Do 6-9-Year-Old Children in Denmark Adhere to National Dietary Recommendations and Are There Sociodemographic Disparities? The Generation Healthy Kids Study

Do 6-9-Year-Old Children in Denmark Adhere to National Dietary Recommendations and Are There Sociodemographic Disparities? 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The Generation Healthy Kids Study Frederik Holmegaard, Anna Gro Eilersen, Lotte Lauritzen, Christian Mølgaard, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7741373/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Jan, 2026 Read the published version in European Journal of Nutrition → Version 1 posted You are reading this latest preprint version Abstract Purpose Diet in childhood is important for growth, brain development, and long-term health. Thus, assessing children’s adherence to dietary recommendations and identifying sociodemographic groups with low adherence is of great public health relevance. We investigated dietary intake, adherence to recommendations and sociodemographic differences in a large population of Danish children. Methods We analyzed baseline data from 1094 children aged 6–9 years from 23 schools across Denmark participating in the Generation Healthy Kids study. Diet was assessed by three-day dietary records and food frequency questionnaires for fish and supplements, focusing on key food groups, macronutrients, and iron. Fasting blood samples were collected from n = 347 and analyzed for nutritional biomarkers of fish, wholegrains and iron for validation. Results Overall adherence to dietary recommendations showed a mean ± SD score of 4.7 ± 0.8 out of 7.0. However, < 15% adhered to the recommendations for fruit + vegetables, fish, and meat, and < 66% to recommendations for saturated fat (SFA) and iron. Adherence decreased with age and shorter parental education due to lower intakes of fruit + vegetables and dairy with age and less wholegrains and more meat in those with short education (all P < 0.01). Also, rural children consumed less fruit + vegetables and more added sugar and SFA than urban, and non-Danish descendants consumed less wholegrains and sugar than Danish (all P < 0.05). Weight status was not associated with adherence. Conclusions Danish children had relatively good dietary adherence, but intakes of fruit + vegetables, fish, meat, SFA, and iron remain a concern. Attention should be given to children of older age and short education and rural backgrounds. Children’s dietary intake dietary recommendations sociodemographic disparities public health Introduction Diet and nutrient intake in childhood are important for optimal growth, cognitive and bone development, and long-term health [1–3]. In Western countries children from the age of 2 years are typically advised to follow the same food based dietary guidelines (FBDG) and nutrient recommendations as adults but adjusted to fit their lower total energy requirements [4–7]. Most dietary recommendations emphasize high intakes of fruit and vegetables, wholegrains and fish while limiting red and processed meats, saturated fat (SFA) and added sugar. Such a dietary pattern has been shown to be associated with reduced overweight and improved cardiometabolic risk markers in children [8–11], which may influence later risk of lifestyle diseases. Thus, it is of great public health relevance to evaluate children’s adherence to dietary recommendations. Previous dietary surveys have shown that children in Western countries have low adherence to dietary recommendations [4, 12]. A report from the European Food Safety Authority concluded that young children in the EU are at risk of insufficient dietary intakes of iron, vitamin D (vitD), and n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) [13], a concern also evident among Danish children and adolescents [12]. However, the most recent national dietary survey among Danish children was conducted more than 10 years ago and it did not include objective nutrient biomarkers, which are important to verify reported intakes and identify nutrient deficiencies. Children’s dietary intake and adherence to recommendations may be influenced by sociodemographic factors. For instance, children of parents with lower education levels have been shown to consume less fruit and vegetables, fish, and dietary fiber than children of parents with higher education [14, 15], and adherence to the recommendations tends to decline as children approach adolescence [15, 16]. Children’s dietary intake may also be associated with other factors such as ethnic origin [17, 18] and rurality [19–21], although previous findings are inconsistent. As many sociodemographic factors are interrelated, comprehensive investigations that account for multiple factors simultaneously are needed to better understand social disparities in children’s food and nutrient intake. Finally, despite the common perception that children with overweight have unhealthy diets, studies on associations between children’s diets and weight status or adiposity remain inconclusive [15, 17, 22]. The present study used baseline data from 1094 6-9-year-old children from 23 schools in three of the five regions in Denmark, who participated in the Generation Healthy Kids (GHK) study. GHK was a cluster-randomized, multi-setting, multi-component intervention designed to promote healthy weight development in 1 st and 2 nd grade children by focusing on healthy diets, physical activity, sleep, and screen media habits [23]. The primary aim of the present study was to investigate the dietary intake of the children and their adherence to the Danish FBDG and Nordic Nutrition Recommendations (NNR2023). We focused on intake of fruit and vegetables, wholegrains, meat, milk and dairy, fish, SFA, added sugar, n-3 LCPUFA, vitD, and iron. In a subgroup of children, blood biomarkers were used to assess n-3 LCPUFA and iron status and to validate reported intakes of fish and wholegrains. Finally, we explored whether dietary intake and adherence differed by the children’s age, sex, parental education level, country of origin, rurality, and weight status. Methods Study design and participants The present study is a cross-sectional investigation based on baseline data from the GHK study, collected during September-December 2023. The core components of the GHK intervention included a free-of-charge school lunch program, three weekly 40-minute sessions of vigorous physical activity during school hours, and classroom exercises and parent workshops on sleep and screen media use, as previously described [23]. The study was approved by the Ethics Committee of Southern Denmark (S-20220094) and registered at clinicaltrials.gov (NCT 05940675). Initial contact was established with 496 Danish schools from December 2022 to April 2023. Inclusion criteria for schools were: 1) location in The Capital Region, the Zealand Region, or the Region of Southern Denmark, 2) suitable kitchen facilities for school meal preparation. A total of 24 schools were recruited and randomized in clusters 1:1 to the intervention and control. One control school withdrew after randomization and 2006 children in 1 st and 2 nd grade were invited from the remaining 23 schools. There were no exclusion criteria for the children; if parents, teachers, or the clinically responsible physician (CM) judged that a child could not participate in certain parts of the intervention or measurements, they could still participate in the rest of the study. All children received oral information, and parents received both written and oral information about the study. Written informed consent for participation was obtained from the parents of 1350 children. Among these, 517 children (from the Capital and Zealand Regions only) also provided separate consent for blood sampling. The present study included the 1094 participating children who had ≥1 complete day of dietary recording and measurements of height and weight at baseline ( Supplementary Fig. 1 ). Background information The children’s age was collected from school records, and parents reported their education level and country of origin in an online questionnaire. Education level was reported in seven categories using the International Standard Classification of Education (ISCED97) adapted to a Danish context; 1) Primary education (1-6 years), 2) Lower secondary education (7-10 years), 3) Upper secondary education in high school (10-13 years), 4) Upper secondary vocational education (10-13 years), 5) Short tertiary education (14-16 years), 6) Bachelor’s degree or similar (14-17 years), and 7) Master’s degree or PhD (18-21 years). These categories were pooled into Short (≤13 y), Medium (14-17 y), and Long (≥18 y) education, and we used the highest level of education in the household for analyses. Children were classified as Danish descendants if one or both parents were born in Denmark, and as non-Danish descendants if both parents were born in other countries. Most non-Danish descendants originated from Eastern Europe (44%) and the Middle East (26%). When data was only available from one parent (n=48), education level and descendance were based on this information. Children’s rurality was based on the geographical location of the schools, i.e. urban when located in cities or areas with ≥10,000 inhabitants or rural when located in towns or areas with <10,000 inhabitants. Dietary records Information about the children’s diet was collected sequentially at each school during the same period as the clinical measurements, but never on the same day. Parents were asked to record their child’s dietary intake prospectively for three consecutive days (two weekdays and one weekend day) using an online self-administered dietary assessment tool (myfood24®, Dietary Assessment Ltd., Leeds, UK).). 24-h dietary recalls in myfood24 have previously been validated against an interviewer-administered 24-h dietary recall in English adolescents [24] and against weighed dietary records and biomarkers in German adults [25]. Each day, parents received a link to the food diary with written guidelines in multiple languages and a video guide in Danish and English, and they had access to support by phone and e-mail. If all three days were not completed, reminder e-mails and text messages were sent to the parents 1-2 weeks later, on the same day(s) of the week. Parents entered all food and drink items consumed by their child by searching a joint food database consisting of a Danish (FRIDA), a Swedish (Livsmedelsverket), an English (myfood24), and an American (USDA FoodData central) food composition database. Portion sizes were estimated using portion images, descriptions, household measures, or by weighing if the parents wished so. Estimation of dietary intake From the dietary records, daily intakes of the food groups: fruit and vegetables, wholegrains, milk and dairy products, as well as meat and meat products were calculated. For mixed dishes, the contribution from each food group was estimated based on common recipes (e.g. for a stir fry with vegetables 50% was estimated to be vegetables). Wholegrain content was calculated using food specific wholegrain factors (e.g. 0.25 for wholegrain bread and buns, and 0.54 for wholegrain muesli and other breakfast cereals) based on the definitions of the Danish wholegrain labelling [26]. Daily intakes of SFA, dietary fiber, and iron were derived directly from myfood24. Intakes of added sugar were estimated as total sugar minus natural sugars (e.g. lactose in dairy) across the categories: sugar and jam, confectionary and chocolate, cakes and desserts, soft drinks, sauces and dips, refined grains, breakfast cereals, and dairy. For food items with missing database information on sugar content, added sugar were estimated from the Danish food composition database (FRIDA) [27] or product labels. Under-, acceptable, and over-reporters of dietary intake Children were classified as either under-reporters, acceptable reporters, or over-reporters of energy based on the ratio of mean reported energy intake (EI) to estimated basal metabolic rate (BMR) using the cut-offs suggested by Black [28]; under-reporters: EI:BMR<1.09, acceptable reporters: 1.09<EI:BMR2.26, assuming a physical activity level of 1.6 [7]. BMR was calculated from the Oxford equations [29] using the child’s height, weight, sex, and age. Food Frequency Questionnaire To better assess habitual fish and n-3 LCPUFA intake, we used a self-administered, online food frequency questionnaire (FFQ) that asked specifically about the intake of fish. This fish FFQ was based on a semi-quantitative FFQ developed to assess overall food, energy, and nutrient intake in Denmark [30]. The original FFQ was validated in the Danish Cancer Cohort [31] and the derived fish specific FFQ has previously been validated among children in the FiSK trial [32]. Parents reported the overall frequency of their child’s fish intake during the last month as bread topping and as hot meals, separately, along with intake frequencies for 11 and 13 specific fish types within each meal type, respectively. Each question had seven response options ranging from “rarely or never” to “twice or more per day”, which were converted to average daily frequencies. To avoid overestimation, we multiplied the daily frequencies for each fish type with a correction factor, calculated as the recorded frequency of overall fish intake divided by the sum of frequencies for intake of all fish types. Average daily intakes of each fish type were then estimated by multiplying the adjusted frequencies with fish-specific portion sizes (30-50 g for bread toppings and 50-125 g for hot meals) based on validated Danish standard portion sizes [33]. Daily intakes of total, oily, and lean fish were calculated, and intakes of n-3 LCPUFA from fish were estimated using nutritional data from FRIDA. The FFQ also included questions about frequency, type and brand of n-3 LCPUFA and vitD supplements used in the past month and during winter (October-April), respectively. Daily intake of n-3 LCPUFA from supplements was estimated and added to the intake from fish to derive total daily intake. Children were categorized as vitD supplement users during winter when they consumed supplements with ≥10 µg of vitD on ≥5 days per week. Comparison with dietary recommendations Children’s dietary intake was compared with the official dietary recommendations in Denmark at the time of data collection: the Danish FBDG 2021 and the NNR2023. The FBDG provide recommended intakes of food groups in a 10 MJ diet, i.e. ≥600 g/d fruit and vegetables, ≥75 g/d wholegrains, ≥350 g/week fish of which ≥200 g should be oily fish, ≥250 g/d milk and dairy, and ≤350 g/week meat and meat products. To compare directly with the FBDG and account for differences in EI, all food group intakes except fish and dairy were converted to g/10 MJ. For fish, the recommended intake was scaled to match the children’s mean reported EI and for dairy, Danish children are recommended to consume the same amount as adults