Effect of changes in season and temperature on cardiovascular mortality associated with nitrogen dioxide air pollution in Shenzhen, China

A Review of the Interactive Effects of Climate and Air Pollution on Human Health in China

PURPOSE OF REVIEW

Through a systematic search of peer-reviewed epidemiologic studies, we reviewed the literature on the human health impacts of climate and ambient air pollution, focusing on recently published studies in China. Selected previous literature is discussed where relevant in tracing the origins.

RECENT FINDINGS

Climate variables and air pollution have a complex interplay in affecting human health. The bulk of the literature we reviewed focuses on the air pollutants ozone and fine particulate matter and temperatures (including hot and cold extremes). The interaction between temperature and ozone presented substantial interaction, but evidence about the interactive effects of temperature with other air pollutants is inconsistent. Most included studies used a time-series design, usually with daily mean temperature and air pollutant concentration as independent variables. Still, more needs to be studied about the co-occurrence of climate and air pollution. The co-occurrence of extreme climate and air pollution events is likely to become an increasing health risk in China and many parts of the world as climate changes. Climate change can interact with air pollution exposure to amplify risks to human health. Challenges and opportunities to assess the combined effect of climate variables and air pollution on human health are discussed in this review. Implications from epidemiological studies for implementing coordinated measures and policies for addressing climate change and air pollution will be critical areas of future work.

Explore the effect of apparent temperature and air pollutants on the admission rate of acute myocardial infarction in Chongqing, China: a time-series study

OBJECTIVE

Limited research has been conducted on the correlation between apparent temperature and acute myocardial infarction (AMI), as well as the potential impact of air pollutants in modifying this relationship. The objective of this study is to investigate the lagged effect of apparent temperature on AMI and assess the effect modification of environmental pollutants on this association.

DESIGN

A time-series study.

SETTING AND PARTICIPANTS

The data for this study were obtained from the Academy of Medical Data Science at Chongqing Medical University, covering daily hospitalisations for AMI between 1 January 2015 and 31 December 2016. Meteorological and air pollutant data were provided by China's National Meteorological Information Centre.

OUTCOME MEASURES

We used a combined approach of quasi-Poisson generalised linear model and distributed lag non-linear model to thoroughly analyse the relationships. Additionally, we employed a generalised additive model to investigate the interaction between air pollutants and apparent temperature on the effect of AMI.

RESULT

A total of 872 patients admitted to hospital with AMI were studied based on the median apparent temperature (20.43°C) in Chongqing. Low apparent temperature (10th, 7.19℃) has obvious lagged effect on acute myocardial infarction, first appearing on the 8th day (risk ratio (RR) 1.081, 95% CI 1.010 to 1.158) and the greatest risk on the 11th day (RR 1.094, 95% CI 1.037 to 1.153). No lagged effect was observed at high apparent temperature. In subgroup analysis, women and individuals aged 75 and above were at high risk. The interaction analysis indicates that there exist significant interactions between PM2.5 and high apparent temperature, as well as nitrogen dioxide (NO2) and low apparent temperature.

CONCLUSION

The occurrence of decreased apparent temperature levels was discovered to be linked with a heightened relative risk of hospitalisations for AMI. PM2.5 and NO2 have an effect modification on the association between apparent temperature and admission rate of AMI.

Association between thermal stress and cardiovascular mortality in the subtropics

Hazardous thermal conditions resulting from climate change may play a role in cardiovascular disease development. We chose the Universal Thermal Climate Index (UTCI) as the exposure metric to evaluate the relationship between thermal conditions and cardiovascular mortality in Shenzhen, China. We applied quasi-Poisson regression non-linear distributed lag models to evaluate the exposure-response associations. The findings suggest that cardiovascular mortality risks were significantly increased under heat and cold stress, and the adverse effects of cold stress were stronger than heat stress. Referencing the 50th percentile of UTCI (25.4°C), the cumulative risk of cardiovascular mortality was 75% (RRlag0-21 =1.75, 95%CI: 1.32, 2.32) higher in the 1st percentile (3.5°C), and 40% (RRlag0-21=1.40, 95%CI: 1.09, 1.80) higher in the 99th percentile (34.1°C). We observed that individuals older than 65 years were more vulnerable to both cold and heat stress, and females were identified as more susceptible to heat stress than males. Moreover, increased mortality risks of hypertensive disease and cerebrovascular disease were observed under cold stress, while heat stress was related to higher risks of mortality for hypertensive disease and ischemic heart disease. We also observed a stronger relationship between cold stress and ischemic heart disease mortality during the cold season, as well as a significant impact of heat stress on cerebrovascular disease mortality in the warm season when compared to the analysis of the entire year. These results confirm the significant relationship between thermal stress and cardiovascular mortality, with age and sex as potential effect modifiers of this association. Providing affordable air conditioning equipment, increasing the amount of vegetation, and establishing comprehensive early warning systems that take human thermoregulation into account could all help to safeguard the well-being of the public, particularly vulnerable populations, in the event of future extreme weather.

Effect of Air Pollutants and Meteorological Factors on Daily Outpatient Visits of Allergic Rhinitis in Hohhot, China

Objective

There is limited evidence that atmospheric pollutants are associated with the number of allergic rhinitis (AR) visits. This study aimed to investigate the relationship between atmospheric pollutants and meteorological factors and the number of daily visits for AR in Hohhot City, providing a theoretical basis for further research on the effects of atmospheric pollutants on AR.

Methods

Microsoft Excel 2016 was used to collect and organize the AR outpatient consultation data, air pollution and meteorological data in Hohhot City during 2018-2020, and the data were descriptively analyzed and Spearman correlation test was performed using SPSS22.0; A generalized additive model was built in R4.2.3 to analyze the effect of air pollution on the number of AR visits and its lagged and cumulative effects, while the robustness of the model was tested using a two-pollutant analysis. Finally, we analyzed the effects of the interaction of temperature, relative humidity and pollutants on the number of AR visits.

Results

The daily average concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 in Hohhot during 2018-2020 were 38.1 μg/m3, 83.3 μg/m3, 36.1 μg/m3, 15.1 μg/m3, 14.2 mg/m3, and 99.95 μg/m3, respectively, with the concentrations of PM2.5 and PM10 exceeding the secondary limit of the national standard. The results of the generalized additive model analysis showed that the RR and 95% CI of the effect of each 10 μg/m3 increase in pollutant concentration (1 mg/m3 increase in CO) on the number of AR outpatient clinics were 1.008 (1.001-1.016), 1.002 (1-1.005), 1.072 (1.033-1.113), 1.020 (1007-1.034), 1.033 (1.014-1.052), 0.987 (0.9804-0.9936).

Conclusion

Short-term exposure to PM2.5, PM10, SO2, NO2, and CO was significantly associated with an increase in AR clinic visits, and short-term exposure to O3 was significantly associated with a decrease in allergic rhinitis clinic visits.

