Background The National Child Measurement Programme (NCMP) measures the weight status of 4–5- and 10–11-year-olds and communicates results, via letter. Parents are sometimes surprised by these results. MapMe is a tool to improve parental acknowledgement and understanding of childhood overweight and obesity. Ten English Local Authorities (LAs) agreed to test MapMe and deliver the intervention to parents via an ‘enhanced’ NCMP results letter including Body Image Scales (BIS): images of NCMP age- and sex-appropriate children of different weight statuses, plus dedicated website. For the trial process evaluation, a qualitative study was conducted to determine the acceptability of the intervention, and views of embedding MapMe into usual practice. Methods Twenty-seven parents and 48 LA staff consented to an interview, focus group or online questionnaire. All interviews/focus groups were conducted online. Data were analysed using thematic Framework analysis. Results Twenty-seven parents were interviewed, 25 had received a healthy weight result letter for their child, one overweight and one very overweight. Parents receiving healthy weight result letters had no concerns about the letters, did not feel the need to visit the website and were happy to receive the BIS. Whilst some LA stakeholders described the enhanced letters as too long or not compassionate in tone, no increase in parental complaints were reported. Conclusions Overall, it was suggested that MapMe could add value to the NCMP and would be unlikely to have a detrimental effect on programme delivery. The MapMe intervention is now available as an optional resource for English local authorities.

Dietary intake is increasingly recognised as a modifiable determinant of cognitive function, with emerging evidence linking higher intake of ultra-processed foods (UPF) to poorer cognitive outcome, especially in older adults aged 60 and above(1-3). However, evidence on specifically the very old (aged 85 and above) are scarce. Since they are a rapidly growing population in the United Kingdom (UK) where the number of adults aged 85 and over has increased by 186% between 1981 and 2021 (4) . Due to this demographic shift, it is essential to study specifically this populations UPF intake in relation to cognition. The Newcastle 85+ Study (n = 790) provides a unique opportunity to investigate nutritional determinants of cognition in the very old (≥ 85 y); the mean (standard deviation) age at baseline was 85.5 (0.4) y. Baseline diet (2006/07) was assessed with two non-consecutive 24-h recalls (5) and foods were classified according to the NOVA food classification system (6) . Global cognition (Mini-Mental State Examination, MMSE) were assessed at baseline and at 1.5, 3 and 5 years, while the Clinical Dementia Rating (CDR), composite attention scores [Power of Attention (PoA), Continuity of Attention (CoA), Reaction-Time Variability (RTA)] and single-task reaction times [simple reaction time (SRT), choice reaction time (CRT), and vigilance reaction time (VIGRT)] times were assessed at baseline, and at 1.5 and 3 years. UPF intake was categorised into tertiles using the Nova system as a proportion of total energy (%TE). UPF intake supplied 56 % of total energy intake at baseline. Cross-sectionally, higher UPF intake was associated with poorer baseline performance on selected attention and processing-speed measures, but not with global cognition. In fully adjusted regression models, each standard-deviation increase in UPF intake was associated with worse baseline PoA (β = 0.020, SE = 0.010, P = 0.045) and slower baseline SRT (β = 0.049, SE = 0.023, P = 0.032). No statistically significant associations were observed for MMSE, CoA, RTV, CRT, VIGRT, or CDR after full adjustment. Additionally, longitudinal mixed-effects models showed no statistically significant associations between baseline UPF intake and subsequent change in MMSE, attention domains, reaction-time measures, or CDR over up to five years of follow-up. Findings indicate that a higher intake of %TE of UPF was cross-sectionally associated with poorer attention and processing-speed performance, but not global cognition, while longitudinal mixed-effects models showed no association with cognitive decline over three and five years. These findings suggest that associations between UPF intake and cognition may vary within older age groups, highlighting the need to avoid treating adults aged ≥60 years as a homogeneous population and to adopt age-stratified approaches in research on UPF. Further research is needed to confirm whether these observed links reflect a causal influence of high UPF intake on cognition or whether the links are driven by overall diet quality, is essential. Future work should also test how the United Kingdom food-policy initiatives could improve both dietary quality and cognitive health in the very old.

Childhood obesity is a major health concern and a public health priority. Parents play a key role in addressing childhood obesity, and one possible solution could be directly informing parents about their child’s weight status, encouraging them to change behaviour. The MapMe intervention has been developed as a tool to improve parental acknowledgement and understanding of childhood obesity. A three-arm cluster randomised trial was delivered within England’s mandatory National Child Measurement Programme as part of the MapMe2 study. Building on the original MapMe trial, it assessed the effect of two versions MapMe intervention on weight in children aged 4–5 and 10–11 years. The aim of this study was to conduct a within-trial cost-utility analysis (CUA) using the MapMe2 trial data to estimate the potential cost-effectiveness of two versions of the MapMe intervention (a ‘Web Only’ version and a ‘Web Boost’ version) compared to a control group. The CUA was carried out from an NHS perspective over a one-year time horizon. In the base case, the primary outcome was child health-related quality of life measured by the CHU-9D. The inclusion of out-of-pocket costs and an alternative measure of health-related quality of life (the WAItE) were conducted as sensitivity analyses. Results were expressed as incremental cost per Quality Adjusted Life Year (QALY) gained. The results indicated that the ‘Web Only’ and ‘Web Boost’ intervention versions were more likely to be cost-effective than the control. This conclusion held true even when including parental out-of-pocket expenses for weight management and physical activity, and when using a condition-specific health-related quality of life measure. However, given the small sample size in the sub-study, the results from this study should be treated with a high degree of caution. Future analysis should focus on estimating the cost-effectiveness of public health interventions such as MapMe over a longer time horizon, given that full costs and benefits are unlikely to be captured in the short time frame of trials such as MapMe2.

