Monitoring dietary intake of sugars in the population’s diet has great importance in evaluating the efficiency of national sugar reduction programmes. The study objective was to provide a comprehensive assessment of dietary sources of added and free sugars to assess adherence to public health recommendations in the UK population and to consider the impact of different sugar definitions on monitoring. The terms “added sugar” and “free sugar” are different sugar definitions which include different sugar components and may result in different sugar intakes depending on the definition. Dietary intake of added sugars, free sugars and seven individual sugar components (sugar from table sugar; other sugars; honey; fruit juice; fruit puree; dried fruit; and stewed fruit) of 2138 males and females (1.5–64 years) from the National Diet and Nutrition Survey (NDNS) 2014–2016, collected using a 4 day estimated food diary, were studied. Added and free sugar intake accounted for 7% to 13% of total energy intake respectively. Major sources of free sugar intake were “cereals and cereal products”, “non-alcoholic beverages”, and “sugars, preserves, confectionery”. Differences between added and free sugar intake were significantly large, and thus use of free sugar versus added sugar definitions need careful consideration for standardised monitoring of sugar intake in relation to public health.

The purpose of the UK National Diet and Nutrition Survey (NDNS) is to provide detailed quantitative data on food consumption, nutrient intakes and the sources of nutrients for the UK population, and an assessment of population nutritional status through objective biomarker analysis. The UK NDNS reports official statistics for ongoing monitoring of diet, to provide the evidence base for developing and evaluating effectiveness of policy and interventions, and for exposure assessment.

The UK National Diet and Nutrition Survey rolling programme (NDNS RP) commenced in 2008 and moved in 2019 from a traditional paper food diary to a web-based 24 h recall, Intake24. This paper describes the approach to update and downsize the underlying UK Nutrient Databank (NDB) for efficient data management and integration into Intake24. Consumption data from the first 10 years (2008/2009 to 2017/2018) of NDNS RP informed decisions on whether foods from the extensive UK NDB were to be retained, excluded, revised or added to for creation of a rationalised NDB. Overall, 5933 food codes in the extensive NDB were reduced to 2481 food codes in the rationalised NDB. Impact on assessment of nutrient intakes was evaluated by re-coding NDNS 2017 data using the rationalised NDB. Small differences were observed between estimated intakes (Cohen’s d ≤ 0.1) for all nutrients and there was a good level of agreement (Cohen’s κ ≥ 0.6) between the extensive and rationalised NDBs. The evaluation provides confidence in dietary intake estimates for ongoing nutritional surveillance in the UK and strengthens the evidence of a good agreement between concise food databases and large food databases incorporated into web-based 24 h recalls for estimating nutrient intakes at the population level.

The measurement of micronutrient status is essential to understand the health of individuals and populations, but there are limited data on the stability of micronutrients in whole blood. The objective was to investigate the effects of delayed processing of whole blood on the stability of 25 micronutrient and selected clinical biomarkers. Blood from 16 healthy adults was collected into EDTA, lithium heparin (LH), or serum tubes. Samples were processed within 2 hours of collection (“2-hour processed”) or mailed overnight (boxed with frozen cold packs) before processing (“24-hour processed”). Micronutrient and clinical biomarker concentrations were quantified with validated methods. The concentration percentage difference between the 2- and 24-hour processed samples was calculated and was compared against quality specifications determined from intra- and interindividual variations. All analytes had a sample type where the percentage difference concentration between 2-hour and 24-hour processed samples was ≤4% and was acceptable based on calculated limits, including for biomarkers of vitamin A, vitamin D, thiamin, folate, vitamin B-12, iron (ferritin), and zinc status and for selected clinical markers, C-reactive protein, HDL and total cholesterol, and triglycerides. EDTA plasma vitamin C was lower compared to the 2-hour processed sample (geometric mean, 43%; 95% CI: 36%–49%). Pyridoxal-5-phosphate (vitamin B-6 biomarker) decreased, with differences from the 2-hour processed samples of −8% (95% CI: −13% to −2%) and −14% (95% CI: −18% to −9%) in LH plasma and serum, respectively. In blood collected from adult participants, delayed processing of chilled whole blood for 24 hours did not materially affect the measured concentrations of the majority of micronutrients and selected clinical biomarkers. This suggests that for these analytes, adherence to a 2-hour processing protocol may be unnecessary. This knowledge is valuable and may help to simplify logistics for sample transport and processing of blood samples for micronutrient status assessment.

