scholarly journals The Characteristics of Community-Driven Allotments and Revitalisation of Allotments in Deprived Areas - Focusing on the Case of Sheffield, UK -

2021 ◽  
Vol 49 (5) ◽  
pp. 138-150
Author(s):  
Jinvo Nam
Keyword(s):  
Deprived Areas

Characteristics of frequent paediatric users of emergency departments in England: an observational study using routine national data

2020 ◽  
pp. emermed-2019-209122
Author(s):  
Geva Greenfield ◽  
Mitch Blair ◽  
Paul P Aylin ◽  
Sonia Saxena ◽  
Azeem Majeed ◽  
...  
Keyword(s):  
Ethnic Groups ◽  
Emergency Departments ◽  
National Data ◽  
Frequent User ◽  
Frequent Users ◽  
Frequent Attender ◽  
Random Intercept ◽  
Frequent Attendance ◽  
Lower Likelihood ◽  
Deprived Areas

BackgroundFrequent attendances of the same users in emergency departments (ED) can intensify workload pressures and are common among children, yet little is known about the characteristics of paediatric frequent users in EDs.AimTo describe the volume of frequent paediatric attendance in England and the demographics of frequent paediatric ED users in English hospitals.MethodWe analysed the Hospital Episode Statistics dataset for April 2014–March 2017. The study included 2 308 816 children under 16 years old who attended an ED at least once. Children who attended four times or more in 2015/2016 were classified as frequent users. The preceding and subsequent years were used to capture attendances bordering with the current year. We used a mixed effects logistic regression with a random intercept to predict the odds of being a frequent user in children from different sociodemographic groups.ResultsOne in 11 children (9.1%) who attended an ED attended four times or more in a year. Infants had a greater likelihood of being a frequent attender (OR 3.24, 95% CI 3.19 to 3.30 vs 5 to 9 years old). Children from more deprived areas had a greater likelihood of being a frequent attender (OR 1.57, 95% CI 1.54 to 1.59 vs least deprived). Boys had a slightly greater likelihood than girls (OR 1.05, 95% CI 1.04 to 1.06). Children of Asian and mixed ethnic groups were more likely to be frequent users than those from white ethnic groups, while children from black and 'other' had a lower likelihood (OR 1.03, 95% CI 1.01 to 1.05; OR 1.04, 95% CI 1.01 to 1.06; OR 0.88, 95% CI 0.86 to 0.90; OR 0.90, 95% CI 0.87 to 0.92, respectively).ConclusionOne in 11 children was a frequent attender. Interventions for reducing paediatric frequent attendance need to target infants and families living in deprived areas.

scholarly journals A deep learning approach to identify unhealthy advertisements in street view images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Palmer ◽  
Mark Green ◽  
Emma Boyland ◽  
Yales Stefano Rios Vasconcelos ◽  
Rahul Savani ◽  
...  
Keyword(s):  
Deep Learning ◽  
Fast Food ◽  
Social Inequalities ◽  
Social Inequalities In Health ◽  
Street Level ◽  
Street View ◽  
Food Advertisements ◽  
Data Collection Effort ◽  
Deprived Areas

AbstractWhile outdoor advertisements are common features within towns and cities, they may reinforce social inequalities in health. Vulnerable populations in deprived areas may have greater exposure to fast food, gambling and alcohol advertisements, which may encourage their consumption. Understanding who is exposed and evaluating potential policy restrictions requires a substantial manual data collection effort. To address this problem we develop a deep learning workflow to automatically extract and classify unhealthy advertisements from street-level images. We introduce the Liverpool $${360}^{\circ }$$ 360 ∘ Street View (LIV360SV) dataset for evaluating our workflow. The dataset contains 25,349, 360 degree, street-level images collected via cycling with a GoPro Fusion camera, recorded Jan 14th–18th 2020. 10,106 advertisements were identified and classified as food (1335), alcohol (217), gambling (149) and other (8405). We find evidence of social inequalities with a larger proportion of food advertisements located within deprived areas and those frequented by students. Our project presents a novel implementation for the incidental classification of street view images for identifying unhealthy advertisements, providing a means through which to identify areas that can benefit from tougher advertisement restriction policies for tackling social inequalities.

scholarly journals Socioeconomic Inequalities and Ethnicity Are Associated with a Positive COVID-19 Test among Cancer Patients in the UK Biobank Cohort

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1514
Author(s):  
Shing Fung Lee ◽  
Maja Nikšić ◽  
Bernard Rachet ◽  
Maria-Jose Sanchez ◽  
Miguel Angel Luque-Fernandez
Keyword(s):  
Cancer Patients ◽  
Socioeconomic Inequalities ◽  
Uk Biobank ◽  
Incident Cancer ◽  
Increased Risk ◽  
Exposure Variable ◽  
Independent Risk Factors ◽  
The Uk ◽  
Deprived Areas

We explored the role of socioeconomic inequalities in COVID-19 incidence among cancer patients during the first wave of the pandemic. We conducted a case-control study within the UK Biobank cohort linked to the COVID-19 tests results available from 16 March 2020 until 23 August 2020. The main exposure variable was socioeconomic status, assessed using the Townsend Deprivation Index. Among 18,917 participants with an incident malignancy in the UK Biobank cohort, 89 tested positive for COVID-19. The overall COVID-19 incidence was 4.7 cases per 1000 incident cancer patients (95%CI 3.8–5.8). Compared with the least deprived cancer patients, those living in the most deprived areas had an almost three times higher risk of testing positive (RR 2.6, 95%CI 1.1–5.8). Other independent risk factors were ethnic minority background, obesity, unemployment, smoking, and being diagnosed with a haematological cancer for less than five years. A consistent pattern of socioeconomic inequalities in COVID-19 among incident cancer patients in the UK highlights the need to prioritise the cancer patients living in the most deprived areas in vaccination planning. This socio-demographic profiling of vulnerable cancer patients at increased risk of infection can inform prevention strategies and policy improvements for the coming pandemic waves.

scholarly journals P1-406 Characteristics of individuals "left behind" in deprived areas in Scotland

2011 ◽  
Vol 65 (Suppl 1) ◽  
pp. A179-A179
Author(s):  
D. Brown ◽  
D. O'Reilly ◽  
V. Gayle ◽  
S. Macintyre ◽  
M. Benzeval ◽  
...  
Keyword(s):  
Left Behind ◽  
Deprived Areas

scholarly journals The impact of area-based initiatives on physical activity trends in deprived areas; a quasi-experimental evaluation of the Dutch District Approach

2014 ◽  
Vol 11 (1) ◽  
pp. 36 ◽  
Author(s):  
Daniëlle Kramer ◽  
Mariël Droomers ◽  
Birthe Jongeneel-Grimen ◽  
Marleen Wingen ◽  
Karien Stronks ◽  
...  
Keyword(s):  
Physical Activity ◽  
Experimental Evaluation ◽  
Quasi Experimental ◽  
The Impact ◽  
Activity Trends ◽  
Deprived Areas

scholarly journals Deprived areas: deprived of training?

2010 ◽  
Vol 60 (580) ◽  
pp. 846-848 ◽  
Author(s):  
Mark Russell ◽  
Murray Lough
Keyword(s):  
Deprived Areas
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