Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML) model for first-trimester screening for pre-eclampsia in a large Asian population. METHODS: This was a secondary analysis of a multicenter prospective cohort study in 10 935 participants with singleton pregnancies attending for routine pregnancy care at 11-13+6 weeks of gestation in seven regions in Asia between December 2016 and June 2018. We applied the AI+ML model for the first-trimester prediction of preterm pre-eclampsia (<37 weeks), term pre-eclampsia (≥37 weeks), and any pre-eclampsia, which was derived and tested in a cohort of pregnant participants in the UK (Model 1). This model comprises maternal factors with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor (PlGF). The model was further retrained with adjustments for analyzers used for biochemical testing (Model 2). Discrimination was assessed by area under the receiver operating characteristic curve (AUC). The Delong test was used to compare the AUC of Model 1, Model 2, and the Fetal Medicine Foundation (FMF) competing risk model. RESULTS: The predictive performance of Model 1 was significantly lower than that of the FMF competing risk model in the prediction of preterm pre-eclampsia (0.82, 95% confidence interval [CI] 0.77-0.87 vs. 0.86, 95% CI 0.811-0.91, P = 0.019), term pre-eclampsia (0.75, 95% CI 0.71-0.80 vs. 0.79, 95% CI 0.75-0.83, P = 0.006), and any pre-eclampsia (0.78, 95% CI 0.74-0.81 vs. 0.82, 95% CI 0.79-0.84, P < 0.001). Following the retraining of the data with adjustments for the PlGF analyzers, the performance of Model 2 for predicting preterm pre-eclampsia, term pre-eclampsia, and any pre-eclampsia was improved with the AUC values increased to 0.84 (95% CI 0.80-0.89), 0.77 (95% CI 0.73-0.81), and 0.80 (95% CI 0.76-0.83), respectively. There were no differences in AUCs between Model 2 and the FMF competing risk model in the prediction of preterm pre-eclampsia (P = 0.135) and term pre-eclampsia (P = 0.084). However, Model 2 was inferior to the FMF competing risk model in predicting any pre-eclampsia (P = 0.024). CONCLUSION: This study has demonstrated that following adjustment for the biochemical marker analyzers, the predictive performance of the AI+ML prediction model for pre-eclampsia in the first trimester was comparable to that of the FMF competing risk model in an Asian population.

Association between Ambient Volatile Organic Compounds Exposome and Emergency Hospital Admissions for Cardiovascular Disease.

The limited research on volatile organic compounds (VOCs) has not taken into account the interactions between constituents. We used the weighted quantile sum (WQS) model and generalized linear model (GLM) to quantify the joint effects of ambient VOCs exposome and identify the substances that play key roles. For a 0 day lag, a quartile increase of WQS index for n-alkanes, iso/anti-alkanes, aromatic, halogenated aromatic hydrocarbons, halogenated saturated chain hydrocarbons, and halogenated unsaturated chain hydrocarbons were associated with 1.09% (95% CI: 0.13, 2.06%), 0.98% (95% CI: 0.22, 1.74%), 0.92% (95% CI: 0.14, 1.69%), 1.03% (95% CI: 0.14, 1.93%), 1.69% (95% CI: 0.48, 2.91%), and 1.85% (95% CI: 0.93, 2.79%) increase in cardiovascular disease (CVD) emergency hospital admissions, respectively. Independent effects of key substances on CVD-related emergency hospital admissions were also reported. In particular, an interquartile range increase in 1,1,1-trichloroethane, methylene chloride, styrene, and methylcyclohexane is associated with a greater risk of CVD-associated emergency hospital admissions [3.30% (95% CI: 1.93, 4.69%), 3.84% (95% CI: 1.21, 6.53%), 5.62% (95% CI: 1.35, 10.06%), 8.68% (95% CI: 3.74, 13.86%), respectively]. We found that even if ambient VOCs are present at a considerably low concentration, they can cause cardiovascular damage. This should prompt governments to establish and improve concentration standards for VOCs and their sources. At the same time, policies should be introduced to limit VOCs emission to protect public health.

Dust particulate matter increases pulmonary embolism onset: A nationwide time-stratified case-crossover study in China.