We aimed to explore how free sugar intake varies across the day in secondary school pupils. Pupils aged 11-15 years were recruited between December 2019-April 2022 from English secondary schools. Pupils completed a sociodemographic questionnaire and recorded all foods and drinks consumed in the previous day. We undertook mixed-effects regression modelling to explore patterns of sugar consumption across different eating occasions, and in and out of school, accounting for school clustering and adjusting for energy intake and participant sociodemographic variables. 2575 pupils were invited to participate, with 2273 participants ultimately included in the study. After adjustment for mealtime energy intake, compared to breakfast, free sugar intake was lower at lunch (mean difference: -7.86 g; 95% CI = -8.87 g, -6.84 g; p = <0.001) and dinner (mean difference: -11.82 g; 95% CI -12.85 g, -10.80 g; p = <0.001). Free sugar intake from snacks was higher than breakfast (mean difference: 7.70 g; 95% CI 6.68 g, 8.72 g; p = <0.001). Snacks on average comprised 28.5% of total energy intake and 43.1% of free sugar intake for the day. Free sugar intake outside of school was higher than intake during school time (mean difference: 3.18 g; 95% CI = 1.67 g, 4.69 g; p = <0.001). Breakfast and snacks made the largest contribution to free sugar intake among adolescents in the study after accounting for variation in energy intake across mealtimes. Free sugar intake was higher outside than inside school. Efforts to reduce free sugar intake in adolescents should focus on breakfast and snack food and drink items, and high sugar items available outside of school.

Objectives To estimate the contribution of ultraprocessed foods (UPF) to total energy intake and to macronutrient and micronutrient intakes among very old people aged 85 years in the Newcastle 85+ Study.Design Cross-sectional observational analysis of baseline dietary and demographic data from the Newcastle 85+ cohort.Setting Community-dwelling and institutionalised adults in Newcastle on Tyne and North Tyneside, UK, recruited through general practice registered between June 2006 and October 2007.Participants Eight hundred participants (62% female) aged 85 years at baseline, with two complete non-consecutive 24-hour dietary recalls.Primary outcome The primary outcome was the contribution of UPF (Nova group 4) to total energy intake, macronutrient intakes, expressed as percentage of total energy for carbohydrate, protein, total fat, saturated fat and added sugars, as grams per day for fibre and to micronutrient intakes (vitamins A, B₆, B₁₂, C, D, E and folate) and minerals (calcium, potassium, magnesium, zinc, selenium, phosphorus, iron and sodium). All evaluated across sex, education and socioeconomic status, adjusted tertiles of UPF intake.Results Among the 800 participants included in the analysis, UPF contributed 56% of total energy intake, surpassing that from unprocessed foods (27%). Total energy intake did not differ across tertiles of UPF consumption (lowest vs highest tertile: 1759.5 kcal/day (95% CI 1684.6 to 1834.4) vs 1740.0 kcal/day (1667.3 to 1812.7)). Higher UPF intake was associated with a higher proportion of energy from carbohydrates and added sugars, and a lower proportion from protein and saturated fat. Intakes of several micronutrients were lower in the highest versus the lowest UPF tertile, including vitamin C (59.9 mg/day (49.8 to 70.0) vs 94.0 mg/day (83.7 to 104.4)) and potassium (2455.9 mg/day (2334.1 to 2577.6) vs 2786.3 mg/day (2660.8 to 2911.8)). By contrast, calcium from fortified foods increased across tertiles (6.3 mg/day (3.7 to 8.9) to 15.4 mg/day (12.9 to 17.9)).Conclusions This study highlights the potential role of UPF in the diets of very old people: higher UPF intake was not associated with higher energy intakes often observed in younger populations. Some UPF, particularly fortified products, may contribute to meeting micronutrient requirements in very old people where dietary inadequacies are common. Further research is needed to confirm these findings and to inform dietary guidance for very old people.

This cohort study evaluates whether socioeconomic factors, including sex, race and ethnicity, material deprivation, and rurality) are associated with the age at which patients are diagnosed with severe mental illness.