Intimately tracking NO2 pollution over the New York City - Long Island Sound land-water continuum: An integration of shipboard, airborne, satellite observations, and models

Nitrogen dioxide (NO2) pollution remains a serious global problem, particularly near highly populated urbanized coasts that face increasing challenges with climate change. Yet, the combined impact of urban emissions, pollution transport, and complex meteorology on the spatiotemporal dynamics of NO2 along heterogeneous urban coastlines remains poorly characterized. Here, we integrated measurements from different platforms - boats, ground-based networks, aircraft, and satellites - to characterize total column NO2 (TCNO2) dynamics across the land-water continuum in the New York metropolitan area, the most populous area in the United States that often experiences the highest national NO2 levels. Measurements were conducted during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS), with a main goal to extend surface measurements beyond the coastline - where ground-based air-quality monitoring networks abruptly stop - and over the aquatic environment where peaks in air pollution often occur. Satellite TCNO2 from TROPOMI correlated strongly with Pandora surface measurements (r = 0.87, N = 100) both over land and water. Yet, TROPOMI overall underestimated TCNO2 (MPD = -12%) and missed peaks in NO2 pollution caused by rush hour emissions or pollution accumulation during sea breezes. Aircraft retrievals were in excellent agreement with Pandora (r = 0.95, MPD = -0.3%, N = 108). Stronger agreement was found between TROPOMI, aircraft, and Pandora over land, while over water satellite, and to a lesser extent aircraft, retrievals underestimated TCNO2 particularly in the highly dynamic New York Harbor environment. Combined with model simulations, our shipborne measurements uniquely captured rapid transitions and fine-scale features in NO2 behavior across the New York City - Long Island Sound land-water continuum, driven by the complex interplay of human activity, chemistry, and local scale meteorology. These novel datasets provide critical information for improving satellite retrievals, enhancing air quality models, and informing management decisions, with important implications for the health of diverse communities and vulnerable ecosystems along this complex urban coastline.

Short-term effect of meteorological factors and extreme weather events on daily outpatient visits for dry eye disease between 2013 and 2020: a time-series study in Urumqi, China

Dry eye disease (DED) is a common disorder of tear secretion on the ocular surface caused by multiple factors with dry eyes as the main symptom, but until now studies focusing on relationship between local meteorological factors and ocular surface diseases in Urumqi are very limited. Besides, the effects of long-term and extreme meteorological factors on DED and the lag effect have not been fully evaluated. Electronic case information of 9970 DED outpatients from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) between January 1, 2013, and December 31, 2020, was screened and analyzed. We used a time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) to fit the effects of exposure to different meteorological factors and extreme weather on DED outpatient visits. Subgroup analyses were further performed for gender, age, and season. The results showed that exposure to extremely low mean temperature (P1:RR = 1.18), atmospheric pressure (P1:RR = 1.11), and extremely high relative humidity (P99:RR = 1.35) were the risk factors, while extremely high atmospheric pressure (P90:RR = 0.883) and extremely low humidity (P10:RR = 0.856) appeared to have a positive effect on reduced risk of DED. Relative humidity exhibited a 1-day lag effect (RR = 1.06). Increased mean temperature positively affected female DED patients (RR = 0.761) with similar effects in the cold season (RR = 0.926). However, elevated relative humidity had a negative effect on female patients (RR = 1.14). We conducted the first large sample size time-series analysis study in this major city at the farthest distance from the ocean in the world and in northwest China, confirming the association of DED outpatient visits with the remaining three meteorological factors except wind speed in Urumqi, and a larger sample size multi-center epidemiological study with a longer duration is still needed.

Exposure to ambient air pollutants and short-term risk for exacerbations of allergic rhinitis: a time-stratified, case-crossover study in the three largest urban agglomerations in Poland

Allergic rhinitis (AR) affects 10% of the world population, with an increased prevalence in regions with substantial air pollution, but the association between exposure to air pollutants and the short-term risk of AR exacerbations is unclear. We used a time-series approach to analyze the risk of hospital admissions due to AR over 8 days from exposure to various air pollutants. Distributed lag nonlinear models were used to analyze data gathered between 2012 and 2018 in the three largest urban agglomerations in Poland. The analyses were carried out separately for the warm (April - September) and cold seasons (October - March). Overall, there were 1407 admissions due to AR. In the warm season, the rate ratio (95% confidence interval) for admission per 10µg/m3 was 1.202 (1.044, 1.384) for particulate matter less than 10 microns (PM10); 1.094 (0.896, 1.335) for particulate matter less than 2.5 microns (PM2.5); 0.946 (0.826, 1.085) for nitrogen dioxide (NO₂); 0.837 (0.418, 1.677) for sulfur dioxide (SO₂); and 1.112 (1.011, 1.224) for ozone (O₃). In the cold season, the rate ratio for admission per 10µg/m3 was 1.035 (0.985, 1.088) for PM10; 1.041 (0.977, 1.108) for PM2.5; 1.252 (1.122, 1.398) for NO₂; 0.921 (0.717, 1.181) for SO₂; and 1.030 (1.011, 1.050) for O₃. In conclusion, the risk of admission due to AR increased significantly after exposure to O₃ in the warm and cold seasons. Exposure to PM10 was associated with a significantly increased risk of AR hospitalizations in the warm season only, whereas exposure to NO₂ was associated with a significantly increased risk of AR admission in the cold season.

Long-term effects of meteorological factors and extreme weather on daily outpatient visits for conjunctivitis from 2013 to 2020: a time-series study in Urumqi, China

Conjunctivitis is a common multifactorial inflammatory ocular surface disease characterized by symptoms such as congestion, edema, and increased secretion of conjunctival tissue, and the potential effects of meteorological factors as well as extreme meteorological factors on conjunctivitis and their lagging effects have not been fully evaluated. We obtained the electronic case information of 59,731 outpatients with conjunctivitis from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) for the period from January 1, 2013, to December 31, 2020. Meteorological data for daily mean temperature (°C), daily relative humidity (%), daily average wind speed (m/s), and atmospheric pressure (hPa) were obtained from the China Meteorological Data Sharing Service. The air pollutant data were obtained from 11 standard urban background fixed air quality monitors. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effects of exposure to different meteorological factors and extreme weather on conjunctivitis outpatient visits. Subgroup analyses were performed on gender, age and season, and type of conjunctivitis. Univariate and multifactorial model results indicated that each 10-unit increase in mean temperature and relative humidity was associated with an increased risk of conjunctivitis outpatient visits, while each 10-unit increase in atmospheric pressure was associated with a decreased risk. The results of the extreme weather analysis suggested that extremely low levels of atmospheric pressure and relative humidity as well as extreme levels of temperature were associated with an increased risk of outpatient conjunctivitis visits, and extreme wind speeds were associated with a decreased risk. The results of the subgroup analysis suggested gender, age, and seasonal differences. We conducted the first large sample size time-series analysis in the large city furthest from the ocean in the world and confirmed for the first time that elevated mean temperature and extreme low levels of relative humidity in Urumqi were risk factors for local conjunctivitis outpatient visits, while elevated atmospheric pressure and extreme low levels of wind speed were protective factors, and there were lagged effects of temperature and atmospheric pressure. Multicenter studies with larger sample sizes are needed.

County level study of the interaction effect of PM2.5 and climate sustainability on mortality in China

Introduction

PM2.5 and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution.

Methods

In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM2.5.

Results and discussions

Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM2.5 is more than 35 μg/m3, the influence on mortality is significantly increased as PM2.5 concentration rises; when PM2.5 is above 70 μg/m3, the trend is sharp. A nonlinear antagonistic effect between CLS and PM2.5 was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM2.5 was higher (above 35 μg/m3), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM2.5 on mortality varies in different geographical regions. A negative and positive influence of CLS and PM2.5 was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.

