Associations of maternal personal exposure to air pollution on fetal weight and fetoplacental Doppler: A prospective cohort study

Carvalho, Mariana Azevedo; Bernardes, Lisandra Stein; Hettfleisch, Karen; Pastro, Luciana Duzolina Manfré; Vieira, Sandra Elisabete; Saldiva, Sílvia Regina Dias Médici; Saldiva, Paulo Hilário Nascimento; Francisco, Rossana Pulcineli Vieira

doi:10.1016/j.reprotox.2016.04.013

Cited by 41 publications

(26 citation statements)

References 71 publications

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“…Though insufficient, current evidence on time windows of susceptibility and the type of structural changes in human beings and mice generally suggests that myelinisation is probably one of the main brain development processes that is most susceptible to damage from particulate pollution. Other processes, such as changes in basal ganglia, may also be involved, though to a lesser extent …”

Section: Are Children More Vulnerable?mentioning

confidence: 99%

“…In this context, it is important to highlight that foetus has higher exposure than mothers in relation to their body size. Moreover, foetal life exposure results in maternal effects such as plasma viscosity, or systemic low‐grade inflammation, hormonal disruption or epigenetic changes in mother that could impair placenta function which in turn could lead to cardiovascular or neurological disruption …”

Section: What Are the Potential Mechanisms Underlying The Effects Of mentioning

confidence: 99%

“…Other processes, such as changes in basal ganglia, may also be involved, though to a lesser extent. 40…”

Section: Vulnerable?mentioning

confidence: 99%

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Pre‐natal brain development as a target for urban air pollution

Sunyer

Dadvand

2019

Basic Clin Pharma Tox

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Air pollution is the main urban‐related environmental hazard and one of the major contributors to the global burden of disease based on its cardiovascular‐respiratory impacts. In children, exposure to urban air pollution is associated, among others, with decelerated neurodevelopment early in life and increased risk of neurodevelopmental problems such as attention‐deficit hyperactivity disorder, autism spectrum disorders, academic failure and the start of Alzheimer's pathogenesis. However, the evidence of the effects of air pollution on brain development is still inadequate, mainly due to the limitations in (a) characterizing brain development (most studies were based on subjective tools such as questionnaires or neuropsychological tests) and (b) air pollution exposure (most studies only used residential levels based on geographical modelling and also overlooking the variation in the mixture of air pollutants as well as the composition and hence toxicity of particulate pollutants in different settings), (c) the lack of studies during the most vulnerable stages of brain development (foetal and early life (first two years post‐natally)) and (d) the lack of structural and functional imaging data underlying these effects. In mice, in utero exposure to fine particles was linked to structural brain changes and there is a need to establish the generalizability of these findings in human beings. Though scarce, current evidence in children supports the importance of the pre‐natal period as a susceptible window of exposure. Two studies in schoolchildren found that pre‐natal air pollution exposure might damage brain structure while exposure during childhood was not linked to any structural alteration. Another study showed that children with higher traffic‐related air pollution at school had lower functional integration in key brain networks, but no changes in brain structure, possibly partly because of the time window of air pollution exposure (in utero versus childhood exposure). A key development is to discover the windows of greatest sensitivity of structural brain changes to air pollution exposure by incorporating the recent advances in non‐invasive imaging to characterize natal and post‐natal brain development and exploring whether and to what extend placental dysfunction could mediate such an association. Studying pre‐natal life is important because effects at this time are of a potentially irreversible nature and because the largest preventive opportunities occur during these periods.

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Section: Are Children More Vulnerable?mentioning

confidence: 99%

Section: What Are the Potential Mechanisms Underlying The Effects Of mentioning

confidence: 99%

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Pre‐natal brain development as a target for urban air pollution

Sunyer

Dadvand

2019

Basic Clin Pharma Tox

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“…The models for fPCG and mPCG signals are inspired by real data acquired from interferometric sensors. The models predict that heartbeat activity causes (triggers) subsequent mechanical effects, which are distributed throughout the human body, and then reflected and attenuated after a certain period of time [108,109,110]. Our results confirm those obtained by Nagel et al [111], who modeled maternal heart sounds (mHS) as periodic signals known as maternal pulses that originate due to blood flow sound within maternal arteries with higher amplitudes relative to fetal heart sounds (fHS).…”

Section: Resultsmentioning

confidence: 99%

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

Martínek

Nedoma

Fajkus

et al. 2017

Sensors

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This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV.

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“…As such, most personal measurement studies have included relatively small sample sizes and/or short time periods [13–16]. For example, in a birth cohort in Sao Paulo, Brazil, NO 2 and O 3 were measured for 366 pregnant women in each trimester for 7–18 days using passive personal samplers [17] and in Barcelona, 122 adults were monitored over a three week period for black carbon using the micro-aethalometer AE51 [15]. These studies, while large for today’s standards, are a long way from our target of personal measurements for large study populations (i.e.…”

Section: Air Pollution Sensorsmentioning

confidence: 99%

Towards Personal Exposures: How Technology Is Changing Air Pollution and Health Research

Larkin

Hystad

2017

Curr Envir Health Rpt

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Purpose of Review We present a review of emerging technologies and how these can transform personal air pollution exposure assessment and subsequent health research. Recent Findings Estimating personal air pollution exposures is currently split broadly into methods for modelling exposures for large populations versus measuring exposures for small populations. Air pollution sensors, smartphones and air pollution models capitalizing on big/new data sources offer tremendous opportunity for unifying these approaches and improving long-term personal exposure prediction at scales needed for population-based research. A multi-disciplinary approach is needed to combine these technologies to not only estimate personal exposures for epidemiological research but also to determine drivers of these exposures and new prevention opportunities. While available technologies can revolutionize air pollution exposure research, ethical, privacy, logistical and data sciences challenges must be met before widespread implementations occur. Summary Available technologies and related advances in data science can improve long-term personal air pollution exposure estimates at scales needed for population-based research. This will advance our ability to evaluate the impacts of air pollution on human health and develop effective prevention strategies.

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Associations of maternal personal exposure to air pollution on fetal weight and fetoplacental Doppler: A prospective cohort study

Cited by 41 publications

References 71 publications

Pre‐natal brain development as a target for urban air pollution

Pre‐natal brain development as a target for urban air pollution

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

Towards Personal Exposures: How Technology Is Changing Air Pollution and Health Research

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