Moving at scale: Promising practice and practical guidance on evaluation of physical activity programmes in the UK

Paper presented at the 7th International Society for Physical Activity and Health Congress, 15th-17th October 2018, London, England.Purpose: To develop effective physical activity (PA) frameworks policy makers require an understanding of which interventions increase PA at population level. This investigation identified PA interventions in the UK; considered key challenges in evaluating interventions; and provided guidance to inform and support effective evaluation. It followed from a 2014 investigation that identified and benchmarked PA interventions in England. Methods: An open call for examples of good and promising practice was made to organisations, groups, and individuals delivering PA interventions in the UK. Participants completed a questionnaire based upon elements of the Standard Evaluation Framework for Physical Activity Programmes. Nesta Standards of Evidence were interpreted and used to score projects and programmes based on an assessment of the evaluation method used. Results: A total of 302 completed submissions were assessed; 17 interventions used a control or comparison group; 12 were evaluated by an external evaluator; 55% of interventions collected pre/post measures; 22% engaged between 1,000 and 5,000 participants with 8% including >25,000 participants; 27% had been on-going for 2-5 years; 55% were delivered in a local authority leisure facility; 40% received funding from local authorities and 32% from private funders. Conclusions: The quality of monitoring, data collection, and evaluation processes embedded into programme delivery has improved since the 2014 review, which is encouraging. Non-inclusion of control or comparison groups (although not always appropriate) remains a barrier in demonstrating the causal impact of programmes. Few studies reported independent evaluation. Inadequate or incomplete submissions also impacted assessment.Published versio

Active Mile Briefing: Evidence And Policy Summary

Active mile initiatives can be defined as initiatives that support pupils to be active during the school day by providing regular opportunities for them to move around a marked route for a dedicated period of time (for example 15 minutes) and at a self-directed pace. It is thought that if moving continuously for this amount of time, most children will accumulate the equivalent distance of approximately one mile. As such, they have been termed as active mile initiatives. Active mile initiatives have gained in popularity and momentum over recent years. Whilst there is much evidence surrounding the health benefits of physical activity for children and young people, there is currently limited peer-reviewed high-quality evaluation and/or research which has focussed specifically on the effectiveness and cost-effectiveness of active mile initiatives. Furthermore, active mile initiatives have predominantly focused on primary schools, therefore there is limited research and/or information on their delivery with other age groups and/or settings such as nurseries and secondary schools. However, many of the principles are equally valid, for example they require no specialised equipment or resources. The evidence base surrounding active mile initiatives is evolving, and further research is needed to be able to draw firm conclusions. However, the evidence reviewed in this document indicates that active mile initiatives: • are intuitively appealing to schools as a means of providing regular physical activity and have high levels of acceptability among teachers and pupils • provide a simple physical activity opportunity for pupils which is suitable for all ages and are fully inclusive • can make a meaningful contribution to the in-school delivery of 30 active minutes and the Chief Medical Officer’s recommendation of an average of at least 60 minutes of physical activity each day across the week • can contribute to improvements in children’s health and wellbeing if implemented as part of a whole school approach to physical activity • should provide an additional opportunity to be active during the school day, they are not equivalent to and should not replace Physical Education (PE) This briefing accompanies, and should be used alongside, Implementing active mile initiatives in primary schools and Practice examples of active mile initiatives in schools

Active Mile Briefing: Evidence And Policy Summary

Active mile initiatives can be defined as initiatives that support pupils to be active during the school day by providing regular opportunities for them to move around a marked route for a dedicated period of time (for example 15 minutes) and at a self-directed pace. It is thought that if moving continuously for this amount of time, most children will accumulate the equivalent distance of approximately one mile. As such, they have been termed as active mile initiatives. Active mile initiatives have gained in popularity and momentum over recent years. Whilst there is much evidence surrounding the health benefits of physical activity for children and young people, there is currently limited peer-reviewed high-quality evaluation and/or research which has focussed specifically on the effectiveness and cost-effectiveness of active mile initiatives. Furthermore, active mile initiatives have predominantly focused on primary schools, therefore there is limited research and/or information on their delivery with other age groups and/or settings such as nurseries and secondary schools. However, many of the principles are equally valid, for example they require no specialised equipment or resources. The evidence base surrounding active mile initiatives is evolving, and further research is needed to be able to draw firm conclusions. However, the evidence reviewed in this document indicates that active mile initiatives: • are intuitively appealing to schools as a means of providing regular physical activity and have high levels of acceptability among teachers and pupils • provide a simple physical activity opportunity for pupils which is suitable for all ages and are fully inclusive • can make a meaningful contribution to the in-school delivery of 30 active minutes and the Chief Medical Officer’s recommendation of an average of at least 60 minutes of physical activity each day across the week • can contribute to improvements in children’s health and wellbeing if implemented as part of a whole school approach to physical activity • should provide an additional opportunity to be active during the school day, they are not equivalent to and should not replace Physical Education (PE) This briefing accompanies, and should be used alongside, Implementing active mile initiatives in primary schools and Practice examples of active mile initiatives in schools

Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis.

