Prenatal and postnatal exposure to heavy metals in PM2.5 and autism spectrum disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders, and its incidence is increasing over time. Although several environmental factors have been suspected to be risk factors for ASD, studies on the effects of airborne heavy metals on newly developed ASD are still limited. We conducted a large birth cohort study of 168,062 live term births in Taichung during 2004-2011 to assess the association of heavy metals in particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) with ASD, and identify sensitive time windows during prenatal and postnatal periods. Heavy metals, including arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) in PM2.5, were estimated using the Weather Research and Forecasting/Chem (WRF/Chem), inserted from the top 75 emission sources for the module. The association between childhood ASD and 4 metals were analyzed from pregnancy to 9 months after birth. The Cox proportional hazard model with a distributed lag nonlinear model (DLNM) was used to estimate the association between heavy metals in PM2.5 and ASD. We identified 666 incident ASD cases in 168,062 participants. A positive association between Hg and ASD was found at 9 months after birth (Hazard Ratio: 1.63; 95% CI: 1.13-2.36). According to the DLNM, there was an increased risk of exposure to Hg during 10-25 weeks after birth, and decreased risk of exposure to Hg during gestational weeks 4-6. Exposure to As and Hg on the risk of ASD were significantly stronger in low birth weight infants (<2500 g) than in those of birth weight ≥2500 g during postnatal period. Postnatal exposure to Hg in PM2.5 may associate with increased ASD incidence. Infants with low birth weight and exposure to As and Hg in PM2.5 are more likely to develop ASD.

Multiple exposures to heavy metals and changes in steroid hormones production in 4-year-old children

BACKGROUND

Prenatal exposure to multiple heavy metals can interfere with early neurodevelopment, lead to changes in sex hormone concentrations in children, and affect female reproductive health. To date, the influence of prenatal exposure to heavy metals on the endocrine system of children in Chinese electronic waste (e-waste) recycling areas has not been elucidated.

METHODS

Four weeks after delivery, 10 mL of human milk was collected for analysis of three heavy metals (lead (Pb), cadmium (Cd), and mercury (Hg)) via inductively coupled plasma mass spectrometry (ICP-MS). Four serum steroid hormones, including progesterone, testosterone, androstenedione (A-dione), and dehydroepiandrosterone (DHEA), were analyzed in 4-year-old children (25 boys and 17 girls). A multiple linear regression (MLR) model was implemented to investigate the association between each individual metal and serum steroid hormone. The exposure-response relationships were explored by generalized additive models (GAMs). Additionally, a Bayesian kernel machine regression (BKMR) model was used to assess the effects of multiple heavy metal exposures on each steroid hormone.

RESULTS

The MLR results show a significant positive association between a natural log unit increase in Hg and DHEA levels after adjusting for confounders (β = 65.50, 95% confidence interval (CI) = 4.37, 126.62). According to the GAM, the univariate exposure-response relationship of Hg on DHEA was almost linear. However, this association was attenuated based on the multiple metal MLR and BKMR results after accounting for multiple heavy metal exposures.

SIGNIFICANCE

Prenatal Hg exposure may affect sex hormones in children by affecting DHEA levels.

IMPACT STATEMENT

Prenatal maternal exposure to Hg may have long-term effects on the next generation. Hence, regulatory measures to reduce Hg exposure and long-term monitoring of children's health in e-waste areas are needed.

Maternal exposure to fine particulate matter and congenital heart defects during preconception and pregnancy period: A cohort-based case-control study in the Taiwan maternal and child health database

BACKGROUND

Few studies have explored the association between maternal exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5) and congenital heart defects occurring before and during pregnancy. We aimed to investigate the association and the critical time windows between the maternal exposure to PM2.5 and congenital heart defects.

METHOD

We conducted a cohort-based case-control study of 507,960 participants obtained from the Taiwan Maternal and Child Health Database between 2004 and 2015. We applied satellite-based spatiotemporal models with 1-km resolution to calculate the average PM2.5 concentration during preconception and the specific periods of pregnancy. We also performed conditional logistic regression with distributed lag non-linear models (DLNMs) to assess the effects of weekly average PM2.5 on both congenital heart defects and their isolated subtypes, as well as the concentration-response relationships.

RESULTS

In DLNMs, exposure to PM2.5 (per 10 μg/m3) during weeks 7-12 before conception and weeks 3-9 after conception was associated with congenital heart defects. The strongest association at 12 weeks before conception (odds ratio [OR] = 1.026, 95% confidence intervals [CI]: 1.012-1.040) and 7 weeks after conception (OR = 1.024, 95% CI: 1.012-1.036) for every 10 μg/m3 increase in PM2.5 concentration. In modification analysis, strongest associations were observed for low SES.

CONCLUSIONS

Our study revealed that exposure to ambient PM2.5 raises the risk of congenital heart defects, particularly among individuals with lower socioeconomic status. Moreover, our findings suggest that preconception exposure to PM2.5 may be a crucial period for the development of congenital heart defects.

Short-term association of air pollution with lung cancer mortality in Osaka, Japan

Long-term air pollution exposure has been linked to increased lung cancer mortality. However, little is known about whether day-to-day fluctuations in air pollution levels are in relation to lung cancer mortality, particularly in low-exposure settings. This study aimed to evaluate the short-term associations between air pollution and lung cancer mortality. Daily data on lung cancer mortality, fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and weather conditions were collected from Osaka Prefecture, Japan, from 2010 to 2014. Generalized linear models were combined with quasi-Poisson regression were applied to evaluate the associations between each air pollutant and lung cancer mortality after adjusting for potential confounders. Mean (standard deviation) concentrations of PM_2.5, NO₂, SO₂, and CO were 16.7 (8.6) μg/m³, 36.8 (14.2) μg/m³, 11.1 (4.0) μg/m³, and 0.51 (0.16) mg/m³, respectively. Interquartile range increases in concentrations of PM_2.5, NO₂, SO₂, and CO (2-d moving average) were associated with 2.65% (95% confidence intervals [CIs]: 0.96%-4.37%), 4.28% (95% CIs: 2.24%-6.36%), 3.35% (95% CIs: 1.03%-5.73%), and 4.60% (95% CIs: 2.19%-7.05%) increased risk of lung cancer mortality, respectively. Stratified analyses showed that the associations were strongest in the older population and men. Exposure‒response curves showed a continuously increasing mortality risk from lung cancer with elevation of air pollution levels, without discernible thresholds. In summary, we found evidence of increased lung cancer mortality in relation to short-term elevations in ambient air pollution. These findings may merit further research to better understand this issue.

