Effect of PM2.5 on macrosomia in China: A nationwide prospective cohort study

Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy

INTRODUCTION

The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before becoming pregnant, there is no prediction model yet.

MATERIAL AND METHODS

The data were collected from the National Free Preconception Health Examination Project in China. A sum of 455 neonates (42 SGA births and 423 non-LGA births) were included. A training set (n = 319) and a test set (n = 136) were created from the dataset at random. To develop prediction models for LGA neonates, conventional logistic regression (LR) method and six machine learning methods were used in this study. Recursive feature elimination approach was performed by choosing 10 features which made a big contribution to the prediction models. And the Shapley Additive Explanation model was applied to interpret the most important characteristics that affected forecast outputs.

RESULTS

The random forest (RF) model had the highest average area under the receiver-operating-characteristic curve (AUC) for predicting LGA in the test set (0.843, 95% confidence interval [CI]: 0.714-0.974). Except for the logistic regression model (AUC: 0.603, 95%CI: 0.440-0.767), other models' AUCs displayed well. Thereinto, the RF algorithm's final prediction model using 10 characteristics achieved an average AUC of 0.821 (95% CI: 0.693-0.949).

CONCLUSION

The prediction model based on machine learning might be a promising tool for the prenatal prediction of LGA births in women with radiation exposure before pregnancy.

Effects of fine particulate matter on bone marrow-conserved hematopoietic and mesenchymal stem cells: a systematic review

The harmful effects of fine particulate matter ≤2.5 µm in size (PM2.5) on human health have received considerable attention. However, while the impact of PM2.5 on the respiratory and cardiovascular systems has been well studied, less is known about the effects on stem cells in the bone marrow (BM). With an emphasis on the invasive characteristics of PM2.5, this review examines the current knowledge of the health effects of PM2.5 exposure on BM-residing stem cells. Recent studies have shown that PM2.5 enters the circulation and then travels to distant organs, including the BM, to induce oxidative stress, systemic inflammation and epigenetic changes, resulting in the reduction of BM-residing stem cell survival and function. Understanding the broader health effects of air pollution thus requires an understanding of the invasive characteristics of PM2.5 and its direct influence on stem cells in the BM. As noted in this review, further studies are needed to elucidate the underlying processes by which PM2.5 disturbs the BM microenvironment and inhibits stem cell functionality. Strategies to prevent or ameliorate the negative effects of PM2.5 exposure on BM-residing stem cells and to maintain the regenerative capacity of those cells must also be investigated. By focusing on the complex relationship between PM2.5 and BM-resident stem cells, this review highlights the importance of specific measures directed at safeguarding human health in the face of rising air pollution.

Joint effects of prenatal exposure to air pollution and pregnancy-related anxiety on birth weight: A prospective birth cohort study in Ma'anshan, China

BACKGROUND

A growing number of studies have shown that prenatal exposure to chemical and non-chemical stressors has effects on fetal growth. The co-exposure of both better reflects real-life exposure patterns. However, no studies have included air pollutants and pregnancy-related anxiety (PrA) as mixtures in the analysis.

METHOD

Using the birth cohort study method, 576 mother-child pairs were included in the Ma'anshan Maternal and Child Health Hospital. Evaluate the exposure levels of six air pollutants during pregnancy using inverse distance weighting (IDW) based on the pregnant woman's residential address and air pollution data from monitoring stations. Prenatal anxiety levels were assessed using the PrA Questionnaire. Generalized linear regression (GLR), quantile g-computation (QgC) and bayesian kernel machine regression (BKMR) were used to assess the independent or combined effects of air pollutants and PrA on birth weight for gestational age z-score (BWz).

RESULT

The results of GLR indicate that the correlation between the six air pollutants and PrA with BWz varies depending on the different stages of pregnancy and pollutants. The QgC shows that during trimester 1, when air pollutants and PrA are considered as a whole exposure, an increase of one quartile is significantly negatively correlated with BWz. The BKMR similarly indicates that during trimester 1, the combined exposure of air pollutants and PrA is moderately correlated with a decrease in BWz.

CONCLUSION

Using the method of analyzing mixed exposures, we found that during pregnancy, the combined exposure of air pollutants and PrA, particularly during trimester 1, is associated with BWz decrease. This supports the view that prenatal exposure to chemical and non-chemical stressors has an impact on fetal growth.

The association between outdoor air pollution and body mass index, central obesity, and visceral adiposity index among middle-aged and elderly adults: a nationwide study in China

Background

Previous animal studies have suggested that air pollution (AP) exposure may be a potential risk factor for obesity; however, there is limited epidemiological evidence available to describe the association of obesity with AP exposure.

Methods

A retrospective cross-sectional study was conducted on 11,766 participants across mainland China in 2015. Obesity was assessed using body mass index (BMI), waist circumference (WC), and visceral adiposity index (VAI). The space-time extremely randomized tree (STET) model was used to estimate the concentration of air pollutants, including SO2, NO2, O3, PM1, PM2.5, and PM10, matched to participants' residential addresses. Logistic regression models were employed to estimate the associations of obesity with outdoor AP exposure. Further stratified analysis was conducted to evaluate whether sociodemographics or lifestyles modified the effects.

Results

Increased AP exposure was statistically associated with increased odds of obesity. The odds ratio (ORs) and 95% confidence interval (CI) of BMI-defined obesity were 1.21 (1.17, 1.26) for SO2, 1.33 (1.26, 1.40) for NO2, 1.15 (1.10, 1.21) for O3, 1.38 (1.29, 1.48) for PM1, 1.19 (1.15, 1.22) for PM2.5, and 1.11 (1.09, 1.13) for PM10 per 10 μg/m3 increase in concentration. Similar results were found for central obesity. Stratified analyses suggested that elderly participants experienced more adverse effects from all 6 air pollutants than middle-aged participants. Furthermore, notable multiplicative interactions were found between O3 exposure and females as well as second-hand smokers in BMI-defined obesity.

