Associations of long-term exposure to ambient PM1 with hypertension and blood pressure in rural Chinese population: The Henan rural cohort study

Association between long-term exposure to PM2.5 chemical components and metabolic syndrome in middle-aged and older adults

Background

Previous studies indicated that exposure to ambient fine particulate matter (PM2.5) could increase the risk of metabolic syndrome (MetS). However, the specific impact of PM2.5 chemical components remains uncertain.

Methods

A national cross-sectional study of 12,846 Chinese middle-aged and older adults was conducted. Satellite-based spatiotemporal models were employed to determine the 3-year average PM2.5 components exposure, including sulfates (SO4 2-), nitrates (NO3 -), ammonia (NH4 +), black carbon (BC), and organic matter (OM). Generalized linear models were used to investigate the associations of PM2.5 components with MetS and the components of MetS, and restricted cubic splines curves were used to establish the exposure-response relationships between PM2.5 components with MetS, as well as the components of MetS.

Results

MetS risk increased by 35.1, 33.5, 33.6, 31.2, 32.4, and 31.4% for every inter-quartile range rise in PM2.5, SO4 2-, NO3 -, NH4 +, OM and BC, respectively. For MetS components, PM2.5 chemical components were associated with evaluated risks of central obesity, high blood pressure (high-BP), high fasting glucose (high-FBG), and low high-density lipoprotein cholesterol (low-HDL).

Conclusion

This study indicated that exposure to PM2.5 components is related to increased risk of MetS and its components, including central obesity, high-BP, high-FBG, and low-HDL. Moreover, we found that the adverse effect of PM2.5 chemical components on MetS was more sensitive to people who were single, divorced, or widowed than married people.

How long-term PM exposure may affect all-site cancer mortality: Evidence from a large cohort in southern China

BACKGROUND

Evidence of a potential causal link between long-term exposure to particulate matter (PM) and all-site cancer mortality from large population cohorts remained limited and suffered from residual confounding issues with traditional statistical methods.

AIMS

We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods.

METHODS

We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality.

RESULTS

With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results.

CONCLUSION

This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.

Long-term associations of PM1 versus PM2.5 and PM10 with asthma and asthma-related respiratory symptoms in the middle-aged and elderly population

Background

Few studies have compared the associations between long-term exposures to particulate matters (aerodynamic diameter ≤1, ≤2.5 and ≤10 µm: PM1, PM2.5 and PM10, respectively) and asthma and asthma-related respiratory symptoms. The objective of the present study was to compare the strength of the aforementioned associations in middle-aged and elderly adults.

Methods

We calculated the mean 722-day personal exposure estimates of PM1, PM2.5 and PM10 at 1 km×1 km spatial resolution between 2013 and 2019 at individual levels from China High Air Pollutants (CHAP) datasets. Using logistic regression models, we presented the associations as odds ratios and 95% confidence intervals, for each interquartile range (IQR) increase in PM1/PM2.5/PM10 concentration. Asthma denoted a self-reported history of physician-diagnosed asthma or wheezing in the preceding 12 months.

Results

We included 7371 participants in COPD surveillance from Guangdong, China. Each IQR increase in PM1, PM2.5 and PM10 was associated with a greater odds (OR (95% CI)) of asthma (PM1: 1.22 (1.02-1.45); PM2.5: 1.24 (1.04-1.48); PM10: 1.30 (1.07-1.57)), wheeze (PM1: 1.27 (1.11-1.44); PM2.5: 1.30 (1.14-1.48); PM10: 1.34 (1.17-1.55)), persistent cough (PM1: 1.33 (1.06-1.66); PM2.5: 1.36 (1.09-1.71); PM10: 1.31 (1.02-1.68)) and dyspnoea (PM1: 2.10 (1.84-2.41); PM2.5: 2.17 (1.90-2.48); PM10: 2.29 (1.96-2.66)). Sensitivity analysis results were robust after excluding individuals with a family history of allergy. Associations of PM1, PM2.5 and PM10 with asthma and asthma-related respiratory symptoms were slightly stronger in males.

Conclusion

Long-term exposure to PM is associated with increased risks of asthma and asthma-related respiratory symptoms.

Effect modification of diet and vitamins on the association between air pollution particles of different diameters and hypertension: A 12-year longitudinal cohort study in densely populated areas of China

INTRODUCTION

Particulate matter (PM) is identified as one of the exacerbating and triggering factors for hypertension. Diet intake and the consumption of vitamins may potentially moderate the impact of PM on hypertension.

METHODS

A 12-year longitudinal cohort study was conducted on a population in densely populated areas of China. Residual balancing with weighted methods was employed to control for time-varying and no time-varying confounding factors. Stratified Cox proportional hazards models were conducted to examine the moderating effects of diet and vitamins on the risk of hypertension with PM.

RESULTS

There was a significant positive association between long-term exposure to different diameter PM and the risk of developing hypertension. The hazard ratios (HRs) for hypertension were 1.0200 (95 % CIs: 1.0147, 1.0253) for PM1, 1.0120 (95 % CIs: 1.0085, 1.0155) for PM2.5, and 1.0074 (95 % CIs, 1.0056, 1.0092) for PM10. The diet and vitamins moderated these associations, the intake of healthy foods and vitamins exhibited a significant positive moderating effect on the relationship between PM exposure and hypertension risk. Among all participants, the high intake of fruit (PM1 (HRs: 1.0102, 95 % CIs: 1.0024, 1.0179), PM2.5 (HRs: 1.0060, 95 % CIs: 1.0011, 1.0109), and PM10 (HRs: 1.0044, 95 % CIs: 1.0018, 1.0070)) and vitamin E (PM1 (HRs: 1.0143, 95 % CIs: 1.0063, 1.0223), PM2.5 (HRs:1.0179, 95 % CIs: 1.0003, 1.0166), and PM10 (HRs: 1.0042, 95 % CIs: 1.0008, 1.0075)) with lower risk of hypertension than the overall level and low intake of related foods and vitamins, exhibited a strong positive moderating effect on the relationship between PM and hypertension. Similar trends were observed for the intake of fish, root food, whole grains, eggs, fungus food, vitamin B2, B3. However, Na, meat, sugary and alcoholic exhibited opposite trends. The moderating effect of vitamin E intake was stronger than vitamin B and C.

CONCLUSIONS

Diet and vitamins intake may moderate the association between PM exposure and the risk of hypertension in adults.

Challenges of Air Pollution and Health in East Asia

PURPOSE OF REVIEW

Air pollution has been a serious environmental and public health issue worldwide, particularly in Asian countries. There have been significant increases in epidemiological studies on fine particulate matter (PM2.5) and ozone pollution in East Asia, and an in-depth review of epidemiological evidence is urgent. Thus, we carried out a systematic review of the epidemiological research on PM2.5 and ozone pollution in East Asia released in recent years.

RECENT FINDINGS

Recent studies have indicated that PM2.5 and ozone are the most detrimental air pollutants to human health, resulting in substantial disease burdens for Asian populations. Many epidemiological studies of PM2.5 and ozone have been mainly performed in three East Asian countries (China, Japan, and South Korea). We derived the following summary findings: (1) both short-term and long-term exposure to PM2.5 and ozone could raise the risks of mortality and morbidity, emphasizing the need for continuing improvements in air quality in East Asia; (2) the long-term associations between PM2.5 and mortality in East Asia are comparable to those observed in Europe and North America, whereas the short-term associations are relatively smaller in magnitude; and (3) further cohort and intervention studies are required to yield robust and precise evidence that can promote evidence-based policymaking in East Asia. This updated review presented an outline of the health impacts of PM2.5 and ozone in East Asia, which may be beneficial for the development of future regulatory policies and standards, as well as for designing subsequent investigations.

Long-term exposure to PM2.5 and its components is associated with elevated blood pressure and hypertension prevalence: Evidence from rural adults

INTRODUCTION

The toxicity of fine particulate matter (PM2.5) is determined by its components, while the evidence regarding associations of PM2.5 components with blood pressure (BP) is limited, especially in rural areas.

OBJECTIVES

This study aimed to explore the associations of PM2.5 and its chemical components with systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP), mean artery pressure (MAP) levels and hypertension prevalence, and to identify key components in Chinese rural areas.

METHODS

39,211 adults from the Henan Rural Cohort were included during 2015-2017. Different periods of PM2.5 and chemical components were estimated by hybrid satellite model. The single-pollutant, component-PM2.5 model, component-residual model and component-proportion model were applied to explore the associations of pollutants with BP levels and hypertension prevalence. Exposure-response (E-R) relationships, stratified analyses and sensitivity analyses were used to explore these associations further.

RESULTS

12,826 (32.71%) were identified with hypertension. For each 1 μg/m3 increase of pollutants, the adjusted odds ratio (OR) for hypertension prevalence was 1.03 for PM2.5 mass, 1.40 for BC, 1.16 for NH4+, 1.08 for NO3-, 1.17 for OM, 1.12 for SO42- and 1.25 for SOIL in the single-pollutant model. BC and SOIL were statistically significant in the component-PM2.5 model, component-residual model and component-proportion model. Similarly, associations of these pollutants with elevated BP levels were also found in aforementioned four models. These pollutants produced a stronger association with SBP than DBP, PP and MAP. Most of associations were non-linear in E-R relationships. The groups of older, the men, with lower per capita monthly income, lower educational level and higher BMI were more vulnerable to these pollutants in stratified analyses. The results remained stable in sensitivity analyses.

CONCLUSION

Long-term exposure to PM2.5 and its components, especially BC and SOIL, was associated with elevated BP and hypertension prevalence in rural adults, and decreasing pollutants may provide additional benefits.

Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

Association between ambient PM1 and the prevalence of chronic kidney disease in China: A nationwide study

Particulate of diameter ≤ 1 µm (PM1) presents a novel risk factor of adverse health effects. Nevertheless, the association of PM1 with the risk of chronic kidney disease (CKD) in the general population is not well understood, particularly in regions with high PM1 levels like China. Based on a nationwide representative survey involving 47,204 adults and multi-source ambient air pollution inversion data, the present study evaluated the association of PM1 with CKD prevalence in China. The two-year average PM1, particulate of diameter ≤ 2.5 µm (PM2.5), and PM1-2.5 values were accessed using a satellite-based random forest approach. CKD was defined as estimated glomerular filtration rate < 60 ml/min/1.73 m2 or albuminuria. The results suggested that a 10 μg/m3 rise in PM1 was related to a higher CKD risk (odds ratio [OR], 1.13; 95% confidence interval [CI] 1.08-1.18) and albuminuria (OR, 1.11; 95% CI, 1.05-1.17). The association between PM1 and CKD was more evident among urban populations, older adults, and those without comorbidities such as diabetes or hypertension. Every 1% increase in the PM1/PM2.5 ratio was related to the prevalence of CKD (OR, 1.03; 95% CI, 1.03-1.04), but no significant relationship was found for PM1-2.5. In conclusion, the present study demonstrated long-term exposure to PM1 was associated with an increased risk of CKD in the general population and PM1 might play a leading role in the observed relationship of PM2.5 with the risk of CKD. These findings provide crucial evidence for developing air pollution control strategies to reduce the burden of CKD.

Long-term exposure to particulate matter is associated with elevated blood pressure: Evidence from the Chinese plateau area

Background

Ambient air pollution could increase the risk of hypertension; however, evidence regarding the relationship between long-term exposure to particulate matter and elevated blood pressure in plateau areas with lower pollution levels is limited.

Methods

We assessed the associations of long-term exposure to particulate matter (PM, PM1, PM2.5, and PM10) with hypertension, diastolic blood pressure (DBP), systolic blood pressure (SBP) and pulse pressure (PP) in 4.235 Tibet adults, based on the baseline of the China multi-ethnic cohort study (CMEC) in Lhasa city, Tibet from 2018-19. We used logistic regression and linear regression models to evaluate the associations of ambient PM with hypertension and blood pressure, respectively.

Results

Long-term exposure to PM1, PM2.5, and PM10 is positively associated with hypertension, DBP, and SBP, while negatively associated with PP. Among these air pollutants, PM10 had the strongest effect on hypertension, DBP, and SBP, while PM2.5 had the strongest effect on PP. The results showed for hypertension odds ratio (OR) = 1.99; 95% confidence interval (CI) = 1.58, 2.51 per interquartile range (IQR) μg/m3 increase in PM1, OR = 1.93; 95% CI = 1.55, 2.40 per IQR μg/m3 increase in PM2.5, and OR = 2.12; 95% CI = 1.67, 2.68 per IQR μg/m3 increase in PM10.

Conclusions

Long-term exposure to ambient air pollution was associated with an increased risk of hypertension, elevated SBP and DBP levels, and decreased PP levels. To reduce the risk of hypertension and PP reduction, attention should be paid to air quality interventions in plateau areas with low pollution levels.

From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey

Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM1, PM2.5, PM10) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from -0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (-0.241 in Romania and -0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality.

Long-term exposure to PM1 is associated with increased prevalence of metabolic diseases: evidence from a nationwide study in 123 Chinese cities

Exposure to particulate matter (PM) has been linked to metabolic diseases. However, the effects of PM with an aerodynamic diameter ≤ 1.0 µm (PM1) on metabolic diseases remain unclear. This study is aimed at assessing the associations of PM1 with metabolic disease risk and quantifying the concentration-response (C-R) relationship of PM1 with metabolic disease risk. A national cross-sectional study was conducted, including 12,495 middle-aged and older adults in 123 Chinese cities. The two-year average concentration of PM1 was evaluated using satellite-based spatiotemporal models. Metabolic diseases, including abdominal obesity, diabetes, hypertension, dyslipidemia, and metabolic syndrome, were identified based on physical examination, blood standard biochemistry examination, and self-reported disease histories. Generalized linear models and C-R curves were used to evaluate the associations of PM1 with metabolic diseases. A total of 12,495 participants were included in this study, with a prevalence of 45.73% for abdominal obesity, 20.22% for diabetes, 42.46% for hypertension, 41.01% for dyslipidemia, and 33.78% for metabolic syndrome. The mean ± standard deviation age of participants was 58.79 ± 13.14 years. In addition to dyslipidemia, exposure to PM1 was associated with increased risks of abdominal obesity, diabetes, hypertension, and metabolic syndrome. Each 10 μg/m3 increase in PM1 concentrations was associated with 39% (odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.33, 1.46) increase in abdominal obesity, 18% (OR = 1.18, 95%CI 1.12, 1.25) increase in diabetes, 11% (OR = 1.11, 95%CI 1.06, 1.16) increase in hypertension, and 25% (OR = 1.25, 95%CI 1.19, 1.31) in metabolic syndrome, respectively. C-R curves showed that the OR values of abdominal obesity, diabetes, hypertension, and metabolic syndrome were increased gradually with the increase of PM1 concentrations. Subgroup analysis indicated that exposure to PM1 was associated with increased metabolic disease risks among participants with different lifestyles and found that solid fuel users were more susceptible to PM1 than clean fuel users. This national cross-sectional study indicated that exposure to higher PM1 might increase abdominal obesity, diabetes, hypertension, and metabolic syndrome risk, and solid fuel use might accelerate the adverse effects of PM1 on metabolic syndrome risk. Further longitudinal cohort studies are warranted to establish a causal inference between PM1 exposure and metabolic disease risk.

Sex Associations Between Air Pollution and Estimated Atherosclerotic Cardiovascular Disease Risk Determination

Objective: The purpose of this study was to investigate the sex correlations of particulate matters (PM2.5, PM10, PM2.5-10), NO2 and NOx with ASCVD risk in the UK Biobank population. Methods: Among 285,045 participants, pollutants were assessed and correlations between ASCVD risk were stratified by sex and estimated using multiple linear and logistic regressions adjusted for length of time at residence, education, income, physical activity, Townsend deprivation, alcohol, smocking pack years, BMI and rural/urban zone. Results: Males presented higher ASCVD risk than females (8.63% vs. 2.65%, p < 0.001). In males PM2.5, PM10, NO2, and NOx each were associated with an increased ASCVD risk >7.5% in the adjusted logistic models, with ORs [95% CI] for a 10 μg/m3 increase were 2.17 [1.87-2.52], 1.15 [1.06-1.24], 1.06 [1.04-1.08] and 1.05 [1.04-1.06], respectively. In females, the ORs for a 10 μg/m3 increase were 1.55 [1.19-2.05], 1.22 [1.06-1.42], 1.07 [1.03-1.10], and 1.04 [1.02-1.05], respectively. No association was observed in both sexes between ASCVD risk and PM2.5-10. Conclusion: Our findings may suggest the possible actions of air pollutants on ASCVD risk.

Association between long-term exposure to ambient particulate matter and blood pressure, hypertension: an updated systematic review and meta-analysis

Evidence of more recent studies should be updated to evaluate the effect of long-term exposure to particulate matter (PM) on blood pressure and hypertension.        Studies of long-term effects of PM₁, PM_2.5 and PM₁₀ on blood pressure (SBP, DBP, MAP), hypertension were searched in Pubmed, Web of Science and Embase before May, 2021. Meta-analysis of 41 studies showed that exposure to PM₁, PM_2.5 was associated with SBP (1.76 mmHg (95%CI:0.71, 2.80) and 0.63 mmHg (95%CI:0.40, 0.85), per 10 μg/m³ increase in PM), all three air pollutants (PM₁, PM_2.5, PM₁₀) was associated with DBP (1.16 mmHg (95%CI:0.34, 1.99), 0.31 mmHg (95%CI:0.16, 0.47), 1.17 mmHg (95%CI:0.24, 2.09), respectively. As for hypertension, PM₁, PM_2.5 and PM₁₀ were all significantly associated with higher risk of hypertension (OR=1.27 (95%CI:1.06, 1.52), 1.15 (95%CI:1.10, 1.20) and 1.11 (95%CI:1.07, 1.16). In conclusion, our study indicated a positive association between long-term exposure to particulate matter and increased blood pressure, hypertension.

Associations of fine particulate matter and its metal constituents with blood pressure: A panel study during the seventh World Military Games

Evidence is needed to elucidate the association of blood pressure (BP) changes with metal constituents in fine particulate matter (PM_2.5). Therefore, we designed a longitudinal panel study enrolling 70 healthy students from Wuhan University in the context of the seventh World Military Games (the 7th WMG) from September 2019 to January 2020. A total of eight visits were conducted before, during, and after the 7th WMG. During every visit, each participant was asked to carry a personal PM_2.5 monitor to measure hourly PM_2.5 levels for three consecutive days. Questionnaire investigation and physical examination were completed on the fourth day. We analyzed ten metal constituents of ambient PM_2.5 collected from the fixed station, and blood pressure was recorded during each visit. The linear mixed-effects models were performed to evaluate associations of metal constituents and blood pressure measurements. We observed a dramatic variation of PM_2.5 concentration ranging from 7.38 to 132.04 μg/m³. A 10 μg/m³ increment of PM_2.5 was associated with an increase of 0.64 mmHg (95% CI: 0.44, 0.84) in systolic BP (SBP), 0.40 mmHg (0.26, 0.54) in diastolic BP (DBP), 0.31 mmHg (0.15, 0.47) in pulse pressure (PP) and 0.44 mmHg (0.26, 0.62) in mean artery pressure (MAP), respectively. For metal constituents in PM_2.5, robust positive associations were observed between BP and selenium, manganese, arsenic, cadmium, and thallium. For example, for an IQR (0.93 ng/m³) increment of selenium, SBP and MAP elevated by 0.98 mmHg (0.09, 1.87) and 0.71 mmHg (0.03, 1.39), respectively. Aluminum was found to be robustly associated with decreased SBP, DBP, and MAP. The study indicated that exposure to PM_2.5 total mass and metal constituents including selenium, manganese, arsenic, cadmium, and thallium were associated with the elevated BP.

Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China

BACKGROUND

The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM₁ which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas.

METHODS

A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM₁, PM_2.5, and PM₁₀ at 1 km² spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels.

RESULTS

37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM₁, PM_2.5, and PM₁₀ tend to be higher in the low-exposure group than in the general population.

CONCLUSIONS

We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM₁compared to large particles and among certain vulnerable subgroups.

Associations of long-term exposure to air pollution, physical activity with blood pressure and prevalence of hypertension: the China Health and Retirement Longitudinal Study

Background

Long-term exposure to air pollution and physical activity (PA) are linked to blood pressure and hypertension. However, the joint effect of air pollution and PA on blood pressure and hypertension are still unknown in Chinese middle-aged and older adults.

Methods

A total of 14,622 middle-aged and older adults from the China Health and Retirement Longitudinal Study wave 3 were included in this study. Ambient air pollution [particulate matter with diameter ≤ 2.5 μm (PM_2.5), or ≤10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbonic oxide (CO)] were estimated using satellite-based spatiotemporal models. PA was investigated using International Physical Activity Questionnaire. Generalized linear models were used to examine the associations of air pollution, PA score with blood pressure [systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP)], and the prevalence of hypertension. Subgroup analysis was conducted to investigate the effects of air pollution on blood pressure and the prevalence of hypertension in different PA groups.

Results

The results showed that for each inter-quartile range (IQR) increase in PM_2.5 (25.45 μg/m³), PM₁₀ (40.56 μg/m³), SO₂ (18.61 μg/m³), NO₂ (11.16 μg/m³), CO (0.42 mg/m³) and PA score (161.3 MET/h-week), the adjusted odd ratio (OR) of hypertension was 1.207 (95% confidence interval (CI): 1.137, 1.281), 1.189 (95%CI: 1.122, 1.260), 1.186 (95%CI: 1.112, 1.266), 1.186 (95%CI: 1.116, 1.260), 1.288 (95%CI: 1.223, 1.357), 0.948 (95%CI: 0.899, 0.999), respectively. Long-term exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO was associated with increased SBP, DBP, and MAP levels. For example, each IQR increase in PM_2.5 was associated with 1.20 mmHg (95%CI: 0.69, 1.72) change in SBP, 0.66 mmHg (95%CI: 0.36, 0.97) change in DBP, and 0.84 mmHg (95%CI: 0.49, 1.19) change in MAP levels, respectively. Each IQR increase in PA score was associated with -0.56 mmHg (95%CI: -1.03, -0.09) change in SBP, -0.32 mmHg (95%CI: -0.59, -0.05) change in DBP, and -0.33 mmHg (95%CI: -0.64, -0.02) change in MAP levels, respectively. Subgroup analysis found that the estimated effects in the sufficient PA group were lower than that in the insufficient PA group.

Conclusion

Long-term exposure to air pollutants is associated with increased blood pressure and hypertension risk, while high-level PA is associated with decreased blood pressure and hypertension risk. Strengthening PA might attenuate the adverse effects of air pollution on blood pressure and hypertension risk.

The impact of prolonged exposure to air pollution on the incidence of chronic non-communicable disease based on a cohort in Tianjin

Evidence on the associations of prolonged ambient pollutants exposure with chronic non-communicable diseases among middle-aged and elderly residents is still limited. This prospective cohort study intends to investigate the long-term effects of ambient pollution on hypertension and diabetes incidence among relatively older residents in China. Individual particulate matter exposure levels were estimated by satellite-based model. Individual gaseous pollutants exposure levels were estimated by Inverse Distance Weighted model. A Cox regression model was employed to assess the risks of hypertension and diabetes morbidity linked to air pollutants exposures. The cross-product term of ambient pollutants exposure and covariates was further added into the regression model to test whether covariates would modify these air pollution-morbidity associations. During the period from 2014 to 2018, a total of 97,982 subjects completed follow-up. 12,371 incidents of hypertension and 2034 of diabetes occurred. In the multi-covariates model, the hazard ratios (HR) and 95% confidence interval (CI) were 1.49 (1.45-1.52), 1.28 (1.26-1.30), 1.17 (1.15-1.18), 1.21 (1.17-1.25) and 1.33 (1.31-1.35) for hypertension morbidity per 10 μg/m³ increment in PM₁, PM_2.5, PM₁₀, NO₂ and SO₂, respectively. For diabetes onsets, the HR (95% CI) were 1.17 (1.11-1.23), 1.09 (1.04-1.13), 1.06 (1.02-1.09), 1.02 (0.95-1.10), and 1.24 (1.19-1.29), respectively. In addition, for hypertension analyses, the effect estimates were more pronounced in the participants with age <60 years old, BMI ≥24 kg/m², and frequent alcohol drinking. These findings provided the evidence on elevated risks of morbidity of hypertension and diabetes associated with prolonged ambient pollutants exposure at relatively high levels.

Systemic inflammation accelerates the adverse effects of air pollution on metabolic syndrome: Findings from the China health and Retirement Longitudinal Study (CHARLS)

Long-term exposure to air pollution and systemic inflammation are associated with increased prevalence of metabolic syndrome (MetS); however, their joint effects in Chinese middle-aged and older adults is unknown. In this cross-sectional study, 11,838 residents aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS) Wave 3 in 2015 were included. MetS was diagnosed using the Joint Interim Societies' definition. C-Reactive Protein (CRP) was assessed to reflect systemic inflammation. Individual exposure to air pollutants (particulate matter with a diameter ≤2.5 μm (PM_2.5) or ≤ 10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO)) was evaluated using satellite-based spatiotemporal models according to participant residence at county-level. Generalized linear models (GLMs) were applied to examine the association between air pollution and MetS, and the modification effects of CRP between air pollution and MetS were estimated using interaction terms of CRP and air pollutants in the GLM models. The prevalence of MetS was 32.37%. The adjusted odd ratio (OR) of MetS was 1.192 (95% confidence interval (CI): 1.116, 1.272), 1.177 (95% CI: 1.103, 1.255), 1.158 (95% CI: 1.072, 1.252), 1.303 (95% CI: 1.211,1.403), 1.107 (95% CI: 1.046, 1.171) and 1.156 (95% CI:1.083, 1.234), per inter-quartile range increase in PM_2.5 (24.04 μg/m³), PM₁₀ (39.00 μg/m³), SO₂ (19.05 μg/m³), NO₂ (11.28 μg/m³), O₃ (9.51 μg/m³) and CO (0.46 mg/m³), respectively. CRP was also associated with increased prevalence of MetS (OR = 1.049, 95% CI: 1.035, 1.064; per 1.90 mg/L increase in CRP). Interaction analysis suggested that high CRP levels enhanced the association between air pollution exposure and MetS. Long-term exposure to air pollution is associated with increased prevalence of MetS, which might be enhanced by systemic inflammation. Given the rapidly aging society and heavy burden of MetS, measures should be taken to improve air quality and reduce systemic inflammation.

Associations of residential greenness with obesity and BMI level among Chinese rural population: findings from the Henan Rural Cohort Study

In recent years, increasing evidence supports the notion that obesity risk is affected by residential greenness. However, limited studies have been established in low- and middle-income countries, especially in China. The study aimed to evaluate the associations of residential greenness with obesity and body mass index (BMI) level in Chinese rural-dwelling adults. A total of 39,259 adults from the Henan Rural Cohort Study (HRCS) were included in the analyses. According to the guideline for prevention and control of overweight and obesity in Chinese adults, obesity was defined as BMI ≥ 28 kg/m². Residential greenness was measured by satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Generalized linear mixed models were used to study the associations between exposure to residential greenness with obesity and BMI level. Higher residential greenness was significantly correlated with lower odds of obesity and BMI level. For example, in the full-adjusted analyses, an interquartile range (IQR) increase in EVI_500-m was linked with reduced odds of obesity (OR = 0.77, 95%CI 0.72-0.82) and BMI level (β =  - 0.41 kg/m², 95%CI - 0.48 to - 0.33 kg/m²). Mediation analyses showed air pollution and physical activity could be potential mediators in these associations. Besides, we found that the association of NDVI_500-m with BMI was stronger in females and low-income populations. Higher residential greenness was associated with a lower prevalence of obesity and BMI level, particularly among females and the low-income population. These relationships were partially mediated by reducing air pollution and increasing physical activity.

Revisiting the atmospheric particles: Connecting lines and changing paradigms

Historically, the atmospheric particles constitute the most primitive and recent class of air pollutants. The science of atmospheric particles erupted more than a century ago covering more than four decades of size, with past few years experiencing major advancements on both theoretic and data-based observational grounds. More recently, the plausible recognition between particulate matter (PM) and the diffusion of the COVID-19 pandemic has led to the accretion of interest in particle science. With motivation from diverse particle research interests, this paper is an 'old engineer's survey' beginning with the evolution of atmospheric particles and identifies along the way many of the global instances signaling the 'size concept' of PM. A theme that runs through the narrative is a 'previously known' generational evolution of particle science to the 'newly procured' portfolio of knowledge, with important gains on the application of unmet concepts and future approaches to PM exposure and epidemiological research.

