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Extensive research has established the link between PM 2.5 exposure and blood pressure (BP) levels among normal individuals. However, the association between PM 2.5 components and BP levels in hypertensive patients has not been fully explored. In this study, 12 971 hypertensive cases from Jinchang cohort (in Jinchang City, China) with nearly 9 years of follow-up were enrolled. Based on the linear mixed-effect model, the effects of fine particulate matter (PM 2.5 ) and five major components [sulfate (SO 4 2- ), nitrate (NO 3 - ), ammonium (NH 4 + ), black carbon (BC) and organic matter (OM)]on BP [systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP)]were evaluated by single-component model, component-joint model and component-residual model, respectively. A positive correlation was found between PM 2.5 as well as its components (SO 4 2- , NO 3 - , NH 4 + , BC and OM) exposure and BP levels. The effects of SO 4 2- , BC and OM on BP were observed to be the most robust among the three models. Based on the results of interaction effects and stratified analysis, the effect of BC exposure on SBP, and the effect of PM 2.5 and its five components on PP were greater in female than in males. Compared with elderly hypertensive patients, OM had more significant effects on SBP, DBP and MAP in young and (or) middle-aged hypertensive patients. During the heating season, the effect of PM 2.5 and its components on BP was grater compared to the non-heating season. Meanwhile, PM 2.5 and its components have a greater influence on BP in patients with hypertension combined with diabetes. Therefore, the findings suggested that both PM 2.5 exposure and its components had a significant effect on BP in patients with hypertension. Women and young and middle-aged hypertensive patient were the sensitive population. The implementation of source control and reduction of PM 2.5 emission (mainly for SO 4 2- , BC and OM) may be of great significance to control BP level and could reduce the risk of cardiovascular disease in patients with hypertension., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Exposure to air pollution during pregnancy has been linked to birth defects. But the directions of studies on the associations between air pollutants exposure and effect on the incidence of congenital heart disease (CHDs) were inconsistent. To date, few studies were concentrated on the effects of both particulate matter and gaseous air pollutant exposure on CHDs across the full gestational week simultaneously. Our study aimed to investigate the critical exposure windows for each air pollutant throughout 40 gestational weeks. Data on CHDs, air pollution, and meteorological factors from 2013 to 2019 were collected in Lanzhou, China. A distributed lag nonlinear model combined with a quasi-Poisson regression model was applied to evaluate the weekly exposure-lag-response association between air pollutants levels and CHDs, and the subgroup analyses were conducted by gender (baby boy and baby girl). The study included 1607 mother-infant pairs. The results demonstrated that exposure of pregnant women to particulate matter ≤ 5 μm (PM 2.5 ) at lag 1-4 weeks was significantly associated with the risk of CHDs, and the strongest effects were observed in the lag 1 week (1.150, 95%CI 1.059-1.248). For exposure to particulate matter ≤ 10 μm (PM 10 ) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.075, 95% CI 1.026-1.128). For exposure to sulfur dioxide (SO 2 ) at lag 1-4 weeks, the strongest effects were observed in the lag 1 week (1.154, 95% CI 1.025-1.299). For exposure to carbon monoxide (CO) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.089, 95% CI 1.002-1.183). For exposure to ozone (O 3 ) concentration at lag 9-15 weeks, the strongest effects were observed in the lag 15 weeks (1.628, 95% CI 1.001-2.649). The cumulative effects of PM 2.5 , PM 10 , SO 2 , and CO along weeks with a maximum of 1.609 (95%CI 1.000-2.589), 1.286 (95%CI 1.007-1.641), 1.648 (95%CI 1.018-2.668), and 1.368 (95%CI 1.003, 1.865), respectively. The effects were obvious in the initial gestational weeks too. Through the gender stratification analysis, the air pollutants with significant effects were PM 2.5 for baby boys and PM 2.5 , PM 10 , SO 2 , CO, NO 2 , and O 3 for baby girl. For the relationship between CHDs and air pollution in Lanzhou, PM 2.5 , PM 10 , SO 2 , CO, and O 3 played an important role in the initial gestational weeks, especially for baby girl., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

