Exposure to PM2.5 Metal Constituents and Liver Cancer Risk in REVEAL-HBV.

BACKGROUND: Ambient particulate matter is classified as a human Class 1 carcinogen, and recent studies found a positive relationship between fine particulate matter (PM2.5) and liver cancer. Nevertheless, little is known about which specific metal constituent contributes to the development of liver cancer. OBJECTIVE: To evaluate the association of long-term exposure to metal constituents in PM2.5 with the risk of liver cancer using a Taiwanese cohort study. METHODS: A total of 13,511 Taiwanese participants were recruited from the REVEAL-HBV in 1991-1992. Participants' long-term exposure to eight metal constituents (Ba, Cu, Mn, Sb, Zn, Pb, Ni, and Cd) in PM2.5 was based on ambient measurement in 2002-2006 followed by a land-use regression model for spatial interpolation. We ascertained newly developed liver cancer (ie, hepatocellular carcinoma [HCC]) through data linkage with the Taiwan Cancer Registry and national health death certification in 1991-2014. A Cox proportional hazards model was utilized to assess the association between exposure to PM2.5 metal component and HCC. RESULTS: We identified 322 newly developed HCC with a median follow-up of 23.1 years. Long-term exposure to PM2.5 Cu was positively associated with a risk of liver cancer. The adjusted hazard ratio (HR) was 1.13 (95% confidence interval [CI], 1.02-1.25; P = 0.023) with one unit increment on Cu normalized by PM2.5 mass concentration in the logarithmic scale. The PM2.5 Cu-HCC association remained statistically significant with adjustment for co-exposures to other metal constituents in PM2.5. CONCLUSION: Our findings suggest PM2.5 containing Cu may attribute to the association of PM2.5 exposure with liver cancer.

Estimating morning and evening commute period O3 concentration in Taiwan using a fine spatial-temporal resolution ensemble mixed spatial model with Geo-AI technology.

Elevated levels of ground-level ozone (O3) can have harmful effects on health. While previous studies have focused mainly on daily averages and daytime patterns, it's crucial to consider the effects of air pollution during daily commutes, as this can significantly contribute to overall exposure. This study is also the first to employ an ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and predictor variables selected using Shapley Additive exExplanations (SHAP) values to predict spatial-temporal fluctuations in O3 concentrations across the entire island of Taiwan. We utilized geospatial-artificial intelligence (Geo-AI), incorporating kriging, land use regression (LUR), machine learning (random forest (RF), categorical boosting (CatBoost), gradient boosting (GBM), extreme gradient boosting (XGBoost), and light gradient boosting (LightGBM)), and ensemble learning techniques to develop ensemble mixed spatial models (EMSMs) for morning and evening commute periods. The EMSMs were used to estimate long-term spatiotemporal variations of O3 levels, accounting for in-situ measurements, meteorological factors, geospatial predictors, and social and seasonal influences over a 26-year period. Compared to conventional LUR-based approaches, the EMSMs improved performance by 58% for both commute periods, with high explanatory power and an adjusted R2 of 0.91. Internal and external validation procedures and verification of O3 concentrations at the upper percentile ranges (in 1%, 5%, 10%, 15%, 20%, and 25%) and other conditions (including rain, no rain, weekday, weekend, festival, and no festival) have demonstrated that the models are stable and free from overfitting issues. Estimation maps were generated to examine changes in O3 levels before and during the implementation of COVID-19 restrictions. These findings provide accurate variations of O3 levels in commute period with high spatiotemporal resolution of daily and 50m * 50m grid, which can support control pollution efforts and aid in epidemiological studies.

Geospatial artificial intelligence for estimating daytime and nighttime nitrogen dioxide concentration variations in Taiwan: A spatial prediction model.

