Air pollution and diabetes mellitus: Association and validation in a desert area in China.

BACKGROUND: Despite the growing evidence pointing to the detrimental effects of air pollution on diabetes mellitus (DM), the relationship remains poorly explored, especially in desert-adjacent areas characterized by high aridity and pollution. METHODS: We conducted a cross-sectional study with health examination data from over 2.9 million adults in two regions situated in the southern part of the Taklamakan Desert, China. We assessed three-year average concentrations (2018-2020) of particulate matter (PM1, PM2.5, and PM10), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) through a space-time extra-trees model. After adjusting for various covariates, we employed generalized linear mixed models to evaluate the association between exposure to air pollutants and DM. RESULTS: The odds ratios for DM associated with a 10 µg/m3 increase in PM1, PM2.5, PM10, CO, and NO2 were 1.898 (95% CI: 1.741, 2.070), 1.07 (95% CI: 1.053, 1.086), 1.013 (95% CI: 1.008, 1.018), 1.009 (95% CI: 1.007, 1.011), and 1.337 (95% CI: 1.234, 1.449), respectively. Notably, men, individuals aged ≥50 years, those with lower educational attainment, nonsmokers, and those not engaging in physical exercise displayed more susceptible to the adverse effects of air pollution. Multiple sensitivity analyses confirmed the stability of these findings. CONCLUSIONS: Our study provides robust evidence of a correlation between prolonged exposure to air pollution and the prevalence of DM among individuals living in the desert-adjacent areas. This research contributes to the expanding knowledge on the relationship between air pollution exposure and DM prevalence in desert-adjacent areas.

Exposure to ambient air pollution and metabolic dysfunction-associated fatty liver disease: Findings from over 2.7 million adults in Northwestern China.

Ambient air pollutants exposures may lead to aggravated Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD). However, there is still a scarcity of empirical studies that have rigorously estimated this association, especially in regions where air pollution is severe. To fill in the literature gap, we conducted a cross-sectional study involving 2711,207 adults living in five regions of southern Xinjiang Uyghur Autonomous Region in 2021. Using a Space-Time Extra-Trees model, we assessed the four-year (2017-2020) average concentrations of particulate matter with aerodynamic diameter ≤1 µm (PM1), particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5), particulate matter with aerodynamic diameter ≤10 µm (PM10), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO), and then assigned these values to the participants. Generalized linear mixed models were employed to examine the relationships between air pollutants and the prevalence of MAFLD, with adjustment for multiple confounding factors. The odds ratios and 95% confidence intervals of MAFLD were 2.002 (1.826-2.195), 1.133 (1.108-1.157), 1.034 (1.027-1.040), 1.077 (1.023-1.134), 2.703 (2.322-3.146) and 1.033 (1.029-1.036) per 10 µg/m3 increase in the 4-year average PM1, PM2.5, PM10, O3, SO2 and CO exposures, respectively. The robustness of the findings was confirmed by a series of sensitivities. In summary, long-term exposure to ambient air pollutants was associated with increased odds of MAFLD, particularly in males and individuals with unhealthy lifestyles.

City-level population projection for China under different pathways from 2010 to 2100.

Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.

Projecting future labor losses due to heat stress in China under climate change scenarios.