OBJECTIVES:Parental underdetection of child underweight and overweight/obesity may negatively affect children's longer-term health. We examined psychological/behavioural mechanisms of a very low-intensity intervention to improve acknowledgement and understanding of child weight after feedback from a school-based weight monitoring programme. DESIGN:This sub-study was nested within a larger 3-arm cluster-RCT (1:1:1; N = 57,300). Parents in all groups received written postal feedback on their child's weight classification. Intervention participants received an enhanced feedback letter with computer-generated photorealistic images depicting children of different weight classifications, and access to a website about supporting healthy weight, once (intervention one) or twice (intervention two; repeated 6 months after first 'dose'). METHODS:A quantitative process and outcome evaluation using baseline and 12-month BMI z-scores of an opt-in sub-sample of 502 children aged 4-5 and 10-11. Children completed dietary reports, used accelerometers (MVPA), and self-reported self-esteem; 10-11-year-olds also self-reported quality of life and dietary restraint. Parents reported perceptions of child's weight classification, and their intentions, self-efficacy, action planning and coping planning for child physical activity, dietary intake; parents of 4-5-year-olds reported their child's quality of life. RESULTS:Neither intervention differentially improved parental acknowledgement or understanding of weight classification at follow-up, although parents in all groups reported better acknowledgement after receiving feedback. The interventions did not affect behavioural/psychological determinants, weight outcomes, children's self-esteem, dietary restraint or quality of life. CONCLUSIONS:The interventions neither improved parental acknowledgement of child weight, child BMI z-scores and their psychological/behavioural determinants, nor worsened psycho-social sequelae.

Economic evaluations of complex public health interventions are becoming increasingly important. This presents health economists with challenges of adapting methodologies originally designed for healthcare to other contexts, such as education. This study presents an economic evaluation of the UK School Food Standards (SFS), with a particular focus on the methodological challenges involved. The economic evaluation was conducted alongside an observational study comparing the SFS-mandated secondary schools to non-mandated schools in the Midlands (UK). Costs of food provision and SFS implementation were collected directly from schools and supplemented by secondary data on schools’ catering expenditure. The outcomes included dietary intake, dental health, health-related quality of life (HRQoL), and educational performance, collected from pupils and secondary data. The analysis comprised a micro-costing, cost-consequence, and an exploratory cost-utility analysis, from school and societal perspectives. Data were collected from 36 schools and 2,543 pupils. We found mandated schools spent less on food provision compared to non-mandated schools, and pupils attending mandated schools had marginally better HRQoL, dental health, and slightly worse nutritional intake. Mandated schools performed worse according to the educational outcomes. There were large amounts of missing cost data despite repeated data collection attempts, and the results of the cost-utility analysis were uncertain. We found no clear evidence on the cost-effectiveness of the SFS in secondary schools, likely due to substantial variation in implementation and compliance across both mandated and non-mandated schools, as well as multiple challenges, including the COVID-19 pandemic, difficulties in collecting cost data from schools, and the complexity of the study context. This study highlights the challenges of primary cost data collection for evaluating complex interventions and the need to balance data accuracy with the resources required. As economic evaluations of school-based interventions become more common, there is a growing need to refine methods for such evaluations.

BACKGROUND:The 'Everyone In' national policy initiative launched in England during the COVID- 19 pandemic provided accommodation and health and care support to people who were (or at risk of) sleeping rough. This study aims to understand what worked well and less well in implementing 'Everyone In' for improving physical and mental health outcomes for people experiencing homelessness. METHODS:Between January and October 2023, in-depth interviews/focus groups were conducted across England with those involved in the delivery/implementation of 'Everyone In' and those accommodated. Framework analysis and case study analysis were used for a contextual understanding of the implementation of the policy initiative. RESULTS:Twenty-five people accommodated through 'Everyone In' (28-58 years; 88% males) and 43 service providers (25-62 years; 40% males) were interviewed. Flexibility in funding and resources, 'joining up' services/support, and innovative responsiveness in services across health, care, and housing systems were key positive features of the initiative. In the long term, 'Everyone In' has provided positive learnings for delivering holistic and integrated health and social care. It has also highlighted the importance of accommodating psychosocial needs and addressing the complexities of alcohol and substance use in all homelessness strategies. CONCLUSIONS:Pathways to care for people experiencing homelessness need to be flexible and responsive. Complexities such as substance use need to be approached with compassion while addressing the role of wider determinants in such health behaviours. Innovative approaches and joined-up work improve delivery of interventions and integrated care can reduce barriers to access to support.

IntroductionThe school holidays can be a challenging time for many families especially for those reliant on free school meals. The Holiday Activities and Food (HAF) programme aims to provide disadvantaged families across England with healthy meals and enriching activities for children and young people. The clubs are usually in the form of a network of independent clubs and often depends on local partnerships and connections, such as the voluntary, community, social and enterprise sectors. In 2023 Southwark Council, interested in building on the findings of a national evaluation and providing more context specific insights relating to access to and use of their clubs, approached the Public Health Intervention Responsive Studies Teams scheme to collaborate in a service provision evaluation.MethodsAs part of the wider evaluation, a qualitative study was conducted. Semi-structured interviews were conducted with parents/carers of HAF eligible children and semi-structured interviews/focus groups were held with children and young people (CYP) attending a HAF club. Recruitment was through the clubs. The transcripts were coded by two independent researchers and thematic analysis applied.ResultsNine parent/carers and two young people took part in an interview. Six discussion groups with 4–6 young people in each took place. Most participants heard about the club they attended through word of mouth from friends and family, through the child’s school or by seeing a flyer/newsletter advert. Many participants were unaware of the variety and number of different clubs available to families. Finding out about the clubs online was reported to be time-consuming and websites not user-friendly. Parents/carers spoke of the frustration in trying to navigate booking systems. There was also a lack of awareness of the types of other support/signposting available from clubs.DiscussionThe evaluation highlighted the low-level of family awareness of all available HAF activities across the borough. Furthermore, navigating the system was reported as challenging. Southwark Council reviewed and revised its online provision to create a centralised repository accessible to families that aimed to improve awareness and ease the club booking process. Further work is required to improve signposting to support services and provision for parents/carers.

