Attributable risk and economic cost of hospital admissions for depression due to short-exposure to ambient air pollution: A multi-city time-stratified case-crossover study

Synergistic effects of air pollution and cold spells on ischemic heart disease hospitalization risk: a case-crossover study in Xinxiang, China

Air pollution and extreme weather events pose a serious threat to human health. We collected atmospheric pollution, meteorological factors, and hospitalisation data for ischemic heart disease (IHD) in Xinxiang, Henan Province, from 2016 to 2021. Using a time-stratified case-crossover design and conditional Poisson regression analysis, we explored the association between atmospheric pollutants (particulate matter with diameter ≤ 2.5 μm [PM2.5], particulate matter with diameter ≤ 10 μm [PM10], nitrogen dioxide [NO2], carbon monoxide [CO]), meteorological factors, and IHD hospitalizations. We evaluated synergistic effects using relative excess risk due to interaction (RERI), attribute proportion (AP), and synergy index (S). PM2.5, PM10, NO2, CO, relative humidity, and cold spells were significantly associated with IHD hospitalization risk. Significant interaction effects (RERI > 0, AP > 0, S > 1) were found in PM2.5-PM10-NO2 combinations. The attributable fractions were 3.4-7.3% for pollutant combinations and 8-17% during cold spells with different PM2.5 levels. Males and individuals aged ≥ 65 were more susceptible to pollutants, while females and elderly individuals showed higher sensitivity to cold spells. These findings provide evidence for optimizing extreme weather warning systems and reducing air pollution exposure to protect public health.

The impact of fine particulate matter on depression: Evidence from social media in China

Depression is a significant public health issue in China that imposes a heavy economic burden on society and families. Using a dataset of 8.54 million Weibo posts from 284 prefecture-level cities across China between 2016 and 2019, we calculate the depression tendency index for residents in each city. Using the weighting of pollutants in nearby cities as an instrumental variable, we apply the two-stage least squares method to estimate the impact of PM2.5 on depression. The findings reveal that (1) air pollution markedly influences residents' susceptibility to depression, and every 1 μg/m3 increase in the PM2.5 concentration results in a 0.0559% increase in the depression tendency value. (2) The influence of air pollution on residents' depression exhibits a distinct weekly pattern, with individuals in heating cities, on weekdays, and in lower-income brackets being more impacted. (3) Our analysis of healthcare expenditures affirms that China's environmental governance policies have yielded significant economic advantages. As mitigation strategies, we propose the adoption of air pollution evasion measures, persistent refinement and enforcement of air pollution regulatory policies to reduce environmental pollution-related damage, paying attention to groups at risk of depression and fostering a healthy society.

Short-term attributable risk and economic burden of hospital admissions for anxiety disorders due to air pollution: a multicity time-stratified case-crossover study

BACKGROUND

Anxiety disorders are a leading cause of severe quality of life impairment and are among the most common mental disorders globally. However, few studies have investigated the association between exposure to high levels of air pollution and an increased risk of developing anxiety disorders. This study aimed to investigate the relationship between air pollutants and hospitalisation for anxiety disorders and the associated economic burden of these hospitalisations in Sichuan, China.

METHODS

We collected 7,282 records of anxiety disorder hospitalisation from medical institutions across nine cities between January 1, 2017, and December 31, 2018. Concurrent meteorological and air pollution data, including temperature, humidity, PM2.5, PM10, SO2, and CO, were obtained from 183 monitoring stations in Sichuan Province. After controlling for long-term trends, day of the week, and meteorological factors, we employed a time-stratified case-crossover design based on conditional logistic regression to assess the association between concentrations of the four pollutants (PM2.5, PM10, SO2, and CO) and hospital admissions for anxiety disorders, with stratified analysis by age, sex, and season. The cost of hospitalisation was evaluated using the cost-of-illness method.

RESULTS

The finding indicated a positive correlation between short-term exposure to air pollutants and hospitalization rates of anxiety disorders. The effect of each 10 µg/m3 increase in airborne particulate matter (PM) and SO2 on hospital admissions for people with anxiety disorders peaked with a lag of 5 days, and each 1 mg/m3 increase in CO had the greatest effect on the 0-7 day moving average lag, with OR values of PM2.5:1.002 (95% CI: 1.001,1.004), PM10:1.001 (95% CI: 1.000,1.002), SO2:1.034 (95% CI: 1.020,1.047), and CO: 1.614 (95% CI: 1.247, 2.089). Air pollution increases the chances of anxiety disorders during the cold season. Furthermore, the elderly are particularly susceptible to these pollutants, which may contribute to an increased hospitalization rates of anxiety disorders (P < 0.05). The total economic cost of hospitalisation for anxiety disorders due to particulate matter pollution was ¥ 966,319 during the study period.