A hybrid model for estimating the number concentration of ultrafine particles based on machine learning algorithms in central Taiwan

Modeling is a cost-effective measure to estimate ultrafine particle (UFP) levels. Previous UFP estimates generally relied on land-use regression with insufficient temporal resolution. We carried out in-situ measurements for UFP in central Taiwan and developed a model incorporating satellite-based measurements, meteorological variables, and land-use data to estimate daily UFP levels at a 1-km resolution. Two sampling campaigns were conducted for measuring hourly UFP concentrations at six sites between 2008-2010 and 2017-2021, respectively, using scanning mobility particle sizers. Three machine learning algorithms, namely random forest, eXtreme gradient boosting (XGBoost), and deep neural network, were used to develop UFP estimation models. The performances were evaluated with a 10-fold cross-validation, temporal, and spatial validation. A total of 1,022 effective sampling days were conducted. The XGBoost model had the best performance with a training coefficient of determination (R²) of 0.99 [normalized root mean square error (nRMSE): 6.52%] and a cross-validation R² of 0.78 (nRMSE: 31.0%). The ten most important variables were surface pressure, distance to the nearest road, temperature, calendar year, day of the year, NO₂, meridional wind, the total length of roads, PM_2.5, and zonal wind. The UFP levels were elevated along the main roads across different seasons, suggesting that traffic emission is an important contributor to UFP. This hybrid model outperformed prior land use regression models and thus can provide more accurate estimates of UFP for epidemiological studies.

Prenatal and postnatal exposure to PM2 .5 and the risk of tic disorders

BACKGROUND

Tic disorders are common neurodevelopmental disorders during childhood. Whether prenatal and postnatal exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5 ) plays a role in the development of tic disorders remains unexplored.

OBJECTIVES

To investigate the association of exposure between PM_2.5 during the pregnancy and infancy periods and the risk of tic disorders.

METHODS

This birth cohort study recruited singleton live births at term gestations in central Taiwan from the Taiwan Maternal and Child Health Database between 2004 and 2012 and followed up to the end of 2017. New cases of tic disorders were defined using the ICD-9-CM (307.2) and ICD-10-CM (F95), which include all tic spectrum disorders. We assigned daily PM_2.5 concentrations derived from a satellite-based model to individuals based on maternal residential addresses at delivery. We fit Cox proportional hazard model and distributed lag non-linear model to estimate the associations between PM_2.5 and tic disorders, with hazard ratio (HR) with 95% confidence interval (CI) as the effect measure.

RESULTS

Of the 309,376 singleton live births at term gestations, we identified 5902 (1.9%) tic disorder cases. The HR of tic disorders was positively associated with a 10 μg/m³ increase in PM_2.5 : during pregnancy HR 1.09, 95% CI 1.04, 1.15 and during infancy HR 1.12, 95% CI 1.06, 1.18. The vulnerable time window for infants with increased risk of tic disorders was 6-52 weeks after birth. We observed a nonlinear relationship between PM_2.5 and the risk of tic disorders, with exposure to PM_2.5 between 16 and 64 μg/m³ being associated with the risk of tic disorders. The association was restricted to Tourette's disorder group. Infant sex did not modify these associations.

CONCLUSIONS

Infants delivered at term and exposed to PM2.5 are associated with an increased risk of tic disorders (6-52 weeks). Further studies are needed to confirm these associations.

Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (b_p), air pollutants (PM₁₀, PM_2.5, SO₂, O₃, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and b_p. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s^-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s^-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO₂ sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO₂ sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to b_p increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating b_p. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

Evaluating postnatal exposure to six heavy metals in a Chinese e-waste recycling area

This study is the first to assess postnatal exposure to heavy metals using breast milk in an electronic waste (e-waste) recycling area. From January to April 2021, 102 and 97 breastfeeding women were recruited from an e-waste recycling area and a control area, respectively. Four weeks after delivery, medical staff collected 20 mL of breast milk from each participant. The breast milk was tested for six heavy metals (lead, cadmium, chromium, arsenic, copper, and manganese) using inductively coupled plasma mass spectrometry (ICP-MS). The estimated daily intake (EDI) of infants during breastfeeding was calculated to assess the impact of postnatal exposure to heavy metals on infant health. The concentrations of chromium and lead in the breast milk were significantly higher in the e-waste recycling area than in the control area. Chromium concentrations in breast milk was 34.3%, exceeding the permissible limits set by the World Health Organization (WHO), in the e-waste recycling area, which is 16 times higher than that in the control areas. The EDIs of lead and chromium in the e-waste area were twice as those in the control area. This strongly indicates that the potential impact of postnatal exposure to lead and chromium on infant and child health in e-waste recycling areas cannot be ignored. Infants and children in e-waste recycling areas are at risk of long-term exposure to heavy metals. Therefore, ongoing health monitoring is necessary.

PM2.5 exposure and incident attention-deficit/hyperactivity disorder during the prenatal and postnatal periods: A birth cohort study

Only a few studies have assessed the effects of fine particulate matter (PM_2.5) exposure during the prenatal and postnatal periods on the development of attention-deficit/hyperactivity disorder (ADHD). We investigated the association of exposure to PM_2.5 during pregnancy and early life with ADHD. This birth cohort consisted of 425,736 singleton live-term births between 2004 and 2015 in Taiwan. Daily PM_2.5 concentrations were derived from a 1-km satellite-based estimation model. A time-dependent Cox model was used to assess the effects of PM_2.5 on ADHD during the first, second, and third trimesters and from age 1-5 years after birth. The distributed lag nonlinear model was utilized to explore the dose-response relationship. Total 9,294 children were diagnosed with ADHD during the study period. The hazard ratio (HR) of ADHD was significantly associated with a 10 μg/m³ increase in PM_2.5 during the first trimester (HR = 1.26; 95% confidence interval [CI]: 1.13-1.40) and increased at PM_2.5 over 16 μg/m³. For postnatal periods, the HR of ADHD was significantly associated with increased PM_2.5 at the first to third year of life (HR ranged between 1.40 and 1.87). According to the dose-response relationship of exposure to PM_2.5 at the third year of life, the HR of ADHD was significantly associated with PM_2.5 above 16 μg/m³ and sharply increased as PM_2.5 >50 μg/m³. We did not observe a significant modification of sex on the relation between PM_2.5 and ADHD. Exposure of pregnant women to PM_2.5 above 16 μg/m³ from conception to the early life of their children may increase the risk of ADHD. The government should improve the criteria for air quality control and meet the WHO air quality guidelines to protect pregnant women and children from developing ADHD in the future.