Healthier Lifestyles Attenuated Association of Single or Mixture Exposure to Air Pollutants with Cardiometabolic Risk in Rural Chinese Adults

There is little research on how long-term exposure to independent and multiple air pollutants changes cardiometabolic risk in adults. In addition, previous studies focused on only the effect of one or two lifestyles on cardiometabolic risk. The evidence on the interactive effects of the lifestyle score and exposure to independent and mixtures of air pollutants on cardiometabolic risk is lacking. A total of 33,638 rural residents were included in the cross-sectional study. The three-year average concentrations of air pollutants for participants were predicted by using a satellite-based prediction. The air pollution score was created to assess the combined exposure of four air pollutants (PM1, PM2.5, PM10, and NO2). A gender−age-specific cardiometabolic risk score was calculated. Multivariable-adjusted linear regression and quantile g-computation were used to investigate the associations between air pollutants and cardiometabolic risk. Interaction plots were applied to describe the interactive effects of air pollution and the healthy lifestyle score on cardiometabolic risk. Per interquartile range (IQR) unit increases in PM1, PM2.5, PM10, or NO2 were associated with 0.162 (95% CI: 0.091, 0.233), 0.473 (95% CI: 0.388, 0.559), 0.718 (95% CI: 0.627, 0.810), and 0.795 (95% CI: 0.691, 0.898) unit increases in cardiometabolic risk score (all p < 0.05), respectively. A 0.854 (95% CI: 0.768, 0.940) unit increase in cardiometabolic risk was associated with each IQR increase in air pollution score. Furthermore, the strengths of associations of PM1, PM2.5, PM10, NO2, and the air pollution score on cardiometabolic risk score were attenuated with the healthy lifestyle score increase. In addition, there was no statistical significance after the lifestyle score equal to four scores for the effect of PM1 on the cardiometabolic risk score. In conclusions, individual or joint air pollutants were associated with an increased cardiometabolic risk. Improving the healthy lifestyle may be an effective method to improve cardiometabolic health in highly polluted rural regions.

Associations of long-term exposure to ambient ozone with hypertension, blood pressure, and the mediation effects of body mass index: A national cross-sectional study of middle-aged and older adults in China

BACKGROUND

The associations between long-term exposure to ozone (O₃) and respiratory diseases are well established. However, its association with cardiovascular disease (CVD) remains controversial. In this study, we examined the associations between O₃ and the prevalence of hypertension and blood pressure, and the mediation effects of body mass index (BMI) in Chinese middle-aged and older adults.

METHODS

In this national cross-sectional study, we estimated the O₃ exposure of 12,028 middle-aged and older adults from 126 county-level cities in China, using satellite-based spatiotemporal models. Generalized linear mixed models were used to evaluate the associations of long-term exposure to O₃ with hypertension and blood pressure, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure (PP). Mediation effect models were applied to examine the mediation effects of BMI among O₃-induced hypertension and elevated blood pressure.

RESULTS

Each 10 μg/m³ increase in O₃ concentration was significantly associated with an increase of 13.7% (95% confidence interval (CI): 4.8%, 23.3%) in the prevalence of hypertension, an increase of 1.128 mmHg (95% CI: 0.248, 2.005), 0.679 mmHg (95% CI: 0.059, 1.298), 0.820 mmHg (95%CI: 0.245, 1.358) in SBP, DBP, and MAP, respectively. Mediation effect models showed that BMI played 40.08%, 37.25%, 39.95%, and 33.51% mediation roles in the effects of long-term exposure to O₃ on hypertension, SBP, DBP, and MAP, respectively.

CONCLUSIONS

Long-term exposure to O₃ can increase the prevalence of hypertension and blood pressure levels of middle-aged and older adults, and an increase of BMI would be an important modification effect for O₃-induced hypertension and blood pressure increase.

Outdoor Physical Activity in an Air Polluted Environment and Its Effect on the Cardiovascular System-A Systematic Review

Air pollution is a global public health threat. Evidence suggests that increased air pollution leads to increased cardiovascular morbidity and mortality. The aim of this review was to systematically review and synthesize scientific evidence to understand the effect of performing outdoor physical activity (PA) in a polluted environment on cardiovascular outcomes. This review was developed and reported in accordance with the PRISMA guidelines. Electronic searches in Embase, Web of Science, and PubMed were undertaken through March 2021 initially, and later updated through to 31st January 2022, for observational studies published in peer-reviewed journals that report cardiovascular mortality or morbidity due to outdoor PA in air polluted environment. These searches yielded 10,840 citations. Two reviewers independently reviewed each citation for its eligibility. Seven studies were found to be eligible. Of these, five were cohort studies and two were cross-sectional studies. Pollutants measured in the selected studies were Particulate Matter (PM)-PM10, PM2.5, nitrogen oxides (NO_x), and ozone (O₃). The most common study outcome was myocardial infarction, followed by cardiovascular mortality, hypertension and heart rate variability. Six studies emphasized that the PA has beneficial effects on cardiovascular outcomes, though air pollutants attenuate this effect to an extent. Two studies showed that walking, even in the polluted environment, significantly reduced the heart rate and heart rate variability indices. The beneficial effects of outdoor PA outweigh the harmful effects of air pollution on cardiovascular health, though the benefits reduce to an extent when PA is carried out in a polluted environment. Because a limited number of studies (n = 7) were eligible for inclusion, the review further emphasizes the critical need for more primary studies that differentiate between outdoor and indoor PA and its effect on cardiovascular health.

Identification of the susceptible subpopulations for wide pulse pressure under long-term exposure to ambient particulate matters

Wide pulse pressure (WPP) is a preclinical indicator for arterial stiffness and cardiovascular diseases. Long-term exposure to ambient particulate matters (PMs) would increase the risk of WPP. Although reducing pollutants emissions and avoiding outdoor activity during a polluted period are effective ways to blunt the adverse effects. Identifying and protecting the susceptible subpopulation is another crucial way to reduce the disease burdens. Therefore, we aimed to identify the susceptible subpopulations of WPP under long-term exposure to PMs. The WPP was defined as pulse pressure over 60 mmHg. Three-year averages of PMs were estimated using random forest approaches. Associations between WPP and PMs exposure were estimated using generalized propensity score weighted logistic regressions. Demographic, socioeconomic characteristics, health-related behaviors, and hematological biomarkers were collected to detect the modification effects on the WPP-PMs associations. Susceptible subpopulations were defined as those with significantly higher risks of WPP under PMs exposures. The PMs-WPP associations were significant with ORs (95%CI) of 1.126 (1.094, 1.159) for PM₁, 1.174 (1.140, 1.210) for PM_2.5, and 1.111 (1.088, 1.135) for PM₁₀. There were 17 subpopulations more sensitive to WPP under long-term exposure to PMs. The susceptibility was higher in subpopulations with high BMI (Q3-Q4 quartiles), high-intensive physical activity (Q3 or Q4 quartile), insufficient or excessive fruit intake (Q1 or Q5 quartile), insufficient or too long sleep length (<7 or >8 h). Subpopulations with elevated inflammation markers (WBC, LYM, BAS, EOS: Q3-Q4 quartiles) and glucose metabolism indicators (HbA1c, GLU: Q3-Q4 quartiles) were more susceptible. Besides, elder, urban living, low socioeconomic level, and excessive red meat and sodium salt intake were also related to higher susceptibility. Our findings on the susceptibility characteristics would help to develop more targeted disease prevention and therapy strategies. Health resources can be allocated more effectively by putting more consideration to subpopulations with higher susceptibility.

Association between cognitive function and ambient particulate matters in middle-aged and elderly Chinese adults: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Increasing studies have discussed how ambient air pollution affects cognitive function, however, the results are inconsistent, and such studies are limited in developing countries. To fill the gap, in this study, we aimed to explore the effect of ambient particulate matters (PM₁, PM_2.5, PM₁₀) on cognitive function of middle-aged and elderly Chinese adults. A total of 7928 participants older than 45 were included from CHARLS collected in 2011, 2013, and 2015. Cognitive function was evaluated with two dimensions, the first one was episodic memory and the second dimension was mental status. The total score of cognitive function was the sum of above two dimensions (0-31 points). Participants' exposure to ambient particulate matters was estimated by using a satellite-based spatiotemporal model. Linear mixed models were applied to analyze the impact of PM₁, PM_2.5, and PM₁₀ on cognition function. Further interaction analyses were applied to examine the potential effect modifications on the association. After adjusting for confounding factors, we found an IQR increase in all three ambient particulate matters was significantly associated with a decrease in cognitive function score, with the greatest effect in the 90-day exposure window for PM₁ (β = -0.227, 95%CI: -0.376, -0.078) and PM_2.5 (β = -0.220, 95%CI: -0.341, -0.099). For ambient PM₁₀, the most significant exposure window was 60-day (β = -0.158, 95%CI: -0.274, -0.042). Interaction analyses showed that the PM-cognitive function association could be modified by gender, region, alcohol consumption, smoking, education level, chronic diseases, and depressive symptoms. In conclusion, exposure to ambient particulate matter for a certain period would significantly decrease cognitive function among middle-aged and elderly Chinese. Furthermore, individuals who were female, or lived in the midland of China were more susceptible to the adverse effect of particulate matters.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM1, PM2.5 and PM10 fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization. The models' predictions were subsequently de-weathered by meteorological normalization using repeated random resampling of all predictive variables except the trend variable. Three pollution periods in 2020 were examined in detail: January and February, as pre-lockdown, the month of April as the lockdown period, as well as June and July as the "new normal". An evaluation using normalized mass concentrations of particulate matter and Analysis of variance (ANOVA) was conducted. The results showed that no significant differences were observed for PM1, PM2.5 and PM10 in April 2020-compared to the same period in 2018 and 2019. No significant changes were observed for the "new normal" as well. The results thus indicate that a reduction in mobility during COVID-19 lockdown in Zagreb, Croatia, did not significantly affect particulate matter concentration in the long-term..

Associations of long-term exposure to ambient air pollutants with metabolic syndrome: The Wuhan Chronic Disease Cohort Study (WCDCS)

BACKGROUND

Evidence on the associations between long-term exposure to ambient air pollutants (including particle with aerodynamic diameter ≤10 μm (PM₁₀), particle with aerodynamic diameter ≤2.5 μm (PM_2.5), ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) and prevalence of metabolic syndrome (MetS) remains inconclusive. This study aimed to determine the associations based on a case-control study nested in the Wuhan Chronic Disease Cohort study (WCDCS), a population-based study with baseline survey in 2019.