CONCLUSION

Short-term exposure to PM2.5, PM10, SO2, and CO may increase the risk of hospital admissions for anxiety disorders and impose significant financial burdens.

Mental Health Vulnerabilities and Environmental Justice: A Collaborative Online International Learning Experience

Collaboration and intercultural interaction and engagement are relevant to all aspects of higher education including distance/remote/virtual courses. Collaborative Online International Learning (COIL) experiences connect students in different countries and provide them with meaningful and significant opportunities for global and intercultural exposure. Such an educational environment enhances students' cultural awareness and knowledge, and guides their personal, relational, and professional actions. Accordingly, engagement in COIL experiences can increase students' understanding of and ability to respond to significant global health-care issues both locally and internationally and to recognize their impact on mental health, and can lead to reflection and awareness that will endure beyond students' individual class experiences. One of these urgent issues is mental health vulnerabilities associated with environmental justice issues. This article describes participation in an international collaborative experience between the Universidad San Francisco de Quito, Ecuador, and the College of Nursing at the University of South Alabama, USA.

Ambient temperature and the risk of childhood epilepsy hospitalizations: Potentially neglected risk of temperature extremes and modifying effects of air pollution

PURPOSE

Extreme temperatures and air pollution are increasingly important risk factors for human health in the background of climate change, with limited evidence available for neurological disorders. This study intended to investigate the short-term effects of extreme temperatures on childhood epilepsy and explore the potential modifying effect of air pollution.

METHODS

Daily childhood epilepsy hospitalization, meteorological and air pollution data were collected from 10 cities in Anhui Province of China during 2016-2018. We firstly employed a space-time-stratified case-crossover design and conditional logistic regression model to fit the short-term relationship between temperature and epilepsy. Then, we conducted stratified analyses by the level of air pollution and individual characteristics.

RESULTS

Both extreme heat and extreme cold increased the risk of hospitalization for childhood epilepsy. The effect of extreme heat [97.5th vs. minimum hospitalization temperature (MHT)] on hospitalization was acute and emerged at lag0 [OR: 1.229 (95 %CI: 1.035 to 1.459)], while the effect of extreme cold (2.5th vs. MHT) was delayed and appeared at lag5 [OR: 1.098 (95 %CI: 1.043 to 1.156)]. We also found children aged 6-18 years were more susceptible to extreme cold than children aged 0-5 years. Besides, extreme heat and cold effects differed by the level of air pollutants.

CONCLUSION

This study suggests that extreme temperatures might be the novel but currently neglected risk factor for childhood epilepsy, and air pollution could further amplify the adverse effect of temperature.

Estimation of Attributable Risk and Direct Medical and Non-Medical Costs of Major Mental Disorders Associated With Air Pollution Exposures Among Children and Adolescents in the Republic of Korea, 2011-2019

BACKGROUND

Recent studies have reported the burden of attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and depressive disorder. Also, there is mounting evidence on the effects of environmental factors, such as ambient air pollution, on these disorders among children and adolescents. However, few studies have evaluated the burden of mental disorders attributable to air pollution exposure in children and adolescents.

METHODS

We estimated the risk ratios of major mental disorders (ADHD, ASD, and depressive disorder) associated with air pollutants among children and adolescents using time-series data (2011-2019) obtained from a nationwide air pollution monitoring network and healthcare utilization claims data in the Republic of Korea. Based on the estimated risk ratios, we determined the population attributable fraction (PAF) and calculated the medical costs of major mental disorders attributable to air pollution.

RESULTS

A total of 33,598 patients were diagnosed with major mental disorders during 9 years. The PAFs for all the major mental disorders were estimated at 6.9% (particulate matter < 10 μm [PM10]), 3.7% (PM2.5), and 2.2% (sulfur dioxide [SO2]). The PAF of PM10 was highest for depressive disorder (9.2%), followed by ASD (8.4%) and ADHD (5.2%). The direct medical costs of all major mental disorders attributable to PM10 and SO2 decreased during the study period.

CONCLUSION

This study assessed the burden of major mental disorders attributable to air pollution exposure in children and adolescents. We found that PM10, PM2.5, and SO2 attributed 7%, 4%, and 2% respectively, to the risk of major mental disorders among children and adolescents.

Effects of short- and long-term exposures to multiple air pollutants on depression among the labor force: A nationwide longitudinal study in China

BACKGROUND

Depression prevalence has surged within the labor force population in recent years. While links between air pollutants and depression were explored, there was a notable scarcity of research focusing on the workforce.

METHODS

This nationwide longitudinal study analyzed 27,457 workers aged 15-64. We estimated monthly mean concentrations of fine particulate matter (PM2.5), its primary components, and Ozone (O3) at participants' residences using spatiotemporal models. To assess the relationship between short- (1 to 3 months) and long-term (1 to 2 years) exposure to various air pollutants and depressive levels and occurrences, we employed linear mixed-effects models and mixed-effects logistic regression. We considered potential occupational moderators, such as labor contracts, overtime compensation, and total annual income.