Conclusions

This study suggested that outdoor AP exposure had a significant association with the risk of obesity in the middle-aged and elderly Chinese population. Elderly individuals and women may be more vulnerable to AP exposure.

Association of Fine Particulate Matter and Its Components with Macrosomia: A Nationwide Birth Cohort Study of 336 Chinese Cities

To examine the associations between macrosomia risk and exposure to fine particulate matter (PM2.5) and its chemical components during pregnancy, we collected birth records between 2010 and 2015 in mainland China from the National Free Preconception Health Examination Project and used satellite-based models to estimate concentrations of PM2.5 mass and five main components, namely, black carbon (BC), organic carbon (OC), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+). Associations between macrosomia risk and prenatal exposure to PM2.5 were examined by logistic regression analysis, and the sensitive subgroups were explored by stratified analyses. Of the 3,248,263 singleton newborns from 336 cities, 165,119 (5.1%) had macrosomia. Each interquartile range increase in concentration of PM2.5 during the entire pregnancy was associated with increased risk of macrosomia (odds ratio (OR) = 1.18; 95% confidence interval (CI), 1.17-1.20). Among specific components, the largest effect estimates were found on NO3- (OR = 1.36; 95% CI, 1.35-1.38) followed by OC (OR = 1.23; 95% CI, 1.22-1.24), NH4+ (OR = 1.22; 95% CI, 1.21-1.23), and BC (OR = 1.21; 95% CI, 1.20-1.22). We also that found boys, women with a normal or lower prepregnancy body mass index, and women with irregular or no folic acid supplementation experienced higher risk of macrosomia associated with PM2.5 exposure.

Maternal exposure to extreme high-temperature, particulate air pollution and macrosomia in 14 countries of Africa

BACKGROUND

Macrosomia has increased rapidly worldwide in the past few decades, with a huge impact on health. However, the effect of PM_2.5 and extreme high-temperature (EHT) on macrosomia has been ignored.

OBJECTIVE

This study aimed to explore the association between maternal exposure to EHT, PM_2.5 and macrosomia based on the Seventh Demographic and Health Survey (DHS) in 14 countries of Africa.

METHODS

The study included detailed demographic information on 106 382 births and maternal. Satellite inversion models estimated monthly mean PM_2.5 and mean surface temperature of 2 m (SMT_2m ). Macrosomia was defined as the birth weight ≥ 4000 g. We used a Cox proportional risk regression model to estimate the association between PM_2.5 , EHT and macrosomia. We further explored the susceptibility of exposure to EHT and PM_2.5 at different pregnancy periods to macrosomia, and plotted the expose-response curve between PM_2.5 and macrosomia risk using a restricted cubic spline function. In addition, the Interplot model was used to investigate the interaction between EHT and PM_2.5 on macrosomia. Finally, some potential confounding factors were analysed by stratification.

RESULTS

There was the positive association between EHT, PM_2.5 and macrosomia, and the risk of macrosomia with the increase in concentrations of PM_2.5 without clear threshold. Meanwhile, EHT and PM_2.5 had a higher effect on macrosomia in middle/later and early/middle stages of pregnancy, respectively. There was a significant interaction between EHT and PM_2.5 on macrosomia.

CONCLUSIONS

Maternal exposure to EHT, PM_2.5 during pregnancy was associated with an increased risk of macrosomia in Africa.

Exposure of ambient PM2.5 during gametogenesis period affects the birth outcome: Results from the project ELEFANT

Various environmental and behavioural factors influence neonatal health. Gamete formation (gametogenesis) is a crucial period which affects embryo development and neonatal health and ambient air pollution exposure at this stage may lead to an adverse birth outcome. Previous epidemiological and toxicological research demonstrated a strong association between maternal ambient air pollution exposure and adverse birth outcomes. However, the joint exposure-outcome of paternal exposure (76 days before the last menstruation and 14 days after the last menstruation) and maternal exposure (14 days after the last menstruation) when exploring the mechanism of the influence of air pollutants on pregnancy outcome and neonatal health remains unexplored. Here, in the Project Environmental and LifEstyle FActors iN metabolic health throughout life-course Trajectories (ELEFANT), we collected the data of 10,960 singleton pregnant women with 24-42 completed gestational weeks and included them in this study. A multinominal logistic regression model was applied to investigate the association between adverse birth outcomes and ambient PM_2.5 exposure levels during spermatogenesis and oogenesis. Results from the binary classification of ambient PM_2.5 exposure showed that the risk of abnormal birthweight was significantly greater when ambient PM_2.5 exposure was both higher during spermatogenesis and oogenesis, with RRs of 1.86 (95% CI: 1.02, 3.39). The risk of macrosomia (RR: 1.88 (95% CI: 1.13, 3.12)) increased significantly when ambient PM_2.5 levels were higher during spermatogenesis. Primiparity and primigravity are more likely to be influenced by higher ambient PM_2.5 levels during spermatogenesis. In conclusion, more attention should be paid to higher exposure level of ambient PM_2.5 during spermatogenesis.

Air pollution exposure and the risk of macrosomia: Identifying specific susceptible months