BACKGROUND: Particulate matter (PM) has been found to elevate the risk of pulmonary embolism (PE) onset. Among the contributors to PM, dust PM stands as the second natural source, and its emissions are escalating due to climate change. Despite this, information on the effect of dust PM on PE onset is scarce. Hence, this study aims to investigate the impacts of dust PM10, dust PM2.5-10, and dust PM2.5 on PE onset. METHODS: A nationwide time-stratified case-crossover study was conducted between 2015 and 2020, using data from 18,616 PE onset cases across 1,921 hospitals in China. The analysis employed a conditional logistic regression model to quantify the associations between dust PM10, dust PM2.5-10, and dust PM2.5 and PE onset. Furthermore, the study explored the time-distributed lag pattern of the effect of dust PM on PE development. Stratified analyses were performed based on sex, age, region, and season. RESULTS: Dust PM10, dust PM2.5-10, and dust PM2.5 exhibited significant health effects on PE onset, particularly concerning exposure on the same day. The peak estimates were observed at lag 01 day, with the odds ratio being 1.011 [95 % confidence interval (CI): 1.003, 1.019], 1.014 (95 % CI: 1.003, 1.026), and 1.039 (95 % CI: 1.011, 1.068), for a 10 µg/m3 increase in the concentration of dust PM10, dust PM2.5-10, and dust PM2.5, respectively. In addition, the study identified a higher risk of PE onset associated with dust PM exposure during the warm season than that in cool season, particularly for dust PM2.5. CONCLUSIONS: The findings from this study suggest that short-term exposure to dust PM, particularly dust PM2.5, may trigger PE onset, posing a significant health threat. Implementing measures to mitigate dust PM emissions and protect patients with PE from dust PM exposure is imperative.

Related health burden with the improvement of air quality across China.

BACKGROUND: Substantial progress in air pollution control has brought considerable health benefits in China, but little is known about the spatio-temporal trends of economic burden from air pollution. This study aimed to explore their spatio-temporal features of disease burden from air pollution in China to provide policy recommendations for efficiently reducing the air pollution and related disease burden in an era of a growing economy. METHODS: Using the Global Burden of Disease method and willingness to pay method, we estimated fine particulate matter (PM2.5) and/or ozone (O3) related premature mortality and its economic burden across China, and explored their spatio-temporal trends between 2005 and 2017. RESULTS: In 2017, we estimated that the premature mortality and economic burden related to the two pollutants were RMB 0.94 million (68.49 per 100,000) and 1170.31 billion yuan (1.41% of the national gross domestic product [GDP]), respectively. From 2005 to 2017, the total premature mortality was decreasing with the air quality improvement, but the economic burden was increasing along with the economic growth. And the economic growth has contributed more to the growth of economic costs than the economic burden decrease brought by the air quality improvement. The premature mortality and economic burden from O3 in the total loss from the two pollutants was substantially lower than that of PM2.5, but it was rapidly growing. The O3-contribution was highest in the Yangtze River Delta region, the Fen-Wei Plain region, and some western regions. The proportion of economic burden from PM2.5 and O3 to GDP significantly declined from 2005 to 2017 and showed a decreasing trend pattern from northeast to southwest. CONCLUSION: The disease burden from O3 is lower than that of PM2.5, the O3-contribution has a significantly increasing trend with the growth of economy and O3 concentration.

Associations of long-term fine particulate matter exposure with all-cause and cause-specific mortality: results from the ChinaHEART project.

Background: The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations. Methods: We enrolled community residents aged 35-75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities. Findings: We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 µg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012-1.028]), CVD death (1.024 [1.011-1.037]), cancer death (1.037 [1.023-1.052]), and respiratory disease death (1.083 [1.049-1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality. Interpretation: The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 µg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution. Funding: The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.

The relationship between particulate matter and lung function of children: A systematic review and meta-analysis.