RESULTS

We found significant increases in depression risks within the workforce linked to both short- and long-term air pollution exposure. A 10 μg/m3 rise in 2-year average PM2.5, black carbon (BC), and O3 concentrations correlated with increments in depressive scores of 0.009, 0.173, and 0.010, and a higher likelihood of depression prevalence by 0.5 %, 12.6 %, and 0.7 %. The impacts of air pollutants and depression were more prominent in people without labor contracts, overtime compensation, and lower total incomes.

CONCLUSION

Exposures to air pollutants could increase the risk of depression in the labor force population. The mitigating effects of higher income, benefits, and job security against depression underscore the need for focused mental health interventions.

Exploring the Modifying Role of GDP and Greenness on the Short Effect of Air Pollutants on Respiratory Hospitalization in Beijing

It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p < 0.001), SO2 (p < 0.001), O3 (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.

Modeling the lagged impacts of hourly weather and speed variation factors on the segment crash risk of rural interstate freeways: Applying a space-time-stratified case-crossover design

In the realm of traditional roadway crash studies, cross-sectional modeling methods have been commonly employed to investigate the intricate relationship between the crash risk of roadway segments and variables including roadway geometrics, weather conditions, and speed distribution. However, these methodologies assume that the explanatory variables and target variable are only associated within the same time period. Although this assumption is well-founded for static factors like roadway geometrics, it proves inadequate when dealing with highly time-varying variables related to weather conditions and speed variation. Recent investigations have unveiled that these time-varying variables may exhibit lagged impacts on segment crash risk, necessitating the adoption of more comprehensive time-series modeling methods. This study employs two interpretable statistical methods, namely the distributed lag model (DLM) and the distributed lag nonlinear model (DLNM), to elucidate meaningful and interpretable patterns of the lagged impacts of weather and speed variation factors on segment crash risk. Empirical evidence based on crash data collected from rural interstate freeways in the state of Texas demonstrates coherent and interpretable lagged impact patterns of these variables. This study's results serve as strong support for the existence of lagged impacts on roadway segment-level crash risk, emphasizing the need for considering time-series effects in future crash modeling research. Furthermore, these findings could offer practical implications for the design of real-time crash warning systems and the effective implementation of variable speed limits to enhance road safety.

Short-term effects of air pollutants on hospital admissions for asthma among older adults: a multi-city time series study in Southwest, China

Background

This study aimed to explore the relationship between air pollution and hospital admissions for asthma in older adults, and to further assess the health and economic burden of asthma admissions attributable to air pollution.

Methods

We collected information on asthma cases in people over 65 years of age from nine cities in Sichuan province, as well as air pollution and meteorological data. The relationship between short-term air pollutant exposure and daily asthma hospitalizations was analyzed using the generalized additive model (GAM), and stratified by gender, age, and season. In addition, we assessed the economic burden of hospitalization for air pollution-related asthma in older adults using the cost of disease approach.

Results

The single pollutant model showed that every 1 mg/m3 increase in CO was linked with an increase in daily hospitalizations for older adults with asthma, with relative risk values of 1.327 (95% CI: 1.116-1.577) at lag7. Each 10 μg/m3 increase in NO2, O3, PM10, PM2.5 and SO2, on asthma hospitalization, with relative risk values of 1.044 (95% CI: 1.011-1.078), 1.018 (95% CI: 1.002-1.034), 1.013 (95% CI: 1.004-1.022), 1.015 (95% CI: 1.003-1.028) and 1.13 (95% CI: 1.041-1.227), respectively. Stratified analysis shows that stronger associations between air pollution and asthma HAs among older adult in females, those aged 65-69 years, and in the warm season, although all of the differences between subgroups did not reach statistical significance. During the study period, the number of asthma hospitalizations attributable to PM2.5, PM10, and NO2 pollution was 764, 581 and 95, respectively, which resulted in a total economic cost of 6.222 million CNY, 4.73 million CNY and 0.776 million CNY, respectively.

Conclusion

This study suggests that short-term exposure to air pollutants is positively associated with an increase in numbers of asthma of people over 65 years of age in Sichuan province, and short-term exposure to excessive PM and NO2 brings health and economic burden to individuals and society.

