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Aims: The current study aimed to evaluate implementation fidelity of an Integrated Healthy Lifestyle Service (IHLS). Methods: A pragmatic sample of 28 individual interviews and 11 focus groups were conducted. This resulted in a total of 81 (22 male) individuals comprising key stakeholders (n = 18), as well as intervention staff across senior management (n = 4), team lead (n = 14) and practitioner (n = 11) roles, and intervention clients (n = 34). Results: A mixed degree of implementation fidelity was demonstrated throughout the five a priori fidelity domains of study design, provider training, intervention delivery, intervention receipt, and enactment. Stakeholders, staff and clients alike noted a high degree of intervention receipt across all services offered. Contrastingly, practitioners noted that they received minimal formal operational, data systems, clinical, and curriculum training as well as a lack of personal development opportunities. Consequently, practitioners reported low confidence in delivering sessions and collecting and analysing any data. A top-down approach to information dissemination within the service was also noted among practitioners which affected motivation and overall team morale. Conclusion: Results can be used to conceptualise best practices as a process to further strengthen the design, delivery and recruitment strategies of the IHLS.

Degree of resident participation in a case is often used as a surrogate marker for operative autonomy, an essential element of surgical resident training. Previous studies have demonstrated a considerable disagreement between the perceptions of attending surgeons and trainees when it comes to estimating operative participation. The Da Vinci Surgical System dual console interface allows machine generated measurements of trainee's active participation, which has the potential to obviate the need for labor intensive direct observation of surgical procedures. However, the robotic metrics require validation. We present a comparison of operative participation as perceived by the resident, faculty, trained research staff observer (gold standard), and robotic machine generated data.A total of 28 consecutive robotic inguinal hernia repair procedures were observed by research staff. Operative time, percent active time for the resident, and number of handoffs between the resident and attending were recorded by trained research staff in the operating room and the Da Vinci Surgical System. Attending and resident evaluations of operative performance and perceptions of percent active time for the resident were collected using standardized forms and compared with the research staff observed values and the robot-generated console data. Wilcoxon two-sample tests and Pearson Correlation coefficients statistical analysis were performed.Robotic inguinal hernia repair cases had a mean operative time of 91.3 (30) minutes and an attending-rated mean difficulty of 3.1 (1.26) out of 5. Residents were recorded to be the active surgeon 71.8% (17.7) of the total case time by research staff. There was a strong correlation (r = 0.77) in number of handoffs between faculty and trainee as recorded by the research staff and robot (4.28 (2.01) vs. 5.8 (3.04) respectively). The robotic machine generated data demonstrated the highest degree of association when compared to the gold standard (research staff observed data), with r = 0.98, p 0.0001. Lower levels of association were seen with resident reported (r = 0.66) perceptions and faculty-reported (r = 0.55) perceptions of resident active operative time.Our findings suggest that robot-generated performance metrics are an extremely accurate and reliable measure of intraoperative resident participation indicated by a very strong correlation with the data recorded by research staff's direct observation of the case. Residents demonstrated a more accurate awareness of their degree of participation compared with faculty surgeons. With high accuracy and ease of use, robotic surgical system performance metrics have the potential to be a valuable tool in surgical training and skill assessment.

Background/objective: Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of ‘big data’ presents a potential solution to this challenge. Big data is defined by Delphi consensus as: always digital, has a large sample size, and a large volume or variety or velocity of variables that require additional computing power (Vogel et al. Int J Obes. 2019). ‘Additional computing power’ introduces the concept of big data analytics. The aim of this paper is to showcase international research case studies presented during a seminar series held by the Economic and Social Research Council (ESRC) Strategic Network for Obesity in the UK. These are intended to provide an in-depth view of how big data can be used in obesity research, and the specific benefits, limitations and challenges encountered. Methods and results: Three case studies are presented. The first investigated the influence of the built environment on physical activity. It used spatial data on green spaces and exercise facilities alongside individual-level data on physical activity and swipe card entry to leisure centres, collected as part of a local authority exercise class initiative. The second used a variety of linked electronic health datasets to investigate associations between obesity surgery and the risk of developing cancer. The third used data on tax parcel values alongside data from the Seattle Obesity Study to investigate sociodemographic determinants of obesity in Seattle. Conclusions: The case studies demonstrated how big data could be used to augment traditional data to capture a broader range of variables in the obesity system. They also showed that big data can present improvements over traditional data in relation to size, coverage, temporality, and objectivity of measures. However, the case studies also encountered challenges or limitations; particularly in relation to hidden/unforeseen biases and lack of contextual information. Overall, despite challenges, big data presents a relatively untapped resource that shows promise in helping to understand drivers of obesity.