Fine particulate matter measured by satellites predicts the risk of age-related macular degeneration in a longitudinal cohort study

Although studies have revealed that ambient particulate matter (PM) has detrimental effects on the ocular surface, there have been limited reports detailing the effect of ambient PM on the posterior segment of the eye. A large-scale longitudinal cohort study evaluating the association between fine PM, especially PM2.5, and the retina could elucidate the risk of ambient pollutants for retinal diseases. We investigated the association between PM2.5 and the development of age-related macular degeneration (AMD). We conducted a population-based cohort study of 4,284,128 participants in Taiwan between 2001 and 2011. PM2.5 was continuously measured by satellites and subsequently assigned to each geographic district along with its postcode. A time-dependent Cox proportional-hazard model was used to assess the overall effects of average PM2.5. We used distributed lag non-linear models to evaluate the dose-response relationship between PM2.5 and AMD development. The annual mean of PM2.5 exposure was 34.23 ± 7.17 μg/m3. The PM2.5 concentrations were highest in spring, followed by those in winter, autumn, and summer. Twelve thousand ninety-five new AMD cases were reported during the study period. After adjusting for covariates, the AMD risk increased by 19% (95% confidence interval 1.13-1.25) for a 10 μg/m3 PM2.5 increase. The present study demonstrated that chronic exposure to PM2.5 increases the risk of AMD. Almost half of the Taiwanese live in a polluted area where the PM2.5 levels are higher than the World Health Organization recommended air quality guideline of 10 μg/m3 had a 1.4-fold risk, which significantly increases concern about their visual health and social burden.

Relationship between dioxins and steroid hormone in 6-year-olds: A follow-up study in an e-waste region of China

We conducted a follow-up observational study on the effects of dioxin exposure on the synthesis of steroid hormones in infants during the perinatal period. The participants included 42 pairs of mothers and infants that were previously studied in 2015. We analyzed four types of steroid hormones including progesterone, testosterone, androstenedione (A-dione), and dehydroepiandrosterone (DHEA) in the serum samples of 6-year-olds and the concentration of dioxins in breast milk. A multivariate linear regression was performed to associate steroid hormones (dependent variables) and dioxins with the body mass index (BMI), sex, age, and residence of participants (independent variables). The results were reported as β (standardized coefficient) and p-values. We found that dioxins have a significant negative correlation with DHEA and A-dione but no significant relationship with progesterone and testosterone. However, in previous studies, we found that testosterone and progesterone levels were significantly related to dioxins in 4-year-olds. We concluded that dioxins can affect the level of steroid hormones, but their effects fluctuate, and the harm caused by dioxins in children requires further long-term monitoring.

Early life exposure to indoor air pollutants and the risk of neurodevelopmental delays: The Japan Environment and Children's Study

Air pollution has been associated with childhood neurodevelopment. However, the role of indoor air pollution, especially volatile organic compounds (VOCs), on childhood neurodevelopment has been poorly explored to date. We investigated the association between indoor air pollutants and childhood neurodevelopment in 5,017 randomly selected children from the Japan Environment and Children's Study. When the participants reached 1.5 and 3 years of age, they were followed up with home visits and neurodevelopmental tests using the Ages and Stages Questionnaire (ASQ). At both ages, we collected indoor air samples for 1 week and measured 13 indoor air pollutants: particulate matter with an aerodynamic diameter of ≤2.5 μm, ozone, nitrogen dioxide, sulfur dioxide, and nine VOCs. The associations between air pollutants and ASQ scores were estimated using linear mixed effects models and weighted quantile sum regressions (WQS) at each age separately. Stratified analysis by sex was conducted. Exposure to m,p-xylene at the age of 3 was associated with lower communication, fine motor, and overall ASQ scores (coefficients: -0.18 [99% confidence intervals (CI): -0.35, -0.02], -0.23 [99 %CI: -0.43, -0.03], and - 0.72 [99 %CI: -1.41, -0.04] per 1 µg/m³ increase, respectively). Exposure to o-xylene at the age of 3 was associated with lower communication, gross motor, fine motor, and overall ASQ scores (coefficients: -0.48 [99 %CI: -0.90, -0.07], -0.45 [99 %CI: -0.78, -0.13], -0.65 [99 %CI: -1.14, -0.16], and -2.15 [99 %CI: -3.83, -0.47] per 1 µg/m³ increase, respectively). The WQS index was associated with lower gross motor ASQ scores at the age of 3 (coefficient: -0.27 [95 %CI: -0.51, -0.03] for one-unit WQS index increases), which was attributed to benzene (33.96%), toluene (26.02%), o-xylene (13.62%), and ethylbenzene (9.83%). Stratified analysis showed similar results. Although further investigations are required, our results suggest an association of neurodevelopmental delays with indoor low-level exposure to m,p-xylene and o-xylene in early life.

Indoor air quality of 5,000 households and its determinants. Part A: Particulate matter (PM2.5 and PM10-2.5) concentrations in the Japan Environment and Children's Study

Exposure to particulate matter (PM) is one of the important risk factors for morbidity and mortality. Although PM concentrations have been assessed using air quality monitoring stations or modelling, few studies have measured indoor PM in large-scale birth cohorts. The Japan Environment and Children's Study (JECS) measured indoor and outdoor air quality in approximately 5000 households when the participating children were aged 1.5 and 3 years. PM was collected using portable pumps for 7 days (total of 24 h), inside and outside each home. Prediction models for indoor PM concentrations were built using data collected at age 1.5 years and post-validated against data collected at age 3 years. Median indoor/outdoor PM_2.5 and PM_10-2.5 concentrations at age 1.5 years [3 years] were 12.9/12.7 [12.5/11.3] μg/m³ and 5.0/6.3 [5.1/6.1] μg/m³, respectively. Random forest regression analysis found that the major predictors of indoor PM_2.5 were indoor PM_10-2.5, outdoor PM_2.5, indoor smoking, observable smoke and indoor/outdoor temperature. Indoor PM_2.5, outdoor PM_10-2.5, indoor humidity and opening room windows were important predictors of indoor PM_10-2.5 concentrations. Indoor benzene, acetaldehyde, ozone and nitrogen dioxide concentrations were also found to predict indoor PM_2.5 and PM_10-2.5 concentrations, possibly due to the formation of secondary organic aerosols. These findings demonstrate the importance of reducing outdoor PM concentrations, avoiding indoor smoking, using air cleaner in applicable and diminishing sources of VOCs that could form secondary organic aerosols, and the resulting models can be used to predict indoor PM concentrations for the rest of the JECS cohort.

Cold Spells and Cause-Specific Mortality in 47 Japanese Prefectures: A Systematic Evaluation

BACKGROUND

Many studies have investigated the devastating health effects of heat waves, but less is known about health risks related to cold spells, despite evidence that extreme cold may contribute to a larger proportion of deaths.

OBJECTIVES

We aimed to systematically investigate the association between cold spells and mortality in Japan.

METHODS

Daily data for weather conditions and 12 common causes of death during the 1972-2015 cold seasons (November-March) were obtained from 47 Japanese prefectures. Cold spells were defined as ≥2 consecutive days with daily mean temperatures ≤5th percentile for the cold season in each prefecture. Quasi-Poisson regression was combined with a distributed lag model to estimate prefecture-specific associations, and pooled associations at the national level were obtained through random-effects meta-analysis. The potential influence of cold spell characteristics (intensity, duration, and timing in season) on associations between cold spells and mortality was examined using a similar two-stage approach. Temporal trends were investigated using a meta-regression model.

RESULTS

A total of 18,139,498 deaths were recorded during study period. Mortality was significantly higher during cold spell days vs. other days for all selected causes of death. Mortality due to age-related physical debilitation was more strongly associated with cold spells than with other causes of death. Associations between cold spells and mortality from all causes and several more specific outcomes were stronger for longer and more intense cold spells and for cold spells earlier in the cold season. However, although all outcomes were positively associated with cold spell duration, findings for cold spell intensity and seasonal timing were heterogeneous across the outcomes. Associations between cold spells and mortality due to cerebrovascular disease, cerebral infarction, and age-related physical debility decreased in magnitude over time, whereas temporal trends were relatively flat for all-cause mortality and other outcomes.

DISCUSSION

Our findings may have implications for establishing tailored public health strategies to prevent avoidable cold spell-related health consequences. https://doi.org/10.1289/EHP7109.

Indoor air quality of 5,000 households and its determinants. Part B: Volatile organic compounds and inorganic gaseous pollutants in the Japan Environment and Children's study

Volatile organic compounds (VOCs) are major indoor air pollutants. Quantification of indoor concentrations of VOCs and identification of factors associated with these concentrations can help manage indoor air quality. This study measured the concentrations of VOCs and inorganic gaseous pollutants in around 5000 households in Japan and utilised a random forest model to estimate these concentrations and identify important determinants. The homes of 5017 randomly selected participants in the Japan Environment and Children's Study (JECS) were visited twice, when the children were aged 1.5 and 3 years. Twelve VOCs and inorganic gaseous pollutants were measured during 7 days by passive samplers. Various factors in these households, including household appliances, building characteristics, cooking styles, use of consumer products, renovation, pets, personal behaviours and ventilation were recorded. A random forest model with recursive feature elimination was utilised to identify factors predictive of VOCs and inorganic gaseous pollutants. Toluene, formaldehyde and acetaldehyde were the dominant indoor VOCs. The 95th percentiles of indoor p-dichlorobenzene concentrations at 1.5 and 3 years were 67 μg/m³ and 71 μg/m³, respectively. Random forest models with coefficients of determination ranging from 0.34 to 0.76 outperformed the traditional linear regression models. Factors associated with indoor VOC and inorganic gaseous pollutant concentrations included their outdoor concentrations, indoor and outdoor temperature and relative humidity, month of the year, hours windows were open, kerosene heater use and times of operation and building age. The results provided basic descriptions of indoor VOCs and inorganic gaseous pollutants in Japan and identified several determinants of these concentrations. These determinants should be considered to maintain indoor air quality. These results can be used in epidemiological assessments of the effects of VOCs and inorganic gaseous pollutants on health in children.

Long-term exposure to fine particulate matter and osteoporotic fracture: A case-control study in Taiwan

Few studies have explored the relationship between long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5) and osteoporotic fracture, particularly in high PM_2.5 level areas. The aim of this study was to assess the association between long-term exposure to PM_2.5 and osteoporotic fracture. We performed a matched case-control study of 16,175 participants obtained from a hospital registry during 2005-2014 in Taiwan. A major osteoporotic fracture was defined as a fracture of the spine, hip, proximal humerus, and forearm. We applied satellite-based spatiotemporal models with 1-km resolution to individually calculate the 1-year average PM_2.5 concentration before the index date which was defined as the first visit date for the osteoporotic fracture. Logistic regression models with and without potential confounding factors were used to estimate odds ratios (OR) and 95% confidence intervals (CI) between PM_2.5 and osteoporotic fracture, whereas a restricted cubic spline model was used to estimate the dose-response relationship. The sample's median age was 44.7 years (interquartile range: 30.7, 63.1 years). We observed that long-term PM_2.5 exposure was associated with osteoporotic fracture, the OR was 1.12 (95% CI: 1.03, 1.22) per 10-μg/m³ increase in PM_2.5 in women. In the dose-response association, the OR of osteoporotic fracture was significantly increased for PM_2.5 exposures more than 41 μg/m³. We did not find a significant association between PM_2.5 (per 10-μg/m³ increase) and osteoporotic fracture among overall population (adjusted OR, 1.02 [95% CI, 0.97 to 1.08]) and men (adjusted OR, 0.94 [95% CI, 0.86 to 1.02]). The results of the stratified analysis showed that women were more sensitive to the adverse impact of PM2.5 that were men, and evidence was obtained of sex-based effect modification (P for interaction = 0.002). Our findings suggest that long-term exposure to PM_2.5 is associated with osteoporotic fracture, particularly among women.

