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Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking ( 2 H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.

Additional file 1: Table S1. Original and modified categories of frequency of fish intake in the Tromsø Study. Table S2. Modifications of the frailtyphenotype in the Tromsø7 Study (2015–2016). Table S3. Characteristics of tracking sample in Tromsø4 and Tromsø6 (n=3229). Table S4. Odds ratios (ORs) and 95% confidence intervals (CIs) for fish intake and 8-year follow-up pre-frailty after exclusion of baseline frailty (n = 3219)a. Table S5. Characteristics of participants in Tromsø6 by Tromsø7 participation status (n = 6837)a. Table S6. Odds ratios (ORs) and 95% confidence intervals (CIs) for baseline fish intake and pre-frailty with inverse probability weightsa (n = 6183)b. Table S7. Characteristics of participants in Tromsø6 with complete and incomplete data on fish intake (n = 5750)a. Table S8. Odds ratios (ORs) and 95% confidence intervals (CIs) for patterns of fish intake and pre-frailty using multiple imputation (MI)a (n = 5750)b. Table S9. Onset of physical frailty characteristics in Tromsø7 (n = 4350)a. Table S10. Frailty prevalence in Tromsø7 stratified by age (n = 4350)a.

Source at https://vkm.no/. In 2006, VKM published “A comprehensive assessment of fish and other seafood in the Norwegian diet”. The assessment supported the recommendation from Norwegian Health authorities to eat more fish both for dinner and on sandwiches. In an update of the assessment in 2014 VKM concluded that “the benefits from fish consumption clearly outweigh the negligible risk presented by current levels of contaminants and other undesirable substances in fish”. Because of new knowledge available, the Norwegian Food Safety Authority requested a new benefit and risk assessment of fish in the Norwegian diet in 2019. In the assignment, they asked VKM to answer the following questions: Which health consequences will it have for the Norwegian population if they: Continue with the same fish consumption levels as of today Increase the consumption of fish to match the recommendations given by the Norwegian Directorate of Health

BACKGROUND: Protein intake is suggested as an important dietary factor in the prevention of frailty, however, the infuence of lifelong intake remains unclear. OBJECTIVES: The present study investigated the relationship between daily protein intake and patterns of protein intake over 21 years and the risk of pre-frailty/frailty. DESIGN: Prospective cohort study. SETTING: The population-based Tromsø Study in Tromsø municipality, Norway. PARTICIPANTS: In total, 1,906 women and 1,820 men aged >45 years in 1994 who participated in both Tromsø4 (1994–95) and Tromsø7 (2015–16). MEASUREMENTS: Frailty status in Tromsø7 was measured according to Fried’s phenotype, classifying participants as “robust” (frailty components present: 0), “pre-frail” (1–2) or “frail” (>3). Daily intake of protein was estimated from self-reported habitual dietary intake using food frequency questionnaires and assessed as grams per kilogram bodyweight (g/kg BW) and per megajoule energy intake (g/MJ). The protein–frailty association was assessed via longitudinal and crosssectional multivariable logistic regression analyses. RESULTS: The prevalence of pre-frailty and frailty in this study was 27% and 1.0%, respectively. Longitudinal analysis showed that the odds of pre-frailty/frailty decreased by 57% (odds ratio (OR) = 0.43, 95% confdence interval (CI) = 0.31;0.58, pCONCLUSIONS: Intake of protein in g/kg BW both in mid-life and later in life was inversely associated with pre-frailty/frailty in older adults. This emphasizes the importance of an adequate protein intake to facilitate healthy ageing in Norwegian older adults.