Nitrogen dioxide (NO2) is a major air pollutant primarily emitted from traffic and industrial activities, posing health risks. However, current air pollution models often underestimate exposure risks by neglecting the bimodal pattern of NO2 levels throughout the day. This study aimed to address this gap by developing ensemble mixed spatial models (EMSM) using geo-artificial intelligence (Geo-AI) to examine the spatial and temporal variations of NO2 concentrations at a high resolution of 50m. These EMSMs integrated spatial modelling methods, including kriging, land use regression, machine learning, and ensemble learning. The models utilized 26 years of observed NO2 measurements, meteorological parameters, geospatial layers, and social and season-dependent variables as representative of emission sources. Separate models were developed for daytime and nighttime periods, which achieved high reliability with adjusted R2 values of 0.92 and 0.93, respectively. The study revealed that mean NO2 concentrations were significantly higher at nighttime (9.60 ppb) compared to daytime (5.61 ppb). Additionally, winter exhibited the highest NO2 levels regardless of time period. The developed EMSMs were utilized to generate maps illustrating NO2 levels pre and during COVID restrictions in Taiwan. These findings could aid epidemiological research on exposure risks and support policy-making and environmental planning initiatives.

Non-linear association between long-term air pollution exposure and risk of metabolic dysfunction-associated steatotic liver disease.

BACKGROUND: Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence. METHOD: In this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly. RESULTS: A total of 131,592 participants were included, with 40.6% met the criteria of MASLD. "Threshold link function," "interaction link function," and "restricted cubic spline (RCS) link functions" best-fitted associations between MASLD and PM2.5, PM10/CO, and O3 /SO2/NO2, respectively. In the six-pollutant model, significant positive associations were observed when pollutant concentrations were over: 34.64 µg/m3 for PM2.5, 57.93 µg/m3 for PM10, 56 µg/m3 for O3, below 643.6 µg/m3 for CO, and within 33 and 48 µg/m3 for NO2. The six-pollutant model using these best-fitted link functions demonstrated superior model fitting compared to exposure-categorized model or linear link function model assuming proportionality of odds. CONCLUSION: Non-linear associations were found between air pollutants and MASLD prevalence. PM2.5, PM10, O3, CO, and NO2 exhibited positive associations with MASLD in specific concentration ranges, highlighting the need to consider non-linear relationships in assessing the impact of air pollution on MASLD.

APOE-ε4 Alleles Modify the Decline of MMSE Scores Associated With Time-Dependent PM2.5 Exposure: Findings From a Community-Based Longitudinal Cohort Study.

OBJECTIVE: Limited research has explored the long-term effect of reduced PM2.5 exposure on cognitive function. This study aimed to investigate the effects of time-dependent PM2.5 exposure and the interactions of PM2.5 and aging on declines in Mini-Mental State Examination (MMSE) scores, in carriers and non-carriers of the APOE-ε4 allele. METHODS: Participants aged over 60 were recruited for this cohort study, undergoing MMSE tests twice from the Taiwan Biobank Program from 2008 to 2020. Participants with dementia or baseline MMSE scores <24 were excluded. Annual PM2.5 levels were estimated using a hybrid kriging/land use regression model with extreme gradient boosting, treated as a time-dependent variable. Generalized estimating equations were used to assess the impacts of repeated PM2.5 on MMSE decline, further stratified by the presence of APOE-ε4 alleles. RESULTS: After follow-up, 290 participants out of the overall 7,000 community residents in the Biobank dataset demonstrated incidences of MMSE declines (<24), with an average MMSE score decline of 1.11 per year. Participants with ε4/ε4 alleles in the APOE gene had significantly 3.68-fold risks of MMSE decline. High levels of PM2.5 across all visits were significantly associated with worsening of scores on the overall MMSE. As annual levels of PM2.5 decreased over time, the impact of PM2.5 on MMSE decline also slowly diminished. CONCLUSION: Long-term PM2.5 exposure may be associated with increased risk of MMSE decline, despite improvements in ambient PM2.5 levels over time. Validation of these results necessitates a large-scale prospective cohort study with more concise cognitive screening tools.

Air pollution during the perinatal period and neurodevelopment in children: A national population study in Taiwan.

