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Abstract In the UK people living in disadvantaged communities are less likely than those with higher socio-economic status to have a healthy diet. To address this inequality, it is crucial scientists, practitioners and policy makers understand the factors that hinder and assist healthy food choice in these individuals. In this scoping review, we aimed to identify barriers and facilitators to healthy eating among disadvantaged individuals living in the UK. Additionally, we used the Theoretical Domains Framework (TDF) to synthesise results and provide a guide for the development of theory-informed behaviour change interventions. Five databases were searched, (CINAHL, Embase, MEDLINE, PsycINFO, and Web of Science) for articles assessing healthy dietary intake of disadvantaged adults living in the UK. A total of 50 papers (34 quantitative; 16 qualitative) were included in this review. Across all studies we identified 78 barriers and 49 facilitators found to either impede and/or encourage healthy eating. Both barriers and facilitators were more commonly classified under the Environmental, Context and Resources TDF domain, with 74% of studies assessing at least one factor pertaining to this domain. Results thus indicate that context related factors such as high cost and accessibility of healthy food, rather than personal factors, such as lack of efficiency in healthy lifestyle drive unhealthy eating in disadvantaged individuals in the UK. We discuss how such factors are largely overlooked in current interventions and propose that more effort should be directed towards implementing interventions that specifically target infrastructures rather than individuals.

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Abstract The UK food system affects social, economic and natural environments and features escalating risk of food insecurity. Yet it should provide access to safe, nutritious, affordable food for all citizens. Disadvantaged UK communities [individuals and families at risk of food and housing insecurity, often culturally diverse] have often been conceptualised in terms of individual behaviour which may lead to findings and conclusions based on the need for individual change. Such communities face public health challenges and are often treated as powerless recipients of dietary and health initiatives or as ‘choiceless’ consumers within food supply chains. As transforming the UK food system has become a national priority, it is important a diverse range of evidence is used to support understanding of the diets of disadvantaged communities to inform food systems transformation research. A scoping review of UK peer reviewed qualitative literature published in MEDLINE, CINAHL Plus with Full Text, EMBASE, PsycINFO and Web of Science between January 2010 and May 2021 in English. Eligibility criteria were applied, a data extraction table summarised data from included studies, and synthesis using social practice theory was undertaken. Forty-five qualitative studies were reviewed, which included the views of 2,434 community members aged between 5 and 83. Studies used different measures to define disadvantage. Synthesis using social practice theory identified themes of food and dietary practices shaped by interactions between ‘material factors’ (e.g. transport, housing and money), ‘meanings’ (e.g. autonomy and independence), and ‘competencies’ (e.g. strategies to maximise food intake). These concepts are analysed and critiqued in the context of the wider literature to inform food systems transformation research. This review suggests to date, qualitative research into diets of UK disadvantaged communities provides diverse findings that mainly conceptualise disadvantage at an individual level. Whilst several studies provide excellent characterisations of individual experience, links to ‘macro’ processes such as supply chains are largely missing. Recommendations are made for future research to embrace transdisciplinary perspectives and utilise new tools (e.g., creative methods and good practice guides), and theories (e.g., assemblage) to better facilitate food systems transformation for disadvantaged communities.

"Race" and "ethnicity" are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as "the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by "race," have been largely ignored in medical research. The Women's Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020-2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include "race" and/or "ethnicity" in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant's self-identified "race" and "ethnicity", and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.

BackgroundAlterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood.MethodsUsing a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval).ResultsWe found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1, KCNH2, and SCN5A), a controversial monogenic SCD gene (KCNE1), and novel genes (PAM and MFGE8) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P=8.4×10-5). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P=4×10-25), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals.ConclusionsOur findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.

