Association between emergency department attendances, sociodemographic factors and long-term health conditions in the population of Norfolk and Waveney, England: Cross sectional study.

INTRODUCTION: Demand for urgent and emergency health care in England has grown over the last decade, for reasons that are not clear. Changes in population demographics may be a cause. This study investigated associations between individuals' characteristics (including socioeconomic deprivation and long term health conditions (LTC)) and the frequency of emergency department (ED) attendances, in the Norfolk and Waveney subregion of the East of England. METHODS: The study population was people who were registered with 91 of 106 Norfolk and Waveney general practices during one year from 1 April 2022 to 31 March 2023. Linked primary and secondary care and geographical data included each individual's sociodemographic characteristics, and number of ED attendances during the same year and, for some individuals, LTCs and number of general practice (GP) appointments. Associations between these factors and ED attendances were estimated using Poisson regression models. RESULTS: 1,027,422 individuals were included of whom 57.4% had GP data on the presence or absence of LTC, and 43.1% had both LTC and general practitioner appointment data. In the total population ED attendances were more frequent in individuals aged under five years, (adjusted Incidence Rate Ratio (IRR) 1.25, 95% confidence interval 1.23 to 1.28) compared to 15-35 years); living in more socioeconomically deprived areas (IRR 0.61 (0.60 to 0.63)) for least deprived compared to most deprived,and living closer to the nearest ED. Among individuals with LTC data, each additional LTC was also associated with increased ED attendances (IRR 1.16 (1.15 to 1.16)). Among individuals with LTC and GP appointment data, each additional GP appointment was also associated with increased ED attendances (IRR 1.03 (1.026 to 1.027)). CONCLUSIONS: In the Norfolk and Waveney population, ED attendance rates were higher for young children and individuals living in more deprived areas and closer to EDs. In individuals with LTC and GP appointment data, both factors were also associated with higher ED attendance.

Digital screen use for a road safety campaign message was not associated with road safety awareness of passers-by: A quasi-experimental study.

INTRODUCTION: Recent evidence suggests fatality risks for cyclists may be increasing in Britain. Understanding how to increase levels of cycling while keeping risk low is paramount. Educating drivers about cyclists may help with road safety, and mass-media messaging is a possible avenue, potentially utilizing digital displays screens in public areas. However, no studies have examined the use of these screens for road safety campaigns. METHODS: A quasi-experiment was conducted to examine if digital screens may be effective to raise awareness of a campaign message and encourage recall of car drivers. A digital campaign image was selected that encouraged car drivers and cyclists to 'look out for each other,' and stated than 80% of cyclists owned a driving license. Views and knowledge on driver priorities around cyclists were examined before (control) and after campaign exposure (intervention), and tested using regression modelling. RESULTS: 364 people were interviewed over five days. Those interviewed on intervention days were more likely to rank 'Look out for cyclists' as being more important compared to those interviewed on control days (OR 1.20), but this was not statistically significant (p = 0.355). Those who said they had seen the image did not rank 'Look out for cyclists' higher than those who said they had not seen it (p = 0.778). The disparity between reported and displayed percentage of cyclists with a driving license did not differ between intervention and control days, but was 8% higher amongst those who claimed to have seen the image (p = 0.026). CONCLUSIONS: We did not find strong evidence that use of an image on digital screens increased public awareness or recall of a casualty reduction campaign message. Work is needed to investigate the effects of longer-term exposure to road safety images. Practical Applications: Short-term use of digital signage is not recommended for raising awareness of road safety campaigns.

Residential neighbourhood greenspace is associated with reduced risk of cardiovascular disease: A prospective cohort study.

BACKGROUND: Living in a greener neighbourhood may reduce the risk of developing incident cardiovascular disease, but evidence is limited by reliance on cross-sectional comparisons. We use data from a longitudinal study with a time-independent measure of risk to explore the association between exposure to greenspace and cardiovascular disease. METHODS: Data was from the European Prospective Investigation of Cancer Norfolk UK cohort, baseline 1993-1997 (n = 24,420). Neighbourhoods were defined as 800m radius zones around participants' home, according to their home postcode (zip code) in the year 2000. Greenspace exposure was identified using classified satellite imagery. Adjusted Cox proportional hazards regression examined associations between greenspace and incident cardiovascular disease. Mediation analysis assessed if physical activity mediated associations, whilst modification by rurality, socio-economic status and age was explored. RESULTS: The mean age of participants was 59.2 years at baseline, 54.7% were female, and mean follow-up time was 14.5 years. Individuals living in the greenest neighbourhood quartile had a 7% lower relative hazard of developing cardiovascular disease than other neighbourhoods (HR 0.93; 95% CI 0.88, 0.97; p = 0.003) after adjusting for age, sex, BMI, prevalent diabetes and socio-economic status (SES). Physical activity did not mediate the relationship (greenest compared to the least green quartile HR 0.99; 95% CI 0.97, 1.01; p = 0.416). Models predicted incidence of cardiovascular disease in the least green neighbourhoods (19.4% greenspace on average) would fall by 4.8% (95% CI 1.6%, 8.2% p = 0.003) if they were as green as the average neighbourhood (59.0% greenspace). Occupation moderated the relationship, whereby exposure to greenspace was not associated with incident CVD for participants engaged in manual occupations. CONCLUSIONS: Greener home neighbourhoods may protect against risk of cardiovascular disease even after accounting for SES, whilst the mechanism does not appear to be strongly associated with physical activity. Putative causal mechanisms require investigation.

Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.

BACKGROUND: Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. METHODS: We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. FINDINGS: The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791-15 875] in Blackpool to 6888 [6145-7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990-2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimer's disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258-2356]) was higher than for ischaemic heart disease (1200 [1155-1246]) or lung cancer (660 [642-679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. INTERPRETATION: These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. FUNDING: Bill & Melinda Gates Foundation and Public Health England.

The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: The CHAMPIONS Study.

BACKGROUND: Observational evidence suggests there is an association between air pollution and type 2 diabetes; however, there is high risk of bias. OBJECTIVE: To investigate the association between air pollution and type 2 diabetes, while reducing bias due to exposure assessment, outcome assessment, and confounder assessment. METHODS: Data were collected from 10,443 participants in three diabetes screening studies in Leicestershire, UK. Exposure assessment included standard, prevailing estimates of outdoor nitrogen dioxide and particulate matter concentrations in a 1×1km area at the participant's home postcode. Three-year exposure was investigated in the primary analysis and one-year exposure in a sensitivity analysis. Outcome assessment included the oral glucose tolerance test for type 2 diabetes. Confounder assessment included demographic factors (age, sex, ethnicity, smoking, area social deprivation, urban or rural location), lifestyle factors (body mass index and physical activity), and neighbourhood green space. RESULTS: Nitrogen dioxide and particulate matter concentrations were associated with type 2 diabetes in unadjusted models. There was no statistically significant association between nitrogen dioxide concentration and type 2 diabetes after adjustment for demographic factors (odds: 1.08; 95% CI: 0.91, 1.29). The odds of type 2 diabetes was 1.10 (95% CI: 0.92, 1.32) after further adjustment for lifestyle factors and 0.91 (95% CI: 0.72, 1.16) after yet further adjustment for neighbourhood green space. The associations between particulate matter concentrations and type 2 diabetes were also explained away by demographic factors. There was no evidence of exposure definition bias. CONCLUSIONS: Demographic factors seemed to explain the association between air pollution and type 2 diabetes in this cross-sectional study. High-quality longitudinal studies are needed to improve our understanding of the association.

Neighbourhood greenspace is associated with a slower decline in physical activity in older adults: A prospective cohort study.

Maintaining physical activity in later life is important for maintaining health and function. Activity outdoors, such as walking, jogging and cycling, may provide an accessible, sociable and practical solution, but maintaining outdoor mobility may be a challenge in later life. Providing green environments which are supportive of physical activity may facilitate this, yet research into how greenspace could be best used is inconclusive. This study evaluates the role of greenspace in protecting against decline in physical activity over time in older adults. Data from the European Prospective Investigation of Cancer Norfolk, UK, cohort 1993-2009 (N=15,672) was used. Linear regression modelling was used to examine the association between exposure to greenspace in the home neighbourhood and change in overall, recreational and outdoor physical activity measured in terms of metabolic equivalent cost (MET) in hours/week. Mediation analysis was conducted to assess if dog walking explained the relationship between greenspace and physical activity change. Models were adjusted for known and hypothesised confounders. People living in greener neighbourhoods experienced less of a decline in physical activity than those living in less green areas. Comparing change for those living in the greenest versus least green quartiles, participants showed a difference in overall physical activity of 4.21 MET hours/week (trend P=0.001), adjusted for baseline physical activity, age, sex, BMI, social class and marital status. This difference was 4.03 MET hours/week for recreational physical activity (trend P<0.001) and 1.28 MET hours/week for outdoor physical activity (trend P=0.007). Dog walking partially mediated the association between greenspace and physical activity change, by 22.6% for overall, 28.1% for recreational and 50.0% for outdoor physical activity (all P<0.001). Greenspace in the home neighbourhood may be protective against decline in physical activity among older people as they age. Dog walking is a potential mechanism in this relationship, and warrants further investigation as a way of maintaining physical activity in later life.