Effect of exposure to fine particulate matter during pregnancy and infancy on paediatric allergic rhinitis

BACKGROUND

The effect of prenatal and postnatal exposure to fine particulate matter (PM_2.5) on the development of allergic rhinitis (AR) is poorly understood. We further identified the vulnerable period for AR development to determine methods to decrease adverse effects.

METHODS

We used a large population-based birth cohort of 140 911 singleton live infants in Taichung, Taiwan with a highly temporal-resolution satellite-based hybrid model to evaluate the effects of prenatal and early postnatal exposure on the onset of AR.

RESULTS

Among 140 911 children, 47 276 (33.55%) were cases of incident AR. The mean age of the children with AR at initial diagnosis was 2.97±1.78 years. We identified a significant association of AR with an interquartile range (IQR 17.98 µg/m³) increase in PM_2.5 from 30 gestational weeks to 52 weeks after birth. The exposure-response relationship revealed that AR had a significant positive association between PM_2.5 of 26-76 µg/m³ (adjusted hazard ratios ranged from 1.00 to 1.05).

CONCLUSION

Our study provides evidence that both prenatal and postnatal exposures to PM_2.5 are associated with later development of AR. The vulnerable time window may be within late gestation and the first year of life. Further study is required to confirm the vulnerable time period of PM_2.5 on AR.

Dioxins in breast milk of Chinese mothers: A survey 40 years after the e-waste recycling activities

In the past two decades, numerous studies on dioxin concentrations in breast milk have been conducted in China. However, information concerning dioxin concentrations in breast milk from women living in e-waste recycling sites remains limited. Thus, this study aimed to evaluate health risk owing dioxin intake in e-waste recycling areas in China. In 2015, 42 mothers were recruited from an e-waste recycling site, and the same number of mothers were recruited from a reference site. We collected 10-mL breast milk samples from each participant. Breast milk concentrations of polychlorinated dibenzo-p-dioxins (PCDDs)/polychlorinated dibenzofurans (PCDFs) were significantly higher in the exposed group than in the reference group. The total toxic equivalents (TEQ) of PCDDs/DFs were 9.68 pg/g lipid in the exposed group, a value two times higher than those in the reference group (4.18 pg/g lipid). The estimated daily intake (EDI) of PCDD/DFs was calculated to assess the risk of dioxins through breastfeeding. The infant EDI level was two times higher in the exposed group (54.21 pg TEQ/kg body wt/day) than in the reference group (23.41 pg TEQ/kg body wt/day). Our findings suggest that mothers and their breastfeeding infants living in an e-waste recycling site were exposed to higher dioxin concentrations than those living in a reference site.

Exposure to heavy metals modifies optimal gestational weight gain: A large nationally representative cohort of the Japan Environment and Children's Study

Clinical guidelines including those set by the US Institute of Medicine, have based optimal gestational weight gain (GWG) on maternal pre-pregnancy body mass index (BMI), but have not considered the role of environmental toxicants such as heavy metals that can disrupt these processes. This study designed to determine optimal GWG ranges in women grouped according to BMI, and to assess whether blood concentrations of heavy metals alter the relationships between GWG and outcomes. A total of 103,060 participants in the Japan Environment and Children's Study recruited between 2011 and 2014 were followed until their children reached 3 years of age. Outcomes included 1 min Apgar score <7, caesarean delivery, childhood obesity, gestational diabetes, pregnancy-induced hypertension, low birth weight, large for gestational age, macrosomia, operative vaginal delivery, postpartum weight retention, preterm birth and small for gestational age. The optimal GWG ranges were determined using multivariate logistic regression models. Stratified analyses were performed to determine optimal GWG ranges according to quartiles of heavy metals. Optimal GWGs for underweight, normal weight and overweight women were found to be 10.0 to <14.0 kg, 6.0 to <12.0 kg and 4.0 to <8.0 kg, respectively. However, the benefits of optimal GWG were attenuated in women exposed to high concentrations of mercury (Hg), lead (Pb) and cadmium (Cd). Despite being within optimal GWG, underweight women with Hg > 5.21 ng/g and overweight women with Hg 3.67-5.21 ng/g, Pb > 7.31 ng/g and Cd > 0.66 ng/g had null effects. Heavy metals can modify the associations between GWG and outcomes, particularly for underweight and overweight women. Because of the complex interactions of environmental toxicants with pre-pregnancy BMI, GWG and adverse outcomes, GWG guidelines should be interpreted cautiously. Environmental toxicants may influence the determination of a clinical guideline.

The relationships between land use and amphibian assemblages in a traditional agricultural area, the Sun Moon Lake, of Taiwan

Abstract ContextUnderstanding the relationships between land use and anuran habitat selection would help make conservation-management and habitat-restoration decisions. However, only a few studies have investigated all the available amphibian habitats in terrestrial and aquatic environments. AimsThe objective of the present study is to assess the associations between different land-use types and individual anuran species in a traditional agricultural area. We also hypothesise that connectivity and land-use heterogeneity are important in determining species richness. MethodsWe conducted monthly roadside calling surveys at 71 sites in the Sun Moon Lake (SML) region in central Taiwan during 2008–2010. Non-metric multidimensional scaling (NMDS) with envfit was used to investigate the relationships between land-use characteristics and anuran assemblage. We use a site-occupancy model to assess the associations between land use and occupancy rate of each species. Generalised linear regression with Poisson distribution was used to assess the relationships among connectivity, land-use heterogeneity and species richness. Key resultsIn total, 19 species in five families were detected by roadside calling surveys. The NMDS results showed anuran assemblages in the SML region being distributed through an environmental gradient from those most dominated by agricultural land to forest-dominant sites. According to site-occupancy models, the occupancy rates of anurans were mainly correlated with proportion of agricultural land, grassland and distance to river. The species richness was positively correlated with land-use heterogeneity. ConclusionsThe results showed that the distributions of anurans largely depended on surrounding land-use types in the terrestrial environment. The major trend of anuran assemblages in the traditional agricultural area was dependent on the transition from forest to agricultural land. ImplicationsThe data suggested that land-use heterogeneity should be a primary consideration for increasing amphibian species richness.