Climate change is expected to increase occupational heat stress, which will lead to diminished work performance and labor losses worldwide. However, sub-regional analyses remain insufficient, especially for countries with a heterogeneous spatial distribution of working populations, industries and climates. Here, we projected heat-induced labor losses in China, by considering local climate simulations, working population characteristics and developing an exposure-response function suitable for Chinese workers. We showed that the annual heat-induced work hours lost (WHL), compared to the baseline of 21.3 billion hours, will increase by 121.1% (111.2%-131.1%), 10.8% (8.3%-15.3%), and -17.8% (-15.3%--20.3%) by the end of the century under RCP(Representative Concentration Pathways)8.5, RCP4.5, and RCP2.6, respectively. We observed an approximately linear upward trend of WHL under RCP8.5, despite the decrease in future working population. Notably, WHL will be most prominent in the southern, eastern and central regions, with Guangdong and Henan accounting for a quarter of national total losses; this is largely due to their higher temperature exposure, larger population size, and higher shares of vulnerable population in total employment. In addition, limiting global warming to 1.5 °C would yield substantial gains. Compared to RCP2.6, RCP4.5, and RCP8.5, all provinces can avoid an average of 11.8%, 33.7%, and 53.9% of annual WHL if the 1.5 °C target is achieved, which is equivalent to avoiding 0.1%, 0.6%, and 1.4% of annual GDP losses in China, respectively. This study revealed climate change will exacerbate future labor losses, and adverse impacts can be minimized by adopting stringent mitigation policies coupled with effective adaptation measures. Policymakers in each province should tailor occupation health protection measures to their circumstances.

Who drives carbon emissions and what emission reduction potential in the resource curse agglomeration: a case of Xinjiang.

The primary problem in achieving carbon emission reduction and carbon peak is to identify the key driving factors and emission reduction potential of the industrial sector, especially in resource-cursed regions like Xinjiang. This study aimed to explore the key driving factors and abatement potential of carbon emissions based on the "energy-environment-economy" hybrid input-output model of Xinjiang during 1997-2017. The result showed that: (1) Industrial carbon emissions have experienced three stages: slow growth-rapid growth-stable growth. (2) Demand change effect and energy intensity effect were the determinants of Xinjiang industrial carbon emission change; Capital formation and domestic trade were the biggest drivers of carbon emissions growth; Especially after entering the "new normal",the driving force of imports in Xinjiang's international trade increased gradually over time. (3) The coal-based energy structure was both the biggest obstacle and the best entry point in carbon emission reduction. (4) Of the 28 key industry sectors, heavy industry including the production and supply of electricity and heat (S22), petroleum processing, coking and nuclear fuel processing (S11), chemical industry (S12), metal smelting and rolling (S14), and energy industries had the greatest potential for carbon reduction. The research findings provide scientific decision-making reference for Xinjiang to accurately grasp the carbon emission reduction potential of the industry and formulate a targeted carbon peak action plan.

Long-term exposure to fine particulate matter and cardiovascular disease: The mitigation role of environmental concerns.

Although it is widely acknowledged that environmental concerns can reduce PM2.5 pollution, few studies have empirically estimated whether environmental concerns could bring health benefits by mitigating PM2.5 pollution. Here, we quantified government and media environmental concerns with text-mining algorithm, matched with cohort data along with high-resolution gridded PM2.5 data. Accelerated failure time model and mediation model were used to explore the association between PM2.5 exposure and onset time to cardiovascular events, and the mitigation effect of environmental concerns. Every 1 µg/m3 increase in PM2.5 exposure was associated with shortened time to stroke and heart problem, with time ratios of 0.9900 and 0.9986, respectively. Each 1 unit increase in government and media environmental concerns, as well as their synergistic effect decreased PM2.5 pollution by 0.32 %, 0.25 % and 0.46 %, respectively; and decrease PM2.5 resulted in prolonged onset time to cardiovascular events. Mediation analysis revealed that reduced PM2.5 mediated up to 33.55 % of the association between environmental concerns and onset time to cardiovascular events, suggesting that other mediation pathways were also possible. Associations of PM2.5 exposure and environmental concerns with stroke and heart problem were similar in different subgroups. Overall, environmental concerns reduce risks of cardiovascular disease by mitigating PM2.5 pollution and other pathways in a real-world data set. This study provides insights for low-and-middle-income countries to address air pollution and improve health co-benefit.

Reconfirmation of the symbiosis on carbon emissions and air pollution: A spatial spillover perspective.