Eating disorders (EDs) are typically diagnosed in the later stages of puberty, but risk factors for EDs are present in pre-pubertal children. This longitudinal, population-based birth cohort study aimed to examine prospective predictors of eating disorder symptoms in 15-year-olds. Specifically, we sought to test an adapted dual pathway model of disordered eating aetiology in this group. Participants in the Gateshead Millennium Study birth cohort (n = 326; 187 girls and 175 boys) completed self-report questionnaires assessing eating disorder symptoms and risk factors at ages 7, 9, 12, and 15 years. Measures included body image, depressive symptoms, and pubertal development; we also measured BMI at each age. The data were fitted to a model of eating disorder symptom development to help us understand the role of puberty, adiposity, body dissatisfaction, depressive symptoms, and previous eating disorder symptoms. We found that previous eating disorder symptoms were the strongest predictor of eating disorder symptoms at 15, and that depressive symptoms prospectively predicted eating disorder symptoms in girls. We furthermore found that depressive symptoms at 12 partially mediated the relationship between body dissatisfaction at 12 and eating disorder symptoms at 15 in girls. Pubertal development predicted concurrent eating disorder symptoms at 12 in girls but not boys. Overall, our findings support the roles of pubertal development, body dissatisfaction, and depressive symptoms in the pathogenesis of eating disorder symptoms across puberty. They add to growing evidence that there are different pathways to eating disorder symptoms in girls and boys.

BackgroundIn DiRECT, a randomised controlled effectiveness trial, weight management intervention after 2 years resulted in mean weight loss of 7·6 kg, with 36% of participants in remission of type 2 diabetes. Of 36 in the intervention group who maintained over 10 kg weight loss at 2 years, 29 (81%) were in remission. Continued low-intensity dietary support was then offered up to 5 years from baseline to intervention participants, aiming to maintain weight loss and gain clinical benefits. This extension study was designed to provide observed outcomes at 5 years.MethodsThe DiRECT trial took place in primary care practices in the UK. Participants were individuals aged 20–65 years who had less than 6 years’ duration of type 2 diabetes, a BMI greater than 27 kg/m2, and were not on insulin. The intervention consisted of withdrawal of antidiabetic and antihypertensive drugs, total diet replacement (825–853 kcal per day formula diet for 12–20 weeks), stepped food reintroduction (2–8 weeks), and then structured support for weight-loss maintenance. After sharing the 2-year results with all participants, UK National Health Service data were collected annually until year 5 from remaining intervention participants who received low-intensity dietary support, intervention withdrawals, and the original randomly allocated groups. The primary outcome was remission of type 2 diabetes; having established in the DiRECT trial that sustained weight loss was the dominant driver of remission, this was assumed for the Extension study. The trial is registered with the ISRCTN registry, number 03267836.FindingsBetween July 25, 2014, and Aug 5, 2016, 149 participants were randomly assigned to the intervention group and 149 were assigned to the control group in the original DiRECT study. After 2 years, all intervention participants still in the trial (101 [68%] of 149) were approached to receive low-intensity support for a further 3 years. 95 (94%) of 101 were able to continue and consented and were allocated to the DiRECT extension group. 54 participants were allocated to the non-extension group, where intervention was withdrawn. At 5 years, DiRECT extension participants (n=85) lost an average of 6·1 kg, with 11 (13%) of 85 in remission. Compared with the non-extension group, DiRECT extension participants had more visits with HbA1c <48 mmol/mol (<6·5%; 36% vs 17%, p=0·0004), without glucose-lowering medication (62% vs 30%, p<0·0001), and in remission (34% vs 12%, p<0·0001). Original control participants (n=149) had mean weight loss 4·6 kg (n=82), and 5 (5%) of 93 were in remission. Compared with control participants, original intervention participants had more visits with weight more than 5% below baseline (61% vs 29%, p<0·0001), HbA1c below 48 mmol/mol (29% vs 15%, p=0·0002), without antidiabetic medication (51% vs 16%, p<0·0001), and in remission (27% vs 4%, p<0·0001). Of those in remission at year 2, 26% remained in remission at 5 years. Serious adverse events in the original intervention group (4·8 events per 100 patient-years) were under half those in the control group (10·2 per 100 patient-years, p=0·0080).InterpretationThe extended DiRECT intervention was associated with greater aggregated and absolute weight loss, and suggested improved health status over 5 years.FundingDiabetes UK.

