Parental diabetes and birthweight in 236 030 individuals in the UK biobank study

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.BACKGROUND: The UK Biobank study provides a unique opportunity to study the causes and consequences of disease. We aimed to use the UK Biobank data to study the well-established, but poorly understood, association between low birthweight and type 2 diabetes. METHODS: We used logistic regression to calculate the odds ratio for participants' risk of type 2 diabetes given a one standard deviation increase in birthweight. To test for an association between parental diabetes and birthweight, we performed linear regression of self-reported parental diabetes status against birthweight. We performed path and mediation analyses to test the hypothesis that birthweight partly mediates the association between parental diabetes and participant type 2 diabetes status. RESULTS: Of the UK Biobank participants, 277 261 reported their birthweight. Of 257 715 individuals of White ethnicity and singleton pregnancies, 6576 had type 2 diabetes, 19 478 reported maternal diabetes (but not paternal), 20 057 reported paternal diabetes (but not maternal) and 2754 participants reported both parents as having diabetes. Lower birthweight was associated with type 2 diabetes in the UK Biobank participants. A one kilogram increase in birthweight was associated with a lower risk of type 2 diabetes (odds ratio: 0.74; 95% CI: 0.71, 0.76; P = 2 × 10(-57)). Paternal diabetes was associated with lower birthweight (45 g lower; 95% CI: 36, 54; P = 2 × 10(-23)) relative to individuals with no parental diabetes. Maternal diabetes was associated with higher birthweight (59 g increase; 95% CI: 50, 68; P = 3 × 10(-37)). Participants' lower birthweight was a mediator of the association between reported paternal diabetes and participants' type 2 diabetes status, explaining 1.1% of the association, and participants' higher birthweight was a mediator of the association between reported maternal diabetes and participants' type 2 diabetes status, explaining 1.2% of the association. CONCLUSIONS: Data from the UK Biobank provides the strongest evidence by far that paternal diabetes is associated with lower birthweight, whereas maternal diabetes is associated with increased birthweight. Our findings with paternal diabetes are consistent with a role for the same genetic factors influencing foetal growth and type 2 diabetes.ERDF (European Regional Development Fund)ESF (European Social Fund) Convergence Programme for Cornwall and the Isles of ScillyWellcome TrustThe European Research CouncilDiabetes U

The potential role of cost-utility analysis in the decision to implement major system change in acute stroke services in metropolitan areas in England

BACKGROUND: The economic implications of major system change are an important component of the decision to implement health service reconfigurations. Little is known about how best to report the results of economic evaluations of major system change to inform decision-makers. Reconfiguration of acute stroke care in two metropolitan areas in England, namely London and Greater Manchester (GM), was used to analyse the economic implications of two different implementation strategies for major system change. METHODS: A decision analytic model was used to calculate difference-in-differences in costs and outcomes before and after the implementation of two major system change strategies in stroke care in London and GM. Values in the model were based on patient level data from Hospital Episode Statistics, linked mortality data from the Office of National Statistics and data from two national stroke audits. Results were presented as net monetary benefit (NMB) and using Programme Budgeting and Marginal Analysis (PBMA) to assess the costs and benefits of a hypothetical typical region in England with approximately 4000 strokes a year. RESULTS: In London, after 90 days, there were nine fewer deaths per 1000 patients compared to the rest of England (95% CI -24 to 6) at an additional cost of £770,027 per 1000 stroke patients admitted. There were two additional deaths (95% CI -19 to 23) in GM, with a total costs saving of £156,118 per 1000 patients compared to the rest of England. At a £30,000 willingness to pay the NMB was higher in London and GM than the rest of England over the same time period. The results of the PBMA suggest that a GM style reconfiguration could result in a total greater health benefit to a region. Implementation costs were £136 per patient in London and £75 in GM. CONCLUSIONS: The implementation of major system change in acute stroke care may result in a net health benefit to a region, even one functioning within a fixed budget. The choice of what model of stroke reconfiguration to implement may depend on the relative importance of clinical versus cost outcomes

Gene-obesogenic environment interactions in the UK Biobank study

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND: Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI). METHODS: We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment. RESULTS: We found gene-environment interactions with TDI (Pinteraction = 3 × 10(-10)), self-reported TV watching (Pinteraction = 7 × 10(-5)) and self-reported physical activity (Pinteraction = 5 × 10(-6)). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely. CONCLUSIONS: Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.J.T. is funded by a Diabetes Research and Wellness Foundation Fellowship. S.E.J. is funded by the Medical Research Council (grant: MR/M005070/1). M.A.T., M.N.W. and A.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). A.R.W., H.Y. and T.M.F. are supported by the European Research Council grant: 323195:SZ-245 50371- GLUCOSEGENES-FP7-IDEAS-ERC. R.M.F. is a Sir Henry Dale Fellow (Wellcome Trust and Royal Society grant: 104150/Z/14/Z). R.B. is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. R.M.A is supported by the Wellcome Trust Institutional Strategic Support Award (WT105618MA). Z.K. is funded by Swiss National Science Foundation (31003A-143914). The funders had no influence on study design, data collection and analysis, decision to publish or preparation of the manuscript. The data reported in this paper are available via application directly to the UK Biobank

