Prenatal Exposure to Fine Particulate Matter and Birth Weight

Bell, Michelle L.; Belanger, Kathleen; Ebisu, Keita; Gent, Janneane F.; Lee, Hyung Joo; Koutrakis, Petros; Leaderer, Brian P.

doi:10.1097/ede.0b013e3181f2f405

Cited by 215 publications

(150 citation statements)

References 39 publications

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“…*P Ͻ 0.05 was considered statistically significant. studies linking higher PM exposure to decreases in birth weight (2,19,30,35). This is confirmed in a similar study where mice were exposed to diesel exhaust during a portion of development (15).…”

Section: -Exposed Mice (B) C: End-systolic Volume (Esv) D: Enddiassupporting

confidence: 56%

Early life exposure to air pollution induces adult cardiac dysfunction

Gorr

Velten²,

Nelin

et al. 2014

American Journal of Physiology-Heart and Circulatory Physiology

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Exposure to ambient air pollution contributes to the progression of cardiovascular disease, particularly in susceptible populations. The objective of the present study was to determine whether early life exposure to air pollution causes persistent cardiovascular consequences measured at adulthood. Pregnant FVB mice were exposed to filtered (FA) or concentrated ambient particulate matter (PM2.5) during gestation and nursing. Mice were exposed to PM2.5 at an average concentration of 51.69 μg/m3 from the Columbus, OH region for 6 h/day, 7 days/wk in utero until weaning at 3 wk of age. Birth weight was reduced in PM2.5 pups compared with FA (1.36 ± 0.12 g FA, n = 42 mice; 1.30 ± 0.15 g PM2.5, n = 67 P = 0.012). At adulthood, mice exposed to perinatal PM2.5 had reduced left ventricular fractional shortening compared with FA-exposed mice (43.6 ± 2.1% FA, 33.2 ± 1.6% PM2.5, P = 0.001) with greater left ventricular end systolic diameter. Pressure-volume loops showed reduced ejection fraction (79.1 ± 3.5% FA, 35.5 ± 9.5% PM2.5, P = 0.005), increased end-systolic volume (10.4 ± 2.5 μl FA, 39.5 ± 3.8 μl PM2.5, P = 0.001), and reduced dP/d t maximum (11,605 ± 200 μl/s FA, 9,569 ± 800 μl/s PM2.5, P = 0.05) and minimum (−9,203 ± 235 μl/s FA, −7,045 ± 189 μl/s PM2.5, P = 0.0005) in PM2.5-exposed mice. Isolated cardiomyocytes from the hearts of PM2.5-exposed mice had reduced peak shortening (%PS, 8.53 ± 2.82% FA, 6.82 ± 2.04% PM2.5, P = 0.003), slower calcium reuptake (τ, 0.22 ± 0.09 s FA, 0.26 ± 0.07 s PM2.5, P = 0.048), and reduced response to β-adrenergic stimulation compared with cardiomyocytes isolated from mice that were exposed to FA. Histological analyses revealed greater picro-sirius red-positive-stained areas in the PM2.5 vs. FA group, indicative of increased collagen deposition. We concluded that these data demonstrate the detrimental role of early life exposure to ambient particulate air pollution in programming of adult cardiovascular diseases and the potential for PM2.5 to induce persistent cardiac dysfunction at adulthood.

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Section: -Exposed Mice (B) C: End-systolic Volume (Esv) D: Enddiassupporting

confidence: 56%

Early life exposure to air pollution induces adult cardiac dysfunction

Gorr

Velten²,

Nelin

et al. 2014

American Journal of Physiology-Heart and Circulatory Physiology

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“…46,117,140,[181][182][183][184] On the other hand, while longitudinal studies follow children for a period of time, these types of studies may be limited by the use of retrospective data, parent-based reporting, limited measurements of other covariates, imperfect or missing measurements of confounders, gaps in data reporting, or selection bias. 165,185,186 Crosscomparison studies may prove difficult due to varying study designs and ages of the children. This situation is especially likely for measurements made during adolescence, when the onset of puberty can modify responses.…”

Section: Discussionmentioning

confidence: 99%

“…162 Prenatal air pollution exposures (PAHs, NO x , CO, PM) associated with birthweight have found either no associations or low birthweight, except for one report by Rundle et al, where prenatal exposures to PAHs were associated with obesity at age 7 years. 160,161,[163][164][165][166][167][168][169][170] Jerrett et al 162,171 examined the relationship between BMI levels in children and traffic density, air pollutants, and proximity of roadways to residential areas. In both studies, exposure to air pollutants resulted in increased BMI levels.…”