Establishing Research Ecosystems in Local Government: Ten lessons from the front line of the first year of the NIHR Health Determinants Research Collaborations (HDRCs). Newbury-Birch D1, Harbin, K2. Adamson A3, Asthana S4, Batey C5, Buffardi A6, Curley J7, Dezateux C8, Divers A1, Fitzsimmons E9, Forbes L10, Frossell S11, Goyder E12, Hampshaw S13, Humphreys E14, O'Malley E15, Maiden H16, Marks D17, Murchie M18, Paranjothy S19,20, Ramsay SE3, Sheldon T8, Shore R21, Simpson A16,22, Speight A16, Wallace G9, Whelan M23, Whiting D10,24, Woolfe I25,26, Ferguson B27. On behalf of the 13 NIHR PHR Health Determinants Research Collaborations funded in 2022/2023. 1. School of Social Sciences, Humanities and Law, Teesside University (HDRC South Tees) 2. HDRC South Tees, Middlesbrough Council 3. Population Health Sciences Institute, Newcastle University (HDRC Gateshead and HDRC Newcastle) 4. Centre for Health Technology, University of Plymouth (HDRC Plymouth) 5. HDRC Newcastle, Newcastle City Council 6. HDRC Islington, Public Health Department, London Borough of Islington 7. HDRC Lambeth, Public Health, London Borough of Lambeth 8. Wolfson Institute of Population Health, Queen Mary University of London (HDRC Tower Hamlets) 9. HDRC Plymouth, Plymouth City Council 10. Centre for Health Services Studies, University of Kent (HDRC Medway) 11. HDRC Coventry, People Directorate, Coventry City Council 12. Sheffield Centre for Health and Related Research, Division of Population Health, University of Sheffield (HDRC Doncaster) 13. HDRC Doncaster, City of Doncaster Council 14. HDRC Tower Hamlets, Health & Adult Social Care Directorate, London Borough of Tower Hamlets 15. HDRC Gateshead, Public Health & Wellbeing, Gateshead Council 16. HDRC Blackpool, Blackpool Council 17. Department of Public Health, Environments & Society, London School of Hygiene and Tropical Medicine (HDRC Islington) 18. HDRC Aberdeen, Aberdeen City Council 19. NHS Grampian (HDRC Aberdeen) 20. Institute of Applied Health Sciences, University of Aberdeen (HDRC Aberdeen) 21. HDRC Bradford, City of Bradford Metropolitan District Council 22. Lancaster University (HDRC Blackpool) 23. Coventry University (HDRC Coventry) 24. HDRC Medway, Public Health, Medway Council 25. Department of Women's and Children's Health, King's College London (HDRC Lambeth) 26. Evelina London Children's Hospital (HDRC Lambeth) 27. Department of Health Sciences, University of York Health inequalities are where we see differences in health across the population, and between different groups in society, that are systematic, unfair and avoidable (1). They need a long-term systemic response to support people to value their health and wellbeing (2). These social, economic environmental, cultural and commercial factors, known as the wider determinants of health, are unequally distributed across the UK population (3). This is despite numerous attempts to address them at a local, national and internationally (4, 5). Both the Marmot review and the Dame Carol Black review highlighted the huge economic costs of failing to act on the wider determinants of health (4-6). Local public health leaders are in a strong position to develop a whole system approach to reducing health inequalities that puts communities at its heart (10). Thirteen Local Authorities (LAs) were awarded funding by the National Institute for Health and Care Research (NIHR) in October 2022 to develop HDRCs. Ten of them as full HDRCs (HDRC Tower Hamlets, HDRC Newcastle, HDRC Doncaster, HDRC Aberdeen, HDRC Bradford, HDRC Plymouth, HDRC Gateshead, HDRC Blackpool, HDRC Coventry and HDRC Lambeth). Three were given a further year to develop their plans and became full HDRCs in October 2023 (HDRC South Tees, HDRC Medway, HDRC Islington). Eleven more full HDRCs were announced in December 2023 and are due to start January 2024 (HDRC Ealing, HDRC Sandwell, HDRC Wakefield, HDRC Southampton, HDRC Rhondda Cynon Taf, HDRC Liverpool, HDRC Somerset, HDRC Cumberland, HDRC Cornwall, HDRC Essex, HDRC North Yorkshire). As in round one there were a number of areas given a year to develop their work further (HDRC Manchester, HDRC Portsmouth, HDRC Torfaen, HDRC Leicestershire, HDRC Glasgow, HDRC Surrey) (11). The aim of the HDRCs is to embed a culture of evidence-based decision-making within Local Government. The HDRCs will help to stimulate economic growth, particularly in some of the most deprived areas of the country and contribute to the Government's plans to act for the longer-term resilience of the health and wealth of the country (12). This article examines the key learning from the first year of the wave one HDRCs and give advice to new HDRCs starting their journeys in 2024. Between April and October 2023, the lead author asked for at least one person from each of the LAs and one academic/other partner involved in HDRCs to complete a small survey with open ended questions which took about ten-minutes to complete. The survey was conducted using Jisc online surveys. Data was downloaded and open-ended questions were coded by DNB and KH. All data was downloaded and analysed using an inductive approach (13). Twenty-seven people responded with representation from all the 13 HDRCs. Below we identify ten key things to consider when starting the journey. Recruit to posts early Recruitment was a colossal problem for both LAs and universities. Bureaucratic hold ups and slow HR processes hindering progress were apparent as well as issues recruiting staff with the right skills, appropriate expertise and at the right time. The precarious financial climate of Local Government also needed to be navigated with care, with jobs being created for the HDRCs against job losses elsewhere. "£5 million funding creating 10+ new jobs has arrived against the backdrop of recent job cuts. We have to be cognisant of this. Developing relationships with teams within the council with similar objectives to HDRC, against the backdrop of funding pressures and job insecurity" (LA) Think about capacity Capacity proved to be significantly stretched during the first year. Academic colleagues reported working well beyond their intended HDRC costed time to counterbalance the time constraints felt by LAs in recruiting staff. These pressures saw a slowing of momentum, research culture change, relationship building and "buy in". "We found that the extent to which LA Finance and HR systems struggle to accept and contract out funding, difficulties in back filling people's time" (LA) Consider priorities The main thing is to expect a slow start and don't underestimate the size of the task at hand. Treat recruitment as a priority and think about job descriptions straight away. Build a cohesive team with strong leadership whose sole focus is on the HDRC, helping to get through the early legal and bureaucratic hassles. Take time to get to know key staff across all sectors and the community, utilising and nurturing relationships. Leadership is vital Ensure that you have good leadership at both the LA and University. Project management is essential. "Appoint a competent project manager to help get through legal and bureaucratic hassles; give researchers time to bed in and understand cultures of both LA and University" (University) Create a plan Create a clear plan, giving individuals time to bed in and understand the diverse cultures of both LAs and Universities. Use the plan to quickly establish priority areas, costing LA and academic staff appropriately. Fully think through each milestone and any potential barriers ensuring to collect baseline data as soon as objectives are set and have robust monitoring processes throughout. But be prepared for fast-paced learning and a constant change of the plan. Be flexible and change your bid/plan as needed. Don't underestimate the size of the job to align organisations Aligning the needs and motivations of the HDRC within LAs was shown to be a delicate process. Managing expectations was a major task for the first year. Being realistic with timelines whilst also harnessing the motivation and excitement to get going. "We use the analogy of doing the groundwork on a building site - there is a lot happening that nobody can see at the moment, but soon there will be something that staff, residents and local academics can really see and engage with" (LA) Culture Change Changing the research culture within LAs was seen to be paramount to the success of HDRCs. It is important to understand current approaches in the LAs. Getting some 'early wins' in terms of research funding is a good thing for staff to see what success looks like and means. It is important to identify "champions" within the LAs to help champion the work. "It has reinforced my knowledge and the organisational and professional gap between LA officers and researchers, different ways of working and thinking. But I am learning to tackle this" (University) It's not a competition Some HDRCs are ahead of others in some things and behind in others. Keep to your project plan and enjoy successes whether they are big or small. "Recognise there is a start-up period and manage expectations" (LA) Community involvement is everything Ensure that you work with your community partners and that they are part of the team from as early as possible. "Recruitment of Co-Researchers with lived experience to the project should be the very first thing you do. Think very strongly about how you will make the community members feel valued for their contribution to the project" (LA) Support is imperative Finally, HDRCs found having other HDRCS to get support from was extremely valuable "It is a new and challenging concept and way of working for many of us - the peer support has been invaluable". NIHR have also been supportive and flexible in a number of ways which has been helpful" (University) This study/project is funded by the NIHR PHR, Health Determinants Research Collaborations. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. References 1. NICE. NICE and health inequalities London [Available from: https://www.nice.org.uk/about/what-we-do/nice-and-health-inequalities. 2. Director of Public Health. Live Well South Tees. Redcar and Cleveland: Public Health South Tees; 2018. 3. Such E. Framing the wider determinants of health and health inequalities: local stakeholder views in England. Evidence & Policy. 2023;19(4):513-35. 4. Marmot M, Allen J, Boyce T, Goldblatt P, Morrison J. Health Equity in England: The Marmot review 10 years on. London: Institute of Health Equity; 2020. 5. Marmot M. Fair Society, Health Lives: Strategic Review of Health Inequalities in England Post-2010. London: The Marmot Review; 2010. 6. Black C. Working for a Healthier Tomorrow: Dame Carol Black's Review of the health of Britain's working age population. London: TSO; 2008. 7. Michie S, Fixsen D, Grimshaw J, Eccles M. Specifying and reporting complex behaviour change interventions: the need for a scientific method. Implementation Science. 2009;4(1):40. 8. Glasgow RE, Lichtenstein E, Marcus AC. Why don't we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition. AJPH. 2003;93(8):1261-7. 9. Ferrer RL. Social Determinants of Health. In: Daaleman TP, Helton MR, editors. Chronic Illness Care: Principles and Practice. Cham: Springer International Publishing; 2023. p. 527-45. 10. Stansfield J, South J, Mapplethorpe T. What are the elements of a whole system approach to community-centred public health? A qualitative study with public health leaders in England's local authority areas. BMJ Open. 2020;10(8):e036044. 11. National Institute for Health and Care Research. NIHR invests a further £55m to tackle health inequalities through local government research: NIHR; 2023 [Available from: www.nihr.ac.uk/news/nihr-invests-a-further-55m-to-tackle-health-inequalities-through-local-government-research/34972. 12. National Institute for Health and Care Research. £50 million awarded to local government to tackle interventions for health inequalities through research 2022 [Available from: https://www.nihr.ac.uk/news/50-million-awarded-to-local-government-to-tackle-interventions-for-health-inequalities-through-research/31654 13. Azungah T. Qualitative research: deductive and inductive approaches to data analysis. Qualitative Research Journal. 2018;18(4):383-400.

