Would the removal of voluntary iron fortification put vulnerable populations at risk? Modelling the risk of inadequate and excess iron intakes in children in Ireland

Would the removal of voluntary iron fortification put vulnerable populations at risk? Modelling the risk of inadequate and excess iron intakes in children in Ireland | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Would the removal of voluntary iron fortification put vulnerable populations at risk? Modelling the risk of inadequate and excess iron intakes in children in Ireland Laura Kehoe, Janette Walton This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8895504/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Iron is an essential element for human health with natural sources and fortified foods being the main contributors to intakes. In the context of setting safe maximum levels (SML) in food supplements and fortified foods in the EU, it is necessary to understand the current role of fortified foods in the diet and the potential impact of any regulatory changes. This study used three modelling scenarios to investigate the impact of removing voluntary iron fortification of current iron fortified foods on iron intakes in children. Methods Data were based on the Irish National Children’s Food Survey II. The modelling scenarios included 1. Removal of iron from all fortified foods, 2. Removal of iron from fortified foods excluding ready-to-eat cereals (RTEC) and 3. Removal of iron from fortified RTEC only. Usual intakes of iron, the prevalence of inadequate intakes and risk of excess intakes were examined at baseline and for each scenario for the total population and consumers only. Results Removing the iron fortified component from all iron fortified foods/RTEC only significantly increased the prevalence of inadequate intakes of iron from 20% to 50% with significantly higher proportions of females (55–61%) having inadequate intakes compared to males (37–44%). There was negligible risk of excess iron intake at baseline and no further impact from any of the three scenarios. Conclusion This study showed that removing voluntary iron fortification could carry a significant nutritional risk and should be carefully evaluated to ensure the iron status of vulnerable population groups are not adversely affected. Iron fortification voluntary fortification iron intakes children Introduction Iron is an essential element in human health, serving as a crucial cofactor in a wide array of biochemical processes. Beyond its well-established role in blood health through hemoglobin production and oxygen transport, iron is integral to cellular energy production, DNA synthesis, immune function, and the regulation of oxidative stress ( 1 ) . Iron deficiency anaemia (IDA) is recognised as the most common nutritional deficiency globally, affecting over 30% of the population ( 2 ) . While IDA is most prevalent in younger children and women, it is estimated that 9% of school-aged children globally have IDA with prevalence estimates for Europe of 2–3% corresponding to over 2 million children impacted by this nutritional deficiency ( 2 , 3 ) . Across Europe, within national dietary surveys, it has been estimated that 20–40% of school-aged children have low iron intakes and while these low intakes may not consistently correspond to clinical outcomes of IDA, low iron intakes or iron deficiency (with or without anaemia) can contribute to negative health outcomes impacting children’s attention, learning and physical capacity during this crucial period of growth and development ( 4 – 7 ) . The key sources of iron among all ages in Europe (including school-aged children) have been reported as natural sources (e.g. meat & meat dishes, cereal products) and fortified foods including those both voluntarily fortified (e.g. ready-to-eat cereals (RTEC)) and those with mandatory fortification (e.g. bread produced from fortified flour) with minimal contributions from food supplements ( 4 , 5 , 8 , 9 ) . The consumption of fortified foods in particular (both those voluntarily and mandatorily fortified) have been shown to contribute to improved iron intakes among all ages globally with school-aged children often reported amongst the highest consumers of fortified foods in population groups ( 10 – 13 ) . However, balancing the benefits of improved nutrient intakes from fortified foods (or food supplements) with the potential risk of increasing intakes above upper limits is continually at the forefront of public health policy and food safety assessments. Within the European Union (EU), the addition of vitamins and minerals to foods has been regulated through European Commission (EC) regulation No. 1925/2006 since 2007 ( 14 ) . This regulation has provided for the setting of safe maximum levels (SML) of addition of vitamins and minerals to foods and food supplements and while several models for the setting of SML have been proposed, no harmonised SML have yet been implemented at an EU level ( 15 – 19 ) . However, in recent years, the EC has set out to introduce SML for food supplements and fortified foods based on a re-evaluation of tolerable upper daily intakes (ULs) by the European Food Safety Authority (EFSA) ( 20 ) . Preceding the setting of these SML by the EC, some countries have provided their own recommendations at a national level intended as a scientific basis for the discussion of the setting of harmonised SML at the EU level e.g. the German Federal Institute for Risk Assessment (BfR) has updated their recommendations for maximum levels of vitamins and minerals in food supplements and fortified foods in 2021 ( 21 ) . These maximum recommended levels were outlined with the intention to limit nutrient intake from fortified foods and food supplements to ensure a significant additional nutrient intake for those in need, whilst protecting the majority of the population with adequate intakes from an excessive intake. For iron, the BfR has outlined two potential options for the addition of iron to fortified foods which include 1. No addition to any foods or 2. Limit addition to ‘breakfast cereals’ and set a maximum level conforming to current fortification practices. Given the important contribution of fortified foods to current iron intakes among children (and other population groups) it is important to consider the potential impact on iron intakes and adequacy in this vulnerable age group if voluntary addition of iron to fortified foods or the iron levels were to be restricted. The National Children’s Food Survey II (NCFS II), in Ireland has collected detailed data on food consumption of children aged 5–12 years at brand level, allowing for the estimation of nutrient intakes from all dietary sources, natural food sources, added nutrients in foods, and from food supplements ( 4 ) . Similar to findings from other national dietary surveys, RTEC were shown to be important contributors to iron intakes among this age group (up to 30%) which prompts the question of the potential impact on iron intakes for this population group if regulations surrounding fortified foods were to change ( 4 ) . Therefore, the aim of this study was to use the BfR example for iron and add to the evidence base for the discussion of setting SML at an EU level using the NCFS II data as an example. Specifically, this study aimed to investigate the impact of removing voluntary iron fortification of current iron fortified foods on iron intakes, adequacy and excess in children based on three modelling scenarios; 1: removal of iron fortification from all iron fortified foods, 2: removal of iron fortification from all iron fortified foods excluding RTEC and given the important contribution of RTEC to current iron intakes in this population group; 3: removal of iron fortification from RTEC only (excluding all other iron fortified foods). Experimental Methods Study sample Analyses for the present study are based on data from the National Children’s Food Survey II (NCFS II) which was a cross-sectional food consumption survey conducted in the Republic of Ireland in the period 2017-18 by the Irish Universities Nutrition Alliance (IUNA) ( www.iuna.net ) to establish a database of habitual food and beverage consumption in a nationally representative sample of children aged 5–12 years ( n 600) in Ireland. A detailed methodology for the NCFS II has previously been described ( 4 , 22 ) and an overview of the methods relevant to this study is outlined below. Briefly, the data collection phase of the NCFS II was carried out between April 2017 and May 2018, providing a seasonal balance to the data collection. A quota sampling approach was adopted using data from the 2016 Census to achieve a nationally representative sample of 600 children (males: 300, females: 300) ( 23 ) . The study was conducted according to the guidelines laid down in the declaration of Helsinki and all procedures involving human participants were approved by the Clinical Research Ethics Committee of the Cork Teaching Hospitals, University College Cork and the Human Ethics Research Committee of University College Dublin (Ref: ECM 4 (aa) 07/02/17). Written informed consent was obtained from children and their parents/guardians. Demographic analysis of the sample has shown it to be representative of children in Ireland with respect to age-group, sex and geographical location when compared to Census 2016 data ( 23 ) . However, the final sample contained a higher proportion of children of professional workers and a lower proportion of children of semi-skilled and unskilled workers than the national population and all data presented in this manuscript have been weighted to account for these differences. Food and beverage consumption data and estimation of nutrient intakes Food and beverage intake data (including food supplements) were collected at brand level using a 4-day weighed food record. For all participants, the study period included at least one weekend day. Participants were provided with a food diary and a digital food scales (Tanita KD-400, Japan) and asked to record detailed information regarding the amount, type and brand of all foods, beverages and food supplements consumed, as well as the amount of any leftovers. Details of recipes of composite dishes were also recorded. Participants were provided with packaging collection bags to retain the food label packaging of all foods, beverages and food supplements consumed during the recording period. Researchers made three visits to the participant’s home over the survey period: an initial training visit to demonstrate how to complete the food diary and use the weighing scales; a second visit 24–36 hours into the recording period to review the diary and clarify details regarding specific food descriptors and quantities; and a final visit one or two days after the recording period to review the last days of the diary and to collect the food diary and food scales. The majority of foods and beverages were weighed by the participant or their parent/guardian directly on the digital food scales (76%) and a further 11% of weights were derived from manufacturers’ information on product labels. The remaining foods and beverages were quantified using photographic food atlases (7%) (24) , standard portion sizes (3%) (25, 26) , household measures (1%) and estimates based on the child’s previous eating patterns (used only when no other quantification method was appropriate) (2%). For all methods of quantification, leftovers were accounted for, and the weight of the food consumed was calculated. Nutritics© software (Dublin, Ireland) was used to estimate nutrient intakes from food, beverage and food supplement intakes using data from McCance and Widdowson’s The Composition of Foods, seventh edition and sixth edition (for a small number of foods) ( 27 , 28 ) . During the survey, modifications were made to the food composition database to include recipes of composite dishes, food supplements, fortified foods and generic Irish foods that were commonly consumed. All food label packaging collected throughout the survey was photographed to capture information from the ingredient list and nutritional labels. Where packaging was not available in the participant’s home, the researchers located the item in the relevant retail outlet and photographed it. Identification of iron containing food supplements Iron containing food supplements were identified as those that had iron present in the ingredient list. Consumers of iron containing food supplements were defined as those who consumed an iron containing food supplement on any day during the survey period (4 days). Identification of iron fortified foods and their consumers Iron fortified foods were identified as those that had iron present in the ingredient list. Ready-to-eat-cereals (RTEC) were defined as all RTEC including muesli/granola etc. but excluding porridge and hot oat cereals. Consumers of iron fortified foods and consumers of iron fortified RTEC were defined as those who consumed an iron fortified food or an iron fortified RTEC on any day during the survey period. Of the foods fortified with iron in the NCFS II, approximately 66% were RTEC, followed by breakfast/cereal type bars (15%), hot oat cereals (6%), milks and milk based beverages (5%) with the remaining 7% consisting of retail savoury products, biscuits/crackers and composite dishes made with iron fortified ingredients. Identification of the naturally occurring iron in iron fortified foods Natural levels of iron present in iron fortified foods were identified in accordance with previous studies of national dietary surveys in Ireland by obtaining food composition data for an unfortified equivalent of the food or based on data previously provided by manufacturers during the IUNA national dietary surveys ( 27 , 29 – 32 ) . Baseline intakes and modelling scenarios Baseline data reflects the intakes of iron based on actual dietary patterns and food composition as per the NCFS II. The modelling scenarios included: Model 1 (FeFortFoods_all): Removal of iron fortification from all iron fortified foods Model 2 (FeFortFoods_exclRTEC): Removal of iron fortification from all iron fortified foods excluding RTEC Model 3 (FeFortRTEC_exclother): Removal of iron fortification from RTEC only (excluding all other iron fortified foods) Estimation of usual iron intakes Usual intake distributions of iron from all sources (food, beverages and food supplements) and from food sources only (food and beverages, excluding food supplements) at baseline and for each of the three modelling scenarios were estimated for all children aged 5–12 years, for consumers of iron fortified foods and for consumers of iron fortified RTEC using the validated National Cancer Institute (NCI)-method ( 33 ) which accounts for both inter- and intra-person