METHODS

A total of 10,253 residents living in Wuhan were recruited. The 3-year average concentrations of main pollutants (PM₁₀, PM_2.5, O₃, NO₂, and SO₂) at residences prior to the survey date were estimated to evaluate the long-term exposures. The generalized linear mixed models were used to investigate the changes in MetS prevalence by an IQR increases in each air pollutant exposure concentrations. Interaction effects between air pollutants and demographic, lifestyle, and dietary factors on MetS were evaluated by including an interactive item in the main model.

RESULTS

The prevalence of MetS in Wuhan was 9.8%, and the 3-year exposure concentrations of PM₁₀, PM_2.5, O₃, NO₂, and SO₂ were 84.1 μg/m³, 50.5 μg/m³, 55.7 μg/m³, 46.0 μg/m³, and 9.4 μg/m³, respectively. Higher PM₁₀, PM_2.5 and O₃ exposure concentrations were associated with an elevated MetS prevalence (e.g. an IQR increase in PM_2.5, OR = 1.193, 95% confidence intervals (95%CIs): 1.028, 1.385; for O₃, OR = 1.074, 95%CIs: 1.025, 1.124), whereas NO₂, and SO₂ were negatively or insignificant correlated with odds of Mets (e.g. an IQR increase in NO₂, OR = 0.865, 95%CIs: 0.795, 0.941). Males, smokers, alcohol drinkers and individuals who intake fruits occasionally exposure to PM₁₀ and PM_2.5 were found had a higher risk of developing MetS.

CONCLUSIONS

Long-term exposure to higher concentrations of ambient air pollutants may elevate the prevalence of MetS in populations in Central China. Susceptible individuals especially those with unhealthy lifestyles had a higher risk for MetS.

Nonlaboratory-based risk assessment model for coronary heart disease screening: Model development and validation

BACKGROUND

Identifying groups at high risk of coronary heart disease (CHD) is important to reduce mortality due to CHD. Although machine learning methods have been introduced, many require laboratory or imaging parameters, which are not always readily available; thus, their wide applications are limited.

OBJECTIVE

The aim of this study was to develop and validate a simple, efficient, and joint machine learning model for identifying individuals at high risk of CHD using easily obtainable nonlaboratory parameters.

METHODS

This prospective study used data from the Henan Rural Cohort Study, which was conducted in rural areas of Henan Province, China, between July 2015 and September 2017. A joint machine learning model was developed by selecting and combining four base machine learning algorithms, including logistic regression (LR), artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM). We used readily accessible variables, including demographics, medical and family history, lifestyle and dietary factors, and anthropometric data, to inform the model. The model was also externally validated by a cohort of individuals from the Dongfeng-Tongji cohort study. Model discrimination was assessed by using the area under the receiver operating characteristic curve (AUC), and calibration was measured by using the Brier score (BS).

RESULTS

A total of 38 716 participants (mean [SD] age, 55.64[12.19] years; 23449[60.6%] female) from the Henan Rural Cohort Study and 17 958 subjects (mean [SD] age, 62.74 [7.59] years; 10,076 [56.1%] female) from the Dongfeng-Tongji cohort study were included in the analysis. Age, waist circumference, pulse pressure, heart rate, family history of CHD, education level, family history of type 2 diabetes mellitus (T2DM), and family history of dyslipidaemia were strongly associated with the development of CHD. In regard to internal validation, the model we built demonstrated good discrimination (AUC, 0.844 (95% CI 0.828-0.860)) and had acceptable calibration (BS, 0. 066). In regard to external validation, the model performed well with clearly useful discrimination (AUC, 0.792 (95% CI 0.774-0.810)) and robust calibration (BS, 0.069).

CONCLUSIONS

In this study, the novel and simple, machine learning-based model comprising readily accessible variables accurately identified individuals at high risk of CHD. This model has the potential to be widely applied for large-scale screening of CHD populations, especially in medical resource-constrained settings.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register. (Trial registration: ChiCTR-OOC-15006699. Registered 6 July 2015 - Retrospectively registered) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Acute effect of fine particulate matter on blood pressure, heart rate and related inflammation biomarkers: A panel study in healthy adults

Epidemiological evidence of short-term fine particulate matter (PM2.5) exposure on blood pressure (BP), heart rate (HR) and related inflammation biomarkers has been inconsistent. We aimed to explore the acute effect of PM2.5 on BP, HR and the mediation effect of related inflammation biomarkers. A total of 32 healthy college students were recruited to perform 4 h of exposure at two sites with different PM2.5 concentrations in Wuhan between May 2019 and June 2019. The individual levels of PM2.5 concentration, BP and HR were measured hourly for each participant. Blood was drawn from each participant after each visit and we measured the levels of inflammation markers, including serum high-sensitivity C-reactive protein and plasma fibrinogen. Linear mixed-effect models were to explore the acute effect of PM2.5 exposure on BP, HR, and related inflammation biomarkers. In addition, we evaluated related inflammation biomarkers as the mediator in the association of PM2.5 and cardiovascular health indicators. The results showed that a 10 μg/m3 increment in PM2.5 concentration was associated with an increase of 0.84 (95% CI: 0.54, 1.15) beats/min (bpm) in HR and a 3.52% (95% CI: 1.60%, 5.48%) increase in fibrinogen. The lag effect model showed that the strongest effect on HR was observed at lag 3 h of PM2.5 exposure [1.96 bpm (95% CI: 1.19, 2.75)], but for fibrinogen, delayed exposure attenuated the association. Increased fibrinogen levels may account for 39.07% (P = 0.44) of the elevated HR by PM2.5. Null association was observed when it comes to short-term PM2.5 exposure and BP. Short-term exposure to PM2.5 was associated with elevated HR and increased fibrinogen levels. But our finding was not enough to suggest that exposure to PM2.5 might induce adverse cardiovascular effects by the pathway of inflammation.

Long-term association of ambient air pollution and hypertension in adults and in children: A systematic review and meta-analysis

AIMS

The association of long-term ambient air pollution and hypertension has been inconsistently reported. We performed an updated systematic review and meta-analysis to assess the association between long-term exposure to ambient air pollution and risk of hypertension in adults and in children.

METHODS

PubMed, EMBASE, and Web of Science were searched up to August 7, 2020 for published articles examining the association of long-term exposure to ambient air pollution, including particulate matter (PM; ultrafine particles, PM₁, PM_1-2.5, PM_2.5, PM_2.5-10 and PM₁₀), nitrogen dioxide (NO₂), nitrogen oxides (NO_x), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO) and hypertension. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension with each 10-μg/m³ increase in air pollutants were calculated by random-effects models.

RESULTS

We included 57 studies (53 of adults and 4 of children) in the meta-analysis. Risk of hypertension was significantly increased in adults with each 10-μg/m³ increase in exposure to PM_2.5 (OR 1.10, 95% CI 1.07-1.14; I² = 93.1%; n = 37), PM₁₀ (1.04, 1.02-1.07; I² = 44.8%; n = 22), and SO₂ (1.21, 1.08-1.36; I² = 96.6%; n = 3). Hypertension was not significantly associated with PM₁ (n = 2), PM_2.5-10 (n = 16), NO₂ (n = 27), or NO_x (n = 17). In children, the summary ORs (95% CIs) for each 10-μg/m³ increase in PM_2.5, PM₁₀, SO₂ and O₃ were 2.82 (0.51-15.68; I² = 83.8%; n = 2), 1.15 (1.01-1.32; I² = 0; n = 2), 8.57 (0.13-575.58; I² = 94.2%; n = 2), and 1.26 (0.81-1.09, I² = 91.6%; n = 2), respectively.

CONCLUSIONS

Long-term ambient air pollution is a potential risk factor for hypertension in adults. More studies are needed to explore the effects of long-term air pollution on hypertension in children.

A geodatabase of blood pressure level and the associated factors including lifestyle, nutritional, air pollution, and urban greenspace

Objectives

Hypertension is a prevalent chronic disease globally. A multifaceted combination of risk factors is associated with hypertension. Scientific literature has shown the association among individual and environmental factors with hypertension, however, a comprehensive database including demographic, environmental, individual attributes and nutritional status has been rarely studied. Moreover, an integrated spatial-epidemiological approach has been scarcely researched. Therefore, this study aims to provide and describe a geodatabase including individual-based and socio-environmental data related to people living in the city of Mashhad, Iran in 2018.

Data description

The database has been extracted from the PERSIAN Organizational Cohort study in Mashhad University of Medical Sciences. The data note includes three shapefiles and a help file. The shapefile format is a digital vector storage format for storing geometric location and associated attribute information. The first shapefile includes the data of population, air pollutants and amount of available green space for each census block of the city. The second shapefile consists of aggregated blood pressure data to the census blocks of the city. The third shapefile comprises the individual characteristics data (i.e., demographic, clinical, and lifestyle). Finally, the fourth file is a guide to the previous data files for users.

