The short-term association of ambient fine particulate air pollution with hypertension clinic visits: A multi-community study in Guangzhou, China

Temporal Trends and Relevant Factors of Hypertension in China: A Cross-Sectional Study Based on National Surveys from 2002 to 2019

PURPOSE

This study aimed to investigate the temporal trends in hypertension prevalence in China from 2002 to 2019, focusing on age-specific, sex-specific, and regional differences, as well as identifying key factors associated with hypertension.

MATERIALS AND METHODS

A retrospective analysis was conducted using data from the China Chronic Disease and Risk Factor Surveillance (CCDRFS) program, involving 120,000 adults aged 18 years and older. Prevalence rates were calculated using descriptive statistics, and multivariable logistic regression was performed to identify significant relevant factors, including age, sex, body mass index (BMI), smoking, alcohol consumption, and physical activity.

RESULTS

The prevalence of hypertension in China increased from 18.9% in 2002 to 29.6% in 2019 (P < 0.001). The most substantial increase occurred in individuals aged 18-44 years, where prevalence tripled from 5.3% to 12.8%. Hypertension prevalence was higher in men (34.2%) than in women (25.4%) by 2019. Significant regional variations were observed, with the western regions exhibiting the highest prevalence (32.9%). Logistic regression identified age, BMI, smoking, alcohol consumption, and physical inactivity as significant relevant factors for hypertension.

CONCLUSION

Hypertension prevalence in China has risen substantially over the past two decades, particularly among younger adults. These findings highlight the need for targeted prevention strategies that address modifiable risk factors and accommodate regional disparities. Further research is warranted to explore underlying mechanisms and to develop comprehensive prevention and treatment strategies.

A comparative analysis of three PM2.5 exposure metrics and their impact on respiratory disease hospitalizations in Lanzhou, China

Research on the associations between PM2.5 and total respiratory diseases (RD) in Lanzhou is limited. We investigated the short-term impact of PM2.5 on total RD hospitalizations in Lanzhou (2015-2019) using various exposure metrics. We collected data on hospitalizations, daily air pollutant concentrations, and meteorological factors during the study period. Daily excessive concentration hours (DECH) were calculated according to the World Health Organization's air quality guidelines. A distributional lag nonlinear model (DLNM) based on a generalized additive model (GAM) was used to comparatively analyze the association between three PM2.5 exposure metrics (DECH (DECH PM2.5), daily mean concentration (Mean PM2.5), and hourly peak concentration (Peak PM2.5)) and RD hospitalizations. Subgroup analyses and sensitivity analyses were also performed. We found similar effects on RD hospitalizations using DECH PM2.5 and Mean PM2.5, but relatively weak associations observed using Peak PM2.5. The cumulative lag effect increased daily. Subgroup analyses showed that females and children aged 0-17 years were more susceptible to PM2.5 pollution and that the association was enhanced during the cold season. Our research strengthened the evidence that exposure to ambient PM2.5 increases the risk of RD. This study revalidated the reliability of the new metrics and confirmed that DECH PM2.5 effect estimates for exposure-disease were more accurate than the Mean PM2.5.

Utilizing daily excessive concentration hours to estimate small for gestational age infants attributable to fine particulate matter in Wuhan, China

Limited studies in China have explored the association between gravidae exposure to PM2.5 and small for gestational age infants (SGA), yielding inconsistent results. This study in Wuhan utilized daily excessive concentration hours (DECH) as a novel measure to assess PM2.5's impact on SGA. Data on air pollutants and pregnant women were collected from the Wuhan Municipal Ecology and Environmental Bureau and Wuhan Children's Hospital, respectively. Logistic regression models were employed to evaluate the contribution of PM2.5-DECH and PM2.5-mean to SGA. Significant correlations were observed between PM2.5-mean and SGA during the second trimester [OR = 1.23 (95% CI: 1.14-1.32)] and the entire pregnancy [OR = 1.15 (95% CI: 1.07-1.24)]. Similar correlations were found between PM2.5-DECH and SGA. These findings suggest that increased PM2.5 exposure is associated with a higher risk of SGA, and DECH may be used as a prospective substitute indicator for daily average concentration in similar studies.

