Anthropometric Markers and Iron Status of 6–12-Year-Old Thai Children: Associations and Predictors

Introduction. Obesity may be associated with poor iron status. The objective of this study was to investigate the association between different indices of iron status and anthropometric measurements in Thai children. Materials and Methods. Anthropometry (weight, height, waist circumference (WC), and body composition assessed by bioelectrical impedance analysis) and iron indices were measured in 336 Thai children aged 6–12 years. Iron deficiency (ID) was defined using two or more of the following: (1) %transferrin saturation (%Tsat)  5 mg/L. Iron deficiency anaemia (IDA) was defined as haemoglobin 5 mg/L. Puberty and menarche were significant predictors of ID (puberty adjusted OR: 2.20, 95% CI: 0.43, 11.25; menarche adjusted OR: 6.11, 95% CI: 1.21, 30.94). Conclusion. Greater adiposity was associated with poorer iron status. However, SF may not be a good indicator of iron status in Thai children, particularly in those who are overweight/obese, whereas sTfR merits further investigation

Comparison of 24-Hour Recall and 3-Day Food Records during the Complementary Feeding Period in Thai Infants and Evaluation of Plasma Amino Acids as Markers of Protein Intake

BACKGROUND: An accurate and reliable measurement of nutrient intake is the first and foremost step in order to optimise infant nutrition and evaluate its impact on health outcomes. However, research on the validity of dietary assessment tools used during the weaning period is limited, especially in lower-middle income countries. The primary aim of this study was to evaluate relative validity of a 24-h recall method (24-HR) using a 3-day food record (3-DFR). A secondary aim was to investigate association between protein intake from 3-DFR and plasma amino acids as a potential protein biomarker. Methods A multicentre, prospective cohort study was conducted in Chiang Mai, Thailand from June 2018 to May 2019. Food consumption data were collected in healthy infants using 24-HR and 3-DFR at 9 and 12 months of age. Blood samples were obtained at 12 months (M). Plasma amino acids were analysed using high performance liquid chromatography. Results Of 145 infants, 49% were female. At group level, paired t-tests/Wilcoxon signed rank tests did not show significant differences between average nutrient intakes from the 2 dietary assessment methods, except for vitamin A and vitamin C. Weighted kappa (Kw) was acceptable for all nutrients, except for vitamin A intake at 9 M (Kw = 0.15). The Bland-Altman analyses were unbiased for most nutrients with variable limits of agreement. At individual level, correlation coefficients (r) ranged from acceptable to excellent (r = 0.37-0.87) while cross-classifications showed acceptable outcomes, except for vitamin A. Multivariate analyses showed significant associations between protein intake at 12 M from the 3-DFR and plasma concentrations of branched-chain amino acids (BCAA) and essential amino acids (EAA), even after adjusting for gender, milk feeding type and energy intake. Conclusions For infants aged 9-12 M, a 24-HR can be used as a more practical alternative to a 3-DFR for most nutrients although caution is required for some micronutrients, especially vitamin A. A repeated interview might further improve the accuracy. Furthermore, protein intake, particularly animal-based protein, significantly predicted plasma BCAA and EAA concentrations regardless of gender, type of milk feeding and energy consumption

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed

Nutrition challenges ahead

The breakout session ‘Nutrition challenges ahead’ was held at the EFSA 2nd Scientific Conference ‘Shaping the Future of Food Safety, Together’ (Milan, Italy, 14–16 October 2015) to address the main problems in the area of nutrition to be faced in the 21st Century, both at a global and individual level. The nutrition challenges ahead are diverse and depend on agricultural, socioeconomic and individual factors. At a global level, food security, food sustainability and decreasing the impact of food production on climate change are of paramount importance. Decreasing the prevalence of obesity and related disorders, which may coexist with selected micronutrient deficiencies, is a major challenge for wealthy countries; for developing countries and rural food systems, fighting protein–energy malnutrition and micronutrient deficiencies is a priority. Diets based on a wide variety of nutrient-rich local plant foods (e.g. fruits, vegetables, whole grain cereals, vegetable oils, nuts) that contain moderate amounts of animal protein (preferably in the form of fish) and are low in saturated and trans-fatty acids, added sugars and sodium, are healthy, nutritious, sustainable and climate friendly. Creating an environment where such diets are also economically advantageous and convenient may be a part of a global solution to these nutritional challenges. Individuals, however, are unique regarding their genetic background, gut microbiota and health status. In addition, nutrition may already play a role in the development (and prevention) of disease very early in life. Thus, additional health benefits could be achieved by tailoring nutritional strategies to particular population subgroups or even individuals on the basis of current and future knowledge about the relationship between nutrients, genes, the microbiome and health. New technologies and food innovation may help in finding novel foods fit for purpose

Assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: Systematic review and meta-regression