despite a lower EI [6]. Nutrient intakes were converted to E% and g/MJ, as appropriate, for comparison with the NNR2023, e.g. <10 E% added sugar, <10 E% SFA, ≥2 g/MJ dietary fiber, and ≥9 mg/d iron. To assess overall adherence to the dietary recommendations, a dietary adherence score was constructed based on seven key components: fruit and vegetables, wholegrains, fish, milk and dairy products, meat and meat products, added sugar, and SFA. For each component, a continuous score was calculated as the ratio of reported to recommended intake, capped at 1 for intakes meeting or exceeding the recommendations. The scores for meat, added sugar, and SFA were inverted, so lower intakes resulted in higher scores. The overall adherence score was calculated as the sum of scores for all components, ranging from 0 to 7, with higher scores indicating better adherence to the dietary recommendations. Clinical measurements and blood sampling Clinical measurements and blood sampling were conducted in accordance with standard operating procedures on two separate school days by trained members of the research team. On the first day, children’s height and weight were measured. Height was determined as the mean of three measurements to the nearest 0.1 cm using a portable stadiometer (Seca 217, Seca, Germany), and weight was measured to the nearest 0.1 kg using a digital scale (InBody 270, InBody Co Ltd., California, USA). Children wore light clothing and were instructed to empty their bladder before being weighed. Sex- and age-adjusted z-scores for body mass index (BMI) was calculated using the WHO AnthroPlus software (v1.0.4, Department of Nutrition, WHO, Geneva, Switzerland) and the International Obesity Task Force (IOTF) LMS-curves [34]. Children were categorized as underweight, normal weight, and overweight as determined by age- and sex-specific cut-offs [34] for the IOTF BMI z-score. On the second day, blood samples were drawn from an antecubital vein before 10:30 am after an overnight fast. In total 347 children had a blood sample drawn and 325 of them (93.7%) confirmed fasting except for 1-2 glasses of water. Local anesthetic patches (EMLA, Astra Zeneca AB, Södertälje, Sweden) were provided beforehand and applied by the parents in the morning. Whole blood for fatty acid analysis was collected with lithium heparin, and 500 µL was transferred to a cryotube with the antioxidant 2,6-di-tert-butyl-4-methylphenol (butylated hydroxytoluene; Sigma-Aldrich, St. Louis, MO, USA) and kept on dry ice. Additional blood collected in tubes with EDTA or clot activator was kept at room temperature and centrifuged at 2000 x g at 4°C for 10 min within 6 h after blood sampling at the Department of Nutrition, Exercise, and Sports (NEXS), University of Copenhagen. All samples were stored at -80°C until analysis. Analysis of blood samples Whole blood EPA+DHA: Whole blood fatty acid composition was analyzed within 7 months by gas chromatography at the Department of Kinesiology and Health, University of Waterloo, ON, Canada, as previously described [35]. Briefly, lipids were extracted with chloroform and methanol containing an internal standard (22:3n-3 ethyl ester, Nu-Chek Prep Inc., Elysian, MN), and fatty acid methyl esters were generated using 14% boron trifluoride (BF 3 ) in methanol and heating for 1 h at 95 °C on a heating block. The fatty acid methyl esters were then determined using a Scion 8300 gas chromatograph (Scion Instruments Canada, Edmonton, AB, Canada) with a DB-FFAP capillary column (15 m x 0.1 mm ID x 0.1 µm film thickness; J&W Scientific from Agilent Technologies, Mississauga, ON, Canada). In the initial analysis, some samples had very low fatty acid concentrations (6.0), indicating sample oxidation, as previously described [36]. Therefore, all samples were reanalyzed or reintegrated, and the results with the lowest SFA:LCPUFA ratio for each sample were included in the statistical analysis. Samples with SFA:LCPUFA ratios >1 SD above or below the mean in both runs (n=15, 4%) were excluded. The relative whole blood content of Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) as a percentage of all fatty acids (FA%) was used as a measure of n-3 LCPUFA status. To allow comparison with omega-3-index cut-offs (8% [optimal]) [37], whole blood EPA+DHA was converted to red blood cell equivalents as suggested by Stark et al. [38]. Plasma alkylresorcinols: Plasma alkylresorcinol concentrations were analyzed at the Department of Life Sciences at Chalmers University of Technology, Sweden by liquid chromatography and tandem mass spectrometry on a QTRAP 6500+ (AB SCIEX, Marlborough, MA, USA) as previously described [39]. Total alkylresorcinol concentration – a marker of wholegrain wheat and rye intake – was used as a biomarker for validating the reported wholegrain intake. The intra- and inter-assay variability were 4.7-7.8% and 10.5-19.0% for each alkylresorcinol homologue, respectively. Iron status: Whole blood hemoglobin was analyzed on a Sysmex KX 21N Analyzer (Sysmex Corporation, Hyogo, Japan) at NEXS within 6 h after blood sampling. Serum ferritin was analyzed on an IMMULITE 2000 Analyzer (Siemens Healthcare GmbH, Erlangen, Germany) at the Department of Clinical Biochemistry at Rigshospitalet, Copenhagen within one year after sampling. Statistical analysis Data were analyzed using R (version 4.2.1). Crude odds ratios (OR) and a logistic regression model for age were used to assess sociodemographic differences between children included and not included in the present study. The sociodemographic characteristics of included children were compared to those of the Danish background population using chi-square tests. Dietary intake, nutrient status, and adherence to dietary recommendations are presented as mean ± SD for normally distributed data and median (IQR) for skewed data. All mean and median intakes include children with zero intakes. Food and nutrient intakes were compared between boys and girls by Student’s unpaired t-test and Mann-Whitney U-test when data were normally distributed and skewed, respectively. Children with acceptable dietary reporting and data on parental education and country of origin were included in the primary multivariable linear regression models to explore associations between sociodemographic factors (age, sex, weight status, parental education level, country of origin, and rurality) and intakes of key food groups and nutrients. The dietary components included in the models – fruit and vegetables, wholegrains, fish, milk and dairy products, meat and meat products, added sugar, and SFA – represent major targets for dietary improvement among children and are linked to both potential nutrient inadequacies and chronic disease prevention goals. All sociodemographic factors were included as fixed effects to assess the independent association of each predictor with dietary intakes. In secondary sensitivity analyses, under-reporters and over-reporters were included in all models first and subsequently children with unanswered parental education and ethnic origin were included. Among the subgroup with blood samples, models of nutrient biomarkers were used as sensitivity analyses for associations with wholegrains and fish. Model assumptions were evaluated by visual inspection of Q-Q plots and scatter plots of residuals. The FFQ-reported intakes of fish and n-3 LCPUFA and the registered intakes of wholegrains were validated against whole blood EPA+DHA and total plasma alkylresorcinols, respectively, using Spearman rank correlations. Furthermore, the dose-response relationships between estimated intakes of n-3 LCPUFA and wholegrains were fitted against their respective biomarkers using both linear and logarithmic regression. The resulting plots were compared by visual inspection and R 2 -values. Results Children’s characteristics and representativeness Of the 1350 children originally included in GHK, 1142 children had at least one complete day of dietary recording at baseline. Ten were excluded from the analyses due to extreme dietary recordings (mean EI 15,000 KJ/day), and 38 were excluded due to missing anthropometric measurements (Supplementary Fig. 1). The 256 non-included children were more likely to have parents with short education (OR, 95% CI: 2.83, 1.75-4.61, P<0.001), be non-Danish descendants (2.55, 1.58-4.04, P0.65). Boys and girls were equally represented among the included children ( Table 1 ). Most children had normal weight, and the prevalence of underweight and overweight were comparable to the national numbers reported among Danish 6-7-year-olds (χ 2 =0.5, P=0.795) [40]. Only 15.5% were from households with ≤13 years of education compared to 39.9% among all Danish families with children (χ 2 =12.3, P=0.002) [41]. There was also a lower proportion of non-Danish descendants (7.8% vs. 16.2% among Danish 6-9-year-olds, χ 2 =43.5, P<0.001) [42], whereas the proportion of children residing in urban areas was similar to the general population (60.1% vs. 58.3%, χ 2 =1.2, P=0.265) [43]. In total, 870 (80%), 128 (12%), and 96 (9%) children had three, two, and one complete dietary recording days, respectively, and more than 80% of the children (n=886) were classified as acceptable reporters (1.09<EI:BMR<2.26). Over- and under-reporters were more likely to have parents with short education (OR, 95% CI: 2.14, 1.37-3.32, P<0.001), be non-Danish descendants (1.73, 1.03-2.82, P=0.030), be boys (1.45, 1.08-1.96, P=0.014), and have overweight (2.55, 1.73-3.74, P<0.001). Dietary intake and nutrient status Acceptable reporters consumed 7.0±1.3 MJ/d ( Table 2 ), which is within the estimated energy requirement range (6.3-7.8 MJ) for 6-9-year-old children with average physical activity levels (PAL=1.6) according to NNR2023 [7]. Boys had higher EI than girls, but the relative macronutrient intakes were similar in boys and girls and aligned with the 45-60 E%, 25-40 E% and 10-20 E% recommended for carbohydrates, fat and protein [7], respectively. Boys had higher absolute intakes of wholegrains, dairy, meat and iron, but did not differ from girls with regards to the other investigated food groups or n-3 LCPUFA intake (Table 2). In the subgroup with blood samples (n=285), nutrient biomarkers did not differ by sex (Table 2). Iron deficiency (serum ferritin <15 µg/L) was observed in 7.8% of the children, and 0.4% (n=1) had anemia (hemoglobin <6.5 mmol/L). n-3 LCPUFA status was generally low as 39.3% had an omega-3 index 8% (optimal). Including over- and under-reporters did not change the results ( Supplementary Table 1 ). Validation of parent-reported wholegrain, fish, and n-3 LCPUFA intakes In the subgroup with blood samples, there was a dose-response relationship between wholegrain intake and total alkylresorcinols ( Supplementary Fig. 2 ), and parent-reported wholegrain intake was moderately correlated with plasma total alkylresorcinols (r=0.33, P<0.001). Absolute intakes of fish, oily fish and total n-3 LCPUFA from fish and supplements were moderately correlated with whole blood EPA+DHA (r=0.30-0.32, all P<0.001), whereas the correlation for lean fish, which contains little n-3 LCPUFA, was weaker (r=0.21, P<0.05). The dose-response relationship between total n-3 LCPUFA intake and whole blood EPA+DHA was best fitted by a logarithmic function ( Supplementary Fig. 3 ). Adherence to dietary recommendations The average adherence score was 4.7±0.8 out of 7.0, indicating that children’s overall adherence to the dietary recommendations was fairly good. However, as shown in Table 3 , less than 15% of the children adhered to the dietary recommendations for fruit and vegetables per 10 MJ EI and for fish when the recommendation was scaled to their mean EI. The low intake of fish, especially oily fish, was in line with the low whole blood n-3 LCPUFA observed (Table 2). The adherence with recommendations for intakes of meat and SFA was also low, as less than one third of the children consumed less than 50 g/10 MJ and 10 E%, respectively. Almost half of the children met the recommendations for wholegrains and dairy, and more than 60% adhered to the recommendations for added sugar, dietary fiber, and vitD supplementation during winter (Table 3). Including children with over- and underreporting in the analyses did not change the results ( Supplementary Table 2 ). Sociodemographic determinants of dietary intake In the primary multivariable linear regression models with acceptable reporters, overall adherence to dietary recommendations decreased with age ( Table 4 ). This was mainly due to lower intakes of fruit and vegetables and dairy as well as tendencies to lower fish and higher sugar intake with age. The associations for fruit and vegetables, dairy and fish were supported in the sensitivity analyses with inclusion of under- and over-reporters and those with missing sociodemographic data, but the significance of the association for sugar decreased somewhat ( Supplementary Table 3 and 4 ). Furthermore, the sensitivity analysis among the subgroup with blood samples showed a tendency to increased whole blood EPA+DHA with age, thus not supporting a decline in fish intake with age ( Supplementary Table 5 ). Longer parental education was associated with better overall adherence to the dietary recommendations, mainly due to higher intakes of wholegrains and lower intakes of meat. The association with wholegrain intake was supported by a positive association between parental education and plasma total alkylresorcinols (Supplementary Table 5). The sensitivity analyses including more children also supported the association with wholegrains (Supplementary table 3 and 4), but they did not provide clear support for the association with meat. The overall adherence score did not differ by residential area, origin or sex in the primary or any of the sensitivity analyses (Table 4; Supplementary Table 4 and 5). All of the analysis did, however, show that children in rural areas consumed less fruit and vegetables, and more added sugar and SFA but also more wholegrains than urban children. Non-Danish descendants were also consistently shown to have a lower intake of wholegrains, but their intake of added sugar was also lower than in those with Danish descendance. Consistent associations were furthermore seen for sex, with higher consumption of wholegrains and less added sugar, but a concomitantly reduced intake of fruit and vegetables in boys relative to girls. Weight status was not associated with intake of any of the food groups or nutrients nor with the overall adherence score in the primary analysis, but in the sensitivity analyses meat intake was higher, whereas added sugar and SFA intake tended to be lower with increasing weight status. Discussion In a large group of Danish 6-9-year-olds, we showed that most children consumed less fruit and vegetables and fish as well as more meat than recommended, whereas almost half of the children reached the recommended level for wholegrain intake and more than 60% adhered to the recommendations for added sugar. Overall