BackgroundInternationally, the prevalence of adults with obesity is a major public health concern. Few studies investigate the explanatory pathways between fast-food outlets and body mass index (BMI). We use structural equation modelling to explore an alternative hypothesis to existing research using area-level deprivation as the predictor of BMI and fast-food outlets and diet quality as mediators.MethodsAdults (n=7544) from wave II of the Yorkshire Health Study provided self-reported diet, height and weight (used to calculate BMI). Diet quality was based on sugary drinks, wholemeal (wholegrain) bread and portions of fruit and vegetables. Fast-food outlets were mapped using the Ordnance Survey Points of Interest within 2 km radial buffers around home postcode which were summed to indicate availability. Age (years), gender (female/male) and long-standing health conditions (yes/no) were included as covariates.ResultsThere was little evidence linking fast-food outlets to diet or BMI. An independent association between fast-food outlet availability and BMI operated counterintuitively and was small in effect. There was also little evidence of mediation between fast-food outlet availability and BMI. However, there was more evidence that area-level deprivation was associated with increased BMI, both as an independent effect and through poorer diet quality.ConclusionThis exploratory study offers a first step for considering complexity and pathways linking fast-food outlets, area-level deprivation, diet quality and BMI. Research should respond to and build on the hypothesised pathways and our simple framework presented within our study.

© 2018 This study investigated if the relationship between residential fast-food outlet availability and obesity varied due to methodological diversity or by age. Cross-sectional data (n = 22,889) from the Yorkshire Health Study, England were used. Obesity was defined using self-reported height and weight (BMI ≥ 30). Food outlets (“fast-food” “large supermarkets” and “convenience or other food retail outlets”) were mapped using Ordnance Survey Points of Interest (PoI) database. Logistic regression was used for all analyses. Methodological diversity included adjustment for other food outlets as covariates and continuous count vs. quartile. The association between residential fast-food outlets and obesity was inconsistent and effects remained substantively the same when considering methodological diversity. This study contributes to evidence by proposing the use of a more comprehensive conceptual model adjusting for wider markers of the food environment. This study offers tentative evidence that the association between fast-food outlets and obesity varies by age.

Background Obesity remains one of the most challenging public health issues of our modern time. Despite the face validity of claims for influence, studies on the causes of obesity have reported the influence of the food environment to be inconsistent. This inconsistency has been attributed to the variability of measures used by researchers to represent the food environments—Researcher-Defined Food Environments (RDFE) like circular, street-network buffers, and others. This study (i.) determined an individual’s Activity Space (AS) (ii.) explored the accuracy of the RDFE in representing the AS, (iii.) investigated the accuracy of the RDFE in representing actual exposure, and (iv.) explored whether exposure to food outlet reflects the use of food outlets. Methods Data were collected between June and December 2018. A total of 65 participants collected Global Positioning System (GPS) data, kept receipt of all their food purchases, completed a questionnaire about their personal information and had their weight and height measured. A buffer was created around the GPS points and merged to form an AS (GPS-based AS). Results Statistical and geospatial analyses found that the AS size of participants working away from home was positively related to the Euclidean distance from home to workplace; the orientation (shape) of AS was also influenced by the direction of workplace from home and individual characteristics were not predictive of the size of AS. Consistent with some previous studies, all types and sizes of RDFE variably misrepresented individual exposure in the food environments. Importantly, the accuracy of the RDFE was significantly improved by including both the home and workplace domains. The study also found no correlation between exposure and use of food outlets. Conclusions Home and workplace are key activity nodes in modelling AS or food environments and the relationship between exposure and use is more complex than is currently suggested in both empirical and policy literature.

Background: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. Methods: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. Results: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. Conclusions: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion.

Little research has investigated associations between a combined measure of the food and physical activity (PA) environment, BMI (body-mass-index) and obesity. Cross-sectional data (n=22,889, age 18-86years) from the Yorkshire Health Study were used [2010-2013]. BMI was calculated using self-reported height and weight; obesity=BMI≥30. Neighbourhood was defined as a 2km radial buffer. Food outlets and PA facilities were sourced from Ordnance Survey Points of Interest (PoI) and categorised into 'fast-food', 'large supermarkets', 'convenience and other food retail outlets' and 'physical activity facilities'. Parks were sourced from Open Street Map. Latent class analysis was conducted on these five environmental variables and availability was defined by quartiles of exposure. Linear and logistic regressions were then conducted for BMI and obesity respectively for different neighbourhood types. Models adjusted for age, gender, ethnicity, area-level deprivation, and rural/urban classification. A five-class solution demonstrated best fit and was interpretable. Neighbourhood typologies were defined as; 'low availability', 'moderate availability', 'moderate PA, limited food', 'saturated' and 'moderate PA, ample food'. Compared to low availability, one typology demonstrated lower BMI (saturated, b=-0.50, [95% CI=-0.76, -0.23]), while three showed higher BMI (moderate availability, b=0.49 [0.27, 0.72]; moderate PA, limited food, b=0.30 [0.01, 0.59]; moderate PA, ample food, b=0.32 [0.08, 0.57]). Furthermore, compared to the low availability, saturated neighbourhoods showed lower odds of obesity (OR=0.86 [0.75, 0.99]) while moderate availability showed greater odds of obesity (OR=1.18 [1.05, 1.32]). This study supports population-level approaches to tackling obesity however neighbourhoods contained features that were health-promoting and -constraining.