Section: Air Pollutionmentioning

confidence: 99%

Chemical and non-chemical stressors affecting childhood obesity: a systematic scoping review

Lichtveld

Thomas

Tulve

2017

J Expo Sci Environ Epidemiol

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Childhood obesity in the United States has doubled over the last three decades and currently affects 17% of children and adolescents. While much research has focused on individual behaviors impacting obesity, little research has emphasized the complex interactions of numerous chemical and non-chemical stressors found in a child's environment and how these interactions affect a child's health and well-being. The objectives of this systematic scoping review were to (1) identify potential chemical stressors in the context of non-chemical stressors that impact childhood obesity; and, (2) summarize our observations for chemical and non-chemical stressors in regards to child-specific environments within a community setting. A review was conducted to identify chemical and non-chemical stressors related to childhood obesity for the childhood life stages ranging from prenatal to adolescence. Stressors were identified and grouped into domains: individual behaviors, family/household behaviors, community stressors, and chemical exposures. Stressors were related to the child and the child's everyday environments and used to characterize child health and well-being. This review suggests that the interactions of chemical and non-chemical stressors are important for understanding a child's overall health and well-being. By considering these relationships, the exposure science research community can better design and implement strategies to reduce childhood obesity.

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“…Recently a few studies have investigated the associations between particle composition and health effects (Bell et al, 2010(Bell et al, , 2007Burnett et al, 2000;Cao et al, 2012;Franklin et al, 2008;Ito et al, 2011;Krall et al, 2013;Levy et al, 2012;Mar et al, 2000;Ostro et al, 2007Ostro et al, , 2010Son et al, 2012). However, there remains large uncertainty about which PM components are most responsible for the observed health effects, possibly due to the fact that central site monitoring measurements used in the PM composition studies have limited temporal, spatial, and chemical resolution, which could potentially lead to misclassification of exposure estimates and mask some detailed correlations.…”

mentioning

confidence: 99%

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

Zhang

Ying

et al. 2015

Atmos. Chem. Phys.

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Abstract. For the first time, a ∼ decadal (9 years from 2000 to 2008) air quality model simulation with 4 km horizontal resolution over populated regions and daily time resolution has been conducted for California to provide air quality data for health effect studies. Model predictions are compared to measurements to evaluate the accuracy of the simulation with an emphasis on spatial and temporal variations that could be used in epidemiology studies. Better model performance is found at longer averaging times, suggesting that model results with averaging times ≥ 1 month should be the first to be considered in epidemiological studies. The UCD/CIT model predicts spatial and temporal variations in the concentrations of O 3 , PM 2.5 , elemental carbon (EC), organic carbon (OC), nitrate, and ammonium that meet standard modeling performance criteria when compared to monthly-averaged measurements. Predicted sulfate concentrations do not meet target performance metrics due to missing sulfur sources in the emissions. Predicted seasonal and annual variations of PM 2.5 , EC, OC, nitrate, and ammonium have mean fractional biases that meet the model performance criteria in 95, 100, 71, 73, and 92 % of the simulated months, respectively. The base data set provides an improvement for predicted population exposure to PM concentrations in California compared to exposures estimated by central site monitors operated 1 day out of every 3 days at a few urban locations. Uncertainties in the model predictions arise from several issues. Incomplete understanding of secondary organic aerosol formation mechanisms leads to OC bias in the model results in summertime but does not affect OC predictions in winter when concentrations are typically highest. The CO and NO (species dominated by mobile emissions) results reveal temporal and spatial uncertainties associated with the mobile emissions generated by the EMFAC 2007 model. The WRF model tends to overpredict wind speed during stagnation events, leading to underpredictions of high PM concentrations, usually in winter months. The WRF model also generally underpredicts relative humidity, resulting in less particulate nitrate formation, especially during winter months. These limitations must be recognized when using data in health studies. All model results included in the current manuscript can be downloaded free of charge at http: //faculty.engineering.ucdavis.edu/kleeman/.

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Prenatal Exposure to Fine Particulate Matter and Birth Weight

Abstract: Background-Exposure to fine particles (PM 2.5 ) during pregnancy has been linked to lower birth weight; however, the chemical composition of PM 2.5 varies widely. The health effects of PM 2.5 constituents are unknown.

Cited by 215 publications

References 39 publications

Early life exposure to air pollution induces adult cardiac dysfunction

Early life exposure to air pollution induces adult cardiac dysfunction

Chemical and non-chemical stressors affecting childhood obesity: a systematic scoping review

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

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