Birth weight is an important indicator of future growth and development for newborns. Few studies investigated the potential effects of air pollutants on macrosomia and their susceptible windows. We included 38,971 singleton full-term births from Beijing HaiDian Maternal and Child Health Hospital between 2014 and 2018, and assessed the associations of air pollutants exposure during preconception and pregnancy with macrosomia as well as the corresponding susceptible windows. The concentrations of air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃) for participants were calculated by the data from the nearest monitoring stations. Distributed lag models (DLM) incorporating logistic regression models were used to estimate the associations between air pollutants exposure during the 3 months before conception and pregnancy period and the risk of macrosomia, identifying susceptible windows of air pollutants. Weighted quantile sum (WQS) regression was applied to estimate the joint effect of air pollutants. A 10 μg/m³ increase in PM_2.5 exposure from 3rd to 8th gestational month was positively associated with the risk of macrosomia, with the strongest effect in the 6th month (OR = 1.010, 95 % CI: 1.002-1.019). For a 10 μg/m³ increase in SO₂, the windows of significant exposure were from the 1st preconception month to the 3rd gestational month, with the strongest effect in the 2nd month (OR = 1.030, 95 % CI: 1.010-1.049). We also observed the significant positive associations were in the 5th-8th gestational months for PM₁₀, the 8th-9th gestational months for NO₂ and the 3rd-7th gestational months for CO respectively. WQS regression also indicated a positive association between co-exposure to air pollutants and macrosomia. Our results suggest air pollution exposure is associated with increased risk of macrosomia. The windows of exposure for susceptibility to the risk of macrosomia vary between air pollutants. The susceptible exposure windows were middle and late pregnancy for PM, CO and NO₂, while for SO₂, early pregnancy is the window of vulnerability. Our findings provide the evidence that air pollution exposure is an independent risk factor for macrosomia and a basis for targeted environment policy.

Susceptible windows of exposure to fine particulate matter and fetal growth trajectories in the Spanish INMA (INfancia y Medio Ambiente) birth cohort

While prior studies report associations between fine particulate matter (PM2.5) exposure and fetal growth, few have explored temporally refined susceptible windows of exposure. We included 2328 women from the Spanish INMA Project from 2003 to 2008. Longitudinal growth curves were constructed for each fetus using ultrasounds from 12, 20, and 34 gestational weeks. Z-scores representing growth trajectories of biparietal diameter, femur length, abdominal circumference (AC), and estimated fetal weight (EFW) during early (0-12 weeks), mid- (12-20 weeks), and late (20-34 weeks) pregnancy were calculated. A spatio-temporal random forest model with back-extrapolation provided weekly PM2.5 exposure estimates for each woman during her pregnancy. Distributed lag non-linear models were implemented within the Bayesian hierarchical framework to identify susceptible windows of exposure for each outcome and cumulative effects [βcum, 95% credible interval (CrI)] were aggregated across adjacent weeks. For comparison, general linear models evaluated associations between PM2.5 averaged across multi-week periods (i.e., weeks 1-11, 12-19, and 20-33) and fetal growth, mutually adjusted for exposure during each period. Results are presented as %change in z-scores per 5 μg/m3 in PM2.5, adjusted for covariates. Weeks 1-6 [βcum = -0.77%, 95%CrI (-1.07%, -0.47%)] were identified as a susceptible window of exposure for reduced late pregnancy EFW while weeks 29-33 were positively associated with this outcome [βcum = 0.42%, 95%CrI (0.20%, 0.64%)]. A similar pattern was observed for AC in late pregnancy. In linear regression models, PM2.5 exposure averaged across weeks 1-11 was associated with reduced late pregnancy EFW and AC; but, positive associations between PM2.5 and EFW or AC trajectories in late pregnancy were not observed. PM2.5 exposures during specific weeks may affect fetal growth differentially across pregnancy and such associations may be missed by averaging exposure across multi-week periods, highlighting the importance of temporally refined exposure estimates when studying the associations of air pollution with fetal growth.

The impact of prolonged exposure to air pollution on the incidence of chronic non-communicable disease based on a cohort in Tianjin

Evidence on the associations of prolonged ambient pollutants exposure with chronic non-communicable diseases among middle-aged and elderly residents is still limited. This prospective cohort study intends to investigate the long-term effects of ambient pollution on hypertension and diabetes incidence among relatively older residents in China. Individual particulate matter exposure levels were estimated by satellite-based model. Individual gaseous pollutants exposure levels were estimated by Inverse Distance Weighted model. A Cox regression model was employed to assess the risks of hypertension and diabetes morbidity linked to air pollutants exposures. The cross-product term of ambient pollutants exposure and covariates was further added into the regression model to test whether covariates would modify these air pollution-morbidity associations. During the period from 2014 to 2018, a total of 97,982 subjects completed follow-up. 12,371 incidents of hypertension and 2034 of diabetes occurred. In the multi-covariates model, the hazard ratios (HR) and 95% confidence interval (CI) were 1.49 (1.45-1.52), 1.28 (1.26-1.30), 1.17 (1.15-1.18), 1.21 (1.17-1.25) and 1.33 (1.31-1.35) for hypertension morbidity per 10 μg/m³ increment in PM₁, PM_2.5, PM₁₀, NO₂ and SO₂, respectively. For diabetes onsets, the HR (95% CI) were 1.17 (1.11-1.23), 1.09 (1.04-1.13), 1.06 (1.02-1.09), 1.02 (0.95-1.10), and 1.24 (1.19-1.29), respectively. In addition, for hypertension analyses, the effect estimates were more pronounced in the participants with age <60 years old, BMI ≥24 kg/m², and frequent alcohol drinking. These findings provided the evidence on elevated risks of morbidity of hypertension and diabetes associated with prolonged ambient pollutants exposure at relatively high levels.

Associations between seasonal ambient air pollution and adverse perinatal outcomes: a retrospective cohort study in Wenzhou, China

Prenatal exposure to ambient air pollution has been associated with adverse perinatal outcomes in previous studies. However, few studies have examined the interaction between air pollution and the season of conception on term low birth weight (TLBW) or macrosomia. Birth registry data of singleton live births in Wenzhou, China, between January 2015 and December 2016 were accessed from the Wenzhou Maternal and Child Health Information Management platform, and data on the ambient air pollutants in Wenzhou were obtained from the Chinese Air Quality Online Monitoring and Analysis Platform. Single-/two-pollutant binary logistic regression models were used to assess the associations between ambient air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, and O₃) and TLBW/macrosomia, further exploring whether the season of conception interacts with air pollution to impact birth weight. Finally, 213,959 term newborns were selected, including 2452 (1.1%) infants with TLBW and 13,173 (6.1%) infants with macrosomia. In the single-/two-pollutant models, we observed an increased risk of TLBW associated with maternal exposure to PM_2.5, PM₁₀, SO₂, and NO₂ during the entire pregnancy, especially in the 2nd trimester. Maternal exposure to O₃ during the 1st trimester was associated with increased macrosomia risk, and O₃ exposure during the 3rd trimester was associated with increased TLBW risk. Pregnant women who conceive in the warm season may experience a more adverse ambient air environment that is related to the risks of TLBW. These findings add to the evidence suggesting that air pollution and the season of conception may have synergistic effects on adverse perinatal outcomes, especially TLBW. Further prospective cohort studies are needed to validate our results.

Associations of Ambient Fine Particulate Matter and Its Chemical Constituents with Birth Weight for Gestational Age in China: A Nationwide Survey

This study examined the associations of fine particulate matter (PM_2.5) and its chemical constituents with risks of small for gestational age (SGA) and large for gestational age (LGA). Based on the China Labor and Delivery Survey, we included 70,206 birth records from 24 provinces in China. Concentrations of PM_2.5 mass and six main constituents were estimated using satellite-based models. Logistic regression analysis was used to examine the associations, adjusted for sociodemographic characteristics and time trends. We found that an interquartile range increase in PM_2.5 exposure during pregnancy was associated with 16% (95% confidence interval [CI]: 3-30%) and 11% (95% CI: 1-22%) higher risk of SGA and LGA, respectively. Elevated risk of SGA was associated with exposure to black carbon [odds ratio (OR) = 1.15, 95% CI: 1.00-1.32], ammonium (OR = 1.12, 95% CI: 1.01-1.25), and sulfate (OR = 1.12, 95% CI: 1.04-1.21); while increased risk of LGA was associated with exposure to black carbon (OR = 1.13, 95% CI: 1.02-1.26), ammonium (OR = 1.13, 95% CI: 1.03-1.24), sulfate (OR = 1.08, 95% CI: 1.01-1.15), and nitrate (OR = 1.14, 95% CI: 1.03-1.27). Our findings provide evidence that PM_2.5 exposure was associated with increased risks of SGA and LGA, and constituents related to emissions from anthropogenic sources may play important roles in these associations.

Recent Insights into Particulate Matter (PM2.5)-Mediated Toxicity in Humans: An Overview

Several epidemiologic and toxicological studies have commonly viewed ambient fine particulate matter (PM_2.5), defined as particles having an aerodynamic diameter of less than 2.5 µm, as a significant potential danger to human health. PM_2.5 is mostly absorbed through the respiratory system, where it can infiltrate the lung alveoli and reach the bloodstream. In the respiratory system, reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress stimulate the generation of mediators of pulmonary inflammation and begin or promote numerous illnesses. According to the most recent data, fine particulate matter, or PM_2.5, is responsible for nearly 4 million deaths globally from cardiopulmonary illnesses such as heart disease, respiratory infections, chronic lung disease, cancers, preterm births, and other illnesses. There has been increased worry in recent years about the negative impacts of this worldwide danger. The causal associations between PM_2.5 and human health, the toxic effects and potential mechanisms of PM_2.5, and molecular pathways have been described in this review.

Preconception TSH and Adverse Pregnancy Outcomes in China: A Nationwide Prospective Cohort Study

BACKGROUND

The relationship between maternal thyroid function and pregnancy outcomes remains controversial and the safe range of TSH is still unclear in women planning pregnancy.

METHODS

This population-based cohort study enrolled Chinese women who became pregnant in 30 provinces from 2010 to 2012 from the National Free Preconception Checkups Project. The maternal TSH level within 6 months before pregnancy and different pregnancy outcomes were collected and analyzed using restricted cubic spline regression model for dose-response relationship and potential optimal cutoff values. Logistic regression was used to reveal the relationship between different TSH groups and the risk of adverse outcomes.

RESULTS

Among 175 112 women, a J-shaped association was revealed between TSH and large for gestational age (LGA; P < 0.001). When TSH was lower than 1.27 or 0.91 mIU/L, lower TSH was associated with higher odds ratio of low birth weight (LBW; P = 0.003) or preterm delivery (P < 0.001). There was no significant association of preconception TSH with SGA, macrosomia, fetal anomalies, stillbirth, natural or induced abortion, and cesarean delivery. The range of TSH for odds ratio lower than 1.0 was within 0.91 to 1.82 mIU/L in dose-response association. Compared with TSH 0.91 to 1.82 mIU/L, TSH low (< 0.40 mIU/L and 0.40-0.90 mIU/L) and high (1.83-2.49 mIU/L, 2.50-3.99 mIU/L, and >4.00 mIU/L) were associated with higher risk of preterm delivery and LGA. There was no significant association between TSH groups and the risk of LBW except for TSH < 0.40 mIU/L.

CONCLUSION

Preconception TSH was associated with preterm delivery, LGA, and LBW. Preconception TSH had a bidirectional effect on LGA, indicating a potential mechanism regarding influence of TSH on birth weight. TSH within 0.91 to 1.82 mIU/L was the potential safe range for preconception women.

High Maternal Triglyceride Levels Mediate the Association between Pre-Pregnancy Overweight/Obesity and Macrosomia among Singleton Term Non-Diabetic Pregnancies: A Prospective Cohort Study in Central China

This study aimed at examining the risk of macrosomia, in relation to maternal pre-pregnancy overweight/obesity mediated via high maternal triglyceride (mTG) levels. In this prospective study, 24,730 singleton term non-diabetic pregnancies were finally included. Serum mTG levels were measured using fasting blood samples that were collected after 28 weeks of gestation. High mTG levels were defined as values ≥ the 90th percentile. The outcome of interest was macrosomia (≥4000 g). Log-binomial regression was used to assess the mediation path between overweight/obesity, high mTG levels, and macrosomia. The mediation analysis found a total effect of overweight on macrosomia of 0.006 (95% CI, 0.001–0.010), including a direct effect of 0.005 (95% CI, 0.001, 0.009) and indirect effect of 0.001 (95% CI, 0.000–0.001), with an estimated proportion of 11.1% mediated by high mTG levels. Additionally, we also found a total effect of obesity on macrosomia of 0.026 (95% CI, 0.018–0.036), including a direct effect of 0.025 (95% CI, 0.017–0.036) and indirect effect of 0.001 (95% CI, 0.000–0.001), with an estimated proportion of 3.8% mediated by high mTG levels. In conclusion, non-diabetic women with overweight or obesity had an increased risk of macrosomia, and this positive association was partly mediated by high mTG levels.