Public health is increasingly engaging with multi-faceted obesity prevention efforts. Although parks represent key community assets for broader public health, they may not be distributed equitably and associations with obesity are equivocal. We investigated park access and quality relative to deprivation and obesity with individual-level data from the Yorkshire Health Study. Compared to the least deprived areas, the moderately and most deprived areas had a greater park access and park quality in terms of features and amenities. However, parks in the moderately and most deprived areas also had the most safety concerns and incivilities. Although deprivation was associated with obesity, contrary to current policy guidance, both park access and quality appear less important for understanding variations in obesity within this study. Although sub-group analyses by deprivation tertile revealed that low quality park amenities in highly and moderately deprived areas may be important for understanding obesity prevalence, all other associations were non-significant., Highlights • We investigated park access and quality relative to deprivation and obesity. • Moderately and highly deprived areas had a greater park access and quality in terms of features and amenities. • Moderately and highly deprived areas also had the most safety concerns and incivilities. • There was no relationship between park access and park quality and obesity.

International research linking food outlets and body mass index (BMI) is largely cross-sectional, yielding inconsistent findings. However, addressing the exposure of food outlets is increasingly considered as an important adult obesity prevention strategy. Our study investigates associations between baseline food environment types and change in BMI over time. Survey data were used from the Yorkshire Health Study (n=8,864; wave one: 2010-2012, wave two: 2013-2015) for adults aged 18-86. BMI was calculated using self-reported height (cm) and weight (kg). Restaurants, cafés, fast-food, speciality, convenience and large supermarkets were identified from the Ordnance Survey Point of Interest database within 1600m radial buffer of home postcodes. K-means cluster analysis developed food environment typologies based on food outlets and population density. Large supermarkets, restaurants, cafés, fast-food, speciality and convenience food outlets all clustered together to some extent. Three neighbourhood typologies were identified. However, multilevel models revealed that relative to cluster one all were unrelated to change in BMI (cluster 2, b= -0.146 [-0.274, 0.566]; cluster 3, b= 0.065 [-0.224, 0.356]). There was also little evidence of gender-based differences in these associations when examined in a three-way interaction. Policymakers may need to begin to consider multiple types of food outlet clusters, while further research is needed to confirm how these relate to changed BMI.

Despite considerable research, evidence supporting associations between the ‘Retail Food Environment’ (RFE) and obesity remains mixed. Differences in the methods used to measure the RFE may explain this heterogeneity. Using data on a large (n = 10,111) sample of adults from the Yorkshire Health Study (UK), we modelled cross-sectional associations between the RFE and weight status using (i) multiple definitions of ‘Fast Food’, ‘Convenience’ and ‘Supermarkets’ and (ii) multiple RFE metrics, identified in a prior systematic review to be common in the literature. Both the choice of outlet definition and the choice of RFE metric substantively impacted observed associations with weight status. Findings differed in relation to statistical significance, effect sizes, and directions of association. This study provides novel evidence that the diversity of RFE measurement methods is contributing to heterogeneous study findings and conflicting policy messages. Greater attention is needed when selecting and communicating RFE measures in research., Highlights • This study compared different Retail Food Environment (RFE) measures. • Food outlet definitions substantively impacted RFE-obesity associations. • Associations also differed substantively when employing different RFE metrics. • Existing literature uses diverse RFE measures, contributing to mixed study findings. • Overlooking measurement differences impairs evidence synthesis and translation.

This systematic review quantifies methods used to measure the 'retail food environment' (RFE), appraises the quality of methodological reporting, and examines associations with obesity, accounting for differences in methods. Only spatial measures of the RFE, such as food outlet proximity were included. Across the 113 included studies, methods for measuring the RFE were extremely diverse, yet reporting of methods was poor (average reporting quality score: 58.6%). Null associations dominated across all measurement methods, comprising 76.0% of 1937 associations in total. Outcomes varied across measurement methods (e.g. narrow definitions of 'supermarket': 20.7% negative associations vs 1.7% positive; broad definitions of 'supermarket': 9.0% negative associations vs 10.4% positive). Researchers should report methods more clearly, and should articulate findings in the context of the measurement methods employed.

This article explores the potential of using Global Positioning Systems (GPS) to capture valuable data in measuring food environments. Such data, when triangulated with more conventional methods of collection, for example daily 24-hour dietary recalls and food purchase receipts, allow researchers to gain a fuller picture of individual activity in dynamic food environments. This is vital to understanding both individual and environmental factors that influence individuals’ decision and behaviour patterns within food environments. However, the practicalities of triangulating data collection methods are challenging to both researchers and participants, and so a pilot study was undertaken to test different methods of measuring the food environment. Recruitment for the pilot study took place between August and September 2017 and of the 16 participants initially recruited, 13 took part and completed all data collection methods and provided valuable feedback about the experience. The participants’ perspectives on the process of triangulating methods, along with the findings, are discussed in the paper.