Background: Selenium has potential safeguarding properties against cognitive decline, because of its role in protecting DNA, proteins, and lipids in the brain from oxidative damage. However, acute and chronic overexposure to selenium can be neurotoxic. Objective: The aim of this analysis was to explore the association between selenium status [serum selenium and selenoprotein P (SELENOP) concentrations and glutathione peroxidase 3 (GPx3) activity] and cognitive function in 85-y olds living in Northeast England at baseline and <= 5 y of follow-up. Methods: Global cognitive performance was assessed in 755 participants from the Newcastle 85+ study using the standardized Mini-Mental State Examination and attention-specific cognition was assessed using composite scores derived from the Cognitive Drug Research System. Serum selenium, SELENOP, and GPx3 activity were measured at baseline by total reflection X-ray fluorescence, enzyme-linked immunosorbent assay, and coupled- enzyme reaction, respectively. Regression analyses explored linear and nonlinear associations between continuous values and tertiles of selenium status biomarkers, respectively, and cognitive function at baseline. Generalized linear mixed models explored associations between continuous values and tertiles of selenium status biomarkers, and global cognitive decline over 5 y, and attention-specific cognitive decline over 3 y. Results: Over 3 and 5 y, none of the selenium biomarkers were associated with the rate of cognitive decline. At baseline, in fully adjusted models, higher serum selenium was nonlinearly associated with global cognition (beta = 0.05 +/- 0.01, P = 0.387 linear, beta = 0.04 +/- 0.01, P = 0.002 nonlinear). SELENOP and GPx3 activity were not associated with any cognitive outcomes. Conclusions: There were no associations between selenium status and cognitive decline. However, serum selenium, but not SELENOP or GPx3 activity, was positively associated nonlinearly with global cognition at baseline. Furthermore, these associations were not evident during follow-up, potentially because of residual confounding and reverse causation.