AIM: To evaluate the association between ambient particulate matter no larger than 2.5 µm in diameter (PM2.5 ) during the prenatal and postnatal periods and infant neurodevelopmental parameters. METHOD: We conducted a population-based birth cohort study using the Taiwan Birth Cohort Study. Participants were assessed for developmental conditions through home interviews at 6 months and 18 months of age. Exposure to PM2.5 of mothers and infants during perinatal periods was estimated using hybrid kriging/land-use regression. The exposure was linked to each participant by home address. Logistic regression was then conducted to determine the risk of neurodevelopmental delay in relation to PM2.5 . RESULTS: A total of 17 683 term singletons without congenital malformations were included in the final analysis. PM2.5 during the second trimester was associated with increased risks of delays in gross motor neurodevelopmental milestones (adjusted odds ratio [aOR] 1.09 per 10 µg/m3 increase in exposure to PM2.5 ). Delayed fine motor development was also found to be related to exposure to PM2.5 in the second and third trimesters (aOR 1.06), as was personal-social skill (aOR 1.11 for the second trimester and 1.06 for the third). These neurodevelopmental parameters were unrelated to postnatal PM2.5 exposure. INTERPRETATION: Exposure to ambient PM2.5 during pregnancy was significantly related to delay in gross motor, fine motor, and personal-social development in this population-based study. WHAT THIS PAPER ADDS: Prenatal exposure to higher PM2.5 was associated with increased risk of delayed early neurodevelopment. The critical period for delayed gross motor development was the second trimester. The critical period for fine motor and personal-social development was the second and third trimesters.

Residential greenness and air pollution's association with nasal microbiota among asthmatic children.

Both greenness and air pollution have widely been linked with asthma. However, the potential mechanism has rarely been investigated. This study aimed to identify the association between residential greenness and air pollution (fine particulate matter [PM2.5]; nitrogen dioxide [NO2]; ozone [O3]) with nasal microbiota among asthmatic children during the recovery phase. The normalized difference vegetation index was used to assess the extent of residential greenness. Spatiotemporal air pollution variation was estimated using an integrated hybrid kriging-LUR with the XG-Boost algorithm. These exposures were measured in 250-m intervals for four incremental buffer ranges. Nasal microbiota was collected from 47 children during the recovery phase. A generalized additive model controlled for various covariates was applied to evaluate the exposure-outcome association. The lag-time effect of greenness and air pollution related to the nasal microbiota also was examined. A significant negative association was observed between short-term exposure to air pollution and nasal bacterial diversity, as a one-unit increment in PM2.5 or O3 significantly decreased the observed species (PM2.5: -0.59, 95%CI -1.13, -0.05 and O3: -0.93, 95%CI -1.54, -0.32) and species richness (PM2.5: -0.64, 95%CI -1.25, -0.02 and O3: -0.68, 95%CI -1.43, -0.07). Considering the lag-time effect, we found a significant positive association between greenness and both the observed species and species richness. In addition, we identified a significant negative association for all pollutants with the observed species richness. These findings add to the evidence base of the links between nasal microbiota and air pollution and greenness. This study establishes a foundation for future studies of how environmental exposure plays a role in nasal microbiota, which in turn may affect the development of asthma.

Determinants of residential greenness and its association with prostate cancer risk: A case-control study in Singapore.

BACKGROUND: Exposure to greenness has been shown to be beneficial to health, but few studies have examined the association between residential greenness and prostate cancer (PCa) risk. Our main objectives were to identify the determinants of residential greenness, and to investigate if residential greenness was associated with PCa risk in Singapore. METHODS: The hospital-based case-control study was conducted between April 2007 and May 2009. The Singapore Prostate Cancer Study (SPCS) comprised 240 prostate cancer cases and 268 controls, whose demographics and residential address were collected using questionnaires. Residential greenness was measured by normalized difference vegetation index (NDVI) around the participants' homes using a buffer size of 1 km. Determinants of NDVI were identified using a multivariable linear regression model. Logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of associations between NDVI and PCa risk, adjusting for potential confounders. RESULTS: Having a BMI within the second quartile, as compared to the lowest quartile, was associated with higher levels of NDVI (ß-coefficient = 0.263; 95% CI = 0.040-0.485) after adjusting for covariates. Additionally, being widowed or separated, as compared to being married, was associated with lower levels of NDVI (ß-coefficient = -0.393; 95% CI = -0.723, -0.063). An interquartile range (IQR) increase in NDVI was positively associated with prostate cancer risk OR = 1.45; 95% CI = 1.02-2.07). Stratified analysis by tumour grade and stage showed that higher NDVI was associated with higher risk of low grade PCa. CONCLUSION: Our findings suggested that residential greenness was associated with higher risk of PCa in Singapore. Future studies on the quality and type of green spaces, as well as other factors of residential greenness, in association with PCa risk should be conducted to better understand this relationship.