Background There continues to be a lack of understanding as to the geographical area at which the environment exerts influence on behaviour and health. This exploratory study compares different potential methods of both researcher- and participant-defined definitions of neighbourhood reflect an adolescent's activity space. Methods Seven consecutive days of global positioning system (GPS) tracking data were collected at 15 s intervals using a small exploratory adolescent sample of 14–18 year olds (n = 69) in West Yorkshire, England. A total of 304,581 GPS tracking points were collected and compared 30 different definitions of researcher-defined neighbourhoods including radial, network and ellipse buffers at 400 m, 800 m, 1000 m, 1600 m and 3000 m, as well as participant-defined self-drawn neighbourhoods. Results This exploratory study supports emerging evidence cautioning against the use of static neighbourhood definitions for defining exposure. Traditional buffers (network and radial) capture at most 67% of activity space (home radial), and at worst they captured only 3.5% (school network) and range from capturing between 3 and 88% of total time. Similarly, self-drawn neighbourhoods captured only 10% of actual daily movement. Interestingly, 40% of an adolescent's self-drawn neighbourhood was not used. We also demonstrate that buffers capture a range of space (22–95%) where adolescents do not go, thus misclassifying the exposure. Conclusion Our exploratory findings demonstrate that neither researcher- nor participant-defined definition of neighbourhood adequately captures adolescent activity space. Further research with larger samples are needed to confirm the findings of this exploratory study.

759 Background: PC is a lethal disease with limited treatment options. We utilized Comprehensive Genomic Profiling (CGP) to identify putative prognostic and/or predictive biomarkers. Methods: We retrospectively reviewed PC patients (pts) at our institution who underwent CGP utilizing the Foundation One assay. CGP was performed on hybrid-capture, adaptor ligation-based libraries for up to 315 genes plus 47 introns from 19 genes frequently rearranged in cancer. PC pts were categorized by clinical stage – localized (resectable and borderline resectable PC; LPC), locally advanced (LAPC) and metastatic (mPC). Effect of gene alterations (GAs) with at least 10% prevalence were analyzed. The marginal effect of each gene on radiographic response and survival outcomes was estimated using proportional odds and multivariate Cox regression analysis, respectively, adjusting for stage. Results: Ninety-three pts were identified - median age was 63, 55% were male, and 50% were smokers. Clinical stage at diagnosis was LPC, LAPC and mPC in 42 (45%), 23 (25%) and 28 (30%) pts, respectively. The most commonly altered genes were KRAS (94%), TP53 (75%), CDKN2A (41.2%) and SMAD4 (32.9%). All patients were microsatellite stable and the median tumor mutational burden was 1.7. 5-FU (52%) or Gemcitabine (46%) based chemotherapy combinations were utilized as the first systemic therapy. Median overall survival for patients with LPC, LAPC and mPC were 30.7, 28.8 and 9.6 months respectively. Thirty-eight (91%) pts with LPC underwent curative intent surgery compared to 15 (65%) pts with LAPC (p = 0.019). Thirty-five (95%) pts with wild type (WT) CDKN2A and 47 (94%) pts with WT CDKN2B underwent curative intent surgery compared to 13 (65%) and 1(14%) pt(s) with GAs in CDKN2A and CDKN2B respectively (p = 0.003 and p < 0.0001 respectively). The response to chemotherapy was statistically significantly higher in pts with WT CDKN2A (53%) and CDKN2B (48%) compared to pts with GAs in CDKN2A (19%) and CDKN2B (12%) (p = 0.03 and p = 0.05, respectively). Conclusions: GAs in CDKN2A/B may have a predictive and possibly a prognostic impact. The clinical validity and biological relevance of these findings need to be further explored in larger studies.

Objective: The purpose of this study was to evaluate the healthy weight services in one local authority in England, where obesity levels have been above the national average since 2006. Design: We conducted process and outcome evaluation using a qualitative methodology. Data were generated in focus group discussions and semi-structured interviews with clients, practitioners, healthcare professionals and volunteers. Results: A total of 91 individuals from six services participated in the evaluation. Staff competencies and empowerment outcomes were identified as areas of strength. However, despite examples of excellent practice and enthusiastic recommendations from clients, access and referral processes were areas of weakness. Conclusion: In England, local authorities have an important role to play in tackling obesity. It is crucial that they are provided with the tools to be able to implement healthy weight interventions effectively. A whole-systems approach presents a real opportunity for staff in local authorities and public health to work collaboratively and innovatively towards the same goal of continuous improvement in obesity management.