Cardiovascular Risk Factors in China

The Annual Report on Cardiovascular Health and Diseases in China (2022) intricate landscape of cardiovascular health in China. This section dissects cardiovascular risk factors in China which including hypertension, dyslipidemia, diabetes mellitus, chronic kidney disease, metabolic syndrome and air pollution. Hypertension prevalence has steadily increased in China, with efforts to control it facing challenges in achieving optimal rates, especially in rural areas. Interventions like salt substitutes and intensive blood pressure control show promise but need improvement. Abnormal lipid levels, indicative of dyslipidemia, have risen significantly, posing a risk for cardiovascular diseases. Despite efforts, many patients struggle to achieve target lipid levels, necessitating improved treatment strategies. Both type 1 and type 2 diabetes mellitus affect millions of adults in China, with long-term complications adding to the disease burden. Early intervention and effective management are crucial to mitigate its impact. Prevalent among older adults, chronic kidney disease is associated with diabetes mellitus, hypertension, and cardiovascular diseases, necessitating comprehensive management approaches. The prevalence of metabolic syndrome, characterized by a cluster of risk factors, has increased in both adults and adolescents, calling for lifestyle modifications and public health interventions. Ambient and household air pollution remain significant environmental risk factors, despite some improvements in air quality. Continued efforts to reduce emissions are essential for mitigating associated health risks. Addressing these risk factors requires a multifaceted approach, including public health initiatives, policy interventions, and individual-level strategies to promote healthy lifestyles and reduce environmental exposures. Surveillance and research efforts are crucial for monitoring trends and developing effective strategies to lessen the burden of cardiovascular diseases in China.

Effects of weather and air pollution on outpatient visits for insect-and-mite-caused dermatitis: an empirical and predictive analysis

BACKGROUND

Dermatitis caused by insects and mites, diagnosed as papular urticaria or scabies, is a common skin disease. However, there is still a lack of studies about the effects of weather and air pollution on outpatient visits for this disease. This study aims to explore the impacts of meteorological and environmental factors on daily visits of dermatitis outpatients.

METHODS

Analyses are conducted on a total of 43,101 outpatient visiting records during the years 2015-2020 from the largest dermatology specialist hospital in Guangzhou, China. Hierarchical cluster models based on Pearson correlation between risk factors are utilized to select regression variables. Linear regression models are fitted to identify the statistically significant associations between the risk factors and daily visits, taking into account the short-term effects of temperatures. Permutation importance is adopted to evaluate the predictive ability of these factors.

RESULTS

Short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. In terms of total outpatients, the one-day lagged temperature not only has a significant impact on daily visits, but also has the highest median value of permutation importance. This conclusion is robust across most subgroups except for subgroups of summer and scabies, wherein the three-day lagged temperature has a negative effect. By contrast, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. Moreover, weekdays, holidays and trends have significant impacts on daily visits, but with weak predictive abilities.

CONCLUSIONS

Our study suggests that short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. Nevertheless, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.

Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review

PURPOSE OF REVIEW

The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs.

RECENT FINDINGS

CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.

Associations between hourly ambient particulate matter air pollution and ambulance emergency calls among 3,022,164 patients: time stratified case-crossover study

BACKGROUND

Associations between short-term exposure to ambient particulate matter (PM) air pollutants and mortality or hospital admissions have been well documented in previous studies. Less is known about the associations of hourly exposure to PM air pollutants with ambulance emergency calls (AECs) for all causes and specific causes by conducting a case-crossover study. In addition, different patterns of AECs may be attributed to different seasons and daytime/nighttime periods.

OBJECTIVE

In this study, we quantified the risk of all-cause and cause-specific AECs associated with hourly PM air pollutants between 1 January 2013 and 31 December 2019 in Shenzhen, China. We also examined whether the observed associations of particulate matter air pollutants with AECs for all causes differed across strata defined by sex, age, season, and time of day.

METHODS

We used ambulance emergency dispatch data and environmental data between 1 January 2013 and 31 December 2019 from the Shenzhen Ambulance Emergency Centre and the National Environmental Monitor Station to conduct a time-stratified case-crossover study design to estimate the associations of air pollutants (i.e., PM2.5, PM10) with all-cause AECs and cause-specific AECs. We generated a well-established distributed lag nonlinear model for nonlinear concentration response and nonlinear lag response functions. We used conditional logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs), adjusted for public holidays, season, time of day, day of the week, hourly temperature, and hourly humidity to examine the association of all-cause and cause-specific AECs with hourly air pollutant concentrations.

