Supplementation with multiple micronutrients (MM) during pregnancy may result in improved pregnancy and infant outcomes. We conducted meta-analyses of randomised controlled trials that evaluated the effects of prenatal supplementation with MM (defined as containing at least five micronutrients and typically included iron or iron and folic acid). The outcomes of interest were low birthweight (<2500 g), birthweight, small-for-gestational age (SGA), gestational age, preterm birth (<37 weeks' gestation), stillbirth and neonatal death, maternal morbidity and mortality. We identified eligible studies through PubMed and EMBASE database searches. Meta-analyses were performed by pooling results for outcomes that were reported from more than one trial and sub-analyses were conducted to evaluate the effect of timing of intervention and amount of iron. We included published results from 16 trials in this review. Compared with control supplementation that was usually iron plus folic acid in most studies, MM supplementation resulted in a significant reduction in the incidence of low birthweight [pooled risk ratio ( There was no significant difference in the overall risk of preterm birth, stillbirth, and maternal or neonatal mortality, but we found an increased risk of neonatal death for the MM group compared with iron-folate in the subgroup of five trials that began the intervention after the first trimester (RR 1.38 [95% CI 1.05, 1.81]). None of the studies evaluated maternal morbidity. Compared with iron plus folic acid supplementation alone, prenatal maternal supplementation with MM resulted in a reduction in the incidence of low birthweight and SGA but increased risk of neonatal death in the subgroup of studies that began the intervention after the first trimester.

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Inflammation affects trace nutrient concentrations, but research on copper and particularly in children is limited. We assessed associations between serum C-reactive protein (CRP) and zinc, iron, copper, and other biomarkers (alkaline phosphatase, hemoglobin, and albumin), in 634 healthy 6- to 11-year-old Guatemalan schoolchildren. CRP was measured by a standardized, high-sensitive method. For significant associations with CRP, we stratified nutrient concentrations across categories of CRP and compared concentrations above and below several CRP cutoff points (0.5, 1, 3, 5, and 10 mg/L), and then adjusted values using correction factors (ratios of geometric means of the nutrients in the low and high groups). Prevalence of serum zinc (<65 μg/dL0, ferritin (<15 μg/L), and copper (<90 μg/dL) deficiency were 21%, 2.1%, and 23.8%, respectively. Median (25th and 75th percentiles) CRP was 0.56 (0.26 and 1.54) mg/L. CRP concentration was positively associated with ferritin and copper concentrations (r=0.23 and 0.29, respectively; P<0.0001) but not with zinc and other bio-markers (P>0.05). Regardless of CRP cutoffs, high (> cutoff) vs. low (≤ cutoff) CRP levels had higher ferritin and copper concentrations and lower prevalence of copper deficiency of <90 μg/dL (P<0.05). Adjustment for inflammation had the greatest influence on recalculated prevalence for the CRP 0.5 mg/L cutoff. The low ferritin prevalence hardly changed (from 2.1% to 2.5%) while the low copper prevalence changed appreciably (from 23.8% to 31.2%). In conclusion, CRP was positively associated with ferritin and copper but not with zinc concentrations. Adjustment for inflammation had little effect on low ferritin prevalence, low to begin with, and a large impact on low copper prevalence. High-sensitive CRP methods and the use of very low CRP cutoffs may be more accurate than traditional CRP methods in the adjustment of serum copper concentrations for inflammation in healthy school children.

Understanding and being able to measure, analyze, compare, and contrast the image of a tourism destination, also known as tourism destination image (TDI), is critical in tourism management and destination marketing. Although various methodologies have been developed, a consistent, reliable, and scalable method for measuring TDI is still unavailable. This study aims to address the challenge by proposing a framework for a holistic measure of TDI in four dimensions, including popularity, sentiment, time, and location. A structural model for TDI measurement that covers various aspects of a tourism destination is developed. TDI is then measured by a comprehensive computational framework that can analyze complex textual and visual data on a large scale. A case study using more than 30,000 images, and 10,000 comments in relation to three tourism destinations in Australia demonstrates the effectiveness of the proposed framework.