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Record W3107650096 · doi:10.1016/j.envint.2020.105775

Secondhand smoke exposure in outdoor children’s playgrounds in 11 European countries

2020· article· en· W3107650096 on OpenAlexfundno aff
Elisabet Henderson, Xavier Continente, Esteve Fernández, Olena Tigova, Núria Cortés-Francisco, Silvano Gallus, Alessandra Lugo, Sean Semple, Rachel O’Donnell, Luke Clancy, Sheila Keogan, Ario Ruprecht, Alessandro Borgini, Anna Tzortzi, Vergina Konstantina Vyzikidou, Giuseppe Gorini, Ángel López Nicolás, Joan B. Soriano, Gergana Geshanova, Joseph Osman, Ute Mons, Krzysztof Przewoźniak, José Precioso, Ramona Brad, María José López

Bibliographic record

VenueEnvironment International · 2020
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersEuropean Regional Development FundHorizon 2020Universidad Politécnica de CartagenaUniversity of StirlingGeneralitat de CatalunyaEuropean CommissionTerry Fox Research InstitutePublic Health AgencyIstituto di Ricerche Farmacologiche Mario Negri - IRCCS
KeywordsEnvironmental healthNicotineMedicineTobacco smokeInterquartile rangeSecondhand smokeTobacco controlSmokeSocioeconomic statusToxicologyGeographyPopulationPublic health

Abstract

fetched live from OpenAlex

Tobacco presence in outdoor children’s playgrounds is concerning not only because it leads to secondhand smoke (SHS) exposure, but also cigarette butt pollution and tobacco normalization. This study aimed to assess SHS exposure in children’s playgrounds, according to area-level socioeconomic status (SES), smoke-free regulations, national smoking prevalence, and SHS exposure prevalence in playgrounds (2017–2018). We monitored vapor-phase nicotine concentration and tobacco-related variables in 20 different playgrounds in 11 European countries (n = 220 measurements) from March 2017 to April 2018. Playgrounds were selected according to area-level SES. Data on the number of people smoking, and cigarette butts inside the playground and on playground surroundings (<1 m away) were recorded. Playground smoking bans, the Tobacco Control Scale (TCS) score, national smoking prevalence and SHS exposure prevalence in playgrounds were used to group countries. To determine nicotine presence, we dichotomized concentrations using the limit of quantification as a cut-off point (0.06 μg/m3). Nicotine median concentrations were compared using non-parametric tests, and nicotine presence and tobacco-related observational variables using the Chi-squared test. Airborne nicotine presence was found in 40.6% of the playgrounds. Median nicotine concentration was <0.06 μg/m3 (Interquartile range: <0.06–0.125) and higher median concentrations were found in more deprived neighborhoods, non-regulated playgrounds, in countries with lower overall TCS scores, higher national smoking prevalence and higher SHS exposure prevalence in playgrounds. Overall, people were smoking in 19.6% of the playgrounds. More than half of playgrounds had cigarette butts visible inside (56.6%) and in the immediate vicinity (74.4%). Presence of butts inside playgrounds was higher in sites from a low area-level SES, in countries with low TCS scores, and greater smoking prevalence and SHS exposure prevalence (p<0.05). There is evidence of SHS exposure in children’s playgrounds across Europe. These findings confirm the need for smoking bans in playgrounds and better enforcement in those countries with smoking bans in playgrounds.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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

Citations31
Published2020
Admission routes1
Has abstractyes

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