Many studies have confirmed the co-emission characteristics of air pollution and carbon emissions. However, studies on the evolution and synergistic factors of the symbiosis of air pollution and carbon emissions over long time scales from a spatial spillover perspective are rare. Here, we identify the spatial evolution and agglomeration characteristics of carbon emissions and air pollution symbiosis by applying local autocorrelation analysis and geographical concentration and by using the dynamic spatial autoregressive model for multiple synergistic factors at city levels during 2006-2019 in China. The results are: (1) The spatial agglomeration and symbiosis of carbon emission and air pollution are similar and show strong spatial locking, as well as path-dependent properties. (2) The spatial imbalance of carbon emission agglomeration and pollution agglomeration gradually improved over time; the concentration centers are all located in Henan province, shifting northward. (3) The symbiosis between both carbon emission agglomeration and pollution agglomeration has significant "spatial and temporal scale effects", and the economic growth is nonlinear. Additionally, innovation vitality has a negative synergistic driving effect on this relationship. In addition to the results above, rapid industrialization and urbanization are taking place in China. Hence, serious actions against greenhouse gases and air pollutants are imminently needed.

The burden of heatwave-related preterm births and associated human capital losses in China.

Frequent heatwaves under global warming can increase the risk of preterm birth (PTB), which in turn will affect physical health and human potential over the life course. However, what remains unknown is the extent to which anthropogenic climate change has contributed to such burdens. We combine health impact and economic assessment methods to comprehensively evaluate the entire heatwave-related PTB burden in dimensions of health, human capital and economic costs. Here, we show that during 2010-2020, an average of 13,262 (95%CI 6,962-18,802) PTBs occurred annually due to heatwave exposure in China. In simulated scenarios, 25.8% (95%CI 17.1%-34.5%) of heatwave-related PTBs per year on average can be attributed to anthropogenic climate change, which further result in substantial human capital losses, estimated at over $1 billion costs. Our findings will provide additional impetus for introducing more stringent climate mitigation policies and also call for more sufficient adaptations to reduce heatwave detriments to newborn.

Projections of heatwave-attributable mortality under climate change and future population scenarios in China.

Background: In China, most previous projections of heat-related mortality have been based on modeling studies using global climate models (GCMs), which can help to elucidate the risks of extreme heat events in a changing climate. However, spatiotemporal changes in the health effects of climate change considering specific regional characteristics remain poorly understood. We aimed to use credible climate and population projections to estimate future heatwave-attributable deaths under different emission scenarios and to explore the drivers underlying these patterns of changes. Methods: We derived climate data from a regional climate model driven by three CMIP5 GCM models and calculated future heatwaves in China under Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. The future gridded population data were based on Shared Socioeconomic Pathway 2 assumption with different fertility rates. By applying climate zone-specific exposure-response functions to mortality during heatwave events, we projected the scale of heatwave-attributable deaths under each RCP scenario. We further analyzed the factors driving changes in heatwave-related deaths and main sources of uncertainty using a decomposition method. We compared differences in death burden under the 1.5°C target, which is closely related to achieving carbon neutrality by mid-century. Findings: The number of heatwave-related deaths will increase continuously to the mid-century even under RCP2.6 and RCP4.5 scenarios, and will continue increasing throughout the century under RCP8.5. There will be 20,303 deaths caused by heatwaves in 2090 under RCP2.6, 35,025 under RCP4.5, and 72,260 under RCP8.5, with half of all heatwave-related deaths in any scenario concentrated in east and central China. Climate effects are the main driver for the increase in attributable deaths in the near future till 2060, explaining 78% of the total change. Subsequent population decline cannot offset the losses caused by higher incidence of heatwaves and an aging population under RCP8.5. Although health loss under the 1.5°C warming scenario is 1.6-fold higher than the baseline period 1986-2005, limiting the temperature rise to 1.5°C can reduce the annual mortality burden in China by 3,534 deaths in 2090 compared with RCP2.6 scenarios. Interpretation: With accelerating climate change and population aging, the effects of future heatwaves on human health in China are likely to increase continuously even under a low emission scenario. Significant health benefits are expected if the optimistic 1.5°C goal is achieved, suggesting that carbon neutrality by mid-century is a critical target for China's sustainable development. Policymakers need to tighten climate mitigation policies tailored to local conditions while enhancing climate resilience technically and infrastructurally, especially for vulnerable elderly people. Funding: National Key R&D Program of China (2018YFA0606200), Wellcome Trust (209734/Z/17/Z), Natural Science Foundation of China (41790471), and Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004).