The aim of this study was to assess the effects of air pollutants on hospital admissions for respiratory disease (RD) by using distributed lag nonlinear model (DLNM) in Lanzhou during 2014-2019. In this study, the dataset of air pollutants, meteorological, and daily hospital admissions for RD in Lanzhou, from January 1st, 2014 to December 31st, 2019, were collected from three national environmental monitoring stations, China meteorological data service center, and three large general hospitals, respectively. A time-series analysis with DLNM was used to estimate the associations between air pollutants and hospital admissions for RD including the stratified analysis of age, gender, and season. The key findings were expressed as the relative risk (RR) with a 95% confidence interval (CI) for single-day and cumulative lag effects (0-7). A total of 90, 942 RD hospitalization cases were identified during the study period. The highest association (RR, 95% CI) of hospital admissions for RD and PM 2.5 (1.030, 1.012-1.049), and PM 10 (1.009, 1.001-1.015), and NO 2 (1.047, 1.024-1.071) were observed at lag 07 for an increase of 10 μg/m 3 in the concentrations, and CO at lag07 (1.140, 1.052-1.236) for an increase of 1 mg/m 3 in the concentration. We observed that the RR estimates for gaseous pollutants (e.g., CO and NO 2 ) were larger than those of particulate matter (e.g., PM 2.5 and PM 10 ). The harmful effects of PM 2.5 , PM 10 , NO 2 , and CO were greater in male, people aged 0-14 group and in the cold season. However, no significant association was observed for SO 2 , O 3 8h, and total hospital admissions for RD. Therefore, some effective intervention strategies should be taken to strengthen the treatment of the ambient air pollutants, especially gaseous pollutants (e.g., CO and NO 2 ), thereby, reducing the burden of respiratory diseases., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

Currently few studies have explored the relationship between exposure to gaseous pollutants and metabolic health indicators in patients, especially in patients with metabolic syndrome (Mets). This study collected 15,520 patients with Mets in a prospective cohort of nearly 50,000 people with 7 years of follow-up from 2011 to 2017, and matched air pollutants and meteorological data during the same period. The mixed effects model was used to analyze the relationship between different short exposure windows (1-week, 1-month, 2-month, and 3-month) of gaseous pollutants (SO 2 , NO 2, and O 3 ) and the metabolic health indicators of patients after controlled the confounding factors. Stratified analysis was performed by demographic characteristics and behavioral factors. The effects of gaseous pollutants on patients with different Met components were also analyzed. The results showed that the short-term exposure to SO 2 , NO 2, and O 3 had a certain effect on the metabolic health indicators of patients with Mets in different exposure windows, and with the extension of the exposure window period, the effects increased. The stratified analysis showed that gender, age, and life behaviors might modify these detrimental effects. In addition, the effects of gaseous pollutants on metabolic health indicators in G4 and G7 were more obvious than other Met components, and the effects of gaseous pollutants on the level of LDL-C were found to be statistically significant in most components. Therefore, patients with Mets should pay more attention to the influence of gaseous pollutants to take appropriate protection to reduce potential health risk., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Few studies have evaluated the association between air pollutants and neural tube defects (NTDs). Moreover, the existing research ignores the lag effect of air pollution on health and provides inconsistent epidemiological evidence. We aim to estimate the association between air pollution and NTDs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was collected from the Birth Defects Surveillance Network in Lanzhou from September 1, 2014, to December 31, 2019. Air quality and meteorological data were collected from ambient air monitoring stations and China Meteorological Data Network. The log connection function of the Poisson distribution function is used to establish a DLNM model to estimate the exposure-effect relationship and exposure-lag relationship association between air pollutants levels and NTDs. There were 320,787 perinatal infants in Lanzhou from September 1, 2014, to December 31, 2019, and 486 cases of NTDs (1.5‰). The result indicates that exposure to inhalable particles (PM 10 ) at lag 2-4 weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.048, 95%CI, 1.015-1.084). Exposure to fine particulate matter (PM 2.5 ) at the lag 2 week was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.077, 95%CI, 1.004-1.155). Exposure to sulfur dioxide (SO 2 ) and nitrogen dioxide (NO 2 ) at lag 3-6weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 4 week (RR=1.220, 95%CI, 1.105-1.348; RR=1.143, 95%CI, 1.048-1.245). This study provides further evidence that exposure to air pollutants in the first trimester of pregnancy significantly increases the risk of neural tube defects., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Current studies on air pollutant exposure during pregnancy and orofacial clefts (OFCs) have inconsistent results, and few studies have investigated refined susceptible windows for OFCs. We aim to estimate association between air pollution and OFCs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was obtained from Birth Defects Surveillance Network in Lanzhou from 2014 to 2019. Air pollution data and temperature data were obtained from ambient air monitoring stations and China Meteorological Data Network, respectively. A distribution lag nonlinear model (DLNM) was applied to estimate weekly-exposure-lag-response association between air pollutant levels and OFCs. The study included 320,787 perinatal infants from 2014 to 2019, of which 685 (2.14‰) were OFCs. The results demonstrated that exposure of pregnant women to aerodynamic diameter ≤ 10 μm (PM 10 ) at lag 4-5 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 4 week (RR = 1.029, 95% CI = 1.001-1.057). Exposure to sulfur dioxide (SO 2 ) at lag 2-4 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 3 week (RR = 1.096, 95% CI = 1.041-1.177). This study provides further evidence that exposure to air pollution increases the risk of OFCs in the first trimester of pregnancy., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Some studies suggested that 24-h temperature change (TC24) was one of the potential risk factors for human health. However, evidence of the short-term effect of TC24 on outpatient and emergency department (O&ED) visits and hospitalizations for cause-specific cardiovascular diseases (CVDs) is still limited. The aim of this study is to explore the short-term effects of TC24 on O&ED visits and hospitalizations for CVDs in northwest China which is an area with large temperature variation. The O&ED visits records for CVDs of 3 general hospitals and the inpatient records for CVDs of 4 general hospitals were collected from January 1, 2013, to December 31, 2016, in Jinchang City, northwest China. Meteorological and air pollution data were also obtained during the same study period from local meteorological monitoring station and environmental monitoring station, respectively. A generalized additive model (GAM) with Poisson regression was employed to analyze the effects of TC24 on O&ED visits and hospitalizations for CVDs. V-shaped relationship were found between TC24 and O&ED visits and hospitalizations for CVDs, including total CVD, hypertension, coronary heart disease (CHD) and stroke. Stratified analysis showed that men and patients over 65 years old were more susceptible to temperature changes. The estimates in non-heating months were higher than in full year. TC24 can affect the O&ED visits and hospitalizations for CVDs in this study. This study provides useful data for policy makers to better prepare local responses to the impact of changes in temperature on population health., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objectives: We aimed to assess the association between long-term exposure to ambient PM 10 and risk of diabetes incidence, based on the "Jinchang Cohort" platform in the Northwest of China., Methods: We selected 19884 subjects who had not yet developed diabetes in the baseline and had completed survey information from "Jinchang Cohort". The residential address was used to match the nearest pollution monitoring station for each subject, and the average concentration of PM 10 from baseline to follow-up were used as an estimate of individual exposure level. Cox regression model and restricted cubic splines functions were used to evaluate the effects of PM 10 on the incidence of diabetes and the dose-response relationship after adjusting for confounding covariates., Results: We observed 791 new-onset diabetics with a total follow-up of 45254.16 person-years (incidence rate of 17.48 per 1000 person-years). The risk of diabetes incidence increased by 17% (HR = 1.17, 95%CI: 1.08-1.26) per 10μg/m 3 increase in environmental PM 10 , and the risk rises gradually with the rise of PM 10 concentration. Comparing with the first quartile of PM 10 , the fully adjusted HRs (95%CI) for incident diabetes from the second to the fourth quartile of PM 10 were 1.15 (95%CI: 0.93-1.43), 1.50 (95%CI: 1.22-1.84) and 1.44 (95%CI: 1.15-1.79), respectively (P for trend<0.001). Stratified analyses suggested that the risk of diabetes incidence associated