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 (PM2.5 ) plays a role in the development of tic disorders remains unexplored. OBJECTIVES: To investigate the association of exposure between PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 : 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 PM2.5 and the risk of tic disorders, with exposure to PM2.5 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.

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.

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.

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 (PM2.5), 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 PM2.5, 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 PM2.5, 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.

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 (PM2.5) exposure during the prenatal and postnatal periods on the development of attention-deficit/hyperactivity disorder (ADHD). We investigated the association of exposure to PM2.5 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 PM2.5 concentrations were derived from a 1-km satellite-based estimation model. A time-dependent Cox model was used to assess the effects of PM2.5 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 PM2.5 during the first trimester (HR = 1.26; 95% confidence interval [CI]: 1.13-1.40) and increased at PM2.5 over 16 µg/m3. For postnatal periods, the HR of ADHD was significantly associated with increased PM2.5 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 PM2.5 at the third year of life, the HR of ADHD was significantly associated with PM2.5 above 16 µg/m3 and sharply increased as PM2.5 >50 µg/m3. We did not observe a significant modification of sex on the relation between PM2.5 and ADHD. Exposure of pregnant women to PM2.5 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.

Combined exposure to heavy metals in PM2.5 and pediatric asthma.

BACKGROUND: Asthma is the most common chronic allergic disease in children; it affects more than 300 million people worldwide. Information on the association between exposure to ambient heavy metals and incidence of pediatric asthma is limited. OBJECTIVE: We sought to evaluate the effects of heavy metals during pregnancy and infancy periods with asthma and identify a sensitive time window, clarifying the effect of ambient heavy metals on lung development. METHODS: A total of 171,281 children, who were born from 2004 to 2011 in Taichung City, were followed until 2014. Concentrations of ambient heavy metals such as arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) were obtained from the Weather Research and Forecasting/Chem model, considering the top 75 emission sources in Taiwan. The distributed lag nonlinear model was used to investigate the relationship between combined exposure to heavy metals in 2.5 µm particulate matter and asthma in pregnant women and 1-year-old infants. RESULTS: We identified 31,277 new asthma cases from the birth cohort. After adjustment for socioeconomic status, maternal age, maternal atopy, maternal anemia, and maternal kidney disease, distributed lag nonlinear model results revealed positive associations of asthma with exposure to Pb during gestational weeks 1 to 14 and 21 to 40, and 1 to 3 weeks after birth. Regarding the sensitivity analyses, coexposure to Pb and As, coexposure to Pb and Cd, and coexposure to Pb and Hg were positively associated with asthma onset as well. CONCLUSIONS: Our study suggested that combined exposure to Pb with As, Cd, and Hg during early and late gestational weeks was associated with the incidence of pediatric asthma.

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 (PM2.5) 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 PM2.5 from 30 gestational weeks to 52 weeks after birth. The exposure-response relationship revealed that AR had a significant positive association between PM2.5 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 PM2.5 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 PM2.5 on AR.

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 PM2.5 and PM10-2.5 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 PM2.5 were indoor PM10-2.5, outdoor PM2.5, indoor smoking, observable smoke and indoor/outdoor temperature. Indoor PM2.5, outdoor PM10-2.5, indoor humidity and opening room windows were important predictors of indoor PM10-2.5 concentrations. Indoor benzene, acetaldehyde, ozone and nitrogen dioxide concentrations were also found to predict indoor PM2.5 and PM10-2.5 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.

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 (PM2.5) and osteoporotic fracture, particularly in high PM2.5 level areas. The aim of this study was to assess the association between long-term exposure to PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 exposure was associated with osteoporotic fracture, the OR was 1.12 (95% CI: 1.03, 1.22) per 10-µg/m3 increase in PM2.5 in women. In the dose-response association, the OR of osteoporotic fracture was significantly increased for PM2.5 exposures more than 41 µg/m3. We did not find a significant association between PM2.5 (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 PM2.5 is associated with osteoporotic fracture, particularly among women.

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.

Particulate Air Pollution and Progression to Kidney Failure With Replacement Therapy: An Advanced CKD Registry-Based Cohort Study in Taiwan.

RATIONALE & OBJECTIVE: Limited evidence concerns fine particulate matter (with aerodynamic diameter ≤ 2.5µm [PM2.5]) exposure and the risk for kidney failure with replacement therapy (KFRT). This study assessed whether PM2.5 exposure was associated with progression of chronic kidney disease (CKD) to KFRT. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 6,628 adult patients with CKD were recruited from the Advanced CKD Program in Taiwan between 2003 and 2015. EXPOSURE: Satellite-based spatiotemporal models were used to calculate each individual's 1-year PM2.5 exposure before the date of enrollment into the Advanced CKD Program. OUTCOMES: Time to KFRT (defined as initiation of maintenance hemodialysis, peritoneal dialysis, or kidney transplantation) and time to all-cause mortality. ANALYTICAL APPROACH: Multivariable proportional hazard regression analyses were used to estimate the association of PM2.5 with KFRT and all-cause mortality. Restricted cubic splines were used to explore dose-response relationships. RESULTS: The study population included 6,628 adult patients with CKD who were aged 20 to 90 years. 941 KFRT events and 1,653 deaths occurred during follow-up. The adjusted HR for progression to KFRT was 1.19 (95% CI, 1.08-1.31) per 7.8µg/m3 greater PM2.5, an amount spanning the interquartile range. There was evidence of a dose-response relationship (adjusted HRs of 1.16 [95% CI, 0.90-1.51], 1.19 [95% CI, 0.94-1.52], and 1.42 [95% CI, 1.12-1.80] for low, medium, and high PM2.5 levels). There was no significant association between PM2.5 and all-cause mortality (adjusted HR, 1.01 [95% CI, 0.95-1.08]). LIMITATIONS: Misclassification of PM2.5 exposure assessment and the potential for residual confounding. CONCLUSIONS: Our findings suggest that long-term exposure to PM2.5 is associated with increased risk for progression to KFRT in patients with CKD.

