Association of Ambient Air Pollution with Perceived Stress in Pregnant Women: A Prospective Cohort Study

Abstract Background: Air pollution is associated with perceived stress in the general population, but its influence on maternal perceived stress during pregnancy has not been investigated.We aimed to investigate the relationship between air pollution and non-specific perceived stress among pregnant women.Methods: Our analysis included2162 pregnant women who had participated in the cohort for childhood origin of asthma and allergic disease study between 2008 and 2015. Maternal exposures to particulate matter with an aerodynamic diameter < 2.5 µm (PM2.5) and < 10 µm (PM10), as well as to nitrogen dioxide (NO2) and ozone (O3) for each trimesterand the entire pregnancy were determined using land-use regression models. Maternal perceived stress during the third trimester was assessed using the 14-item Perceived Stress Scale (PSS): scores ranged from 0-56 with higher scores indicating increased stress. Linear regression models were applied to estimate associations between PSS scores and each air pollutant, after adjusting for socio-demographic and behavioral covariates.Results: In single-pollutant models,after adjustment, an IQR increase in the whole pregnancy exposure to PM2.5 and PM10 and O3 in the third trimester was related to 0.37 (95% confidence interval [CI]: 0.01, 0.74) and 0.55 (95% CI: 0.12, 0.98) and 0.29 (95% CI: 0.05, 0.52) points increase in the PSS score, respectively.This association was more evident in women with child-bearing age and lower levelofeducation, and the association of PM10was stronger in thespring season.In multi-pollutant models, exposures to PM10 and O3 were associated with higher perceived stress. Conclusion:Our findings suggest that pregnancy exposure to PM2.5, PM10and O3 is positively associated with maternal PSS score during the third trimester.

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Association between ambient air pollution and perceived stress in pregnant women

Scientific Reports ◽

10.1038/s41598-021-02845-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Dirga Kumar Lamichhane ◽

Dal-Young Jung ◽

Yee-Jin Shin ◽

Kyung-Sook Lee ◽

So-Yeon Lee ◽

...

Keyword(s):

Air Pollution ◽

Pregnant Women ◽

Perceived Stress ◽

Regression Models ◽

Maternal Stress ◽

Ambient Air ◽

Air Pollutant ◽

Ambient Air Pollution ◽

Prenatal Maternal Stress ◽

Linear Regression Models

AbstractAir pollution may influence prenatal maternal stress, but research evidence is scarce. Using data from a prospective cohort study conducted on pregnant women (n = 2153), we explored the association between air pollution and perceived stress, which was assessed using the 14-item Perceived Stress Scale (PSS), among pregnant women. Average exposures to particulate matter with an aerodynamic diameter of < 2.5 µm (PM2.5) or < 10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) for each trimester and the entire pregnancy were estimated at maternal residential addresses using land-use regression models. Linear regression models were applied to estimate associations between PSS scores and exposures to each air pollutant. After adjustment for potential confounders, interquartile-range (IQR) increases in whole pregnancy exposures to PM2.5, PM10, and O3 in the third trimester were associated with 0.37 (95% confidence interval [CI] 0.01, 0.74), 0.54 (95% CI 0.11, 0.97), and 0.30 (95% CI 0.07, 0.54) point increases in prenatal PSS scores, respectively. Furthermore, these associations were more evident in women with child-bearing age and a lower level of education. Also, the association between PSS scores and PM10 was stronger in the spring. Our findings support the relationship between air pollution and prenatal maternal stress.

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Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18105353 ◽

2021 ◽

Vol 18 (10) ◽

pp. 5353

Author(s):

Qiwei Yu ◽

Liqiang Zhang ◽

Kun Hou ◽

Jingwen Li ◽

Suhong Liu ◽

...

Keyword(s):

Air Pollution ◽

Cancer Risk ◽

Air Pollutants ◽

Gynecological Cancer ◽

Gynecologic Cancer ◽

Ambient Air ◽

Air Pollutant ◽

Ambient Air Pollution ◽

Short Term Exposure ◽

Increased Risk

Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case–control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1–Phase 6) of women’s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM2.5, CO, O3, and SO2) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m−3 increase in CO exposures was 1.010 (95% CI: 0.881–1.139) below 0.8 mg m−3, 1.032 (95% CI: 0.871–1.194) at 0.8–1.0 mg m−3, 1.059 (95% CI: 0.973–1.145) at 1.0–1.4 mg m−3, and 1.120 (95% CI: 0.993–1.246) above 1.4 mg m−3. The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.