Identifying Sensitive Windows of Exposure to NO2 and Fetal Growth Trajectories in a Spanish Birth Cohort

BACKGROUND

We previously identified associations between trimester-specific NO2 exposures and reduced fetal growth in the Spanish INfancia y Medio Ambiente (INMA) project. Here, we use temporally refined exposure estimates to explore the impact of narrow (weekly) windows of exposure on fetal growth.

METHODS

We included 1,685 women from INMA with serial ultrasounds at 12, 20, and 34 gestational weeks. We measured biparietal diameter (BPD), femur length, and abdominal circumference (AC) and from them calculated estimated fetal weight (EFW). We calculated z-scores describing trajectories of each parameter during early (0-12 weeks), mid (12-20 weeks), and late (20-34 weeks) pregnancy, based on longitudinal growth curves from mixed-effects models. We estimated weekly NO2 exposures at each woman's residence using land-use regression models. We applied distributed lag nonlinear models to identify sensitive windows of exposure. We present effect estimates as the percentage change in fetal growth per 10 μg/m3 increase in NO2 exposure, and we calculated cumulative effect estimates by aggregating estimates across adjacent lags.

RESULTS

We identified weeks 5-12 as a sensitive window for NO2 exposure on late EFW (cumulative β = -3.0%; 95% CI = -4.1%, -1.9%). We identified weeks 6-19 as a sensitive window for late growth in BPD (cumulative β = -2.0%; 95% CI = -2.7%, -1.4%) and weeks 8-13 for AC (cumulative β = -0.68%; 95% CI = -0.97%, -0.40%). We found suggestive evidence that third trimester NO2 exposure is associated with increased AC, BPD, and EFW growth in late pregnancy.

CONCLUSIONS

Our findings are consistent with the hypothesis that NO2 exposure is associated with alterations in growth of EFW, BPD, and AC dependent on the specific timing of exposure during gestation.

Prenatal exposure to air pollution and the risk of macrosomia: Identifying windows of susceptibility

This study explores the effects of prenatal exposure to air pollution on the risk of macrosomia and its window of susceptibility. We conducted a retrospective cohort study utilizing records of birth certificates for all full-term live newborns born in Xi'an city, China from January 1, 2015, to December 31, 2018.Weekly- and trimester-specific exposures of PM_2.5, PM₁₀, NO₂, and O₃ during pregnancy were calculated by inverse distance weighting (IDW) based on their residences. Cox proportional hazard model and distributed lag models (DLMs) were performed to estimate the effects of air pollution exposure during pregnancy on macrosomia risk and its window of susceptibility. In total, 318,323 full-term newborns were identified, including 24,996 (7.8%) cases of macrosomia. An IQR increase in PM_2.5 exposure (45.46 μg/m³) from the 33rd until the 37th weeks of gestation was positively associated with an elevated risk of macrosomia, with the strongest effect in the 37th weeks (HR = 1.007, 95%CI: 1.002-1.013). The window of susceptibility for NO₂ exposure on macrosomia risk was in the 29th-35th gestational weeks, with the strongest effect in the 34th weeks (IQR = 21.96 μg/m³, HR = 1.006, 95%CI:1.000-1.013). For prenatal exposure to O₃, 5th-24th weeks of gestation was identified as susceptible windows for elevated risk of macrosomia, with the strongest associations observed in the 15th weeks (IQR = 80.53 μg/m³, HR = 1.022, 95%CI: 1.011-1.033). However, we did not observe any associations between weekly exposure of PM₁₀ and macrosomia. Our findings imply that the windows of susceptibility to PM_2.5 and NO₂ exposure on macrosomia are mainly in late pregnancy, whereas the windows of susceptibility to O₃ exposure are in early and middle pregnancy.

The Impact of PM2.5 on the Growth Curves of Children's Obesity Indexes: A Prospective Cohort Study

Aims

To explore the effect of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on childhood obesity based on a cohort study in Chongqing.

Methods

A total of 4,284 children aged 6-8 years at baseline were enrolled from the Chongqing Children Health Cohort in 2014-2015 and were followed up in 2019. A stratified cluster sampling was applied to select the participants. A Mixed-effects linear regression model was used to examine the effect of long-term exposure to PM2.5 on the growth curve of obesity indicators [including body mass index (BMI), BMI Z-score (BMIz), and waist-to-height ratio (WHtR)]. A mixed-effects logistic regression model was used to study the dose relationship between PM2.5 exposure and the risk of obesity indicators.

Results

A higher level of accumulating exposure to PM2.5 was associated with an increased childhood obesity index, and the effect was the most significant for WHtR than BMI and BMIz. This effect was more pronounced in boys than in girls except for WHtR, and it was the most significant under the PM2.5 exposure period from pregnancy to 6 years old. Compared the annual average PM2.5 exposure level of <60 μg/m³, the WHtR and BMI were increased by 0.019 [(95% CIs): 0.014, 0.024] and 0.326 [(95% CIs): 0.037, 0.616] Kg/m² for participants living with the PM2.5 exposure level of 70-75 μg/m³, respectively. For every 5 μg/m³ increase in PM2.5 levels (from pregnancy to 6 years old), the risk of central obesity was increased by 1.26 {odds ratio [OR] (95% CIs): 1.26 (1.16, 1.37), p < 0.001} times.

Conclusions

This study confirmed a dose-response relationship between PM2.5 exposure and childhood obesity, especially central obesity, suggesting that controlling ambient air pollution can prevent the occurrence of obesity in children and adolescents.