Spatial distribution and determinants of PM2.5 in China's cities: fresh evidence from IDW and GWR.

While numerous studies have explored the spatial patterns and underlying causes of PM2.5 at the urban scale, little attention has been paid to the spatial heterogeneity affecting PM2.5 factors. In order to enrich this research field, we collected PM2.5 monitoring data from 367 cities across China in 2016 and combined inverse distance weighted interpolation (IDW) and geographically weighted regression (GWR) model. As a result, we could dynamically describe the spatial distribution pattern of urban PM2.5 at monthly, seasonal, and annual scales and investigate the spatial heterogeneity of the influential factors on urban PM2.5. Furthermore, in order to make the result more scientific and reasonable, the paper used selection.gwr function and bw.gwr function, respectively, to optimize model, thereby avoiding local collinearity caused by independent variables. The main results are as follows: (1) PM2.5 in Chinese cities is characterized as time-space non-equilibrium pattern. The Beijing-Tianjin-Hebei region, the Yangtze River corner region, the Pearl River Delta region, and the northeast region have formed a pollution-concentrating core area with Beijing-Tianjin-Hebei region as the axis, which brings greater difficulties and challenges to PM2.5 governance. (2) The effects of various factors of socio-economic activities on the concentration of PM2.5 have significant spatial heterogeneity among Chinese cities. (3) There is an inverted "U" curve between economic growth and PM2.5. When the per capita income reaches 47,000 yuan, the PM2.5 emission reaches the peak, which proves the existence of environmental Kuznets curve (EKC). These findings could provide a significant reference for policy makers in China to facilitate targeted and differentiated regional PM2.5 governance measures.

[Study on the relationship between dietary patterns and metabolic syndrome and its components in Xinjiang Uygur population].

OBJECTIVE: To analysis the dietary patterns and their relevance with MS and its components in the Uygur adults in Kashi of Xinjiang. METHODS: Used multi-stage random cluster sampling method, investigated the adult residents of Uighur aged over 18 years old in one county and one townships / street of three city in Kashi, may and six month in 2013 year. 24 hour dietary recall method for three consecutive days and food weighing method was used to collect the dietary intake of individual and family. The application of factor analysis to establish the dietary patterns and analysis, used the factor analysis method to establish the dietary pattern and analyzed the relevance between the dietary patterns and MS and its components. RESULTS: The named of the four main dietary patterns of adult residents in Kashi area, the traditional dietary patterns, the western dietary patterns. The meat eating patterns and the Uygur specific dietary pattern. The main dietary pattern is the traditional model of the diet. The western dietary pattern were negative correlationwith WHR and TC(r_(WHR)=- 0. 361, r_(TC)=- 0. 145) before and after the adjustment of covariates. The meat eating pattern were positive correlation between BMI and WHR and FPG( rBMI= 0. 128, r_(WHR)= 0. 149; r_(FPG)= 0. 083). The positive correlation between the Uygur specific pattern of diet and the fasting blood glucose(r_(FPG)=- 0. 112). There was no correlation between the traditional dietary pattern and MS and its components( P > 0. 05). The western dietary pattern was negative correlation with the prevalence of MS and hypertension. The meat eating patterns were positively correlated with high fasting blood glucose and obesity. The Uygur specific pattern of diet was negatively correlated with high fasting blood glucose. CONCLUSION: There were certain relevance in the Uygur population dietary patterns with MS and its components, which the western dietary pattern may was a protective factor for MS and hypertension, and the meat eating patterns may was fasting hyperglycemia and obesity risk factors, and the Uygur specific pattern of diet may was a protective factor for fasting hyperglycemia.