Estimation of PM2·5-associated disease burden in China in 2020 and 2030 using population and air quality scenarios: a modelling study

Exposure to air pollution and scarlet fever resurgence in China: a six-year surveillance study

Scarlet fever has resurged in China starting in 2011, and the environment is one of the potential reasons. Nationwide data on 655,039 scarlet fever cases and six air pollutants were retrieved. Exposure risks were evaluated by multivariate distributed lag nonlinear models and a meta-regression model. We show that the average incidence in 2011-2018 was twice that in 2004-2010 [RR = 2.30 (4.40 vs. 1.91), 95% CI: 2.29-2.31; p < 0.001] and generally lower in the summer and winter holiday (p = 0.005). A low to moderate correlation was seen between scarlet fever and monthly NO₂ (r = 0.21) and O₃ (r = 0.11). A 10 μg/m³ increase of NO₂ and O₃ was significantly associated with scarlet fever, with a cumulative RR of 1.06 (95% CI: 1.02-1.10) and 1.04 (95% CI: 1.01-1.07), respectively, at a lag of 0 to 15 months. In conclusion, long-term exposure to ambient NO₂ and O₃ may be associated with an increased risk of scarlet fever incidence, but direct causality is not established.

Substantial changes in PM2.5 pollution and corresponding premature deaths across China during 2015-2019: A model prospective

Long-term exposure to the ambient fine particulate matter (PM_2.5) is the major public health risk factor in China. Several past studies have assessed premature mortalities associated with PM_2.5 in China at varying levels of temporal and spatial scales using different methodological approaches. However, recently developed global exposure mortality model [GEMM NCD + LRI and GEMM 5-COD] provides a much more sophisticated methodology in capturing mortality due to PM_2.5-exposure than the commonly accepted integrated exposure-response (IER) model, which this study applied to China. This study provides a comparative assessment of the excess long-term PM_2.5-attributed nonaccidental deaths as well as cause-specific deaths for 349 cities in mainland China during five years (from 2015 to 2019) and compares the results with the spatial resolution scale of 0.1° × 0.1° across overall China. The results demonstrate that the national annual average PM_2.5 concentration declined from 51.9 ± 18.2 μg/m³ in 2015 to 39.0 ± 13.2 μg/m³ in 2019, and the overall annual negative trend was around -3.1 ± 2.2 μg/m³/year [-5.6 ± 3.4%/year] across China. Consequently, the number of PM_2.5-related deaths decreased by 383 thousand [95% CI: 331-429] to 1755 thousand [95% Confidence Interval: 1470-2025; GEMM NCD + LRI]; 315 thousand [95% CI: 227-370] to 1380 thousand [95% CI: 948-1740; GEMM 5-COD] and 125 thousand [95% CI: 64-140] to 876 thousand [95% CI: 394-1262; IER] in 2019, derived from the pre-established models (GEMM and IER). The estimate PM_2.5-attributed death with a spatial resolution of 0.1° × 0.1° was 2419 thousand [95% CI: 2041-2771; GEMM NCD + LRI], 1918 thousand [95% CI: 1333-2377; GEMM 5-COD] and 1162 thousand [95% CI: 534-1611; IER] in 2015, which is about 11-16% higher value than the city-level health risk assessment study. The estimated deaths by GEMM NCD + LRI and GEMM 5-COD were 104% and 61% higher than the estimated by IER, highlighting that total premature mortalities associated with PM_2.5 were substantially left behind based on the pre-existing model. The "other noncommunicable diseases" mortality, which IER method doesn't account for, was 375 thousand in 2019, 68 thousand less than in 2015. Such significant mortality was previously overlooked in estimation methods, which should now be considered for the air pollution-related policy development in China. The high number of premature deaths in central and northern parts of China, calls for the need for the Government to quickly impose even more stringent and effective pollution control measures.

Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100

In response to a growing demand for subnational and spatially explicit data on China’s future population, this study estimates China’s provincial population from 2010 to 2100 by age (0–100+), sex (male and female) and educational levels (illiterate, primary school, junior-high school, senior-high school, college, bachelor’s, and master’s and above) under different shared socioeconomic pathways (SSPs). The provincial projection takes into account fertility promoting policies and population ceiling restrictions of megacities that have been implemented in China in recent years to reduce systematic biases in current studies. The predicted provincial population is allocated to spatially explicit population grids for each year at 30 arc-seconds resolution based on representative concentration pathway (RCP) urban grids and historical population grids. The provincial projection data were validated using population data in 2017 from China’s Provincial Statistical Yearbook, and the accuracy of the population grids in 2015 was evaluated. These data have numerous potential uses and can serve as inputs in climate policy research with requirements for precise administrative or spatial population data in China.