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Trimester effects of source-specific PM10 on birth weight outcomes in the Avon Longitudinal Study of Parents and Children (ALSPAC)

Environmental Health ◽

10.1186/s12940-020-00684-w ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Yingxin Chen ◽

Susan Hodgson ◽

John Gulliver ◽

Raquel Granell ◽

A. John Henderson ◽

...

Keyword(s):

Longitudinal Study ◽

Birth Weight ◽

Regression Models ◽

Linear Regression Models ◽

Exposure Misclassification ◽

Third Trimester ◽

Residential History ◽

The Third ◽

Parents And Children ◽

Avon Longitudinal Study

Abstract Background Evidence suggests that exposure to particulate matter with aerodynamic diameter less than 10 μm (PM10) is associated with reduced birth weight, but information is limited on the sources of PM10 and exposure misclassification from assigning exposures to place of residence at birth. Methods Trimester and source-specific PM10 exposures (PM10 from road source, local non-road source, and total source) in pregnancy were estimated using dispersion models and a full maternal residential history for 12,020 births from the Avon longitudinal study of parents and children (ALSPAC) cohort in 1990–1992 in the Bristol area. Information on birth outcomes were obtained from birth records. Maternal sociodemographic and lifestyle factors were obtained from questionnaires. We used linear regression models for continuous outcomes (birth weight, head circumference (HC), and birth length (BL) and logistic regression models for binary outcomes (preterm birth (PTB), term low birth weight (TLBW) and small for gestational age (SGA)). Sensitivity analysis was performed using multiple imputation for missing covariate data. Results After adjustment, interquartile range increases in source specific PM10 from traffic were associated with 17 to 18% increased odds of TLBW in all pregnancy periods. We also found odds of TLBW increased by 40% (OR: 1.40, 95%CI: 1.12, 1.75) and odds of SGA increased by 18% (OR: 1.18, 95%CI: 1.05, 1.32) per IQR (6.54 μg/m3) increase of total PM10 exposure in the third trimester. Conclusion This study adds to evidence that maternal PM10 exposures affect birth weight, with particular concern in relation to exposures to PM10 from road transport sources; results for total PM10 suggest greatest effect in the third trimester. Effect size estimates relate to exposures in the 1990s and are higher than those for recent studies – this may relate to reduced exposure misclassification through use of full residential history information, changes in air pollution toxicity over time and/or residual confounding.

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Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population

10.21203/rs.3.rs-109665/v2 ◽

2021 ◽

Author(s):

Wenqian Lu ◽

Mingjuan Luo ◽

Xiangnan Fang ◽

Rong Zhang ◽

Mengyang Tang ◽

...

Keyword(s):

Diabetes Mellitus ◽

Logistic Regression ◽

Gestational Diabetes ◽

Pregnant Women ◽

Regression Models ◽

Second Trimester ◽

Third Trimester ◽

Logistic Regression Models ◽

The Third ◽

Clinical Indices

Abstract Background: Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings.Methods: Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices. Results: This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices. Conclusions: Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

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Ambient Air Pollution and Hospital Admissions for Peptic Ulcers in Taipei: A Time-Stratified Case-Crossover Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16111916 ◽

2019 ◽

Vol 16 (11) ◽

pp. 1916 ◽

Cited By ~ 5

Author(s):

Shang-Shyue Tsai ◽

Hui-Fen Chiu ◽

Chun-Yuh Yang

Keyword(s):

Air Pollution ◽

Peptic Ulcer ◽

Crossover Study ◽

Air Pollutants ◽

Hospital Admissions ◽

Ambient Air ◽

Air Pollutant ◽

Ambient Air Pollution ◽

Research Database ◽

Case Crossover

Very few studies have been performed to determine whether there is a relationship between air pollution and increases in hospitalizations for peptic ulcer, and for those that have occurred, their results may not be completely relevant to Taiwan, where the mixture of ambient air pollutants differ. We performed a time-stratified case-crossover study to investigate the possible association between air pollutant levels and hospital admissions for peptic ulcer in Taipei, Taiwan. To do this, we collected air pollution data from Taiwan's Environmental Protection Agency and hospital admissions for peptic ulcer data for the years 2009–2013 from Taiwan's National Health Insurance's research database. We used conditional logistic regression to analyze the possible association between the two, taking temperature and relative humidity into account. Risk was expressed as odds ratios and significance was expressed with 95% confidence intervals. In our single pollutant model, peptic ulcer admissions were significantly associated with all pollutants (PM10, PM2.5, SO2, NO2, CO, and O3) on warm days (>23 °C). On cool days (<23 °C), peptic ulcer admissions were significantly associated with PM10, NO2, and O3. In our two-pollutant models, peptic ulcer admissions were significantly associated NO2 and O3 when combined with each of the other pollutants on warm days, and with PM10, NO2, and O3 on cool days. It was concluded that the likelihood of peptic ulcer hospitalizations in Taipei rose significantly with increases in air pollutants during the study period.