In 2021, the UK Government announced additional funding in England for Adult Weight Management Services (AWMS); it was specified that the extra funding must be used to commission or extend existing tier 2 services. The Office for Health Improvement and Disparities encouraged commissioners to prioritise services for higher-risk groups such as those with learning disabilities, severe mental illness, people from minority ethnic groups, those living in deprived areas and men. To better understand the findings from previous survey work and to explore the implementation of targeted services in greater depth, we undertook a multiple case study comprising eight tier 2 adult weight management service providers and 35 individual stakeholder interviewees. Using the Consolidated Framework for Implementation Research as an interview guide and in data analysis, we determined key enablers and barriers to successful service provision and programme implementation. Good practice for successful AWMS provision for higher-risk groups includes, having an existing programme in place that can be adapted, ensuring adequate time for programme development/implementation, having good existing networks/partnerships, collaborative working and putting the target group at the heart of any intervention. The findings from this work provide practical recommendations for policy and practice when targeting tier 2 services for higher-risk groups.

Objectives: Tracking of physical activity from childhood onwards is an important public health issue, but evidence on tracking is limited. This study quantified the tracking of Moderate-Vigorous Physical Activity (MVPA) across childhood and adolescence in a recent cohort from England. Design: Longitudinal, with a socio-economically representative sample from North-East England, over an 8-year period. Methods: Measures of time spent in MVPA, with an Actigraph GT1M accelerometer, were made at age 7-8y (n = 622, T1), age 9-10y (n = 585, T2), age 12-13y (n = 525, T3) and age 14-16y (n = 361, T4). Tracking of MVPA was assessed using rank order correlations between time spent in MVPA T1-T2, T1-T3, and T1-T4, and by using Cohen's kappa to examine tracking of meeting the MVPA guideline (mean of 60 min/d). We examined whether tracking varied by sex, socio-economic status (SES), initial MVPA, or initial body fatness. Results: Rank order correlations were all statistically significant at p < 0.01 and moderate: 0.58 between T1 and T2; 0.42 between T1 and T3; 0.41 between T1 and T4. Cohen's kappas for meeting the global MVPA guideline were all significant, weakening from moderate to low over the 8 years. Tracking was stronger in higher SES compared to lower SES groups, and there was some evidence that it was stronger in girls than boys, but the other explanatory variables had little influence on tracking. Conclusions: Tracking of MVPA from mid-childhood to mid-adolescence in this cohort was moderate. This study suggests there is a need to establish high MVPA by mid-childhood, and to mitigate the age-related reduction in MVPA which occurs from mid-childhood. (c) 2024 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Childhood overweight and obesity is a worldwide problem and to treat it parents’ detection has to be improved. The MapMe Body Image Scales (BIS) are a visual tool developed to improve parental perception of child weight in the United Kingdon (UK) based on British growth reference criteria. The aim of this study was to make a transcultural adaptation and validation of the MapMe BIS in Spain based on International Obesity Task Force (IOTF) cut offs A descriptive cross-sectional study was done. First, a translation and cultural adaptation was carried out. A total of 155 10–11-year-old children and their parents participated in this study. Children were measured to calculate their weight status, Body Mass Index (BMI), Body Fat Percentage (BFP) and Waist Circumference (WC), and their parents completed a purpose designed questionnaire about their perception and satisfaction of child’s body weight status using the adapted BIS. Test-retest reliability, criterion validity and concurrent validity of the adapted BIS were analyzed. This study shows that the adapted MapMe BIS has good psychometric properties and is a suitable visual scale to assess parental perception of weight status in 10 and 11-year-old children in Spain.