Background: Little is known about population levels of energy expenditure as national surveillance systems typically employ only crude measures. The National Diet and Nutrition Survey (NDNS) in the UK measures energy expenditure in a 10% subsample by gold-standard doubly-labelled water (DLW). Methods: DLW-subsample participants from the NDNS (383 males, 387 females) aged 4-91yrs were recruited between 2008 and 2015. Height and weight were measured, and bodyfat percentage was estimated by deuterium dilution. Results: Absolute Total Energy Expenditure (TEE) increases steadily throughout childhood, ranging from 6.3 and 7.2 MJ/day in 4-7yr-old to 9.9 and 11.8 MJ/day for 14-16yr-old girls and boys, respectively. TEE peaked in 17-27yr-old women (10.9 MJ/day) and 28-43yr-old men (14.4 MJ/day), before decreasing gradually in old age. Physical Acitivty Energy Expenditure (PAEE) declines steadily with age from childhood (87.7 kJ/day/kg in 4-7yr olds) through to old age (38.9 kJ/day/kg in 71-91yr olds). Bodyfat percentage was strongly inversely associated with PAEE throughout life, irrespective of expressing PAEE relative to bodymass or fat-free mass. Compared to females with 40% recorded 28 kJ/day/kg and 17 kJ/day/kg fat-free mass less PAEE in analyses adjusted for age, geographical region, and time of assessment. Similarly, compared to males with 35% recorded 26 kJ/day/kg and 10 kJ/day/kg fat-free mass less PAEE. Conclusions: This first nationally representative study reports levels of human energy expenditure as measured by gold-standard methodology; values may serve as reference for other population studies. Age, sex and body composition are main biological determinants of energy expenditure. Key messages: First nationally representative study of human energy expenditure, covering the UK in the period 2008-2015 Total Energy Expenditure (MJ/day) increases steadily with age thoughout childhood and adolescence, peaks in the 3 ^rd decade of life in women and 4 ^th decade of life in men, before decreasing gradually in old age Physical Acitivty Energy Expenditure (kJ/day/kg or kJ/day/kg fat-free mass) declines steadily with age from childhood to old age, more steeply so in males Bodyfat percentage is strongly inversely associated with physical activity energy expenditure

Background and aims: This paper describes the data resource profile of South Asia Biobank (SAB), which was set up in South Asia from November 2018 to March 2020, to identify the risk factors and their complex interactions underlying the development of type-2 diabetes mellitus, cardiovascular disease and other chronic diseases in South Asians.Data resource basics: This cross-sectional population-based study has recruited 52713 South Asian adults from 118 surveillance sites at five centres of excellence in South Asia (Bangladesh, North India, South India, Pakistan and Sri Lanka). Structured assessments of participants included six complementary domains: i). Registration and consent; ii). Questionnaire (information on behavioural risk factors, personal and family medical history, medications, socioeconomic status); iii). Physical measurements (height, weight, waist and hip circumference and bio-impedance for body fat composition, blood pressure, cardiac evaluation, retinal photography, respiratory evaluation); iv). Biological samples (blood and urine); v). Physical activity monitoring and vi). Dietary intake by a 24-hour recall. Aliquots of whole blood, serum, plasma, and urine were put into storage at −80°C for further analysis.Key results: The prevalence of obesity is 6.6% in Bangladesh, 19.7% in India, 33.9% in Pakistan and 15.7% in Sri Lanka. The prevalence of diabetes is 11.5%, 27.7%, 25.3%, and 24.8%, and the prevalence of hypertension is 26.7%, 36.9%, 44.5%, 35.0% in Bangladesh, India, Pakistan and Sri Lanka respectively.Collaboration and data access: SAB is the first comprehensive biobank of South Asian individuals. Collected data are available to the global scientific community upon request.