INTRODUCTION: To compare the ability of Body Mass Index (BMI), waist circumference (WC) and waist to height ratio (WHtR) to estimate cardiovascular disease (CVD) risk levels in adolescents. EVIDENCE ACQUISITION: A systematic review and meta-analysis was performed after a database search for relevant literature (Cochrane, Centre for Review and Dissemination, PubMed, British Nursing Index, CINAHL, BIOSIS citation index, ChildData, metaRegister). EVIDENCE SYNTHESIS: The study included 117 records representing 96 studies with 994,595 participants were included in the systematic review, 14 of which (13 studies, N.=14,610) were eligible for the meta-analysis. The results of the meta-analysis showed that BMI was a strong indicator of systolic blood pressure, diastolic blood pressure, triglycerides, high-density lipoprotein cholesterol and insulin; but not total cholesterol, low-density lipoprotein or glucose. Few studies were eligible for inclusion in the meta-analysis considering WC or WHtR (N.≤2). The narrative synthesis found measures of central adiposity to be consistently valid indicators of the same risk factors as BMI. CONCLUSIONS: BMI was an indicator of CVD risk. WC and WHtR were efficacious for indicating the same risk factors BMI performed strongly for, though there was insufficient evidence to judge the relative strength of each measure possibly due to heterogeneity in the methods for measuring and classifying WC.

This case-control study was designed to assess the efficacy of cryotherapy to prevent paclitaxel-induced painful peripheral neuropathy in women with breast cancer. Participants served as their own paired control, with randomization of the cooled glove/sock to either the dominant or the non-dominant hand/foot, worn for 15 min prior to, during, and 15 min after completion of the paclitaxel infusion. Outcome measures included the Neuropathic Pain Symptom Inventory, the Brief Pain Inventory, and quantitative sensory testing. Data were measured at each of six time points—baseline, post-treatment (approximately 2 weeks after the last paclitaxel infusion), and at the first, fifth, ninth, and final weekly paclitaxel treatments. Of 29 randomized participants, 20 (69%) received at least one cryotherapy treatment, and 11 (38%) received all four cryotherapy treatments. Ten (34%) participants could not tolerate the cryotherapy, and six (21%) declined further participation at some point during the trial. Only seven participants (24%) were available for the final post-chemotherapy QST and questionnaires. There were no significant differences in measures of neuropathy or pain between treated and untreated hands or feet. Strategies to prevent painful peripheral neuropathy are urgently needed. In this current trial, dropout due to discomfort precluded adequate power to fully understand the potential benefits of cryotherapy. Much more research is needed to discover safe and effective preventive strategies that can be easily implemented within busy infusion centers.

Background Public Health England recently published a tool to help local authorities monitor the density of fast food outlets, with restrictions on access to these ‘unhealthy’ outlets being promoted in the fight against obesity. Secondary data containing the locations of food outlets present valuable resources to guide and evaluate these interventions. However, evidence appraising these data sources is limited. This study therefore seeks to validate two sources of secondary food environment data (SFED): Ordnance Survey Points of Interest (POI) data and food hygiene data from the Food Standards Agency (FSA), against street audits. These data sources are commonly used in research, with the former also being used in the Public Health England tool. Methods Audits were conducted across 54 Lower Super Output Areas in England. All streets within each Lower Super Output Area were covered to identify the name and street address of all food outlets therein. Audit identified outlets were matched to outlets in the SFED to identify true positives (TP: outlets in both the SFED and the audits), false positives (FP: outlets in the SFED only) and false negatives (FN: outlets in the audits only). Agreement was assessed using positive predictive values (PPV: TP/(TP +FP)) and sensitivities (TP/(TP +FN)). Confidence intervals were calculated in Excel using the Agresti-Coull method. Results Overall, the street audits identified 1188 food outlets, compared to 1102 and 1098 for the POI and FSA data respectively. Sensitivity and PPV were significantly higher for FSA data (sensitivity: 0.80, CI: 0.77–0.82; PPV: 0.86, CI: 0.84–0.88) than for the POI data (sensitivity: 0.73, CI: 0.71–0.76; PPV: 0.79, CI: 0.77–0.81). Both datasets had ‘good’ agreement with street audits according to the Paquet classifications (‘good’ defined as PPV and sensitivities between 0.71 and 0.90). Conclusion This study provides new evidence for the validity of SFED commonly used in research and emergently used by policymakers. Agreement between the SFED and street audits is sufficiently good to provide local authorities with confidence in using tools and research based on these SFED. Whilst FSA data has statistically significantly higher agreement with street audits than POI, the magnitude of the difference is relatively small. POI also has other advantages (e.g. more detailed outlet classifications and better spatial accuracy). Thus, POI is still a useful and recommended source of food environment data.