Background Childhood overweight (OW) is a public health priority. Parents are key to maintaining a healthy weight in their child but may not recognise child OW. The mandated National Child Measurement Programme (NCMP) measures the weight status of 4–5- and 10–11-year-olds in England providing results to parents via letter; where follow up is offered, this is usually available only to children in the very overweight category. 'MapMe' is a web-based tool aimed at improving parental recognition of child OW and includes family-based lifestyle behaviours/support suitable for all families. MapMe is being delivered to families across 10 local authorities (LA) as part of the NCMP results letter. Repeat measures at 12 months will measure the impact on child weight outcomes. Little is known about LA delivery or implementation of a large-scale public health intervention and research trial. This work describes the views and experiences of those LA staff involved in supporting the trial and implementing the intervention collected as part of the process evaluation. Methods Semi-structured interviews/focus groups were conducted with LA staff. Thirty-seven staff were invited by email to participate via Teams or Zoom. Interviews/focus groups were video-recorded and transcribed verbatim. Thematic framework analysis was applied. Results Ten staff members consented to interview (n=4) or focus group (n=2 with 3 participants in each). Participant roles included public health specialists, public health practitioners, NCMP leads, school nurses, child/family health managers and business-support staff. Six themes were identified, including the implementation of the study. Supporting and implementing research was a new concept for many: 'Whereas [for] LAs,…to a lot of the departments, it's just a little bit too new to them.' Communication and data-sharing between LA departments could be problematic: '…all the LAs work differently… I mean we sit on the same floor as our School Admissions Department, but because of GDPR they cannot physically provide us with that [data].' Most interviewees reported that, dependent on trial results, they would support a national roll-out of MapMe: '…it feels like NCMP might become more than just a data collection exercise… that there will be something positive'. Some implementation issues needed to be resolved, such as stream-lining the administration process, having more follow-up meetings, and providing a 'test participant.' Conclusion Despite the challenges and novelty faced by LAs in implementing the study, LA respondents thought MapMe could be a beneficial addition if fully integrated as part of the routine delivery of the NCMP.

Research suggests parental ability to recognise when their child has overweight is limited. It is hypothesised that recognition of child overweight/obesity is fundamental to its prevention, acting as a potential barrier to parental action to improve their child’s health-related behaviours and/or help seeking. The purpose of this study was to investigate the efficacy of an intervention (MapMe) to improve parental ability to correctly categorise their child as having overweight one-month post-intervention, and reduce child body mass index (BMI) z-score 12 months post-intervention. MapMe consists of body image scales of known child BMI and information on the consequences of childhood overweight, associated health-related behaviours and sources of support. We conducted a three-arm (paper-based MapMe, web-based MapMe and control) randomised control trial in fifteen English local authority areas with parents/guardians of 4–5- and 10–11-year-old children. Parental categorisation of child weight status was assessed using the question ‘How would you describe your child’s weight at the moment?’ Response options were: underweight, healthy weight, overweight, and very overweight. Child weight status and BMI z-scores were calculated using objectively measured height and weight data and UK90 clinical thresholds. There was no difference in the percentage of parents correctly categorising their child as having overweight/very overweight (n = 264: 41% control, 48% web-based, and 43% paper-based, p = 0.646). BMI z-scores were significantly reduced for the intervention group at 12 months post-intervention compared to controls (n = 338, mean difference in BMI z-score change −0.11 (95% CI −0.202 to −0.020, p = 0.017). MapMe was associated with a decrease in BMI z-score 12 months post-intervention, although there was no direct evidence of improved parental ability to correctly categorise child overweight status. Further work is needed to replicate these findings in a larger sample of children, investigate mechanisms of action, and determine the use of MapMe as a public health initiative.

Dietary intake information is key to understanding nutrition-related outcomes. Intake changes with age and some older people are at increased risk of malnutrition. Application, difficulties, and advantages of the 24-hour multiple pass recall (24hr-MPR) dietary assessment method in three cohorts of advanced age in the United Kingdom (UK) and New Zealand (NZ) is described. The Newcastle 85+ study (UK) recruited a single year birth cohort of people aged 85 years during 2006–7. LiLACS NZ recruited a 10-year birth cohort of Māori (indigenous New Zealanders) aged 80–90 years and a single year birth cohort of non-Māori aged 85 years in 2010. Two 24hr-MPR were conducted on non-consecutive days by trained assessors. Pictorial resources and language were adapted for the New Zealand and Māori contexts. Detailed methods are described. In the Newcastle 85+ study, 805 (93%) participants consented to the 24-MPR, 95% of whom completed two 24hr-MPR; in LiLACS NZ, 218 (82%) consented and 203 (76%) Māori and 353 (90%) non-Māori completed two 24hr-MPR. Mean time to complete each 24hr-MPR was 22 minutes in the Newcastle 85+ study, and 45 minutes for Māori and 39 minutes for non-Māori in LiLACS NZ. Dietary assessment of participants residing in residential care and those requiring proxy respondents were successfully included in both studies. Most participants (83–94%) felt that data captured by the 24hr-MPR reflected their usual dietary intake. Dietary assessment using 24hr-MPR was successful in capturing detailed dietary data including information on portion size and time of eating for over 1300 octogenarians in the UK and New Zealand (Māori and non- Māori). The 24hr-MPR is an acceptable method of dietary assessment in this age group.