Inequities in health status exist in New Zealand across the rural–urban spectrum. In parallel, rural–urban differences in health service utilisation vary by service type. Despite the New Zealand public health system being based on principles of universal access, equity and fairness, levels of health expenditure on rural and urban populations are not well understood. The purpose of the study is to undertake a rural–urban analysis of public health system expenditure, based on individual-level service utilisation and national pricing of health service events.

Individual-level service utilisation and pricing will be collated from national collection databases for all eligible users of publicly funded services. The analysis will include calendar years 2017–2024. Descriptive analysis and a two-part generalised linear regression model will be used to identify if rural–urban differences in expenditure exist, and what the association of rurality is with expenditure (if any). The model will also be used to identify geographic regions with expenditure levels that vary from those predicted using regression model weights. As the specific statistical approach will be determined by data attributes, this protocol outlines the intended approach to construct the analytical model.

Ethics approval was obtained from the University of Otago Human Research Ethics Committee (HD23/052). Māori consultation has been undertaken with the Ngāi Tahu Research Consultation Committee and will continue throughout the research process.

The aim of this work was to understand carer involvement in transitions of care from hospital to home in relation to medicines management. Specifically, via a realist review, to describe how carers provide support, to what extent do they support patients and under what circumstances are carers able to provide support towards patient care in relation to medicines management.

A realist review was conducted in line with a published protocol and as registered via PROSPERO (CRD42021262827). An initial programme theory (PT) was developed before searches of three databases, PubMed, CINHAL and EMBASE, were conducted in accordance with eligibility criteria. Data were extracted from eligible studies and synthesised into realist causal explanations in the form of Context-Mechanism-Outcome-Configurations (CMOCs) and the PT was refined. Throughout the review, a patient and PPIE group (n≥5) was involved, meeting five times, to inform the research focus and develop CMOCs and the PT by providing feedback and ensuring they capture the carer experience.

Following title and abstract screening of 4835 papers, the final number of included articles was 208. The evidence synthesis identified 31 CMOCs which were categorised into three themes: (1) continuum of support; (2) understanding the carers’ priorities, role and responsibilities through shared decision-making (SDM) and (3) access to appropriate materials, resources and support information. These themes were formed into an updated PT with accompanying narrative that explained the transition from hospital to home involving carers in medicines management and identified possible areas for future intervention development.

This review provides insights and recommendations on how carers can be better supported when managing medicines when patients are discharged from hospital. Carers need a continuum of support throughout and following the transition. Healthcare professionals can support this by understanding the carer’s priorities, role and responsibilities through SDM during the hospital stay. Consequently, carers can then be offered access to appropriate materials, resources and support information which allows them to provide better care relating to medicines in the long term.

Digital inclusion (which includes skills, accessibility and connectivity to the internet and digital devices) is a ‘super social determinant of health’ because it affects many aspects of life that influence health. Older people are especially vulnerable to digital exclusion. Existing digital inclusion interventions are commonly offered opportunistically to people who come into contact with services, or in specific locations. The lack of systematic identification of need unintentionally excludes older people who may be most in need of support, and that support is not addressing their needs.

This multi-method project includes six workstreams: (1) A survey of people aged 65+ to ask about digital use and engagement. Survey data will be used to develop a model that predicts digital exclusion from data available in primary care records. (2) Testing, via a further survey, the external validity of the model to identify those who are digitally excluded. (3) Interviews with community service providers to identify, understand and define the components of existing digital inclusion services for older people. Concurrently, a rapid review of the literature will identify evidence for interventions aimed at supporting digitally excluded adults aged 65+. (4) Interviews with people aged 65+ representing a range of digital use will explore factors from the COM-B model that influence digital behaviours—their capability (C), opportunity (O) and motivation (M) relating to digital engagement. Analysis outputs will identify the intersectional nature of barriers or facilitators to digital inclusion. (5) Co-production workshops with older people and community service providers will identify key components of interventions that are required to address digital exclusion. Components will be mapped against existing interventions, and the ‘best fit’ intervention(s) refined. An implementation plan will be developed in parallel. (6) Feasibility testing of the refined intervention(s) to assess acceptability and obtain feedback on content and delivery mechanisms.

This study was approved by the Yorkshire & The Humber - Bradford Leeds Research Ethics Committee on 23 October 2023 (ref. 23/YH/0234). Findings will be disseminated in academic journals and shared at webinars, seminars, conferences and events arranged by organisations operating across the digital inclusion and older people fields.

https://www.isrctn.com/ISRCTN18306736

Gestational diabetes mellitus (GDM) is common in pregnancy and is increasing in prevalence. It is associated with an increased risk of maternal and perinatal complications if not diagnosed and managed early. Most guidelines suggest making a diagnosis of GDM using an oral glucose tolerance test (OGTT) between 24 and 28 weeks of pregnancy at which stage there still is an increased risk of complications. Increased beta-cell secretory product concentrations have been observed prior to changes in glycaemia and can potentially be used as an early marker to diagnose and assess risk of developing GDM.

