NIHRDataInsights/HRCSData huggingface dataset:
Title: Health economic skills for advancing health policy: capturing effects of prevention and intervention beyond traditional health services
Funder: Medical Research Council

Abstract: The Fellowship research has three specific objectives: 1) Examine the relative effects of NHS/Local Authority public spending on prevention and priority outcomes; I will use a variety of publically-available data (e.g. NOMIS, ONS, and NHS Digital) and fixed-effects regression and decomposition methods for analysis. The outcomes will include theoretical expectations from improved prevention, e.g. 1) economic productivity, 2) hospital utilisation, 3) prevalence of disease/multimorbidity. I will draw on my formal training in econometrics and heterogeneity/decomposition methods. 2) Map Vanguard new care models using my published framework and examine what combination of interventions works to affect specific outcomes; I will first map already well-described Vanguard care models to my published Foundations Framework. I will then exploit variation in the interventions and quasi-experimental analysis to determine the effectiveness of the various intervention mix on outcomes. At a national level, I will use advanced econometric analysis to compare effects of formalised ACO organisational and financial integration (14/44 STPs) with STP formation (effectively, joint commissioning). These analyses will draw on advances in programme evaluation methods. I will use individual-level data from HES and GPPS to construct outcome measures. I will draw on my formal training in econometrics and specific training on microeconomics for policy evaluation. 3) Build a model to examine and simulate within-system effects of new policy changes; At a local level, I will work with linked (health and social care data) from the Salford integrated care record and local policymakers to construct a microsimulation model. This work will build on previous examples of comprehensive models for use in evaluating health and health-related policies, e.g. the Population Health Model (POHEM) and Future Elderly Model (FEM). I will draw on my formal training in microsimulation for public policy.


Research activity codes: 8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Do gender-differences in access to urban landscapes lead to gender-inequalities in mental and physical health?
Funder: Medical Research Council

Abstract: Aims: The primary objective of this research is to fill data gaps between health geography and urban planning by quantifying gender- and age- disaggregated mobility and use of urban landscapes. Specifically, individual-level GPS-tracking and activity data will be used to determine if gender-differences in access health-promoting and health-constraining features in urban landscapes lead to gender-inequalities in mental and physical health. Methods: Existing GPS and accelerometer datasets from previous physical-activity studies we be used to identify individual 'activity spaces' of participants, including 'trips' between destinations, mode of travel, and 'places of attraction'. Various methods (e.g. Latent class analysis, Random Forests) will be used to characterise urban environments based on a hyperdimensional mix of physical, social, and economic variables measured at different spatial scales. Existing mapped datasets (e.g. Ordnance Survey, CORINE Land Cover) and new mapped data (e.g. NDVI from satellite imagery) will then be used to quantitatively-define urban environmental context (composition, configuration, density). A key strategy here is to use covariates common to other disciplines (e.g. urban planning) and that are quantitatively-defined, and therefore repeatable, to allow national and international comparison and application. Analysis of patterns will involve multi-level modelling with Bayesian inference to incorporate spatiotemporal autocorrelation among the data. Impact: The proposed research seeks to determine how individual-level patterns of behaviour and mobility interact with the built environment to create inequalities in access to health-promoting and health-constraining features in the urban landscape. Findings will help identify interventions to remove barriers to healthy lifestyles.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: Understanding the regulation of adult stem cell migration during regeneration.
Funder: Medical Research Council

Abstract: This project aims to understand the regulation of stem cell migration during regeneration, using planarians as a model system. Aspects of our previous MRC funded work have demonstrated that i) stem cell migration to a wound site requires conserved epithelial to mesenchymal transition (EMT) transcription factors, ii) that loss of tumor suppressor function is accompanied by uncontrolled migration, and that iii) migration both leads to increased DNA damage in stem cells and requires active DNA repair mechanisms to proceed. The recent novel observation that migrating stem cells in vivo encounter DNA damage , called migration-coupled DNA damage (MCDD), suggests migratory activity is a potentially novel source of significant genome instability that may underpin both transformation and/or aging of animal stem cell populations. However, as yet we do not understand the gene regulatory network (GRN) controlling normal stem cell migration during regeneration, the changes in this that lead to over-migration as tumor suppressor mechanisms fails, or how the regulation of migration and DNA repair may interact during normal migration. In this project we will perform functional genomic experiments, combining RNA-seq, ATAC-seq and RNAi knockdown with detailed observations of stem cell migration, to advance our understanding of these processes. Using RNA-seq and ATAC-seq we can establish the sets of regulatory changes that underpin migration, that lead to over-migration and that are shared between migrating cells and this that are repairing DNA damage. This will allow us to then build and test a GRN to better understand the mechanisms controlling these processes. Ultimately this work will reveal conserved regulatory interactions relevant to human disease processes.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Mechanisms of adhesion-dependent haematopoietic transdetermination
Funder: Medical Research Council