Combined effect of preconceptional and prenatal exposure to air pollution and temperature on childhood pneumonia: A case-control study

Mounting evidence have linked ambient air pollution and temperature with childhood pneumonia, but it is unclear whether there is an interaction between air pollution and temperature on childhood pneumonia. We aim to assess the combined effect of ambient air pollution and temperature exposure during preconception and pregnancy on pneumonia by a case-control study of 1510 children aged 0-14 years in Changsha, China. We obtained the data of childhood pneumonia from XiangYa Hospital electrical records. We estimated personal exposure to outdoor air pollution (PM₁₀, SO₂ and NO₂) by inverse distance weighted (IDW) method and temperature indicators. Multiple logistic regression models were used to evaluate associations of childhood pneumonia with air pollution, temperature (T), and diurnal temperature variation (DTV). We found that exposure to industry-related air pollution (PM₁₀ and SO₂) during preconception and pregnancy were associated with childhood pneumonia, with ORs (95% CI) of 1.72 (1.48-1.98) and 2.96 (2.50-3.51) during 1 year before pregnancy and 1.83 (1.59-2.11) and 3.43 (2.83-4.17) in pregnancy. Childhood pneumonia was negatively associated with T exposure during 1 year before pregnancy and pregnancy, with ORs (95% CI) of 0.57 (0.41-0.80) and 0.85 (0.74-0.98). DTV exposure during pregnancy especially during the 1st and 2nd trimesters significantly increased pneumonia risk, with ORS (95% CI) of 1.77 (1.19-2.64), 1.47 (1.18-1.83), and 1.37 (1.07-1.76) respectively. We further observed interactions of PM₁₀ and SO₂ exposure with low T and high DTV during conception and pregnancy in relation to childhood pneumonia. This study suggests that there were interactions air pollution with temperature and DTV on pneumonia development.

Association between ambient carbon monoxide levels and hospitalization costs of patients with myocardial infarction: Potential effect modification by ABO blood group

Previous researches have reported the association between air pollution and various diseases. However, few researches have investigated whether air pollutants are associated with the economic loss resulting from patients' hospitalization, especially the economic loss of hospitalization due to acute cardiovascular events. The purpose of our research was to explore the association between the levels of carbon monoxide (CO), taken as an index of pollution, and the hospitalization costs of myocardial infarction (MI), and the potential effect modification by the ABO blood group. A total of 3237 MI inpatients were included in this study. A multiple linear regression model was used to evaluate the association between ambient CO levels and hospitalization costs of MI patients. Moreover, we performed stratified analyses by age, gender, body mass index (BMI), season, hypertension, and ABO blood types. There was a positive association between the levels of CO in the air and the costs of hospitalization caused by MI. Furthermore, such association was stronger in males, BMI ≥25, <65 years, with hypertension, and non-O blood group. Interestingly, we found the association was particularly significant in patients with blood group B. Overall, our study first found that ambient CO levels could have an impact on the hospitalization costs for MI patients, and those with blood group B can be more sensitive.

Health and economic impacts of ambient air pollution on hospital admissions for overall and specific cardiovascular diseases in Panzhihua, Southwestern China

Background

The associations of ambient air pollution with hospital admissions (HAs) for overall and specific causes of cardiovascular diseases (CVDs), as well as related morbidity and economic burdens remain understudied, especially in low-pollution areas of low- and middle-income countries (LMICs). We evaluated the short-term effects of exposure to PM_2.5 (particles with an aerodynamic diameter ≤2.5 μm), PM₁₀ (particles with an aerodynamic diameter ≤10 μm), and SO₂ (sulfur dioxide) on HAs for CVDs in Panzhihua, China, during 2016-2020, and calculated corresponding attributable risks and economic burden.

Methods

We used a generalized additive model (GAM) while controlling for time trends, meteorological conditions, holidays, and days of the week to estimate the associations. The cost of illness (COI) method was adopted to further assess corresponding hospitalization costs and productivity losses.

Results

A total of 27 660 HAs for CVDs were included in this study. PM₁₀ and SO₂ were significantly associated with elevated risks of CVDs hospitalizations. Each 10 μg/m³ increase in PM₁₀ and SO₂ at lag06 corresponded to an increase of 2.48% (95% confidence interval (CI) = 0.92%-4.06%), and 5.50% (95% CI = 3.09%-7.97%) in risk of HAs for CVDs, respectively. The risk estimates of PM₁₀ and SO₂ on CVD hospitalizations were generally robust after adjustment for other pollutants in two-pollutant models. We found stronger associations between air pollution (PM₁₀ and SO₂) and CVDs in cool seasons than in warm seasons. For specific causes of CVDs, significant associations of PM₁₀ and SO₂ exposure with cerebrovascular disease and ischaemic heart disease were observed. Using 0 μg/m³ as the reference concentrations, 11.91% (95%CI = 4.64%-18.56%) and 15.71% (95%CI = 9.30%-21.60%) of HAs for CVDs could be attributable to PM₁₀ and SO₂, respectively. During the study period, PM₁₀ and SO₂ brought 144.34 million Yuan economic losses for overall CVDs, accounting for 0.028% of local GDP.

Conclusions

Our results suggest that PM₁₀ and SO₂ exposure might be an important trigger of HAs for CVDs and accounted for substantial morbidity and economic burden.

Identification of Health Effects of Complex Air Pollution in China

After the Chinese government introduced a series of policies to strengthen the control of air pollution, the concentration of particulate matter has decreased, but the concentration of ozone has increased, and the problem of complex air pollution still exists, posing a serious threat to public health. Therefore, disentangling the health effect of multi-pollutants has been a long-discussed challenge in China. To evaluate the adverse effects of complex air pollution, a generalized additive model was used to assess the health risks of different pollution types in eight metropolises in different climates in China from 2013 to 2016. Instead of directly introducing multiple pollutant concentrations, we integrated the concentration levels of PM_2.5, NO₂, and O₃ into a set of predictors by grouping methods and divided air pollution into three high single-pollutant types and four high multi-pollutant types to calculate mortality risk in different types. The comprehensive results showed that the impact of high multi-pollutant types on mortality risk was greater than that of high single-pollutant types. Throughout the study period, the high multi-pollutant type with high PM_2.5, NO₂, and O₃ and the high multi-pollutant type with high PM_2.5 and NO₂ were more associated with death, and the highest RRs were 1.129 (1.080, 1.181) and 1.089 (1.066, 1.113), respectively. In addition, the pollution types that most threaten people are different in different cities. These differences may be related to different pollution conditions, pollutant composition, and indoor-outdoor activity patterns in different cities. Seasonally, the risk of complex air pollution is greater in most cities in the warm season than in the cold season. This may be caused by the modifying effects of high temperature on pollutants in addition to different indoor-outdoor activity patterns in different seasons. The results also show that calculating the effect of individual air pollutants separately and adding them together may lead to an overestimation of the combined effect. It further highlights the urgency and need for air pollution health research to move towards a multi-pollutant approach that considers air pollution as a whole in the context of atmospheric abatement and global warming.

Association between ambient PM2.5 and outpatient visits of children's respiratory diseases in a megacity in Central China

Objective

To explore the relationship between ambient PM_2.5 level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China.

Methods

We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman's rank correlation to analyze the correlation between children's respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM_2.5 exposures and children's respiratory outpatient visits. A stratified analysis was further carried out for the seasons.

Results

From 2018 to 2020, the total number of outpatients with children's respiratory diseases was 79,1107, and the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h in Zhengzhou were respectively 59.48 μg/m³, 111.12 μg/m³, 11.10 μg/m³, 47.77 μg/m³, 0.90 mg/m³ and 108.81 μg/m³. The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m³ increase in PM_2.5 with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM_2.5 on children's respiratory disease visits was robust. The excess risk of PM_2.5 on children's respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO₂ was adjusted. However, the PM_2.5 effects were stronger during the heating period than during the non-heating period.