adherence to the dietary recommendations improved with higher parental education level and decreased with age. Children living in rural areas had lower adherence to the recommendations for fruit and vegetables, added sugar, and SFA, whereas the wholegrain intake was lower among urban children and Danish descendants. The low intake of fruit and vegetables aligns with previous findings among Western children [12, 17, 44]. This is a concern as fruit and vegetables are key sources of micronutrients and dietary fiber and have been linked to lower risk of overweight [45] and improved cardiometabolic risk profile in children [10]. In contrast to the relatively high fish intake and n-3 LCPUFA status among children in Norway [46, 47], fish intake in the present study was very low as previously seen in Denmark [12, 32, 44], the US [4], and the UK [17]. This finding was supported by the low whole blood EPA+DHA which also aligned with previous reports in Danish children [32, 48]. Increasing the n-3 LCPUFA status of Danish children would be desirable, as this has been linked to better cognitive function [49] and a more favorable cardiometabolic risk profile [48], and both of these outcomes were found to be improved by an oily fish intake of ≈300 g/wk in our previous randomized trial in Danish children [8, 50]. The persistent low intakes of fruit and vegetables and fish may reflect barriers such as cost, accessibility, preferences, time constraints, and cooking skills [32, 51]. In contrast, intake of meat was high, as also seen in the latest national dietary survey [12], suggesting a continued predominance of animal-based foods in the Danish diet despite increased trends towards plant-based diets. In general, wholegrain intake was high with a median intake approximately three times greater than among children in the UK and the US [4, 52]. Even though Denmark has one of the highest wholegrain recommendations globally [53], nearly half of the children met the recommendation, consistent with the latest national dietary survey [12]. This is likely beneficial for long-term health, as a high wholegrain intake has been shown to improve the plasma lipid profile in children [9] and to be linked to reduced risk of cardiovascular disease and mortality in adults [54]. Wholegrain intakes have increased substantially in Denmark since the early 2000’s [26], likely due to initiatives such as the Danish Wholegrain Partnership, which has improved the availability, labeling, and public awareness of wholegrain products. However, wholegrain intake among non-Danish descendants remained particularly low in the present study, with only 21.5% meeting the recommendation. One explanation may be that wholegrain products, such as sour dough rye bread and rolled oats, are distinctive characteristics of the Danish food culture, which may take time to adopt among immigrant populations. The Danish recommendation for wholegrains was raised to 90 g/10 MJ in June 2024, and when compared to this update, 31.3% of the children still adhered. Surprisingly, 64% of the children adhered to the recommendation of limiting added sugar to <10 E%. This is a marked improvement compared to the 49% and 34% of 4-14-year-olds reported in the Danish national surveys from 2011-2013 and 2003-2008, respectively [12, 55]. Despite efforts to expand the myfood24 database with added sugar values to minimize underestimation, some underreporting either due to incomplete databases or parental reporting cannot be ruled out [56]. Nevertheless, similar downward trends in sugar intake have been observed in the US and Germany since the early 2000s, especially between 2010-2016 [57, 58]. However, unlike in the present study, children’s mean and median intakes of added sugar still exceeded the recommendation in these populations [57, 58]. The reported iron intake was somewhat low considering the children’s high meat consumption, and when compared to the recommended intake (8.0 mg/d for 7-8-year-olds [7]) and the latest national dietary survey (6.7±1.7 mg/d vs. 8.9±2.1 mg/d and 7.7±2.0 mg/d vs. 9.6±2.4 mg/d in 6-9-year-old girls and boys, respectively [12]). However, both hemoglobin and ferritin levels were within the recommended ranges and only 8% of the children had iron deficiency, suggesting that the intake was adequate for most children. The intake of iron might be underestimated, but the findings may also indicate that the high bioavailability of iron from meat, or increased iron absorption seen at low intakes, compensated for the low total intake. Consistent with previous studies [14–16], adherence to dietary recommendations improved with higher parental education level and decreased with age. Similar to the present study, parental education level was also associated with wholegrain intake in the Danish national survey 20 years ago, although only among girls [14], and the observed tendency for reduced meat intake with longer parental education aligns with findings from the EU and the UK, particularly for processed meats [59, 60]. These associations may reflect greater health- and environmental awareness among highly educated parents. The decline in adherence to dietary recommendations with increasing age was evident despite a narrow age range in the present study [15, 16]. Early school years may be a period of rapid dietary changes, as children have to adapt to new environments and engage in new social relationships, which may prompt them to align their food preferences with perceived peer norms to ensure social acceptance [61]. The lower fruit and vegetable intake and higher sugar intake among rural compared to urban children are consistent with studies from Europe [19] and Canada [20], whereas the higher SFA intake has not previously been reported. Rural children also had a higher wholegrain intake, which may reflect a stronger adherence to the Danish tradition of having wholegrain rye bread for lunch in rural areas as also seen in Finland [62]. In contrast, an Australian study found that children residing in remote areas had overall healthier eating habits and consumed more fruit, and less takeaway foods and unhealthy snacks [21]. Besides differences in the definitions of urban and rural areas and the remoteness of the rural areas in the studies, the discrepancies could relate to country-specific differences in rural versus urban food environments. A major strength of the present study was the large sample size of 1094 children which exceeded that of the national Danish dietary surveys [12]. We included participants from a wide geographic area across Denmark, who were representative of the general population in terms of sex, weight status, and residential area. Non-Danish descendants were better represented than in the national surveys [12], but they were still under-represented as were children from shorter educational backgrounds. This may have led to an overestimation of the adherence to the dietary recommendations and limited our ability to detect differences between groups, particularly by origin. The detailed dietary records of the whole diet combined with the fish-specific FFQ allowed for a comprehensive assessment of habitual dietary intake, which was validated against objective biomarkers. A three-day recording period was selected to ensure feasibility, particularly among less advantaged families, but it was not suited for evaluating micronutrient intake [63]. The online recording tool helped structure the recordings, had built-in reminders (e.g. for snacks and toppings), and allowed parents to edit entries during the day, thereby reducing reliance on memory. To support non-Danish families, we provided text instructions in Arabic and English and video instructions in English, and the software interface was available in 10 languages. However, the food item list remained in Danish which may have challenged families with other language backgrounds. In conclusion, the overall adherence to the Danish FBDG and NNR2023 was relatively high in the examined large group of Danish 6-9-year-old children, but challenges remain particularly in terms of intakes of fruit and vegetables, fish, meat, SFA, and iron. Sociodemographic differences in dietary intake were especially related to children’s age, parental education level, and residential area, but not to weight status. These findings highlight the need for early interventions to improve children’s dietary quality while also considering strategies for specific sociodemographic groups where improvements are needed the most. Abbreviations BMR Basal metabolic rate DHA Docosahexaenoic acid EI Energy intake EPA Eicosapentaenoic acid FBDG Food Based Dietary Guidelines FFQ Food frequency questionnaire FRIDA The Danish food composition database GHK Generation Healthy Kids NNR2023 Nordic Nutrition Recommendations n-3 LCPUFA n-3 long chain polyunsaturated fatty acids SFA Saturated fat vitD Vitamin D Declarations Ethical approval: The study was approved by the Ethics Committee of Southern Denmark (S-20220094). Consent to participate: All children received oral information, and custody holders received both written and oral information about the study before custody holders gave written informed consent for their child to participate. Availability of data and materials: The datasets analyzed in the current study are not publicly available due to ethical restrictions, but they are available from the corresponding author upon reasonable request. Conflict of interest: The authors declare that they have no conflict of interest. Funding: The Generation Healthy Kids study was funded by the Novo Nordisk Foundation (grant no. NNF22SA0077224). Acknowledgements: The authors would like to thank the study participants and local partners within schools and local communities for fruitful collaborations. We also acknowledge the valuable contribution of other community members, GHK colleagues and students. Authors’ contributions: Conceptualization: RFK, UT, CTD. Methodology: FH, AGE, LL, CM, CTD. Formal analysis and investigation: FH, AGE, MRL, KDS, RL. Writing – original draft: FH, AGE. Writing – review and editing: LL, CM, MRL, KDS, RL, RFK, UT, CTD. Funding acquisition: CM, RFK, UT, CTD. Supervision: LL, CM, CTD. References Nguyen AN, Jen V, Jaddoe VWV, et al (2020) Diet quality in early and mid-childhood in relation to trajectories of growth and body composition. 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Characteristics of all children (n=1094) Demographics and anthropometrics Sex, % girls / % boys 48.8 / 51.2 Age, y 7.8±0.6 Height, cm 130.3±6.7 Weight, kg 26.7 (24.1-30.4) BMI, kg/m 2 15.7 (14.8-17.2) BMI z-score 0.2±1.1 Weight status Underweight 95 (8.7) Normal weight 858 (78.4) Overweight 141 (12.9) Parental education level Short education (≤13 y) 170 (15.5) Medium education (14-17 y) 468 (42.8) Long education (≥18 y) 364 (33.3) Unanswered 92 (8.4) Origin Danish descendants 921 (84.2) Non-Danish descendants 85 (7.8) Unanswered 88 (8.0) Rurality Urban 657 (60.1) Rural 437 (39.9) Dietary reporting Under-reporters 184 (16.8) Acceptable reporters 886 (81.0) Over-reporters 24 (2.2) Data are presented as mean±SD for continuous, normally distributed variables, median (IQR) for continuous, skewed variables and n (%) for categorical variables Table 2. Dietary intake (n=886) and nutrient biomarkers (n=264-283) of acceptable reporters. Boys Girls Total Energy and macronutrient intake Energy, MJ 7.3±1.4 6.5±1.2*** 7.0±1.3 Carbohydrates, E% 49.9±5.5 50.4±5.6 50.2±5.6 Dietary fiber, g/MJ 2.7±0.7 2.6±0.7 2.7±0.7 Added sugar, E% 8.0 (5.2-11.2) 8.8 (5.4-12.2)* 8.5 (5.4-11.7) Fat, E% 32.9±5.2 32.7±5.0 32.8±5.1 SFA, E% 11.2±2.5 11.2±2.5 11.2±2.5 Monounsaturated fat, E% 11.2±2.6 11.0±2.4 11.1±2.5 Polyunsaturated fat, E% 5.5±1.4 5.4±1.3 5.5±1.4 Protein, E% 15.0±2.9 14.8±2.8 14.9±2.8 Intake of food groups Fruit and vegetables, g/d 218 (130-327) 228 (143-326) 222 (137-326) Wholegrains, g/d 53 (33-76) 39 (22-60)*** 47 (28-70) Fish a , g/d 12 (6-19) 12 (6-18) 12 (6-19) Oily fish a , g/d 4 (0-8) 4 (1-7) 4 (1-7) Milk and dairy products, g/d 217 (120-363) 188 (90-316)* 203 (104-343) Meat and meat products, g/d 82 (52-124) 67 (44-101)*** 75 (47-114) Micronutrient intake n-3 LCPUFA a (mg/d) 120 (42-242) 117 (54-231) 117 (44-238) Iron (mg/d) 7.7±2.0 6.7±1.7*** 7.2±1.9 Food and nutrient biomarkers Total plasma alkylresorcinols b , nmol/L 275 (165-426) 234 (156-350) 248 (160-391) Whole blood EPA+DHA c , FA% 3.2±0.8 3.3±0.8 3.3±0.8 Whole blood hemoglobin e , mmol/L 8.1±0.5 8.1±0.6 8.1±0.5 Serum ferritin d , µg/L 28 (21-38) 28 (21-40) 28 (21-39) Data are presented as mean±SD and median (IQR), when data were normally distributed and skewed, respectively. a Data from FFQ where n=780, b n=264, c n=270, d n=283, e n=277 *P<0.05, ***P<0.001 for differences between boys and girls. Table 3. Children’s adherence to dietary recommendations (n=886) Food group or nutrient Danish FBDG or NNR2023 Daily intake Adherence, n (%) Fruit and vegetables, g/10 MJ ≥600 g/10 MJ 322 (196-472) 104 (11.7) Wholegrains, g/10 MJ ≥75 g/10 MJ 68 (41-99) 394 (44.5) Fish a , g/d ≥35 g/d (Min. 245 g/w) c 12 (6-19) 56 (7.2) Oily fish a , g/d ≥20 g/d (Min. 140 g/w) c 3.7 (0.7-7.2) 46 (5.9) Milk and dairy products, g/d ≥250 g/d 203 (104-343) 356 (40.2) Meat and meat products, g/10 MJ ≤50 g/10 MJ (Max. 350 g/w) 110 (72-164) 125 (14.1) SFA, E% <10 E% 11.1 (9.4-12.8) 288 (32.5) Dietary fiber, g/MJ ≥2 g/MJ 2.7±0.7 731 (82.5) Added sugar, E% <10 E% 8.5 (5.4-11.7) 568 (64.1) Iron, mg/d ≥8 mg/d 7.2±1.9 272 (30.7) VitD supplement during winter b Supplement during winter (Oct-Apr) 487 yes, 307 no 487 (61.3) Daily intakes are presented as median (IQR), mean±SD, and n when data were skewed, normally distributed, and binomial respectively. a Data was derived from the food frequency questionnaire, n=780. b Data was derived from the supplements’ questionnaire, n=794. c The recommendation for fish and oily fish was recalculated to match the average energy intake of the included children. Table 4. Associations between sociodemographic characteristics and dietary intake among children with acceptable dietary reporting and complete data on parental education and country of origin (n = 824). Fruit and vegetables, g/10 MJ Wholegrains, g/10 MJ Fish a , g/d Milk and dairy, g/10 MJ Meat and meat products, g/10 MJ Added sugar, E% SFA, E% Adherence score β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P Sex Girls Ref. <0.001 Ref. <0.001 Ref. 0.727 Ref. 0.943 Ref. 0.091 Ref. 0.008 Ref. 0.409 Ref. 0.874 Boys -59.2 (-86.3, -32.1) 13.6 (7.7, 19.5) -0.4 (-2.6, 1.8) -1.3 (-36.4, 33.8) 8.2 (-1.3, 17.6) -0.9 (-1.6, -0.2) -0.1 (-0.5, 0.2) 0.0 (-0.1, 0.1) Age, y -27.6 (-50.5, -4.7) 0.018 -4.1 (-9.1, 0.9) 0.110 -1.7 (-3.6, 0.1) 0.070 -67.7 (-97.4, -38.1) <0.001 2.8 (-5.2, 10.8) 0.492 0.5 (-0.1, 1.1) 0.075 -0.1 (-0.4, 0.2) 0.648 -0.2 (-0.3, -0.1) <0.001 Weight status Underweight 9.5 (-45.6, 64.5) 0.494 8.9 (-3.2, 20.9) 0.198 3.4 (-1.2, 8.0) 0.234 36.1 (-35.3, 107.6) 0.399 -15.6 (-34.8, 3.7) 0.168 0.0 (-1.4, 1.3) 0.811 0.3 (-0.5, 1.0) 0.557 