variance. The NCI-method has been implemented in SAS macros (version 2.1) which were downloaded from www.riskfactor.cancer.gov/diet/usualintakes/macro.html (date of download: July 2015). For these analyses, the covariates used were sex (male/female) and age group (5-8y/9-12y). Adequacy of iron intakes The prevalence of inadequate intakes of iron was estimated using the estimated average requirement (EAR) from EFSA as a cut point ( 34 ) . The EAR is the level of (nutrient) intake estimated to meet the requirements of 50% of a population group ( 35 ) . This method has been shown to be effective in obtaining a realistic estimate of the prevalence of dietary inadequacy ( 36 ) . As under-reporting of food consumption can result in an overestimate of the prevalence of inadequacy in a population group ( 37 ) , under-reporters (URs) were identified and excluded from these analyses (19.5% of total sample). URs were identified using Goldberg’s cut-off2 criterion updated by Black (which evaluates the ratio of energy intake to basal metabolic rate (EI:BMR) against age-specific energy cut offs based on physical activity levels) ( 38 – 41 ) . Risk of excessive intake of iron Whilst the risk of excessive intake of micronutrients is typically evaluated using the tolerable upper intake level (UL) (maximum level of total chronic daily intake of a nutrient (from all sources) judged to be unlikely to pose a risk of adverse health effects to humans ( 42 ) ), a recent review of the evidence to establish a UL for iron intakes by EFSA concluded that there was insufficient evidence to establish a UL and instead set a Safe Level of intake (SI) ( 43 ) and the proportion of children with intakes above this SI were calculated within this study. Statistical analysis Statistical analysis was carried out using SPSS© for Windows™ Version 28.0. Differences in intakes of iron between sexes (males, females) were assessed using independent sample t -tests. Differences in intakes of iron between baseline and the modelled scenarios were assessed using paired sample t -tests. Differences in the prevalence of inadequate intakes of iron (proportion of children with intakes below the EAR) between baseline and the modelled scenarios and between sexes (males, females) were assessed using Chi-square tests. To minimise type 1 errors (as a result of multiple testing), the Bonferroni adjustment was used by dividing the alpha level (0.05) by the number of comparisons with intakes considered to be significantly different from each other if p < 0.001 (44) . Results Table 1 presents the distribution of iron intakes (mg), the proportion of the population with intakes below the EAR (excluding energy-under reporters) (%) and the proportion with intakes above the SI (%) from all sources (including food supplements) and food sources only (excluding food supplements) in children aged 5–12 years in Ireland in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified RTEC based on actual intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods as per the three modelling scenarios. The proportion of children consuming any iron fortified food was 82% and the proportion consuming iron fortified RTEC was 78%. Among the total population of children, the mean intake of iron from all sources (including nutritional supplements) at baseline was 9.0 ± 2.4mg with significantly lower intakes observed following all modelling scenarios which restricted iron fortification: FeFortFoods_all (7.0 ± 1.8mg), FeFortFoods_exclRTEC (8.9 ± 2.4mg) and FeFortRTEC_exclother (7.1 ± 1.8mg). Similarly, among consumers of iron fortified foods, the mean intake of iron from all sources was significantly lower in all modelling scenarios: FeFortFoods_all (6.9 ± 1.7mg), FeFortFoods_exclRTEC (9.3 ± 2.4mg) and FeFortRTEC_exclother (7.1 ± 1.7mg) than baseline (9.5 ± 2.3mg) and for consumers of iron fortified RTEC, the mean intake of iron from all sources at baseline was (9.5 ± 2.3mg) with significantly lower intakes observed following all modelling scenarios: FeFortFoods_all (6.9 ± 1.7mg), FeFortFoods_exclRTEC (9.4 ± 2.4mg) and FeFortRTEC_exclother (7.0 ± 1.7mg). As the proportion of children using an iron containing supplement was low (6%; data not shown), similar findings were found for intakes from food sources only (as with all sources) with mean intakes of iron significantly lower in each of the modelling scenarios compared to baseline for the total population of children, consumers of iron fortified foods and consumers of iron fortified RTEC. The proportion of children with iron intakes below the EAR from all sources at baseline was 18.8% and this was significantly higher in FeFortFoods_all (49%), FeFortFoods_exclRTEC (21%) and FeFortRTEC_exclother (46%). Similarly, the proportion of children with iron intakes below the EAR from all sources was significantly higher in each modelling scenario compared to baseline for consumers of iron fortified foods (baseline: 16%, FeFortFoods_all: 52%, FeFortFoods_exclRTEC: 18%, FeFortRTEC_exclother: 49%) and consumers of iron fortified RTEC (baseline: 14%, FeFortFoods_all: 53%, FeFortFoods_exclRTEC: 16%, FeFortRTEC_exclother: 50%). The proportion of children with intakes above the SI from all sources at baseline was negligible (0.2%) but was significantly lower in all three modelling scenarios (< 0.1%, for each) with similar findings among consumers of iron fortified foods and consumers of iron fortified RTEC. Table 2 presents the distribution of iron intakes (mg), the proportion of the population with intakes below the EAR (excluding energy-under reporters) (%) and the proportion with intakes above the SI (%) from all sources (including food supplements) and food sources only in children aged 5–12 years in Ireland, by sex in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified RTEC based on actual intakes (baseline) and after modelling the removal of the iron content fortified component of iron fortified foods as per the three modelling scenarios. At baseline, females had significantly lower mean intakes of iron from all sources compared to males, in the total population (males: 9.8 ± 2.5mg; females: 8.4 ± 2.1mg), among consumers of iron fortified foods (males: 10.2 ± 2.4mg; females: 8.8 ± 2.0mg) and among consumers of iron fortified RTEC (males: 10.2 ± 2.4mg; females: 8.9 ± 2.0mg). Similarly, females had significantly lower intakes of iron from all sources in each modelling scenario and from food sources only at baseline and in each modelling scenario. Significantly higher proportions of females had iron intakes below the EAR from all sources and food sources only at baseline and in each modelling scenario. At baseline up to 25% of females (total population, consumers of iron fortified foods and consumers of iron fortified RTEC) were at risk of inadequate iron intakes compared to up to 12% of males. In FeFortFoods_all, up to 61% of females were at risk of inadequate iron intakes compared to up to 44% of males. In FeFortFoods_exclRTEC, up to 28% of females were at risk of inadequate iron intakes compared to up to 13% of males. In FeFortRTEC_exclother, up to 58% of females were at risk of inadequate iron intakes compared to up to 41% of males. Discussion Given the importance of iron at all stages of the lifecycle and the potential regulatory changes surrounding food fortification, this study aimed to examine the potential impact of removing the iron fortified component of iron fortified foods using three modelling scenarios to provide an evidence base for the discussion of the setting of SML of addition of vitamins and minerals to foods at an EU level. More specifically, this study examined the impact of removing the iron fortified component of all iron fortified foods, all iron fortified foods excluding RTEC or iron fortified RTEC only on the intake of iron in children aged 5–12 years in Ireland including the prevalence of inadequate intakes and risk of excess intakes. The main finding was that removing the iron fortified component from all iron fortified foods or from RTEC only would significantly increase the prevalence of inadequate intakes of iron to approximately one-half of all children compared to current levels (approximately one-fifth) with significantly higher proportions of females (55–61%) having inadequate intakes compared to males (37–44%) in all modelling scenarios. However, removing the iron fortified component from all foods excluding RTEC would have little impact on the prevalence of inadequate intakes in children compared to current levels albeit with significant proportions (approximately one-fifth) remaining with inadequate iron intakes. All scenarios showed negligible risk of iron intakes above the SI. In order to set SML for the fortification of foods with vitamins and minerals, it is essential to understand the current role of fortified foods in the diet and the potential impact of restrictions or changes to the legislation surrounding these foods on intakes and risk of inadequate nutrient intakes in vulnerable population groups ( 19 ) . Furthermore, previously proposed models for the setting of SML have outlined the need to account for all potential sources of nutrient intakes within the diet (natural foods, fortified foods and food supplements) ( 15 – 19 ) . The NCFS II data allowed for this modelling exercise to examine the impact of full restrictions on fortified foods, various models of inclusion of iron fortified foods and for each model to examine the intakes from all sources (all foods and food supplements) and from food sources only (excluding food supplements). Of the scenarios examined in this study, removal of the iron fortified component from all iron fortified foods or from just RTEC would substantially increase the prevalence of inadequate iron intakes in children from approximately one-fifth to up to one half with a significantly higher prevalence amongst females (up to 61%) compared to males (up to 44%). These findings should be carefully considered as presently in Ireland (a country with a long-standing, liberal policy on food fortification), significant proportions of children already have inadequate intakes of iron which may have implications for cognitive and behavioural development at this age ( 4 , 45 ) . Further exacerbation of these high levels of inadequate intakes, particularly for females, would have additional implications for older girls due to the onset of menstruation, which may elevate the risk of low iron stores and IDA ( 4 , 45 ) . While there are no biochemical data of iron status available from the NCFS II, low iron status has been found for counterparts of this age group in the UK with increasing prevalence in teenagers (particularly for females) ( 8 ) . A similar modelling study to ours in the US which examined three scenarios: baseline, zero fortification and optimised fortification for a number of nutrients reported that the optimisation of RTEC fortification could be useful to minimise the proportion of the population with intakes below the EAR for all nutrients including iron across all age groups (1y+) (0% at baseline or optimised fortification compared to 7% for zero fortification) ( 46 ) . In the current study, similar findings were observed across all scenarios whether examining intakes from all dietary sources (including food supplements) or from food sources only (excluding food supplements) which was to be expected given the low prevalence of iron supplement users (6%) thus, it can be observed that iron intakes in this population group are primarily driven by food intake. Similar to our study, a study in the UK examining the contribution of base diet, voluntary fortified foods and supplements to micronutrient intakes found that voluntary fortified foods (but not supplements) made a meaningful contribution to intakes of vitamin and minerals, without the risk of unacceptably high intakes, with fortified foods contributing up to 13% of total iron intake across all ages ( 10 ) . The same study also reported that voluntary fortified foods helped to reduce the prevalence of inadequate intakes for many nutrients including iron reducing the prevalence from 45% from base diet only to approximately 33% from base diet and fortified foods (~ 30% from base diet, fortified foods and supplements) ( 10 ) . Given the increasing emphasis on planetary health, in particular surrounding the advice to reduce the intakes of animal based foods which are important natural sources of iron ( 47 , 48 ) and possible future restrictions in iron levels of voluntary fortified foods the findings of this study indicate that any policy recommendations surrounding changes to the composition of the existing food supply should be carefully considered. At the forefront of setting SML for vitamins and minerals, it is of utmost importance to balance the benefits of improved nutrient intakes from fortified foods (and/or food supplements) with the potential risk of increasing intakes above upper limits/safe intakes. In the current study, each of the modelling scenarios for restricting iron fortification of foods showed negligible risk of iron intakes above the SI which is unsurprising given the negligible risk at baseline based on current dietary patterns among this population group, which has also been reflected in other national dietary survey data of both children and other population groups where the risk of excessive iron intakes are negligible (< 1–3%) based on current dietary patterns across Europe and the developed world ( 49 – 52 ) . While this study examined the impact of removing iron fortification of foods on intakes of iron in school-aged children, the findings may have potential implications for other population groups both in Ireland and globally. National dietary surveys of other population groups in Ireland and across the developed world have consistently shown that (iron fortified) RTEC are key contributors to iron intakes in all age groups ( 53 – 64 ) and a recent systematic review including data from five different countries showed that RTEC provided up to 28% of daily iron intakes in the total population across all ages and from 32–51% of daily iron intake in RTEC consumers only ( 56 ) . Any change to regulations around fortification of foods could have implications not only for iron but for other nutrients that are routinely added to RTEC or other nutrients which are largely obtained from fortified foods (e.g. vitamin D, folic acid) ( 56 ) . Strengths and limitations The key strengths of this study include the nationally representative sample of children aged 5–12 years included in the NCFS II and the comprehensive dietary intake and food composition data (including brand level detail) which allowed for the estimation of naturally occurring and added iron in foods. Another important strength is the use of statistical modelling to estimate usual intakes of iron, resulting in a better estimate of the true distribution of usual intakes therefore improving the estimates of the proportions of the population with intakes above or below a particular reference value (e.g. EAR or SI) which would otherwise be overestimated. Misreporting or under reporting of food (energy) intake, is a known limitation with all dietary assessment; this issue was minimised by a high level of researcher-participant interaction (3–4 visits over the recording period). Additionally, the removal of URs from estimates of the prevalence of inadequacy provides a better representation of the scale of nutrient inadequacy. Conclusion In summary, this study has shown that that removing the iron fortified component from all iron fortified foods or from RTEC only would significantly increase the prevalence of inadequate intakes of iron to approximately one-half compared to current levels (approximately one-fifth) with significantly higher proportions of females (55–61%) having inadequate intakes compared to males (37–44%) in all modelling scenarios. This study used iron as an example to investigate the potential impact and unintended consequences of removing fortification from specific foods and serves as a scientific basis to support discussions surrounding the setting SML of vitamins and minerals at an EU level. Beyond the setting of SML at an EU level, in light of evolving dietary patterns driven by planetary health concerns, continual monitoring of dietary intakes from natural food sources, fortified foods and supplements is essential to ensure the nutritional status (including iron) of all population groups are not adversely affected and to inform appropriate public health strategies where necessary. Declarations Competing Interests JW and LK were paid a fee from the Ceereal asbl for the production of this manuscript. Ceereal asbl had no role in the design, analysis or writing of this manuscript. Funding: The National Children’s Food Survey II (NCFS II) was funded by the Irish Department of Agriculture, Food and the Marine (DAFM) under the 2015 Food Institutional Research Measure (FIRM) awards and this research was funded by Ceereal asbl. Author Contribution LK and JW contributed to the conception, design and execution of the study. LK carried out the data analyses and wrote the first draft. Both authors contributed to the writing of the final manuscript. Data Availability The data presented in this study are available from the corresponding author upon reasonable request. References Obeagu EI (2025) Iron homeostasis and health: understanding its role beyond blood health - a narrative review. Annals of medicine and surgery (2012) 87, 3362–3371 World Health Organisation (WHO) (2025) Anaemia Fact Sheet. https://www.who.int/news-room/fact-sheets/detail/anaemia (accessed 1st January 2025) Sukwuttichai P, Tidwong N, Chaipichit N et al (2026) Global prevalence of iron deficiency anaemia among children aged 5–12 years: a systematic review and meta-analysis. J global health 16:04027 Kehoe L, Buffini M, McNulty B et al (2022) Food and nutrient intakes and compliance with recommendations in school-aged children in Ireland: Findings from the National Children's Food Survey II (2017-18) and changes since 2003-04. British Journal of Nutrition Under review Samaniego-Vaesken ML, Partearroyo T, Olza J et al (2017) Iron Intake and Dietary Sources in the Spanish Population: Findings from the ANIBES Study. Nutrients 9:203 Stahl A, Vohmann C, Richter A et al (2009) Changes in food and nutrient intake of 6- to 17-year-old Germans between the 1980s and 2006. Public Health Nutr 12:1912–1923 Bates B, Collins D, Cox L et al (2019) National Diet and Nutrition Survey: Years 1 to 9 of the Rolling Programme (2008-2009-2016/2017): Time trend and income analyses . https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/772434/NDNS_UK_Y1-9_report.pdf : Food Standards Agency and the Department of Health Bates B, Collins D, Jones K et al (2020) National Diet and Nutrition Survey: Rolling programme Years 9 to 11 (2016/2017 to 2018/2019) . https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/943114/NDNS_UK_Y9-11_report.pdf : Food Standards Agency and the Department of Health Lopes C, Torres D, Oliveira A et al (2017) National Food and Physical Activity Survey (IAN-AF) Part II. University of Porto, Portugal. http://ciafel.fade.up.pt/modules/file_repository/data/Site/relatorio_resultados_ian_af.pdf Bird JK, Barron R, Pigat S et al (2022) Contribution of base diet, voluntary fortified foods and supplements to micronutrient intakes in the UK. J Nutr Sci 11:e51 Berner LA, Keast DR, Bailey RL et al (2014) Fortified Foods Are Major Contributors to Nutrient Intakes in Diets of US Children and Adolescents. J Acad Nutr Dietetics 114:1009–1022e1008 de Jong MH, Nawijn EL, Verkaik-Kloosterman J (2022) Contribution of voluntary fortified foods to micronutrient intake in The Netherlands. Eur J Nutr 61:1649–1663 Walsh N, Walton J, Buffini M et al (2021) Characterising the fortified foods consumed by school-aged children (5–12y) in Ireland. Proceedings of the Nutrition Society 80, E174 EC (2006) Regulation (EC) 1925/2006 of the European Parliament and of the Council of 20 December 2006. Official J Eur Union L404:26–38 Flynn A, Moreiras O, Stehle P et al (2003) Vitamins and minerals: a model for safe addition to foods. Eur J Nutr 42:118–130 Kloosterman J, Fransen HP, de Stoppelaar J et al (2007) Safe addition of vitamins and minerals to foods: setting maximum levels for fortification in the Netherlands. Eur J Nutr 46:220–229 Rasmussen SE, Andersen NL, Dragsted LO et al (2006) A safe strategy for addition of vitamins and minerals to foods. Eur J Nutr 45:123–135 Dufour A, Wetzler S, Touvier M et al (2010) Comparison of different maximum safe levels in fortified foods and supplements using a probabilistic risk assessment approach. Br J Nutr 104:1848–1857 Flynn A, Kehoe L, Hennessy Á et al (2016) Estimating safe maximum levels of vitamins and minerals in fortified foods and food supplements. Eur J Nutr, 1–11 Eurofins (2025) Update: Planned EU maximum levels for vitamins, minerals and trace elements. https://www.eurofins.de/food-analysis/food-news/food-testing-news/planned-eu-maximum-levels-for-vitamins-minerals-and-trace-elements/ BfR (2021) Updated recommended maximum levels for the addition of vitamins and minerals to food supplements and conventional foods. wwwbfrbundde Irish Universities Nutrition Alliance (IUNA) (2020) The National Children's Food Survey II (NCFS II) Main Report . https://www.iuna.net/surveyreports Central Statistics Office (2017) Census 2016 Summary Results - Part 1. Central Statistics Office, Dublin, Ireland Foster E, Hawkins A, Adamson A (2010) Young Person's Food Atlas: Primary School. Food Standards Agency, London Ministry of Agriculture Fisheries and Food (1997) Food Portion Sizes. The Stationary Office, London Lyons J, Giltinan M (2013) The Irish Food Portion Sizes Database, First Edition. www.iuna.net Public Health England (2015) McCance and Widdowson's The Composition of Foods, 7th edn. Royal Society of Chemistry, Cambridge Food Standards Agency (2002) McCance and Widdowson's The Composition of Foods, 6th edn. Royal Society of Chemistry, Cambridge Black LJ, Walton J, Flynn A et al (2014) Adequacy of vitamin D intakes in children and teenagers from the base diet, fortified foods and supplements. Public Health Nutr 17:721–731 Hennessy Á, Browne F, Kiely M et al (2016) The role of fortified foods and nutritional supplements in increasing vitamin D intake in Irish preschool children. Eur J Nutr, 1–13 Hennessy Á, Hannon EM, Walton J et al (2015) Impact of voluntary food fortification practices in Ireland: trends in nutrient intakes in Irish adults between 1997–9 and 2008–10. Br J Nutr 113:310–320 Hopkins SM, Gibney MJ, Nugent AP et al (2015) Impact of voluntary fortification and supplement use on dietary intakes and biomarker status of folate and vitamin B-12 in Irish adults. Am J Clin Nutr 101:1163–1172 Tooze JA, Kipnis V, Buckman DW et al (2010) A mixed-effects model approach for estimating the distribution of usual intake of nutrients: The NCI method. Stat Med 29:2857–2868 EFSA Panel on Dietetic Products Nutrition and Allergies (2015) Scientific Opinion on Dietary Reference Values for iron. EFSA J 13:4254 EFSA Panel on Dietetic Products Nutrition and Allergies (2010) Scientific Opinion on principles for deriving and applying Dietary Reference Values. EFSA J 8:1458 de Lauzon B, Volatier J, Martin A (2004) A Monte Carlo simulation to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level. Public Health Nutr 7:893–900 Carriquiry AL (1999) Assessing the prevalence of nutrient inadequacy. Public Health Nutr 2:23–34 Goldberg G, Black A, Jebb S et al (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45:569–581 Black AE (2000) Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes 24:1119–1130 Schofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutrition: Clin Nutr 39C:5–41 European Food Safety Authority (2017) Dietary Reference Values for nutrients Summary report. EFSA Supporting Publications 14:e15121E EFSA Panel on Dietetic Products Nutrition and Allergies (2006) Tolerable Upper Intake Levels for Vitamins and Minerals. EFSA J EFSA Panel on Nutrition NF, Allergens F, Turck D et al (2024) Scientific opinion on the tolerable upper intake level for iron. EFSA J 22:e8819 Fagerland MW (2012) t-tests, non-parametric tests, and large studies—a paradox of statistical practice? BMC Med Res Methodol 12:78 Moschonis G, Papandreou D, Mavrogianni C et al (2013) Association of Iron Depletion with Menstruation and Dietary Intake Indices in Pubertal Girls: The Healthy Growth Study. BioMed Research International 2013, 423263 Smith JD, Jain N, Bailey RL (2020) Ready-to-eat cereal fortification: a modelling study on the impact of changing ready-to-eat cereal fortification levels on population intake of nutrients. Public Health Nutr 23:2165–2178 Willett W, Rockström J, Loken B et al (2019) Food in the Anthropocene: the EAT Lancet Commission on healthy diets from sustainable food systems. Lancet 393:447–492 Rockström J, Thilsted SH, Willett WC et al (2025) The EAT Lancet Commission on healthy, sustainable, and just food systems. Lancet 406:1625–1700 Irish Universities Nutrition Alliance (IUNA) (2024) The National Adult Nutrition Survey II (NANS II) Main Report. https://www.iuna.net/surveyreports Irish Universities Nutrition Alliance (IUNA) (2021) The National Teens' Food Survey II (NTFS II) Main Report . https://www.iuna.net/surveyreports Bird JK, Bruins MJ, Turini ME (2023) Micronutrient intakes in the Dutch diet: foods, fortified foods and supplements in a cross sectional study. Eur J Nutr 62:3161–3179 Bailey ADL, Miketinas DC, London HE et al (2026) Usual Nutrient Intake Adequacy and Nutritional Status of US Children and Adolescents: NHANES 2001 -March 2020. J Nutr Irish Universities Nutrition Alliance (2012) National Pre-School Nutrition Survey. Summary Report. Cork: IUNA, www.iuna.net Irish Universities Nutrition Alliance (IUNA) (2021) The National Teens' Food Survey II (NTFS II) Summary Report. IUNA, Cork. https://www.iuna.net/surveyreports Irish Universities Nutrition Alliance (IUNA) (2024) The Adult Nutrition Survey II (NANS II) Summary Report. IUNA, Cork. https://www.iuna.net/surveyreports Derbyshire EJ, Ruxton CHS (2025) A Systematic Review of Evidence on the Role of Ready-to-Eat Cereals in Diet and Non-Communicable Disease Prevention. Nutrients 17:1680 Sanders LM, Zhu Y, Jain N et al (2023) Ready-to-eat cereal consumption is associated with improved nutrient intakes and diet quality in Canadian adults and children across income levels. Front Nutr 10:1282252 Smith JD, Zhu Y, Vanage V et al (2019) Association between Ready-to-Eat Cereal Consumption and Nutrient Intake, Nutritional Adequacy, and Diet Quality among Infants, Toddlers, and Children in the National Health and Nutrition Examination Survey 2015–2016. Nutrients 11, 1989 Powers HJ, Stephens M, Russell J et al (2016) Fortified breakfast cereal consumed daily for 12 wk leads to a significant improvement in micronutrient intake and micronutrient status in adolescent girls: a randomised controlled trial. Nutr J 15:69 Smith J, Jain N, Normington J et al (2022) Associations of Ready-to-Eat Cereal Consumption and Income With Dietary Outcomes: Results From the National Health and Nutrition Examination Survey 2015–2018. Front Nutr 9:816548 Michels N, De Henauw S, Breidenassel C et al (2015) European adolescent ready-to-eat-cereal (RTEC) consumers have a healthier dietary intake and body composition compared with non-RTEC consumers. Eur J Nutr 54:653–664 Sanders LM, Dicklin MR, Zhu Y et al (2023) The Impact of Ready-to-Eat Cereal Intake on Body Weight and Body Composition in Children and Adolescents: A Systematic Review of Observational Studies and Controlled Trials. Adv Nutr 14:161–172 Michels N, De Henauw S, Beghin L et al (2016) Ready-to-eat cereals improve nutrient, milk and fruit intake at breakfast in European adolescents. Eur J Nutr 55:771–779 Fayet-Moore F, McConnell A, Cassettari T et al (2019) Breakfast Choice Is Associated with Nutrient, Food Group and Discretionary Intakes in Australian Adults at Both Breakfast and the Rest of the Day. Nutrients 11 Tables Table 1 Distribution of iron intakes (mg), the proportion of the population with intakes below the Estimated Average Requirement (EAR)(34) (excluding energy-under reporters‡) (%) and the proportion with intakes above the Safe Level of Intake (SI)(43) (%) from all sources† (including food supplements) and food sources† only (excluding food supplements) in children aged 5–12 years in Ireland in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified ready-to-eat-cereal (RTEC) based on current intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods per the three modelling scenarios Baseline (actual) Model 1 (Removal of iron from all foods) Model 2 (Removal of iron from all foods excluding RTEC) Model 3 (Removal of iron from RTEC only) All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC n 600 n 493 n 466 n 600 n 493 n 466 n 600 n 493 n 466 n 600 n 493 n 466 mg/d All sources † Mean 9.0 9.5 9.5 7.0* 6.9* 6.9* 8.9* 9.3* 9.4* 7.1* 7.1* 7.0* SD 2.4 2.3 2.3 1.8 1.7 1.7 2.4 2.4 2.3 1.8 1.7 1.7 P5 5.5 6.1 6.2 4.4 4.4 4.5 5.4 5.9 6.0 4.6 4.6 4.6 P25 7.3 7.8 7.9 5.7 5.7 5.7 7.2 7.6 7.7 5.8 5.9 5.8 P50 8.8 9.2 9.3 6.8 6.7 6.7 8.6 9.0 9.1 6.9 6.9 6.8 P75 10.5 10.9 10.9 8.0 7.9 7.9 10.3 10.7 10.7 8.2 8.1 8.0 P95 13.5 13.7 13.6 10.2 10.0 9.9 13.3 13.5 13.5 10.4 10.2 10.0 % %SI (43) 0.2 0.2 0.2 0.0* 0.0* 0.0* 0.1* 0.2* 0.1* 0.0* 0.0* 0.0* mg/d Food sources † Mean 8.8 9.2 9.2 6.7* 6.6* 6.6* 8.6* 9.0* 9.1* 6.8* 6.8* 6.8* SD 2.2 2.1 2.1 1.5 1.4 1.4 2.2 2.2 2.1 1.5 1.4 