PM2.5 constituents and mortality from a spectrum of causes in Guangzhou, China

As the major constituents of PM_2.5, carbonaceous constituents and inorganic ions have attracted emerging attentions on their health risks, particularly on cardiorespiratory diseases. However, evidences on the risks of PM_2.5 constituents on other diseases (eg. nervous disease, genitourinary disease, neoplasms and endocrine disease) remain scarce. In our study, we firstly calculated residuals of PM_2.5 constituents regressed on PM_2.5 to remove the confounding effect of PM_2.5. Then, generalized additive model (GAM) was used to assess impacts of residuals of PM_2.5 constituents on mortality from 36 diseases (10 broad categories and 26 subcategories) during 2011-2015 in Guangzhou, China. Results of constituent-residual models showed that only EC, OC and NO₃^- were significantly associated with all-cause mortality, with per IQR change in corresponding constituent residuals related to percentage changes of 1.69% (95% CI: 0.42, 2.97), 1.94% (95% CI: 0.37, 3.54) and 2.59% (95% CI: 1.02, 4.18) at lag 03 days. All these pollutants were significantly associated with elevated mortality risk of cardiovascular disease, but only EC was significantly associated with respiratory mortality, and NO₃^- with endocrine disease and neoplasm. For more specific causes, the highest effect estimates of EC and NO₃^-were both observed on mortality from other form of heart disease, and OC on intentional self-harm, with estimates of 11.45% (95% CI: 2.74, 20.91), 12.59% (95% CI: 1.41, 25.02) and 18.01% (95% CI: 2.14, 36.36), respectively. Our findings highlighted that stricter emission control measures are still warranted to reduce air pollution level and protect the public health.

Association of long-term exposure to ambient particulate pollution with stage 1 hypertension defined by the 2017 ACC/AHA Hypertension Guideline and cardiovascular disease: The CHCN-BTH cohort study

BACKGROUND

Evidence regarding the effects of ambient air pollution on new stage 1 hypertension defined by the 2017 ACC/AHA Hypertension Guideline remains sparse.

OBJECTIVES

To investigate the association of long-term exposure to ambient PM_2.5 with stage 1 hypertension and to explore the mediating and modifying effects of PM_2.5 on cardiovascular disease (CVD).

METHODS

A total of 32,135 participants aged 18-80 years were recruited in 2017. The three-year (2014-2016) average PM_2.5 concentrations were assessed by a spatial statistical model. Blood pressure (BP) was divided into four categories according to the 2017 ACC/AHA Hypertension Guideline: normal BP (SBP<120 mmHg and DBP<80 mmHg), elevated BP (SBP 120-129 mmHg and DBP<80 mmHg), stage 1 hypertension (SBP 130-139 mmHg or DBP 80-89 mmHg), and stage 2 hypertension (SBP≥140 mmHg or DBP≥90 mmHg or taking antihypertensive medications). The associations of PM_2.5 with BP categories were estimated by two-level generalized linear mixed models. Analyses stratified by age, mediation and interaction analyses of PM_2.5 and stage 1 hypertension with CVD were performed.

RESULTS

We detected a positive significant association between long-term exposure to PM_2.5 and stage 1 hypertension. Compared to normal BP, the OR was 1.05 (95% CI: 1.02, 1.08) per 10 μg/m³ increase in PM_2.5. The association was stronger than that of elevated BP but weaker than that of stage 2 hypertension. Stage 1 hypertension only partially mediated the association between PM_2.5 and CVD, and the mediation proportions ranged from 1.55% to 11.00%. However, it modified the association between PM_2.5 and CVD, which was greater in participants with stage 1 hypertension (OR: 1.66; 95% CI: 1.43, 1.93) than in participants with normal BP (OR: 1.32; 95% CI: 1.11, 1.57), with P_interaction<0.001. In the analysis stratified by age, the above associations were age-specific, and significant associations were only observed in the young and middle-aged (<60 years) groups.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 was significantly associated with stage 1 hypertension. This earlier stage of hypertension may be a trigger BP range for adverse effects of air pollution in the development of hypertension and CVD, especially in young and middle-aged individuals.

Air pollution-associated blood pressure may be modified by diet among children in Guangzhou, China

OBJECTIVES

To assess the associations between long-term air pollution exposure and blood pressure in children, and to explore the modifying effects of diet on prehypertension and hypertension.

METHODS

We evaluated 7225 primary school children aged 6-12 years from Guangzhou, China, in 2017. The blood pressure was measured objectively. The individual 1-year average concentration of particles with an aerodynamic diameter of 2.5 μm or less or 10 μm or less (PM2.5, PM10), sulfur dioxide (SO2), and ozone (O3) before each blood pressure measurement were calculated by inverse distance weighting interpolation according to each home address. Generalized linear mixed-effects models were used to examine the health effects and potential effect modifications by diet factors after adjusting for covariates.

RESULTS

The results showed that the estimated increase in mean SBP was 0.92 mmHg (95% CI 0.05-1.79) per interquartile range increase in O3. An interquartile range increase in the 1-year mean of SO2 and O3 was associated with odds ratios of 1.26 (95% CI 1.04-1.52) and 1.20 (95% CI 1.06-1.35) for prehypertension, respectively. In addition, an interquartile range increase in PM2.5, SO2, and O3 exposure was positively associated with hypertension, with odds ratios of 1.33 (95% CI 1.11-1.61), 1.70 (95% CI 1.33-2.16), and 1.48 (95% CI 1.20-1.83), respectively. Stronger effect estimates between PM2.5, SO2, and O3 concentration on prehypertension were exhibited among subgroups of children with a higher intake of sugar-sweetened beverages.

CONCLUSION

Long-term exposure to PM2.5, SO2, and O3 were associated with higher blood pressure levels in children, and dietary intake might modify these associations.

Ambient particulate matter (PM1, PM2.5, PM10) and childhood pneumonia: The smaller particle, the greater short-term impact?

BACKGROUND

Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia.

AIMS

We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), respectively.

METHODS

Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM₁, PM_2.5, PM₁₀, and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed.

RESULTS

For each 10 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM₁ effects, while PM_2.5 and PM₁₀ effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM₁, but PM_2.5 and PM₁₀ were only associated with children aged 1-4 years. Furthermore, PM₁ effects were greater in autumn and winter, while greater PM_2.5 and PM₁₀ effects were evident only in autumn.

CONCLUSION

This study suggests a greater short-term impact on childhood pneumonia from PM₁ in comparison to PM_2.5 and PM₁₀. Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.

Long-term exposure to PM1 and PM2.5 is associated with serum cortisone level and meat intake plays a moderation role

BACKGROUND

Although short-term exposure to particulate matter (PM) was associated with increased glucocorticoids (GCs) levels, available evidence on associations of long-term exposure to PM and GCs levels is still scant. Previous studies has showed that meat intake is associated with sex hormones levels, but it is unknown whether meat intake is associated with GCs levels. Furthermore, the role of meat intake in the associations between PM and GCs levels remains unclear.

AIMS

The aims of this study were to explore the associations of long-term exposure to PM and GCs levels among Chinese rural adults, and the role of meat intake in these associations.

MATERIALS AND METHODS

A total of 6223 subjects were recruited from the Henan Rural Cohort Study. Serum GCs levels were measured with liquid chromatography-tandem mass spectrometry. The concentrations of PM (PM₁ and PM_2.5) for each subject were assessed with machine learning algorithms. The food frequency questionnaire (FFQ) was used to obtain each participant' information on meat intake. The effects of PM and meat intake on GCs levels were assessed using generalized linear models. In addition, modification analyses were performed to identify the role of meat intake played in the associations of PM with serum GCs levels.

RESULTS

Per 1 μg/m³ increment in PM₁ or PM_2.5 concentration was associated with a 0.364 ng/ml (95% confidence interval (CI): 0.234, 0.494) or 0.227 ng/ml (95%CI: 0.110, 0.343) increase in serum cortisone, respectively. In addition, the moderation effects of total meat intake and red meat intake on the associations of long-term exposure to PM₁ or PM_2.5 with serum cortisone were observed (P < 0.05), indicating that individuals who had high levels of PM₁ or PM_2.5 and meat intake were more susceptible to have a higher state of serum cortisone.

CONCLUSIONS

Our findings suggested that long-term exposure to PM₁ or PM_2.5 was associated with serum cortisone. Moreover, meat intake was found to be a significant moderator in the association of PM₁ or PM_2.5 with serum cortisone levels.

Associations of maternal exposure to fine particulate matter constituents during pregnancy with Apgar score and duration of labor: A retrospective study in Guangzhou, China, 2012-2017

BACKGROUND

Limited evidence is available for demonstrating effects of prenatal PM_2.5 and its components exposure on Apgar score and duration of labor.

OBJECTIVE

We sought to investigate the associations between PM_2.5 constituents, Apgar score and duration of labor, and evaluated the potential mediating role of duration of labor.

METHODS

This study included 5396 participants. The V4·CH.02 was applied to assessing exposure to PM_2.5 constituents. The associations between PM_2.5 constituents Apgar score and duration of labor were examined by multivariate linear regression. Mediation analysis was conducted to estimate the potential mediation effect of duration of labor.

RESULTS

Trimester-specific exposure to soil dust was significantly associated with 1-min Apgar score (1st trimester: OR: 1.03, 95% CI:0.97, 1.10; 2nd trimester: OR: 1.07, 95% CI: 1.01, 1.14; 3rd trimester: OR: 1.07, 95% CI: 1.01, 1.13), duration of first stage of labor (1st trimester: β: 0.32, 95% CI: 0.07, 0.58; 2nd trimester: β: 0.27, 95% CI: 0.04, 0.51; 3rd trimester: β: 0.37, 95% CI: 0.13, 0.61) and duration of second stage of labor (1st trimester: β: 0.04, 95% CI: -0.00, 0.09; 2nd trimester: β: 0.05, 95% CI: 0.01, 0.10; 3rd trimester: β: 0.05, 95% CI: 0.00, 0.09). The duration of labor mediated the relationship between soil dust and 1-min Apgar score.

CONCLUSION

This study demonstrated that prenatal exposure to soil dust was significantly associated with the risk of abnormal 1-min Apgar score and extended stage of labor.

Dietary Pattern and Long-Term Effects of Particulate Matter on Blood Pressure: A Large Cross-Sectional Study in Chinese Adults

[Figure: see text].