Objective: To assess the impact of inadequate water and sanitation on diarrhoeal disease in low- and middle-income settings. Methods: The search strategy used Cochrane Library, MEDLINE & PubMed, Global Health, Embase and BIOSIS supplemented by screening of reference lists from previously published systematic reviews, to identify studies reporting on interventions examining the effect of drinking water and sanitation improvements in low- and middle-income settings published between 1970 and May 2013. Studies including randomised controlled trials, quasi-randomised trials with control group, observational studies using matching techniques and observational studies with a control group where the intervention was well defined were eligible. Risk of bias was assessed using a modified Ottawa-Newcastle scale. Study results were combined using meta-analysis and meta-regression to derive overall and intervention-specific risk estimates. Results: Of 6819 records identified for drinking water, 61 studies met the inclusion criteria, and of 12 515 records identified for sanitation, 11 studies were included. Overall, improvements in drinking water and sanitation were associated with decreased risks of diarrhoea. Specific improvements, such as the use of water filters, provision of high-quality piped water and sewer connections, were associated with greater reductions in diarrhoea compared with other interventions. Conclusions: The results show that inadequate water and sanitation are associated with considerable risks of diarrhoeal disease and that there are notable differences in illness reduction according to the type of improved water and sanitation implemented

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.Comment: 18 pages, 5 figure

Quality and Safety Aspects of Infant Nutrition

Quality and safety aspects of infant nutrition are of key importance for child health, but oftentimes they do not get much attention by health care professionals whose interest tends to focus on functional benefits of early nutrition. Unbalanced diets and harmful food components induce particularly high risks for untoward effects in infants because of their rapid growth, high nutrient needs, and their typical dependence on only one or few foods during the first months of life. The concepts, standards and practices that relate to infant food quality and safety were discussed at a scientific workshop organized by the Child Health Foundation and the Early Nutrition Academy jointly with the European Society for Paediatric Gastroenterology, Hepatology and Nutrition, and a summary is provided here. The participants reviewed past and current issues on quality and safety, the role of different stakeholders, and recommendations to avert future issues. It was concluded that a high level of quality and safety is currently achieved, but this is no reason for complacency. The food industry carries the primary responsibility for the safety and suitability of their products, including the quality of composition, raw materials and production processes. Introduction of new or modified products should be preceded by a thorough science based review of suitability and safety by an independent authority. Food safety events should be managed on an international basis. Global collaboration of food producers, food-safety authorities, paediatricians and scientists is needed to efficiently exchange information and to best protect public health. Copyright (C) 2012 S. Karger AG, Base

Development and validation of a prediction model for fat mass in children and adolescents: Meta-analysis using individual participant data

© Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to. To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment. Design Individual participant data meta-analysis. Setting Four population based cross sectional studies and a fifth study for external validation, United Kingdom. Participants A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass. Main outcome measure Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model\u27s predictive performance within the four development studies; external validation followed using the fifth dataset. Results Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R 2: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R 2: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was -1.29 kg (95% confidence interval -1.62 to -0.96 kg). Conclusion The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity

Body-mass index adjustments to increase the validity of body fatness assessment in UK black African and South Asian children: a cross-sectional calibration study

BackgroundExcess childhood body fatness, overweightness, and obesity are a major public health challenge in the UK. Accurate assessments, usually based on body-mass index (BMI), are crucial. However, recent studies have demonstrated that BMI underestimates body fatness in South Asian children and overestimates it in black African children. These errors are a concern in these ethnic minority populations, particularly UK South Asians, who are at high risk of obesity, type 2 diabetes, and cardiovascular disease. We aimed to develop BMI adjustments for these children to ensure that BMI relates to body fatness in the same way as for white European children.MethodsFour recent UK population-based studies, which used deuterium dilution assessments of fat mass as a reference method, were pooled to include 1725 children (52% girls) aged 4–12 years (mean 9·3, SD 1·6) of white European, South Asian, and black African origins. A height-standardised fat-mass index (FMI) was derived to represent body fatness. Linear regression models were fitted, separately by sex, to quantify ethnic differences in BMI–FMI associations and to provide ethnic-specific BMI adjustments.FindingsThe FMI derived for this study population and used in analyses was fat mass/height5, which was independent of height for the 4–12-year age-group. BMI consistently underestimated body fatness in South Asians, requiring a BMI adjustment of +1·12 kg/m2 (95% CI 0·83–1·41) for boys and +1·07 (0·74–1·39) for girls, irrespective of age and FMI. BMI overestimated body fatness in black Africans. However, adjustments for black African children were more complex, with statistically significant interactions between black African ethnicity and FMI (p=0·004 boys, p=0·003 girls) and between FMI and age-group (p\u3c0·0001 boys and girls). BMI adjustments therefore varied by age-group and FMI level, between −0·24 and −2·84 kg/m2 for boys and between −0·22 and −2·86 kg/m2 for girls for unadjusted BMI values of 13 kg/m2 in 10–12 year-olds and 25 kg/m2 in 4–6 year-olds, respectively.InterpretationBMI underestimated body fatness in South Asians and overestimated it in black Africans. Ethnic-specific adjustments—increasing BMI in South Asians and reducing BMI in black Africans—can improve the accuracy of body fatness assessment in these children.FundingThis work was supported by the British Heart Foundation (grant ref PG/15/19/31336) and National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (South London) (grant ref CLAHRC-2013-10022). Primary data collection was funded by the British Heart Foundation (PG/11/42/28895), BUPA Foundation (TBF-S09-019), Child Growth Foundation (GR 10/03), and Wellcome Trust (WT094129MA). MF is supported by Great Ormond Street Hospital Childrens\u27 Charity

The effectiveness of public health interventions to reduce the health impact of climate change:a systematic review of systematic reviews

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases