Industrial air pollution and low birth weight: a case-control study in Texas, USA

The association between exposure to polycyclic aromatic hydrocarbons and birth outcomes: A systematic review and meta-analysis of observational studies

Exposure to polycyclic aromatic hydrocarbons (PAHs) has been linked to adverse birth outcomes; however, to date, the available studies on such relations, with the exception of birth weight, has not been systematically synthesized. We conducted a systematic review and meta-analysis of the available observational studies on the association of maternal exposure to PAHs and their metabolites during pregnancy with indicators of fetal growth and gestational age at delivery. We searched Web of Science, PubMed and Scopus systematically for all relevant published papers in English until 13 January 2023. Random effects meta-analysis was applied to synthesize the association estimates. Publication bias was assessed using Egger's regression. A total of 31 articles were included in our review (n = 703,080 participants). Our quality assessment of reviewed papers showed that 19 research had excellent, nine had good, and three had fair quality. Most of the reviewed studies on exposure to PAHs and their metabolites with gestational age and preterm birth (seven studies) reported no statistically significant association. Eight studies were eligible for our meta-analysis. Results of the meta-analysis indicated that higher levels of maternal urinary 1-OHP was associated with lower birth weight, birth length and head circumference and a higher risk of low birth weight (LBW). However, these associations were not statistically significant. Similarly, the combined association between maternal urinary 1-OHP and newborn's Ponderal index (PI) and Cephalization index were not statistically significant. Overall, our systematic review and meta-analysis suggested a potential adverse impact of exposure to PAHs on LBW, HC, and CC; however, further studies are required to be able to draw concrete conclusions on such associations.

Industrial air pollution and low birth weight in New Mexico, USA

In recent decades, the low birth weight (LBW) rate in New Mexico has consistently exceeded the Unites States average. Maternal exposure to air pollution during pregnancy may be a significant contributor to LBW in offspring. This study investigated the links between maternal residential exposure to air pollution from industrial sources and the risk of LBW in offspring. The analysis included 22,375 LBW cases and 233,340 controls. It focused on 14 common chemicals listed in the Toxic Release Inventory (TRI) and monitoring datasets, which have abundant monitoring samples. The Emission Weighted Proximity Model (EWPM) was used to calculate maternal air pollution exposure intensity. Adjusted odds ratios (adjORs) were calculated using binary logistic regressions to examine the association between maternal residential air pollution exposure and LBW, while controlling for potential confounders, such as the maternal age, race/ethnicity, gestational age, prenatal care, education level, consumption of alcohol during pregnancy, public health regions, child's sex, and the year of birth. Multiple comparison correction was applied using the False Discovery Rate approach. The results showed that maternal residential exposure to 1,2,4-trimethylbenzene, benzene, chlorine, ethylbenzene, and styrene had significant positive associations with LBW in offspring, with adjusted odds ratios ranging from 1.10 to 1.13. These five chemicals remained as significant risk factors after dividing the estimated exposure intensities into four categories. In addition, significant linear trends were found between LBW and maternal exposure to each of the five identified chemicals. Furthermore, 1,2,4-trimethylbenzene was identified as a risk factor to LBW for the first time. The findings of this study should be confirmed through additional epidemiological, biological, and toxicological studies.

A pruned feed-forward neural network (pruned-FNN) approach to measure air pollution exposure

Environmental epidemiology studies require accurate estimations of exposure intensities to air pollution. The process from air pollutant emission to individual exposure is however complex and nonlinear, which poses significant modeling challenges. This study aims to develop an exposure assessment model that can strike a balance between accuracy, complexity, and usability. In this regard, neural networks offer one possible approach. This study employed a custom-designed pruned feed-forward neural network (pruned-FNN) approach to calculate the air pollution exposure index based on emission time and rates, terrain factors, meteorological conditions, and proximity measurements. The model's performance was evaluated by cross-validating the estimated exposure indexes with ground-based monitoring records. The pruned FNN can predict pollution exposure indexes (PEIs) that are highly and stably correlated with the monitored air pollutant concentrations (Spearman's rank correlation coefficients for tenfold cross-validation (mean ± standard deviation: 0.906 ± 0.028) and for random cross-validation (0.913 ± 0.024)). The predicted values are also close to the ground truth in most cases (95.5% of the predicted PEIs have relative errors smaller than 10%) when the training datasets are sufficiently large and well-covered. The pruned-FNN method can make accurate exposure estimations using a flexible number of variables and less extensive data in a less money/time-consuming manner. Compared to other exposure assessment models, the pruned FNN is an appropriate and effective approach for exposure assessment that covers a large geographic area over a long period of time.

Industrial Air Pollution Leads to Adverse Birth Outcomes: A Systematized Review of Different Exposure Metrics and Health Effects in Newborns

Objectives: To review the evidence of associations between adverse birth outcomes (ABO) and industrial air pollution.