Medical cost of environmental pollution: evidence from the Chinese Social Survey

Environmental pollution impairs residents' health, while the pursuit of health is highly correlated to medical costs. Understanding how environmental pollution affects medical costs is closely linked to the welfare of society. Based on theoretical analysis, this paper uses data from 5112 households of the Chinese Social Survey (CSS) in 2019, constructs a composite indicator to quantify environmental pollution using respondents' evaluations, and empirically investigates the causal effect of environmental pollution on household medical cost and the mechanism. The conclusions are shown as follows. First, environmental pollution can increase household medical costs, and this estimation result still holds after dealing with the endogeneity problem and other robustness tests. Second, there is heterogeneity in the impact of environmental pollution on household medical costs, households in the upper socioeconomic class, with heavy pension burdens or with strong health insurance coverage are more sensitive to environmental pollution and incur relatively higher household medical costs. Third, environmental pollution reduces residents' satisfaction with their spiritual life, which adversely affects their physical and mental health and can increase household medical costs. Residents' satisfaction with their spiritual life is an important mechanism for environmental pollution to affect household health care expenditures. Therefore, governments should enhance the enforcement of environmental protection and governance, strengthen the awareness of green issues and health education, and increase the supply of facilities for leisure and sports, thus reducing medical costs due to environmental pollution and easing the medical burden of residents.

Association between long working hours and mental health among nurses in China under COVID-19 pandemic: based on a large cross-sectional study

OBJECTIVE

Nurses were more likely to experience mental disorders due to long working hours and irregular schedules. However, studies addressing this issue are scarce; therefore, we aimed to investigate the association between long working hours and mental health in Chinese nurses during the coronavirus disease pandemic.

METHODS

A cross-sectional study was conducted with 2,811 nurses at a tertiary hospital in China from March to April 2022. We collected data on demographic, psychological characteristics, dietary habits, life, and work-related factors using a self-reported questionnaire and measured mental health using Patient Health Questionnaire-9 and General Anxiety Disorder-7. Binary logistic regression to determine adjusted odds ratios and 95% confidence intervals.

RESULTS

The effective response rates were 81.48%, 7.80% (219), and 6.70% (189) of the respondents who reported depression and anxiety, respectively. We categorized the weekly working hours by quartiles. Compared with the lowest quartile, the odds ratios and 95% confidence intervals across the quartiles for depression after adjustment were 0.98 (0.69, 1.40), 10.58 (2.78, 40.32), and 1.79 (0.81, 3.97) respectively, the P for trend was 0.002. The odds ratios across the quartiles for anxiety after adjustment were 0.87 (0.59, 1.30), 8.69 (2.13, 35.46), and 2.67 (1.26, 5.62), respectively, and the P for trend was 0.008.

CONCLUSIONS

This study demonstrated that extended working hours increased the risk of mental disorders among nurses during the coronavirus disease pandemic, particularly in those who worked more than 60 h per week. These findings enrich the literature on mental disorders and demonstrate a critical need for additional studies investigating intervention strategies.

The Relationship between Ambient Fine Particulate Matter (PM2.5) Pollution and Depression: An Analysis of Data from 185 Countries

Several studies have identified a relationship between air pollution and depression, particularly in relation to fine particulate matter (PM2.5) exposure. However, the strength of this association appears to be moderated by variables such as age, gender, genetic vulnerability, physical activity, and climatic conditions, and has not been assessed at a cross-national level to date. Moreover, certain studies in this field have yielded negative results, and there are discrepancies between the results obtained in high-income countries and those from low- and middle-income countries. The current study examines cross-sectional and longitudinal associations between the incidence of depression in each country, based on Global Burden of Disease Study data, and the average national level of PM2.5 based on the World Health Organization’s database, over the past decade (2010–2019). The observed associations were adjusted for age, gender, level of physical activity, income, education, population density, climate, and type of depression. It was observed that while PM2.5 levels showed significant cross-sectional associations with the incidence of depression, longitudinal analyses were not suggestive of a direct causal relationship. These findings are discussed in the light of recent contradictory results in this field, and the need to consider the intermediate roles of a number of individual and environmental factors.

Population Aging Driven Slowdown in the Reduction of Economic Cost-Attributed to PM2.5 Pollution after 2013 in China

Since seniors are more susceptible to ambient fine particulate matter (PM2.5), the high economic cost to protect the aged population from PM2.5 exposure is expected. Significant efforts have been made in China to mitigate PM2.5 since 2013 under the Air Pollution Prevention and Control Action (APPCA) Plan, which remarkably reduced PM2.5 contamination and its associated economic and health burdens. However, to what extent population aging could influence the economic benefits from the APPCA Plan is unclear. Here, we estimate five driving factors contributing to the economic cost of mortality attributable to PM2.5 pollution. The results show that the economic cost attributed to PM2.5 pollution increased from 1980 to 2013 and decreased from 2013 to 2019 in China, benefiting from the APPCA Plan. Since 2013, population aging becomes the most significant positive driver that almost offsets declining economic cost from significantly declining PM2.5. Rapid aging has become an enormous burden to PM2.5-associated health and economic loss. Our findings suggest that we should further improve air quality and enhance health care for the elderly population.