1.4 Median 8.5 9.0 9.0 6.6 6.5 6.5 8.4 8.8 8.9 6.7 6.7 6.6 P25 7.2 7.7 7.8 5.7 5.6 5.6 7.0 7.5 7.6 5.8 5.8 5.8 P75 10.1 10.5 10.5 7.6 7.5 7.4 9.9 10.3 10.4 7.8 7.7 7.6 P5 5.5 6.1 6.2 4.6 4.6 4.6 5.4 5.9 6.1 4.7 4.7 4.7 P95 12.8 13.0 13.0 9.3 9.2 9.1 12.6 12.9 12.9 9.5 9.4 9.2 % %SI (43) 0.1 0.1 0.1 0.0* 0.0* 0.0 0.0* 0.1* 0.0* 0.0* 0.0* 0.0* Abbreviations: RTEC, ready-to-eat cereal; M, males; F, females; mg, milligram; d, day; %, percentage; SD, standard deviation; P, percentile; , above; SI, safe level of intake Note: All includes non-consumers and consumers of any iron fortified food; Consumers of iron fortified foods were defined as any participant who consumed an iron fortified food at least once over the 4-day recording period; Consumers of iron fortified RTEC were defined as any participant who consumed an iron fortified RTEC at least once over the 4-day recording period † All sources refers to all sources including foods and food supplements; Food sources refers to food sources only (excludes food supplements) * Statistically different ( p < 0.001) from intake at baseline via paired samples t -tests and adjusted for multiple testing EAR: EFSA, 2015 ( 34 ) ; 5-6y (5mg/d), 7-11y (8mg/d), 12y males (8mg/d), 12y females (7mg/d), ‡ Excludes energy-under reporters (19.5%) SI: EFSA, 2024 ( 43 ) ; 5-6y (15mg/d), 7-10y (20mg/d), 11-12y (30mg/d) Table 2 Distribution of iron intakes (mg), the proportion of the population with intakes below the Estimated Average Requirement (EAR)(34) (excluding energy-under reporters‡) (%) and the proportion with intakes above the Safe Level of Intake (SI)(43) (%) from all sources† (including food supplements) and food sources† only (excluding food supplements) in children aged 5–12 years in Ireland, by sex in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified ready-to-eat-cereal (RTEC) based on current intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods per the three modelling scenarios Baseline (actual) Model 1 (Removal of iron from all foods) Model 2 (Removal of iron from all foods excluding RTEC) Model 3 (Removal of iron from RTEC only) All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC All Consumers of iron fortified foods Consumers of iron fortified RTEC M F M F M F M F M F M F M F M F M F M F M F M F n 300 n 300 n 244 n 249 n 230 n 236 n 300 n 300 n 244 n 249 n 230 n 236 n 300 n 300 n 244 n 249 n 230 n 236 n 300 n 300 n 244 n 249 n 230 n 236 mg/d All sources † Mean 9.8 8.4* 10.2 8.8* 10.2 8.9* 7.5 6.5* 7.4 6.4* 7.3 6.4* 9.6 8.2* 10.0 8.6* 10.1 8.7* 7.7 6.6* 7.6 6.6* 7.5 6.6* SD 2.5 2.1 2.4 2.0 2.4 2.0 1.9 1.5 1.8 1.5 1.8 1.4 2.5 2.1 2.5 2.0 2.4 2.0 1.9 1.5 1.8 1.5 1.8 1.5 P5 6.1 5.2 6.6 5.8 6.6 5.9 4.8 4.2 4.8 4.2 4.8 4.3 5.9 5.1 6.3 5.6 6.5 5.8 5.0 4.3 4.9 4.4 4.9 4.4 P25 8.0 6.8 8.5 7.4 8.5 7.5 6.2 5.4 6.1 5.4 6.1 5.4 7.8 6.7 8.2 7.2 8.3 7.3 6.4 5.5 6.3 5.5 6.2 5.6 P50 9.6 8.2 10.0 8.6 10.0 8.7 7.3 6.3 7.2 6.3 7.1 6.3 9.4 8.0 9.8 8.4 9.8 8.6 7.5 6.5 7.5 6.5 7.3 6.5 P75 11.3 9.7 11.7 10.0 11.7 10.1 8.7 7.4 8.6 7.3 8.4 7.3 11.2 9.5 11.6 9.8 11.6 10.0 8.8 7.5 8.7 7.5 8.6 7.5 P95 14.3 12.2 14.6 12.3 14.5 12.4 10.8 9.2 10.7 9.0 10.5 9.0 14.1 12.0 14.5 12.1 14.4 12.2 11.0 9.4 10.9 9.2 10.6 9.2 % %SI (43) 0.3 0.1* 0.3 0.1* 0.3 0.1* 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.1* 0.3 0.0* 0.2 0.0* 0.0 0.0 0.0 0.0 0.0 0.0 mg/d Food sources † Mean 9.4 8.2* 9.8 8.6* 9.9 8.7* 7.2 6.3* 7.1 6.2* 7.0 6.2* 9.3 8.0* 9.6 8.4* 9.7 8.5* 7.3 6.4* 7.3 6.4* 7.1 6.4* SD 2.3 1.9 2.3 1.8 2.2 1.8 1.5 1.2 1.5 1.2 1.4 1.2 2.3 1.9 2.3 1.8 2.2 1.8 1.5 1.3 1.5 1.2 1.4 1.2 Median 9.2 8.0 9.6 8.5 9.7 8.5 7.0 6.2 6.9 6.1 6.8 6.1 9.1 7.8 9.4 8.3 9.5 8.4 7.2 6.3 7.1 6.3 7.0 6.3 P25 7.8 6.8 8.2 7.3 8.3 7.4 6.1 5.4 6.0 5.4 5.9 5.4 7.6 6.6 8.0 7.1 8.1 7.3 6.2 5.5 6.2 5.5 6.1 5.6 P75 10.8 9.3 11.3 9.8 11.2 9.8 8.1 7.0 8.0 7.0 7.9 7.0 10.7 9.2 11.1 9.6 11.1 9.7 8.3 7.2 8.2 7.2 8.1 7.1 P5 6.0 5.3 6.5 5.8 6.6 5.9 4.9 4.4 4.8 4.4 4.8 4.5 5.9 5.2 6.2 5.6 6.4 5.8 5.0 4.5 5.0 4.5 5.0 4.6 P95 13.5 11.6 13.9 11.8 13.8 11.9 9.9 8.4 9.8 8.3 9.6 8.3 13.4 11.4 13.8 11.6 13.6 11.7 10.1 8.6 10.0 8.6 9.7 8.5 % %SI (43) 0.1 0.0* 0.1 0.0* 0.1 0.0* 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0* 0.1 0.0* 0.1 0.0* 0.0 0.0 0.0 0.0 0.0 0.0 Abbreviations: RTEC, ready-to-eat cereal; M, males; F, females; mg, milligram; d, day; %, percentage; SD, standard deviation; P, percentile; , above; SI, safe level of intake Note: All includes non-consumers and consumers of any iron fortified food; Consumers of iron fortified foods were defined as any participant who consumed an iron fortified food at least once over the 4-day recording period; Consumers of iron fortified RTEC were defined as any participant who consumed an iron fortified RTEC at least once over the 4-day recording period † All sources refers to all sources including foods and food supplements; Food sources refers to food sources only (excludes food supplements) * Statistically different ( p < 0.001) from that of males within each scenario via independent samples t -tests and adjusted for multiple testing EAR: EFSA, 2015 ( 34 ) ; 5-6y (5mg/d), 7-11y (8mg/d), 12y males (8mg/d), 12y females (7mg/d), ‡ Excludes energy-under reporters (19.5%) SI: EFSA, 2024 ( 43 ) ; 5-6y (15mg/d), 7-10y (20mg/d), 11-12y (30mg/d) Additional Declarations Competing interest reported. JW and LK were paid a fee from the Ceereal asbl for the production of this manuscript. Ceereal asbl had no role in the design, analysis or writing of this manuscript. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8895504","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599465999,"identity":"bf3091fb-9951-4025-992c-de45469a66b0","order_by":0,"name":"Laura Kehoe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBACPgiVwGDAwMD4AMRkI6SFDUkLswGQJk0LmwRIC0HAxn7G7MMPhjQ5c/bmY1U3fxxm4GNvIKCFJ8d4Zg9DjrFlz7G02zkJh4EiBwg5LMeYgYehInHDjRwziBYJAq5j439jzPiHoaJ+w438b8VgLfIPCGiRyDFm5mHISTC4kcPGDLEFvw6ggmfFzDIGaYYbzhwzls5JS+dh4yHgMH7+5M2MbyqS5Q2ONz/8nGNjLSfffoCANWBggGDyEKN+FIyCUTAKRgEBAADstTg6agl3fwAAAABJRU5ErkJggg==","orcid":"","institution":"Munster Technological University","correspondingAuthor":true,"prefix":"","firstName":"Laura","middleName":"","lastName":"Kehoe","suffix":""},{"id":599466000,"identity":"74812dc1-fe92-42de-9da2-174a6d4f3dab","order_by":1,"name":"Janette Walton","email":"","orcid":"","institution":"Munster Technological University","correspondingAuthor":false,"prefix":"","firstName":"Janette","middleName":"","lastName":"Walton","suffix":""}],"badges":[],"createdAt":"2026-02-16 19:08:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8895504/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8895504/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108491831,"identity":"016dc2e2-81cc-4769-893d-0c668436edb3","added_by":"auto","created_at":"2026-05-05 09:55:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":761639,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8895504/v1/a0286400-a117-47c5-82cc-3aeaae48d56a.pdf"}],"financialInterests":"Competing interest reported. JW and LK were paid a fee from the Ceereal asbl for the production of this manuscript. Ceereal asbl had no role in the design, analysis or writing of this manuscript.","formattedTitle":"Would the removal of voluntary iron fortification put vulnerable populations at risk? Modelling the risk of inadequate and excess iron intakes in children in Ireland","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIron is an essential element in human health, serving as a crucial cofactor in a wide array of biochemical processes. Beyond its well-established role in blood health through hemoglobin production and oxygen transport, iron is integral to cellular energy production, DNA synthesis, immune function, and the regulation of oxidative stress\u003csup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/sup\u003e. Iron deficiency anaemia (IDA) is recognised as the most common nutritional deficiency globally, affecting over 30% of the population\u003csup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/sup\u003e. While IDA is most prevalent in younger children and women, it is estimated that 9% of school-aged children globally have IDA with prevalence estimates for Europe of 2\u0026ndash;3% corresponding to over 2\u0026nbsp;million children impacted by this nutritional deficiency\u003csup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAcross Europe, within national dietary surveys, it has been estimated that 20\u0026ndash;40% of school-aged children have low iron intakes and while these low intakes may not consistently correspond to clinical outcomes of IDA, low iron intakes or iron deficiency (with or without anaemia) can contribute to negative health outcomes impacting children\u0026rsquo;s attention, learning and physical capacity during this crucial period of growth and development\u003csup\u003e(\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/sup\u003e. The key sources of iron among all ages in Europe (including school-aged children) have been reported as natural sources (e.g. meat \u0026amp; meat dishes, cereal products) and fortified foods including those both voluntarily fortified (e.g. ready-to-eat cereals (RTEC)) and those with mandatory fortification (e.g. bread produced from fortified flour) with minimal contributions from food supplements\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/sup\u003e. The consumption of fortified foods in particular (both those voluntarily and mandatorily fortified) have been shown to contribute to improved iron intakes among all ages globally with school-aged children often reported amongst the highest consumers of fortified foods in population groups\u003csup\u003e(\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/sup\u003e. However, balancing the benefits of improved nutrient intakes from fortified foods (or food supplements) with the potential risk of increasing intakes above upper limits is continually at the forefront of public health policy and food safety assessments.\u003c/p\u003e \u003cp\u003eWithin the European Union (EU), the addition of vitamins and minerals to foods has been regulated through European Commission (EC) regulation No. 1925/2006 since 2007\u003csup\u003e(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/sup\u003e. This regulation has provided for the setting of safe maximum levels (SML) of addition of vitamins and minerals to foods and food supplements and while several models for the setting of SML have been proposed, no harmonised SML have yet been implemented at an EU level\u003csup\u003e(\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/sup\u003e. However, in recent years, the EC has set out to introduce SML for food supplements and fortified foods based on a re-evaluation of tolerable upper daily intakes (ULs) by the European Food Safety Authority (EFSA)\u003csup\u003e(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/sup\u003e. Preceding the setting of these SML by the EC, some countries have provided their own recommendations at a national level intended as a scientific basis for the discussion of the setting of harmonised SML at the EU level e.g. the German Federal Institute for Risk Assessment (BfR) has updated their recommendations for maximum levels of vitamins and minerals in food supplements and fortified foods in 2021\u003csup\u003e(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/sup\u003e. These maximum recommended levels were outlined with the intention to limit nutrient intake from fortified foods and food supplements to ensure a significant additional nutrient intake for those in need, whilst protecting the majority of the population with adequate intakes from an excessive intake. For iron, the BfR has outlined two potential options for the addition of iron to fortified foods which include 1. No addition to any foods or 2. Limit addition to \u0026lsquo;breakfast cereals\u0026rsquo; and set a maximum level conforming to current fortification practices.\u003c/p\u003e \u003cp\u003eGiven the important contribution of fortified foods to current iron intakes among children (and other population groups) it is important to consider the potential impact on iron intakes and adequacy in this vulnerable age group if voluntary addition of iron to fortified foods or the iron levels were to be restricted. The National Children\u0026rsquo;s Food Survey II (NCFS II), in Ireland has collected detailed data on food consumption of children aged 5\u0026ndash;12 years at brand level, allowing for the estimation of nutrient intakes from all dietary sources, natural food sources, added nutrients in foods, and from food supplements\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/sup\u003e. Similar to findings from other national dietary surveys, RTEC were shown to be important contributors to iron intakes among this age group (up to 30%) which prompts the question of the potential impact on iron intakes for this population group if regulations surrounding fortified foods were to change\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study was to use the BfR example for iron and add to the evidence base for the discussion of setting SML at an EU level using the NCFS II data as an example. Specifically, this study aimed to investigate the impact of removing voluntary iron fortification of current iron fortified foods on iron intakes, adequacy and excess in children based on three modelling scenarios; 1: removal of iron fortification from all iron fortified foods, 2: removal of iron fortification from all iron fortified foods excluding RTEC and given the important contribution of RTEC to current iron intakes in this population group; 3: removal of iron fortification from RTEC only (excluding all other iron fortified foods).\u003c/p\u003e"},{"header":"Experimental Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy sample\u003c/h2\u003e \u003cp\u003eAnalyses for the present study are based on data from the National Children\u0026rsquo;s Food Survey II (NCFS II) which was a cross-sectional food consumption survey conducted in the Republic of Ireland in the period 2017-18 by the Irish Universities Nutrition Alliance (IUNA) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.iuna.net\u003c/span\u003e\u003cspan address=\"http://www.iuna.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to establish a database of habitual food and beverage consumption in a nationally representative sample of children aged 5\u0026ndash;12 years (\u003cem\u003en\u003c/em\u003e 600) in Ireland. A detailed methodology for the NCFS II has previously been described\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/sup\u003e and an overview of the methods relevant to this study is outlined below.