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Background: Micronutrient intake and status in lactating women may impact micronutrient levels in milk. Objectives: This study aimed to determine the micronutrient intake and status in lactating women, and their association with micronutrient levels in human milk. Methods: Lactating women were enrolled at 4–6 months postpartum. A 24h food recall was examined and nutrient intakes were analyzed using INMUCAL software. Human milk samples were collected to analyze calcium, copper, iron, and zinc levels. Plasma zinc and serum ferritin levels were determined. Results: Thirty-four women participated; 19 were classified as full breastfeeding and 15 as partial breastfeeding. Mean levels of calcium, copper, iron, and zinc in human milk were 243, 0.2, 0.2, and 1.56 mg/L, respectively. The prevalence of zinc deficiency (plasma zinc < 10.7 µmol/L) was 11.8%. No lactating women had iron deficiency. Nutrient intakes were lower than the recommended amounts in 38%–70% of participants, and were not correlated with corresponding nutrient levels in human milk. Multiple linear regression showed significant association between zinc levels in human milk and plasma for lactating women with full breastfeeding (β = 0.034, 95% confidence interval [0.003, 0.067], p = 0.040). Conclusions: Lactating women were at risk of micronutrient deficiency. There was an association between zinc levels in human milk and plasma of lactating women with full breastfeeding. As the nutritional status of lactating women influences the quality of human milk, we should encourage good nutrient intake for lactating women. [ABSTRACT FROM AUTHOR]

Rice is a staple food for nearly half the world's population. The discrimination of geographical origin of rice in order to its authenticity is essential to prevent mislabeling and adulteration problems. The multi-element fingerprinting has a great potential for the differentiation of rice grains. A study of the capability of the high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) methodology for multi-element fingerprinting of rice has been carried out. A total of 31 Thai jasmine rice and 5 foreign (France, India, Italy, Japan and Pakistan) rice samples were analysed by high resolution ICP-MS after acid digestion. Accuracy of the whole procedure was verified by the analysis of rice flour standard reference material (NIST SRM 1568a). The concentrations of 21 elements were evaluated and used as chemical indicator to discriminate the origin of rice samples. The classification of rice samples was carried out based on elemental composition by a radar plot and multivariate data analysis, including principal component analysis (PCA) and discriminant analysis (DA). Thai jasmine rice can be differentiated from foreign rice samples by radar plots and multivariate data analysis. Furthermore, the DA can differentiate Thai jasmine rice samples according to each region of origin (northern, northeastern or central regions of Thailand). Therefore, multi-element fingerprinting combined with the use of multivariate statistical techniques can be considered as a powerful tool for rice authentication., (Copyright © 2013 Elsevier Ltd. All rights reserved.)