Determination of Urinary Cotinine Cut-Off Concentrations for Pregnant Women in the Japan Environment and Children's Study (JECS)

Few studies have assessed the accuracy of self-reported questionnaires to determine smoking habits relative to urinary biomarkers. This study investigated urinary cotinine cut-off concentrations distinguishing active, passive and non-smokers among pregnant women who participated in the Japan Environment and Children's Study, a nationwide birth cohort study. Pregnant participants with measured urinary cotinine concentrations (UCCs) and who completed self-reported questionnaires on smoking status were included (n = 89,895). The cut-off values (COVs) for active and passive smokers were calculated by fitting mixed normal distribution functions to UCCs. The sensitivity and specificity of the questionnaires were subsequently evaluated. The median (interquartile range) UCC was 0.24 (0.083-0.96) µg/g-creatinine, with the detection rate of 89%. The COV for distinguishing active smokers from passive and non-smokers was 36.8 µg/g-creatinine. When this COV was considered to represent the true condition, the questionnaire had a sensitivity of 0.523, a specificity of 0.998, a positive predictive value (PPV) of 0.967 and a negative predictive value (NPV) of 0.957. The COV for distinguishing passive smokers from non-smokers was 0.31 µg/g-creatinine, with the questionnaire having a sensitivity of 0.222, a specificity of 0.977, a PPV of 0.868 and an NPV of 0.644. As many as 78% of passive smokers might be misclassified as non-smokers.

The relationship between perinatal exposure to dioxins and serum steroid hormone levels in preschool-aged children at an e-waste region in China

Perinatal exposure to dioxins affects steroid hormone synthesis. The purpose of the present study was to evaluate the associations between perinatal exposure to dioxins and serum steroid hormone levels in preschool-aged children from an e-waste recycling region in China. In the present study, we enrolled 50 pairs of mothers and infants from the Taizhou, Luqiao region in 2015. Of the 50 pairs of mothers and infants, 42 pairs participated in this study when the children were 4 years old. We measured breast milk dioxin concentrations using high-resolution gas chromatography/mass spectrometry. Additionally, we used liquid chromatography-tandem mass spectrometry to measure the concentrations of progesterone, testosterone, androstenedione (A-dione), and dehydroepiandrosterone (DHEA) in serum samples from the 4-year-old children. We used multivariate linear regressions to assess the associations between dioxin congeners and steroid hormones. Results were reported as beta estimates and 95% confidence intervals by bootstrapping. We observed sex-related differences between breast milk dioxins and serum steroid hormone levels in 4-year-old children. An increase in breast milk dioxins was associated with a decrease in testosterone in serum samples from boys. Similarly, an increase in breast milk dioxins was associated with a decrease in progesterone levels in serum samples from girls. However, dioxins were not associated with changes in the levels of testosterone, DHEA, or A-dione in girls. Based on these results, we conclude that perinatal exposure to dioxins modifies steroidogenesis in preschool-aged children. However, the long-term impact of dioxins requires further large-scale studies to assess these effects in school-going children and adolescents.

The association between dioxins and steroid hormones in general adult males: a cross-sectional study in an e-waste region of China

As observed among residents in electronic waste (e-waste) recycling areas, dioxins can disrupt the homeostasis of endocrine hormones and the balance of thyroid hormones. Few studies, however, have examined whether e-waste recycling activities influence steroid hormone equilibrium in the general adult male population. This study evaluated the association between steroid hormones and the physical burdens of dioxins in the general adult male population residing in an e-waste region. In September 2017, 74 adult males residing in an e-waste dismantling region were enrolled in the current study. Approximately 10 mL of blood was collected from each adult male, and the serum samples were separated through centrifugation. Then, the levels of dioxin and steroid hormones in the serum of the participants were measured. We treated dioxin levels as categorical variables in the general linear model according to quartiles (25, 50, and 75 percentile). Comparing the findings with a reference group (< 25th percentile), we noted significantly higher dehydroepiandrosterone (DHEA) level in men with low serum polychlorinated dibenzofuran-toxic equivalent (PCDFs-TEQ) level between 3.80 and 6.31 pg/g lipid (1933 vs. 1447 pg/ml) and low polychlorinated dibenzo-p-dioxins and dibenzofurans-TEQ (PCDD/PCDFs-TEQ) between 8.57 and 15.11 pg/g lipid (1996 vs. 1360 pg/ml). Moreover, a significantly higher androstenedione (A-dione) level was found in men whose serum PCDFs-TEQ ≥ 11.34 pg/g lipd (2404 vs. 1848). What's more, there were significantly higher 3β-hydroxysteroid dehydrogenase (3β-HSD) concentrations in low- and high-2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) groups (1.30-1.67 and ≥ 2.64 pg-TEQ/g lipid, respectively with 719 and 807 vs. 496, respectively). Our findings suggest that specific dioxin exposure may disturb normal DHEA, A-dione levels, and enzyme activity in the general adult male population in an e-waste region of China.

Exposure to fine particulate matter (PM2.5) and pediatric rheumatic diseases

Few studies have assessed the association between fine particulate matter (PM_2.5) exposure during pregnancy and infancy and pediatric rheumatic diseases (PRDs). The goal of this study was to investigate the association of PM_2.5 with PRDs, and to explore sensitive windows of exposure. Therefore, we conducted a cohort-based case-control study to investigate the association between weekly exposure to PM_2.5 and PRDs in Taiwan. Our birth cohort consisted of infants born in 2004-2014 (n = 1,991,592) who were followed from conception to the end of 2015. There were 2363 cases of incident PRDs in children, and 23,630 children served as controls using density matching (1:10) based on date of birth, gender, and gestational week. We used a linear mixed effect (LME) model to incorporate the aerosol optical depth (AOD), meteorological variables, and land-use data to predict daily PM_2.5 concentrations. We also performed conditional logistic regression with distributed lag non-linear models (DLNMs) to assess the effects of weekly average PM_2.5 on PRDs, as well as dose-response relationships. In DLNMs, exposure to PM_2.5 during pregnancy (11-40 weeks) or infancy (1-14 weeks after birth) was associated with incident PRDs adjusting for potential confounding factors, and for carbon monoxide and sulfur dioxide. In the dose-response association, the odds ratios of PRDs were significantly increased for PM_2.5 exposures between 26 and 54 μg/m³. In addition, exposure to PM_2.5 above 81 μg/m³ dramatically increased the risk of PRDs. In conclusions, our study provides new data to suggest that PM_2.5 exposure from 11-40 gestational weeks to 1-14 weeks after birth can increase the risk for PRDs in a non-linear dose-response fashion.