0.1 (-0.1, 0.3) 0.228 Normal weight Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Overweight -25.1 (-79.5, 29.3) -1.9 (-13.8, 10.0) 0.0 (-4.4, 4.4) -17.0 (-87.6, 53.7) -2.3 (-21.3, 16.7) -0.4 (-1.7, 1.0) -0.2 (-0.9, 0.5) -0.1 (-0.3, 0.1) Parental education Long Ref. 0.148 Ref. 0.003 Ref. 0.124 Ref. 0.820 Ref. 0.003 Ref. 0.652 Ref. 0.923 Ref. <0.001 Medium -23.2 (-59.3, 12.9) -8.2 (-16.1, -0.4) -2.1 (-5.0, -0.8) -3.1 (-49.9, 43.8) 15.2 (2.6, 27.8) 0.0 (-0.8, 0.9) -0.1 (-0.5, 0.4) -0.2 (-0.4, -0.1) Short -38.7 (-89.5, 12.0) -15.2 (-26.3, -4.1) -3.2 (-7.3, 1.0) 13.6 (-52.2, 79.5) 23.0 (5.3, 40.8) 0.5 (-0.8, 1.7) 0.0 (-0.7, 0.6) -0.3 (-0.5, -0.1) Origin Danish Ref. 0.498 Ref. <0.001 Ref. 0.827 Ref. 0.233 Ref. 0.666 Ref. <0.001 Ref. 0.051 Ref. 0.352 Non-Danish 17.5 (-33.2, 68.2) -28.6 (-39.6, -17.5) 0.5 (-3.7, 4.6) 40.0 (-25.8, 105.8) 3.9 (-13.8, 21.6) -2.5 (-3.7, -1.2) 0.6 (0.0, 1.3) -0.1 (-0.3, 0.1) Residential area Urban Ref. <0.001 Ref. 0.017 Ref. 0.255 Ref. 0.444 Ref. 0.362 Ref. 0.002 Ref. 0.026 Ref. 0.150 Rural -52.9 (-81.7, -24.1) 7.7 (1.4, 13.9) -1.4 (-3.7, 1.0) 14.6 (-51.9, 22.8) 4.7 (-5.4, 14.7) 1.1 (0.4,1.8) 0.4 (0.0, 0.8) -0.1 (-0.2, 0.0) Regression coefficients (β), 95% confidence intervals (CI), and P -values were derived from multivariable linear regression models examining the independent associations of sex, age, weight status, parental education level, country of origin, and residential area with intake of selected food groups and nutrients, as well as an overall dietary adherence score. a Fish intake data were derived from the food frequency questionnaire, n=776 Additional Declarations No competing interests reported. Supplementary Files Supplementaryfiles.docx Cite Share Download PDF Status: Published Journal Publication published 16 Jan, 2026 Read the published version in European Journal of Nutrition → 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-7741373","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529933887,"identity":"4da61880-fe60-43d3-8457-08cd18a98e2e","order_by":0,"name":"Frederik Holmegaard","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYBAC9hkMiQ/ALB4QPkCEFp4bDMkGJGthkyBRi3TDs+qCisP2DDxnDBjenCFGi8yBtNszzqQlNvD2GDDOuUGEFnuJhLTbvG02CQz8PAbMPB+IsQWopZj3n4Q9aVqYeRtsGEEOY+YhxmFALcnSPMfSEtt4jhUcnEOU9yVyEj/z1By25+dJ3vjgzTEitAA1JYApNiA+QJQGYJIhVuEoGAWjYBSMWAAAcHgwu4CJmBUAAAAASUVORK5CYII=","orcid":"","institution":"University of Copenhagen","correspondingAuthor":true,"prefix":"","firstName":"Frederik","middleName":"","lastName":"Holmegaard","suffix":""},{"id":529933888,"identity":"612a375e-03ca-4237-b7eb-bacf98cc0112","order_by":1,"name":"Anna Gro Eilersen","email":"","orcid":"","institution":"University of Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"Gro","lastName":"Eilersen","suffix":""},{"id":529933889,"identity":"7f8c0c65-26c9-4619-8359-780bbcb9447b","order_by":2,"name":"Lotte Lauritzen","email":"","orcid":"","institution":"University of Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Lotte","middleName":"","lastName":"Lauritzen","suffix":""},{"id":529933891,"identity":"3690fc18-4765-4c25-9287-bad50c5730b8","order_by":3,"name":"Christian Mølgaard","email":"","orcid":"","institution":"University of Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Mølgaard","suffix":""},{"id":529933892,"identity":"31a241ae-d429-4ac6-819a-03626fe05983","order_by":4,"name":"Ming Rong Liu","email":"","orcid":"","institution":"University of Waterloo","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"Rong","lastName":"Liu","suffix":""},{"id":529933894,"identity":"6295d3f9-4724-40df-a250-95181b3fca0e","order_by":5,"name":"Ken D. 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The Generation Healthy Kids Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiet and nutrient intake in childhood are important for optimal growth, cognitive and bone development, and long-term health\u0026nbsp;[1\u0026ndash;3]. In Western countries children from the age of 2 years are typically advised to follow the same food based dietary guidelines (FBDG) and nutrient recommendations as adults but adjusted to fit their lower total energy requirements [4\u0026ndash;7]. Most dietary recommendations emphasize high intakes of fruit and vegetables, wholegrains and fish while limiting red and processed meats, saturated fat (SFA) and added sugar. Such a dietary pattern has been shown to be associated with reduced overweight and improved cardiometabolic risk markers in children [8\u0026ndash;11], which may influence later risk of lifestyle diseases. Thus, it is of great public health relevance to evaluate children\u0026rsquo;s adherence to dietary recommendations.\u003c/p\u003e\n\u003cp\u003ePrevious dietary surveys have shown that children in Western countries have low adherence to dietary recommendations [4, 12]. A report from the European Food Safety Authority concluded that young children in the EU are at risk of insufficient dietary intakes of iron, vitamin D (vitD), and n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) [13], a concern also evident among Danish children and adolescents [12]. However, the most recent national dietary survey among Danish children was conducted more than 10 years ago and it did not include objective nutrient biomarkers, which are important to verify reported intakes and identify nutrient deficiencies.\u003c/p\u003e\n\u003cp\u003eChildren\u0026rsquo;s dietary intake and adherence to recommendations may be influenced by sociodemographic factors. For instance, children of parents with lower education levels have been shown to consume less fruit and vegetables, fish, and dietary fiber than children of parents with higher education [14, 15], and adherence to the recommendations tends to decline as children approach adolescence [15, 16]. Children\u0026rsquo;s dietary intake may also be associated with other factors such as ethnic origin [17, 18] and rurality [19\u0026ndash;21], although previous findings are inconsistent. As many sociodemographic factors are interrelated, comprehensive investigations that account for multiple factors simultaneously are needed to better understand social disparities in children\u0026rsquo;s food and nutrient intake. Finally, despite the common perception that children with overweight have unhealthy diets, studies on associations between children\u0026rsquo;s diets and weight status or adiposity remain inconclusive [15, 17, 22].\u003c/p\u003e\n\u003cp\u003eThe present study used baseline data from 1094 6-9-year-old children from 23 schools in three of the five regions in Denmark, who participated in the Generation Healthy Kids (GHK) study. GHK was a cluster-randomized, multi-setting, multi-component intervention designed to promote healthy weight development in 1\u003csup\u003est\u003c/sup\u003e and 2\u003csup\u003end\u003c/sup\u003e grade children by focusing on healthy diets, physical activity, sleep, and screen media habits [23].\u003c/p\u003e\n\u003cp\u003eThe primary aim of the present study was to investigate the dietary intake of the children and their adherence to the Danish FBDG and Nordic Nutrition Recommendations (NNR2023). We focused on intake of fruit and vegetables, wholegrains, meat, milk and dairy, fish, SFA, added sugar, n-3 LCPUFA, vitD, and iron. In a subgroup of children, blood biomarkers were used to assess n-3 LCPUFA and iron status and to validate reported intakes of fish and wholegrains. Finally, we explored whether dietary intake and adherence differed by the children\u0026rsquo;s age, sex, parental education level, country of origin, rurality, and weight status.\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003e\u003cu\u003eStudy design and participants\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe present study is a cross-sectional investigation based on baseline data from the GHK study, collected during September-December 2023. The core components of the GHK intervention included a free-of-charge school lunch program, three weekly 40-minute sessions of vigorous physical activity during school hours, and classroom exercises and parent workshops on sleep and screen media use, as previously described [23]. The study was approved by the Ethics Committee of Southern Denmark (S-20220094) and registered at clinicaltrials.gov (NCT 05940675).\u003c/p\u003e\n\u003cp\u003eInitial contact was established with 496 Danish schools from December 2022 to April 2023. Inclusion criteria for schools were: 1) location in The Capital Region, the Zealand Region, or the Region of Southern Denmark, 2) suitable kitchen facilities for school meal preparation. A total of 24 schools were recruited and randomized in clusters 1:1 to the intervention and control. One control school withdrew after randomization and 2006 children in 1\u003csup\u003est\u003c/sup\u003e and 2\u003csup\u003end\u003c/sup\u003e grade were invited from the remaining 23 schools. There were no exclusion criteria for the children; if parents, teachers, or the clinically responsible physician (CM) judged that a child could not participate in certain parts of the intervention or measurements, they could still participate in the rest of the study. All children received oral information, and parents received both written and oral information about the study. Written informed consent for participation was obtained from the parents of 1350 children. Among these, 517 children (from the Capital and Zealand Regions only) also provided separate consent for blood sampling. The present study included the 1094 participating children who had \u0026ge;1 complete day of dietary recording and measurements of height and weight at baseline (\u003cstrong\u003eSupplementary Fig. 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eBackground information\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe children\u0026rsquo;s age was collected from school records, and parents reported their education level and country of origin in an online questionnaire. Education level was reported in seven categories using the International Standard Classification of Education (ISCED97) adapted to a Danish context; 1) Primary education (1-6 years), 2) Lower secondary education (7-10 years), 3) Upper secondary education in high school (10-13 years), 4) Upper secondary vocational education (10-13 years), 5) Short tertiary education (14-16 years), 6) Bachelor\u0026rsquo;s degree or similar (14-17 years), and 7) Master\u0026rsquo;s degree or PhD (18-21 years). These categories were pooled into Short (\u0026le;13 y), Medium (14-17 y), and Long (\u0026ge;18 y) education, and we used the highest level of education in the household for analyses. Children were classified as Danish descendants if one or both parents were born in Denmark, and as non-Danish descendants if both parents were born in other countries. Most non-Danish descendants originated from Eastern Europe (44%) and the Middle East (26%). When data was only available from one parent (n=48), education level and descendance were based on this information. Children\u0026rsquo;s rurality was based on the geographical location of the schools, i.e. urban when located in cities or areas with \u0026ge;10,000 inhabitants or rural when located in towns or areas with \u0026lt;10,000 inhabitants.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eDietary records\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eInformation about the children\u0026rsquo;s diet was collected sequentially at each school during the same period as the clinical measurements, but never on the same day. Parents were asked to record their child\u0026rsquo;s dietary intake prospectively for three consecutive days (two weekdays and one weekend day) using an online self-administered dietary assessment tool (myfood24\u0026reg;, Dietary Assessment Ltd., Leeds, UK).). 24-h dietary recalls in myfood24 have previously been validated against an interviewer-administered 24-h dietary recall in English adolescents [24] and against weighed dietary records and biomarkers in German adults [25]. Each day, parents received a link to the food diary with written guidelines in multiple languages and a video guide in Danish and English, and they had access to support by phone and e-mail. If all three days were not completed, reminder e-mails and text messages were sent to the parents 1-2 weeks later, on the same day(s) of the week.\u003c/p\u003e\n\u003cp\u003eParents entered all food and drink items consumed by their child by searching a joint food database consisting of a Danish (FRIDA), a Swedish (Livsmedelsverket), an English (myfood24), and an American (USDA FoodData central) food composition database. Portion sizes were estimated using portion images, descriptions, household measures, or by weighing if the parents wished so.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEstimation of dietary intake\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFrom the dietary records, daily intakes of the food groups: fruit and vegetables, wholegrains, milk and dairy products, as well as meat and meat products were calculated. For mixed dishes, the contribution from each food group was estimated based on common recipes (e.g. for a stir fry with vegetables 50% was estimated to be vegetables). Wholegrain content was calculated using food specific wholegrain factors (e.g. 0.25 for wholegrain bread and buns, and 0.54 for wholegrain muesli and other breakfast cereals) based on the definitions of the Danish wholegrain labelling [26].\u0026nbsp;Daily intakes of SFA, dietary fiber, and iron were derived directly from myfood24. Intakes of added sugar were estimated as total sugar minus natural sugars (e.g. lactose in dairy) across the categories: sugar and jam, confectionary and chocolate, cakes and desserts, soft drinks, sauces and dips, refined grains, breakfast cereals, and dairy. For food items with missing database information on sugar content, added sugar were estimated from the Danish food composition database (FRIDA) [27] or product labels.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eUnder-, acceptable, and over-reporters of dietary intake\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eChildren were classified as either under-reporters, acceptable reporters, or over-reporters of energy based on the ratio of mean reported energy intake (EI) to estimated basal metabolic rate (BMR) using the cut-offs suggested by Black [28]; under-reporters: EI:BMR\u0026lt;1.09, acceptable reporters: 1.09\u0026lt;EI:BMR\u0026lt;2.26, and over-reporters: EI:BMR\u0026gt;2.26, assuming a physical activity level of 1.6 [7]. BMR was calculated from the Oxford equations [29] using the child\u0026rsquo;s height, weight, sex, and age.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFood Frequency Questionnaire\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTo better assess habitual fish and n-3 LCPUFA intake, we used a self-administered, online food frequency questionnaire (FFQ) that asked specifically about the intake of fish. This fish FFQ was based on a semi-quantitative FFQ developed to assess overall food, energy, and nutrient intake in Denmark [30]. The original FFQ was validated in the Danish Cancer Cohort [31] and the derived fish specific FFQ has previously been validated among children in the FiSK trial [32].