There have been many studies on the relationship between fine particulate matter (PM2.5) and lung function. However, the impact of short-term or long-term PM2.5 exposures on lung function in children is still inconsistent globally, and the reasons for the inconsistency of the research results are not clear. Therefore, we searched the PubMed, Embase and Web of Science databases up to May 2022, and a total of 653 studies about PM2.5 exposures on children's lung function were identified. Random effects meta-analysis was used to estimate the combined effects of the 25 articles included. PM2.5 concentrations in short-term exposure studies mainly come from individual and site monitoring. And for every 10 µg/m3 increase, forced vital capacity (FVC), forced expiratory volume in the first second (FEV1) and peak expiratory flow (PEF) decreased by 21.39 ml (95% CI: 13.87, 28.92), 25.66 ml (95% CI: 14.85, 36.47) and 1.76 L/min (95% CI: 1.04, 2.49), respectively. The effect of PM2.5 on lung function has a lag effect. For every 10 µg/m3 increase in the 1-day moving average PM2.5 concentration, FEV1, FVC and PEF decreased by 14.81 ml, 15.40 ml and 1.18 L/min, respectively. PM2.5 concentrations in long-term exposure studies mainly obtained via ground monitoring stations. And for every 10 µg/m3 increase, FEV1, FVC and PEF decreased by 61.00 ml (95% CI: 25.80, 96.21), 54.47 ml (95% CI: 7.29, 101.64) and 10.02 L/min (95% CI: 7.07, 12.98), respectively. The sex, body mass index (BMI), relative humidity (RH), temperature (Temp) and the average PM2.5 exposure level modify the relationship between short-term PM2.5 exposure and lung function. Our study provides further scientific evidence for the deleterious effects of PM2.5 exposures on children's lung function, suggesting that exposure to PM2.5 is detrimental to children's respiratory health. Appropriate protective measures should be taken to reduce the adverse impact of air pollution on children's health.

Long-term exposure to ozone and cardiovascular mortality in a large Chinese cohort.

BACKGROUND: Evidence for the association between long-term exposure to ozone (O3) and cause-specific cardiovascular disease (CVD) mortality is inconclusive, and this association has rarely been evaluated at high O3 concentrations. OBJECTIVES: We aim to evaluate the associations between long-term O3 exposure and cause-specific CVD mortality in a Chinese population. METHODS: From 2009 to 2018, 744,882 subjects (median follow-up of 7.72 years) were included in the CHinese Electronic health Records Research in Yinzhou (CHERRY) study. The annual average concentrations of O3 and fine particulate matter (PM2.5), which were estimated using grids with a resolution up to 1 × 1 km, were assigned to the community address for each subject. The outcomes were deaths from CVD, ischemic heart disease (IHD), myocardial infarction (MI), stroke, and hemorrhagic/ischemic stroke. Time-varying Cox model adjusted for PM2.5 and individual-level covariates was used. RESULTS: The mean of annual average O3 concentrations was 68.05 µg/m3. The adjusted hazard ratio per 10 µg/m3 O3 increase was 1.22 (95% confidence interval [CI]: 1.13-1.33) for overall CVD mortality, 1.08 (0.91-1.29) for IHD, 1.21 (0.90-1.63) for MI, 1.28 (1.15-1.43) for overall stroke, 1.39 (1.16-1.67) for hemorrhagic stroke and 1.22 (1.00-1.49) for ischemic stroke, respectively. The study showed that subjects without hypertension had a higher risk for CVD mortality associated with long-term O3 exposure (1.66 vs. 1.15, p = 0.01). CONCLUSIONS: We observed the association between long-term exposure to high O3 concentrations and cause-specific CVD mortality in China, independent of PM2.5 and other CVD risk factors. This suggested an urgent need to control O3 pollution, especially in developing countries.

Prospective Evaluation of International Prediction of Pregnancy Complications Collaborative Network Models for Prediction of Preeclampsia: Role of Serum sFlt-1 at 11-13 Weeks' Gestation.