Abstract: The proposed research explores the pathway that links mechanosensing and cell fate decisions. Integrin extracellular matrix receptors are key players in mechanosensing, with contrasting roles in survival and proliferation. However, identification of a consensus pathway for the signals sensed by integrin adhesion complexes has remained elusive. We propose to use Drosophila haematopoiesis as a model system to elucidate this pathway. We have discovered a physiological cell fate change that relies on integrin mechanosensing, which is the natural reprogramming step that converts mature plasmatocytes to crystal cells. Preliminary data has shown that two integrin associated proteins are essential for the formation of crystal cells, and the number of crystal cells is easy to assay in live animals. We propose to exploit this powerful new assay to elucidate the signalling pathway linking integrins to transdetermination of cell fate. We will combine live imaging, genetics and genomics to characterize how mechanotransduction contributes to crystal cell transdetermination, and discover the different components in this integrin signalling pathway. This project will provide insights into how mechanical changes transmitted to cells orchestrate cell fate decisions, and how mechanical signals contribute to modulating immune function. The molecular mechanism of crystal cell fate determination shares conserved pathways and transcription factors with the process of haematopoietic stem cell fate acquisition in humans. Therefore, elucidating how integrin signalling intersects with these factors may aid the production of haematopoietic stem cells for therapeutic purposes.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Factors affecting childhood exposures to urban particulates (FACE-UP)
Funder: Medical Research Council

Abstract: The 2019 State of Global Air report confirmed that LMICs suffer PM2.5 concentrations which are 4-5 times those of HICs, and that this correlates with attributable diseases, deaths and reduction in life expectancy. Today's LMIC children are thus predicted, throughout their life-course, to have substantial risk of illness and reduced earning potential. FACE-UP will build evidence for culturally-relevant protective actions to decrease children's exposure to PM2.5 in cities in Indonesia and Nepal. Specific objectives and methods are: 1) To compare country contexts by: a) assessing children's exposures via ambient and personal PM2.5 monitoring, b) identifying potentially feasible protective actions with communities and agencies, c) assessing community and policy-level drivers that will influence behaviour change using social research (focus groups, interviews and questionnaire surveys) with children, parents/guardians, teachers, and policy makers, and d) evaluating children's and adults' learning behaviours; 2) To develop and test context-sensitive practices to reduce children's exposures at home, school and when outdoors, including: a) personal actions such as facemask use, building adaptations and affordable air purifiers, and b) a health impact assessment of their potential to reduce NCDs; 3) To promote sustainable behaviour change via a holistic assessment of: a) ethical issues, policy requirements, and logistics of access to affordable, effective intervention materials, and b) co-development (with children, carers and practitioners) and evaluation of informational products to maximise their usefulness and uptake at a local and global level, via agency websites/social media, schools and dissemination campaigns. The FACE-UP evidence will support ethical policy decisions, and individual actions, so that, combined with emissions reduction strategies, the world's children can grow up with the ability to reduce their risk of developing diseases from PM2.5 exposures.


Research activity codes: 3.2 INTERVENTIONS TO ALTER PHYSICAL AND BIOLOGICAL ENVIRONMENTAL RISKS
Health categories: GENERIC HEALTH RELEVANCE
Title: MRC Transition Support CDA Amandine MARECHAL
Funder: Medical Research Council

