One Ring to Contain Them all: The Pivotal Role of the Built Environment in all Pillars of Lifestyle Medicine
Bibliographic record
Abstract
The built environment - defined as the human-made physical aspects of where people live, work, and play - has long influenced morbidity and mortality. While historical examples include environmental exposures such as climate extremes or access to clean water, modern urbanization presents distinct health challenges and opportunities. This article explores the built environment's role in shaping health through the lens of lifestyle medicine, encompassing six key pillars: nutrition, physical activity, stress management, sleep health, social connection, and avoidance of risky substances. Neighbourhood food environments affect dietary behaviours, with greater access to fast food linked to obesity and cardiovascular disease, while fresh food availability promotes healthier choices. Walkability and greenspace enhance physical activity, while urban design incorporating green- and blue-spaces supports stress management. Environmental noise and artificial light at night impact sleep quality, whereas community infrastructure fosters social connectedness. Lastly, the spatial distribution of alcohol and tobacco outlets influences substance use behaviours. Given the built environment's wide-ranging influence, designing neighbourhoods that naturally promote health could yield significant public health benefits. This perspective underscores the need for policy-driven urban planning that prioritizes health-supportive environments, making the healthy choice the default choice for populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".