with ambient PM 10 was higher in female, young to middle-aged people, overweight and obese subjects, and subjects with FPG level at baseline lower than 5.6 mmol/L., Conclusions: Long-term exposure to ambient PM 10 significantly associated with a higher risk of diabetes development. Some urgent strategies may be advocated to reduce air pollution that can aid in preventing the prevalence of diabetes in the population., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Air pollution exposure may play an adverse role in diabetes. However, little data are available directly evaluating the effects of air pollution exposure in blood lipids of which dysfunction has been linked to diabetes or its complications. We aimed to evaluate the association between air pollution and lipids level among type 2 diabetic patients in Northwest China. We performed a population-based study of 3912 type 2 diabetes patients in an ongoing cohort study in China. Both spline and multiple linear regressions analysis were used to examine the association between short-term exposure to PM 10 , SO₂, NO₂ and total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). By spline analyses, we observed that the relationship between SO₂ and HDL-C and LDL-C was shown to be non-linear ( p &#95;non-lin-association = 0.0162 and 0.000). An inverted U-shaped non-linear relationship between NO₂ and LDL-C was found ( p &#95;non-lin-association < 0.0001). A J-shaped non-linear relationship between PM 10 and TC, HDL-C ( p &#95;non-lin-association = 0.0173, 0.0367) was also revealed. In linear regression analyses, a 10 μg/m³ increment in SO₂ was associated with 1.31% (95% CI: 0.40-2.12%), 3.52% (95% CI: 1.07-6.03%) and 7.53% (95% CI: 5.98-9.09%) increase in TC, TG and LDL-C, respectively. A 10 μg/m³ increment in PM 10 was associated with 0.45% (95% CI: 0.08-0.82%), 0.29% (95% CI: 0.10-0.49%) and 0.83% (95% CI: 0.21-1.45%) increase in TC, HDL-C and LDL-C, respectively. For NO₂, an increment of 10 μg/m³ was statistically associated with -3.55% (95% CI: -6.40-0.61%) and 39.01% (95% CI: 31.43-47.03%) increase in HDL-C and LDL-C. The adverse effects of air pollutants on lipid levels were greater in female and elder people. Further, we found SO₂ and NO₂ played a more evident role in lipid levels in warm season, while PM 10 appeared stronger in cold season. The findings suggest that exposure to air pollution has adverse effects on lipid levels among type 2 diabetes patients, and vulnerable people may pay more attention on severe air pollution days., Competing Interests: The authors declare no conflict of interest.

We aimed to assess the association between long-term exposure to ambient PM 10 and risk of diabetes incidence, based on the "Jinchang Cohort" platform in the Northwest of China. We selected 19884 subjects who had not yet developed diabetes in the baseline and had completed survey information from "Jinchang Cohort". The residential address was used to match the nearest pollution monitoring station for each subject, and the average concentration of PM 10 from baseline to follow-up were used as an estimate of individual exposure level. Cox regression model and restricted cubic splines functions were used to evaluate the effects of PM 10 on the incidence of diabetes and the dose-response relationship after adjusting for confounding covariates. We observed 791 new-onset diabetics with a total follow-up of 45254.16 person-years (incidence rate of 17.48 per 1000 person-years). The risk of diabetes incidence increased by 17% (HR = 1.17, 95%CI: 1.08–1.26) per 10μg/m3 increase in environmental PM 10 , and the risk rises gradually with the rise of PM 10 concentration. Comparing with the first quartile of PM 10 , the fully adjusted HRs (95%CI) for incident diabetes from the second to the fourth quartile of PM 10 were 1.15 (95%CI: 0.93–1.43), 1.50 (95%CI: 1.22–1.84) and 1.44 (95%CI: 1.15–1.79), respectively (P for trend<0.001). Stratified analyses suggested that the risk of diabetes incidence associated with ambient PM 10 was higher in female, young to middle-aged people, overweight and obese subjects, and subjects with FPG level at baseline lower than 5.6 mmol/L. Long-term exposure to ambient PM 10 significantly associated with a higher risk of diabetes development. Some urgent strategies may be advocated to reduce air pollution that can aid in preventing the prevalence of diabetes in the population. • To assess the association between exposure to ambient PM 10 and diabetes incidence. • Ambient PM 10 is positively associated with diabetes incidence. • The risk of diabetes incidence rise gradually with the increase of PM 10. • Female, younger age, higher BMI and FPG<5.6mmol/L were more susceptible to PM 10. [ABSTRACT FROM AUTHOR]