Abstract: The aim of this project is to elucidate the pumping mechanism of CcO and to investigate the effect of allosteric factors and isoforms on catalysis, using a yeast system that allows production and large scale purification of mitochondrial mutant forms of the enzyme. We will also progress the construction of a chimeric yeast/human CcO as a platform to investigate human diseases. Having identified the internal hydrophilic pathway responsible for proton pumping, we will now address the coupling mechanism using time-resolved FTIR spectroscopy to detect concerted movements of key amino acids and water molecules on chosen reaction steps with purified CcOs. This will be done on photolysis of the fully reduced CO-bound enzyme, comparing the signals recorded for the wild-type and mutant forms and, subsequently, be extended to redox reactions. We will investigate how long range factors can regulate catalysis. For instance, we will follow by FTIR spectroscopy the structural changes induced by the binding of ADP or ATP to allosteric sites on yeast supernumerary subunits from preparation of CcO-containing respiratory supercomplexes, purified from strains in which CcO isoform expression is tightly controlled. We will complete our structural biology investigations on the two CcO isoforms to reveal the molecular details responsible for the change in catalytic activity observed when the yeast is grown in normoxic and hypoxic conditions. Finally, we will look at the effect of human disease-related mutations in a chimeric yeast/human enzyme CcO. We will use our range of now established biochemical methods to determine level of expression/stability, turnover number, affinity for substrate and efficiency to pump protons. If required, more advanced biophysical techniques including FTIR spectroscopy, fast kinetics and cryo-electron microscopy will be used.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Public Health Impacts of UK's Clean Air Zones.
Funder: Medical Research Council

Abstract: The London Ultra Low Emission Zone (ULEZ) was implemented in April 2019 and will be expanded in 2021. It is a large-scale Clear Air Zone (CAZ) intervention targeting urban air pollution, principally from traffic emissions. CAZs are planned across the UK and global urban jurisdictions. There is a paucity of evidence on the impact of air quality interventions which is hampering international policy decisions. We will undertake a natural-experiment study of ULEZ to determine its impact on 1) air quality, 2) pollutant composition, 3) non-communicable disease (birth outcomes, cardiovascular and respiratory disease), 4) health inequalities and 5) multi-morbidity across the life-course. Environmental exposure data pre- and post the introduction of the ULEZ will be combined with high temporal and geographical resolution modelling approaches to quantify the impact of ULEZ on London air quality with a focus on composition. We will extend current exposure estimates from the CMAQ-urban model to include traffic related metals and PAHs. We will apply interrupted time-series analysis using a Bayesian hierarchical framework to existing (hospital and birth) and emerging (primary care) healthcare data linked to fine spatial resolution air quality, environmental and demographic data to estimate the impact of ULEZ on exposure and health. We will extend with spatio-temporal point process regression models to estimate exposure-response of modelled air quality over the implementation period (2016-2024). We will test and validate these estimates using real-world data from the planned CAZ in Birmingham. We will refine our logic model of pathways from CAZ to health by linking this research to the mechanistic findings from a prospective cohort of children (CHILL study). Policy implications for the UK, Europe and global cities, focused on health inequalities and multi-morbidity, will be synthesised through the application of a Health Effects Institute Outcomes Evaluation Cycle framework.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: Enhancing the design and analysis of cluster randomised trials using machine learning
Funder: Medical Research Council

Abstract: Pragmatic trials emerged in response to concerns that clinical trials, traditionally designed to assess efficacy, were failing to inform clinical practice. Assessing benefits and harms in highly selected patient populations under well-trained experienced clinical teams can lead to over-estimation of benefit and underestimation of harm in practice. Pragmatic trials, conversely, aim to assess benefits, harms, and cost-effectiveness in real-world settings, and to identify subgroups for whom the intervention is most effective. Cluster Randomised Trials (CRTs) have emerged as an important design for pragmatic trials. However, there are a number of methodological challenges that must be addressed in order for CRTs to fulfil their promise, including enhancing their generalizability, reducing bias, improving precision, and the identification of individualized intervention effects. In this fellowship I will gain theoretical and practical training in the emerging area of machine learning (ML) to address the above challenges. To achieve this, I will: 1. Develop a framework to emulate CRTs from observational studies to evaluate the effect of cluster-level interventions and compare parametric and non-parametric methods, including ML approaches, to estimate inverse-probability-weights to address confounding; 2. Provide practical guidance for researchers on how to exploit ML to improve the selection and adjustment for covariates in CRTs, in order to both increase precision by reducing the intra-cluster correlation and to minimise bias by adjusting for confounding; 3. Propose and evaluate ML methods to study heterogeneity in intervention effects in CRTs and estimate subgroup effects while maintaining valid confidence intervals. These objectives will be achieved by developing, extending and assessing ML methods using a mixture of theory, simulation studies and applications to case studies, including CRTs in pharmacy and psychiatry and observational data from Cancer Registries.