\u003c/p\u003e \u003cp\u003eBriefly, the data collection phase of the NCFS II was carried out between April 2017 and May 2018, providing a seasonal balance to the data collection. A quota sampling approach was adopted using data from the 2016 Census to achieve a nationally representative sample of 600 children (males: 300, females: 300)\u003csup\u003e(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/sup\u003e. The study was conducted according to the guidelines laid down in the declaration of Helsinki and all procedures involving human participants were approved by the Clinical Research Ethics Committee of the Cork Teaching Hospitals, University College Cork and the Human Ethics Research Committee of University College Dublin (Ref: ECM 4 (aa) 07/02/17). Written informed consent was obtained from children and their parents/guardians. Demographic analysis of the sample has shown it to be representative of children in Ireland with respect to age-group, sex and geographical location when compared to Census 2016 data\u003csup\u003e(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/sup\u003e. However, the final sample contained a higher proportion of children of professional workers and a lower proportion of children of semi-skilled and unskilled workers than the national population and all data presented in this manuscript have been weighted to account for these differences.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFood and beverage consumption data and estimation of nutrient intakes\u003c/h3\u003e\n\u003cp\u003eFood and beverage intake data (including food supplements) were collected at brand level using a 4-day weighed food record. For all participants, the study period included at least one weekend day. Participants were provided with a food diary and a digital food scales (Tanita KD-400, Japan) and asked to record detailed information regarding the amount, type and brand of all foods, beverages and food supplements consumed, as well as the amount of any leftovers. Details of recipes of composite dishes were also recorded. Participants were provided with packaging collection bags to retain the food label packaging of all foods, beverages and food supplements consumed during the recording period. Researchers made three visits to the participant\u0026rsquo;s home over the survey period: an initial training visit to demonstrate how to complete the food diary and use the weighing scales; a second visit 24\u0026ndash;36 hours into the recording period to review the diary and clarify details regarding specific food descriptors and quantities; and a final visit one or two days after the recording period to review the last days of the diary and to collect the food diary and food scales.\u003c/p\u003e \u003cp\u003eThe majority of foods and beverages were weighed by the participant or their parent/guardian directly on the digital food scales (76%) and a further 11% of weights were derived from manufacturers\u0026rsquo; information on product labels. The remaining foods and beverages were quantified using photographic food atlases (7%)\u003csup\u003e(24)\u003c/sup\u003e, standard portion sizes (3%)\u003csup\u003e(25, 26)\u003c/sup\u003e, household measures (1%) and estimates based on the child\u0026rsquo;s previous eating patterns (used only when no other quantification method was appropriate) (2%). For all methods of quantification, leftovers were accounted for, and the weight of the food consumed was calculated.\u003c/p\u003e \u003cp\u003eNutritics\u0026copy; software (Dublin, Ireland) was used to estimate nutrient intakes from food, beverage and food supplement intakes using data from McCance and Widdowson\u0026rsquo;s The Composition of Foods, seventh edition and sixth edition (for a small number of foods)\u003csup\u003e(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/sup\u003e. During the survey, modifications were made to the food composition database to include recipes of composite dishes, food supplements, fortified foods and generic Irish foods that were commonly consumed. All food label packaging collected throughout the survey was photographed to capture information from the ingredient list and nutritional labels. Where packaging was not available in the participant\u0026rsquo;s home, the researchers located the item in the relevant retail outlet and photographed it.\u003c/p\u003e\n\u003ch3\u003eIdentification of iron containing food supplements\u003c/h3\u003e\n\u003cp\u003eIron containing food supplements were identified as those that had iron present in the ingredient list. Consumers of iron containing food supplements were defined as those who consumed an iron containing food supplement on any day during the survey period (4 days).\u003c/p\u003e\n\u003ch3\u003eIdentification of iron fortified foods and their consumers\u003c/h3\u003e\n\u003cp\u003eIron fortified foods were identified as those that had iron present in the ingredient list. Ready-to-eat-cereals (RTEC) were defined as all RTEC including muesli/granola etc. but excluding porridge and hot oat cereals. Consumers of iron fortified foods and consumers of iron fortified RTEC were defined as those who consumed an iron fortified food or an iron fortified RTEC on any day during the survey period. Of the foods fortified with iron in the NCFS II, approximately 66% were RTEC, followed by breakfast/cereal type bars (15%), hot oat cereals (6%), milks and milk based beverages (5%) with the remaining 7% consisting of retail savoury products, biscuits/crackers and composite dishes made with iron fortified ingredients.\u003c/p\u003e\n\u003ch3\u003eIdentification of the naturally occurring iron in iron fortified foods\u003c/h3\u003e\n\u003cp\u003eNatural levels of iron present in iron fortified foods were identified in accordance with previous studies of national dietary surveys in Ireland by obtaining food composition data for an unfortified equivalent of the food or based on data previously provided by manufacturers during the IUNA national dietary surveys \u003csup\u003e(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline intakes and modelling scenarios\u003c/h2\u003e \u003cp\u003eBaseline data reflects the intakes of iron based on actual dietary patterns and food composition as per the NCFS II. The modelling scenarios included:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eModel 1 (FeFortFoods_all): Removal of iron fortification from all iron fortified foods\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eModel 2 (FeFortFoods_exclRTEC): Removal of iron fortification from all iron fortified foods excluding RTEC\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eModel 3 (FeFortRTEC_exclother): Removal of iron fortification from RTEC only (excluding all other iron fortified foods)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEstimation of usual iron intakes\u003c/h3\u003e\n\u003cp\u003eUsual intake distributions of iron from all sources (food, beverages and food supplements) and from food sources only (food and beverages, excluding food supplements) at baseline and for each of the three modelling scenarios were estimated for all children aged 5\u0026ndash;12 years, for consumers of iron fortified foods and for consumers of iron fortified RTEC using the validated National Cancer Institute (NCI)-method\u003csup\u003e(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/sup\u003e which accounts for both inter- and intra-person variance. The NCI-method has been implemented in SAS macros (version 2.1) which were downloaded from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.riskfactor.cancer.gov/diet/usualintakes/macro.html\u003c/span\u003e\u003cspan address=\"http://www.riskfactor.cancer.gov/diet/usualintakes/macro.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (date of download: July 2015). For these analyses, the covariates used were sex (male/female) and age group (5-8y/9-12y).\u003c/p\u003e\n\u003ch3\u003eAdequacy of iron intakes\u003c/h3\u003e\n\u003cp\u003eThe prevalence of inadequate intakes of iron was estimated using the estimated average requirement (EAR) from EFSA as a cut point\u003csup\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/sup\u003e. The EAR is the level of (nutrient) intake estimated to meet the requirements of 50% of a population group\u003csup\u003e(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/sup\u003e. This method has been shown to be effective in obtaining a realistic estimate of the prevalence of dietary inadequacy\u003csup\u003e(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)\u003c/sup\u003e. As under-reporting of food consumption can result in an overestimate of the prevalence of inadequacy in a population group\u003csup\u003e(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/sup\u003e, under-reporters (URs) were identified and excluded from these analyses (19.5% of total sample). URs were identified using Goldberg\u0026rsquo;s cut-off2 criterion updated by Black (which evaluates the ratio of energy intake to basal metabolic rate (EI:BMR) against age-specific energy cut offs based on physical activity levels)\u003csup\u003e(\u003cspan additionalcitationids=\"CR39 CR40\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk of excessive intake of iron\u003c/h2\u003e \u003cp\u003eWhilst the risk of excessive intake of micronutrients is typically evaluated using the tolerable upper intake level (UL) (maximum level of total chronic daily intake of a nutrient (from all sources) judged to be unlikely to pose a risk of adverse health effects to humans\u003csup\u003e(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/sup\u003e), a recent review of the evidence to establish a UL for iron intakes by EFSA concluded that there was insufficient evidence to establish a UL and instead set a Safe Level of intake (SI)\u003csup\u003e(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/sup\u003e and the proportion of children with intakes above this SI were calculated within this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was carried out using SPSS\u0026copy; for Windows\u0026trade; Version 28.0. Differences in intakes of iron between sexes (males, females) were assessed using independent sample \u003cem\u003et\u003c/em\u003e-tests. Differences in intakes of iron between baseline and the modelled scenarios were assessed using paired sample \u003cem\u003et\u003c/em\u003e-tests. Differences in the prevalence of inadequate intakes of iron (proportion of children with intakes below the EAR) between baseline and the modelled scenarios and between sexes (males, females) were assessed using Chi-square tests. To minimise type 1 errors (as a result of multiple testing), the Bonferroni adjustment was used by dividing the alpha level (0.05) by the number of comparisons with intakes considered to be significantly different from each other if p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003csup\u003e(44)\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the distribution of iron intakes (mg), the proportion of the population with intakes below the EAR (excluding energy-under reporters) (%) and the proportion with intakes above the SI (%) from all sources (including food supplements) and food sources only (excluding food supplements) in children aged 5\u0026ndash;12 years in Ireland in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified RTEC based on actual intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods as per the three modelling scenarios.\u003c/p\u003e \u003cp\u003eThe proportion of children consuming any iron fortified food was 82% and the proportion consuming iron fortified RTEC was 78%. Among the total population of children, the mean intake of iron from all sources (including nutritional supplements) at baseline was 9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg with significantly lower intakes observed following all modelling scenarios which restricted iron fortification: FeFortFoods_all (7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8mg), FeFortFoods_exclRTEC (8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg) and FeFortRTEC_exclother (7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8mg). Similarly, among consumers of iron fortified foods, the mean intake of iron from all sources was significantly lower in all modelling scenarios: FeFortFoods_all (6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7mg), FeFortFoods_exclRTEC (9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg) and FeFortRTEC_exclother (7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7mg) than baseline (9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3mg) and for consumers of iron fortified RTEC, the mean intake of iron from all sources at baseline was (9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3mg) with significantly lower intakes observed following all modelling scenarios: FeFortFoods_all (6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7mg), FeFortFoods_exclRTEC (9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg) and FeFortRTEC_exclother (7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7mg). As the proportion of children using an iron containing supplement was low (6%; data not shown), similar findings were found for intakes from food sources only (as with all sources) with mean intakes of iron significantly lower in each of the modelling scenarios compared to baseline for the total population of children, consumers of iron fortified foods and consumers of iron fortified RTEC.\u003c/p\u003e \u003cp\u003eThe proportion of children with iron intakes below the EAR from all sources at baseline was 18.8% and this was significantly higher in FeFortFoods_all (49%), FeFortFoods_exclRTEC (21%) and FeFortRTEC_exclother (46%). Similarly, the proportion of children with iron intakes below the EAR from all sources was significantly higher in each modelling scenario compared to baseline for consumers of iron fortified foods (baseline: 16%, FeFortFoods_all: 52%, FeFortFoods_exclRTEC: 18%, FeFortRTEC_exclother: 49%) and consumers of iron fortified RTEC (baseline: 14%, FeFortFoods_all: 53%, FeFortFoods_exclRTEC: 16%, FeFortRTEC_exclother: 50%).\u003c/p\u003e \u003cp\u003eThe proportion of children with intakes above the SI from all sources at baseline was negligible (0.2%) but was significantly lower in all three modelling scenarios (\u0026lt;\u0026thinsp;0.1%, for each) with similar findings among consumers of iron fortified foods and consumers of iron fortified RTEC.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the distribution of iron intakes (mg), the proportion of the population with intakes below the EAR (excluding energy-under reporters) (%) and the proportion with intakes above the SI (%) from all sources (including food supplements) and food sources only in children aged 5\u0026ndash;12 years in Ireland, by sex in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified RTEC based on actual intakes (baseline) and after modelling the removal of the iron content fortified component of iron fortified foods as per the three modelling scenarios.