RESULTS

A total of 3,022,164 patients were identified during the study period in Shenzhen. Each IQR increase in PM2.5 (24.0 µg/m3) and PM10 (34.0 µg/m3) concentrations in 24 hours was associated with an increased risk of AECs (PM2.5: all-cause, 1.8%, 95% CI, 0.8%-2.4%; PM10: all-cause, 2.0%, 95% CI, 1.1%-2.9%). We observed a stronger association of all-cause AECs with PM2.5 and PM10 in the daytime than in the nighttime and in the elderly group than in the younger group (PM2.5 daytime, 1.7%, 95% CI, 0.5%-3.0%; nighttime, 1.4%, 95% CI, 0.3%-2.6%; PM10 daytime, 2.1%, 95% CI, 0.9%-3.4%; nighttime, 1.7%, 95% CI, 0.6%-2.8%; PM2.5 18-64 years, 1.4%, 95% CI, 0.6%-2.1%; ≥65 years, 1.6%, 95% CI, 0.6%-2.6%; PM10 18-64 years, 1.8%, 95% CI, 0.9%-2.6%; ≥65 years, 2.0%, 95% CI, 1.1%-3.0%).

CONCLUSIONS

The risk of all-cause AECs increased consistently with increasing concentrations of PM air pollutants, showing a nearly linear relationship with no apparent thresholds. Particulate matter air pollution increase was associated with a higher risk of AECs for all causes, cardiovascular, respiratory, and reproductive AECs. The results of this study may be valuable to air pollution attributable to the distribution of emergency resources, and consistent air pollution control.

CLINICALTRIAL

Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing

Air pollution seriously threats to human health. Understanding the health effects of air pollution is of great importance for developing countermeasures. However, little is known about the real-time impacts of air pollution on the human heath in a comprehensive way in developing nations, like China. To fill this research gap, the Chinese urbanites' health were sensed from more than 210.82 million Weibo (Chinese Twitter) data in 2017. The association between air pollution and the health sensing were quantified through generalized additive models, based on which the sensitivities and adaptions to air pollution in 70 China's cities were assessed. The results documented that the Weibo data can well sense urbanites' health in real time. With the different geographical characteristics and socio-economic conditions, the Chinese residents have adaption to air pollution, indicated by the spatial heterogeneity of the sensitivities to air pollution. Cities with good air quality in South China and East China were more sensitive to air pollution, while cities with worse air quality in Northwest China and North China were less sensitive. This research provides a new perspective and methodologies for health sensing and the health effect of air pollution.

Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China

Ambient fine particulate matter (PM_2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM_2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM_2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM_2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49–15.18%), compared with 11.20% (95% CI: 8.34–14.13%) for daily mean and 9.73% (95% CI: 6.97–12.55%) for hourly peak. The associations between the three metrics of PM_2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM_2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM_2.5.

Regional years of life lost, years lived with disability, and disability-adjusted life-years for severe mental disorders in Guangdong Province, China: a real-world longitudinal study

BACKGROUND

To understand the magnitude and spatial-temporal distribution of the regional burden attributable to severe mental disorders is of great essential and high policy relevance. The study aimed to address the burden of severe mental disorders by evaluating the years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) in Guangdong, China.

METHODS

We undertook a longitudinal study based on a multicenter database established by the Health Commission of Guangdong, involving a total of 21 prefectures and four economic regions in the Guangdong province. A total of 520,731 medical records from patients with severe mental disorders were collected for 2010-2020. Data were analyzed via an integrated evaluation framework by synthesizing prevalence estimates, epidemiological adjustment as well as comorbidity assessment to develop internally consistent estimates of DALY. DALY changes during 2010-2020 were decomposed by population growth and aging and further grouped by Socio-demographic Index (SDI). DALYs were projected to 2030 by the weighted median annualized rate of change in 2010-2020.

RESULTS

In 2010-2020, the average DALYs for severe mental disorders reached 798,474 (95% uncertainty interval [UI]: 536,280-1,270,465) person-years (52.2% for males, and 47.8% for females). Severe mental disorders led to a great amount of disease burden, especially in Guangzhou, Shenzhen, and Foshan cities. Schizophrenia and mental retardation with mental disorders were the two leading sources of the burden ascribed to severe mental disorders. Population growth and aging could be accountable for the increasing burden of severe mental disorders. Economic regions with higher SDI carried a greater burden but had lower annualized rates of change in DALYs. The overall burden of severe mental disorders is projected to rise modestly over the next decade.

CONCLUSIONS

The findings urge prioritization of initiatives focused on public mental health, prevention strategies, health resources reallocation, and active involvement of authorities to effectively address the anticipated needs.