Determination of potential sources of heavy metals in patients with urothelial carcinoma in central Taiwan: a biomonitoring case-control study.

The clarification of possible exposure sources of multiple metals to identify associations between metal doses and urothelial carcinoma (UC) risk is currently limited in the literature. We sought to identify the exposure sources of 10 metals (Vanadium, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, cadmium, and lead) using principal component analysis (PCA) and then linked various principal component (PC) scores with environmental characteristics, including smoking-related indices, PM2.5, and distance to the nearest bus station. In addition, urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) and DNA hypomethylation markers (5-methyl-2'-deoxycytidine levels; %5-MedC) were investigated in combination with UC risks. We conducted this hospital-based case control study in 359 UC patients with histologically confirmed disease and 718 controls. All data were collected from face-to-face interviews and medical records. Approximately 6 mL blood was collected from participants for analysis of multiple heavy metal and DNA methylation in leukocyte DNA. Further, a 20 mL urine sample was collected to measure urinary cotinine and 8-OHdG levels. In addition, average values for PM2.5 for individual resident were calculated using the hybrid kriging/land-use regression model. In UC patients, significantly higher cobalt, nickel, copper, arsenic, and cadmium (µg/L) levels were observed in blood when compared with controls. Three PCs with eigenvalues > 1 accounted for 24.3, 15.8, and 10.7% of UC patients, and 26.9, 16.7, and 11.1% of controls, respectively. Environmental metal sources in major clusters were potentially associated with industrial activities and traffic emissions (PC1), smoking (PC2), and food consumption, including vitamin supplements (PC3). Multiple metal doses were linked with incremental urinary 8-OHdG and DNA hypomethylation biomarkers. For individuals with high PC1 and PC2 scores, both displayed an approximate 1.2-fold risk for UC with DNA hypomethylation.In conclusion, we provide a foundation for health education and risk communication strategies to limit metal exposure in environment, so that UC risks can be improved potentially.

Air pollution enhance the progression of restrictive lung function impairment and diffusion capacity reduction: an elderly cohort study.

BACKGROUND: Some evidences have shown the association between air pollution exposure and the development of interstitial lung diseases. However, the effect of air pollution on the progression of restrictive ventilatory impairment and diffusion capacity reduction is unknown. This study aimed to evaluate the effects of long-term exposure to ambient air pollution on the change rates of total lung capacity, residual volume, and diffusion capacity among the elderly. METHODS: From 2016 to 2018, single-breath helium dilution with the diffusion capacity of carbon monoxide was performed once per year on 543 elderly individuals. Monthly concentrations of ambient fine particulate matters (PM2.5) and nitric dioxide (NO2) at the individual residential address were estimated using a hybrid Kriging/Land-use regression model. Linear mixed models were used to evaluate the association between long-term (12 months) exposure to air pollution and lung function with adjustment for potential covariates, including basic characteristics, indoor air pollution (second-hand smoke, cooking fume, and incense burning), physician diagnosed diseases (asthma and chronic airway diseases), dusty job history, and short-term (lag one month) air pollution exposure. RESULTS: An interquartile range (5.37 ppb) increase in long-term exposure to NO2 was associated with an additional rate of decline in total lung volume (- 1.8% per year, 95% CI: - 2.8 to - 0.9%), residual volume (- 3.3% per year, 95% CI: - 5.0 to - 1.6%), ratio of residual volume to total lung volume (- 1.6% per year, 95% CI: - 2.6 to - 0.5%), and diffusion capacity (- 1.1% per year, 95% CI: - 2.0 to - 0.2%). There is no effect on the transfer factor (ratio of diffusion capacity to alveolar volume). The effect of NO2 remained robust after adjustment for PM2.5 exposure. CONCLUSIONS: Long-term exposure to ambient NO2 is associated with an accelerated decline in static lung volume and diffusion capacity in the elderly. NO2 related air pollution may be a risk factor for restrictive lung disorders.

Living proximity to petrochemical industries and the risk of attention-deficit/hyperactivity disorder in children.