The study was a prospective, longitudinal cohort study. OGTTs were carried out at visit one: 16–18 weeks and visit two: 24–28 weeks gestation in pregnant women with at least one risk factor for GDM [Body Mass Index >30 kg/m², previous macrosomic baby (>4.5 kg), previous GDM, first degree relative with type 2 diabetes mellitus (T2DM)]. Blood sampling was performed at fasting, 30 min, 1 and 2 hours following a 75-g oral glucose load. Samples were analysed for glucose, total and intact proinsulin, insulin and C-peptide. Hormonal concentrations at visit 1 were compared between those that remained normal glucose tolerant (NGT) and those that progressed to GDM at visit 2 using receiver operator characteristic (ROC) area under the curve (AUC) to assess for discrimination between the two groups.

Unfortunately, a smaller than planned sample size was recruited due to the start of COVID-19 pandemic midway through the study. 83 pregnant women had OGTT at visit 1. Of these, 12 reached the threshold for GDM at visit 1 and were excluded. In total, data from 66 patients were included for analysis (5 Did Not Attend). Visit 1 hormone comparisons were carried out between 51 who remained NGT and 15 who progressed to GDM at visit 2. There were no significant differences at each time point in ROC AUC between the two groups for total and intact proinsulin and insulin. However, there were significant differences observed in C-peptide ROC AUC at 30 (p=0.041) and 60 min (p=0.003) between the two groups.

This study did not demonstrate significant increase in early proinsulin concentrations in patients that developed GDM. However, there were differences in C-peptide concentrations. The COVID-19 pandemic restricted the recruitment of patient numbers and further studies in a larger cohort will be needed to validate these findings.

ISRCTN16416602.

We examined studies that analysed the spatial association of cancers with demographic, environmental, behavioural and/or socioeconomic factors and the statistical methods applied.

Systematic mapping review.

Web of Science (SSCI) (search on 28 July 2022), MEDLINE, SocINDEX and CINAHL (search on 4 August 2022), additional searches included grey literature.

(1) Focused on the constituent countries of the UK (England, Wales, Scotland and Northern Ireland) and its major regions (eg, the North West); (2) compared cancer(s) outcomes with demographic, environmental, behavioural and socioeconomic characteristics by applying methods to identify their spatial association; (3) reported cancer prevalence, incidence rates, relative risk or ORs for a risk factor or to an average level of cancer.

A standardised data extraction form was developed and for all studies, core data were extracted including bibliographic information, study design, geographical factors analysed, data aggregation level, methods applied and main findings. We described and synthesised the characteristics of the studies using summary tables, charts and graphs.

52 studies were included covering a variety of objectives and geographical scales. These studies considered different types of cancer, with the most common cancer types analysed being blood and lymphoid cell cancers. The most common methods used to assess the association between cancers and geographical level factors were regression analyses, with the majority being Poisson regression, then logistic and linear regression. Studies were usually conducted at ward and local authority level, or by exact point location when distances from putative risk sources were considered. The results were usually presented in plots or as tables, instead of maps.

Our results highlight the lack of consideration of spatially explicit models in the analysed studies, with the risk of having failed the assumption of independence in the data.

CRD42022349165.

There is a need for early, non-invasive and inexpensive biomarkers for Alzheimer’s disease (AD), which could serve as a proxy measure in prevention and intervention trials that might eventually be suitable for mass screening. People with Down syndrome (DS) are the largest patient group whose condition is associated with a genetically determined increased risk of AD. The REVEAL study aims to examine changes in the structure and function of the eye in individuals with DS compared with those with mild cognitive impairment (MCI) and cognitively healthy control (HC) individuals. REVEAL will also explore whether these changes are connected to inflammatory markers previously associated with AD.

The protocol describes a cross-sectional, non-interventional, single-centre study recruiting three cohorts, including (1) participants with DS (target n=50; age range, 6–60 years), (2) participants with MCI (target n=50; age range, 50–80 years) and (3) HC participants (target n=50; age range, 50–80 years). The primary research objective is to profile retinal, choroidal and lenticular status using a variety of eye imaging modalities and retinal functional testing to determine potential associations with cognitive status. The REVEAL study will also measure and compare established blood markers for AD and proteomic and transcriptomic marker profiles between DS, MCI and HC groups. Between-group differences will be assessed with an independent sample t-test and ² tests for normally distributed or binary measures, respectively. Multivariate regression analysis will be used to analyse parameters across all three cohorts. Data collection began in October 2023 and is expected to end in October 2025.

The study gained a favourable opinion from Health and Social Care Research Ethics Committee A (REC reference 22/NI/0158; approved on 2 December 2022; Amendment 22/0064 Amend 1, 5 April 2023; Amendment 22/0064 Amend 2; 23 May 2024; Amendment 22/0064 Amend 3; 25 June 2024; Amendment 22/0064 Amend 4; 16 January 2025; Amendment 22.0064 Amend 5; 9 May 2025; Amendment 22.0064 Amend 6; 9 June 2025). The study has also been reviewed and approved by the School of Biomedical Sciences Research Ethics Filter Committee within Ulster University. Findings from the REVEAL study will be presented to academic audiences at international conferences and peer-reviewed publications in targeted high-impact journals after data collection and analysis are complete. Dissemination activities will also include presentations at public events.