The study aimed to investigate whether serum sFlt-1 (soluble fms-like tyrosine kinase-1) at 11-13 weeks' gestation in pregnancies that subsequently developed preeclampsia was different from those without preeclampsia and compare screening performance of the International Prediction of Pregnancy Complications (IPPIC) reported models, which include various combinations of maternal factors, systolic blood pressure, diastolic blood pressure, PlGF (placental growth factor) and sFlt-1 and the competing risk (CR) models, which include various combinations of maternal factors, mean arterial pressure (MAP) and PlGF for predicting any-onset, early-onset, and late-onset preeclampsia. This was a prospective multicenter study in 7877 singleton pregnancies. The differences of the predictive performance between the IPPIC and CR models were compared. There were 141 women (1.79%) who developed preeclampsia, including 13 cases (0.17%) of early-onset preeclampsia and 128 cases (1.62%) of late-onset preeclampsia. In pregnancies that developed preeclampsia compared to unaffected pregnancies, median serum sFlt-1 levels and its MoMs were not significantly different (p>0.05). There was no significant association between gestational age at delivery and log10 sFlt-1 and log10 sFlt-1 MoM (p>0.05). The areas under the curve of CR models were significantly higher than the IPPIC models for the prediction of any-onset and late-onset preeclampsia but not for early-onset preeclampsia. In conclusion, there are no significant differences in the maternal serum sFlt-1 levels at 11-13 weeks' gestation between women who subsequently develop preeclampsia and those who do not. Moreover, the CR models for the prediction of any-onset and late-onset preeclampsia perform better than the IPPIC reported model.

Risk of Cardiovascular Hospital Admission After Exposure to Fine Particulate Pollution.

BACKGROUND: Heavy fine particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) pollution events continue to occur frequently in developing countries. OBJECTIVES: The authors conducted a case-crossover study aimed at exploring the association between heavy PM2.5 pollution events and hospital admission for cardiovascular diseases. METHODS: Hospital admissions for cardiovascular diseases were observed by Beijing Municipal Commission of Health and Family Planning Information Center from 2013 to 2017. Air pollution data were collected from the Beijing Municipal Environmental Monitoring Center. Distinct definitions were used to identify heavy and extremely heavy fine particulate pollution events. A conditional logistic regression model was used. The hospital admission burdens for cardiovascular disease were also estimated. RESULTS: A total of 2,202,244 hospital admissions for cardiovascular diseases and 222 days of extremely heavy PM2.5 pollution events (PM2.5 concentration ≥150 µg/m3) were observed. The ORs associated with extremely heavy PM2.5 pollution events lasting for 3 days or more for total cardiovascular disease, angina, myocardial infarction, ischemic stroke, and heart failure were 1.085 (95% CI: 1.077-1.093), 1.112 (95% CI: 1.095-1.130), 1.068 (95% CI: 1.037-1.100), 1.071 (95% CI: 1.053-1.090), and 1.060 (95% CI: 1.021-1.101), respectively. The numbers and days of cardiovascular disease hospital admission annually related to extremely heavy PM2.5 pollution events lasting for 1 day or more were 3,311 (95% CI: 2,969-3,655) and 37,020 (95% CI: 33,196-40,866), respectively. CONCLUSIONS: Heavy and extremely heavy PM2.5 pollution events resulted in substantial increased hospital admission risk for cardiovascular disease. With higher PM2.5 concentration and longer duration of heavy PM2.5 pollution events, a greater risk of cardiovascular hospital admission was observed.

Impact of childbirth policy changes on obstetric workload over a 13-year period in a regional referral center in China - implications on service provision planning.

BACKGROUND: We aimed to appraise the impact of the changing national childbirth policy since 2002, currently allowing two children per family, on obstetric workload in a regional referral center in China. METHODS: In a retrospective cohort study, temporal changes were examined in relation with maternal demographics, incidence of women with high risk pregnancies and resource statistics in our hospital in managing singleton viable pregnancies (birth from 28 weeks gestational age onwards) for the period 2005-2017. RESULTS: During this 13-year period, the number of singleton livebirths from 28 weeks gestational age onwards was 49,479. Annual numbers of births increased from 1,941 to 2005 to 5,777 in 2017. There were concomitant and significant increases in the incidence of multiparous women (10.6-50.8 %), of age ≥35 years (6.5-24.3 %), with prior caesarean Sec. (2.6-23.6 %), with ≥3 previous pregnancy terminations (1.0-4.9 %), with pre-gestational diabetes (0.2-0.9 %), and with chronic hypertension (0.2-1.2 %). There were associated increases in beds and staff complement and reduced average hospital stay. Nevertheless, while the workload of medical staff remained stable with increasing staff complement, that of midwives increased significantly as reflected by the total births: midwife ratio which increased from 194.1:1 to 320.9:1 (p < 0.001). CONCLUSIONS: In our hospital, progressively increasing numbers of annual births in combination with an increased incidence of women with high risk pregnancies took place following the revised national childbirth policy. Only the increase in medical and nursing, but not midwifery, staff was commensurate with workload. Remedial measures are urgently required before the anticipated progressive increase in care demand would overwhelm maternity care with potentially disastrous consequences.