Interaction of PM2.5 and pre-pregnancy body mass index on birth weight: A nationwide prospective cohort study

BACKGROUND

Fine particulate matter (PM_2.5), one of the most common air pollutants worldwide, has been associated with many adverse birth outcomes in some studies. Pre-pregnancy body mass index (BMI) is an important indicator of maternal obesity that may also contribute to a wide range of birthweight outcomes. Both PM_2.5 and maternal obesity have been found associated with issues on neonatal birthweight respectively, and more attentions and interests are focusing on their combined effect on pregnancy outcomes.

PURPOSE

To explore the modifying effect of pre-pregnancy BMI on the association between gestational PM_2.5 and birthweight; to investigate the interactive effect between gestational PM_2.5 and pre-pregnancy BMI on birthweight among pregnant women during three trimesters and the whole pregnancy.

METHODS

This nationwide cohort study used the National Free Preconception Health Examination Project (NFPHEP) data collected from January 1, 2010, to December 31, 2012. A total population of 248,501 Chinese women from 220 counties registered this project. Pre-pregnancy BMI as a common anthropometric examination was collected during preconception investigation, and gestational PM_2.5 was derived from a hindcast model for historical PM_2.5 estimation from satellite-retrieved aerosol optic depth. Subgroup analysis was conducted to explore a potential modifying effect on the association between PM_2.5 and birthweight during pregnancy by four pre-pregnancy BMI subgroups. Interaction analysis by introducing product terms to multivariable linear regression was also used to examine whether there was an interactive relationship between PM_2.5 and pre-pregnancy BMI.

RESULTS

Totally, 193,461 participants were included in our study. The average concentration of PM_2.5 was 75.33 μg/m³. Higher exposure of PM_2.5 during the entire pregnancy was associated with higher birthweight (17.15 g per 10 μg/m3; 95% CI:16.15, 18.17). Each 10 μg/m³ increase in PM_2.5 during the first, second, and third trimesters was associated with increases in birthweight by 14.93 g (95%CI: 13.96, 15.89), 13.75 g (95% CI: 12.81, 14.69), and 8.79 g (95% CI: 8.09, 9.49), respectively. Higher pre-pregnancy BMI per kg/m² was associated with an increase of birthweight by 7.012 g (95% CI: 6.121, 7.902). Product terms between PM_2.5 and pre-pregnancy BMI were significant for the first, second trimesters, and the entire duration of pregnancy.

CONCLUSIONS

Our results found both gestational PM_2.5 exposure and pre-pregnancy BMI respectively correlated with the increase of birthweight. A negative interaction between pre-pregnancy BMI and gestational PM_2.5 was discovered in term of birthweight gain. Avoidance of high-dose exposure to PM_2.5 during the early and middle stages of pregnancy and pre-pregnancy overweight/obesity may help prevent high birthweight.

Prenatal air pollution exposure increases the risk of macrosomia: evidence from a prospective cohort study in the coastal area of China

Effects of prenatal ambient air pollution exposure could increase the risk of adverse pregnancy outcomes, which have been well documented by various studies. However, only very few studies investigated the effects on macrosomia. This study investigated the effects of prenatal air pollution exposure on the risk of macrosomia in a coastal city of China. Data of birth outcomes and air pollution in a coastal city in China between November 1, 2013, and December 31, 2017, were collected. Finally, 58,713 eligible births, including 8159 (13.9%) macrosomia and 50554 (86.1%) normal birth weight (NBW) infants, were included in the analysis. Logistic regression analyses were used to evaluate the effects of prenatal air pollution exposure on macrosomia. In the single-pollutant models, each 10 μg/m³ increase of PM_2.5, PM₁₀, and SO₂ exposures, during the entire pregnancy or three trimesters, were related to elevated risk of macrosomia (adjusted RR, 95% CI) ranging from 1.018 (1.001, 1.035) to 1.314 (1.188, 1.454). In addition, O₃ exposure in the first trimester (adjusted RR =1.034, 95% CI 1.009, 1.059) also increased the macrosomia risk. Prenatal PM_2.5, PM₁₀, and SO₂ exposure could significantly increase the risk of macrosomia. These findings need to be further verified in more studies with multiple coastal cities included.

Maternal Secondhand Smoke Exposure Enhances Macrosomia Risk Among Pregnant Women Exposed to PM2.5: A New Interaction of Two Air Pollutants in a Nationwide Cohort

Background: Fine particulate matter (PM_2.5) is one of the most common outdoor air pollutants, and secondhand smoking (SHS) is an important source of inhalable indoor air pollution. Previous studies were controversial and inconsistent about PM_2.5 and SHS air pollutants on neonatal birth weight outcomes, and no studies assessed the potential interactive effects between PM_2.5 and SHS on birth weight outcomes. Purpose: To investigate the interaction between gestational PM_2.5 and SHS air pollution exposure on the risk of macrosomia among pregnant women and examine the modifying effect of SHS exposure on the association of PM_2.5 air pollution and birth weight outcomes during pregnancy. Methods: Research data were derived from the National Free Preconception Health Examination Project (NFPHEP), which lasted 3 years from January 1, 2010, to December 31, 2012. At least 240,000 Chinese women from 220 counties were enrolled in this project. PM_2.5 exposure concentration was obtained using a hindcast model specific for historical PM_2.5 estimation from satellite-retrieved aerosol optic depth. Different interaction models about air pollution exposure on birth weight outcomes were established, according to the adjustment of different confounding factors and different pregnancy stages. The establishment of interaction models was based on multivariable logistic regression, and the main confounding factors were maternal age at delivery and pre-pregnancy body mass index (BMI) of participants. SHS subgroups analysis was conducted to further confirm the results of interaction models. Results: In total, 197,877 participants were included in our study. In the full-adjusted interaction model, maternal exposure to PM_2.5 was associated with an increased risk of macrosomia in whole, the first-, second-, and third trimesters of pregnancy (p < 0.001). The interactive effect was statistically significant between maternal exposure to PM_2.5 and SHS on the risk of macrosomia in the whole (interaction p < 0.050) and the first-trimester pregnancy (interaction p < 0.050), not in the second (interaction p > 0.050) or third trimester (interaction p > 0.050) of pregnancy. The higher frequency of SHS exposure prompted the stronger interaction between the two air pollutants in the whole pregnancy and the first-trimester pregnancy. Conclusions: In the whole and first-trimester pregnancy, maternal exposure to SHS during pregnancy enhanced the risk of macrosomia among pregnant women exposed to PM_2.5 air pollutants, and the interaction became stronger with the higher frequency of SHS exposure.

