflammation from ferritin concentrations. We estimated the increase in ferritin associated with inflammation (ie, CRP gt 5 mg/L and/or AGP gt 1 g/L). The 32 studies comprised infants (5 studies), children (7 studies), men (4 studies), and women (16 studies) (n = 8796 subjects). In 2-group analyses (either CRP or AGP), we compared the ratios of log ferritin with or without inflammation in 30 studies. In addition, in 22 studies, the data allowed a comparison of ratios of log ferritin between 4 subgroups: reference (no elevated APP), incubation (elevated CRP only), early convalescence (both APP and CRP elevated), and late convalescence (elevated AGP only). In the 2-group analysis, inflammation increased ferritin by 49.6% (CRP) or 38.2% (AGP; both P lt 0.001). Elevated AGP was more common than CRP in young persons than in adults. In the 4-group analysis, ferritin was 30%, 90%, and 36% (all P lt 0.001) higher in the incubation, early convalescence, and late convalescence subgroups, respectively, with corresponding correction factors of 0.77, 0.53, and 0.75. Overall, inflammation increased ferritin by ap 30% and was associated with a 14% (CI: 7%, 21%) underestimation of ID. Measures of both APP and CRP are needed to estimate the full effect of inflammation and can be used to correct ferritin concentrations. Few differences were observed between age and sex subgroups.

The measurement of vitamin A (VA) and iron status is very important in the assessment of nutritional deficiencies. The objective of this research was to develop a sandwich ELISA technique for the simultaneous measurement of ferritin, soluble transferrin receptor, retinol binding protein, and C-reactive protein (CRP) as indicators for VA and iron status. The inclusion of CRP as marker of infection allows for more accurate interpretation of VA and iron status. This is accomplished in a 30-microL serum or plasma sample using an ELISA with different capture and detection antibodies and different dilutions of the sample. Commercially available clinical serum controls were used for calibration purposes. The developed assays were compared to commercially available traditional tests. Regression coefficients comparing both assays were better than 0.84 (P < 0.001). Using a limited sample set, the sandwich ELISA assay produced very similar specificity and sensitivity compared to traditional methods when common cutoff values were applied. Intra- and interassay variability was between 5 and 14% for all tests. The cost of the materials for all 5 measurements decreases to less than $1/sample if a large number of samples is analyzed. Due to the low cost, high throughput, and comparability to traditional tests, this procedure has several advantages for assessing VA and iron status in population surveys.

Dietary iron absorption from a meal is determined by iron status, heme- and nonheme-iron contents, and amounts of various dietary factors that influence iron absorption. Limited information is available about the net effect of these factors. The objective was to develop an algorithm for predicting the effects of factors known to influence heme- and nonheme-iron absorption from meals and diets. The basis for the algorithm was the absorption of iron from a wheat roll (22.1 +/- 0.18%) containing no known inhibitors or enhancers of iron absorption and adjusted to a reference dose absorption of 40%. This basal absorption was multiplied by the expected effect of different amounts of dietary factors known to influence iron absorption: phytate, polyphenols, ascorbic acid, meat, fish and seafood, calcium, egg, soy protein, and alcohol. For each factor, an equation describing the dose-effect relation was developed. Special considerations were made for interactions between individual factors. Good agreement was seen when measurements of iron absorption from 24 complete meals were compared with results from use of the algorithm (r(2) = 0.987) and when mean iron absorption in 31 subjects served a varied whole diet labeled with heme- and nonheme-iron tracers over a period of 5 d was compared with the mean total iron absorption calculated by using the algorithm (P = 0.958). This algorithm has several applications. It can be used to predict iron absorption from various diets, to estimate the effects expected by dietary modification, and to translate physiologic into dietary iron requirements from different types of diets.