Evidence regarding the negative neurodevelopmental effects of compound exposure to petrochemicals remains limited. We aimed to evaluate the association between exposure to petrochemical facilities and generated emissions during early life and the risk of attention-deficit/hyperactivity disorder (ADHD) development in children. We conducted a population-based birth cohort study using the 2004 to 2014 Taiwanese Birth Certificate Database and verified diagnoses of ADHD using the National Health Insurance Database. The level of petrochemical exposure in each participant's residential township was evaluated using the following 3 measurements: distance to the nearest petrochemical industrial plant (PIP), petrochemical exposure probability (accounting for monthly prevailing wind measurements), and monthly benzene concentrations estimated using kriging-based land-use regression models. We applied Cox proportional hazard models to evaluate the association. During the study period, 48,854 out of 1,863,963 children were diagnosed as having ADHD. The results revealed that residents of townships in close proximity to PIPs (hazard ratio [HR] = 1.20, 95% confidence interval [CI]: 1.16-1.23, <3 vs. ≥10 km), highly affected by petrochemical-containing prevailing winds (HR = 1.12, 95% CI: 1.08-1.16, ≥40% vs. <10%), and with high benzene concentrations (HR = 1.26, 95% CI: 1.23-1.29, ≥0.75 vs. <0.55 ppb) were consistently associated with the increased risk of ADHD development in children. The findings of the sensitivity analysis remained robust, particularly for the 2004 to 2009 birth cohort and for models accounting for a longer duration of postnatal exposure. This work provided clear evidence that living near petrochemical plants increases the risk of ADHD development in children. Further studies are warranted to confirm our findings.

Frequent occurrence of respiratory symptoms in children is associated with exposure to air pollution, land use types, and parental mental health in the Greater Taipei area.

Although studies have investigated the individual effects of air pollution, land use types, and parental mental health on children's respiratory health, few studies have examined the effects of these risk factors simultaneously in children aged <2 years. We investigated the effects of exposure to air pollution, land use types surrounding residences, and parental mental health on the frequent occurrence of respiratory symptoms in children aged <2 years in the Greater Taipei area. Participants were recruited from an ongoing Taiwanese birth cohort study. We analyzed the data of the participants who had been recruited from January 2011 to April 2014 and had responded to the follow-up questionnaires at 6, 12, and 24 months. Self-administered questionnaires were used to collect participants' sociodemographic background and health, such as respiratory symptoms, and parental mental health. Pre- and postnatal pollution levels were estimated using the spatial interpolation technique (ordinary kriging) at children's residential addresses. Land use types surrounding participants' homes were evaluated by performing buffer analysis. Multiple logistic regression analyses were conducted to examine the effects of risk factors on the frequent occurrence of child respiratory symptoms in children aged 6, 12, and 24 months. We included 228, 360, and 441 children aged 6, 12, and 24 months, respectively. Our results indicated that postnatal exposure to PM2.5 and O3 was positively associated with children's respiratory symptoms. Traffic-related land-use types, sports facilities, and commercial land surrounding homes exerted adverse effects on children's respiratory symptoms, whereas the presence of schools in the neighborhood was beneficial. Parental mental health was also associated with children's respiratory symptoms. Postnatal exposure to air pollution and land use types surrounding residences were associated with respiratory health in children aged <2 years. The residential environment is a critical factor affecting children's respiratory health of children aged <2 years.

PM2.5 exposure and risk of lung adenocarcinoma in women of Taiwan: A case-control study with density sampling.

BACKGROUND AND OBJECTIVE: The prevalence of smoking among women in Taiwan is <5%, but the incidence of lung cancer remains high. This study determined the association between PM2.5 (fine particulate matter with an aerodynamic diameter of ≤2.5 µm) exposure and lung cancer among women in Taiwan. METHODS: In total, 21,301 female lung cancer cases nationwide were newly diagnosed between 2012 and 2017. Each case was age-, sex- and calendar year-matched with four controls randomly selected from the general population. Allowing a latent period of 5 years, we estimated the PM2.5 and nitrogen dioxide (NO2 ) exposures for each individual according to the residential changes from 2000. We adopted self-reported smoking statuses for the cases, while those of controls were estimated using annual surveys in each residential county. We performed multiple logistic regression analyses to examine the associations between PM2.5 and NO2 exposures and incident lung cancer cases. RESULTS: The ORs of lung adenocarcinoma for the third (30.5-35.1 µg/m3 ), fourth (35.1-39.3 µg/m3 ) and fifth PM2.5 exposure quintiles (39.3-48.1 µg/m3 ) relative to the first quintile were 1.10 (95% CI: 1.04-1.16), 1.12 (95% CI: 1.06-1.19) and 1.10 (95% CI: 1.04-1.16), respectively, after adjusting for smoking, residence and comorbidities. A dose-response relationship (p = 0.004) was found. The associations persisted with a 10-year latency and were not detected for small-cell and squamous cell carcinoma after control for smoking. We did not observe a similar effect for NO2 exposure. CONCLUSION: Residential PM2.5 exposure higher than 30 µg/m3 was associated with an increased risk of lung adenocarcinoma in women of Taiwan.