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.

Prenatal exposure to residential PM2.5 and its chemical constituents and weight in preschool children: A longitudinal study from Shanghai, China

BACKGROUND

Studies have reported that prenatal exposure to fine particulate matter (PM_2.5) might be associated with adverse birth outcomes in offspring. However, evidence with regard to the effects of prenatal exposure to PM_2.5 and, especially, its main chemical constituents on offspring's weight in childhood is limited and inconsistent.

OBJECTIVES

The present study aimed to examine associations of prenatal exposure to PM_2.5 total mass and its chemical constituents in each trimester with children's weight from birth to 6 years of age using data from Shanghai-Minhang Birth Cohort Study.

METHODS

A total of 1,084 mother-infant pairs were included with both PM_2.5 exposure data and at least one measurement of weight and height. Weight-for-Length (WLZ), BMI-for-Age (BMIz), and Weight-for-Age (WAZ) z-scores were generated according to the World Health Organization guidelines. Exposure to PM_2.5 total mass and its chemical constituents [organic carbon (OC), black carbon (BC), ammonium (NH₄⁺), nitrate (NO₃^-), sulfate (SO₄^2-), and soil dust (SOIL)] during pregnancy was estimated from a satellite based modelling framework. We used multiple informant model to estimate the associations of trimester-specific PM_2.5 total mass and its specific constituents concentrations with WLZ/BMIz and WAZ of offspring at birth and 1, 4, and 6 years of age.

RESULTS

In multiple informant model, we observed consistent patterns of associations between exposure to PM_2.5 total mass, OC, BC, NH₄⁺, NO₃^-, and SO₄^2- during the 2^nd and 3^rd trimesters and decreased WLZ/BMIz and WAZ at 1, 4, and 6 years of age in boys. We observed associations between prenatal exposure to PM_2.5 total mass, NH₄⁺, and NO₃^- during the 1^st and 2^nd trimesters and increased WLZ/BMIz and WAZ in girls at birth. However, there were null associations at 1 and 4 years of age and inverse associations at 6 years of age.

CONCLUSIONS

Prenatal exposure to PM_2.5 total mass and its main chemical constituents was associated with decreased weight in boys from 1 to 6 years of age, with increased weight at birth and decreased weight at 6 years of age in girls. Our findings suggest that prenatal exposure to PM_2.5 and its chemical constituents may have a lasting effect on offspring's weight in childhood.

Could Subtle Obstetrical Brachial Plexus Palsy Be Related to Unilateral B Glenoid Osteoarthritis?

Background: Several factors associated with B glenoid are also linked with obstetrical brachial plexus palsy (OBPP). The purpose of this observational study was to determine the incidence of OBPP risk factors in type B patients. Methods: A cohort of 154 patients (68% men, 187 shoulders) aged 63 ± 17 years with type B glenoids completed a questionnaire comprising history of perinatal characteristics related to OBPP. A literature review was performed following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) to estimate the incidence of OBPP risk factors in the general population. Results: Twenty-seven patients (18%) reported one or more perinatal OBPP risk factors, including shoulder dystocia (n = 4, 2.6%), macrosomia >4 kg (n = 5, 3.2%), breech delivery (n = 6, 3.9%), fetal distress (n = 8, 5.2%), maternal diabetes (n = 2, 1.3%), clavicular fracture (n = 2, 1.3%), and forceps delivery (n = 4, 2.6%). The comparison with the recent literature suggested that most perinatal OBPP risk factors were within the normal range, although the incidence of shoulder dystocia, forceps and vaginal breech deliveries exceeded the average rates. Conclusion: Perinatal factors related to OBPP did not occur in a higher frequency in patients with Walch type B OA compared to the general population, although some of them were in the high normal range.

The Role of Maternal Weight in the Hierarchy of Macrosomia Predictors; Overall Effect of Analysis of Three Prediction Indicators

So far it has not been established which maternal features play the most important role in newborn macrosomia. The aim of this study is to provide assessment of a hierarchy of twenty six (26) maternal characteristics in macrosomia prediction. A Polish prospective cohort of women with singleton pregnancy (N = 912) which was recruited in the years 2015–2016 has been studied. Two analyses were performed: for probability of macrosomia > 4000 g (n = 97) (vs. 755 newborns 2500–4000 g); and for birthweight > 90th percentile (n = 99) (vs. 741 newborns 10–90th percentile). A multiple logistic regression was used (with 95% confidence intervals (CI)). A hierarchy of significance of potential predictors was established after summing up of three prediction indicators (NRI, IDI and AUC) calculated for the basic prediction model (maternal age + parity) extended with one (test) predictor. ‘Net reclassification improvement’ (NRI) focuses on the reclassification table describing the number of women in whom an upward or downward shift in the disease probability value occurred after a new factor had been added, including the results for healthy and ill women. ‘Integrated discrimination improvement’ (IDI) shows the difference between the value of mean change in predicted probability between the group of ill and healthy women when a new factor is added to the model. The area under curve (AUC) is a commonly used indicator. Results. The macrosomia risk was the highest for prior macrosomia (AOR = 7.53, 95%CI: 3.15–18.00, p < 0.001). A few maternal characteristics were associated with more than three times higher macrosomia odds ratios, e.g., maternal obesity and gestational age ≥ 38 weeks. A different hierarchy was shown by the prediction study. Compared to the basic prediction model (AUC = 0.564 (0.501–0.627), p = 0.04), AUC increased most when pre-pregnancy weight (kg) was added to the base model (AUC = 0.706 (0.649–0.764), p < 0.001). The values of IDI and NRI were also the highest for the model with maternal weight (IDI = 0.061 (0.039–0.083), p < 0.001), and (NRI = 0.538 (0.33–0.746), p < 0.001). Adding another factor to the base model was connected with significantly weaker prediction, e.g., for gestational age ≥ 38 weeks (AUC = 0.602 (0.543–0.662), p = 0.001), (IDI = 0.009 (0.004; 0.013), p < 0.001), and (NRI = 0.155 (0.073; 0.237), p < 0.001). After summing up the effects of NRI, IDI and AUC, the probability of macrosomia was most strongly improved (in order) by: pre-pregnancy weight, body mass index (BMI), excessive gestational weight gain (GWG) and BMI ≥ 25 kg/m². Maternal height, prior macrosomia, fetal sex-son, and gestational diabetes mellitus (GDM) occupied an intermediate place in the hierarchy. The main conclusions: newer prediction indicators showed that (among 26 features) excessive pre-pregnancy weight/BMI and excessive GWG played a much more important role in macrosomia prediction than other maternal characteristics. These indicators more strongly highlighted the differences between predictors than the results of commonly used odds ratios.