Background Recent research has demonstrated that neighbourhood features such as fast-food outlets and supermarkets may co-occur. However, little research has investigated the combined influences of both the built food and physical activity (PA) environments and associations with body mass index and obesity. This study aims to use latent class analysis within a large UK adult population to investigate associations between the combined environment and obesity. Methods Cross-sectional, individual-level data (n=22,889) from Wave 1 of The Yorkshire Health Study (2010–2012) were used. Body mass index (BMI) was calculated using self-reported height and weight; obesity=BMI≥30. Neighbourhood was defined as a 2 km radial buffer; food outlets and physical activity facilities were sourced (2012) from Ordnance Survey Points of Interest (PoI) and categorised into ‘fast-food’, ‘large supermarkets’, ‘convenience and other food retail outlets’ and ‘physical activity facilities’. Parks were sourced from Open Street Map. Latent class analysis (LCA) was conducted on these five environmental variables. Logistic regression was then conducted to predict obesity based on the five neighbourhood types identified within LCA. Models adjusted for age, gender, ethnicity, area-level deprivation and rural or urban classification of the neighbourhood. Results A five-class solution fitted the dataset best and was interpretable. Neighbourhood typologies were labelled as; “low exposure” (19.0% of study population); “moderate exposure” (33.3%); “moderate PA, limited food” (12.2%); “saturated” (13.6%); “moderate PA, ample food” (21.2%). For associations with obesity, those within the low exposure typology were chosen as the exposure because low exposure to physical activity environments have the potential to reduce physical activity behaviours and although more debatable poorer access to the food environment may result in poorer dietary intake. Compared to the low exposure, one typology showed lower odds of obesity (“saturated”, OR=0.86 [0.75,0.99]) and one showed increased odds of obesity (“moderate exposure, OR=1.18 [1.05,1.32]. Discussion Meaningful neighbourhood typologies were derived from a range of food and physical activity measures using latent class analysis which explained differences in obesity in large UK based sample of adults. This study suggests that neighbourhoods were not wholly unhealthy or healthy, they were characterised by neighbourhood features that are both health-promoting and health-constraining and this resulted in complex associations with obesity.

Widespread allegations of doping in sport consistently make front page news. The findings of an independent commission for the WADA1 underscore the importance of moving beyond a focus on individual athletes to concurrently address individual, social and environmental factors in anti-doping policy and practice (socioecological perspective). The concept of such a complex interactive system has successfully generated positive behaviour change in other domains. Many sports physicians will be familiar with the Foresight Report,2 the UK’s most comprehensive investigation into obesity and its causes. This report highlighted that many obesity risk factors emerge from multiple contexts and interact to place individuals at risk. Building on this, researchers and policy makers are increasingly engaging with the idea that ‘whole systems’ create the deep harm associated with obesity and this has spawned the term ‘obesogenic environment’.3 Appreciating the equivalent complexity of doping in sport, we define a ‘dopogenic environment’ to acknowledge the sum of influences produced by the surroundings, opportunities and conditions that promote anti-doping rule violations (ADRVs). Local level factors …

Objectives Current research in the field of childhood weight management (WM) effectiveness is hampered by inconsistent terminology and criterion for WM programme completion, alongside other engagement-related concepts (e.g. adherence, dropout and attrition). Evidence reviews are not able to determine conclusive intervention effectiveness because of this issue. This study aims to quantify how various completion criterion impacts upon on: 1) the percentage of WM completers; 2) the standardised body mass index (BMI SDS) reduction; and 3) the predictors of WM completion. Study design A methodological, sensitivity analysis to examine how differential completion criterion affect programme outcomes and predictors. Methods Secondary data of 2948 children were used. All children attended a MoreLife WM programme between 2009 and 2014. The completion criterion was incrementally adjusted by 10% (i.e. completer attends 10%, 20%, 30%... of sessions) for research aims 1–2, with the percentage of completers and change in BMI SDS calculated at each increment. For aim 3, the stability (strength, direction and significance) of the predictors were examined when using the completion criterion of four alternative studies against our previous study (completion ≥70% attendance). Results The volume of programme completers decreased in a linear manner as the completion criterion became more stringent (i.e. 70–100% attendance). The change in BMI SDS conversely became incrementally greater. The strength, direction and significance of the predictors was highly dependent on the completion criterion; the odds ratio varied by 24.2% across a single predictor variable (delivery period). The degree of change is evidenced in the paper. Conclusions Inconsistent completion criterion greatly limits the synthesis of programme effectiveness and explains some of the inconsistency in the predictors of engagement. Standardised criterion for engagement-related terminology are called for.

It has been suggested that childhood obesity is inversely associated with deprivation, such that the prevalence is higher in more deprived groups. However, comparatively few studies actually use an area-level measure of deprivation, limiting the scope to assess trends in the association with obesity for this indicator. Furthermore, most assume a linear relationship. Therefore, the aim of this study was to investigate associations between area-level deprivation and three measures of adiposity in children: body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). This is a cross-sectional study in which data were collected on three occasions a year apart (2005–2007). Data were available for 13 333 children, typically aged 11–12 years, from 37 schools and 542 lower super-output areas (LSOAs). Stature, mass and WC. Obesity was defined as a BMI and WC exceeding the 95th centile according to British reference data. WHtR exceeding 0.5 defined obesity. The Index of Multiple Deprivation affecting children (IDACI) was used to determine area-level deprivation. Considerable differences in the prevalence of obesity exist between the three different measures. However, for all measures of adiposity the highest probability of being classified as obese is in the middle of the IDACI range. This relationship is more marked in girls, such that the probability of being obese for girls living in areas at the two extremes of deprivation is around half that at the peak, occurring in the middle. These data confirm the high prevalence of obesity in children and suggest that the relationship between obesity and residential area-level deprivation is not linear. This is contrary to the ‘deprivation theory’ and questions the current understanding and interpretation of the relationship between obesity and deprivation in children. These results could help make informed decisions at the local level.

