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Natural Environments, Health, and Well-Being

2016· reference-entry· en· W2547459699 on OpenAlexaff
Matilda van den Bosch

Bibliographic record

VenueOxford Research Encyclopedia of Environmental Science · 2016
Typereference-entry
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsUrban heat islandUrbanizationEnvironmental planningGeographyNatural resource economicsEnvironmental healthEnvironmental resource managementBusinessEnvironmental scienceEcologyBiologyEconomicsMedicine

Abstract

fetched live from OpenAlex

Abstract Human beings are part of natural ecosystems and depend on them for their survival. In a rapidly changing environment and with increasing urbanization, this dependence is challenged. Natural environments affect human health and well-being both directly and indirectly. Urban green and blue areas provide opportunities for stress recovery and physical activity. They offer spaces for social interactions in the neighborhood and places for children’s play. Chronic stress, physical inactivity, and lack of social cohesion are three major risk factors for noncommunicable diseases, and therefore abundant urban greenery is an important asset for health promotion. Through numerous ecosystem services natural environments play a fundamental role in protecting health. Various populations depend on nature for basic material, such as fresh water, wood, fuel, and nutritious food. Biodiverse natural areas are also necessary for regulating the environment and for mitigating and adapting to climate change. For example, tree canopy cover can reduce the urban heat island effect substantially, preventing excess morbidity during heat waves. This natural heat-reducing effect also lessens the need for air conditioning systems and as a consequence decreases energy spending. Urban trees also support storm-water management, preventing flooding and related health issues. Air pollution is a major threat to population health. Urban trees sequester pollutants and, even though the effect may be relatively small, given the severity of the problem it may still have some public-health implications. The evidence around the effects of natural environments on health and well-being is steadily increasing. Several pathways and mechanisms are suggested, such as health services through functional ecosystems, early life exposure to biodiverse microbiota, which is important for the immune-system development, and sensory exposure, which has direct neurobiological impact supporting cognitive development and stress resilience. Support for several pathways is at hand that shows lower mortality rates and prevalence of cardiovascular and respiratory diseases, healthier pregnancy outcomes, reduced health inequalities, and improved mental health in urban areas with greater amounts of green and blue space. Altogether, the interactions between healthy natural environments and healthy people are multiple and complex, and require interdisciplinary attention and action for full understanding and resilient development of both nature and human beings.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.038
GPT teacher head0.341
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations14
Published2016
Admission routes1
Has abstractyes

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