PM2.5-associated risk for cardiovascular hospital admission and related economic burdens in Beijing, China.

BACKGROUND: The study of ambient air particulate matter (PM2.5)-associated health and economic burdens of cardiovascular disease are crucial for air pollution control and disease prevention strategies. Quantified evidence remains inadequate. OBJECTIVES: This study aimed to estimate the PM2.5 associated risk in cardiovascular hospital admission as well as attributable health burdens and economic costs. METHODS: A total of 2,202,244 hospital admission records of cardiovascular disease and six common clinical subtypes in Beijing were included. A time-stratified case-crossover design was applied to estimate the associations and the concentration-response curve. Then, the annual average additional hospital admissions, days of hospital stay, and hospital expenditures were evaluated from 2013 to 2017 and compared between 2017 and 2013. RESULTS: The results showed that each 10 µg/m3 increase in previous-day PM2.5 concentration was associated with a risk increase of 0.44% (95%CI: 0.40%, 0.47%) for cardiovascular disease, 0.66% (95%CI: 0.58%, 0.73%) for angina pectoris, 0.53% (95%CI: 0.39%, 0.66%) for chronic ischemic heart disease, 0.48% (95%CI: 0.34%, 0.63%) for myocardial infarction, 0.44% (95%CI: 0.29%, 0.60%) for hypertensive heart disease and 0.40% (95%CI: 0.27%, 0.52%) for ischemic stroke. There were 1938 PM2.5 attributed additional hospital admissions, resulting in 21,668 additional days in hospital, along with 5527.12 and 1947.04 ten-thousand of additional total hospital cost and self-afforded cost, respectively. Compared with 2013, the above-mentioned four burdens decreased by 18.17%, 28.80%, 18.90% and 13.72% in 2017, respectively. CONCLUSION: PM2.5 exposure was significantly associated with substantial burdens of cardiovascular hospital admission and economic expenditures. The results highlight the necessity of continuous PM2.5 control from the perspective of healthy and sustainable city development in urban China.

Chronic maternal hepatitis B virus infection and pregnancy outcome- a single center study in Kunming, China.

BACKGROUND: Chinese population has a high prevalence of chronic hepatitis B virus (HBV) infection, the impact of which on pregnancy outcome remains controversial. A single-center retrospective cohort study was performed in Kunming, a multi-ethnic city in south-western China to examine this issue. METHODS: The singleton pregnancies delivering at ≥28 weeks gestation under our care in 2005-2017 constituted the study cohort. Maternal characteristics and pregnancy outcome were compared between mothers with and without seropositivity for hepatitis B surface antigen (HBsAg) determined at routine antenatal screening. RESULTS: Among the 49,479 gravidae in the cohort, the 1624 (3.3%) HBsAg seropositive gravidae had a lower incidence of nulliparity (RR 0.963, 95% CI 0.935-0.992) and having received tertiary education (RR 0.829, 95% CI 0.784-0.827). There was no significant difference in the medical history, pregnancy complications, or labor or perinatal outcome, except that HBV carriers had significantly lower incidence of labor induction (RR 0.827, 95% CI 0.714-0.958) and of small-for-gestational age (SGA) infants (RR 0.854, 95% CI 0.734-0.994). On regression analysis, maternal HBV carriage was independently associated with spontaneous labor (aRR 1.231, 95% CI 1.044-1.451) and reduced SGA infants (aRR 0.842, 95% CI 0.712-0.997). CONCLUSIONS: Our 3.3% prevalence of maternal HBV infection was around the lower range determined in the Chinese population. The association with spontaneous labor and reduced SGA infants could have helped to promote the perpetuation of the infection through enhanced survival of the offspring infected at birth, thus explaining the high prevalence in the Chinese population.