Conclusion

The short-term exposure to PM_2.5 was significantly associated with outpatient visits for children's respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children's health.

Interactive short-term effects of meteorological factors and air pollution on hospital admissions for cardiovascular diseases

A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.

The impact of cold spells on schizophrenia admissions and the synergistic effect with the air quality index

OBJECTIVES

Under current global climate conditions, there are insufficient studies on the health influences of cold spells, especially on mental health. This study aimed to examine the effect of cold spells on schizophrenia admissions and to analyze the potential interaction effect with the air quality index (AQI).

METHODS

Daily data on schizophrenia admissions and climatic variables in Hefei were collected from 2013 to 2019. Based on 20 definitions, the impacts of cold spells were quantified separately to find the most appropriate definition for the region, and meta-regression was used to explore the different effect sizes of the different days in a cold spell event. In addition, the potential interaction effect was tested by introducing a categorical variable, CSH, reflecting the cold spell and AQI level.

RESULTS

The cold spell defined by temperature below the 6th centile while lasting for at least three days produced the optimum model fit performance. In general, the risk of schizophrenia admissions increased on cold spell days. The largest single-day effect occurred on the 12th day with RR = 1.081 (95% CI: 1.044, 1.118). In a single cold spell event, the effect of the 3rd and subsequent days of a cold spell (RR = 1.082, 95% CI: 1.036, 1.130) was higher than that on the 2nd day (RR = 1.054, 95% CI: 1.024, 1.085). Similarly, the effect of the 2nd day was also higher than that of the 1st day (RR = 1.027, 95% CI: 1.012, 1.042). We found a synergistic effect between cold spells and high AQI in the male group, and the relative excess risk due to interaction (RERI) was 0.018 (95% CI: 0.005-0.030).

CONCLUSIONS

This study suggested that the impacts of cold spells should be considered based on the definition of the most appropriate for the region when formulating targeted measures of schizophrenia. The discovery of the synergistic effect was referred to help the selection of the timing of precautions for susceptible people.

More obvious association between short-term ambient nitrogen dioxide and atrial fibrillation outpatient visits in cool seasons: A hospital-based study in northwestern China

Atrial fibrillation (AF) is the most common sustained heart rhythm disorder associated with high mortality and morbidity. Limited studies have been conducted to assess the relationship between short-term exposure to ambient air pollution and AF attacks. This study aimed to explore the association between short-term ambient nitrogen dioxide (NO₂) exposure and outpatient visits for AF in Xi'an, China. Data on daily AF outpatient visits and air pollutants from 2013 to 2019 (2555 days) were obtained. A time-series approach using over-dispersed Poisson generalized additive model (GAM) was employed, and stratified analyses were performed to investigate the potential modifying effects by season, age, and gender. A total of 8307 outpatient visits for AF were recorded. Increased levels of NO₂ were associated with increased AF outpatient visits, and the most significant effect estimates were observed at lag 03: A 10 μg/m³ increase of NO₂ at lag 03 was related to an elevation of 5.59% (95% CI: 2.67%, 8.51%) in daily outpatient visits for AF. Stratified analyses showed that there were no gender and age difference in the effect of NO₂, while more obvious association was observed in cool seasons (October to March) than in warm seasons (April to September). In summary, short-term ambient NO₂ exposure can be positively associated with daily outpatient visits for AF, especially in cool seasons. This work provided novel data that the association between air pollutants and AF can vary by seasons, further supporting that the prevention of cardiovascular health effects should be strengthened in winter.

Modification effects of seasonal and temperature variation on the association between exposure to nitrogen dioxide and ischemic stroke onset in Shenzhen, China

The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO₂) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO₂ on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO₂ and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO₂-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO₂ and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 μg/m³ increment in NO₂ concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO₂ during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO₂, were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO₂ on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.

"Medical Assistance in Contextual Awareness" (AMICO): A Project for a Better Quality of Care for Patients in Cardiac Rehabilitation Unit

The "Medical Assistance in Contextual Awareness" (AMICO) project proposes an infrastructure, called an "instrumented environment", consisting of the home environment and the person, both of which are suitably equipped with sensors, a telemedicine service platform (in the Internet of Things) and a Robot who acts as a mediator/master between the person, the surrounding environment and the external environment. This infrastructure, oriented to the citizen's well-being, can offer both services oriented to the person in his home environment, monitoring their behavior and psycho-physical state, and telemedicine services to support the remote monitoring of citizens affected by a cardiovascular event undergoing rehabilitation therapies from part of doctors or caregiver.

Impact of Short-Term Air Pollution on Respiratory Infections: A Time-Series Analysis of COVID-19 Cases in California during the 2020 Wildfire Season

The 2020 California wildfire season coincided with the peak of the COVID-19 pandemic affecting many counties in California, with impacts on air quality. We quantitatively analyzed the short-term effect of air pollution on COVID-19 transmission using county-level data collected during the 2020 wildfire season. Using time-series methodology, we assessed the relationship between short-term exposure to particulate matter (PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), and Air Quality Index (AQI) on confirmed cases of COVID-19 across 20 counties impacted by wildfires. Our findings indicate that PM2.5, CO, and AQI are positively associated with confirmed COVID-19 cases. This suggests that increased air pollution could worsen the situation of a health crisis such as the COVID-19 pandemic. Health policymakers should make tailored policies to cope with situations that may increase the level of air pollution, especially during a wildfire season.

Effects of nitrogen dioxide exposure on the risk of eye and adnexa diseases among children in Shenzhen, China: an assessment using the generalized additive modeling approach

This study aimed to assess the relationship between nitrogen dioxide (NO₂) exposure and the risk of eye and adnexa diseases (EADs) among children in Shenzhen, China. Information about the daily number of outpatients with EADs and the concentration of air pollutants and meteorological data were collected. A generalized additive model was used to assess the effect of NO₂ exposure on the risk of EADs during outpatient visits. An increase in NO₂ level by 10 μg/m³ was related to an increase in the daily number of outpatients by 5.43% (95% confidence interval [CI]: 2.25%, 8.70%) at lag0, by 4.35% (95% CI: 1.15%, 7.66%) at lag1, and by 3.21% (95% CI: 0.05%, 6.47%) at lag3. In addition, the relationship between NO₂ exposure and the risk of dacryoadenitis was the strongest, with an estimated value of 15.0% (95% CI: 7.99%, 22.5%) at lag0. Moreover, the association between NO₂ exposure and the risk of EADs among children in Shenzhen was confirmed in this study. Therefore, the government should introduce stringent environmental policies to control air pollution and protect human health, particularly that of the vulnerable population.

