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Climate change is a major stressor causing poor pregnancy outcomes and child development

2020· preprint· en· W3092483446 on OpenAlexafffund
David M. Olson, Gerlinde A. S. Metz

Bibliographic record

VenueF1000Research · 2020
Typepreprint
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of LethbridgeUniversity of Alberta
FundersCanadian Institutes of Health ResearchWorldwide Universities Network
KeywordsOpen peer reviewStressorPlant biologyClimate changeMedicinePregnancyPhysiologyBiologyPsychiatryEcology

Abstract

fetched live from OpenAlex

The climate crisis is the existential threat of our times and for generations to come. This is no longer a threat but a reality affecting us, our children, and the generations that follow. Pregnant mothers, their fetuses, and their children are among those at greatest risk in every population and every jurisdiction. A timely consideration is the health of racialized groups who are particularly vulnerable owing to the confluence of several risk factors that are compounded by climate change. Included among these are Indigenous communities that are the most directly threatened by climate change. This review discusses the main health challenges faced by mothers, fathers, and their children during the climate crisis, focusing on mental health as a causal factor. Exploration of this topic includes the role of prenatal maternal and paternal stresses, allostatic load, and the effect of degradation of the environment and ecosystems on individuals. These will be examined in relation to adverse pregnancy outcomes and altered developmental trajectories of children. The climate crisis is a health threat multiplier that amplifies the health inequities of the most at-risk populations and individuals. It accelerates the increase in allostatic load of those at risk. The path of tragedy begins with an accumulating allostatic load that overwhelms both individual and socio-ecological resilience. This can lead to worse mental health including depression and anxiety and, in the case of pregnant women and their children, more adverse pregnancy outcomes and impaired developmental trajectories for their newborn children. We argue that there is an urgent need to develop new (or re-discover or re-purpose existing) tools that will predict communities and individuals who are experiencing the highest levels of climate-related hazards and intervene to reduce stress and increase resilience in pre-conceptual women and men, pregnant and post-partum women, and their young children.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.210
GPT teacher head0.399
Teacher spread0.189 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations63
Published2020
Admission routes2
Has abstractyes

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