Using genetics to understand the causal influence of higher BMI on depression

 This is the final version. Available on open access from OUP via the DOI in this record.Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women. Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways. Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence. Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression.Diabetes Research and Wellness FoundationAustralian Research Training ProgramMedical Research CouncilWellcome TrustEuropean Research CouncilRoyal SocietyGillings Family FoundationDiabetes UKNational Institute for Health Research (NIHR

Higher adiposity and mental health: Causal inference using Mendelian randomization

This research has been conducted using the UK Biobank resource under application number 9072.Copyright © The Author(s) 2021. Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one-and two-sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß:-0.15, 95%CI:-0.26,-0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being.Academy of Medical Sciences (AMS) Springboard award, which is supported by the AMS, the Wellcome Trust, GCRF, the Government Department of Business, Energy and Industrial strategy, the British Heart Foundation and Diabetes UK (SBF004\1079 to J.O., F.C. and J.T.); Wellcome Senior Research Fellowship (WT220390 to R.M.F.). Diabetes UK RD Lawrence fellowship (17/0005594 to H.Y.)

Impact and sustainability of centralising acute stroke services in English metropolitan areas: retrospective analysis of hospital episode statistics and stroke national audit data

OBJECTIVES: To investigate whether further centralisation of acute stroke services in Greater Manchester in 2015 was associated with changes in outcomes and whether the effects of centralisation of acute stroke services in London in 2010 were sustained. DESIGN: Retrospective analyses of patient level data from the Hospital Episode Statistics (HES) database linked to mortality data from the Office for National Statistics, and the Sentinel Stroke National Audit Programme (SSNAP). SETTING: Acute stroke services in Greater Manchester and London, England. PARTICIPANTS: 509 182 stroke patients in HES living in urban areas admitted between January 2008 and March 2016; 218 120 stroke patients in SSNAP between April 2013 and March 2016. INTERVENTIONS: Hub and spoke models for acute stroke care. MAIN OUTCOME MEASURES: Mortality at 90 days after hospital admission; length of acute hospital stay; treatment in a hyperacute stroke unit; 19 evidence based clinical interventions. RESULTS: In Greater Manchester, borderline evidence suggested that risk adjusted mortality at 90 days declined overall; a significant decline in mortality was seen among patients treated at a hyperacute stroke unit (difference-in-differences -1.8% (95% confidence interval -3.4 to -0.2)), indicating 69 fewer deaths per year. A significant decline was seen in risk adjusted length of acute hospital stay overall (-1.5 (-2.5 to -0.4) days; P0.05), length of hospital stay declined (P<0.01), and more than 90% of patients were treated in a hyperacute stroke unit. Achievement of evidence based clinical interventions generally remained constant or improved in both areas. CONCLUSIONS: Centralised models of acute stroke care, in which all stroke patients receive hyperacute care, can reduce mortality and length of acute hospital stay and improve provision of evidence based clinical interventions. Effects can be sustained over time

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively.

Genome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases.This article is freely available via Open Access. Click on the 'Additional Link' above to access the full-text from the publisher's site.Published (Open Access

Evaluation of reconfigurations of acute stroke services in different regions of England and lessons for implementation: a mixed-methods study