Random forest model based fine scale spatiotemporal O3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017.

Ambient ozone (O3) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O3 (O3-8hmax) concentration, daily average O3 (O3-mean) concentration, and daily maximum 1h O3 (O3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R2 of sample-based O3-8hmax, O3-mean and O3-1hmax models were all greater than 0.80, while the R2 of site-based and date-based model were 0.68-0.87. From 2010 to 2017, O3-8hmax, O3-mean, and O3-1hmax concentrations in the BTH region increased by 4.18 µg/m3, 0.11 µg/m3, and 4.71 µg/m3, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O3 concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude.

Associations between short-term exposure to PM2.5 and stroke incidence and mortality in China: A case-crossover study and estimation of the burden.

Stroke and fine particulate matter (PM2.5) are two important public health concerns worldwide. Although numerous studies have reported the associations between PM2.5 and stroke, scientific evidence in China is incomplete, particularly the effect of PM2.5 on the acute incidence and national acute health burdens of stroke attributed to PM2.5 pollution. This study identified about 131,947 registered patients and 23,018 deaths due to stroke in 10 counties located in various regions from 2013 to 2017. Using a time-stratified case-crossover design, this study evaluated the associations between short-term exposure to PM2.5 and the risks of acute incidence and mortality for different types of stroke on the same spatiotemporal scale. With a 10 µg/m3 increase in the PM2.5 concentration, the acute incidence risk increased by 0.37% (0.15%, 0.60%) for stroke, 0.46% (0.21%, 0.72%) for ischemic stroke, and -0.13% (-0.73%, 0.48%) for hemorrhagic stroke. The corresponding values for the mortality risk were 0.71% (0.08%, 1.33%), 1.09% (0.05%, 2.14%), and 0.43% (-0.44%, 1.31%) for stroke, ischemic stroke and hemorrhagic stroke, respectively. Compared with the other groups, females and patients aged over 64 years presented higher incidence and mortality risks, while the group aged >75 years may exhibit a greater risk of mortality. Based on the estimated effects, we evaluated 43,300 excess deaths and 48,800 acute incidences attributed to short-term PM2.5 exposure across China in 2015. This study provided robust estimates of PM2.5-induced stroke incidence and mortality risks, and susceptible populations were identified. Excess mortality and morbidity attributed to short-term PM2.5 exposure indicate the necessity to implement health care and prevention strategies, as well as medical resource allocation for noncommunicable diseases in regions with high levels of air pollution.

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort.

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 µg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5.

Statistical spatial-temporal modeling of ambient ozone exposure for environmental epidemiology studies: A review.

BACKGROUND: Studies have discovered the adverse health impacts of ambient ozone. Most epidemiological studies explore the relationship between ambient ozone and health effects based on fixed site monitoring data. Fine modeling of ground-level ozone exposure conducted by statistical models has great advantages for improving exposure accuracy and reducing exposure bias. However, there is no review summarizing such studies. OBJECTIVES: A review is presented to summarize the basic process of model development and to provide some suggestions for researchers. METHODS: A search of PubMed, Web of Science and the Wanfang Database was performed for dates through July 1, 2019 to obtain relevant studies worldwide. We also examined the references of the articles of interest to ensure that as many articles as possible were included. RESULTS: The land use regression model (LUR model), random forest model and artificial neural network model have been used in this field. We summarized these studies in terms of model selection, data preparation, simulation scale selection, and model establishment and validation. Multiparameters are a major feature of models. Parameters that influence the formation of ground-level ozone concentrations and parameters that have been extremely important in previous articles should be considered first. The process of model establishment and validation is essentially a process of continuously optimizing the model performance, but there are certain differences in the specific models. CONCLUSION: This review summarized the basic process of the statistical model for ambient ozone exposure. We gave the applicable conditions and application scope of different models and summarized the advantages and disadvantages of various models in ozone modeling research. In the future, research is still needed to explore this area based on its own research purposes and capabilities.