The effects of traffic-related air pollutants on chronic obstructive pulmonary disease in the community-based general population.

BACKGROUND: Previous studies have shown inconsistent results regarding the impact of traffic pollution on the prevalence of chronic obstructive pulmonary disease (COPD). Therefore, using frequency matching and propensity scores, we explored the association between traffic pollution and COPD in a cohort of 8284 residents in a major agricultural county in Taiwan. METHODS: All subjects completed a structured questionnaire interview and health checkups. Subjects with COPD were identified using Taiwan National Health Insurance Research Databases. A hybrid kriging/LUR model was used to identify levels of traffic-related air pollutants (PM2.5 and O3). Multiple logistic regression models were used to calculate the prevalence ratios (PRs) of COPD and evaluate the role played by traffic-related indices between air pollutants and COPD. The distributed lag nonlinear model was applied in the analysis; we excluded current or ever smokers to perform the sensitivity analysis. RESULTS: Increased PRs of COPD per SD increment of PM2.5 were 1.10 (95% CI 1.05-1.15) and 1.25 (95% CI 1.13-1.40) in the population with age and sex matching as well as propensity-score matching, respectively. The results of the sensitivity analysis were similar between the single and two pollutant models. PM2.5 concentrations were significantly associated with traffic flow including sedans, buses, and trucks (p < 0.01). The higher road area and the higher PM2.5 concentrations near the subject's residence correlated with a greater risk of developing COPD (p for interaction < 0.01). CONCLUSIONS: Our results suggest that long-term exposure to traffic-related air pollution may be positively associated with the prevalence of COPD.

Outdoor air pollutants exposure associated with pulmonary function and EBC pH value in atopic asthmatic and non-asthmatic children.

OBJECTIVE: Air pollution is associated with the prevalence of respiratory diseases. This study aimed to evaluate the impacts of outdoor air pollutants and indoor Dermatophagoides pteronyssinus 1 (Der p 1) exposure on levels of fractional exhaled nitric oxide (FeNO), exhaled breath condensate (EBC) pH, and pulmonary function in atopic children. METHODS: This study recruited 59 atopic mild-to-moderate asthmatic children and 23 atopic non-asthmatic children. Data on personal characteristics, FeNO, EBC pH, and pulmonary function were collected. Group 1 allergens of Der p 1 were measured on the tops of mattresses and on bedroom floors in the children's homes, and outdoor air pollutant concentrations were estimated from air quality monitoring stations, using the ordinary kriging method. RESULTS: Exposure levels of outdoor air pollutants, except for particulate matter (PM)2.5, for the recruited children met outdoor air quality standards set by the Taiwan Environmental Protection Agency. The lag effect of outdoor PM10 exposure was negatively associated with the forced expiratory volume in one second (FEV1) [(Lag 1: ß=-0.771, p = 0.028), and O3 (Lag 1-7: ß=-2.02, p = 0.04, Lag 1-28: ß=-3.213, p = 0.029)]. Median pulmonary function parameters differed significantly in forced vital capacity (FVC) (p = 0.004) and FEV1 (p = 0.024) values between atopic asthmatic and non-asthmatic children. No association was found between the FeNO/EBC pH level and exposure to Der p 1 allergen and air pollutants in the recruited children. CONCLUSIONS: Outdoor PM10 and O3 exposure was associated with reduction in FEV1 in atopic asthmatic and non-asthmatic children.

Effects of air pollution, land-use type, and maternal mental health on child development in the first two years of life in the Greater Taipei area.