Long-term exposure to air pollutants enhanced associations of obesity with blood pressure and hypertension

Although obesity reflected by BMI can enhance the association of air pollution with increase blood pressures (BP) and prevalent hypertension in susceptible population, there remains lack evidence on interactive effects of different obesity indices and air pollutants on BP and prevalent hypertension in rural adults. 39,259 individuals were recruited from the Henan Rural Cohort. Concentrations of air pollutants (PM₁, PM_2.5, PM₁₀ and NO₂) were evaluated by a spatio-temporal model based on satellites data. Independent associations of air pollutants and obesity reflected by BMI, WC, WHR, WHtR, BFP and VFI on BP indicators (SBP, DBP, MAP and PP) and prevalent hypertension were analyzed by linear regression and logistic regression models, respectively. Furthermore, their additive effects were quantified by RERI, AP and S. Six obesity indices enhanced the associations of four air pollutants and BP indicators. Individuals with high PM₁ concentrations plus obesity classified by BMI, WC, WHR, WHtR, BFP and VFI had a 4.18-fold (95% CI: 3.86, 4.53), 3.58-fold (95% CI: 3.34, 3.84), 3.53-fold (95% CI: 3.28, 3.81), 4.02-fold (95% CI: 3.72, 4.35), 3.89-fold (95% CI: 3.59, 4.23), 3.87-fold (95% CI: 3.62, 4.14) increase in prevalent hypertension, respectively, compared to non-obese individuals with low PM₁ concentrations; similar results were observed for combined effect of PM_2.5, PM₁₀ or NO₂ and obesity indices on prevalent hypertension. The significant values of RERI, AP and S indicated additive effects of air pollutants and obesity indices on hypertension. Obesity amplified the effects of exposure to high levels of air pollutants on increased BP values and prevalent hypertension, implying that obese individuals may be susceptible to elevate BP and prevalent hypertension in relation to air pollution exposure. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).

Residential Green and Blue Spaces and Type 2 Diabetes Mellitus: A Population-Based Health Study in China

Evidence on the health benefits of green space in residential environments is still limited, and few studies have investigated the potential association between blue space and type 2 diabetes mellitus (T2DM) prevalence. This study included 39,019 participants who had completed the baseline survey from the Henan Rural Cohort Study, 2015-2017. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were employed to characterize the residential green space, and the distance from the participant's residential address to the nearest water body was considered to represent the residential blue space. Mixed effect models were applied to evaluate the associations of the residential environment with T2DM and fasting blood glucose (FBG) levels. An interquartile range (IQR) increase in NDVI and EVI was significantly associated with a 13.4% (odds ratio (OR): 0.866, 95% Confidence interval (CI): 0.830,0.903) and 14.2% (OR: 0.858, 95% CI: 0.817,0.901) decreased risk of T2DM, respectively. The residential green space was associated with lower fasting blood glucose levels in men (%change, -2.060 in men vs. -0.972 in women) and the elderly (%change, -1.696 in elderly vs. -1.268 in young people). Additionally, people who lived more than 5 km from the water body had a 15.7% lower risk of T2DM (OR: 0.843, 95% CI: 0.770,0.923) and 1.829% lower fasting blood glucose levels (95% CI: -2.335%,-1.320%) than those who lived closer to the blue space. Our findings suggest that residential green space was beneficially associated with T2DM and fasting blood glucose levels. However, further research is needed to explore more comprehensively the relationship between residential blue space and public health.

Is PM1 similar to PM2.5? A new insight into the association of PM1 and PM2.5 with children's lung function

Experimental data suggests that PM₁ is more toxic than PM_2.5 although the epidemiologic evidence suggests that the health associations are similar. However, few objective exposure data are available to compare the associations of PM₁ and PM_2.5 with children lung function. Our objectives are a) to evaluate associations between long-term exposure to PM₁, PM_2.5 and children's lung function, and b) to compare the associations between PM₁ and PM_2.5. From 2012 to 2013, we enrolled 6,740 children (7-14 years), randomly recruited from primary and middle schools located in seven cities in northeast China. We measured lung function including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), peak expiratory flow (PEF), and maximal mid-expiratory flow (MMEF) utilizing two portable electronic spirometers. We dichotomized continuous lung function measures according the expected values for gender and age. The spatial resolution at which PM₁ and PM_2.5 estimated were estimated using a machine learning method and the temporal average concentrations were averaged from 2009 to 2012. A multilevel regression model was used to estimate the associations of PM₁, PM_2.5 exposure and lung function measures, adjusted for confounding factors. Associations with lower lung function were consistently larger for PM₁ than for PM_2.5. Adjusted odds ratios (OR) per interquartile range greater PM₁ ranged from 1.53 for MMEF (95% confidence interval [CI]: 1.20-1.96) to 2.14 for FEV1 (95% CI: 1.66-2.76) and ORs for PM_2.5 ranged from 1.36 for MMEF (95%CI: 1.12-1.66) to 1.82 for FEV1 (95%CI: 1.49-2.22), respectively. PM₁ and PM_2.5 had significant associations with FVC and FEV1 in primary school children, and on PEF and MMEF in middle school children. Long-term PM₁ and PM_2.5 exposure can lead to decreased lung function in children, and the associations of PM₁ are stronger than PM_2.5. Therefore, PM₁ may be more hazardous to children's respiratory health than PM_2.5 exposure.

Acute effect of ambient fine particulate matter on heart rate variability: an updated systematic review and meta-analysis of panel studies

Background

Decreased heart rate variability (HRV) is a predictor of autonomic system dysfunction, and is considered as a potential mechanism of increased risk of cardiovascular disease (CVD) induced by exposure to particulate matter less than 2.5 μm in diameter (PM_2.5). Previous studies have suggested that exposure to PM_2.5 may lead to decreased HRV levels, but the results remain inconsistent.

Methods

An updated systematic review and meta-analysis of panel studies till November 1, 2019 was conducted to evaluate the acute effect of exposure to ambient PM_2.5 on HRV. We searched electronic databases (PubMed, Web of Science, and Embase) to identify panel studies reporting the associations between exposure to PM_2.5 and the four indicators of HRV (standard deviation of all normal-to-normal intervals (SDNN), root mean square of successive differences in adjacent normal-to-normal intervals (rMSSD), high frequency power (HF), and low frequency power (LF)). Random-effects model was used to calculate the pooled effect estimates.

Results

A total of 33 panel studies were included in our meta-analysis, with 16 studies conducted in North America, 12 studies in Asia, and 5 studies in Europe. The pooled results showed a 10 μg/m³ increase in PM_2.5 exposure which was significantly associated with a − 0.92% change in SDNN (95% confidence intervals (95%CI) − 1.26%, − 0.59%), − 1.47% change in rMSSD (95%CI − 2.17%, − 0.77%), − 2.17% change in HF (95%CI − 3.24%, − 1.10%), and − 1.52% change in LF (95%CI − 2.50%, − 0.54%), respectively. Overall, subgroup analysis suggested that short-term exposure to PM_2.5 was associated with lower HRV levels in Asians, healthy population, and those aged ≥ 40 years.

Conclusion

Short-term exposure to PM_2.5 was associated with decreased HRV levels. Future studies are warranted to clarity the exact mechanism of exposure to PM_2.5 on the cardiovascular system through disturbance of autonomic nervous function.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-020-00912-2.

Association of long-term exposure to ambient air pollutants with prolonged sleep latency: The Henan Rural Cohort Study

BACKGROUND

Prolonged sleep latency is associated with far-reaching public health consequences. Although evidence about the effect of air pollution on sleep problem has been shown, the effect on sleep latency remained unknown. The study aimed to analyze the association between long-term exposure to air pollution and prolonged sleep latency in rural China.

METHODS

In all, 27935 participants were included in the study from Henan Rural Cohort Study. A satellite-based spatiotemporal model was used to evaluate the 3-year average concentration of air pollutants at the home address of participants before the baseline survey. Air pollutants included NO₂ (nitrogen dioxide), PM₁ (particulate matter with aerodynamic diameters ≤1 μm), PM_2.5 (particulate matter with aerodynamic diameters ≤ 2.5 μm), and PM₁₀ (particulate matter with aerodynamic diametes ≤ 10 μm). A logistic regression model was conducted to assess the odds ratio (OR) and 95% confidence interval (95% CI) between air pollutants and prolonged sleep latency.

RESULTS

There were 5825 (20.85%) participants with prolonged sleep latency. The average concentration of NO₂, PM₁, PM_2.5, and PM₁₀ were 38.22 (2.54) μg/m³, 56.29 (1.75) μg/m³, 72.30 (1.87) μg/m³, and 130.01 (4.58) μg/m³. The odds ratio (95%CI) of prolonged sleep latency with an IQR increase of NO₂, PM₁, PM_2.5, and PM₁₀ were 1.59 (1.33-1.90), 1.23 (1.13-1.33), 1.28 (1.13-1.45) and 1.43 (1.22-1.67). The stratified analysis showed the effect of air pollutants was stronger among those with stroke.

CONCLUSION

Long-term exposure to NO₂, PM₁, PM_2.5 and PM₁₀ were associated with prolonged sleep latency. The adverse impact of air pollution should be considered when treating sleep problems.

Phthalate exposure linked to high blood pressure in Chinese children

BACKGROUND

Exposure to phthalate esters may be linked to the risk of high blood pressure (HBP), but limited evidence is available in Chinese children.

OBJECTIVE

To investigate the associations between nine phthalate metabolites (mPAEs) and systolic/diastolic BP, pulse pressure (PP), mean arterial pressure (MAP), and the risk of HBP.

METHODS

In this cross-sectional study, a total of 1044 primary school children (6-8 years old) were enrolled from Shenzhen, China, between 2016 and 2017. Nine mPAEs were analyzed from urine using ultra-performance liquid chromatography and tandem mass spectrometry. A multivariable linear regression model was used to explore the associations between phthalate exposure and systolic/diastolic BP, PP, and MAP. A binary logistic regression model was used to examine the associations between phthalate exposure and the risk of HBP.