Methods: Searches were conducted in PubMed, and Scopus databases, and additional articles were found from snowball search techniques. The included studies feature a study population of mothers with live-born babies exposed to industrial air pollutants, and they examine the effects of industrial pollutants on adverse birth outcomes—namely, low birth weight, term low birth weight, preterm birth, and small for gestational age.

Results: Altogether, 45 studies were included in this review. Exposure to PM2.5, PAHs, benzene, cadmium, and mixtures of industrial air pollutants and living near an industrial area affect birth outcomes.

Conclusion: This study concludes that industrial air pollution is an important risk factor for ABO, especially low birth weight and preterm birth. The strongest evidence is associations between ABO and air pollution from power plants and petrochemical industries. Understanding of specific chemicals that are critical to birth outcomes is still vague. However, the evidence is strongest for more specific air pollutants from the industry, such as PAH, benzene, BTEX, and cadmium.

A method for identifying critical time windows of maternal air pollution exposures associated with low birth weight in offspring using massive geographic data

Associations between maternal exposures to air pollutants and low birth weight (LBW) in offspring varied when different exposure windows were considered. Methods used in previous studies lacked flexibility in delineating exposure windows and did not consider time periods before conception, which may restrict the discoveries of critical exposure windows. This study introduces a novel method to identify critical windows of maternal air pollution exposures associated with LBW in offspring using massive georeferenced data. Through a case-control study based on birth data (94,106 LBW cases and 376,424 controls) and air quality monitoring data (367 chemicals) in Texas during 1996-2008, this study used the average ambient concentration measured by the monitoring site closest to the residence location of a mother during a time window as the maternal exposure to a specific chemical during that exposure window. Binary logistic regression was utilized to estimate air pollutant-LBW associations in different exposure windows. The odds ratios (ORs) were adjusted for child's sex, gestational weeks, maternal age, race/ethnicity, and education. The adjusted ORs were plotted against the exposure window series of different sizes for each chemical, aiming at interactively visualizing and exploring the critical exposure windows across multiple temporal scales. This study identifies ten chemicals and seventeen corresponding critical exposure windows where strong air pollutant-LBW associations are detected. The ten identified chemicals are benzaldehyde, sum of Photochemical Assessment Monitoring Stations (PAMS) target compounds, n-undecane, m-tolualdehyde, organic carbon fraction 2 (OC2), ethylene dibromide, valeraldehyde, propionaldehyde, 4-methyl-1-pentene, and zirconium. Nine critical exposure windows involving six chemicals start more than five months prior to conception, seven windows involving five chemicals commence in the second and/or third trimester of pregnancy, and the remaining one window is located in other time periods. The novel method reveals a number of critical time windows of maternal exposure to ten chemicals that are positively associated with LBW in offspring. These ten chemicals were identified as LBW risk factors for the first time. Additional studies with more data are needed to validate the results in the future.

The impact of environmental pollution on the physical health of middle-aged and older adults in China

While several studies have demonstrated the negative impacts of environmental pollution on population health, in general, few studies have examined the potential differential effects on the physical health of middle-aged and older populations, i.e., 45 years and older. Given the twin concerns of environmental pollution and population aging in China, this article employed a fixed effects model to infer the impact of environmental pollution on public health with a particular focus on middle-aged and older adults. The analyses were based on data from the 2011 to 2018 waves of the CHARLS and pollutant data from prefecture-level cities. The results showed that both the level and intensity of environmental pollution significantly increased the risk of chronic diseases and negatively impacted the physical health of middle-aged and older adults. Environmental pollution had its greatest negative effect on the physical health of the elderly, urban residents, residents of the Eastern region, and those with lower incomes than their counterparts. We further found that the potential channels of health effect were through reduced physical exercise and sleep duration and an increase in depressive symptoms, and the pollution prevention actions alleviated the health deterioration of environmental pollution for the middle-aged and the elderly. It is imperative for the government to urgently reinforce policy enforcement to decrease air and water pollution and enhance the ability to circumvent pollution for the lower socioeconomic groups.

Assimilative capacity approach for air pollution control in automotive engines through magnetic field-assisted combustion of hydrocarbons