INTRODUCTION: Few studies have investigated the associations of child development with air pollution, land-use type, and maternal mental health simultaneously. Therefore, we evaluated the effect of exposure to air pollutants during several critical periods of life, with adjustment for land-use type and maternal mental status, on child development at 6, 12, and 24 months of age in the Greater Taipei area. METHODS: Participants were selected from an ongoing Taiwanese birth cohort study. We analyzed the data of the participants who had been recruited from January 2011 to April 2014. Self-administered standardized questionnaires were used to collect information on sociodemographic factors, infant development and health, maternal mental status, etc. Air pollution levels in pre- and postnatal periods were estimated using a spatial interpolation technique (ordinary kriging) at children's residential addresses. Land-use types around participants' homes were evaluated using buffer analysis. We used multiple logistic regression analysis to examine the relationships between child development delay and environmental factors. RESULTS: In total, 228, 361, and 441 families completed child development forms at 6, 12, and 24 months of age, respectively. Our results indicated that prenatal exposure to particulate matter with aerodynamic diameter ≤10 µm and O3 and postnatal exposure to NO2 were negatively associated with child development. Traffic-related land-use types, gas stations, and power generation areas around participants' homes were also adversely correlated with child development. Moreover, poor maternal mental health was associated with child development delay. CONCLUSION: Prenatal exposure and postnatal exposure to air pollution were associated with development delay in children under 2 years of age, specifically those under 1 year of age, even after adjustment for land-use type and maternal mental status. Living environment is critical for the development of children under 2 years of age.

Association Between Traffic Count and Cardiovascular Mortality: A Prospective Cohort Study in Taiwan.

BACKGROUND: Exposure to traffic-related pollution is positively associated with cardiovascular diseases (CVD), but little is known about how different sources of traffic pollution (eg, gasoline-powered cars, diesel-engine vehicles) contribute to CVD. Therefore, we evaluated the association between exposure to different types of engine exhaust and CVD mortality. METHODS: We recruited 12,098 participants from REVEAL-HBV cohort in Taiwan. The CVD mortality in 2000-2014 was ascertained by the Taiwan Death Certificates. Traffic pollution sources (2005-2013) were based on information provided by the Directorate General of Highway in 2005. Exposure to PM2.5 was based on a land-use regression model. We applied Cox proportional hazard models to assess the association of traffic vehicle exposure and CVD mortality. A causal mediation analysis was applied to evaluate the mediation effect of PM2.5 on the relationship between traffic and CVD mortality. RESULTS: A total of 382 CVD mortalities were identified from 2000 to 2014. We found participants exposed to higher volumes of small car and truck exhausts had an increased CVD mortality. The adjusted hazard ratio (HR) was 1.10 for small cars (95% confidence interval [CI], 0.94-1.27; P-value = 0.23) and 1.24 for truck (95% CI, 1.03-1.51; P-value = 0.03) per one unit increment of the logarithm scale. The findings were still robust with further adjustment for different types of vehicles. A causal mediation analysis revealed PM2.5 had an over 60% mediation effect on traffic-CVD association. CONCLUSIONS: Exposure to exhaust from trucks or gasoline-powered cars is positively associated with CVD mortality, and air pollution may play a role in this association.

Residential greenness and birth outcomes: Evaluating the mediation and interaction effects of particulate air pollution.