Fine particulate matter is a potential determinant of Alzheimer's disease: A systemic review and meta-analysis

Air pollution is a modifiable and preventable factor, and it is a possible risk factor for dementia. However, evidence from epidemiological studies is still limited. We conducted a systematic review and meta-analysis to summarize the epidemiological evidence for long-term effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM_2.5) on dementia/Alzheimer's disease (AD). Our inclusion criteria for eligible studies were: longitudinal cohort study design, no overlap in study population, age of study subject ≥50 years, detailed description of exposure assessment for PM_2.5, outdoor assessment of exposure to PM_2.5, usage of a clear definition of dementia/AD, and accessibility of sufficient information for meta-analysis. Six databases were searched for eligible studies. The random-effect model was used to synthesize the associations between PM_2.5 and dementia. After exclusion of all irrelevant studies, we analyzed the results of four cohort studies conducted in Canada, Taiwan, the UK, and the US during 2015-2018 among more than 12 million elderly subjects aged ≥50 years (N = 12,119,853). Our meta-analysis reveals that exposure to a 10 μg/m³ increase in PM_2.5 was significantly and positively associated with dementia (pooled HR = 3.26, 95% CI: 1.20, 5.31). In subgroup analyses, exposure to a 10 μg/m³ increase in PM_2.5 was found to be positively associated with AD (pooled HR = 4.82, 95% CI: 2.28, 7.36). Analysis of current epidemiological research on PM_2.5 and dementia confirmed that exposure to PM_2.5 was positively associated with a higher risk for dementia. However, it is to be noted that the included studies mainly relied on claim-based diagnosis and showed large differences in methods of exposure assessment, hence further epidemiological studies with well validated outcomes and with standardized exposure assessment models are required to ascertain the relationship between PM_2.5 and dementia/AD.

Long-term exposure to traffic-related air pollution and systemic lupus erythematosus in Taiwan: A cohort study

Systemic lupus erythematosus (SLE) is a multi-systemic chronic autoimmune disease, the etiology of SLE is still unclear. Only a few studies evaluated the associations between air pollution and SLE. We conducted a population-based cohort study in Taiwan to examine the associations of air pollution with SLE. A total of 682,208 individuals aged 18-70 years were retrieved from National Health Insurance Research Database. We applied 1-km resolution land use regression and satellite-based models to estimate air pollutant concentrations during 2001-2010. The mixed effect Cox models with time-dependent variables were performed to estimate the associations between air pollution and SLE, as hazard ratios (HRs) with 95% confidence interval (CI). We identified 1292 newly diagnosed SLE patients with average age of 43.26 ± 13.64 years, most of them were female. There were positive associations of SLE with exposure to a 9.76 ppb increase in nitrogen dioxide (NO₂), a 0.20 ppm increase in carbon monoxide (CO), and a 10.2 μg/m³ increase in fine particles (PM_2.5) (HR = 1.21, 95% CI: 1.08-1.36, HR = 1.44, 95% CI: 1.31-1.59, and HR = 1.12, 95% CI: 1.02-1.23, respectively). Additionally, we observed negative associations with ozone (O₃) and sulfur dioxide (SO₂). According to the exposure-response relationships, exposure to NO₂ between 28 and 38 ppb, exposure to CO above 0.6 ppm, and exposure to PM_2.5 between 18 and 46 μg/m³ were positively associated with SLE. The results suggested that long-term exposure to traffic-related gaseous air pollutants (NO₂ and CO) less than current National Ambient Air Quality Standards and PM_2.5 are significantly associated with the risk of SLE.

Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015

Satellite-based aerosol optical depth (AOD) is now comprehensively applied to estimate ground-level concentrations of fine particulate matter (PM_2.5). This study aimed to construct the AOD-PM_2.5 estimation models over Taiwan. The AOD-PM_2.5 modeling in Taiwan island is challenging owing to heterogeneous land use, complex topography, and humid tropical to subtropical climate conditions with frequent cloud cover and prolonged rainy season. The AOD retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites were combined with the meteorological variables from reanalysis data and high resolution localized land use variables to estimate PM_2.5 over Taiwan island from 2005 to 2015. Ten-fold cross validation was carried out and the residuals of the estimation model at various locations and seasons are assessed. The cross validation (CV) R² based on monitoring stations were 0.66 and 0.66, with CV root mean square errors of 14.0 μg/m³ (34%) and 12.9 μg/m³ (33%), respectively, for models based on Terra and Aqua AOD. The results provided PM_2.5 estimations at locations without surface stations. The estimation revealed PM_2.5 concentration hotspots in the central and southern part of the western plain areas, particularly in winter and spring. The annual average of estimated PM_2.5 concentrations over Taiwan consistently declined during 2005-2015. The AOD-PM_2.5 model is a reliable and validated method for estimating PM_2.5 concentrations at locations without monitoring stations in Taiwan, which is crucial for epidemiological study and for the assessment of air quality control policy.

PM2.5 components and outpatient visits for asthma: A time-stratified case-crossover study in a suburban area

The effects of fine particles (PM_2.5) on asthma have been widely confirmed by epidemiological research studies. However, a limited number of studies have investigated the relationship between exposure to different PM_2.5 components and asthma. We characterized the PM_2.5 components in a suburban site of central Taiwan and conducted a time-stratified case-crossover study to elaborate the effects of daily concentration of each PM_2.5 component on asthma outpatient visits. We retrieved asthma outpatient claims for individuals less than 20 years old with a residential address in the Shalu district, Taiwan, from the National Health Insurance Research Database during 2000-2010. Multiple linear regression models were used to back extrapolate the historic concentration of individual components of PM_2.5 from 2000 through to 2010, including black carbon (BC) and eight ions, namely, sulfate, nitrate (NO₃^-), ammonium, chloride, potassium (K⁺), magnesium, calcium, sodium. The odds ratio (OR) with a 95% confidence interval (CI) of individual PM_2.5 components on asthma was estimated by conditional logistic regression. A total of 887 asthma outpatient visits with individuals who have an average age of 7.96±3.88 years were selected. After adjusting for confounders, we found an interquartile range (IQR) increase in BC level, an IQR increase in NO₃^- level, and an IQR increase in K⁺ level that were all associated with the increased risk of asthma outpatient visits from the current day (OR = 1.18, 95% CI: 1.05-1.34; OR = 1.11, 95% CI: 1.01-1.21; and OR = 1.16, 95% CI: 1.04-1.30, respectively). The effects of these components on asthma were stronger in the cold season than in the warm season. However, we did not find any lagging effects. The results suggest that exposure to NO₃^-, BC, and K⁺ derived from industry-related combustion or motor vehicles emission sources may increase the risk of asthma outpatient visits, particularly during the cold season.

