Hannah Jordan

The Index of Multiple Deprivation 2000 and accessibility effects on health

Study objective: To investigate whether the Index of Multiple Deprivation 2000 (IMD) is more strongly related to inequalities in health in rural areas than traditional deprivation indices. To explore the contribution of the IMD domain “geographical access to services” to understanding rural health variations. Design: A geographically based cross sectional study. Setting: Nine counties in the south west region of England. Participants: All those aged below 65 who reported a limiting long term illness in the 1991 census, and all those who died during 1991–96, aged less than 65 years. Main results: The IMD is comparable with the Townsend score in its overall correlation with premature mortality (r2 = 0.44 v 0.53) and morbidity (r2 = 0.79 v 0.76). Correlation between the Townsend score and population health is weak in rural areas but the IMD maintains a strong correlation with rates of morbidity (r2 = 0.70). The “geographical access to services” domain of the IMD is not strongly correlated with rates of morbidity in rural areas (r2 = 0.04), and in urban areas displays a negative correlation (r2 = −0.47). Conclusions: The IMD has a strong relation with health in both rural and urban areas. This is likely to be the result of the inclusion of data in the IMD on the numbers of people claiming benefits related to ill health and disability. The domain “geographical access to services” is not associated with health in rural areas, although it displays some association in urban areas. This domain is potentially important but, as yet, inadequately specified in the IMD for the purposes of health research.

Socioeconomic deprivation, travel distance, location of service, and uptake of breast cancer screening in North Derbyshire, UK

Background and aim: This study examined the association between socioeconomic deprivation, travel distance, urban-rural status, location and type of screening unit, and breast screening uptake. Screening was provided at 13 locations—1 fixed and 12 mobile (3 at non-health locations). Methods: The study examined data from 1998 to 2001 for 34 868 women aged 50–64 years, calculated road travel distance, used 1991 enumeration district level Townsend socioeconomic deprivation scores, and a ward level urban-rural classification. Results: Odds of attendance for screening decreased with increasing socioeconomic deprivation, with an adjusted odds ratio of 0.64 (95%CI 0.59 to 0.70) in the most deprived relative to the least deprived category. 87% of women lived within 8 km of their screening location. The odds ratio for a 10 km increase in distance was 0.87 (95%CI 0.79 to 0.95). The odds ratios were 1.18 (95%CI 1.08 to 1.28) for screening at a non-health relative to a health location, 1.00 (95%CI 0.94 to 1.07) for the fixed site relative to the mobile unit and 1.00 (95%CI 0.91 to 1.09) for mainly rural relative to mainly urban areas. Conclusions: Socioeconomic inequality in breast screening uptake seems to persist in an established service. There was a small decrease with increasing distance, no difference between fixed and mobile units, and no difference between urban and rural areas but uptake seemed to be higher at non-health sites. Further work is needed to identify effective methods of decreasing socioeconomic inequalities in uptake and to confirm if non-health locations are associated with higher screening uptake.

Taking the Bus: Incorporating Public Transport Timetable Data into Health Care Accessibility Modelling

This paper is concerned with geographical access to hospital services by public transport. By taking advantage of newly available public transport timetable data, a software tool is developed for the analysis of bus travel times under specified journey scenarios. The example of population access to Derriford Hospital in Devon, England, is used to illustrate the application of these methods, and the social and spatial pattern of accessibility by bus is explored. The analysis reveals substantial differences between access by public and private transport, and highlights the difficulty of combining conventional drive-time analysis with the discontinuous accessibility provided by public transport. There is a need for more attention to be paid to the incorporation of public transport in accessibility modelling.

value of urban green spaces in promoting healthy living and wellbeing: prospects for planning

There has been considerable work done in recent years exploring the value of urban green space for health and wellbeing. Urban green spaces provide environmental benefits through their effects on negating urban heat, offsetting greenhouse gas emissions, and attenuating storm water. They also have direct health benefits by providing urban residents spaces for physical activity and social interaction, and allowing psychological restoration to take place. Consequently, there is a real need to understand the mechanisms by which these benefits accrue. Previously, much of the focus has been on the characteristics of the urban green space that are likely to influence its use, such as its accessibility, quality, facilities, attractiveness, and security. This assumes a causal relationship, when in reality the relationship is more complex and multifactorial. It is more likely that it is the functionality of the green space, be it for exercise or sociocultural activities, rather than its character, which translates to the reported benefits. Challenges exist, such as competing urban planning priorities, economic considerations, and market forces. There is thus a need for urban planning to match the health benefits sought with the needs of the community and the functionality that the urban green space will serve.

How different data sources and definitions of neighbourhood influence the association between food outlet availability and body mass index: a cross-sectional study

Inconsistencies in methodologies continue to inhibit understanding of the impact of the environment on body mass index (BMI). To estimate the effect of these differences, we assessed the impact of using different definitions of neighbourhood and data sets on associations between food outlet availability within the environment and BMI. Previous research has not extended this to show any differences in the strength of associations between food outlet availability and BMI across both different definitions of neighbourhood and data sets. Descriptive statistics showed differences in the number of food outlets, particularly other food retail outlets between different data sets and definitions of neighbourhood. Despite these differences, our key finding was that across both different definitions of neighbourhood and data sets, there was very little difference in size of associations between food outlets and BMI. Researchers should consider and transparently report the impact of methodological choices such as the definition of neighbourhood and acknowledge any differences in associations between the food environment and BMI.