\u003c/p\u003e\n\u003cp\u003eParents reported the overall frequency of their child\u0026rsquo;s fish intake during the last month as bread topping and as hot meals, separately, along with intake frequencies for 11 and 13 specific fish types within each meal type, respectively. Each question had seven response options ranging from \u0026ldquo;rarely or never\u0026rdquo; to \u0026ldquo;twice or more per day\u0026rdquo;, which were converted to average daily frequencies. To avoid overestimation, we multiplied the daily frequencies for each fish type with a correction factor, calculated as the recorded frequency of overall fish intake divided by the sum of frequencies for intake of all fish types. Average daily intakes of each fish type were then estimated by multiplying the adjusted frequencies with fish-specific portion sizes (30-50 g for bread toppings and 50-125 g for hot meals) based on validated Danish standard portion sizes [33]. Daily intakes of total, oily, and lean fish were calculated, and intakes of n-3 LCPUFA from fish were estimated using nutritional data from FRIDA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe FFQ also included questions about frequency, type and brand of n-3 LCPUFA and vitD supplements used in the past month and during winter (October-April), respectively. Daily intake of n-3 LCPUFA from supplements was estimated and added to the intake from fish to derive total daily intake. Children were categorized as vitD supplement users during winter when they consumed supplements with \u0026ge;10 \u0026micro;g of vitD on \u0026ge;5 days per week.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eComparison with dietary recommendations\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eChildren\u0026rsquo;s dietary intake was compared with the official dietary recommendations in Denmark at the time of data collection: the Danish FBDG 2021 and the NNR2023. The FBDG provide recommended intakes of food groups in a 10 MJ diet, i.e. \u0026ge;600 g/d fruit and vegetables, \u0026ge;75 g/d wholegrains, \u0026ge;350 g/week fish of which \u0026ge;200 g should be oily fish, \u0026ge;250 g/d milk and dairy, and \u0026le;350 g/week meat and meat products. To compare directly with the FBDG and account for differences in EI, all food group intakes except fish and dairy were converted to g/10 MJ. For fish, the recommended intake was scaled to match the children\u0026rsquo;s mean reported EI and for dairy, Danish children are recommended to consume the same amount as adults despite a lower EI [6]. Nutrient intakes were converted to E% and g/MJ, as appropriate, for comparison with the NNR2023, e.g. \u0026lt;10 E% added sugar, \u0026lt;10 E% SFA, \u0026ge;2 g/MJ dietary fiber, and \u0026ge;9 mg/d iron.\u003c/p\u003e\n\u003cp\u003eTo assess overall adherence to the dietary recommendations, a dietary adherence score was constructed based on seven key components: fruit and vegetables, wholegrains, fish, milk and dairy products, meat and meat products, added sugar, and SFA. For each component, a continuous score was calculated as the ratio of reported to recommended intake, capped at 1 for intakes meeting or exceeding the recommendations. The scores for meat, added sugar, and SFA were inverted, so lower intakes resulted in higher scores. The overall adherence score was calculated as the sum of scores for all components, ranging from 0 to 7, with higher scores indicating better adherence to the dietary recommendations.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eClinical measurements and blood sampling\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eClinical measurements and blood sampling were conducted in accordance with standard operating procedures on two separate school days by trained members of the research team. On the first day, children\u0026rsquo;s height and weight were measured. Height was determined as the mean of three measurements to the nearest 0.1 cm using a portable stadiometer (Seca 217, Seca, Germany), and weight was measured to the nearest 0.1 kg using a digital scale (InBody 270, InBody Co Ltd., California, USA). Children wore light clothing and were instructed to empty their bladder before being weighed. Sex- and age-adjusted z-scores for body mass index (BMI) was calculated using the WHO AnthroPlus software (v1.0.4, Department of Nutrition, WHO, Geneva, Switzerland) and the International Obesity Task Force (IOTF) LMS-curves [34].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eChildren were categorized as underweight, normal weight, and overweight as determined by age- and sex-specific cut-offs [34] for the IOTF BMI z-score.\u003c/p\u003e\n\u003cp\u003eOn the second day, blood samples were drawn from an antecubital vein before 10:30 am after an overnight fast. In total 347 children had a blood sample drawn and 325 of them (93.7%) confirmed fasting except for 1-2 glasses of water. Local anesthetic patches (EMLA, Astra Zeneca AB, S\u0026ouml;dert\u0026auml;lje, Sweden) were provided beforehand and applied by the parents in the morning.\u003c/p\u003e\n\u003cp\u003eWhole blood for fatty acid analysis was collected with lithium heparin, and 500 \u0026micro;L was transferred to a cryotube with the antioxidant 2,6-di-tert-butyl-4-methylphenol (butylated hydroxytoluene; Sigma-Aldrich, St. Louis, MO, USA) and kept on dry ice. Additional blood collected in tubes with EDTA or clot activator was kept at room temperature and centrifuged at 2000 x g at 4\u0026deg;C for 10 min within 6 h after blood sampling at the Department of Nutrition, Exercise, and Sports (NEXS), University of Copenhagen. All samples were stored at -80\u0026deg;C until analysis.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAnalysis of blood samples\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWhole blood EPA+DHA:\u003c/em\u003e Whole blood fatty acid composition was analyzed within 7 months by gas chromatography at the Department of Kinesiology and Health, University of Waterloo, ON, Canada, as previously described [35]. Briefly, lipids were extracted with chloroform and methanol containing an internal standard (22:3n-3 ethyl ester, Nu-Chek Prep Inc., Elysian, MN), and fatty acid methyl esters were generated using 14% boron trifluoride (BF\u003csub\u003e3\u003c/sub\u003e) in methanol and heating for 1 h at 95 \u0026deg;C on a heating block. The fatty acid methyl esters were then determined using a Scion 8300 gas chromatograph (Scion Instruments Canada, Edmonton, AB, Canada) with a DB-FFAP capillary column (15 m x 0.1 mm ID x 0.1 \u0026micro;m film thickness; J\u0026amp;W Scientific from Agilent Technologies, Mississauga, ON, Canada). In the initial analysis, some samples had very low fatty acid concentrations (\u0026lt;0.5 \u0026micro;g/mg) with high SFA:LCPUFA ratios (\u0026gt;6.0), indicating sample oxidation, as previously described [36]. Therefore, all samples were reanalyzed or reintegrated, and the results with the lowest SFA:LCPUFA ratio for each sample were included in the statistical analysis. Samples with SFA:LCPUFA ratios \u0026gt;1 SD above or below the mean in both runs (n=15, 4%) were excluded. The relative whole blood content of Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) as a percentage of all fatty acids (FA%) was used as a measure of n-3 LCPUFA status. To allow comparison with omega-3-index cut-offs (\u0026lt;4% [undesirable], 6%, and \u0026gt;8% [optimal])\u003csup\u003e\u0026nbsp;\u003c/sup\u003e[37], whole blood EPA+DHA was converted to red blood cell equivalents as suggested by Stark et al. [38].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlasma alkylresorcinols:\u0026nbsp;\u003c/em\u003ePlasma alkylresorcinol concentrations were analyzed at the Department of Life Sciences at Chalmers University of Technology, Sweden by liquid chromatography and tandem mass spectrometry on a QTRAP 6500+ (AB SCIEX, Marlborough, MA, USA) as previously described [39]. Total alkylresorcinol concentration \u0026ndash; a marker of wholegrain wheat and rye intake \u0026ndash; was used as a biomarker for validating the reported wholegrain intake. The intra- and inter-assay variability were 4.7-7.8% and 10.5-19.0% for each alkylresorcinol homologue, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIron status:\u003c/em\u003e Whole blood hemoglobin was analyzed on a Sysmex KX 21N Analyzer (Sysmex Corporation, Hyogo, Japan) at NEXS within 6 h after blood sampling. Serum ferritin was analyzed on an IMMULITE 2000 Analyzer (Siemens Healthcare GmbH, Erlangen, Germany) at the Department of Clinical Biochemistry at Rigshospitalet, Copenhagen within one year after sampling.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eStatistical analysis\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using R (version 4.2.1). Crude odds ratios (OR) and a logistic regression model for age were used to assess sociodemographic differences between children included and not included in the present study. The sociodemographic characteristics of included children were compared to those of the Danish background population using chi-square tests.\u003c/p\u003e\n\u003cp\u003eDietary intake, nutrient status, and adherence to dietary recommendations are presented as mean \u0026plusmn; SD for normally distributed data and median (IQR) for skewed data. All mean and median intakes include children with zero intakes. Food and nutrient intakes were compared between boys and girls by Student\u0026rsquo;s unpaired t-test and Mann-Whitney U-test when data were normally distributed and skewed, respectively.\u003c/p\u003e\n\u003cp\u003eChildren with acceptable dietary reporting and data on parental education and country of origin were included in the primary multivariable linear regression models to explore associations between sociodemographic factors (age, sex, weight status, parental education level, country of origin, and rurality) and intakes of key food groups and nutrients. The dietary components included in the models \u0026ndash; fruit and vegetables, wholegrains, fish, milk and dairy products, meat and meat products, added sugar, and SFA \u0026ndash; represent major targets for dietary improvement among children and are linked to both potential nutrient inadequacies and chronic disease prevention goals. All sociodemographic factors were included as fixed effects to assess the independent association of each predictor with dietary intakes. In secondary sensitivity analyses, under-reporters and over-reporters were included in all models first and subsequently children with unanswered parental education and ethnic origin were included. Among the subgroup with blood samples, models of nutrient biomarkers were used as sensitivity analyses for associations with wholegrains and fish. Model assumptions were evaluated by visual inspection of Q-Q plots and scatter plots of residuals.\u003c/p\u003e\n\u003cp\u003eThe FFQ-reported intakes of fish and n-3 LCPUFA and the registered intakes of wholegrains were validated against whole blood EPA+DHA and total plasma alkylresorcinols, respectively, using Spearman rank correlations. Furthermore, the dose-response relationships between estimated intakes of n-3 LCPUFA and wholegrains were fitted against their respective biomarkers using both linear and logarithmic regression. The resulting plots were compared by visual inspection and R\u003csup\u003e2\u003c/sup\u003e-values.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cu\u003eChildren\u0026rsquo;s characteristics and representativeness\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eOf the 1350 children originally included in GHK, 1142 children had at least one complete day of dietary recording at baseline. Ten were excluded from the analyses due to extreme dietary recordings (mean EI \u0026lt;2000 or \u0026gt;15,000 KJ/day), and 38 were excluded due to missing anthropometric measurements (Supplementary Fig. 1). The 256 non-included children were more likely to have parents with short education (OR, 95% CI: 2.83, 1.75-4.61, P\u0026lt;0.001), be non-Danish descendants (2.55, 1.58-4.04, P\u0026lt;0.001), reside in urban areas (1.37, 1.03-1.83, P=0.031) and have overweight (1.65, 1.09-2.45, P=0.015), but did not differ with regards to sex and age (P\u0026gt;0.65).\u003c/p\u003e\n\u003cp\u003eBoys and girls were equally represented among the included children (\u003cstrong\u003eTable 1\u003c/strong\u003e). Most children had normal weight, and the prevalence of underweight and overweight were comparable to the national numbers reported among Danish 6-7-year-olds (\u0026chi;\u003csup\u003e2\u003c/sup\u003e=0.5, P=0.795) [40]. Only 15.5% were from households with\u0026nbsp;\u0026le;13 years of education compared to 39.9% among all Danish families with children (\u0026chi;\u003csup\u003e2\u003c/sup\u003e=12.3, P=0.002) [41]. There was also a lower proportion of non-Danish descendants (7.8% vs. 16.2% among Danish 6-9-year-olds, \u0026chi;\u003csup\u003e2\u003c/sup\u003e=43.5, P\u0026lt;0.001) [42], whereas the proportion of children residing in urban areas was similar to the general population (60.1% vs. 58.3%, \u0026chi;\u003csup\u003e2\u003c/sup\u003e=1.2, P=0.265) [43].\u003c/p\u003e\n\u003cp\u003eIn total, 870 (80%), 128 (12%), and 96 (9%) children had three, two, and one complete dietary recording days, respectively, and more than 80% of the children (n=886) were classified as acceptable reporters (1.09\u0026lt;EI:BMR\u0026lt;2.26). Over- and under-reporters were more likely to have parents with short education (OR, 95% CI: 2.14, 1.37-3.32, P\u0026lt;0.001), be non-Danish descendants (1.73, 1.03-2.82, P=0.030), be boys (1.45, 1.08-1.96, P=0.014), and have overweight (2.55, 1.73-3.74, P\u0026lt;0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eDietary intake and nutrient status\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAcceptable reporters consumed 7.0\u0026plusmn;1.3 MJ/d (\u003cstrong\u003eTable 2\u003c/strong\u003e), which is within the estimated energy requirement range (6.3-7.8 MJ) for 6-9-year-old children with average physical activity levels (PAL=1.6) according to NNR2023 [7]. Boys had higher EI than girls, but the relative macronutrient intakes were similar in boys and girls and aligned with the 45-60 E%, 25-40 E% and 10-20 E% recommended for carbohydrates, fat and protein [7], respectively. Boys had higher absolute intakes of wholegrains, dairy, meat and iron, but did not differ from girls with regards to the other investigated food groups or n-3 LCPUFA intake (Table 2). In the subgroup with blood samples (n=285), nutrient biomarkers did not differ by sex (Table 2). Iron deficiency (serum ferritin \u0026lt;15 \u0026micro;g/L) was observed in 7.8% of the children, and 0.4% (n=1) had anemia (hemoglobin \u0026lt;6.5 mmol/L). n-3 LCPUFA status was generally low as 39.3% had an omega-3 index \u0026lt;4% (undesirable), and only 0.4% had an index \u0026gt;8% (optimal). Including over- and under-reporters did not change the results (\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eValidation of parent-reported wholegrain, fish, and n-3 LCPUFA intakes\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIn the subgroup with blood samples, there was a dose-response relationship between wholegrain intake and total alkylresorcinols (\u003cstrong\u003eSupplementary Fig. 2\u003c/strong\u003e), and parent-reported wholegrain intake was moderately correlated with plasma total alkylresorcinols (r=0.33, P\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eAbsolute intakes of fish, oily fish and total n-3 LCPUFA from fish and supplements were moderately correlated with whole blood EPA+DHA (r=0.30-0.32, all P\u0026lt;0.001), whereas the correlation for lean fish, which contains little n-3 LCPUFA, was weaker (r=0.21, P\u0026lt;0.05). The dose-response relationship between total n-3 LCPUFA intake and whole blood EPA+DHA was best fitted by a logarithmic function (\u003cstrong\u003eSupplementary Fig. 