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Maternal Exposure to Indoor Air Pollution and Birth Outcomes

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16081364 ◽

2019 ◽

Vol 16 (8) ◽

pp. 1364 ◽

Cited By ~ 5

Author(s):

Peter Franklin ◽

Mark Tan ◽

Naomi Hemy ◽

Graham L. Hall

Keyword(s):

Air Pollution ◽

Pregnant Women ◽

Birth Outcomes ◽

Indoor Air ◽

Indoor Air Pollution ◽

Linear Models ◽

Ambient Air ◽

Ambient Air Pollution ◽

Z Score ◽

Birth Records

There is a growing body of research on the association between ambient air pollution and adverse birth outcomes. However, people in high income countries spend most of their time indoors. Pregnant women spend much of that time at home. The aim of this study was to investigate if indoor air pollutants were associated with poor birth outcomes. Pregnant women were recruited prior to 18 weeks gestation. They completed a housing questionnaire and household chemical use survey. Indoor pollutants, formaldehyde (HCHO), nitrogen dioxide (NO2) and volatile organic compounds (VOCs), were monitored in the women’s homes at 34 weeks gestation. Gestational age (GA), birth weight (BW) and length (BL) and head circumference (HC) were collected from birth records. The associations between measured pollutants, and pollution surrogates, were analysed using general linear models, controlling for maternal age, parity, maternal health, and season of birth. Only HCHO was associated with any of the birth outcomes. There was a 0.044 decrease in BW z-score (p = 0.033) and 0.05 decrease in HC z-score (p = 0.06) for each unit increase in HCHO. Although HCHO concentrations were very low, this finding is consistent with other studies of formaldehyde and poor birth outcomes.

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Ambient air pollution exposure and risk and progression of interstitial lung abnormalities: the Framingham Heart Study

Thorax ◽

10.1136/thoraxjnl-2018-212877 ◽

2019 ◽

Vol 74 (11) ◽

pp. 1063-1069 ◽

Cited By ~ 8

Author(s):

Mary B Rice ◽

Wenyuan Li ◽

Joel Schwartz ◽

Qian Di ◽

Itai Kloog ◽

...

Keyword(s):

Air Pollution ◽

Logistic Regression ◽

Regression Models ◽

Cardiac Ct ◽

Prediction Models ◽

Ambient Air ◽

Chest Ct ◽

Ambient Air Pollution ◽

Logistic Regression Models ◽

Lung Abnormalities

BackgroundAmbient air pollution accelerates lung function decline among adults, however, there are limited data about its role in the development and progression of early stages of interstitial lung disease.AimsTo evaluate associations of long-term exposure to traffic and ambient pollutants with odds of interstitial lung abnormalities (ILA) and progression of ILA on repeated imaging.MethodsWe ascertained ILA on chest CT obtained from 2618 Framingham participants from 2008 to 2011. Among 1846 participants who also completed a cardiac CT from 2002 to 2005, we determined interval ILA progression. We assigned distance from home address to major roadway, and the 5-year average of fine particulate matter (PM2.5), elemental carbon (EC, a traffic-related PM2.5 constituent) and ozone using spatio-temporal prediction models. Logistic regression models were adjusted for age, sex, body mass index, smoking status, packyears of smoking, household tobacco exposure, neighbourhood household value, primary occupation, cohort and date.ResultsAmong 2618 participants with a chest CT, 176 (6.7%) had ILA, 1361 (52.0%) had no ILA, and the remainder were indeterminate. Among 1846 with a preceding cardiac CT, 118 (6.4%) had ILA with interval progression. In adjusted logistic regression models, an IQR difference in 5-year EC exposure of 0.14 µg/m3 was associated with a 1.27 (95% CI 1.04 to 1.55) times greater odds of ILA, and a 1.33 (95% CI 1.00 to 1.76) times greater odds of ILA progression. PM2.5 and O3 were not associated with ILA or ILA progression.ConclusionsExposure to EC may increase risk of progressive ILA, however, associations with other measures of ambient pollution were inconclusive.

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Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population

Nutrition & Metabolism ◽

10.1186/s12986-021-00606-8 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Wenqian Lu ◽

Mingjuan Luo ◽

Xiangnan Fang ◽

Rong Zhang ◽

Shanshan Li ◽

...