\u003c/p\u003e \u003cp\u003eAt baseline, females had significantly lower mean intakes of iron from all sources compared to males, in the total population (males: 9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5mg; females: 8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1mg), among consumers of iron fortified foods (males: 10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg; females: 8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0mg) and among consumers of iron fortified RTEC (males: 10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4mg; females: 8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0mg). Similarly, females had significantly lower intakes of iron from all sources in each modelling scenario and from food sources only at baseline and in each modelling scenario.\u003c/p\u003e \u003cp\u003eSignificantly higher proportions of females had iron intakes below the EAR from all sources and food sources only at baseline and in each modelling scenario. At baseline up to 25% of females (total population, consumers of iron fortified foods and consumers of iron fortified RTEC) were at risk of inadequate iron intakes compared to up to 12% of males. In FeFortFoods_all, up to 61% of females were at risk of inadequate iron intakes compared to up to 44% of males. In FeFortFoods_exclRTEC, up to 28% of females were at risk of inadequate iron intakes compared to up to 13% of males. In FeFortRTEC_exclother, up to 58% of females were at risk of inadequate iron intakes compared to up to 41% of males.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGiven the importance of iron at all stages of the lifecycle and the potential regulatory changes surrounding food fortification, this study aimed to examine the potential impact of removing the iron fortified component of iron fortified foods using three modelling scenarios to provide an evidence base for the discussion of the setting of SML of addition of vitamins and minerals to foods at an EU level. More specifically, this study examined the impact of removing the iron fortified component of all iron fortified foods, all iron fortified foods excluding RTEC or iron fortified RTEC only on the intake of iron in children aged 5\u0026ndash;12 years in Ireland including the prevalence of inadequate intakes and risk of excess intakes. The main finding was that removing the iron fortified component from all iron fortified foods or from RTEC only would significantly increase the prevalence of inadequate intakes of iron to approximately one-half of all children compared to current levels (approximately one-fifth) with significantly higher proportions of females (55\u0026ndash;61%) having inadequate intakes compared to males (37\u0026ndash;44%) in all modelling scenarios. However, removing the iron fortified component from all foods excluding RTEC would have little impact on the prevalence of inadequate intakes in children compared to current levels albeit with significant proportions (approximately one-fifth) remaining with inadequate iron intakes. All scenarios showed negligible risk of iron intakes above the SI.\u003c/p\u003e \u003cp\u003eIn order to set SML for the fortification of foods with vitamins and minerals, it is essential to understand the current role of fortified foods in the diet and the potential impact of restrictions or changes to the legislation surrounding these foods on intakes and risk of inadequate nutrient intakes in vulnerable population groups\u003csup\u003e(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/sup\u003e. Furthermore, previously proposed models for the setting of SML have outlined the need to account for all potential sources of nutrient intakes within the diet (natural foods, fortified foods and food supplements)\u003csup\u003e(\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/sup\u003e. The NCFS II data allowed for this modelling exercise to examine the impact of full restrictions on fortified foods, various models of inclusion of iron fortified foods and for each model to examine the intakes from all sources (all foods and food supplements) and from food sources only (excluding food supplements). Of the scenarios examined in this study, removal of the iron fortified component from all iron fortified foods or from just RTEC would substantially increase the prevalence of inadequate iron intakes in children from approximately one-fifth to up to one half with a significantly higher prevalence amongst females (up to 61%) compared to males (up to 44%). These findings should be carefully considered as presently in Ireland (a country with a long-standing, liberal policy on food fortification), significant proportions of children already have inadequate intakes of iron which may have implications for cognitive and behavioural development at this age\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)\u003c/sup\u003e. Further exacerbation of these high levels of inadequate intakes, particularly for females, would have additional implications for older girls due to the onset of menstruation, which may elevate the risk of low iron stores and IDA\u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)\u003c/sup\u003e. While there are no biochemical data of iron status available from the NCFS II, low iron status has been found for counterparts of this age group in the UK with increasing prevalence in teenagers (particularly for females)\u003csup\u003e(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/sup\u003e. A similar modelling study to ours in the US which examined three scenarios: baseline, zero fortification and optimised fortification for a number of nutrients reported that the optimisation of RTEC fortification could be useful to minimise the proportion of the population with intakes below the EAR for all nutrients including iron across all age groups (1y+) (0% at baseline or optimised fortification compared to 7% for zero fortification)\u003csup\u003e(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the current study, similar findings were observed across all scenarios whether examining intakes from all dietary sources (including food supplements) or from food sources only (excluding food supplements) which was to be expected given the low prevalence of iron supplement users (6%) thus, it can be observed that iron intakes in this population group are primarily driven by food intake. Similar to our study, a study in the UK examining the contribution of base diet, voluntary fortified foods and supplements to micronutrient intakes found that voluntary fortified foods (but not supplements) made a meaningful contribution to intakes of vitamin and minerals, without the risk of unacceptably high intakes, with fortified foods contributing up to 13% of total iron intake across all ages\u003csup\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/sup\u003e. The same study also reported that voluntary fortified foods helped to reduce the prevalence of inadequate intakes for many nutrients including iron reducing the prevalence from 45% from base diet only to approximately 33% from base diet and fortified foods (~\u0026thinsp;30% from base diet, fortified foods and supplements)\u003csup\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/sup\u003e. Given the increasing emphasis on planetary health, in particular surrounding the advice to reduce the intakes of animal based foods which are important natural sources of iron \u003csup\u003e(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e)\u003c/sup\u003e and possible future restrictions in iron levels of voluntary fortified foods the findings of this study indicate that any policy recommendations surrounding changes to the composition of the existing food supply should be carefully considered.\u003c/p\u003e \u003cp\u003eAt the forefront of setting SML for vitamins and minerals, it is of utmost importance to balance the benefits of improved nutrient intakes from fortified foods (and/or food supplements) with the potential risk of increasing intakes above upper limits/safe intakes. In the current study, each of the modelling scenarios for restricting iron fortification of foods showed negligible risk of iron intakes above the SI which is unsurprising given the negligible risk at baseline based on current dietary patterns among this population group, which has also been reflected in other national dietary survey data of both children and other population groups where the risk of excessive iron intakes are negligible (\u0026lt;\u0026thinsp;1\u0026ndash;3%) based on current dietary patterns across Europe and the developed world\u003csup\u003e(\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile this study examined the impact of removing iron fortification of foods on intakes of iron in school-aged children, the findings may have potential implications for other population groups both in Ireland and globally. National dietary surveys of other population groups in Ireland and across the developed world have consistently shown that (iron fortified) RTEC are key contributors to iron intakes in all age groups \u003csup\u003e(\u003cspan additionalcitationids=\"CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62 CR63\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e)\u003c/sup\u003e and a recent systematic review including data from five different countries showed that RTEC provided up to 28% of daily iron intakes in the total population across all ages and from 32\u0026ndash;51% of daily iron intake in RTEC consumers only\u003csup\u003e(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e)\u003c/sup\u003e. Any change to regulations around fortification of foods could have implications not only for iron but for other nutrients that are routinely added to RTEC or other nutrients which are largely obtained from fortified foods (e.g. vitamin D, folic acid)\u003csup\u003e(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe key strengths of this study include the nationally representative sample of children aged 5\u0026ndash;12 years included in the NCFS II and the comprehensive dietary intake and food composition data (including brand level detail) which allowed for the estimation of naturally occurring and added iron in foods. Another important strength is the use of statistical modelling to estimate usual intakes of iron, resulting in a better estimate of the true distribution of usual intakes therefore improving the estimates of the proportions of the population with intakes above or below a particular reference value (e.g. EAR or SI) which would otherwise be overestimated. Misreporting or under reporting of food (energy) intake, is a known limitation with all dietary assessment; this issue was minimised by a high level of researcher-participant interaction (3\u0026ndash;4 visits over the recording period). Additionally, the removal of URs from estimates of the prevalence of inadequacy provides a better representation of the scale of nutrient inadequacy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study has shown that that removing the iron fortified component from all iron fortified foods or from RTEC only would significantly increase the prevalence of inadequate intakes of iron to approximately one-half compared to current levels (approximately one-fifth) with significantly higher proportions of females (55\u0026ndash;61%) having inadequate intakes compared to males (37\u0026ndash;44%) in all modelling scenarios. This study used iron as an example to investigate the potential impact and unintended consequences of removing fortification from specific foods and serves as a scientific basis to support discussions surrounding the setting SML of vitamins and minerals at an EU level. Beyond the setting of SML at an EU level, in light of evolving dietary patterns driven by planetary health concerns, continual monitoring of dietary intakes from natural food sources, fortified foods and supplements is essential to ensure the nutritional status (including iron) of all population groups are not adversely affected and to inform appropriate public health strategies where necessary.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eJW and LK were paid a fee from the Ceereal asbl for the production of this manuscript. Ceereal asbl had no role in the design, analysis or writing of this manuscript.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThe National Children\u0026rsquo;s Food Survey II (NCFS II) was funded by the Irish Department of Agriculture, Food and the Marine (DAFM) under the 2015 Food Institutional Research Measure (FIRM) awards and this research was funded by Ceereal asbl.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eLK and JW contributed to the conception, design and execution of the study. LK carried out the data analyses and wrote the first draft. Both authors contributed to the writing of the final manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data presented in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eObeagu EI (2025) Iron homeostasis and health: understanding its role beyond blood health - a narrative review. \u003cem\u003eAnnals of medicine and surgery (2012)\u003c/em\u003e 87, 3362\u0026ndash;3371\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organisation (WHO) (2025) Anaemia Fact Sheet. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/anaemia\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/anaemia\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed 1st January 2025)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSukwuttichai P, Tidwong N, Chaipichit N et al (2026) Global prevalence of iron deficiency anaemia among children aged 5\u0026ndash;12 years: a systematic review and meta-analysis. J global health 16:04027\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKehoe L, Buffini M, McNulty B et al (2022) Food and nutrient intakes and compliance with recommendations in school-aged children in Ireland: Findings from the National Children's Food Survey II (2017-18) and changes since 2003-04. \u003cem\u003eBritish Journal of Nutrition\u003c/em\u003e Under review\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSamaniego-Vaesken ML, Partearroyo T, Olza J et al (2017) Iron Intake and Dietary Sources in the Spanish Population: Findings from the ANIBES Study. Nutrients 9:203\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStahl A, Vohmann C, Richter A et al (2009) Changes in food and nutrient intake of 6- to 17-year-old Germans between the 1980s and 2006. Public Health Nutr 12:1912\u0026ndash;1923\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBates B, Collins D, Cox L et al (2019) \u003cem\u003eNational Diet and Nutrition Survey: Years 1 to 9 of the Rolling Programme (2008-2009-2016/2017): Time trend and income analyses\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/772434/NDNS_UK_Y1-9_report.pdf\u003c/span\u003e\u003cspan address=\"https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/772434/NDNS_UK_Y1-9_report.