OBJECTIVES: 1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs. METHODS: This study linked routine primary and secondary care EHRs in Wales, UK. A machine learning based scheme was used to identify patients with rheumatoid arthritis from primary care EHRs via the following steps: i) selection of variables by comparing relative frequencies of Read codes in the primary care dataset associated with disease case compared to non-disease control (disease/non-disease based on the secondary care diagnosis); ii) reduction of predictors/associated variables using a Random Forest method, iii) induction of decision rules from decision tree model. The proposed method was then extensively validated on an independent dataset, and compared for performance with two existing deterministic algorithms for RA which had been developed using expert clinical knowledge. RESULTS: Primary care EHRs were available for 2,238,360 patients over the age of 16 and of these 20,667 were also linked in the secondary care rheumatology clinical system. In the linked dataset, 900 predictors (out of a total of 43,100 variables) in the primary care record were discovered more frequently in those with versus those without RA. These variables were reduced to 37 groups of related clinical codes, which were used to develop a decision tree model. The final algorithm identified 8 predictors related to diagnostic codes for RA, medication codes, such as those for disease modifying anti-rheumatic drugs, and absence of alternative diagnoses such as psoriatic arthritis. The proposed data-driven method performed as well as the expert clinical knowledge based methods. CONCLUSION: Data-driven scheme, such as ensemble machine learning methods, has the potential of identifying the most informative predictors in a cost-effective and rapid way to accurately and reliably classify rheumatoid arthritis or other complex medical conditions in primary care EHRs

Longer-term efficiency and safety of increasing the frequency of whole blood donation (INTERVAL): extension study of a randomised trial of 20 757 blood donors

Background: The INTERVAL trial showed that, over a 2-year period, inter-donation intervals for whole blood donation can be safely reduced to meet blood shortages. We extended the INTERVAL trial for a further 2 years to evaluate the longer-term risks and benefits of varying inter-donation intervals, and to compare routine versus more intensive reminders to help donors keep appointments. Methods: The INTERVAL trial was a parallel group, pragmatic, randomised trial that recruited blood donors aged 18 years or older from 25 static donor centres of NHS Blood and Transplant across England, UK. Here we report on the prespecified analyses after 4 years of follow-up. Participants were whole blood donors who agreed to continue trial participation on their originally allocated inter-donation intervals (men: 12, 10, and 8 weeks; women: 16, 14, and 12 weeks). They were further block-randomised (1:1) to routine versus more intensive reminders using computer-generated random sequences. The prespecified primary outcome was units of blood collected per year analysed in the intention-to-treat population. Secondary outcomes related to safety were quality of life, self-reported symptoms potentially related to donation, haemoglobin and ferritin concentrations, and deferrals because of low haemoglobin and other factors. This trial is registered with ISRCTN, number ISRCTN24760606, and has completed. Findings: Between Oct 19, 2014, and May 3, 2016, 20 757 of the 38 035 invited blood donors (10 843 [58%] men, 9914 [51%] women) participated in the extension study. 10 378 (50%) were randomly assigned to routine reminders and 10 379 (50%) were randomly assigned to more intensive reminders. Median follow-up was 1·1 years (IQR 0·7–1·3). Compared with routine reminders, more intensive reminders increased blood collection by a mean of 0·11 units per year (95% CI 0·04–0·17; p=0·0003) in men and 0·06 units per year (0·01–0·11; p=0·0094) in women. During the extension study, each week shorter inter-donation interval increased blood collection by a mean of 0·23 units per year (0·21–0·25) in men and 0·14 units per year (0·12–0·15) in women (both p<0·0001). More frequent donation resulted in more deferrals for low haemoglobin (odds ratio per week shorter inter-donation interval 1·19 [95% CI 1·15–1·22] in men and 1·10 [1·06–1·14] in women), and lower mean haemoglobin (difference per week shorter inter-donation interval −0·84 g/L [95% CI −0·99 to −0·70] in men and −0·45 g/L [–0·59 to −0·31] in women) and ferritin concentrations (percentage difference per week shorter inter-donation interval −6·5% [95% CI −7·6 to −5·5] in men and −5·3% [–6·5 to −4·2] in women; all p<0·0001). No differences were observed in quality of life, serious adverse events, or self-reported symptoms (p>0.0001 for tests of linear trend by inter-donation intervals) other than a higher reported frequency of doctor-diagnosed low iron concentrations and prescription of iron supplements in men (p<0·0001). Interpretation: During a period of up to 4 years, shorter inter-donation intervals and more intensive reminders resulted in more blood being collected without a detectable effect on donors' mental and physical wellbeing. However, donors had decreased haemoglobin concentrations and more self-reported symptoms compared with the initial 2 years of the trial. Our findings suggest that blood collection services could safely use shorter donation intervals and more intensive reminders to meet shortages, for donors who maintain adequate haemoglobin concentrations and iron stores. Funding: NHS Blood and Transplant, UK National Institute for Health Research, UK Medical Research Council, and British Heart Foundation