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAdherence to dietary recommendations\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe average adherence score was 4.7\u0026plusmn;0.8 out of 7.0, indicating that children\u0026rsquo;s overall adherence to the dietary recommendations was fairly good. However, as shown in \u003cstrong\u003eTable 3\u003c/strong\u003e, less than 15% of the children adhered to the dietary recommendations for fruit and vegetables per 10 MJ EI and for fish when the recommendation was scaled to their mean EI. The low intake of fish, especially oily fish, was in line with the low whole blood n-3 LCPUFA observed (Table 2). The adherence with recommendations for intakes of meat and SFA was also low, as less than one third of the children consumed less than 50 g/10 MJ and 10 E%, respectively. Almost half of the children met the recommendations for wholegrains and dairy, and more than 60% adhered to the recommendations for added sugar, dietary fiber, and vitD supplementation during winter (Table 3). Including children with over- and underreporting in the analyses did not change the results (\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eSociodemographic determinants of dietary intake\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIn the primary multivariable linear regression models with acceptable reporters, overall adherence to dietary recommendations decreased with age (\u003cstrong\u003eTable 4\u003c/strong\u003e). This was mainly due to lower intakes of fruit and vegetables and dairy as well as tendencies to lower fish and higher sugar intake with age. The associations for fruit and vegetables, dairy and fish were supported in the sensitivity analyses with inclusion of under- and over-reporters and those with missing sociodemographic data, but the significance of the association for sugar decreased somewhat (\u003cstrong\u003eSupplementary Table 3 and 4\u003c/strong\u003e). Furthermore, the sensitivity analysis among the subgroup with blood samples showed a tendency to increased whole blood EPA+DHA with age, thus not supporting a decline in fish intake with age (\u003cstrong\u003eSupplementary Table 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eLonger parental education was associated with better overall adherence to the dietary recommendations, mainly due to higher intakes of wholegrains and lower intakes of meat. The association with wholegrain intake was supported by a positive association between parental education and plasma total alkylresorcinols (Supplementary Table 5). The sensitivity analyses including more children also supported the association with wholegrains (Supplementary table 3 and 4), but they did not provide clear support for the association with meat.\u003c/p\u003e\n\u003cp\u003eThe overall adherence score did not differ by residential area, origin or sex in the primary or any of the sensitivity analyses (Table 4; Supplementary Table 4 and 5). All of the analysis did, however, show that children in \u0026nbsp;rural areas consumed less fruit and vegetables, and more added sugar and SFA but also more wholegrains than urban children. Non-Danish descendants were also consistently shown to have a lower intake of wholegrains, but their intake of added sugar was also lower than in those with Danish descendance. Consistent associations were furthermore seen for sex, with higher consumption of wholegrains and less added sugar, but a concomitantly reduced intake of fruit and vegetables in boys relative to girls. Weight status was not associated with intake of any of the food groups or nutrients nor with the overall adherence score in the primary analysis, but in the sensitivity analyses meat intake was higher, whereas added sugar and SFA intake tended to be lower with increasing weight status.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn a large group of Danish 6-9-year-olds, we showed that most children consumed less fruit and vegetables and fish as well as more meat than recommended, whereas almost half of the children reached the recommended level for wholegrain intake and more than 60% adhered to the recommendations for added sugar. Overall adherence to the dietary recommendations improved with higher parental education level and decreased with age. Children living in rural areas had lower adherence to the recommendations for fruit and vegetables, added sugar, and SFA, whereas the wholegrain intake was lower among urban children and Danish descendants.\u003c/p\u003e\n\u003cp\u003eThe low intake of fruit and vegetables aligns with previous findings among Western children [12, 17, 44]. This is a concern as fruit and vegetables are key sources of micronutrients and dietary fiber and have been linked to lower risk of overweight [45] and improved cardiometabolic risk profile in children [10]. In contrast to the relatively high fish intake and n-3 LCPUFA status among children in Norway [46, 47], fish intake in the present study was very low as previously seen in Denmark [12, 32, 44], the US [4], and the UK [17]. This finding was supported by the low whole blood EPA+DHA which also aligned with previous reports in Danish children [32, 48]. Increasing the n-3 LCPUFA status of Danish children would be desirable, as this has been linked to better cognitive function [49] and a more favorable cardiometabolic risk profile [48], and both of these outcomes were found to be improved by an oily fish intake of \u0026asymp;300 g/wk in our previous randomized trial in Danish children [8, 50]. The persistent low intakes of fruit and vegetables and fish may reflect barriers such as cost, accessibility, preferences, time constraints, and cooking skills [32, 51]. In contrast, intake of meat was high, as also seen in the latest national dietary survey [12], suggesting a continued predominance of animal-based foods in the Danish diet despite increased trends towards plant-based diets.\u003c/p\u003e\n\u003cp\u003eIn general, wholegrain intake was high with a median intake approximately three times greater than among children in the UK and the US [4, 52]. Even though Denmark has one of the highest wholegrain recommendations globally [53], nearly half of the children met the recommendation, consistent with the latest national dietary survey [12]. This is likely beneficial for long-term health, as a high wholegrain intake has been shown to improve the plasma lipid profile in children [9] and to be linked to reduced risk of cardiovascular disease and mortality in adults [54]. Wholegrain intakes have increased substantially in Denmark since the early 2000\u0026rsquo;s [26], likely due to initiatives such as the Danish Wholegrain Partnership, which has improved the availability, labeling, and public awareness of wholegrain products. However, wholegrain intake among non-Danish descendants remained particularly low in the present study, with only 21.5% meeting the recommendation. One explanation may be that wholegrain products, such as sour dough rye bread and rolled oats, are distinctive characteristics of the Danish food culture, which may take time to adopt among immigrant populations. The Danish recommendation for wholegrains was raised to 90 g/10 MJ in June 2024, and when compared to this update, 31.3% of the children still adhered.\u003c/p\u003e\n\u003cp\u003eSurprisingly, 64% of the children adhered to the recommendation of limiting added sugar to \u0026lt;10 E%. This is a marked improvement compared to the 49% and 34% of 4-14-year-olds reported in the Danish national surveys from 2011-2013 and 2003-2008, respectively [12, 55]. Despite efforts to expand the myfood24 database with added sugar values to minimize underestimation, some underreporting either due to incomplete databases or parental reporting cannot be ruled out [56]. Nevertheless, similar downward trends in sugar intake have been observed in the US and Germany since the early 2000s, especially between 2010-2016 [57, 58]. However, unlike in the present study, children\u0026rsquo;s mean and median intakes of added sugar still exceeded the recommendation in these populations [57, 58].\u003c/p\u003e\n\u003cp\u003eThe reported iron intake was somewhat low considering the children\u0026rsquo;s high meat consumption, and when compared to the recommended intake (8.0 mg/d for 7-8-year-olds [7]) and the latest national dietary survey (6.7\u0026plusmn;1.7 mg/d vs. 8.9\u0026plusmn;2.1 mg/d and 7.7\u0026plusmn;2.0 mg/d vs. 9.6\u0026plusmn;2.4 mg/d in 6-9-year-old girls and boys, respectively [12]). However, both hemoglobin and ferritin levels were within the recommended ranges and only 8% of the children had iron deficiency, suggesting that the intake was adequate for most children. The intake of iron might be underestimated, but the findings may also indicate that the high bioavailability of iron from meat, or increased iron absorption seen at low intakes, compensated for the low total intake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsistent with previous studies [14\u0026ndash;16], adherence to dietary recommendations improved with higher parental education level and decreased with age. Similar to the present study, parental education level was also associated with wholegrain intake in the Danish national survey 20 years ago, although only among girls [14],\u0026nbsp;and the observed tendency for reduced meat intake with longer parental education aligns with findings from the EU and the UK, particularly for processed meats [59, 60]. These associations may reflect greater health- and environmental awareness among highly educated parents. The decline in adherence to dietary recommendations with increasing age was evident despite a narrow age range in the present study [15, 16]. Early school years may be a period of rapid dietary changes, as children have to adapt to new environments and engage in new social relationships, which may prompt them to align their food preferences with perceived peer norms to ensure social acceptance [61].\u003c/p\u003e\n\u003cp\u003eThe lower fruit and vegetable intake and higher sugar intake among rural compared to urban children are consistent with studies from Europe [19]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand Canada [20], whereas the higher SFA intake has not previously been reported. Rural children also had a higher wholegrain intake, which may reflect a stronger adherence to the Danish tradition of having wholegrain rye bread for lunch in rural areas as also seen in Finland [62]. In contrast, an Australian study found that children residing in remote areas had overall healthier eating habits and consumed more fruit, and less takeaway foods and unhealthy snacks [21]. Besides differences in the definitions of urban and rural areas and the remoteness of the rural areas in the studies, the discrepancies could relate to country-specific differences in rural versus urban food environments.\u003c/p\u003e\n\u003cp\u003eA major strength of the present study was the large sample size of 1094 children which exceeded that of the national Danish dietary surveys [12]. We included participants from a wide geographic area across Denmark, who were representative of the general population in terms of sex, weight status, and residential area. Non-Danish descendants were better represented than in the national surveys [12], but they were still under-represented as were children from shorter educational backgrounds. This may have led to an overestimation of the adherence to the dietary recommendations and limited our ability to detect differences between groups, particularly by origin. The detailed dietary records of the whole diet combined with the fish-specific FFQ allowed for a comprehensive assessment of habitual dietary intake, which was validated against objective biomarkers. A three-day recording period was selected to ensure feasibility, particularly among less advantaged families, but it was not suited for evaluating micronutrient intake [63]. The online recording tool helped structure the recordings, had built-in reminders (e.g. for snacks and toppings), and allowed parents to edit entries during the day, thereby reducing reliance on memory. To support non-Danish families, we provided text instructions in Arabic and English and video instructions in English, and the software interface was available in 10 languages. However, the food item list remained in Danish which may have challenged families with other language backgrounds.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the overall adherence to the Danish FBDG and NNR2023 was relatively high in the examined large group of Danish 6-9-year-old children, but challenges remain particularly in terms of intakes of fruit and vegetables, fish, meat, SFA, and iron. Sociodemographic differences in dietary intake were especially related to children\u0026rsquo;s age, parental education level, and residential area, but not to weight status. These findings highlight the need for early interventions to improve children\u0026rsquo;s dietary quality while also considering strategies for specific sociodemographic groups where improvements are needed the most.