Geographic Information Systems (GIS) are widely used to measure retail food environments. However the methods used are hetrogeneous, limiting collation and interpretation of evidence. This problem is amplified by unclear and incomplete reporting of methods. This discussion (i) identifies common dimensions of methodological diversity across GIS-based food environment research (data sources, data extraction methods, food outlet construct definitions, geocoding methods, and access metrics), (ii) reviews the impact of different methodological choices, and (iii) highlights areas where reporting is insufficient. On the basis of this discussion, the Geo-FERN reporting checklist is proposed to support methodological reporting and interpretation.

Purpose The purpose of this paper is to outline the work of a service provider, service user and carer group created to develop a strategy for service user and carer co-production. Design/methodology/approach A reflective narrative account is given of the process through which the group formed and began to develop a working model aimed at shaping a cultural shift towards more co-produced services. The paper has been co-produced and includes the collaborative voices of service users, carers, multi-disciplinary staff, third-sector representatives, managers and colleagues from associated services. Findings The model developed outlines three stages for services to work through in order to achieve meaningful and sustainable co-produced services. The importance of developing associated policies related to such areas as recruitment, payment, support and training is also outlined. Challenges to co-production are noted along with suggested approaches to overcoming these. Originality/value The ethos of co-production is relatively new in the UK and so knowledge of the process and model may help guide others undertaking similar work.

This essay aims to extend recent critical interest in the theatrical presence of religious confession in Shakespeare's Measure for Measure. Whilst the traditions of confession in drama are recognized, the presence of confession on stage does not make the play necessarily nostalgic for the pre-Reformation era. The play, I argue, dramatizes a multiplicity of ways in which both individuals and communities deal with the problem of sin in a post-Reformation context of doctrinal plurality. As the performance of, and allusions to, various modes of confession are presented in productive juxtaposition a dramatic dialogue emerges that critiques their respective approaches to ethical evaluation and in so doing their capacity to expose hypocrisy, to save lives, spiritual and temporal, and to restore communal harmony.

BackgroundIt is uncertain which simple measures of childhood obesity are best for predicting future obesity-related health problems and the persistence of obesity into adolescence and adulthood.ObjectivesTo investigate the ability of simple measures, such as body mass index (BMI), to predict the persistence of obesity from childhood into adulthood and to predict obesity-related adult morbidities. To investigate how accurately simple measures diagnose obesity in children, and how acceptable these measures are to children, carers and health professionals.Data sourcesMultiple sources including MEDLINE, EMBASE and The Cochrane Library were searched from 2008 to 2013.MethodsSystematic reviews and a meta-analysis were carried out of large cohort studies on the association between childhood obesity and adult obesity; the association between childhood obesity and obesity-related morbidities in adulthood; and the diagnostic accuracy of simple childhood obesity measures. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and a modified version of the Quality in Prognosis Studies (QUIPS) tool. A systematic review and an elicitation exercise were conducted on the acceptability of the simple measures.ResultsThirty-seven studies (22 cohorts) were included in the review of prediction of adult morbidities. Twenty-three studies (16 cohorts) were included in the tracking review. All studies included BMI. There were very few studies of other measures. There was a strong positive association between high childhood BMI and adult obesity [odds ratio 5.21, 95% confidence interval (CI) 4.50 to 6.02]. A positive association was found between high childhood BMI and adult coronary heart disease, diabetes and a range of cancers, but not stroke or breast cancer. The predictive accuracy of childhood BMI to predict any adult morbidity was very low, with most morbidities occurring in adults who were of healthy weight in childhood. Predictive accuracy of childhood obesity was moderate for predicting adult obesity, with a sensitivity of 30% and a specificity of 98%. Persistence of obesity from adolescence to adulthood was high. Thirty-four studies were included in the diagnostic accuracy review. Most of the studies used the least reliable reference standard (dual-energy X-ray absorptiometry); only 24% of studies were of high quality. The sensitivity of BMI for diagnosing obesity and overweight varied considerably; specificity was less variable. Pooled sensitivity of BMI was 74% (95% CI 64.2% to 81.8%) and pooled specificity was 95% (95% CI 92.2% to 96.4%). The acceptability to children and their carers of BMI or other common simple measures was generally good.LimitationsLittle evidence was available regarding childhood measures other than BMI. No individual-level analysis could be performed.ConclusionsChildhood BMI is not a good predictor of adult obesity or adult disease; the majority of obese adults were not obese as children and most obesity-related adult morbidity occurs in adults who had a healthy childhood weight. However, obesity (as measured using BMI) was found to persist from childhood to adulthood, with most obese adolescents also being obese in adulthood. BMI was found to be reasonably good for diagnosing obesity during childhood. There is no convincing evidence suggesting that any simple measure is better than BMI for diagnosing obesity in childhood or predicting adult obesity and morbidity. Further research on obesity measures other than BMI is needed to determine which is the best tool for diagnosing childhood obesity, and new cohort studies are needed to investigate the impact of contemporary childhood obesity on adult obesity and obesity-related morbidities.Study registrationThis study is registered as PROSPERO CRD42013005711.FundingThe National Institute for Health Research Health Technology Assessment programme.