Residential neighbourhood greenspace is associated with reduced risk of incident diabetes in older people: a prospective cohort study.

BACKGROUND: Three cross sectional studies suggest that neighbourhood greenspace may protect against incident diabetes. This study uses data from a longitudinal study with a large sample size to investigate the association between greenspace and the occurrence of incident diabetes over time. METHODS: Data was from the European Prospective Investigation of Cancer Norfolk, UK, cohort, recruitment 1993-2007 (N = 23,865). Neighbourhoods were defined as 800 m circular buffers around participants' home locations, according to their home postcode (zip code). Greenspace exposure was defined as the percentage of the home neighbourhood that was woodland, grassland, arable land, mountain, heath and bog, according to the UK Land Cover Map. Cox proportional hazards regression examined the association between neighbourhood greenspace exposure and incident diabetes. The population attributable fraction assessed the proportion of diabetes cases attributable to exposure to least green neighbourhoods. Mediation analysis assessed if physical activity explained associations between greenspace and diabetes. Interaction analysis was used to test for the modifying effect of rurality and socio-economic status on the relationship between greenspace and diabetes. Models were adjusted for known and hypothesised confounders. RESULTS: The mean age of participants was 59 years at baseline and 55.1% were female. The mean follow-up time was 11.3 years. Individuals living in the greenest neighbourhood quartile had a 19% lower relative hazard of developing diabetes (HR 0.81; 95% CI 0.67, 0.99; p = 0.035; linear trend p = 0.010). The hazard ratio remained similar (HR 0.81; 95% CI 0.65, 0.99; p = 0.042) after adjusting for age, sex, BMI, whether a parent had been diagnosed with diabetes and socio-economic status at the individual and neighbourhood level. A HR of 0.97 was attributed to the pathway through physical activity in a fully adjusted model, although this was non-significant (95% CI 0.88, 1.08; p = 0.603). The incidence of diabetes in the least green neighbourhoods (with 20% greenspace on average) would fall by 10.7% (95% CI -2.1%, 25.2%; p = 0.106) if they were as green as the average neighbourhood observed across the whole cohort (59% greenspace on average). There were no significant interactions between rurality or socio-economic status and level of greenspace. CONCLUSIONS: Greener home neighbourhoods may protect against risk of diabetes in older adults, although this study does not support a mediation role for physical activity. Causal mechanisms underlying the associations require further investigation.

Are GIS-modelled routes a useful proxy for the actual routes followed by commuters?

Active commuting offers the potential to increase physical activity among adults by being built into daily routines. Characteristics of the route to work may influence propensity to walk or cycle. Geographic information system (GIS) software is often used to explore this by modelling routes between home and work. However, if the validity of modelled routes depends on the mode of travel used, studies of environmental determinants of travel may be biased. We aimed to understand how well modelled routes reflect those actually taken, and what characteristics explain these differences. We compared modelled GIS shortest path routes with actual routes measured using QStarz BT-Q1000X Global Positioning System (GPS) devices in a free-living sample of adults working in Cambridge and using varying travel modes. Predictors of differences, according to length and percentage overlap, between the two route sets were assessed using multilevel regression models and concordance coefficients. The 276 trips, made by 51 participants, were on average 27% further than modelled routes, with an average geographical overlap of 39%. However, predictability of the route depended on travel mode. For route length, there was moderate-to-substantial agreement for journeys made on foot and by bicycle. Route overlap was lowest for trips made by car plus walk (22%). The magnitude of difference depended on other journey characteristics, including travelling via intermediate destinations, distance, and use of busy roads. In conclusion, GIS routes may be acceptable for distance estimation and to explore potential routes, particularly active commuting. However, GPS should be used to obtain accurate estimates of environmental contexts in which commuting behaviour actually occurs. Public health researchers should bear these considerations in mind when studying the geographical determinants and health implications of commuting behaviour, and when recommending policy changes to encourage active travel.

The association between neighbourhood greenspace and type 2 diabetes in a large cross-sectional study.

