Prenatal exposure to criteria air pollutants and associations with congenital anomalies: A Lebanese national study

Noaimi, Ghaliya Al; Yunis, Khalid; Asmar, Khalil El; Salem, Fatima K. Abu; Afif, Charbel; Ghandour, Lilian; Hamandi, Ahmad; Dhaini, Hassan R.

doi:10.1016/j.envpol.2021.117022

Cited by 15 publications

(13 citation statements)

References 62 publications

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“…These harmful components are carcinogenic which bring chronic impacts to the health, and worse, it could result in mortality. Last but not least, from the review, exposure to air pollution could lead to adverse pregnancy outcomes, in both infant and pregnant women proven by Achebak, Petetin et al ( 2 ), Al Noaimi et al ( 3 ), Bruni Zani et al ( 5 ), Wang et al ( 17 ).…”

Section: Resultsmentioning

confidence: 95%

“…Based on the review performed, the most significant and dominant pollutant marker was the particulate matter particles (PM 2.5 ). The majority of the studies conducted had analyzed the impact of particulate matter (PM 2.5 , PM 10 , PM <2.5 ) on human health ( 3 , 5 – 18 , 28 ). Pollution markers such as ozone (O 3 ), carbon monoxide (CO), nitrogen dioxide (NO 2 ) and sulfur dioxide (SO 2 ) are among other important contaminants that were studied by ( 2 – 4 , 6 , 7 , 10 – 15 ).…”

Section: Resultsmentioning

confidence: 99%

“…By using these techniques, the authors, able to predict the hospitalization of cardiorespiratory and chronic respiratory disease due to long term exposure to pollutants (PMs, ozone, CO, NO, NO x , NO 2 , and SO 2 ). Meanwhile, studies by ( 3 – 6 , 12 , 14 , 16 , 18 , 28 ) analyzed the impact of air pollution on health and their association using machine learning techniques such as MLP, random forest, neural network, regression, etc. The contribution of these studies enables to predict and forecast the health hazards contributed by air pollution.…”

Section: Resultsmentioning

confidence: 99%

“…A few other researchers study the association between health hazards and air pollution. To assess the association, researchers developed models using mathematical and statistical knowledge ( 2 , 3 , 7 , 8 , 14 , 17 ). These authors performed the association assessment using modeling of Poison's regression, quasi-Poison distribution, generalized additive model (GAM), etc.…”

Section: Resultsmentioning

confidence: 99%

“…According to Al Noaimi et al ( 3 ), exposure to PM 2.5 during the pregnancy, especially first trimester causes higher risk of birth defect in infants and genitourinary defect in pregnant women, while according to Bruni Zani, Lonati ( 5 ) long term impact of PM 2.5 exposure increases the premature deaths in babies. Aside from PM 2.5 , NO 2 , and O 3 also contributed to premature mortality, proven by Achebak, Petetin et al ( 2 ).…”

Section: Resultsmentioning

confidence: 99%

See 4 more Smart Citations

Towards Integrated Air Pollution Monitoring and Health Impact Assessment Using Federated Learning: A Systematic Review

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et al. 2022

Front. Public Health

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Environmental issues such as environmental pollutions and climate change are the impacts of globalization and become debatable issues among academics and industry key players. One of the environmental issues which is air pollution has been catching attention among industrialists, researchers, and communities around the world. However, it has always neglected until the impacts on human health become worse, and at times, irreversible. Human exposure to air pollutant such as particulate matters, sulfur dioxide, ozone and carbon monoxide contributed to adverse health hazards which result in respiratory diseases, cardiorespiratory diseases, cancers, and worst, can lead to death. This has led to a spike increase of hospitalization and emergency department visits especially at areas with worse pollution cases that seriously impacting human life and health. To address this alarming issue, a predictive model of air pollution is crucial in assessing the impacts of health due to air pollution. It is also critical in predicting the air quality index when assessing the risk contributed by air pollutant exposure. Hence, this systemic review explores the existing studies on anticipating air quality impact to human health using the advancement of Artificial Intelligence (AI). From the extensive review, we highlighted research gaps in this field that are worth to inquire. Our study proposes to develop an AI-based integrated environmental and health impact assessment system using federated learning. This is specifically aims to identify the association of health impact and pollution based on socio-economic activities and predict the Air Quality Index (AQI) for impact assessment. The output of the system will be utilized for hospitals and healthcare services management and planning. The proposed solution is expected to accommodate the needs of the critical and prioritization of sensitive group of publics during pollution seasons. Our finding will bring positive impacts to the society in terms of improved healthcare services quality, environmental and health sustainability. The findings are beneficial to local authorities either in healthcare or environmental monitoring institutions especially in the developing countries.

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Section: Resultsmentioning

confidence: 95%