Background: Centralising acute stroke services is an example of major system change (MSC). ‘Hub and spoke’ systems, consisting of a reduced number of services providing acute stroke care over the first 72 hours following a stroke (hubs), with a larger number of services providing care beyond this phase (spokes), have been proposed to improve care and outcomes. Objective: To use formative evaluation methods to analyse reconfigurations of acute stroke services in different regions of England and to identify lessons that will help to guide future reconfigurations, by studying the following contrasting cases: (1) London (implemented 2010) – all patients eligible for Hyperacute Stroke Units (HASUs); patients admitted 24 hours a day, 7 days a week; (2) Greater Manchester A (GMA) (2010) – only patients presenting within 4 hours are eligible for HASU treatment; one HASU operated 24/7, two operated from 07.00 to 19.00, Monday to Friday; (3) Greater Manchester B (GMB) (2015) – all patients eligible for HASU treatment (as in London); one HASU operated 24/7, two operated with admission extended to the hours of 07.00–23.00, Monday to Sunday; and (4) Midlands and East of England – planned 2012/13, but not implemented. Design: Impact was studied through a controlled before-and-after design, analysing clinical outcomes, clinical interventions and cost-effectiveness. The development, implementation and sustainability of changes were studied through qualitative case studies, documentation analysis (n = 1091), stakeholder interviews (n = 325) and non-participant observations (n = 92; ≈210 hours). Theory-based framework was used to link qualitative findings on process of change with quantitative outcomes. Results: Impact – the London centralisation performed significantly better than the rest of England (RoE) in terms of mortality [–1.1%, 95% confidence interval (CI) –2.1% to –0.1%], resulting in an estimated additional 96 lives saved per year beyond reductions observed in the RoE, length of stay (LOS) (–1.4 days, 95% –2.3 to –0.5 days) and delivering effective clinical interventions [e.g. arrival at a Stroke Unit (SU) within 4 hours of ‘clock start’ (when clock start refers to arrival at hospital for strokes occurring outside hospital or the appearance of symptoms for patients who are already in-patients at the time of stroke): London = 66.3% (95% CI 65.6% to 67.1%); comparator = 54.4% (95% CI 53.6% to 55.1%)]. Performance was sustained over 6 years. GMA performed significantly better than the RoE on LOS (–2.0 days, 95% CI –2.8 to –1.2 days) only. GMB (where 86% of patients were treated in HASU) performed significantly better than the RoE on LOS (–1.5 days, 95% CI –2.5 to –0.4 days) and clinical interventions [e.g. SU within 4 hours: GMB = 79.1% (95% CI 77.9% to 80.4%); comparator = 53.4% (95%CI 53.0% to 53.7%)] but not on mortality (–1.3%, 95% CI –2.7%to 0.01%; p = 0.05, accounting for reductions observed in RoE); however, there was a significant effect when examining GMB HASUs only (–1.8%, 95% CI –3.4% to –0.2%), resulting in an estimated additional 68 lives saved per year. All centralisations except GMB were cost-effective at 10 years, with a higher net monetary benefit than the RoE at a willingness to pay for a quality-adjusted life-year (QALY) of £20,000–30,000. Per 1000 patients at 10 years, London resulted in an additional 58 QALYs, GMA resulted in an additional 18 QALYs and GMB resulted in an additional 6 QALYs at costs of £1,014,363, –£470,848 and £719,948, respectively. GMB was cost-effective at 90 days. Despite concerns about the potential impact of increased travel times, patients and carers reported good experiences of centralised services; this relied on clear information at every stage. Planning change – combining top-down authority and bottom-up clinical leadership was important in co-ordinating multiple stakeholders to agree service models and overcome resistance. Implementation – minimising phases of change, use of data, service standards linked to financial incentives and active facilitation of changes by stroke networks was important. The 2013 reforms of the English NHS removed sources of top-down authority and facilitative capacity, preventing centralisation (Midlands and East of England) and delaying implementation (GMB). Greater Manchester’s Operational Delivery Network, developed to provide alternative network facilitation, and London’s continued use of standards suggested important facilitators of centralisation in a post-reform context. Limitations: The main limitation of our quantitative analysis was that we were unable to control for stroke severity. In addition, findings may not apply to non-urban settings. Data on patients’ quality of life were unavailable nationally, clinical interventions measured changed over time and national participation in audits varied. Some qualitative analyses were retrospective, potentially influencing participant views. Conclusions: Centralising acute stroke services can improve clinical outcomes and care provision. Factors related to the service model implemented, how change is implemented and the context in which it is implemented are influential in improvement. We recommend further analysis of how different types of leadership contribute to MSC, patient and carer experience during the implementation of change, the impact of change on further clinical outcomes (disability and QoL) and influence of severity of stroke on clinical outcomes. Finally, our findings should be assessed in relation to MSC implemented in other health-care specialties. Funding: The National Institute for Health Research Health Services and Delivery Research programme

Effects of centralizing acute stroke services on stroke care provision in two large metropolitan areas in England

BACKGROUND AND PURPOSE In 2010, Greater Manchester and London centralized acute stroke care into ‘hyperacute’ units (Greater Manchester=3, London=8), with additional units providing ongoing specialist stroke care nearer patients’ homes. Greater Manchester patients presenting within four hours of symptom onset were eligible for hyperacute unit admission; all London patients were eligible. Research indicates that, post-centralization, only London’s stroke mortality fell significantly more than elsewhere in England. This paper attempts to explain this difference by analyzing how centralization affects provision of evidence-based clinical interventions. METHODS Controlled before and after analysis was conducted, using national audit data covering Greater Manchester, London, and a non-centralized urban comparator (38,623 adult stroke patients, April 2008-December 2012). Likelihood of receiving all interventions measured reliably in pre- and post-centralization audits (brain scan; stroke unit admission; receiving antiplatelet; physiotherapist, nutrition, and swallow assessments) was calculated, adjusting for age, sex, stroke-type, consciousness, and whether stroke occurred in-hospital. RESULTS Post-centralization, likelihood of receiving interventions increased in all areas. London patients were overall significantly more likely to receive interventions, e.g. brain scan within three hours: Greater Manchester=65.2%[95% Confidence Interval=64.3-66.2]; London=72.1%[71.4-72.8]; comparator=55.5%[54.8-56.3]. Hyperacute units were significantly more likely to provide interventions, but fewer Greater Manchester patients were admitted to these (Greater Manchester=39%; London=93%). Differences resulted from contrasting hyperacute unit referral criteria, and how reliably they were followed. CONCLUSIONS Centralized systems admitting all stroke patients to hyperacute units, as in London, are significantly more likely to provide evidence-based clinical interventions. This may help explain previous research showing better outcomes associated with fully-centralized model