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBasal metabolic rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDHA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDocosahexaenoic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEnergy intake\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEPA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEicosapentaenoic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFBDG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e Food Based Dietary Guidelines\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFFQ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFood frequency questionnaire\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFRIDA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThe Danish food composition database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGHK\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGeneration Healthy Kids\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNNR2023\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNordic Nutrition Recommendations\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003en-3 LCPUFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003en-3 long chain polyunsaturated fatty acids\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSaturated fat\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003evitD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVitamin D\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e The study was approved by the Ethics Committee of Southern Denmark (S-20220094).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eAll children received oral information, and custody holders received both written and oral information about the study before custody holders gave written informed consent for their child to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The datasets analyzed in the current study are not publicly available due to ethical restrictions, but they are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe Generation Healthy Kids study was funded by the Novo Nordisk Foundation (grant no. NNF22SA0077224).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The authors would like to thank the study participants and local partners within schools and local communities for fruitful collaborations. We also acknowledge the valuable contribution of other community members, GHK colleagues and students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eConceptualization: RFK, UT, CTD. Methodology: FH, AGE, LL, CM, CTD. Formal analysis and investigation: FH, AGE, MRL, KDS, RL. Writing \u0026ndash; original draft: FH, AGE. Writing \u0026ndash; review and editing: LL, CM, MRL, KDS, RL, RFK, UT, CTD. Funding acquisition: CM, RFK, UT, CTD. Supervision: LL, CM, CTD.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNguyen AN, Jen V, Jaddoe VWV, et al (2020) Diet quality in early and mid-childhood in relation to trajectories of growth and body composition. Clin Nutr 39:845\u0026ndash;852. https://doi.org/10.1016/j.clnu.2019.03.017\u003c/li\u003e\n\u003cli\u003eCohen JFW, Gorski MT, Gruber SA, et al (2016) The effect of healthy dietary consumption on executive cognitive functioning in children and adolescents: A systematic review. Br J Nutr 116:989\u0026ndash;1000\u003c/li\u003e\n\u003cli\u003eFuntikova AN, Navarro E, Bawaked RA, et al (2015) Impact of diet on cardiometabolic health in children and adolescents. Nutr J 14:118. https://doi.org/10.1186/s12937-015-0107-z\u003c/li\u003e\n\u003cli\u003eUSDA (2020) Dietary Guidelines for Americans 2020 - 2025\u003c/li\u003e\n\u003cli\u003ePublic Health England (2018) The Eatwell Guide\u003c/li\u003e\n\u003cli\u003eDanish Veterinary and Food Administration (2021) The Official Dietary Guidelines - good for health and climate. Glostrup, Denmark\u003c/li\u003e\n\u003cli\u003eBlomhoff R, Andersen R, Arnesen EK, et al (2023) Nordic Nutrition Recommendations 2023. 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Public Health Nutr 14:2037\u0026ndash;2048. https://doi.org/10.1017/S136898001100036X\u003c/li\u003e\n\u003cli\u003eLandwehr SC, Hartmann M (2024) Is it all due to peers? The influence of peers on children\u0026rsquo;s snack purchase decisions. Appetite 192:107111. https://doi.org/10.1016/j.appet.2023.107111\u003c/li\u003e\n\u003cli\u003ePr\u0026auml;tt\u0026auml;l\u0026auml; R, Helasoja V, Mykk\u0026auml;nen H (2001) The consumption of rye bread and white bread as dimensions of health lifestyles in Finland. Public Health Nutr 4:813\u0026ndash;819. https://doi.org/10.1079/phn2000120\u003c/li\u003e\n\u003cli\u003eBasiotis PP, Welsh SO, Cronin FJ, et al (1987) Number of Days of Food Intake Records Required to Estimate Individual and Group Nutrient Intakes with Defined Confidence. J Nutr 117:1638\u0026ndash;1641\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"397\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Characteristics of all children (n=1094)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics and anthropometrics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eSex, % girls / % boys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e48.8 / 51.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e7.8\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eHeight, cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e130.3\u0026plusmn;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eWeight, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e26.7 (24.1-30.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e15.7 (14.8-17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eBMI z-score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e0.2\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eUnderweight\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e95 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eNormal weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e858 (78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e141 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParental education level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eShort education (\u0026le;13 y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e170 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eMedium education (14-17 y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e468 (42.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eLong education (\u0026ge;18 y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e364 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eUnanswered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e92 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrigin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eDanish descendants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e921 (84.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eNon-Danish descendants\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e85 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eUnanswered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e88 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRurality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e657 (60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e437 (39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary reporting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.9824%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eUnder-reporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e184 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eAcceptable reporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e886 (81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 69.0176%;\"\u003e\n \u003cp\u003eOver-reporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.9824%;\"\u003e\n \u003cp\u003e24 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100%;\"\u003e\n \u003cp\u003eData are presented as mean\u0026plusmn;SD for continuous, normally distributed variables, median (IQR) for continuous, skewed variables and n (%) for categorical variables\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDietary intake (n=886) and nutrient biomarkers (n=264-283) of acceptable reporters.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergy and macronutrient intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eEnergy, MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e7.3\u0026plusmn;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e6.5\u0026plusmn;1.2***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e7.0\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eCarbohydrates, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e49.9\u0026plusmn;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e50.4\u0026plusmn;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e50.2\u0026plusmn;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eDietary fiber, g/MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e2.6\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eAdded sugar, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e8.0 (5.2-11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e8.8 (5.4-12.2)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e8.5 (5.4-11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eFat, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e32.9\u0026plusmn;5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e32.7\u0026plusmn;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e32.8\u0026plusmn;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eSFA, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e11.2\u0026plusmn;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e11.2\u0026plusmn;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e11.2\u0026plusmn;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eMonounsaturated fat, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e11.2\u0026plusmn;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e11.0\u0026plusmn;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e11.1\u0026plusmn;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003ePolyunsaturated fat, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e5.5\u0026plusmn;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e5.4\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e5.5\u0026plusmn;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eProtein, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e15.0\u0026plusmn;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e14.8\u0026plusmn;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e14.9\u0026plusmn;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntake of food groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eFruit and vegetables, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e218 (130-327)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e228 (143-326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e222 (137-326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eWholegrains, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e53 (33-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e39 (22-60)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e47 (28-70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eFish\u003csup\u003ea\u003c/sup\u003e, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e12 (6-19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e12 (6-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e12 (6-19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eOily fish\u003csup\u003ea\u003c/sup\u003e, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e4 (0-8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e4 (1-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e4 (1-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eMilk and dairy products, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e217 (120-363)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e188 (90-316)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e203 (104-343)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eMeat and meat products, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e82 (52-124)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e67 (44-101)***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e75 (47-114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMicronutrient intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003en-3 LCPUFA\u003csup\u003ea\u003c/sup\u003e (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e120 (42-242)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e117 (54-231)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e117 (44-238)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eIron (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e7.7\u0026plusmn;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e6.7\u0026plusmn;1.7***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e7.2\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood and nutrient biomarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eTotal plasma alkylresorcinols\u003csup\u003eb\u003c/sup\u003e, nmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e275 (165-426)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e234 (156-350)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e248 (160-391)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eWhole blood EPA+DHA\u003csup\u003ec\u003c/sup\u003e, FA%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e3.2\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e3.3\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e3.3\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eWhole blood hemoglobin\u003csup\u003ee\u003c/sup\u003e, mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e8.1\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e8.1\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e8.1\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.4933%;\"\u003e\n \u003cp\u003eSerum ferritin\u003csup\u003ed\u003c/sup\u003e, \u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e28 (21-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.3308%;\"\u003e\n \u003cp\u003e28 (21-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8405%;\"\u003e\n \u003cp\u003e28 (21-39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.83159%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eData are presented as mean\u0026plusmn;SD and median (IQR), when data were normally distributed and skewed, respectively.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eData from FFQ where n=780,\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003en=264,\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ec\u003c/sup\u003en=270,\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ed\u003c/sup\u003en=283,\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ee\u003c/sup\u003en=277\u003c/p\u003e\n \u003cp\u003e*P\u0026lt;0.05, ***P\u0026lt;0.001 for differences between boys and girls.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"756\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 756px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Children\u0026rsquo;s adherence to dietary recommendations (n=886)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eFood group or nutrient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eDanish FBDG or NNR2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eDaily intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eAdherence, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eFruit and vegetables, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;600 g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e322 (196-472)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e104 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eWholegrains, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;75 g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e68 (41-99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e394 (44.