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e: Food Standards Agency and the Department of Health\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBates B, Collins D, Jones K et al (2020) \u003cem\u003eNational Diet and Nutrition Survey: Rolling programme Years 9 to 11 (2016/2017 to 2018/2019)\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/943114/NDNS_UK_Y9-11_report.pdf\u003c/span\u003e\u003cspan address=\"https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/943114/NDNS_UK_Y9-11_report.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e: Food Standards Agency and the Department of Health\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopes C, Torres D, Oliveira A et al (2017) National Food and Physical Activity Survey (IAN-AF) Part II. University of Porto, Portugal. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ciafel.fade.up.pt/modules/file_repository/data/Site/relatorio_resultados_ian_af.pdf\u003c/span\u003e\u003cspan address=\"http://ciafel.fade.up.pt/modules/file_repository/data/Site/relatorio_resultados_ian_af.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBird JK, Barron R, Pigat S et al (2022) Contribution of base diet, voluntary fortified foods and supplements to micronutrient intakes in the UK. J Nutr Sci 11:e51\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerner LA, Keast DR, Bailey RL et al (2014) Fortified Foods Are Major Contributors to Nutrient Intakes in Diets of US Children and Adolescents. J Acad Nutr Dietetics 114:1009\u0026ndash;1022e1008\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Jong MH, Nawijn EL, Verkaik-Kloosterman J (2022) Contribution of voluntary fortified foods to micronutrient intake in The Netherlands. Eur J Nutr 61:1649\u0026ndash;1663\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalsh N, Walton J, Buffini M et al (2021) Characterising the fortified foods consumed by school-aged children (5\u0026ndash;12y) in Ireland. \u003cem\u003eProceedings of the Nutrition Society\u003c/em\u003e 80, E174\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEC (2006) Regulation (EC) 1925/2006 of the European Parliament and of the Council of 20 December 2006. Official J Eur Union L404:26\u0026ndash;38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlynn A, Moreiras O, Stehle P et al (2003) Vitamins and minerals: a model for safe addition to foods. Eur J Nutr 42:118\u0026ndash;130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKloosterman J, Fransen HP, de Stoppelaar J et al (2007) Safe addition of vitamins and minerals to foods: setting maximum levels for fortification in the Netherlands. Eur J Nutr 46:220\u0026ndash;229\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasmussen SE, Andersen NL, Dragsted LO et al (2006) A safe strategy for addition of vitamins and minerals to foods. Eur J Nutr 45:123\u0026ndash;135\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDufour A, Wetzler S, Touvier M et al (2010) Comparison of different maximum safe levels in fortified foods and supplements using a probabilistic risk assessment approach. Br J Nutr 104:1848\u0026ndash;1857\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlynn A, Kehoe L, Hennessy \u0026Aacute; et al (2016) Estimating safe maximum levels of vitamins and minerals in fortified foods and food supplements. Eur J Nutr, 1\u0026ndash;11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEurofins (2025) Update: Planned EU maximum levels for vitamins, minerals and trace elements. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.eurofins.de/food-analysis/food-news/food-testing-news/planned-eu-maximum-levels-for-vitamins-minerals-and-trace-elements/\u003c/span\u003e\u003cspan address=\"https://www.eurofins.de/food-analysis/food-news/food-testing-news/planned-eu-maximum-levels-for-vitamins-minerals-and-trace-elements/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBfR (2021) Updated recommended maximum levels for the addition of vitamins and minerals to food supplements and conventional foods. \u003cem\u003ewwwbfrbundde\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (IUNA) (2020) \u003cem\u003eThe National Children's Food Survey II (NCFS II) Main Report\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iuna.net/surveyreports\u003c/span\u003e\u003cspan address=\"https://www.iuna.net/surveyreports\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCentral Statistics Office (2017) Census 2016 Summary Results - Part 1. Central Statistics Office, Dublin, Ireland\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoster E, Hawkins A, Adamson A (2010) Young Person's Food Atlas: Primary School. Food Standards Agency, London\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Agriculture Fisheries and Food (1997) Food Portion Sizes. The Stationary Office, London\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyons J, Giltinan M (2013) \u003cem\u003eThe Irish Food Portion Sizes Database, First Edition.\u003c/em\u003e www.iuna.net\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePublic Health England (2015) McCance and Widdowson's The Composition of Foods, 7th edn. Royal Society of Chemistry, Cambridge\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFood Standards Agency (2002) McCance and Widdowson's The Composition of Foods, 6th edn. Royal Society of Chemistry, Cambridge\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlack LJ, Walton J, Flynn A et al (2014) Adequacy of vitamin D intakes in children and teenagers from the base diet, fortified foods and supplements. Public Health Nutr 17:721\u0026ndash;731\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHennessy \u0026Aacute;, Browne F, Kiely M et al (2016) The role of fortified foods and nutritional supplements in increasing vitamin D intake in Irish preschool children. Eur J Nutr, 1\u0026ndash;13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHennessy \u0026Aacute;, Hannon EM, Walton J et al (2015) Impact of voluntary food fortification practices in Ireland: trends in nutrient intakes in Irish adults between 1997\u0026ndash;9 and 2008\u0026ndash;10. Br J Nutr 113:310\u0026ndash;320\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHopkins SM, Gibney MJ, Nugent AP et al (2015) Impact of voluntary fortification and supplement use on dietary intakes and biomarker status of folate and vitamin B-12 in Irish adults. Am J Clin Nutr 101:1163\u0026ndash;1172\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTooze JA, Kipnis V, Buckman DW et al (2010) A mixed-effects model approach for estimating the distribution of usual intake of nutrients: The NCI method. Stat Med 29:2857\u0026ndash;2868\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEFSA Panel on Dietetic Products Nutrition and Allergies (2015) Scientific Opinion on Dietary Reference Values for iron. EFSA J 13:4254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEFSA Panel on Dietetic Products Nutrition and Allergies (2010) Scientific Opinion on principles for deriving and applying Dietary Reference Values. EFSA J 8:1458\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Lauzon B, Volatier J, Martin A (2004) A Monte Carlo simulation to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level. Public Health Nutr 7:893\u0026ndash;900\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarriquiry AL (1999) Assessing the prevalence of nutrient inadequacy. Public Health Nutr 2:23\u0026ndash;34\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldberg G, Black A, Jebb S et al (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45:569\u0026ndash;581\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlack AE (2000) Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes 24:1119\u0026ndash;1130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutrition: Clin Nutr 39C:5\u0026ndash;41\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Food Safety Authority (2017) Dietary Reference Values for nutrients Summary report. EFSA Supporting Publications 14:e15121E\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEFSA Panel on Dietetic Products Nutrition and Allergies (2006) Tolerable Upper Intake Levels for Vitamins and Minerals. EFSA J\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEFSA Panel on Nutrition NF, Allergens F, Turck D et al (2024) Scientific opinion on the tolerable upper intake level for iron. EFSA J 22:e8819\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFagerland MW (2012) t-tests, non-parametric tests, and large studies\u0026mdash;a paradox of statistical practice? BMC Med Res Methodol 12:78\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoschonis G, Papandreou D, Mavrogianni C et al (2013) Association of Iron Depletion with Menstruation and Dietary Intake Indices in Pubertal Girls: The Healthy Growth Study. \u003cem\u003eBioMed Research International\u003c/em\u003e 2013, 423263\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith JD, Jain N, Bailey RL (2020) Ready-to-eat cereal fortification: a modelling study on the impact of changing ready-to-eat cereal fortification levels on population intake of nutrients. Public Health Nutr 23:2165\u0026ndash;2178\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWillett W, Rockstr\u0026ouml;m J, Loken B et al (2019) Food in the Anthropocene: the EAT Lancet Commission on healthy diets from sustainable food systems. Lancet 393:447\u0026ndash;492\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRockstr\u0026ouml;m J, Thilsted SH, Willett WC et al (2025) The EAT Lancet Commission on healthy, sustainable, and just food systems. Lancet 406:1625\u0026ndash;1700\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (IUNA) (2024) The National Adult Nutrition Survey II (NANS II) Main Report. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iuna.net/surveyreports\u003c/span\u003e\u003cspan address=\"https://www.iuna.net/surveyreports\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (IUNA) (2021) \u003cem\u003eThe National Teens' Food Survey II (NTFS II) Main Report\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iuna.net/surveyreports\u003c/span\u003e\u003cspan address=\"https://www.iuna.net/surveyreports\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBird JK, Bruins MJ, Turini ME (2023) Micronutrient intakes in the Dutch diet: foods, fortified foods and supplements in a cross sectional study. Eur J Nutr 62:3161\u0026ndash;3179\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBailey ADL, Miketinas DC, London HE et al (2026) Usual Nutrient Intake Adequacy and Nutritional Status of US Children and Adolescents: NHANES 2001 -March 2020. J Nutr\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (2012) National Pre-School Nutrition Survey. Summary Report. Cork: IUNA, www.iuna.net\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (IUNA) (2021) The National Teens' Food Survey II (NTFS II) Summary Report. IUNA, Cork. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iuna.net/surveyreports\u003c/span\u003e\u003cspan address=\"https://www.iuna.net/surveyreports\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish Universities Nutrition Alliance (IUNA) (2024) The Adult Nutrition Survey II (NANS II) Summary Report. IUNA, Cork. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.iuna.net/surveyreports\u003c/span\u003e\u003cspan address=\"https://www.iuna.net/surveyreports\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDerbyshire EJ, Ruxton CHS (2025) A Systematic Review of Evidence on the Role of Ready-to-Eat Cereals in Diet and Non-Communicable Disease Prevention. Nutrients 17:1680\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanders LM, Zhu Y, Jain N et al (2023) Ready-to-eat cereal consumption is associated with improved nutrient intakes and diet quality in Canadian adults and children across income levels. Front Nutr 10:1282252\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith JD, Zhu Y, Vanage V et al (2019) Association between Ready-to-Eat Cereal Consumption and Nutrient Intake, Nutritional Adequacy, and Diet Quality among Infants, Toddlers, and Children in the National Health and Nutrition Examination Survey 2015\u0026ndash;2016. \u003cem\u003eNutrients\u003c/em\u003e 11, 1989\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowers HJ, Stephens M, Russell J et al (2016) Fortified breakfast cereal consumed daily for 12 wk leads to a significant improvement in micronutrient intake and micronutrient status in adolescent girls: a randomised controlled trial. Nutr J 15:69\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith J, Jain N, Normington J et al (2022) Associations of Ready-to-Eat Cereal Consumption and Income With Dietary Outcomes: Results From the National Health and Nutrition Examination Survey 2015\u0026ndash;2018. Front Nutr 9:816548\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMichels N, De Henauw S, Breidenassel C et al (2015) European adolescent ready-to-eat-cereal (RTEC) consumers have a healthier dietary intake and body composition compared with non-RTEC consumers. Eur J Nutr 54:653\u0026ndash;664\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanders LM, Dicklin MR, Zhu Y et al (2023) The Impact of Ready-to-Eat Cereal Intake on Body Weight and Body Composition in Children and Adolescents: A Systematic Review of Observational Studies and Controlled Trials. Adv Nutr 14:161\u0026ndash;172\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMichels N, De Henauw S, Beghin L et al (2016) Ready-to-eat cereals improve nutrient, milk and fruit intake at breakfast in European adolescents. Eur J Nutr 55:771\u0026ndash;779\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFayet-Moore F, McConnell A, Cassettari T et al (2019) Breakfast Choice Is Associated with Nutrient, Food Group and Discretionary Intakes in Australian Adults at Both Breakfast and the Rest of the Day. \u003cem\u003eNutrients\u003c/em\u003e 11\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of iron intakes (mg), the proportion of the population with intakes below the Estimated Average Requirement (EAR)(34) (excluding energy-under reporters\u0026Dagger;) (%) and the proportion with intakes above the Safe Level of Intake (SI)(43) (%) from all sources\u0026dagger; (including food supplements) and food sources\u0026dagger; only (excluding food supplements) in children aged 5\u0026ndash;12 years in Ireland in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified ready-to-eat-cereal (RTEC) based on current intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods per the three modelling scenarios\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"24\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eBaseline (actual)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eModel 1 (Removal of iron from all foods)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c18\" namest=\"c14\"\u003e \u003cp\u003eModel 2 (Removal of iron from all foods excluding RTEC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c24\" namest=\"c20\"\u003e \u003cp\u003eModel 3 (Removal of iron from RTEC only)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c24\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"23\" nameend=\"c24\" namest=\"c2\"\u003e \u003cp\u003emg/d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAll sources\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e7.