Background: Current UK policy in relation to the influence of the ‘food environment’ on childhood obesity appears to be driven largely on assumptions or speculations because empirical evidence is lacking and findings from studies are inconsistent. The aim of this study was to investigate the number of food outlets and the proximity of food outlets in the same sample of children, without solely focusing on fast food. Methods: Cross sectional study over 3 years (n = 13,291 data aggregated). Body mass index (BMI) was calculated for each participant, overweight and obesity were defined as having a BMI >85th (sBMI 1.04) and 95th (sBMI 1.64) percentiles respectively (UK90 growth charts). Home and school neighbourhoods were defined as circular buffers with a 2 km Euclidean radius, centred on these locations. Commuting routes were calculated using the shortest straight line distance, with a 2 km buffer to capture varying routes. Data on food outlet locations was sourced from Leeds City Council covering the study area and mapped against postcode. Food outlets were categorised into three groups, supermarkets, takeaway and retail. Proximity to the nearest food outlet in the home and school environmental domain was also investigated. Age, gender, ethnicity and deprivation (IDACI) were included as covariates in all models. Results: There is no evidence of an association between the number of food outlets and childhood obesity in any of these environments; Home Q4 vs. Q1 OR = 1.11 (95% CI = 0.95-1.30); School Q4 vs. Q1 OR = 1.00 (95% CI 0.87 – 1.16); commute Q4 vs. Q1 OR = 0.1.00 (95% CI 0.83 – 1.20). Similarly there is no evidence of an association between the proximity to the nearest food outlet and childhood obesity in the home (OR = 0.77 [95% CI = 0.61 – 0.98]) or the school (OR = 1.01 [95% CI 0.84 – 1.23]) environment. Conclusions: This study provides little support for the notion that exposure to food outlets in the home, school and commuting neighbourhoods increase the risk of obesity in children. It seems that the evidence is not well placed to support Governmental interventions/recommendations currently being proposed and that policy makers should approach policies designed to limit food outlets with caution.

Research suggests that there has been a leveling off in obesity prevalence occurring in the child population. However, a concern with the evidence base is that all of the studies have relied upon the use of BMI. The purpose of this study was to compare waist circumference (WC), BMI, and waist-to-height ratio (WHtR) data in three different sample of children (total number: 14,697) typically aged 11-12 years. Obesity prevalence defined by BMI did not change significantly between measurement years (2005 boys 20.6%, girls 18.0%; 2006 boys 19.3%, girls 17.3%; 2007 boys 19.8%, girls 16.4%). Obesity prevalence defined by WC was considerably higher especially, in girls (2005 boys 26.3%, girls 35.6%; 2006 boys 20.3%, girls 28.2%; 2007 boys 22.1%, girls 30.1%). The prevalence of children defined as "at risk" according to WHtR (2005 boys 23.3%, girls 21.1%; 2006 boys 16.7%, girls 15.6%; 2007 boys 17.6%, girls 17.2%) was found to be between obesity prevalence, estimated using BMI and WC. This data are the most up to date collection that includes BMI and WC in three large samples of children and clearly demonstrates inconsistencies between different measurements based on current classification systems. There is a need to understand the relationship between BMI and WC, with growth and health risk to establish a consistent public health message that is easily understood by the public.

© 2015 The Royal Society for Public Health. Objectives: The accurate mass assessment of physical activity is essential for effective Public Health policy and practice. Combined with a desire to minimize participant burden, the self-reported single-item physical activity screening measure has become increasingly attractive and widespread. To help reduce any potential misclassification, refining this instrumentation in line with any changes in prescribed activity levels is essential to optimize accuracy. Study design: This study compares the levels of agreement, sensitivity and specificity for the single-item measure versus International Physical Activity Questionnaire (IPAQ) using current physical activity recommendations. Methods: Agreement was assessed in a non-probability sample of 7650 adults. The κ statistic, sensitivity and specificity were used to assess agreement between the tools for classifying participants as sufficiently active for health (≥150 min of physical activity per week) or not, and being classified as inactive (

Although complications associated with vaginal hysterectomy are rare, the most common complications involve bladder injury. These injuries are sustained most commonly during mobilization of the posterior bladder wall off of the lower uterine segment, particularly in the setting of adhesions from prior cesarean sections. Bladder injuries may present with urinary retention, gross hematuria, serum electrolyte, and creatinine abnormalities, a bowel ileus or abdominal pain. This report describes a patient who underwent a total vaginal hysterectomy complicated by an unrecognized bladder injury, rupture, and subsequent abdominopelvic urinoma, requiring surgical drainage and repair.