The Xi'an longitudinal mother-child cohort study: design, study population and methods

The large-scale Xi'an longitudinal mother-child cohort study has started to enroll pregnant women who attended Northwest Women's and Children's Hospital (NWCH) for antenatal care in early pregnancy (less than 20 weeks' gestation) from January 2013 and the enrollment will be ended in January 2023. We aimed to investigate the role of external factors (i.e., diet and environment) and internal (i.e., biological, genetic and epigenetic) on the short- and long-term outcomes of mothers and children up to at least 12 years. Mothers completed all routine prenatal care during pregnancy and four times of follow-up at 42 days, 3, 6 and 12 years after delivery, respectively. For children, birth information were obtained from routine medical records and the follow-up information were obtained from child health care clinics of NWCH at age 42 days, 6, 12 and 24 months, then by interviewing mothers every two years until 12 years old. A range of data (including biological, demographic, birth outcomes/birth defects and nutritional factors from both maternal and off-spring) were collected by both interviews and laboratory tests. By June 30th 2019, a total of 114,946 mothers and 124,454 live births had been recruited.

Impact of air pollution exposure during various periods of pregnancy on term birth weight: a large-sample, retrospective population-based cohort study

Previous studies have suggested that maternal exposure to air pollution might affect term birth weight. However, the conclusions are controversial. Birth data of all term newborns born in Xi'an city of Shaanxi, China, from 2015 to 2018 and whose mother lived in Xi'an during pregnancy were selected form the Birth Registry Database. And the daily air quality data of Xi'an city was collected from Chinese Air Quality Online Monitoring and Analysis Platform. Generalized additive models (GAM) and 2-level binary logistic regression models were used to estimate the effects of air pollution exposure on term birth weight, the risk term low birth weight (TLBW), and macrosomia. Finally, 321521 term newborns were selected, including 4369(1.36%) TLBW infants and 24,960 (7.76%) macrosomia. The average pollution levels of PM_2.5, PM₁₀, and NO₂ in Xi'an city from 2015 to 2018 were higher than national limits. During the whole pregnancy, maternal exposure to PM_2.5, PM₁₀, SO₂, and CO all significantly reduced the term birth weight and increased the risk of TLBW. However, NO₂ and O₃ exposure have significantly increased the term birth weight, and O₃ even increased the risk of macrosomia significantly. Those effects were also observed in the first and second trimesters of pregnancy. But during the third trimester, high level of air quality index (AQI) and maternal exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO increased the term birth weight and the risk of macrosomia, while O₃ exposure was contrary to this effect. The findings suggested that prenatal exposure to air pollution might cause adverse impacts on term birth weight, and the effects varied with trimesters and pollutants, which provides further pieces of evidence for the adverse effects of air pollution exposure in heavy polluted-area on term birth weight.

Changing trends of birth weight with maternal age: a cross-sectional study in Xi'an city of Northwestern China

BACKGROUND

Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight.

METHODS

Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi'an, China. A total of 490,143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, neonatal birth date, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia.

RESULTS

The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age was less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051 g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824 g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR = 0.917, 95%CI: 0.903, 0.932 when maternal age was younger than 27 years old; OR = 0.965, 95%CI: 0.955, 0.976 when maternal age ranged from 27 to 36 years old), then increased when maternal age was older than 36 years old (OR = 1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR = 1.102, 95%CI: 1.075, 1.129 when maternal age was younger than 24 years old; OR = 1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR = 1.029, 95%CI: 1.012, 1.046 when maternal age was older than 33 years old).

CONCLUSIONS

For women of childbearing age (20-40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

The mediation effect of maternal glucose on the association between ambient air pollution and birth weight in Foshan, China

Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, China during 2015-2019 were recruited. Oral glucose tolerance test (OGTT) was administered to each participant after late trimester 2. Air pollution data at the monitoring stations in residential districts was used to estimate exposures of each participant during trimester 1 and trimester 2. Mixed-effects linear models were used to estimate the associations between air pollution and birth weight. After controlling for ten covariates, the direct effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight was -15.7 g (95% CI: -29.4, -4.8 g) and -83.6 g (95% CI: -134.8, -33.0 g) during trimester 1. The indirect effect of PM_2.5 and SO₂ (each 10 μg/m³ increment) on birth weight by increasing maternal fasting glucose level was 6.6 g (95% CI: 4.6, 9.1 g) and 22.0 g (95% CI: 4.1, 44.0 g) during trimester 1. Our findings suggest that air pollution might affect the birth weight through direct and indirect pathway, and the indirect effect might be mediated by maternal blood glucose.

Earth Observation Data Supporting Non-Communicable Disease Research: A Review

A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.