© The Authors 2019, Objective: To evaluate daily eating frequency (main meals and snacks) in relation to weight status in children aged 3–9 years, representative of the Portuguese population. Design: Cross-sectional study. Dietary intake was estimated as the mean of two non-consecutive days of food diaries, followed by face-to-face interviews. Weight and height were measured by trained observers. Eating occasions (EO) were defined by the children’s caregiver; an EO was considered separate if the time of consumption was different from other EO and it provided at least 209 kJ (50 kcal). Main meals defined as ‘breakfast’, ‘lunch’ and ‘dinner’ could be selected only once per day. The remaining EO were considered snacks. The association between eating frequency and overweight/obesity was evaluated through logistic regressions weighted for the population distribution. Setting: National Food, Nutrition and Physical Activity Survey of the Portuguese population, 2015–2016. Participants: Portuguese children aged 3–9 years with complete dietary data and anthropometric measurements (n 517). Results: Overall, the number of daily EO ranged from 3·5 to 11, and on average children had 5·7 daily EO. After adjustment for child’s sex, age and total energy intake, and considering only plausible energy intake reporters, having < 3 snacks/d was positively associated with being overweight/obese (OR = 1·98; 95 % CI 1·00, 3·90), compared with having ≥ 3 snacks/d. Conclusions: Lower daily frequency of EO was associated with increased odds of being overweight or obese in children. A higher eating frequency, maintaining the same energy intake, seems to contribute to a healthy body weight in children., This study had institutional support from the General Directorate of Health (DGS), the Regional Health Administration Departments, the Central Administration of the Health System (ACSS) and the European Food Safety Authority (CFT/EFSA/DCM/2012/01-C03). The researchers acknowledge all these institutions and persons involved in all phases of the IAN-AF 2015–2016, as well as the participants. Financial support: The IAN-AF 2015–2016 received funding from the EEA Grants Program, Public Health Initiatives (grant number PT06-000088SI3). The EEA Grant Program had no role in the design, analysis or writing of this article.

Additional file 4. CDQI score calculation. Detailed description of the CDQI score components and calculations

Additional file 1: Figure S1. Estimated marginal means of the BRA-study, showing vegetables served in the kindergarten departments (n = 34) at baseline and follow-up 1, in relation to what degree the intervention components (posters, supplementary material and 1-day inspirational course) were perceived useful by the kindergarten staff. (Black box) Baseline data, (Orange dotted box) Follow-up 1 data.

Additional file 8. Supplementary table. Relative risk for ADHD diagnosis for one SD increase in PDQI, UPFI and CDQI score

Additional file 1. The Impact of a Community-Oriented Problem-Based Learning Curriculum Reform on the Quality of Primary Care Delivered by Gradua

Additional file 9. Supplementary figure. Relative AME (%) change in ADHD symptom score for one SD increase in PDQI, UPFI and CDQI score, stratified by child sex and maternal ADHD symptoms (0–3, higher score equaling more symptoms)

Additional file 2. PDQI score calculation. Detailed description of the PDQI score components and calculations

Additional file 5. Supplementary figure. Visualization of covariate selection for maternal diet quality during pregnancy as exposure via a Directed Acyclic Graph

Additional file 7. Supplementary table. Absolute AME and corresponding relative AME change in ADHD symptoms for one SD increase in PDQI, UPFI and CDQI score

Additional file 2: Supplementary file 2. Interview guide patients.

Additional file 3. Supplementary Table. Foods and beverages from group 4 in the NOVA classification included in the Ultra-Processed Food Index (UPFI)

In 2019, the Nordic network on dietary surveys compared results regarding 24 h recalls, if the method was used in a systematic Nordic set up. A standardized central food list for 7 days was entered into national nutrients calculation systems and the intakes of individual food groups and nutrients on each day and as a daily average of the 7 days were compared. Results were presented at an online workshop on November 20th, 2020. In addition to the country specific presentations of the analysis, each country also gave a presentation on the latest national dietary survey. Despite standardized input, there were many differences in the results. The presentations on national dietary surveys showed differences and similarities of conducting dietary surveys and elucidated a lot of the common challenges researchers face. Many topics could be further elucidated on future network meetings.

Additional file 6. Supplementary figure. Visualization of covariate selection for child diet quality at 3 years as exposure via a Directed Acyclic Graph.

Additional file 1: Supplementary file 1. Interview guide nurses.