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Record W4288067827 · doi:10.1093/humupd/dmac029

Indoor and outdoor air pollution and couple fecundability: a systematic review

2022· review· en· W4288067827 on OpenAlexaboutno aff
Eva Siegel, Akhgar Ghassabian, Alison E. Hipwell, Pam Factor‐Litvak, Yeyi Zhu, Hannah G Steinthal, Carolina Focella, Lindsey Battaglia, Christina A. Porucznik, Scott C. Collingwood, Michele Klein‐Fedyshin, Linda G. Kahn

Bibliographic record

VenueHuman Reproduction Update · 2022
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsEnvironmental healthAir pollutionAir quality indexPollutantEnvironmental scienceIndoor air qualityPollutionContext (archaeology)MedicineEnvironmental engineeringMeteorologyGeographyBiologyEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Air pollution is both a sensory blight and a threat to human health. Inhaled environmental pollutants can be naturally occurring or human-made, and include traffic-related air pollution (TRAP), ozone, particulate matter (PM) and volatile organic compounds, among other substances, including those from secondhand smoking. Studies of air pollution on reproductive and endocrine systems have reported associations of TRAP, secondhand smoke (SHS), organic solvents and biomass fueled-cooking with adverse birth outcomes. While some evidence suggests that air pollution contributes to infertility, the extant literature is mixed, and varying effects of pollutants have been reported. OBJECTIVE AND RATIONALE: Although some reviews have studied the association between common outdoor air pollutants and time to pregnancy (TTP), there are no comprehensive reviews that also include exposure to indoor inhaled pollutants, such as airborne occupational toxicants and SHS. The current systematic review summarizes the strength of evidence for associations of outdoor air pollution, SHS and indoor inhaled air pollution with couple fecundability and identifies gaps and limitations in the literature to inform policy decisions and future research. SEARCH METHODS: We performed an electronic search of six databases for original research articles in English published since 1990 on TTP or fecundability and a number of chemicals in the context of air pollution, inhalation and aerosolization. Standardized forms for screening, data extraction and study quality were developed using DistillerSR software and completed in duplicate. We used the Newcastle-Ottawa Scale to assess risk of bias and devised additional quality metrics based on specific methodological features of both air pollution and fecundability studies. OUTCOMES: The search returned 5200 articles, 4994 of which were excluded at the level of title and abstract screening. After full-text screening, 35 papers remained for data extraction and synthesis. An additional 3 papers were identified independently that fit criteria, and 5 papers involving multiple routes of exposure were removed, yielding 33 articles from 28 studies for analysis. There were 8 papers that examined outdoor air quality, while 6 papers examined SHS exposure and 19 papers examined indoor air quality. The results indicated an association between outdoor air pollution and reduced fecundability, including TRAP and specifically nitrogen oxides and PM with a diameter of ≤2.5 µm, as well as exposure to SHS and formaldehyde. However, exposure windows differed greatly between studies as did the method of exposure assessment. There was little evidence that exposure to volatile solvents is associated with reduced fecundability. WIDER IMPLICATIONS: The evidence suggests that exposure to outdoor air pollutants, SHS and some occupational inhaled pollutants may reduce fecundability. Future studies of SHS should use indoor air monitors and biomarkers to improve exposure assessment. Air monitors that capture real-time exposure can provide valuable insight about the role of indoor air pollution and are helpful in assessing the short-term acute effects of pollutants on TTP.

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)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0110.013
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.055
GPT teacher head0.330
Teacher spread0.275 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations45
Published2022
Admission routes1
Has abstractyes

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