Particulate Air Pollution and Fetal Health

Glinianaia, Svetlana V.; Rankin, Judith; Bell, R; Pless‐Mulloli, Tanja; Howel, Denise

doi:10.1097/01.ede.0000101023.41844.ac

Cited by 322 publications

(130 citation statements)

References 38 publications

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“…We identified relevant publications using database searches with a comprehensive list of search terms and other established search methods (for details, see Glinianaia et al 2004). …”

Section: Methodsmentioning

confidence: 99%

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Does Particulate Air Pollution Contribute to Infant Death? A Systematic Review

Glinianaia¹,

Rankin²,

Bell³

et al. 2004

Environ Health Perspect

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There is now substantial evidence that both short- and long-term increases in ambient air pollution are associated with increased mortality and morbidity in adults and children. Children’s health is particularly vulnerable to environmental pollution, and infant mortality is still a major contributor to childhood mortality. In this systematic review we summarize and evaluate the current level of epidemiologic evidence of an association between particulate air pollution and infant mortality. We identified relevant publications using database searches with a comprehensive list of search terms and other established search methods. We included articles in the review according to specified inclusion criteria. Fifteen studies met our inclusion criteria. Evidence of an association between particulate air pollution and infant mortality in general was inconsistent, being reported from locations with largely comparable pollution levels. There was some evidence that the strength of association with particulate matter differed by subgroups of infant mortality. It was more consistent for post-neonatal mortality due to respiratory causes and sudden infant death syndrome. Differential findings for various mortality subgroups within studies suggest a stronger association of particulate air pollution with some causes of infant death. Research is needed to confirm and clarify these links, using the most appropriate methodologies for exposure assessment and control of confounders.

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“…We identified relevant publications using database searches with a comprehensive list of search terms and other established search methods (for details, see Glinianaia et al 2004). …”

Section: Methodsmentioning

confidence: 99%

“…We undertook a systematic review to summarize the epidemiologic evidence for an association between levels of particulate air pollution and infant outcomes. This work was part of a broader systematic review of the association between ambient air pollution and fetal (Glinianaia et al 2004) and infant health outcomes.…”

mentioning

confidence: 99%

Does Particulate Air Pollution Contribute to Infant Death? A Systematic Review

Glinianaia¹,

Rankin²,

Bell³

et al. 2004

Environ Health Perspect

Self Cite

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“…PM10 also has a direct effect on health via inhalation [5]. Glinianaia et al [17] and Šrám et al [18] have reported the effects of particulate matter on infant birth weight. Samet et al [19] found that an elevated PM10 concentration can increase mortality rates the following day.…”

Section: Introductionmentioning

confidence: 99%

Statistical Modeling Approaches for PM10 Prediction in Urban Areas; A Review of 21st-Century Studies

2016

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PM 10 prediction has attracted special legislative and scientific attention due to its harmful effects on human health. Statistical techniques have the potential for high-accuracy PM 10 prediction and accordingly, previous studies on statistical methods for temporal, spatial and spatio-temporal prediction of PM 10 are reviewed and discussed in this paper. A review of previous studies demonstrates that Support Vector Machines, Artificial Neural Networks and hybrid techniques show promise for suitable temporal PM 10 prediction. A review of the spatial predictions of PM 10 shows that the LUR (Land Use Regression) approach has been successfully utilized for spatial prediction of PM 10 in urban areas. Of the six introduced approaches for spatio-temporal prediction of PM 10 , only one approach is suitable for high-resolved prediction (Spatial resolution < 100 m; Temporal resolution ď 24 h). In this approach, based upon the LUR modeling method, short-term dynamic input variables are employed as explanatory variables alongside typical non-dynamic input variables in a non-linear modeling procedure.

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“…Our article followed on from many other studies reporting associations between atmospheric pollution levels and pregnancy outcomes, the earliest of which was published more than 30 years ago (Williams et al 1977). These studies have been the subject of several reviews (Glinianaia et al 2004;Lacasana et al 2005;Maisonet et al 2004;Ritz and Wilhelm 2008;Slama et al 2008;Sram et al 2005) and have led the WHO to conclude that, "There is evidence that implicates ambient air pollution in adverse eVects on pregnancy, birth outcomes and male fertility." (Krzyzanowski et al 2005).…”

mentioning

confidence: 95%