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Record W3194565385 · doi:10.1289/isee.2021.p-451

Association between residential green space and menstrual cycle characteristics among North American women

2021· article· en· W3194565385 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueISEE Conference Abstracts · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNormalized Difference Vegetation IndexDemographyConfidence intervalInterquartile rangePoisson regressionProspective cohort studyCohort studyPopulationMenstrual cycleEnvironmental healthEcologyClimate changeSurgeryBiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM: Exposure to green space (natural vegetation) has been linked to improved reproductive outcomes, potentially through behavioral, psychological, and physiological mechanisms. However, there has been no study of the role of green space in gynecologic health. We examined the association between residential green space and menstrual cycle characteristics in a cohort of reproductive-aged women. METHODS: We performed a cross-sectional analysis within Pregnancy Study Online (PRESTO), a web-based prospective cohort study of women aged 21-45 years who reside in the United States or Canada. We included 7,733 women who enrolled during June 2013-April 2019. We geocoded their residential addresses and calculated annual maximum normalized difference vegetation index (NDVI) at 30 meter resolution within 250 meters around their residences to quantify green space exposure. Women reported on menstrual cycle regularity, cycle length, bleed length, heaviness of bleed, and intensity of menstrual pain. We used log-binomial regression models to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs), adjusting for sociodemographic, lifestyle, and neighborhood characteristics, including population density and census tract median household income. RESULTS:The median (interquartile range) NDVI within 250 meters was 0.64 (0.52, 0.74). Low residential green space was associated with a higher prevalence of long bleeds (≥6 days) and severe period pain (medication and bed rest required). The PRs comparing the lowest levels of green space (NDVI 0.2) with the highest levels of green space (NDVI ≥0.8) were 1.43 (95% CI: 0.99, 2.08) for long bleeds and 1.71 (95% CI: 1.01, 2.89) for severe period pain. However, there was little evidence of dose-response associations. Other menstrual cycle characteristics were not appreciably associated with NDVI. CONCLUSIONS:Women with the lowest residential green space were more likely to have long menstrual bleeds and severe menstrual pain, indicating a potential role for green space in menstrual health. KEYWORDS: reproductive outcomes, green space, built environment, epidemiology

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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