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Heterogeneous and long-term effects of social interventions on mortality and psychological health
Funder: Medical Research Council

Abstract: In this fellowship, I will evaluate how non-medical social interventions shape health and disease. The expansive literature documenting the social determinants of health has led policy-makers in many countries to believe that social policies could have large positive spillover effects on population health, potentially even larger than targeted healthcare policies. However, robust evidence is needed to support this claim as it remains unclear whether we can actually expect health returns from investments in education or income. For this fellowship, I will focus on education and income, the two main social determinants of health particularly amenable to policy intervention. I propose an interdisciplinary programme of work and training on the health effects of social interventions drawing on my extensive experience in policy evaluation using experimental and quasi-experimental methods. I will take advantage of three recent major advances: (1) the linkage of randomised controlled trials of education interventions to long-term routinely collected administrative data; (2) the development of novel machine learning techniques to robustly explore effect heterogeneity and (3) the addition of curated genetic data to large longitudinal social science datasets to explore the differential biosocial effects of social interventions. This will allow me to begin to address key questions on when to intervene, whom to target, and for how long.


Research activity codes: 8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE
Title: JIBE Joining Impact models of transport to spatial measures of the Built Enviornment
Funder: Medical Research Council

Abstract: Creating healthy, sustainable, 'liveable' cities is a priority in Australia and the UK. The built environment (BE) in cities - including population density, proximity to shops and services, greenspace, and the street and road network influence distribution of non-communicable diseases (NCDs) risk factors across populations. The BE shapes risk factors for NCDs including physical inactivity, and air and noise pollution. BE factors also affect traffic injuries. In response to growing concerns about preventable NCDs and policy interest in creating healthier more sustainable cities our research groups in Australia and the UK have undertaken high impact policy-relevant research by 1) conceptualising, measuring, validating, mapping and identifying inequities in the spatial distribution of measures of urban liveability; 2) examining associations between the BE and transport and other health-behaviours; 3) creating models to simulate health risks and benefits of shifting away from car travel to active modes (walking and cycling) and public transport. However, in England these impact models have not been linked to detailed BE measures assessing liveability. This means we are not able to assess current variations in, or health impacts of scenarios of new BE interventions across the population. In Australia, comprehensive BE measures assessing liveability have been developed, but these have yet to be linked to state-of-the art health impact models. Together we will overcome these limitations by creating new BE measures for city regions in England and linking these to an improved health impact model, and linking our BE measures in Australia to a version of this improved model. Our aim is to create high impact informative research that speaks directly to the needs of stakeholders. By testing co-designed urban and transport planning scenarios and estimating their health impacts, we will inform debate and policy on reducing NCDs and health inequities.


Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS;3.2 INTERVENTIONS TO ALTER PHYSICAL AND BIOLOGICAL ENVIRONMENTAL RISKS
Health categories: GENERIC HEALTH RELEVANCE
Title: Healthy survival after tuberculosis
Funder: Medical Research Council

Abstract: BACKGROUND. Health is defined as "a state of complete physical, mental and social wellbeing and not merely the absence of disease". Yet TB treatment outcomes are principally assessed by microbiological indicators immediately after completing antibiotics. Patients who have successfully completed treatment may have residual lung damage, remain at high risk of developing TB again and have a higher risk of early all-cause mortality. In addition, household contacts of patients with TB are at high risk of developing TB disease. Despite increasing awareness that TB affects the life course trajectory, the long-term impacts of TB on health - and the interventions that may mitigate against them - are poorly understood. HYPOTHESIS. TB-affected people have an unfavourable life trajectory compared with people not affected by TB. STUDY DESIGN. A prospective case control study with 20-year follow-up in the Pampas shanty-town, Lima, Peru. Data from 411 TB-affected households (2346 individuals) in which the index case was diagnosed, recruited and interviewed multiple times during treatment between 1999-2002 will be compared with the same number of community controls who were recruited into surveys in the same area and time period, who did not have any household member with active TB. STUDY PLAN. The individual and household-level data collected at multiple time points between recruitment and final follow-up aim to: - characterise and quantify the long-term impact of TB on the health trajectories of patients and their households, utilising measurements for physical, mental and social components of health; - identify determinants and causal pathways associated with long-term impacts of TB from the multitude of explanatory variables that have been collected; and - develop a predictive model of TB-related drivers over the life course and use this to identify cost-effective interventions suitable for diminishing the long-term health and socioeconomic impacts of TB.


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: GENERIC HEALTH RELEVANCE