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eFish\u003csup\u003ea\u003c/sup\u003e, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;35 g/d (Min. 245 g/w)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e12 (6-19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e56 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eOily fish\u003csup\u003ea\u003c/sup\u003e, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;20 g/d (Min. 140 g/w)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e3.7 (0.7-7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e46 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eMilk and dairy products, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;250 g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e203 (104-343)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e356 (40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 228px;\"\u003e\n \u003cp\u003eMeat and meat products, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026le;50 g/10 MJ (Max. 350 g/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e110 (72-164)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e125 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eSFA, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026lt;10 E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e11.1 (9.4-12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e288 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eDietary fiber, g/MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;2 g/MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e731 (82.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eAdded sugar, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026lt;10 E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e8.5 (5.4-11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e568 (64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eIron, mg/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 253px;\"\u003e\n \u003cp\u003e\u0026ge;8 mg/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e7.2\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e272 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eVitD supplement during winter\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eSupplement during winter (Oct-Apr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e487 yes, 307 no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e487 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 756px;\"\u003e\n \u003cp\u003eDaily intakes are presented as median (IQR), mean\u0026plusmn;SD, and n when data were skewed, normally distributed, and binomial respectively.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eData was derived from the food frequency questionnaire, n=780.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003eData was derived from the supplements\u0026rsquo; questionnaire, n=794.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ec\u003c/sup\u003eThe recommendation for fish and oily fish was recalculated to match the average energy intake of the included children.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1080\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"36\" style=\"width: 1080px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eAssociations between sociodemographic characteristics and dietary intake among children with acceptable dietary reporting and complete data on parental education and country of origin (n = 824).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 121px;\"\u003e\n \u003cp\u003eFruit and vegetables, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWholegrains, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 104px;\"\u003e\n \u003cp\u003eFish\u003csup\u003ea\u003c/sup\u003e, g/d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 121px;\"\u003e\n \u003cp\u003eMilk and dairy, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 122px;\"\u003e\n \u003cp\u003eMeat and meat products, g/10 MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 112px;\"\u003e\n \u003cp\u003eAdded sugar, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 103px;\"\u003e\n \u003cp\u003eSFA, E%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 112px;\"\u003e\n \u003cp\u003eAdherence score\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026beta;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"27\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-59.2\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-86.3, -32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(7.7, 19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.4\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-2.6, 1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-1.3\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-36.4, 33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-1.3, 17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-1.6, -0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.5, 0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.1, 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-27.6\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-50.5, -4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-4.1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-9.1, 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-1.7\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-3.6, 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-67.7\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-97.4, -38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-5.2, 10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.5\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-0.1, 1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.4, 0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.3, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"27\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9.5\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-45.6, 64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8.9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-3.2, 20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-1.2, 8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-35.3, 107.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-15.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-34.8, 3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-1.4, 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.5, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.1, 0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eNormal weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-25.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-79.5, 29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-13.8, 10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-4.4, 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-17.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-87.6, 53.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-2.3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-21.3, 16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-1.7, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.9, 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.3, 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"27\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParental education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eLong\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"3\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-23.2\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-59.3, 12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-8.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-16.1, -0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-5.0, -0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-3.1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-49.9, 43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e15.2\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.6, 27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.8, 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.5, 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.4, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eShort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-38.7\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-89.5, 12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-15.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-26.3, -4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-7.3, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e13.6\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-52.2, 79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(5.3, 40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.8, 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-0.7, 0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.5, -0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"27\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrigin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDanish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eNon-Danish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-33.2, 68.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-28.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-39.6, -17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-3.7, 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e40.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-25.8, 105.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-13.8, 21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.5\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-3.7, -1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(0.0, 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-0.3, 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"27\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidential area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-52.9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-81.7, -24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7.7\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.4, 13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-1.4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-3.7, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-51.9, 22.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(-5.4, 14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.4,1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(0.0, 0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(-0.2, 0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"36\" style=\"width: 1080px;\"\u003e\n \u003cp\u003eRegression coefficients (\u0026beta;), 95% confidence intervals (CI), and\u0026nbsp;\u003cem\u003eP\u003c/em\u003e-values were derived from multivariable linear regression models examining the independent associations of sex, age, weight status, parental education level, country of origin, and residential area with intake of selected food groups and nutrients, as well as an overall dietary adherence score.\u003cbr\u003e\u003csup\u003ea\u003c/sup\u003eFish intake data were derived from the food frequency questionnaire, n=776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Children’s dietary intake, dietary recommendations, sociodemographic disparities, public health","lastPublishedDoi":"10.21203/rs.3.rs-7741373/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7741373/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eDiet in childhood is important for growth, brain development, and long-term health. Thus, assessing children\u0026rsquo;s adherence to dietary recommendations and identifying sociodemographic groups with low adherence is of great public health relevance. We investigated dietary intake, adherence to recommendations and sociodemographic differences in a large population of Danish children.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe analyzed baseline data from 1094 children aged 6\u0026ndash;9 years from 23 schools across Denmark participating in the Generation Healthy Kids study. Diet was assessed by three-day dietary records and food frequency questionnaires for fish and supplements, focusing on key food groups, macronutrients, and iron. Fasting blood samples were collected from n\u0026thinsp;=\u0026thinsp;347 and analyzed for nutritional biomarkers of fish, wholegrains and iron for validation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverall adherence to dietary recommendations showed a mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD score of 4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 out of 7.0. However, \u0026lt;\u0026thinsp;15% adhered to the recommendations for fruit\u0026thinsp;+\u0026thinsp;vegetables, fish, and meat, and \u0026lt;\u0026thinsp;66% to recommendations for saturated fat (SFA) and iron. Adherence decreased with age and shorter parental education due to lower intakes of fruit\u0026thinsp;+\u0026thinsp;vegetables and dairy with age and less wholegrains and more meat in those with short education (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Also, rural children consumed less fruit\u0026thinsp;+\u0026thinsp;vegetables and more added sugar and SFA than urban, and non-Danish descendants consumed less wholegrains and sugar than Danish (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Weight status was not associated with adherence.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eDanish children had relatively good dietary adherence, but intakes of fruit\u0026thinsp;+\u0026thinsp;vegetables, fish, meat, SFA, and iron remain a concern. Attention should be given to children of older age and short education and rural backgrounds.\u003c/p\u003e","manuscriptTitle":"Do 6-9-Year-Old Children in Denmark Adhere to National Dietary Recommendations and Are There Sociodemographic Disparities? The Generation Healthy Kids Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 12:49:00","doi":"10.21203/rs.3.rs-7741373/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":"2509d444-4bbc-484c-b33b-0fac1f9fb0df","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T17:04:39+00:00","versionOfRecord":{"articleIdentity":"rs-7741373","link":"https://doi.org/10.1007/s00394-025-03863-y","journal":{"identity":"european-journal-of-nutrition","isVorOnly":false,"title":"European Journal of Nutrition"},"publishedOn":"2026-01-16 16:28:59","publishedOnDateReadable":"January 16th, 2026"},"versionCreatedAt":"2025-10-16 12:49:00","video":"","vorDoi":"10.1007/s00394-025-03863-y","vorDoiUrl":"https://doi.org/10.1007/s00394-025-03863-y","workflowStages":[]},"version":"v1","identity":"rs-7741373","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7741373","identity":"rs-7741373","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}