Deterioration of air quality through the combustion of hydrocarbon fuels has been one of the global transboundary problems put before the research community since last five decades. According to the updated statistics, 79% of energy needs in India are met by fossil fuel combustion which results in the emission of toxic pollutants like carbon monoxide, oxides of nitrogen, and unburned hydrocarbons. Air quality has seriously been affected in many parts of India, and statistically, 13 out of 15 most polluted cities in the world lie in India. Magnetic field-assisted combustion has been proven as a reliable technology in internal combustion engines for enhancing the combustion of fuels and reduction of harmful emissions that are the byproducts of incomplete combustion of fuels. In the present work, the magnetic field-assisted combustion of a liquid-phase and a gas-phase fuel (gasoline and LPG) has been studied in a multicylinder automobile engine replicating on road driving conditions in a laboratory focusing on the levels of emissions in comparison with normal combustion of both the fuels. The experimental study concludes that the applied magnetic field positively influences combustion, resulting in reduced level of emission of toxic components irrespective of the phase of hydrocarbon fuels. It is also observed that the percentage reduction in emissions increases with increase in intensity of magnetization. The maximum reduction obtained for CO and UBHC emissions through this technique is 20.58% and 14.47%, respectively. The effectiveness of MFAC in countering air pollution from vehicular exhaust is also studied with respect to fuel phase and mode of operation. The effectiveness of MFAC is observed to be more in high-speed operation of the engine and decreases in the order CO > UBHC > NO. The obtained emission results have a cumulative significance as 45% of total air pollution in India is caused by combustion of hydrocarbons in automotive engines.

Prenatal Air Pollution Exposure and Placental DNA Methylation Changes: Implications on Fetal Development and Future Disease Susceptibility

The Developmental Origins of Health and Disease (DOHaD) concept postulates that in utero exposures influence fetal programming and health in later life. Throughout pregnancy, the placenta plays a central role in fetal programming; it regulates the in utero environment and acts as a gatekeeper for nutrient and waste exchange between the mother and the fetus. Maternal exposure to air pollution, including heavy metals, can reach the placenta, where they alter DNA methylation patterns, leading to changes in placental function and fetal reprogramming. This review explores the current knowledge on placental DNA methylation changes associated with prenatal air pollution (including heavy metals) exposure and highlights its effects on fetal development and disease susceptibility. Prenatal exposure to air pollution and heavy metals was associated with altered placental DNA methylation at the global and promoter regions of genes involved in biological processes such as energy metabolism, circadian rhythm, DNA repair, inflammation, cell differentiation, and organ development. The altered placental methylation of these genes was, in some studies, associated with adverse birth outcomes such as low birth weight, small for gestational age, and decreased head circumference. Moreover, few studies indicate that DNA methylation changes in the placenta were sex-specific, and infants born with altered placental DNA methylation patterns were predisposed to developing neurobehavioral abnormalities, cancer, and atopic dermatitis. These findings highlight the importance of more effective and stricter environmental and public health policies to reduce air pollution and protect human health.

Predict Health Care Accessibility for Texas Medicaid Gap

Medicaid is a unique approach in ensuring the below poverty population obtains free insurance coverage under federal and state provisions in the United States. Twelve states without expanded Medicaid caused two million people who were under the poverty line into health insecurity. Principal Component-based logistical regression (PCA-LA) is used to consider health status (HS) as a dependent variable and fourteen social-economic indexes as independent variables. Four composite components incorporated health conditions (i.e., “no regular source of care” (NRC), “last check-up more than a year ago” (LCT)), demographic impacts (i.e., four categorized adults (AS)), education (ED), and marital status (MS). Compared to the unadjusted LA, direct adjusted LA, and PCA-unadjusted LA three methods, the PCA-LA approach exhibited objective and reasonable outcomes in presenting an odd ratio (OR). They included that health condition is positively significant to HS due to beyond one OR, and negatively significant to ED, AS, and MS. This paper provided quantitative evidence for the Medicaid gap in Texas to extend Medicaid, exposed healthcare geographical inequity, offered a sight for the Centers for Disease Control and Prevention (CDC) to improve the Medicaid program and make political justice for the Medicaid gap.

Prevalence and risk factors of childhood blepharoptosis in Koreans: the Korea National Health and Nutrition Examination Survey

Purpose:

Childhood blepharoptosis may cause cosmetic and functional problems in children, but there is a paucity of studies about its epidemiology. This study aimed to investigate the prevalence of childhood blepharoptosis and associated risk factors in a representative Korean population.

Methods:

This cross-sectional nation-wide study analysed the data set acquired from the Korea National Health and Nutrition Examination Survey 2008–2012. A total of 8218 children aged 3–18 years were included. The prevalence of childhood blepharoptosis, defined as a margin reflex distance (MRD) of < 2 mm in either eye, was estimated, and the risk factors were identified using multivariate logistic regression analysis.

Results:

The mean age of participants was 11.3 ± 0.1 years, and 52.8 ± 0.6% were boys. The overall prevalence of childhood blepharoptosis in Korea was 8.0% (95% CI, 6.9–9.1%). Boys exhibited a higher prevalence of blepharoptosis than girls at most of ages. Levator function increased with age in the normal general population. The proportion of subjects exhibiting MRD1 ≥ 4.0 mm also increased significantly with age (p < 0.001). Male gender, higher body mass index, and urban residency were significantly associated with childhood blepharoptosis.

Conclusions:

The prevalence of childhood blepharoptosis is higher in urban obese boys. The increase of levator function with age should be considered in evaluations of childhood ptosis.