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e7.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e7.0*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"23\" nameend=\"c24\" namest=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026lt;EAR\u003csup\u003e(34)\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e49.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e53.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e20.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e18.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e16.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e46.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e48.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e50.1*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026gt;SI\u003csup\u003e(43)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"23\" nameend=\"c24\" namest=\"c2\"\u003e \u003cp\u003emg/d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood sources\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e6.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e6.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e6.8*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"23\" nameend=\"c24\" namest=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026lt;EAR\u003csup\u003e(34)\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e57.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e22.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e19.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e17.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e50.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e53.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e54.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026gt;SI\u003csup\u003e(43)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"24\" nameend=\"c24\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: RTEC, ready-to-eat cereal; M, males; F, females; mg, milligram; d, day; %, percentage; SD, standard deviation; P, percentile; \u0026lt;, below; EAR, estimated average requirement; \u0026gt;, above; SI, safe level of intake\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"24\" nameend=\"c24\" namest=\"c1\"\u003e \u003cp\u003eNote: All includes non-consumers and consumers of any iron fortified food; Consumers of iron fortified foods were defined as any participant who consumed an iron fortified food at least once over the 4-day recording period; Consumers of iron fortified RTEC were defined as any participant who consumed an iron fortified RTEC at least once over the 4-day recording period\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"24\" nameend=\"c24\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e All sources refers to all sources including foods and food supplements; Food sources refers to food sources only (excludes food supplements)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"24\" nameend=\"c24\" namest=\"c1\"\u003e \u003cp\u003e* Statistically different (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) from intake at baseline via paired samples \u003cem\u003et\u003c/em\u003e-tests and adjusted for multiple testing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"24\" nameend=\"c24\" namest=\"c1\"\u003e \u003cp\u003eEAR: EFSA, 2015\u003csup\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/sup\u003e; 5-6y (5mg/d), 7-11y (8mg/d), 12y males (8mg/d), 12y females (7mg/d), \u003csup\u003e\u0026Dagger;\u003c/sup\u003eExcludes energy-under reporters (19.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"24\"\u003eSI: EFSA, 2024\u003csup\u003e(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/sup\u003e; 5-6y (15mg/d), 7-10y (20mg/d), 11-12y (30mg/d)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of iron intakes (mg), the proportion of the population with intakes below the Estimated Average Requirement (EAR)(34) (excluding energy-under reporters\u0026Dagger;) (%) and the proportion with intakes above the Safe Level of Intake (SI)(43) (%) from all sources\u0026dagger; (including food supplements) and food sources\u0026dagger; only (excluding food supplements) in children aged 5\u0026ndash;12 years in Ireland, by sex in the total population of children, among consumers of iron fortified foods and among consumers of iron fortified ready-to-eat-cereal (RTEC) based on current intakes (baseline) and after modelling the removal of the iron fortified component of iron fortified foods per the three modelling scenarios\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"36\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c25\" colnum=\"25\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c26\" colnum=\"26\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c27\" colnum=\"27\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c28\" colnum=\"28\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c29\" colnum=\"29\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c30\" colnum=\"30\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c31\" colnum=\"31\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c32\" colnum=\"32\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c33\" colnum=\"33\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c34\" colnum=\"34\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c35\" colnum=\"35\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c36\" colnum=\"36\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c9\" namest=\"c2\"\u003e \u003cp\u003eBaseline (actual)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c18\" namest=\"c11\"\u003e \u003cp\u003eModel 1 (Removal of iron from all foods)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c27\" namest=\"c20\"\u003e \u003cp\u003eModel 2 (Removal of iron from all foods excluding RTEC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c36\" namest=\"c29\"\u003e \u003cp\u003eModel 3 (Removal of iron from RTEC only)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c21\" namest=\"c20\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c24\" namest=\"c23\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c27\" namest=\"c26\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c30\" namest=\"c29\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c33\" namest=\"c32\"\u003e \u003cp\u003eConsumers of iron fortified foods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c36\" namest=\"c35\"\u003e \u003cp\u003eConsumers of iron fortified RTEC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e 236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"35\" nameend=\"c36\" namest=\"c2\"\u003e \u003cp\u003emg/d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAll sources\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e8.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e8.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e8.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e6.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e6.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e6.6*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"35\" nameend=\"c36\" namest=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026lt;EAR\u003csup\u003e(34)\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e58.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e61.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e61.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e27.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e24.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e21.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e54.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e57.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e57.9*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026gt;SI\u003csup\u003e(43)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"35\" nameend=\"c36\" namest=\"c2\"\u003e \u003cp\u003emg/d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood sources\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e8.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e8.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e8.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e6.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e6.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e6.4*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"35\" nameend=\"c36\" namest=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026lt;EAR\u003csup\u003e(34)\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e44.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e63.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e66.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e65.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e30.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e26.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e23.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e59.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e62.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e62.4*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u0026gt;SI\u003csup\u003e(43)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e0.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"36\" nameend=\"c36\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: RTEC, ready-to-eat cereal; M, males; F, females; mg, milligram; d, day; %, percentage; SD, standard deviation; P, percentile; \u0026lt;, below; EAR, estimated average requirement; \u0026gt;, above; SI, safe level of intake\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"36\" nameend=\"c36\" namest=\"c1\"\u003e \u003cp\u003eNote: All includes non-consumers and consumers of any iron fortified food; Consumers of iron fortified foods were defined as any participant who consumed an iron fortified food at least once over the 4-day recording period; Consumers of iron fortified RTEC were defined as any participant who consumed an iron fortified RTEC at least once over the 4-day recording period\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"36\" nameend=\"c36\" namest=\"c1\"\u003e \u003cp\u003e\u0026dagger; All sources refers to all sources including foods and food supplements; Food sources refers to food sources only (excludes food supplements)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"36\" nameend=\"c36\" namest=\"c1\"\u003e \u003cp\u003e* Statistically different (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) from that of males within each scenario via independent samples \u003cem\u003et\u003c/em\u003e-tests and adjusted for multiple testing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"36\" nameend=\"c36\" namest=\"c1\"\u003e \u003cp\u003eEAR: EFSA, 2015\u003csup\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/sup\u003e; 5-6y (5mg/d), 7-11y (8mg/d), 12y males (8mg/d), 12y females (7mg/d), \u003csup\u003e\u0026Dagger;\u003c/sup\u003eExcludes energy-under reporters (19.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"36\"\u003eSI: EFSA, 2024\u003csup\u003e(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/sup\u003e; 5-6y (15mg/d), 7-10y (20mg/d), 11-12y (30mg/d)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Iron fortification, voluntary fortification, iron intakes, children","lastPublishedDoi":"10.21203/rs.3.rs-8895504/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8895504/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIron is an essential element for human health with natural sources and fortified foods being the main contributors to intakes. In the context of setting safe maximum levels (SML) in food supplements and fortified foods in the EU, it is necessary to understand the current role of fortified foods in the diet and the potential impact of any regulatory changes. This study used three modelling scenarios to investigate the impact of removing voluntary iron fortification of current iron fortified foods on iron intakes in children.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eData were based on the Irish National Children\u0026rsquo;s Food Survey II. The modelling scenarios included 1. Removal of iron from all fortified foods, 2. Removal of iron from fortified foods excluding ready-to-eat cereals (RTEC) and 3. Removal of iron from fortified RTEC only. Usual intakes of iron, the prevalence of inadequate intakes and risk of excess intakes were examined at baseline and for each scenario for the total population and consumers only.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRemoving the iron fortified component from all iron fortified foods/RTEC only significantly increased the prevalence of inadequate intakes of iron from 20% to 50% with significantly higher proportions of females (55\u0026ndash;61%) having inadequate intakes compared to males (37\u0026ndash;44%). There was negligible risk of excess iron intake at baseline and no further impact from any of the three scenarios.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study showed that removing voluntary iron fortification could carry a significant nutritional risk and should be carefully evaluated to ensure the iron status of vulnerable population groups are not adversely affected.\u003c/p\u003e","manuscriptTitle":"Would the removal of voluntary iron fortification put vulnerable populations at risk? Modelling the risk of inadequate and excess iron intakes in children in Ireland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-04 17:38:43","doi":"10.21203/rs.3.rs-8895504/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dca92604-85c8-4722-913e-af48c6376219","owner":[],"postedDate":"March 4th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-02T13:11:26+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-02T13:25:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-04 17:38:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8895504","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8895504","identity":"rs-8895504","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}