Genetic associations with sporadic cerebral small vessel disease

Background: Cerebral small vessel disease (SVD) causes substantial cognitive, psychiatric and physical disabilities. Despite its common nature, SVD pathogenesis and molecular mechanisms remain poorly understood, and prevention and treatment are probably suboptimal. Identifying the genetic determinants of SVD will improve understanding and may help identify novel treatment targets. The aim of this thesis is to better understand genetic associations with SVD through investigating its pathological, radiological and clinical phenotypes. Methods: To unravel the genetic associations with SVD, I used three complementary approaches. First, I performed a systematic review looking at existing intracerebral haemorrhage (ICH) classification systems and their reliability, to help inform future studies of ICH genetics. Second, I performed a series of systematic reviews and meta-analyses, investigating associations between genetic polymorphisms and histopathologically confirmed cerebral amyloid angiopathy (CAA). Third, I performed meta-analyses of existing genome-wide datasets to determine associations of >1000 common single nucleotide polymorphisms (SNP) in the COL4A1/COL4A2 genomic region with clinico-radiological SVD phenotypes: ICH and its subtypes, ischaemic stroke and its subtypes, and white matter hyperintensities. Results: The reliability of existing ICH classification systems appeared excellent in eight studies conducted in specialist centres with experienced raters, although these existing systems have several limitations. In my systematic evaluation of CAA genetics, meta-analyses of 24 studies including 3520 participants showed robust evidence for a dose-dependent association between APOE ɛ4 and histopathological CAA. There was, however, no convincing association between APOE ɛ2 and presence of CAA in a meta-analysis of 11 studies including 1640 participants. Meta-analyses of five studies including 497 participants showed, contrary to an existing popular hypothesis, that while APOE 4 may increase the risk of developing severe CAA vasculopathy, there is no clear evidence to support a role of ɛ2. There were few data about the role of APOE in hereditary CAA, but in the three studies that had looked at this, there was no evidence for an association between APOE ɛ4 and CAA severity. There were too few studies and participants to draw firm conclusions about the effect of non-APOE ε2/ε3/ε4 genetic polymorphisms on CAA, but there were positive associations with TGF-β1, TOMM40 and CR1 genes in four studies. Finally, in my meta-analyses of the COL4A1/COL4A2 genomic region, three intronic SNPs in COL4A2 were associated with SVD phenotypes: significantly with deep ICH, and suggestively with lacunar ischaemic stroke and WMH. Conclusions: I have shown that while existing ICH classification systems appear to have very good reliability, further research is needed to determine their performance in different settings. For large population-based prospective studies of ICH genetics, anatomical systems are likely to be more feasible, scalable and appropriate, although they have limitations and will need to be further developed. Using systematic reviews and meta-analyses, I have confirmed a dose-related association between APOE ɛ4 and histopathological CAA, but also demonstrated that, despite popular acceptance, there is insufficient data to draw firm conclusions about the association with APOE ɛ2. I found some positive associations with CAA in other genes, which merit replication in further larger studies, and showed that there is currently insufficient data about the role of APOE in hereditary CAA. Finally, I identified a novel association between a locus in a known hereditary SVD gene – COL4A2 – and sporadic SVD. This highlights a new and successful approach for selecting candidate genes and can be expanded in future studies to include other known hereditary SVD genes

A Data Integration Approach to Estimating Personal Exposures to Air Pollution

Globally, air pollution is the largest environmental risk to public health. In order to inform policy and target mitigation strategies there is a need to increase our understanding of the (personal) exposures experienced by different population groups. The Data Integration Model for Exposures (DIMEX) integrates data on daily travel patterns and activities with measurements and models of air pollution using agent-based modelling to simulate the daily exposures of different population groups. Here we present the results of a case study using DIMEX to model personal exposures to PM2.5 in Greater Manchester, UK, and demonstrate its ability to explore differences in time activities and exposures for different population groups. DIMEX can also be used to assess the effects of reductions in ambient air pollution and when run with concentrations reduced to 5 µg/m 3 (new WHO guidelines) lead to an estimated (mean) reduction in personal exposures between 2.7 and 3.1 µg/m 3 across population (gender-age) groups