Keyword(s):

Diabetes Mellitus ◽

Logistic Regression ◽

Gestational Diabetes ◽

Pregnant Women ◽

Regression Models ◽

Second Trimester ◽

Third Trimester ◽

Logistic Regression Models ◽

The Third ◽

Clinical Indices

Abstract Background Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings. Methods Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices. Results This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices. Conclusions Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

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Lead exposure and serum metabolite profiles in pregnant women in Mexico City

Environmental Health ◽

10.1186/s12940-021-00810-2 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Megan M. Niedzwiecki ◽

Shoshannah Eggers ◽

Anu Joshi ◽

Georgia Dolios ◽

Alejandra Cantoral ◽

...

Keyword(s):

Pregnant Women ◽

Mexico City ◽

Health Hazard ◽

Linear Regression Models ◽

Third Trimester ◽

Growth Environment ◽

Negatively Associated ◽

The Third ◽

Wide Range ◽

Pb Exposure

Abstract Background Lead (Pb) exposure is a global health hazard causing a wide range of adverse health outcomes. Yet, the mechanisms of Pb toxicology remain incompletely understood, especially during pregnancy. To uncover biological pathways impacted by Pb exposure, this study investigated serum metabolomic profiles during the third trimester of pregnancy that are associated with blood Pb and bone Pb. Methods We used data and specimens from 99 women enrolled in the Programming Research in Obesity, Growth, Environment, and Social Stressors birth cohort in Mexico City. Maternal Pb exposure was measured in whole blood samples from the third trimester of pregnancy and in the tibia and patella bones at 1 month postpartum. Third-trimester serum samples underwent metabolomic analysis; metabolites were identified based on matching to an in-house analytical standard library. A metabolome-wide association study was performed using multiple linear regression models. Class- and pathway-based enrichment analyses were also conducted. Results The median (interquartile range) blood Pb concentration was 2.9 (2.6) µg/dL. Median bone Pb, measured in the tibia and patella, were 2.5 (7.3) µg/g and 3.6 (9.5) µg/g, respectively. Of 215 total metabolites identified in serum, 31 were associated with blood Pb (p < 0.05). Class enrichment analysis identified significant overrepresentation of metabolites classified as fatty acids and conjugates, amino acids and peptides, and purines. Tibia and patella Pb were associated with 14 and 8 metabolites, respectively (p < 0.05). Comparing results from bone and blood Pb, glycochenodeoxycholic acid, glycocholic acid, and 1-arachidonoylglycerol were positively associated with blood Pb and tibia Pb, and 7-methylguanine was negatively associated with blood Pb and patella Pb. One metabolite, 5-aminopentanoic acid, was negatively associated with all three Pb measures. Conclusions This study identified serum metabolites in pregnant women associated with Pb measured in blood and bone. These findings provide insights on the metabolic profile around Pb exposure in pregnancy and information to guide mechanistic studies of toxicological effects for mothers and children.

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Assessment of Household and Outdoor Air Pollution Exposure Link to Urinary Metals Content in Pregnant Women

Atmosphere ◽

10.3390/atmos11060638 ◽

2020 ◽

Vol 11 (6) ◽

pp. 638

Author(s):

Isabella Karakis ◽

Nofar Shemesh ◽

Ofir Tirosh ◽

Daniella Landau ◽

Roni Gat ◽

...

Keyword(s):

Air Pollution ◽

Pregnant Women ◽

Prevalence Ratio ◽

Ambient Air ◽

Ambient Air Pollution ◽

Nickel Aluminum ◽

Simultaneous Exposure ◽

Exposure Effect ◽

Cobalt Nickel ◽

Pollution Exposure

We aimed to estimate the association of urinary metal content with the exposure to hazardous household factors and ambient air pollution in pregnant women. We analyzed urine samples of 143 women enrolled at delivery and assessed household exposure by questionnaire. Air pollution estimates were based on monitoring stations and satellite-based models. Complaints about noise, rubbish, and sewage in the neighborhood were associated with higher uranium concentrations (prevalence ratio (PR) = 1.42, 1.46, and 1.18, respectively). Complaints about noise were more frequent in women with higher cobalt, nickel, molybdenum, cadmium, and vanadium urine concentrations (PRs = 2.42–9.43), and complaints about smell in women with higher cobalt and strontium (PRs = 2.55–6.27). Exposure to nitrogen oxides was associated with higher concentrations of nickel, aluminum, lead, and chromium in urine (PRs = 1.80–5.85). Women exposed to elevated levels of particulate matter were more likely to have higher concentrations of cobalt, nickel, thallium, lead, iron, strontium, barium, silver, and chromium (PRs = 1.97–13.64). Exposure to high levels of sulfur dioxide was positively associated with cobalt and nickel (PR = 1.98 and 1.88, respectively). The current analysis suggests the possibility of a related simultaneous exposure to multiple pollutants. Further studies are warranted to corroborate the findings and reveal the multiple exposure effect on human health.

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