Time series analysis of short-term effects of particulate matter pollution on the circulatory system disease mortality risk in Lishui District, China

Epidemiological evidence has shown a significant association between short-term exposure to air pollution and mortality risk for circulatory system diseases (CSD). However, informative insights on the significance and magnitude of its relationship in the process of government interventions on abating air pollution are still lacking, particularly in a burgeoning Chinese city. In this study, we conducted a time series study in Lishui District, Nanjing, to examine the effect of ambient particulate matter (PM), e.g., PM_2.5 and PM₁₀, on daily death counts of CSD which included cardiovascular disease (CVD), cerebrovascular disease (CEVD), and arteriosclerotic heart disease (ASHD) mortality from January 1, 2015, to December 31, 2019. The results revealed that each 10 μg/m³ increase in PM_2.5 and PM₁₀ concentration at lag0 day was associated with an increase of 1.33% (95% confidence interval, 0.08%, 2.60%) and 1.12% (0.43%, 1.82%) in CSD mortality; 2.42% (0.44%, 4.43%) and 1.43% (0.32%, 2.55%) in CVD mortality; 1.20% (- 0.31%, 2.73%) and 1.21% (0.38%, 2.05%) in CEVD mortality; and 2.78% (0.00%, 5.62%) and 1.66% (0.14%, 3.21%) in ASHD mortality, respectively. For cumulative risk, the corresponding increase in daily mortality for the same change in PM_2.5 concentration at lag03 day was significantly associated with 1.94% (0.23%, 3.68%), 3.17% (0.58%, 5.84%), 2.38% (0.17%, 4.63%), and 4.92% (1.18%, 8.81%) for CSD, CVD, CEVD, and ASHD, respectively. The exposure-response curves were approximately nonlinear over the entire exposure range of the PM concentrations. We also analyzed the effect modifications by season (warm or cold), age group (0-64 years, 65-74 years, or ≥ 75 years), and sex (male or female). Although not statistically significant, stratified analysis showed greater vulnerability to PM exposure for cold season, population over 65 years of age, and female group.

Association between air pollution and emergency room visits for eye diseases and effect modification by temperature in Beijing, China

The growing burden of eye disease worldwide has aroused increasing concern upon its environmental etiology. This study aims to evaluate the associations of air pollutants with emergency room visits for eye diseases and the effect modification by temperature. Based on 24,389 cases from a general hospital during 2014-2019 in Beijing, China, this study used generalized additive models to examine the associations of air pollutants and emergency room visits for total eye diseases (ICD10: H00-H59) and conjunctivitis (ICD10: H10). Short-term exposures to PM_2.5, PM₁₀, CO, and NO₂ were associated with increased visits for total eye diseases and conjunctivitis, and stronger effect estimates were observed in high (>75th) temperature group for PM_2.5, PM₁₀, CO, and NO₂ and low (<75th) temperature group for CO and NO₂. For instance, a 10 μg/m³ increase in PM_2.5 at lag0-1 were associated with a 0.73% (95% CI: 0.23%, 1.24%) increase in total eye disease visits and a 1.34% (95% CI: 0.55%, 2.13%) increase in conjunctivitis visits, respectively. Meanwhile, a 10 μg/m³ increase in PM_2.5 was associated with a 1.57% (95% CI: 0.49%, 2.64%) change in high temperature group and a 0.48% (95% CI: -0.24%, 1.19%) change in medium temperature group (P for interaction = 0.04) in total eye disease visits. Our study emphasizes the importance of controlling the potential hazards of air pollutants on eyes, especially on days with relatively higher or colder temperature.

Declines and peaks in NO2 pollution during the multiple waves of the COVID-19 pandemic in the New York metropolitan area

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NO _x ) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO₂) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO₂ pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO₂ across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NO _x emissions by approx. 30% on top of long-term trends, in agreement with sector-specific changes in NO _x emissions. Ground-based measurements showed a sudden drop in total column NO₂ in spring 2020, by up to 36% in Manhattan and 19%-29% in Queens, New Jersey (NJ), and Connecticut (CT), and a clear weakening (by 16%) of the typical weekly NO₂ cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO₂ across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO₂ coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO₂ biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO₂ conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO₂ declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO with low-speed (< 5 ms^-1) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO₂ pollution episodes in Manhattan, even during - and despite - the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO₂ measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO _x emission control strategies.

Effect of Cold Spells and Their Different Definitions on Mortality in Shenzhen, China

A high premium has been put on researching the effects of cold spells because of their adverse influence on people's daily lives and health. The study aimed to find the most appropriate definition of the cold spell in Shenzhen and quantify the impact of cold spells on mortality. Based on the daily mortality data in Shenzhen from 2013 to 2017 and the meteorological and pollutant data from the same period, we quantified the effect of cold spells using eight different definitions in the framework of a distributed lag non-linear model with a quasi-Poisson distribution. In Shenzhen, low temperatures increase the risk of death more significantly than high temperatures (using the optimal temperature as the cut-off value). Comparing the quasi-Akaike information criterion value, attribution fraction (b-AF), and attribution number (b-AN) for all causes of deaths and non-accidental deaths, the optimal definition of the cold spell was defined as the threshold was 3rd percentile of the daily average temperature and duration for 3 or more consecutive days (all causes: b-AF = 2.31% [1.01–3.50%], b-AN = 650; non-accidental: b-AF = 1.92% [0.57–3.17%], b-AN = 471). For cardiovascular deaths, the best definition was the temperature threshold as the 3rd percentile of the daily average temperature with a duration of 4 consecutive days (cardiovascular: b-AF = 1.37% [0.05–2.51%], b-AN = 142). Based on the best definition in the model, mortality risk increased in cold spells, with a statistically significant lag effect occurring as early as the 4th day and the effect of a single day lasting for 6 days. The maximum cumulative effect occurred on the 14th day (all-cause: RR = 1.54 [95% CI, 1.20–1.98]; non-accidental: RR = 1.43 [95% CI, 1.11–1.84]; cardiovascular: RR = 1.58 [95% CI, 1.00–2.48]). The elderly and females were more susceptible to cold spells. Cold spells and their definitions were associated with an increased risk of death. The findings of this research provide information for establishing an early warning system, developing preventive measures, and protecting susceptible populations.

Acute effects of ambient nitrogen oxides and interactions with temperature on cardiovascular mortality in Shenzhen, China

BACKGROUND

Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality.

METHODS

Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO₂), and nitrogen oxides (NO_X) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups.

RESULTS

The average daily concentrations of NO, NO₂, and NO_X were 11.7 μg/m³, 30.7 μg/m³, and 53.2 μg/m³, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO₂ on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships.

CONCLUSIONS

Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.

The moderating effect of solar radiation on the association between human mobility and COVID-19 infection in Europe

The novel coronavirus disease 2019 (COVID-19) has caused a global pandemic. Some studies have suggested a negative association between sunlight intensity and COVID-19 infection, alluding to the belief that it might be safe to go out on sunny days. This paper examined whether solar radiation mitigated the association between human mobility and COVID-19 infection in Europe using a dynamic panel data model to investigate the effect of human mobility, solar radiation, and their interaction on COVID-19 infection. The results revealed that outgoing mobility was positively correlated and solar radiation was negatively correlated with COVID-19 infection at lag levels of 1, 2, and 3 weeks. The coefficients of the interaction items indicated that solar radiation negatively moderated the relationship between outgoing mobility and the number of daily new confirmed cases at 2- and 3-week lag levels. However, the moderating effect was limited and unable to eliminate the positive effect of outgoing mobility on COVID-19 infection. Thus, these results suggested that solar radiation only weakly mitigated the relationship between human mobility and COVID-19 infection, providing policy implications that mobility should still be restricted on sunny days during the COVID-19 pandemic.

Six air pollutants and cause-specific mortality: a multi-area study in nine counties or districts of Anhui Province, China

Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM_2.5 and NO₂ and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM_2.5, with RR (lag 07): 1.89 (1.45-2.34). PM_2.5 and PM₁₀ had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM₁₀ and PM_2.5 had a considerable impact on the elderly.

Long-Term Exposure to Low-Level NO2 and Mortality among the Elderly Population in the Southeastern United States

BACKGROUND

Mounting evidence has shown that long-term exposure to fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] and ozone (O3) can increase mortality. However, the health effects associated with long-term exposure to nitrogen dioxide (NO2) are less clear, in particular the evidence is scarce for NO2 at low levels that are below the current international guidelines.

