Bibliographic record
Abstract
Urbanisation is one of the leading global trends of the 21st century and the UN predicts that seven in ten people will live in urban areas by 2050.1UN Department of Economic and Social AffairsThe 2014 revision. United Nations, New York2014Google Scholar With hasty global urbanisation, the importance of understanding relationships between environment, human health, and wellbeing is being increasingly recognised. Urban advance offers many opportunities, including access to better health care; however, this growth is also associated with many emerging environment and health hazards. Over the past decades, urbanisation and subsequent changes in our living standards, lifestyles, and dietary patterns have been suggested to be associated with different exposures and the risk of disease.2WHOBulletin of the World Health Organization, Urbanization and health.http://www.who.int/bulletin/volumes/88/4/10-010410/en/Date: 2010Google Scholar An increasing number of studies are investigating the effect of urban density and land-use mix on health gains, including reduced levels of obesity, and aim to identify types of neighbourhoods or characteristics of neighbourhoods that will promote health benefits.3Croucher KL Wallace A Duffy S The influence of land use mix, density and urban design on health: Centre for Housing Policy. University of York, York2012Google Scholar However, uncertainty regarding the effect of urbanisation on obesity remains due to discrepancies in conceptual and methodological approaches in urban definitions. In this issue of The Lancet Planetary Health, Chinmoy Sarkar and colleagues4Sarkar C Webster C Gallacher J Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants.Lancet Planet Health. 2017; 1: e277-e288Summary Full Text Full Text PDF Scopus (51) Google Scholar report their findings on the association between adiposity and residential density using objective measures of the built environment. In a large and diverse population in the UK, they provide evidence for a curvilinear dose–response relationship indicating inflexion points at 1800 and 3200 residential units per km2. Findings were consistent across measures of adiposity, with stronger associations being found for people who were female, younger, and accumulating higher levels of physical activity.4Sarkar C Webster C Gallacher J Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants.Lancet Planet Health. 2017; 1: e277-e288Summary Full Text Full Text PDF Scopus (51) Google Scholar This beneficial urban environment is particularly important because, irrespective of geographical location, residential density seems to be associated with decreased levels of obesity.5Rundle A Diez Roux AV Free LM Miller D Neckerman KM Weiss CC The urban built environment and obesity in New York City: a multilevel analysis.Am J Health Promot. 2007; 21: 326-334Crossref PubMed Scopus (248) Google Scholar This association suggests that high-density areas can provide and support increased levels of physical activity because they have nearby destinations that support walking.6Witten K Geographies of obesity: environmental understandings of the obesity epidemic. Ashgate Publishing, Farnham2010Google Scholar Taken together these findings inform policies and practices aiming to create healthier cities through optimisation of urban planning and built environment design and to reduce health expenses by decreasing urban detrimental exposures. Unfortunately, the urban neighbourhood effect might not be always beneficial for the obesity risk. First, the increased urbanisation associated with high residential density, street intersections, and mixed land-use, together with low physical activity, increases reliance on foods that are often highly processed and containing high levels of salt, sugar, and fat.7Kim J Shon C Yi S The relationship between obesity and urban environment in Seoul.Int J Environ Res Public Health. 2017; 14: 898Crossref Scopus (6) Google Scholar, 8Pouliou T Elliott SJ Individual and socio-environmental determinants of overweight and obesity in urban Canada.Health Place. 2010; 16: 389-398Crossref PubMed Scopus (88) Google Scholar, 9Sobal J Commentary: globalization and the epidemiology of obesity.Int J Epidemiol. 2001; 30: 1136-1137Crossref PubMed Scopus (42) Google Scholar Second, the complex interaction between human beings and urbanisation is dependent, not only on individual determinants and behaviours such as gender, age, social or economic resources, and lifestyle, but also on urbanisation landscapes, including air pollution, handiness of green areas and recreational facilities, neighbourhood safety, and opportunities for mobility and physical activity.10Papas MA Alberg AJ Ewing R Helzlsouer KJ Gary TL Klassen AC The built environment and obesity.Epidemiol Rev. 2007; 29: 129-143Crossref PubMed Scopus (783) Google Scholar, 11Brody J The global epidemic of childhood obesity: poverty, urbanization, and the nutrition transition. Nutrition Bytes.http://www.escholarship.org/uc/item/1xb9x54zDate: 2002Google Scholar Therefore, to be effective in promoting health and healthy behaviour, public health interventions have to address not only individual characteristics but also the physical and social environment.1UN Department of Economic and Social AffairsThe 2014 revision. United Nations, New York2014Google Scholar The complexity of the linkages between urbanisation, environmental change, and human health and wellbeing requires a systems approach towards these factors. The study by Sarkar and colleagues4Sarkar C Webster C Gallacher J Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants.Lancet Planet Health. 2017; 1: e277-e288Summary Full Text Full Text PDF Scopus (51) Google Scholar provides us with an improved understating of how the urban environment and land use can affect a complex chronic disease such as obesity. In fact, the rewiring of public health and urban planning is an opportunity to understand the effect of urbanisation and many other urban exposures on health, providing information to build up successful community-based disease prevention efforts. Ultimately, it is not only who you are, but also, and mostly, where and how you live that affects your health. We declare no competing interests. Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participantsHousing-level policy related to the optimisation of healthy density in cities might be a potential upstream-level public health intervention towards the minimisation and offsetting of obesity; however, further research based on accumulated prospective data is necessary for evidencing specific pathways. The findings might mean that governments, such as the UK Government, who are attempting to prevent suburban densification by, for example, prohibiting the subdivision of single lot housing and the conversion of domestic gardens to housing lots, will potentially have the effect of inhibiting the conversion of suburbs into more healthy places to live. Full-Text PDF Open Access
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 | 0.003 | 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 | 0.008 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".