Measurement(s)	population
Technology Type(s)	computational modeling technique
Factor Type(s)	age • sex • education level • Shared Socioeconomic Pathway • year • province
Sample Characteristic - Location	China

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11898405

Ambient air pollution is associated with airway inflammation in older women: a nested cross-sectional analysis

BACKGROUND

Air pollution is a risk factor for chronic obstructive pulmonary disease (COPD). Fraction of exhaled nitric oxide (FeNO) could be a useful biomarker for health effects of air pollutants. However, there were limited data from older populations with higher prevalence of COPD and other inflammatory conditions.

METHODS

We obtained data from the German Study on the influence of Air pollution on Lung function, Inflammation and Ageing. Spirometry and FeNO were measured by standard techniques. Air pollutant exposures were estimated following the European Study of Cohorts for Air Pollution Effects protocols, and ozone (O3) measured at the closest ground level monitoring station. Multiple linear regression models were fitted to FeNO with each pollutant separately and adjusted for potential confounders.

RESULTS

In 236 women (mean age 74.6 years), geometric mean FeNO was 15.2ppb. Almost a third (n=71, 30.1%) of the women had some chronic inflammatory respiratory condition. A higher FeNO concentration was associated with exposures to fine particles (PM2.5), PM2.5absorbance and respirable particles (PM10). There were no significant associations with PMcoarse, NO2, NOx, O3 or length of major roads within a 1 km buffer. Restricting the analysis to participants with a chronic inflammatory respiratory condition, with or without impaired lung function produced similar findings. Adjusting for diabetes did not materially alter the findings. There were no significant interactions between individual pollutants and asthma or current smoking.

CONCLUSIONS

This study adds to the evidence to reduce ambient PM2.5 concentrations as low as possible to protect the health of the general population.

Short-term effects of ambient PM1 and PM2.5 air pollution on hospital admission for respiratory diseases: Case-crossover evidence from Shenzhen, China

BACKGROUND

Ambient PM₁ (particulate matter with aerodynamic diameter ≤1 μm) is an important contribution of PM_2.5 mass. However, little is known worldwide regarding the PM₁-associated health effects due to a wide lack of ground-based PM₁ measurements from air monitoring stations.

METHODS

We collected daily records of hospital admission for respiratory diseases and station-based measurements of air pollution and weather conditions in Shenzhen, China, 2015-2016. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate hospitalization risks associated with short-term exposures to PM₁ and PM_2.5.

RESULTS

PM₁ and PM_2.5 showed significant adverse effects on respiratory disease hospitalizations, while no evident associations with PM_1-2.5 were identified. Admission risks for total respiratory diseases were 1.09 (95% confidence interval: 1.04 to 1.14) and 1.06 (1.02 to 1.10), corresponding to per 10 μg/m³ rise in exposure to PM₁ and PM_2.5 at lag 0-2 days, respectively. Both PM₁ and PM_2.5 were strongly associated with increased admission for pneumonia and chronic obstructive pulmonary diseases, but exhibited no effects on asthma and upper respiratory tract infection. Largely comparable risk estimates were observed between male and female patients. Groups aged 0-14 years and 45-74 years were significantly affected by PM₁- and PM_2.5-associated risks. PM-hospitalization associations exhibited a clear seasonal pattern, with significantly larger risks in cold season than those in warm season among some subgroups.

CONCLUSIONS

Our study suggested that PM₁ rather than PM_1-2.5 contributed to PM_2.5-induced risks of hospitalization for respiratory diseases and effects of PM₁ and PM_2.5 mainly occurred in cold season.

The lag effect of water pollution on the mortality rate for esophageal cancer in a rapidly industrialized region in China

The Huai River basin (located in eastern China) has a population of 180 million and has the highest risk of esophageal cancer (EC) mortality in China. Some studies found that contaminants in drinking water are a major risk factor for cancers of the digestive system. However, the effect of water pollution in the historical period on the current EC mortality remains unclear. Data were collected on the EC mortality rate in 2004 in the Huai River basin in 11 counties, and data on the surface water quality in the region from 1987 to 2004 were used. The Pearson correlation and the GeoDetector q-statistic were employed to explore the association between water pollution and the EC mortality rate in different lag periods, from linear and nonlinear perspectives, respectively. The study showed apparently spatial heterogeneity of the EC mortality rate in the region. The EC mortality rate downstream is significantly higher than that in other regions; in the midstream, the region north of the mainstream has a lower average mortality rate than that south of the area. Upstream, the region north of the mainstream has a higher mortality rate than that in the southern area. The spatial pattern was formed under the influence of water pollution in the historical period. 1996, 1997, and 1998 have the strongest linear or nonlinear effect on the EC mortality rate in 2004, in which the Pearson correlation coefficient and the q-statistic were the highest, 0.79 and 0.89, respectively. Rapid industrialization in the past 20 years has caused environmental problems and poses related health risks. The study indicated that the current EC mortality rate was mainly caused by water pollution from the previous 8 years. The findings provide knowledge about the lag time for pollution effects on the EC mortality rate, and can contribute to the controlling and preventing esophageal cancer.