RESULTS

Monomethyl phthalate (MMP) concentrations were significantly higher in HBP children than normal BP children. MMP, monoisobutyl phthalate (MiBP), monobutyl phthalate (MnBP), mono(5-carboxy-2-ethylpentyl) phthalate, mono-[(2-carboxy methyl)hexyl] phthalate (MCMHP), the sum of four short-chain mPAEs (∑LMW), and the sum of all nine mPAEs (∑₉mPAEs) were significantly positively associated with increases in systolic BP z-score, while only MMP was significantly positively associated with diastolic BP z-score. MMP, MiBP, MnBP, MCMHP, ∑LMW, and ∑₉mPAEs were significantly associated with increases in PP, while MMP and MnBP were significantly associated with increases in MAP. MMP was significantly associated with the risk of HBP, with an odds ratio of 1.87 (95% CI: 1.23, 2.85).

CONCLUSIONS

The present study suggests that dimethyl phthalate exposure increases the risk of HBP. And some types of phthalates are associated with elevations in systolic/diastolic BP z scores, PP, and MAP in Chinese children.

Associations of long-term exposure to ambient air pollution with cardiac conduction abnormalities in Chinese adults: The CHCN-BTH cohort study

BACKGROUND

Evidence regarding the effects of long-term and high-level ambient air pollution exposure on cardiac conduction systems remains sparse.

OBJECTIVES

To investigate the associations of long-term exposure to air pollution and cardiac conduction abnormalities in Chinese adults and explore the susceptibility characteristics.

METHODS

In 2017, a total of 27,047 participants aged 18-80 years were recruited from the baseline survey of the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin and Hebei (CHCN-BTH). The three year (2014-2016) average pollutant concentrations were assessed by a spatial statistical model for PM_2.5 and air monitoring stations for PM₁₀, SO₂, NO₂, O₃ and CO. Residential proximity to a roadway was calculated by neighborhood analysis. Associations were estimated by two-level generalized linear mixed models. Stratified analyses related to demographic characteristics, health behaviors, and cardiometabolic risk factors were performed. Two-pollutant models were used to evaluate the possible role of single pollutants.

RESULTS

We detected significant associations of long-term air pollutant exposure with increased heart rate (HR), QRS and QTc, such that an interquartile range increase in PM_2.5 was associated with 3.63% (95% CI: 3.07%, 4.19%), 1.21% (95% CI: 0.83%, 1.60%), and 0.13% (95% CI: 0.07%, 0.18%) changes in HR, QRS and QTc, respectively. Compared to the other pollutants, the estimates of PM_2.5 remained the most stable across all two-pollutant models. Similarly, significant associations were observed between living closer to a major roadway and higher HR, QRS and QTc. Stratified analyses showed generally greater association estimates in older people, males, smokers, alcohol drinkers, and those with obesity, hypertension and diabetes.

CONCLUSIONS

Long-term exposure to ambient air pollution was associated with cardiac conduction abnormalities in Chinese adults, especially in older people, males, smokers, alcohol drinkers, and those with cardiometabolic risk factors. PM_2.5 may be the most stable pollutant to reflect the associations.

Ambient air pollutants aggravate association of snoring with prevalent hypertension: results from the Henan Rural Cohort

AIM

We aimed to assess if snoring and ambient air pollutants were jointly associated with prevalent hypertension in a cross-sectional study.

METHODS

A total of 28440 participants aged 18-79 years were obtained from the Henan Rural Cohort. Snoring evaluated using Pittsburgh sleep quality index (PSQI) scale was classified into 'Never', '<3 times/week' and '≥3 times/week' groups. Concentrations of air pollutants (PM₁, PM_2.5, PM₁₀, and NO₂) were evaluated by a satellite-based spatiotemporal model. The independent and joint associations between snoring and air pollutants on prevalence of hypertension were analyzed by logistic regression models.

RESULTS

The mean age of all participants was 56.0 ± 12.2 years. The frequencies and prevalence of participants with hypertension were 3666 (32.39%) in men and 5576(32.57%) in women, respectively. The odds ratio (OR) and 95% confidence interval (CI) of participants with snoring frequency of <3 times/week, ≥3 times/week was 1.10(1.02-1.20), and 1.15(1.08-1.23) for hypertension, compared to those without snoring. Participants with a snoring (≥3 times/week) and higher exposure concentrations of PM₁, PM_2.5, PM₁₀, and NO₂ had 2.58-fold(95% CI: 2.30-2.90), 3.03-fold(95% CI: 2.69-3.41), 2.89-fold(95% CI: 2.57-3.25) and 2.75-fold(95% CI: 2.44-3.10) for hypertension, compared to those without snoring and low concentrations of air pollutants. Additionally, participants with high PM₁ and ≥3 times/week snoring (OR: 1.32, 95% CI: 1.18-1.48) was at a higher likelihood for prevalent hypertension, compared to those without snoring and with high PM₁.

CONCLUSIONS

Snoring and high ambient air pollutants might be important predictors of hypertension, and higher concentration of PM₁ might aggravate the association between snoring and hypertension.

Long-term effects of ambient air pollutants on suicidal ideation in China: The Henan Rural Cohort Study

BACKGROUND

The association between ambient air pollutants exposure and suicidal ideation (SI) has rarely been explored, especially in Chinese population. Therefore, we aimed to investigate the long-term effects of ambient air pollutants on SI among a Chinese rural population.

METHOD

We recruited 29997 participants from the Henan Rural Cohort study in 2016-2017. SI was evaluated by using the ninth item of the Patient Health Questionnaire-9 (PHQ-9) in the baseline survey. We adopted a satellite-based spatiotemporal model to estimate participants' exposure to particulate matters (PMs) (PM with an aerodynamic diameter ≤1 μm (PM₁), ≤2.5 μm (PM_2.5) or ≤10 μm (PM₁₀), respectively) and nitrogen dioxide (NO₂), and then calculated the 3-year average concentrations of the four pollutants. We used logistic regression models to explore the association between long-term exposure to ambient air pollutants and SI. In addition, we conducted several stratified analyses to examine effect modification of selected factors.

RESULTS

The odds ratios (95% confidence intervals [CI]) of SI in response to each 1 μg/m³ increase in PM₁, PM_2.5, PM₁₀ and NO₂ concentrations were 1.08 (1.01, 1.15), 1.10 (1.02, 1.19), 1.05 (1.01, 1.09) and 1.12 (1.04, 1.21), respectively. Individuals exposed to PM₁, PM_2.5, PM₁₀ or NO₂ concentrations in the fourth quartile had a 1.36-fold (95%CI: 1.08, 1.72), 1.69-fold (95%CI: 1.05, 2.72), 1.49-fold (95%CI: 1.09, 2.05) or 1.71-fold (95%CI: 1.15, 2.85) risks of SI, compared to the ones with corresponding air pollutants in the first quartile. Besides, the risks of SI increased with the quartiles of air pollutants (PM₁: P_trend = 0.002, PM_2.5: P_trend = 0.003, PM₁₀: P_trend = 0.010, NO₂: P_trend = 0.010). Stratified analyses suggested that males, highly educated participants, ever-drinkers and people aged range 36-64 years were more vulnerable to the adverse effects of air pollutants.

CONCLUSIONS

This study provided evidence for the long-term effects of ambient PMs and NO₂ on SI in rural Chinese adults, particularly for males, highly educated participants, ever-drinkers and people aged range 36-64 years.

Earth Observation Data Supporting Non-Communicable Disease Research: A Review

A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.

Physical activity attenuated association of air pollution with estimated 10-year atherosclerotic cardiovascular disease risk in a large rural Chinese adult population: A cross-sectional study

BACKGROUND

Although long-term exposure to air pollution and physical inactivity are linked to increased risk for atherosclerotic cardiovascular diseases (ASCVD), however, the interactive effect of air pollution and physical activity (PA) on high 10-year ASCVD risk is largely unknown.

METHODS

A total of 31,162 individuals aged 35-74 years were derived from the Henan Rural Cohort Study, after individuals with personal histories of ASCVD or missing data on predictors of high 10-year ASCVD risk were excluded. Concentrations of air pollutants (nitrogen dioxide (NO₂), particulate matter with an aerodynamics diameters ≤ 1.0 µm (PM₁), ≤2.5 µm (PM_2.5) or ≤10 µm (PM₁₀)) of individuals were estimated using a spatiotemporal model based on satellites data. The metabolic equivalent (MET) of PA of each individual was evaluated using the formula: duration (hour/time) × frequency/week × MET coefficient of each type of activity. Logistic regression models were used to analyze associations between air pollutants, PA and high 10-year ASCVD risk. Interaction plots were used to describe interactive effects of air pollutants and PA on high 10-year ASCVD risk.

RESULTS

Each 1 µg/m³ increase in PM₁, PM_2.5, PM₁₀ and NO₂ were related to a 4.4% (odds ratio (OR): 1.044, 95% confidence interval (CI): 1.034, 1.056), 9.1% (OR: 1.091, 95% CI: 1.079, 1.104), 4.6% (OR: 1.046, 95% CI: 1.040, 1.051) or 6.4% (OR: 1.064, 95% CI: 1.055, 1.072) increase in high 10-year ASCVD risk (all p < 0.001), respectively; each one unit-increase in PA MET (hour/day) value was related to a 1.8% (OR: 0.982, 95% CI: 0.980, 0.985) decrease in high 10-year ASCVD risk. Negative interactive effects of PA and PM₁, PM_2.5, PM₁₀ and NO₂ on high 10-year ASCVD risk were observed (all p < 0.001).

CONCLUSION

Exposure to high levels of air pollutants were related to increase high 10-year ASCVD risk and these associations were attenuated by PA, implying that PA may be an effective method to the prevention of high 10-year ASCVD risk in highly polluted rural regions.