METHODS

We constructed a population-based full cohort comprising all Medicare beneficiaries (aged ≥65, N=13,590,387) in the southeastern United States from 2000 to 2016, and we then further defined the below-guideline cohort that included only those who were always exposed to low-level NO2, that is, with annual means below the current World Health Organization guidelines (i.e., ≤21 ppb). We applied previously estimated spatially and temporally resolved NO2 concentrations and assigned annual means to study participants based on their ZIP code of residence. Cox proportional hazards models were used to examine the association between long-term exposure to low-level NO2 and all-cause mortality, adjusting for potential confounders.

RESULTS

About 71.1% of the Medicare beneficiaries in the southeastern United States were always exposed to low-level NO2 over the study period. We observed an association between long-term exposure to low-level NO2 and all-cause mortality, with a hazard ratio (HR)= 1.042 (95% CI: 1.040, 1.045) in single-pollutant models and a HR= 1.047 (95% CI: 1.045, 1.049) in multipollutant models (adjusting for PM2.5 and O3), per 10-ppb increase in annual NO2 concentrations. The penalized spline indicates a linear exposure-response relationship across the entire NO2 exposure range. Medicare enrollees who were White, female, and residing in urban areas were more vulnerable to long-term NO2 exposure.

CONCLUSION

Using a large and representative cohort, we provide epidemiological evidence that long-term exposure to NO2, even below the national and global ambient air quality guidelines, was approximately linearly associated with a higher risk of mortality among older adults, independent of PM2.5 and O3 exposure. Improving air quality by reducing NO2 emissions, therefore, may yield significant health benefits. https://doi.org/10.1289/EHP9044.

Air pollution and cardiovascular disease hospitalization - Are associations modified by greenness, temperature and humidity?

BACKGROUND

Studies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity.

METHODS

We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM2.5, NO2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization.

RESULTS

PM2.5 and NO2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m3) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m3 PM2.5. Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (<40 ppb). Associations of PM2.5 were stronger in areas with higher greenness, lower ozone and Ox, lower summer and winter temperature and lower summer and winter specific humidity.

CONCLUSION

PM2.5 and NO2 were positively associated with CVD, CHD and CBV hospitalization. Associations were more pronounced at low exposure levels. Associations of PM2.5 were stronger with higher greenness, lower ozone and Ox, lower temperature and lower specific humidity.

Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO₂), is related to adverse health effects and mortality.

METHODS

We conducted a systematic review of short-term NO₂ and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias.

RESULTS

We included 87 articles in our quantitative analysis. NO₂ and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO₂ was associated with a 1.58% (95%CI 1.28%-1.88%, I² = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO₂ was associated with a 1.72% (95%CI 1.41%-2.04%, I² = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I² = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification.

CONCLUSIONS

This study provides evidence of an association between short-term exposure to NO₂, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.

Association between particulate matter pollution and the incidence of mumps in 31 provinces from China

Previous studies have found that particulate matter (PM) pollution is a risk factor for respiratory disease by affecting body's immunity and carrying microorganisms. This study aimed to explore the association between PM and the incidence of mumps in 31 provinces from China. Monthly mumps cases, air pollution concentration, and meteorological factors in each province were obtained between January 2014 to December 2017. We used a generalized additive model (GAM) to investigate the associations of PM2.5 and PM10 with monthly mumps cases. We also tested the statistical significance of the differences between effect estimates in the warm season (April to September) and cold season (October to March) to explore potential effect modification. We found that a 10-μg/m3 increase (lag0) in PM2.5, and PM10 was associated with a 2.34% (95% CI: 1.32 to 3.36) and 1.90% (95% CI: 1.19 to 2.62) increase in the monthly counts of mumps cases, respectively. We also observed significant positive associations of PM2.5 and PM10 with mumps cases at lag0-1. These results were robust in our sensitivity analyses. No significant differences were found between the season-specific effects. Our results indicate that there is a positive relationship between PM and the incidence of mumps, which provides important implications for the prevention and control of mumps.

The Impact of the Synergistic Effect of Temperature and Air Pollutants on Chronic Lung Diseases in Subtropical Taiwan

Previous studies have suggested an association between air pollution and lung disease. However, few studies have explored the relationship between chronic lung diseases classified by lung function and environmental parameters. This study aimed to comprehensively investigate the relationship between chronic lung diseases, air pollution, meteorological factors, and anthropometric indices. We conducted a cross-sectional study using the Taiwan Biobank and the Taiwan Air Quality Monitoring Database. A total of 2889 participants were included. We found a V/U-shaped relationship between temperature and air pollutants, with significant effects at both high and low temperatures. In addition, at lower temperatures (<24.6 °C), air pollutants including carbon monoxide (CO) (adjusted OR (aOR):1.78/Log 1 ppb, 95% CI 0.98–3.25; aOR:5.35/Log 1 ppb, 95% CI 2.88–9.94), nitrogen monoxide (NO) (aOR:1.05/ppm, 95% CI 1.01–1.09; aOR:1.11/ppm, 95% CI 1.07–1.15), nitrogen oxides (NO_x) (aOR:1.02/ppm, 95% CI 1.00–1.05; aOR:1.06/ppm, 95% CI 1.04–1.08), and sulfur dioxide (SO₂) (aOR:1.29/ppm, 95% CI 1.01–1.65; aOR:1.77/ppm, 95% CI 1.36–2.30) were associated with restrictive and mixed lung diseases, respectively. Exposure to CO, NO, NO₂, NO_x and SO₂ significantly affected obstructive and mixed lung disease in southern Taiwan. In conclusion, temperature and air pollution should be considered together when evaluating the impact on chronic lung diseases.

Do air pollutants as well as meteorological factors impact Corona Virus Disease 2019 (COVID-19)? Evidence from China based on the geographical perspective

The COVID-19 is still a huge challenge that seriously threatens public health globally. Previous studies focused on the influence of air pollutants and probable meteorological parameters on confirmed COVID-19 infections via epidemiological methods, whereas the findings of relations between possible variables and COVID-19 incidences using geographical perspective were scarce. In the present study, data concerning confirmed COVID-19 cases and possible affecting factors were collected for 325 cities across China up to May 27, 2020. The geographically weighted regression (GWR) model was introduced to explore the impact of probable determinants on confirmed COVID-19 incidences. Some results were obtained. AQI, PM2.5, and PM10 demonstrated significantly positive impacts on COVID-19 during the most study period with the majority lag group (P< 0.05). Nevertheless, the relation of temperature with COVID-19 was significantly negative (P< 0.05). Especially, CO exhibited a negative effect on COVID-19 in most study period with the majority lag group. The impacts of each possible determinant on COVID-19 represented significantly spatial heterogeneity. The obvious influence of the majority of possible factors on COVID-19 was mainly detected during the after lockdown period with the lag 21 group. Although the COVID-19 spreading has been effectively controlled by tough measures taken by the Chinese government, the study findings remind us to address the air pollution issues persistently for protecting human health.

Climatic modification effects on the association between PM1 and lung cancer incidence in China

Background

Nationwide studies that examine climatic modification effects on the association between air pollution and health outcome are limited in developing countries. Moreover, few studies focus on PM1 pollution despite its greater health effect.

Objectives

This study aims to determine the modification effects of climatic factors on the associations between PM1 and the incidence rates of lung cancer for males and females in China.