OBJECTIVE: To investigate the relationship between neighbourhood greenspace and type 2 diabetes. DESIGN: Cross-sectional. SETTING: 3 diabetes screening studies conducted in Leicestershire, UK in 2004-2011. The percentage of greenspace in the participant's home neighbourhood (3 km radius around home postcode) was obtained from a Land Cover Map. Demographic and biomedical variables were measured at screening. PARTICIPANTS: 10,476 individuals (6200 from general population; 4276 from high-risk population) aged 20-75 years (mean 59 years); 47% female; 21% non-white ethnicity. MAIN OUTCOME MEASURE: Screen-detected type 2 diabetes (WHO 2011 criteria). RESULTS: Increased neighbourhood greenspace was associated with significantly lower levels of screen-detected type 2 diabetes. The ORs (95% CI) for screen-detected type 2 diabetes were 0.97 (0.80 to 1.17), 0.78 (0.62 to 0.98) and 0.67 (0.49 to 0.93) for increasing quartiles of neighbourhood greenspace compared with the lowest quartile after adjusting for ethnicity, age, sex, area social deprivation score and urban/rural status (Ptrend=0.01). This association remained on further adjustment for body mass index, physical activity, fasting glucose, 2 h glucose and cholesterol (OR (95% CI) for highest vs lowest quartile: 0.53 (0.35 to 0.82); Ptrend=0.01). CONCLUSIONS: Neighbourhood greenspace was inversely associated with screen-detected type 2 diabetes, highlighting a potential area for targeted screening as well as a possible public health area for diabetes prevention. However, none of the risk factors that we considered appeared to explain this association, and thus further research is required to elicit underlying mechanisms. TRIAL REGISTRATION NUMBER: This study uses data from three studies (NCT00318032, NCT00677937, NCT00941954).

Patterns and predictors of changes in active commuting over 12 months.

OBJECTIVE: To assess the predictors of uptake and maintenance of walking and cycling, and of switching to the car as the usual mode of travel, for commuting. METHODS: 655 commuters in Cambridge, UK reported all commuting trips using a seven-day recall instrument in 2009 and 2010. Individual and household characteristics, psychological measures relating to car use and environmental conditions on the route to work were self-reported in 2009. Objective environmental characteristics were assessed using Geographical Information Systems. Associations between uptake and maintenance of commuting behaviours and potential predictors were modelled using multivariable logistic regression. RESULTS: Mean within-participant changes in commuting were relatively small (walking: +3.0 min/week, s.d.=66.7; cycling: -5.3 min/week, s.d.=74.7). Self-reported and objectively-assessed convenience of public transport predicted uptake of walking and cycling respectively, while convenient cycle routes predicted uptake of cycling and a pleasant route predicted maintenance of walking. A lack of free workplace parking predicted uptake of walking and alternatives to the car. Less favourable attitudes towards car use predicted continued use of alternatives to the car. CONCLUSIONS: Improving the convenience of walking, cycling and public transport and limiting the availability of workplace car parking may promote uptake and maintenance of active commuting.

Neighbourhood, Route and Workplace-Related Environmental Characteristics Predict Adults' Mode of Travel to Work.

OBJECTIVE: Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics. METHODS: Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS) software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression. RESULTS: Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20-1.85]; cycling OR 0.43 [95% CI 0.23-0.83]), low street connectivity (OR 0.22, [0.07-0.67]; OR 0.48 [0.26-0.90]) and free car parking at work (OR 0.24 [0.10-0.59]; OR 0.55 [0.32-0.95]). Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools) close to work (OR 0.36 [0.21-0.62]) and a railway station further from home (OR 0.53 [0.30-0.93]). Covariates strongly predicted travel mode (pseudo r-squared 0.74). CONCLUSIONS: Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode choice, and could be addressed as part of transport policy and infrastructural interventions to promote active commuting.

Using spatial equity analysis in the process evaluation of environmental interventions to tackle obesity: the healthy towns programme in England.

INTRODUCTION: Process evaluations of environmental public health interventions tend not to consider issues of spatial equity in programme delivery. However, an intervention is unlikely to be effective if it is not accessible to those in need. Methods are required to enable these considerations to be integrated into evaluations. Using the Healthy Towns programme in England, we demonstrate the potential of spatial equity analysis in the evaluation of environmental interventions for diet and physical activity, examining whether the programme was delivered to those in greatest need. METHODS: Locations of new physical infrastructure, such as cycle lanes, gyms and allotments, were mapped using a geographic information system. A targeting ratio was computed to indicate how well-located the infrastructure was in relation to those at whom it was specifically aimed, as detailed in the relevant project documentation, as well as to generally disadvantaged populations defined in terms of U.K. Census data on deprivation, age and ethnicity. Differences in targeting were examined using Kruskal-Wallis and t-tests. RESULTS: The 183 separate intervention components identified were generally well located, with estimated targeting ratios above unity for all population groups of need, except for black and ethnic minorities and children aged 5-19 years. There was no evidence that clustering of population groups influenced targeting, or that trade-offs existed when components were specifically targeted at more than one group. CONCLUSIONS: The analysis of spatial equity is a valuable initial stage in assessing the provision of environmental interventions. The Healthy Towns programme can be described as well targeted in that interventions were for the most part located near populations of need.