Ambient Air Pollutant Exposures and Hospitalization for Kawasaki Disease in Taiwan: A Case-Crossover Study (2000-2010)

BACKGROUND

Kawasaki disease (KD) is an acute and multi-systemic vasculitis that occurs predominantly in infants and young children. Although the etiological agent of KD remains unclear, limited studies have reported that windborne environmental factors may trigger KD.

OBJECTIVES

We conducted a time-stratified case-crossover study to assess the associations between air pollutants and KD in Taiwan.

METHODS

We identified children < 5 years old with a diagnosis of KD from the Longitudinal Health Insurance Database 2000 (LHID2000) between 2000 and 2010. We obtained data regarding carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), particulate matter with aerodynamic diameter < 10 μm (PM₁₀), and sulfate dioxide (SO₂) from 70 monitoring stations and used inverse distance weighting to calculate average daily exposures for the residential postal code of each case. We performed conditional logistic regression to estimate associations between KD and each air pollutant according to interquartile range (IQR) increases and quartiles of exposure on the day of hospitalization versus 3-4 reference days during the same month for each case. Additionally, we estimated associations with single-day exposures lagged 1-2 days.

RESULTS

We identified 695 KD hospital admissions during the study period. An IQR increase (28.73 ppb) of O₃ was positively associated with KD after adjusting for temperature, humidity, northward wind, and eastward wind [adjusted odds ratio = 1.21; 95% confidence interval (CI): 1.01, 1.44]. There were no significant associations between KD and CO, NO₂, PM₁₀, or SO₂. The association with O₃ was limited to exposure on the day of hospitalization and to exposure during the summer months (June-August).

CONCLUSIONS

Our results provide new evidence that exposure to O₃ may increase the risk of KD in children. However, further investigation is needed to confirm the association and identify a potential biological mechanism.

Associations between ozone and preterm birth in women who develop gestational diabetes

Prenatal exposure to ambient air pollutants might cause adverse birth outcomes; however, there have been few studies in which the association between air pollution and preterm birth was examined after stratifying by pregnancy complications. We conducted a population-based case-control study of 1,510,064 singleton births from the Taiwanese birth registry during 2001-2007. Of the total of 1,510,064 births, we designated all 86,224 preterm births as the case group and then randomly selected an additional 344,896 from the remaining births (equivalent to 4 full-term births for every 1 preterm birth) as the control sample. We used an inverse distance weighting approach to calculate an average exposure parameter for air pollutants. The adjusted odds ratio for preterm birth per 10-ppb increase in ozone was 1.12 (95% confidence interval: 1.01, 1.23) for women with gestational diabetes mellitus who were exposed in the third trimester and 1.02 (95% confidence interval: 1.01, 1.03) for women without gestational diabetes (P for interaction <0.001). These findings suggest that exposure to ozone in pregnancy is associated with an increased risk of preterm birth, particularly for women who have gestational diabetes mellitus.

Air pollution and limb defects: a matched-pairs case-control study in Taiwan

BACKGROUND

Air pollution influences the development of limb defects in animals. There is little epidemiologic evidence on the effect of prenatal air pollution exposure on the risk of limb defects.

OBJECTIVE

To assess the relations between exposure to ambient air pollutants and the risk of limb defects.

METHODS

We conducted a matched-pairs case-control study in Taiwan from 2001 through 2007. The case group consisted of 1687 limb defects and the control group was density-sampling matched one to ten based on the month and year of conception from 1510,064 live singleton newborns in 2001-2007. Adjusted conditional logistic regression models were used to estimate odds ratios per 10 ppb change for O3, NO2, 1 ppb change for SO2, 10 µg/m(3) change for PM10, and 100 ppb change for CO during the first trimester and first three gestational months.

RESULTS

Of the specific limb defects, reduction deformities of limbs (adjusted OR=1.024, 95% CI: 1.000, 1.048) was associated with a 1 ppb increase in SO2 during weeks of 9-12 of gestation as well as the first trimester. Reduction deformities of limbs was also associated with a 10 ppb increase in O3 during weeks of 1-4 of gestation (adjusted OR=1.391, 95% CI: 1.064, 1.818) among preterm births.

CONCLUSION

The present study provides evidence that exposure to outdoor air SO2 during the first trimester of pregnancy may increase the risk of limb defects. Exposure to O3 was associated with reduction deformities of limbs among preterm births. Similar levels of SO2 and O3 are encountered globally by large numbers of pregnant women.

Air pollution and newly diagnostic autism spectrum disorders: a population-based cohort study in Taiwan

There is limited evidence that long-term exposure to ambient air pollution increases the risk of childhood autism spectrum disorder (ASD). The objective of the study was to investigate the associations between long-term exposure to air pollution and newly diagnostic ASD in Taiwan. We conducted a population-based cohort of 49,073 children age less than 3 years in 2000 that were retrieved from Taiwan National Insurance Research Database and followed up from 2000 through 2010. Inverse distance weighting method was used to form exposure parameter for ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particles with aerodynamic diameter less than 10 µm (PM10). Time-dependent Cox proportional hazards (PH) model was performed to evaluate the relationship between yearly average exposure air pollutants of preceding years and newly diagnostic ASD. The risk of newly diagnostic ASD increased according to increasing O3, CO, NO2, and SO2 levels. The effect estimate indicating an approximately 59% risk increase per 10 ppb increase in O3 level (95% CI 1.42–1.79), 37% risk increase per 100 ppb in CO (95% CI 1.31–1.44), 340% risk increase per 10 ppb increase in NO2 level (95% CI 3.31–5.85), and 17% risk increase per 1 ppb in SO2 level (95% CI 1.09–1.27) was stable with different combinations of air pollutants in the multi-pollutant models. Our results provide evident that children exposure to O3, CO, NO2, and SO2 in the preceding 1 year to 4 years may increase the risk of ASD diagnosis.