ObjectiveFew studies have prospectively examined the associations of lipoprotein(a) [Lp(a)] levels with the risk of abdominal aortic aneurysm (AAA), especially in women. Accounting for commonly recognized risk factors, we investigated the baseline Lp(a) levels and the risk of AAA among postmenopausal women participating in the ongoing national Women's Health Initiative.MethodsWomen's Health Initiative participants with baseline Lp(a) levels available who were beneficiaries of Medicare parts A and B fee-for-service at study enrollment or who had aged into Medicare at any point were included. Participants with missing covariate data or known AAA at baseline were excluded. Thoracic aneurysms were excluded owing to the different pathophysiology. The AAA cases and interventions were identified using the International Classification of Diseases, 9th and 10th revision, codes and Current Procedural Terminology codes from claims data. Hazard ratios were computed using Cox proportional hazard models according to the quintiles of Lp(a).ResultsThe mean age of the 6615 participants included in the analysis was 65.3 years. Of the 6615 participants, 66.6% were non-Hispanic white, 18.9% were black, 7% were Hispanic and 4.7% were Asian/Pacific Islander. Compared with the participants in the lowest Lp(a) quintile, those in higher quintiles were more likely to be overweight, black, and former or current smokers, to have hypertension, hyperlipidemia, and a history of cardiovascular disease, and to use menopausal hormone therapy and statins. During 65,476 person-years of follow-up, with a median of 10.4 years, 415 women had been diagnosed with an AAA and 36 had required intervention. More than one half had required intervention for a ruptured AAA. We failed to find a statistically significant association between Lp(a) levels and incident AAA. Additional sensitivity analyses stratified by race, with exclusion of statin users and alternative categorizations of Lp(a) using log-transformed levels, tertiles, and a cutoff of >50 mg/dL, were conducted, which did not reveal any significant associations.ConclusionsWe found no statistically significant association between Lp(a) levels and the risk of AAA in a large and well-phenotyped sample of postmenopausal women. Women with high Lp(a) levels were more likely to be overweight, black, and former or current smokers, and to have hypertension, hyperlipidemia, and a history of cardiovascular disease, or to use hormone therapy and statins compared with those with lower Lp(a) levels. These findings differ from previous prospective, case-control, and meta-analysis studies that had supported a significant relationship between higher Lp(a) levels and an increased risk of AAA. Differences in the association could have resulted from study limitations or sex differences.

Higher trait optimism and/or lower cynical hostility are associated with healthier behaviors and lower risk of morbidity and mortality, yet their association with health care utilization has been understudied. Whether these psychological attitudes are associated with breast cancer screening behavior is unknown. To assess the association of optimism and cynical hostility with screening mammography in older women and whether sociodemographic factors acted as mediators of these relationships, we used Women's Health Initiative (WHI) observational cohort survey data linked to Medicare claims. The sample includes WHI participants without history of breast cancer who were enrolled in Medicare Parts A and B for ≥2 years from 2005-2010, and who completed WHI baseline attitudinal questionnaires (n = 48,291). We used survival modeling to examine whether screening frequency varied by psychological attitudes (measured at study baseline) after adjusting for sociodemographic characteristics, health conditions, and healthcare-related variables. Psychological attitudes included trait optimism (Life Orientation Test-Revised) and cynical hostility (Cook Medley subscale), which were self-reported at study baseline. Sociodemographic, health conditions, and healthcare variables were self-reported at baseline and updated through 2005 as available. Contrary to our hypotheses, repeated events survival models showed that women with the lowest optimism scores (i.e., more pessimistic tendencies) received 5% more frequent screenings after complete covariate adjustment (p

Co‐production is a collaborative way of working which emphasises the exchange of diverse forms of knowledge in an equal partnership for equal benefits. Co‐produced research is a key strategic aim of the UK Research and Innovation (UKRI) Transforming UK Food Systems (TUKFS) Strategic Priorities Fund; this research programme brings together researchers, policymakers, industry and communities to create positive change in the way food is produced, accessed and consumed. However, more generally, there are diverse understandings of co‐production and a lack of consensus on what 'good practice' looks like. Therefore, this study aimed to identify and map examples of co‐production methods employed across the TUKFS programme. Two creative workshops (n = 15 participants), conversations with TUKFS researchers and stakeholders (n = 15), and systematic analysis of project documents were used to critically explore co‐production activities within six TUKFS projects. A range of co‐production activities were identified. Findings highlighted areas of 'messiness' and complexity, challenges associated with applying co‐production approaches and practical solutions. Four key shared principles for co‐production were identified: (1) Relationships: developing and maintaining reciprocity‐based partnerships; (2) Knowledge: recognising the contribution of diverse forms of expertise; (3) Power: considering power dynamics and addressing imbalances; and (4) Inclusivity: ensuring research is accessible to all who wish to participate. Opportunities for reflection and reflexivity were considered crucial across all these areas. Findings contribute important insights towards a shared conceptual understanding of co‐production for food system transformation research. This paper makes recommendations for researchers, practitioners, academic institutions and funders working in this area of research and practice. [ABSTRACT FROM AUTHOR]

Abstract “Race” and “ethnicity” are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as “the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by “race,” have been largely ignored in medical research. The Women’s Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020–2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include “race” and/or “ethnicity” in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant’s self-identified “race” and “ethnicity”, and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.

Immune cell engager therapeutic strategies using bioengineered molecules to redirect immune cells into tumor are starting to demonstrate promising clinical activity in multiple early phase trials across numerous targets and a range of solid tumor types. These therapies, however, carry the risk of exaggerated cytokine-mediated on-target off-tumor adverse events that require highly specialized inpatient facilities. We report here the Royal Marsden experience of treating patients with advanced solid tumors on early phase immune engager clinical trials in a dedicated inpatient facility, focusing specifically on patterns of cytokine-mediated toxicity seen and proposing a risk-mitigation algorithm for the safe, feasible and scalable delivery of these therapies.