Methods

We conducted a nationwide analysis in 345 Chinese counties (districts) from 2014 to 2015. Mean air temperature and relative humidity over the study period were used as the proxies of climatic conditions. In terms of the multivariable linear regression model, we examined climatic modification effects in the stratified and combined datasets according to the three-category and binary divisions of climatic factors. Moreover, we performed three sensitivity analyses to test the robustness of climatic modification effects.

Results

We found a stronger association between PM1 and the incidence rate of male lung cancer in counties with high levels of air temperature or relative humidity. If there is a 10 μg/m³ shift in PM1, then the change in male incidence rate relative to its mean was higher by 4.39% (95% CI: 2.19, 6.58%) and 8.37% (95% CI: 5.18, 11.56%) in the middle and high temperature groups than in the low temperature group, respectively. The findings of climatic modification effects were robust in the three sensitivity analyses. No significant modification effect was discovered for female incidence rate.

Conclusions

Male residents in high temperature or humidity counties suffer from a larger effect of PM1 on the incidence rate of lung cancer in China. Future research on air pollution-related health impact assessment should consider the differential air pollution effects across different climatic conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10912-8.

Impact of environmental temperature and relative humidity on spread of COVID-19 infection in India: a cross-sectional time-series analysis

Purpose: Coronavirus disease 2019 (COVID-19) has become a serious public health problem worldwide. This study sought to examine the associations of daily average temperature (AT) and relative humidity (ARH) with the percent increase in COVID-19 cases. Methods: Daily confirmed cases and meteorological factors in 38 districts of India were collected between 1^st April 2020 to 30^th April 2020. Taking a 5-day time lag of average values of the variables and multiple days-samples, we ran multiple models and performed appropriate hypothesis tests to decide the single preferred model for each sample data. Suitable fixed effects (FE) and random effects (RE) models with cluster-robust standard errors were applied to quantify the district-specific associations of meteorological and other variables with COVID-19 cases. Results: All FE models revealed that every one-degree rise in AT led to a decrease in 3.909 points (on average) in percent increase in COVID-19 cases. All RE models showed that with one unit increase in the malaria annual parasite index, there was a significant increase in 10.835 points (on average) in percent increase in COVID-19 cases. In both FE and RE models, ARH was found to be negatively associated with a percent increase in COVID-19 cases, although in half of these models the association was statistically insignificant. Conclusion: Our results indicate that mean temperature, mean relative humidity, and malaria endemicity might have an essential role in the stability and transmissibility of the 2019 novel coronavirus.

No impact of weather conditions on the outcome of intensive care unit patients

Global warming leads to increased exposure of humankind to meteorological variation, including short-term weather changes. Weather conditions involve changes in temperature, heat and cold, in air pressure and in air humidity. Every single condition influences the incidence and mortality of different diseases such as myocardial infarction and stroke. This study investigated the impact of weather conditions on short- and long-term mortality of 4321 critically ill patients (66 ± 14 years, 2638 men) admitted to an intensive care unit (ICU) over a period of 5 years. Meteorological information (air temperature, air pressure and humidity) for the same period was retrieved. The influence of absolute weather parameters, different seasons, sudden weather changes including "warm" and "cold" spells on ICU and long-term mortality was analyzed. After correction for Simplified Acute Physiology Score (SAPS-2), no impact of meteorological conditions on mortality was found. Different seasons, sudden weather changes, "warm spells" or "cold spells" did not affect the outcome of critically ill patients.

Child buccal telomere length and mitochondrial DNA content as biomolecular markers of ageing in association with air pollution

BACKGROUND

Pro-inflammatory conditions such as air pollution might induce biological ageing. However, the available evidence on such an impact in children is still very scarce. We studied in primary schoolchildren the association of ambient residential air pollution exposure with telomere length (TL) and mitochondrial DNA content (mtDNAc), two important targets of the core axis of ageing.

METHODS

Between 2012 and 2014, buccal TL and mtDNAc were repeatedly assessed using qPCR in 197 Belgian primary schoolchildren (mean age 10.3 years) as part of the COGNAC study. At the child's residence, recent (week), sub-chronic (month) and chronic (year) exposure to nitrogen dioxide (NO₂), particulate matter ≤ 2.5 µm (PM_2.5) and black carbon (BC) were estimated using a high resolution spatiotemporal model. A mixed-effects model with school and subject as random effect was used while adjusting for a priori chosen covariates.

RESULTS

An interquartile range (IQR) increment (1.9 µg/m³) in chronic PM_2.5 exposure was associated with a 8.9% (95% CI: -15.4 to -1.9%) shorter TL. In contrast to PM_2.5, chronic exposure to BC and NO₂ was not associated with TL but recent exposure to BC and NO₂ showed significant inverse associations with TL: an IQR increment in recent exposure to BC (0.9 µg/m³) and NO₂ (10.2 µg/m³) was associated with a 6.2% (95% CI: -10.6 to -1.6%) and 6.4% (95% CI: -11.8 to -0.7%) shorter TL, respectively. Finally, an IQR increment in chronic PM_2.5 exposure was associated with a 12.7% (95% CI: -21.7 to -2.6%) lower mtDNAc. However, no significant associations were seen for NO₂ and BC or for other exposure windows.

CONCLUSION

Chronic exposure to PM_2.5 below the EU threshold was associated with child's shorter buccal TL and lower mtDNAc, while traffic-related pollutants (BC and NO₂) showed recent effects on telomere biology. Our data add to the literature on air pollution-induced effects of TL and mtDNAc, two measures part of the core axis of cellular ageing, from early life onwards.

Directional Water Transfer Janus Nanofibrous Porous Membranes for Particulate Matter Filtration and Volatile Organic Compound Adsorption

In order to reduce the possible harm caused by air pollution, excellent personal protective materials are attracting more and more attention. Therefore, the research of multifunctional materials that can filter particulate matter (PM) and volatile organic compounds (VOCs) simultaneously is of great significance. In addition, in cold weather, water vapor in the exhaled gas condenses into small droplets inside the respirator causing uncomfortable feeling of dampness. Herein, we prepared several types of cyclodextrin-containing Janus nanofibrous porous membranes by electrospinning, which can efficiently filter PM of different sizes in the air, effectively adsorb VOCs, and orientate moisture from exhaled gas to the outside of the membranes to provide a dry and comfortable environment. These advantageous features, combined with the cheap price and easy availability of component materials and low respiratory resistance, highlight the great potential of these Janus nanofibrous porous membranes in the development of personal wearable air purifiers.

Deep learning for predicting the occurrence of cardiopulmonary diseases in Nanjing, China

The efficiency of disease prevention and medical care service necessitated the prediction of incidence. However, predictive accuracy and power were largely impeded in a complex system including multiple environmental stressors and health outcome of which the occurrence might be episodic and irregular in time. In this study, we established four different deep learning (DL) models to capture inherent long-term dependencies in sequences and potential complex relationships among constituents by initiating with the original input into a representation at a higher abstract level. We collected 504,555 and 786,324 hospital outpatient visits of grouped categories of respiratory (RESD) and circulatory system disease (CCD), respectively, in Nanjing from 2013 through 2018. The matched observations in time-series that might pose risk to cardiopulmonary health involved conventional air pollutants concentrations and metrological conditions. The results showed that a well-trained network architecture built upon long short-term memory block and a working day enhancer achieved optimal performance by three quantitative statistics, i.e., 0.879 and 0.902 of Nash-Sutcliffe efficiency, 0.921% and 0.667% of percent bias, and 0.347 and 0.312 of root mean square error-standard deviation ratio for RESD and CCD hospital visits, respectively. We observed the non-linear association of nitrogen dioxide and ambient air temperature with CCD hospital visits. Furthermore, these two environmental stressors were identified as the most sensitive predictive variables, and exerted synergetic effect for two health outcomes, particular in winter season. Our study indicated that high-quality surveillance data of atmospheric environments could provide novel opportunity for anticipating temporal trend of cardiopulmonary health outcomes based on DL model.