Evaluating health outcome metrics and their connections to air pollution and vulnerability in Southern California's Coachella Valley

The ongoing desiccation of California's Salton Sea has led to increasing concerns about air quality and health for its surrounding communities, including the nearby Coachella Valley - a region already experiencing severe air quality and health disparities. Here we explore spatial air pollution and human health disparities in the Coachella Valley with particular attention to disparities arising across population characteristics including both socioeconomic and demographic vulnerabilities. We use two different measures of respiratory and cardiovascular health outcomes at the individual and census tract levels - one measure based on a randomly sampled telephone survey and the other measure based on emergency room visitation data - to investigate the degree to which these health outcomes are connected to air pollution and socioeconomic metrics. We further investigate biases and differences between the health outcome metrics themselves and suggest opportunities to address them in future analyses and survey efforts. We find that more vulnerable communities are associated with higher levels of fine particulates, but lower levels of ozone. While emergency visit rates show a significant positive correlation with both pollutants, no such association is found when using surveyed health outcome data. The ratio of emergency visits versus survey rates shows a positive relationship with socioeconomic and demographic vulnerability, indicating that vulnerable communities are less likely to self-report diagnoses despite higher rates of respiratory or cardiovascular hospitalization. Additionally, survey respondents tend to show less vulnerability relative to their surrounding census-based demographics. These findings suggest the need for greater attention to health issues specifically within disadvantaged communities in the Coachella Valley, building upon and working within existing community networks and local resources, to better address current and projected health needs. Our findings also highlight disparities in air pollution exposure, health outcomes, and population characteristics in the Coachella Valley, providing context for crucial pollution reduction efforts in the face of increasing environmental threats.

Three exposure metrics of size-specific particulate matter associated with acute lower respiratory infection hospitalization in children: A multi-city time-series analysis in China

BACKGROUND

The global burden of acute lower respiratory infection (ALRI) attributable to air pollution has increased in recent years, but the association between ALRI and exposure to size-specific particulate matter has not been investigated using different exposure metrics.

METHODS

We obtained ALRI admission from seven cities from 2014 to 2016 in China. Different sized particles were measured using three metrics (a) daily mean, (b) hourly peak, and (c) daily excessive concentration hours (DECH). Generalized additive models were fitted for each of the seven cities, and the city-specific estimates were then pooled using random-effects meta-analysis models. Stratified analyses were conducted to examine the effect modifications of gender, age, and season. We also estimated the disease burden due to particulate matter exposures.

RESULTS

There were 111,426 ALRI (79,803 pneumonia and 31,622 bronchiolitis) hospital admissions under the age of 15 between 2014 and 2016 in our study. Daily means were associated with the largest ALRI estimates (95% confidence interval [CI]): 2.43% (0.79%, 4.11%) for PM_2.5, 2.25% (0.11%, 4.44%) for PM_c, and 2.64% (0.73%, 4.58%) for PM₁₀. The magnitude of effect sizes were followed by DECH: 1.94% (0.51%, 3.39%) for PM_2.5, 0.88% (-0.14%, 1.92%) for PM_c, 1.86% (0.50%, 2.01%) for PM₁₀; and hourly peak: 0.70% (-0.60%, 2.01%) for PM_2.5, 1.05% (-0.13%, 2.66%) for PM_c, and 1.20% (-0.20%, 2.62%) for PM₁₀ at lag03. We found significantly higher effects in cold seasons than that in warm seasons, while we did not find a significant different between gender and age groups.

CONCLUSIONS

The adverse effects of exposure to particulate matter on ALRI hospitalizations are reconfirmed. DECH was a possible alternative exposure indicator for PM_2.5 assessment, which may affect air quality standards in the future.

Spatial-Temporal Evolution of Health Impact and Economic Loss upon Exposure to PM2.5 in China

Exposure to PM_2.5 can seriously endanger public health. Policies for controlling PM_2.5 need to consider health hazards under different circumstances. Unlike most studies on the concentration, distribution, and influencing factors of PM_2.5, the present study focuses on the impact of PM_2.5 on human health. We analysed the spatial-temporal evolution of health impact and economic loss caused by PM_2.5 exposure using the log-linear exposure-response function and benefit transfer method. The results indicate that the number of people affected by PM_2.5 pollution fluctuated and began to decline after reaching a peak in 2014, benefiting from the Air Pollution Prevention and Control Action Plan. Regarding the total economic loss, the temporal pattern continued to rise until 2014 and then declined, with an annual mean of 86,886.94 million USD, accounting for 1.71% of China’s GDP. For the spatial pattern, the health impact and economic loss show a strong spatial correlation and remarkable polarisation phenomena, with high values in East China, North China, Central China, and South China, but low values in Southwest China, Northwest China, and Northeast China. The spatial-temporal characterisation of PM_2.5 health hazards is visualised and analysed accordingly, which can provide a reference for more comprehensive and effective policy decisions.