Fine particulate matter exposure during pregnancy and infancy and incident asthma.

BACKGROUND: Lung development is a multistage process from conception to the postnatal period, disruption of which by air pollutants can trigger later respiratory morbidity. OBJECTIVE: We sought to evaluate the effects of weekly average fine particulate matter (particulate matter with an aerodynamic diameter less than 2.5 µm [PM2.5]) exposure during pregnancy and infancy on asthma and identify vulnerable times to help elucidate possible mechanisms of the effects of PM2.5 on asthma symptoms. METHODS: A birth cohort study including 184,604 children born during 2004-2011 in Taichung City was retrieved from the Taiwan Maternal and Child Health Database and followed until 2014. A daily satellite-based hybrid model was applied to estimate PM2.5 exposure for each subject. A Cox proportional hazard model combined with a distributed lag nonlinear model was used to evaluate the associations of asthma with PM2.5 exposure during pregnancy and infancy. RESULTS: The birth cohort contained 34,336 asthmatic patients, and the mean age of children given a diagnosis of asthma was 3.39 ± 1.78 years. Increased exposure to PM2.5 during gestational weeks 6 to 22 and 9 to 46 weeks after birth were significantly associated with an increased incidence of asthma. The exposure-response relationship indicated that the hazard ratio (HR) of asthma increased steeply at PM2.5 exposure of greater than 93 µg/m3 during pregnancy. Additionally, the HRs remained significant with postnatal exposure to PM2.5 between 26 and 72 µg/m3 (range, 1.01-1.07 µg/m3), followed by a sharp increase in HRs at PM2.5 exposure of greater than 73 µg/m3. CONCLUSION: Both prenatal and postnatal exposures to PM2.5 were associated with later development of asthma. The vulnerable time windows might be within early gestation and midgestation and infancy.

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 (PM2.5) 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 PM2.5, outdoor assessment of exposure to PM2.5, 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 PM2.5 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 PM2.5 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 PM2.5 was found to be positively associated with AD (pooled HR = 4.82, 95% CI: 2.28, 7.36). Analysis of current epidemiological research on PM2.5 and dementia confirmed that exposure to PM2.5 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 PM2.5 and dementia/AD.

Air Pollution as a Potential Determinant of Rheumatoid Arthritis: A Population-based Cohort Study in Taiwan.

BACKGROUND: Limited studies have explored the relationship between air pollution and rheumatoid arthritis (RA), with the results being somewhat inconsistent. METHODS: This was a retrospective cohort study that included 322,301 subjects aged 30-50 years, selected from the National Health Insurance Research Database in Taiwan, were followed from 2001 to 2010. We used a time-dependent extended Cox model and incorporated time-dependent variables to estimate the associations between the annual mean concentrations of air pollutants with RA, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), particles with an aerodynamic diameter less than 10 µm (PM10), and sulfur dioxide (SO2), and reported the hazard ratio (HR) and 95% confidence interval (CI). RESULTS: Newly diagnosed RA was positively associated with a 100-ppb increase in CO (adjusted HR = 1.17 [95% CI = 1.16, 1.18]), a 10-ppb increase in NO2 (1.54 [1.45, 1.64]), a 10-ppb increase in O3 (1.37 [1.33, 1.41]), and a 1 ppb in SO2 (1.02 [1.00, 1.04]). There was no association between a 10-µg/m increase in PM10 and RA (1.02 [0.99, 1.05]). CONCLUSIONS: Our finding suggests that O3 and traffic-related air pollutants (CO and NO2) may be positively associated with incident RA. This is an important finding given that many individuals are exposed to similar levels of O3 and NO2 globally.

Interaction Between Catalase Gene Promoter Polymorphisms and Indoor Environmental Exposure in Childhood Allergic Rhinitis.

BACKGROUND: Allergic rhinitis (AR) is a highly prevalent chronic inflammatory disease affecting nearly 40% of the children in Taiwan. Genetic susceptibility may interact with specific environmental factors leading to allergic disease development. METHODS: To assess the interactions between catalase gene promoter polymorphisms and environmental factors on the risk of AR, we conducted a case-control study in Taiwan. Data on AR and environmental factors were collected from 800 children using the ISSAC questionnaire. The case group consisted of 263 children with AR, and the control group consisted of =537 healthy children. Genotyping was performed for rs1001179 and rs769214 polymorphisms, and environmental exposure was assessed using four indicators including dwelling visible molds, mold odor, moisture on surfaces, and water damage. RESULTS: We found that the presence of visible molds, mold odor, and moisture was associated with AR. An apparent joint effect of the GG genotype and mold odor, compared with the AA and AG combined genotypes and without any exposure indicator (adjusted odds ratio [OR] = 1.95 [95% confidence interval (CI) = 1.20, 3.18]; interaction adjusted odds ratio = 2.59 [95% CI = 1.27, 5.30]), was observed. CONCLUSIONS: Our findings suggest that gene-environment interactions between the catalase polymorphism rs769214 and mold odor may play an important role in childhood AR development.

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.

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, PM2.5, 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.

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 (bp), air pollutants (PM10, PM2.5, 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 bp. 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 bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating bp. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

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 (ß = 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.