BACKGROUND: The few studies that examined the association between residential greenness and birth outcomes have produced inconsistent results, and the underlying mechanisms of these associations remain unclear. OBJECTIVES: We examined the mediation and interaction effects of particulate matter (PM) air pollution on the relationship between greenness exposure during the first and third trimesters of pregnancy and birth outcomes, including preterm birth (PTB), term low birth weight (TLBW), small for gestational age (SGA), birth weight (BW), and head circumference (HC). METHODS: We conducted a retrospective cohort study on 16,184 singleton live births between 2010 and 2012 in Taiwan. Residential greenness was estimated based on the normalized difference vegetation index (NDVI), and the PM information during the first and third trimesters was estimated through hybrid kriging land use regression and ordinary kriging interpolation methods. Multiple regression analyses were performed to evaluate the associations between greenness exposure and birth outcomes. We estimated the mediating effects of PM associated with greenness exposure on birth outcomes through causal mediation analyses. We also examined the potential multiplicative and additive interactions between greenness exposure and PM and their effects on birth outcomes. RESULTS: The first trimester NDVI exposure was associated with reduced risks for PTB, TLBW, and SGA, which had an adjusted OR (aOR) of 0.93 (95% CI: 0.89-0.97), 0.91 (95% CI: 0.83-0.99), and 0.95 (95% CI: 0.91-1.00), respectively, per 0.1 unit increase in multi-pollutant models. The causal mediation analysis showed that PM mediated approximately 5-19% of the association between first and third trimester greenness and PTB and mediated approximately 15-37% of the association between greenness and SGA. We identified multiplicative interactions in log scale between first trimester PM10 and NDVI exposure for SGA (aORinteraction = 0.92, p = 0.03) and HC (estimateinteraction = 1.47, p = 0.04). CONCLUSIONS: This study revealed beneficial associations between residential greenness and birth outcomes, including PTB, TLBW, and SGA. The associations were partly mediated by a reduction in exposure to PM air pollution. SUMMARY: The beneficial effects of greenness on PTB and SGA are partly mediated by a reduction in exposure to PM air pollution.

Association Between Long-term Exposure to PM2.5 and Incidence of Type 2 Diabetes in Taiwan: A National Retrospective Cohort Study.

BACKGROUND: Long-term exposure to fine particulate matter (PM with an aerodynamic diameter ≤2.5 µm; PM2.5) contributes to an elevated incidence of type 2 diabetes (T2D) in North America and Europe, but there is limited empirical evidence for Asian countries. This study determined the association between and the exposure-response relationship for PM2.5 and the incidence of T2D in Taiwan. METHODS: This retrospective cohort study was conducted for the years 2001-2012. Health information, including age, sex, health insurance premium, type of occupation, medication, and disease status, was retrieved from the Longitudinal Health Insurance Database 2000. Monitoring data for PM2.5 came from the Environmental Protection Administration of Taiwan, and Land-use Regression modeling was used to approximate participants' long-term exposure to PM2.5. Cox proportional hazards models with a generalized estimating equation to account for the correlation within the locations of the medical facilities were used to estimate the association between exposure to PM2.5 and the incidence of T2D, adjusting for the potential confounders. We also examined effect modification of sex, age, hyperlipidemia, and National Health Insurance premium for the association. RESULTS: Forty-eight thousand six hundred eleven new cases of diabetes were identified among 505,151 eligible participants, with the median follow-up of 12 years. Positive associations were identified between long-term exposure to PM2.5 exposure and the incidence of T2D. An increase of 10 µg/m PM2.5 was associated with an 11.0% increase in the risk of contracting diabetes (95% confidence interval = 8.0%, 13.0%). The results show that there is an almost linear relationship between exposure to PM2.5 and the incidence of T2D. Sex, age, hyperlipidemia, and National Health Insurance premium acted as effect modifiers of the association between diabetes incidence and levels of PM2.5 exposure in Taiwan. CONCLUSIONS: In the population in Taiwan, long-term exposure to PM2.5 increases the risk of incidence of T2D by 11%. This effect is more pronounced in elderly male patients who exhibit hyperlipidemia and in individuals who have a lower insurance health insurance premium.

[Application of Geospatial Information Technologies in Assessing Changes in Regional Health Risks Related to Climate Change].

Changes in climate and global warming trends impact the ecological balance as well as human health. The recent development of geospatial information technologies such as Geographic Information Systems (GIS) and remote sensing provides useful tools to assess the impacts of climate changes on human health over large areas. This article aimed to conduct a literature review related to the application of geospatial information technologies in order to assess climate-change-related health risks in Taiwan, with primary outcomes of interest including physiological and mental health and infectious diseases. Three environmental factors, including temperature, precipitation, and air pollution, and their impacts on human health were considered. Comments were raised for future studies in Taiwan on this subject area. Among the hundred papers reviewed, 28 were related to the target topic, and air pollution and fine particle studies were the focus of most of these 28 papers. Studies related to extreme temperature indicted growing concern with this issue. However, limited research was found related to precipitation and environmental greenness. Therefore, future studies should pay greater attention to these two environmental issues. We hope that the findings of this literature review will encourage more researchers to investigate this subject.