The mediating effect of air quality on the association between human mobility and COVID-19 infection in China

BACKGROUND

Previous studies have found that human mobility restrictions could not only prevent the spread of COVID-19, but also improve the air quality because of the reduction of industrial production, transportation and traffic. It is noteworthy that air quality is also closely related to the risk of COVID-19 infection. Therefore, we aimed to assess the mediating role of air quality on the association between human mobility and the infection caused by this novel coronavirus.

METHODS

We collected daily confirmed cases, human mobility data, air quality data and meteorological variables in 120 cities from China between January 23, 2020 and February 29, 2020. We applied the generalized additive model to examine the association of human mobility index with COVID-19 confirmed cases, and to assess the mediating effects of air quality index and each pollutant.

RESULTS

We observed a significant positive relationship between human mobility index and the daily counts of COVID-19 confirmed cases. A unit increase in human mobility index (lag0-14) was associated with a 6.45% increase in daily COVID-19 confirmed cases, and air quality index significantly mediated 19.47% of this association. We also observed a positive relationship between human mobility index and air quality index. In the pollutant level analyses, we found significant mediating effects of PM2.5, PM10, and NO2.

CONCLUSIONS

Our study suggests that limiting human movements could reduce COVID-19 cases by improving air quality besides decreasing social contact.

The Interactive Effects between Particulate Matter and Heat Waves on Circulatory Mortality in Fuzhou, China

The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32–16.72) and 3.84% (95% CI: 0.28–7.54) per 10 μg/m³ increase of PM_2.5 and PM₁₀, respectively, compared to non-heat waves. Compared with low-level PM_2.5 concentration on non-heat waves layer, the high level of PM_2.5 concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37–106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.

Spatio-temporal analysis of meteorological factors in abating the spread of COVID-19 in Africa

In Asia, Europe and South America, the role of atmospheric condition in aiding or abating the growth curve of COVID-19 has been analysed. However, no study to date has examined such climatic extensions for the growth or otherwise of the novel coronavirus in Africa. Africa, with a mostly relatively warmer temperature differs from other regions of the world and in addition, has recorded far fewer cases compared to Asian, Europeans and the Americans (North and South). It then becomes imperative to examine the influence of meteorological indices in the growth or otherwise of coronavirus diseases in Africa to establish whether findings on the climatic conditions-COVID-19 growth are regionally specific. In this study, we examined the influence of meteorological factors for aiding or abating the spread of the aerosolised pathogen of COVID-19 in Africa. We rely on the generalised additive model (GAM) and found wind speed to positively relate to COVID-19 growth while mean temperature and relative humidity to inversely relates to COVID-19 growth curve in Africa. We accounted for potential cofounders in the core GAM model and discuss policy implications.

Nitrogen Dioxide Inhalation Exposures Induce Cardiac Mitochondrial Reactive Oxygen Species Production, Impair Mitochondrial Function and Promote Coronary Endothelial Dysfunction

Traffic air pollution is a major health problem and is recognized as an important risk factor for cardiovascular (CV) diseases. In a previous experimental study, we showed that diesel exhaust (DE) exposures induced cardiac mitochondrial and CV dysfunctions associated with the gaseous phase. Here, we hypothesized that NO₂ exposures to levels close to those found in DE induce a mitochondrial reactive oxygen species (ROS) production, which contribute to an endothelial dysfunction, an early indicator for numerous CV diseases. For this, we studied the effects of NO₂ on ROS production and its impacts on the mitochondrial, coronary endothelial and cardiac functions, after acute (one single exposure) and repeated (three h/day, five days/week for three weeks) exposures in Wistar rats. Acute NO₂ exposure induced an early but reversible mitochondrial ROS production. This event was isolated since neither mitochondrial function nor endothelial function were impaired, whereas cardiac function assessment showed a reversible left ventricular dysfunction. Conversely, after three weeks of exposure this alteration was accompanied by a cardiac mitochondrial dysfunction highlighted by an alteration of adenosine triphosphate (ATP) synthesis and oxidative phosphorylation and an increase in mitochondrial ROS production. Moreover, repeated NO₂ exposures promoted endothelial dysfunction of the coronary arteries, as shown by reduced acetylcholine-induced vasodilatation, which was due, at least partially, to a superoxide-dependent decrease of nitric oxide (NO) bioavailability. This study shows that NO₂ exposures impair cardiac mitochondrial function, which, in conjunction with coronary endothelial dysfunction, contributes to cardiac dysfunction. Together, these results clearly identify NO₂ as a probable risk factor in ischemic heart diseases.

Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China

The novel coronavirus pneumonia, namely COVID-19, has become a global public health problem. Previous studies have found that air pollution is a risk factor for respiratory infection by carrying microorganisms and affecting body's immunity. This study aimed to explore the relationship between ambient air pollutants and the infection caused by the novel coronavirus. Daily confirmed cases, air pollution concentration and meteorological variables in 120 cities were obtained from January 23, 2020 to February 29, 2020 in China. We applied a generalized additive model to investigate the associations of six air pollutants (PM2.5, PM10, SO2, CO, NO2 and O3) with COVID-19 confirmed cases. We observed significantly positive associations of PM2.5, PM10, NO2 and O3 in the last two weeks with newly COVID-19 confirmed cases. A 10-μg/m3 increase (lag0-14) in PM2.5, PM10, NO2, and O3 was associated with a 2.24% (95% CI: 1.02 to 3.46), 1.76% (95% CI: 0.89 to 2.63), 6.94% (95% CI: 2.38 to 11.51), and 4.76% (95% CI: 1.99 to 7.52) increase in the daily counts of confirmed cases, respectively. However, a 10-μg/m3 increase (lag0-14) in SO2 was associated with a 7.79% decrease (95% CI: -14.57 to -1.01) in COVID-19 confirmed cases. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which could partially explain the effect of national lockdown and provide implications for the control and prevention of this novel disease.

Association between ambient temperature and COVID-19 infection in 122 cities from China

BACKGROUND

Coronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus.

METHODS

Daily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail.

RESULTS

The exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in the range of <3 °C and became flat above 3 °C. When mean temperature (lag0-14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209-6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses.

CONCLUSIONS

Our results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.

Association between ambient temperature and COVID-19 infection in 122 cities from China

BACKGROUND

Coronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus.

METHODS

Daily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail.

RESULTS

The exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in the range of <3 °C and became flat above 3 °C. When mean temperature (lag0-14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209-6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses.

CONCLUSIONS

Our results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China

BACKGROUND

A great number of studies have confirmed that children are a particularly vulnerable population to air pollution.

METHODS

In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season.

RESULTS

We found that PM_2.5, NO₂ and SO₂ were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO₂ and SO₂, a 10 μg/m³ increase in NO₂ and SO₂ was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM₁₀ were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO₂ and SO₂ were positively related to the pneumonia outpatient visits. PM_2.5 and SO₂ were significantly related to the outpatient visits of other respiratory diseases, while only NO₂ was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM₁₀, PM_2.5 and SO₂.

CONCLUSIONS

Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.