Associations between the combined physical activity environment, socioeconomic status, and obesity: a cross-sectional study

Aims: This study investigates associations between the combined physical activity environment and obesity and explores any sub-group effects by individual-level socioeconomic status. Methods: In a large cross-sectional cohort (n = 22,889) from the Yorkshire Health Study, body mass index was calculated using self-reported height and weight and obesity was defined as a body mass index ≥ 30. The physical activity environment was split into ‘unfavourable physical activity’, ‘moderately favourable physical activity’ and ‘favourable physical activity’ environments. This was based on the count of parks and physical activity facilities within a 2 km radial buffer centred on home addresses. A favourable physical activity environment was defined as having ≥1 physical activity facility and ≥1 park, unfavourable as having no physical activity facility and park and any other combinations defined as moderately favourable. Logistic regression (odds ratios) identified associations with obesity. Results: Relative to ‘unfavourable physical activity environments’, individuals within favourable physical activity environments were less likely to be obese (odds ratio = 0.90; 95% confidence interval = 0.82–0.97), and there was no effect for moderately favourable environment. Furthermore, once stratified by education level, this relationship was only present for those of higher education. Conclusion: Our findings provide novel UK evidence and is one of the first papers internationally that highlights the importance of considering the interplay of individual-level socioeconomic factors when investigating associations between the physical activity environment and obesity.

Access and quality of parks and associations with obesity: A cross-sectional study

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.

What are older smokers' attitudes to quitting and how are they managed in primary care?: An analysis of the cross-sectional English Smoking Toolkit Study

Objectives To investigate whether age is associated with access to smoking cessation services. Design Data from the Smoking Toolkit Study 2006–2015, a repeated multiwave cross-sectional household survey (n=181 157). Setting England. Participants Past-year smokers who participated in any of the 102 waves stratified into age groups. Outcome measures Amount smoked and nicotine dependency, self-reported quit attempts and use of smoking cessation interventions. Self-report of whether the general practitioner (GP) raised the topic of smoking and made referrals for pharmacological support (prescription of nicotine replacement therapies (NRTs)) or other support (counselling or support groups). Results Older smokers (75+ years) were less likely to report that they were attempting to quit smoking or seek help from a GP, despite being less nicotine-dependent. GPs raised smoking as a topic equally across all age groups, but smokers aged 70+ were more likely not to be referred for NRT or other support (ORs relative to 16–54 years; 70–74 years 1.27, 95% CI 1.03 to 1.55; 75–79 years 1.87, 95% CI 1.43 to 2.44; 80+ years 3.16, 95% CI 2.20 to 4.55; p value for trend <0.001). Conclusions Our findings suggest that there are potential missed opportunities in facilitating smoking cessation in older smokers. In this large population-based study, older smokers appeared less interested in quitting and were less likely to be offered support, despite being less addicted to nicotine than younger smokers. It is unclear whether this constitutes inequitable access to services or reflects informed choices by older smokers and their GPs. Future research is needed to understand why older smokers and GPs do not pursue smoking cessation. Service provision should consider how best to reduce these variations, and a stronger effectiveness evidence base is required to support commissioning for this older population so that, where appropriate, older smokers are not missing out on smoking cessation therapies and the health benefits of cessation at older ages.

What factors facilitate the engagement with flipped classrooms used in the preparation for postgraduate medical membership examinations

Background The “flipped classroom,” a pedagogical model where typical lecture and homework elements are reversed, is being advocated in medical education to support the teaching of a large curriculum. However, research into the use of this model in postgraduate medical education, which requires the application of acquired knowledge, is limited. The aim of this study was to explore the barriers and facilitators to engagement with the flipped classroom model in preparation for the written element of postgraduate membership examinations. Methods Three focus groups (n=14) were held between February and June 2016. Participants were drawn from a membership examination preparation course, run by the University of Shef-field. Two of the groups (n=10) involved “students” (public health registrars) while the other focus group (n=4) was held with “tutors” (experienced registrars and consultants). The focus groups were audiorecorded and transcribed verbatim. Transcripts were thematically analyzed by using both predetermined and emergent themes. Results Key themes that emerged from the data included variation in learning and teaching styles of individuals as well as the feasibility and flexibility of the overall course design. However, management of students’ expectations was found to be the fundamental factor, which underpinned the engagement. Conclusion The complex interaction of factors affecting engagement in this study highlights the need to consider the appropriateness of the flipped classroom model. However, this must be balanced by the potential benefits of the approach for delivering a large curriculum. Recognizing the central importance of managing expectations at the outset would be useful when considering this model in postgraduate medical education.

P26 Associations between typologies of neighbourhood environments and associations with obesity: a cross-sectional study

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.