Bibliographic record
Abstract
Recent trends such as globalisation and urbanisation, combined with an ageing population and population growth, result in new challenges for public health. To tackle these emerging public health issues, novel approaches are required. The paradigm shift in public health supports this needed change. Public health is moving from a medical model, focused on the individual, to a social model, where public health is the result of various socio-economic, cultural and environmental factors. As stated in the Ottawa Charter1 and the "Health in All Policies" strategies2 of the World Health Organization (WHO), environment and living spaces are considered as global, social and political entities that determine the health status of populations. \n \nThis e-collection examines the relationship between built environment and health by presenting evidence from the papers that are recently published in the European Journal of Public Health. This evidence can support decision-makers in innovative policies, strategies and tangible actions in order to face contemporary public health challenges. \n \nSocial inequalities and social cohesion. In recent years, urban regeneration has widened its approach not only to give cities a new and more competitive look but also to boost cultural, economic and societal aspects. Those operations might result in gentrification processes which are demonstrated to have negative impacts on the population with a lower socioeconomic status (SES)3. Negative impacts include social relationship and daily routine disruption, psychosocial stress, health accessibility, stigmatization and discrimination resulting in anxiety and depression. Other studies highlight how adults who live in lower SES areas are more prone to develop psychological distress (Erdem et al., 2015). Instead, an inclusive approach to urban regeneration can improve the living conditions of the inhabitants with new services, resources, safety and social relationships (Mehdipanah et al., 2018). \n \nTo maximise health gains for the whole population, draft urban policies should be assessed. Pennington and colleagues (2017) present tools to measure the impact of urban policies on the health of residents in urban areas and potential variations within the urban population. \n \nPhysical activity and green areas. According to the WHO, over 3.2 million deaths are caused by insufficient physical activity. Physical inactivity is a risk factor for several non-communicable diseases, and as Dallat et al. (2014) underline, an increase of 10% of physical activity could lead to reduced cases and deaths from ischaemic heart disease, type 2 diabetes, stroke, colon and breast cancer. Urban areas with public space, walking circuits, and pedestrian paths can contribute to improved well-being, especially in elderly people (Bailly et al., 2018). A study on children (from 3 to 5 years old) investigating the relationship between obesity risk and the presence of green space, demonstrates that the quality and quantity of green areas has an impact on public health (Schalkwijk et al., 2018). \n \nNevertheless, the availability of green areas is not always correlated with high levels of physical activity. The perceived quality of green spaces is detrimental, as a study in 13 cities in the United Kingdom shows (Ali et al., 2017). Similarly, Pope et al. (2018) showed that the risk of psychological distress in people with access to lower quality green areas is up to 54% higher than those close to high quality spaces. \n \nAssessment of urban areas and neighbourhoods. The quality of urban areas and neighbourhoods is very important for the public's health. A collection of 13 tools to measure the perceived quality of urban area residents are presented by Hofland and colleagues (2018). These tools survey residents about amenities, landscape, public space, sidewalks, and more. Consulting residents about the quality of their living areas can give insight in important living quality aspects that cannot be retrieved from registries. Innovative methodologies (e.g. mobile applications) could provide tools to receive feedback from residents about the quality of living areas and this information could support policy and decision makers in strategic choices. Furthermore, the importance of using locally based aggregate measures in urban health policy making, is highlighted by Gemmell et al., 2017. \n \nA comparison of the health of people living in urban areas versus those not living in urban areas shows interesting differences between and within Eastern and Western European countries (Koster et al., 2017). In general, people living in Western European cities have a better health status than those living in Eastern European cities. While the urban population in Western European countries are less healthy than the country's average and people living in Eastern European cities are more healthy than the general population of that country. \n \nAs the papers in this e-collection demonstrate, there is an urgent need for joint actions in order to involve communities and policy makers as main stakeholders of the urban planning process. Starting from the concepts of evidence-based medicine and evidence-based design, future studies should develop a multidisciplinary approach for evidence-based urban health planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".