Chronic kidney disease (CKD) is a global public health concern, and accumulating evidence has indicated that air pollution increases the odds of CKD. However, a limited number of studies have examined the long-term effects of ambient fine particulate matter (PM2.5) components on the risk of CKD among general population; thus, major knowledge gaps remain. Using data from a nationwide representative cross-sectional survey in China and a validated PM2.5 composition dataset, we established generalized linear models to quantify the association between five major components of PM2.5 and CKD prevalence. There were significant associations between long-term exposure to three PM2.5 components [including black carbon (BC), sulfate (SO42−), organic matter (OM)] and increased odds of CKD prevalence. Along with an interquartile range (IQR) increment in BC (3.3 μg/m3), SO42− (9.7 μg/m3), and OM (16.2 μg/m3) at a 4-year moving average, the odds ratios (ORs) for CKD prevalence were 1.28 (95

BACKGROUND:High blood pressure (HBP) and diabetes mellitus (DM) are two of the most prevalent cardiometabolic disorders globally, especially among individuals with lower socio-economic status (SES). Studies have linked residential greenness to decreased risks of HBP and DM. However, there has been limited evidence on whether SES may modify the associations of residential greenness with HBP and DM. METHODS:Based on a national representative cross-sectional study among 44,876 adults, we generated the normalized difference vegetation index (NDVI) at 1 km spatial resolution to characterize individuals' residential greenness level. Administrative classification (urban/rural), nighttime light index (NLI), individual income, and educational levels were used to characterize regional urbanicity and individual SES levels. RESULTS:We observed weaker inverse associations of NDVI with HBP and DM in rural regions compared to urban regions. For instance, along with per interquartile range (IQR, 0.26) increment in residential NDVI at 0∼5 year moving averages, the ORs of HBP were 1.04 (95%CI: 0.94, 1.15) in rural regions and 0.85 (95%CI: 0.79, 0.93) in urban regions (P = 0.003). Along with the decrease in NLI levels, there were continuously decreasing inverse associations of NDVI with DM prevalence (P for interaction <0.001). In addition, weaker inverse associations of residential NDVI with HBP and DM prevalence were found among individuals with lower income and lower education levels compared to their counterparts. CONCLUSIONS:Lower regional urbanicity and individual SES could attenuate the associations of residential greenness with odds of HBP and DM prevalence.

Ambient air pollution exposure may increase the risk of obesity, but the population susceptibility associated with urbanicity has been insufficiently investigated. Based on a nationwide representative cross-sectional survey on 44,544 adults, high-resolution night light satellite remote sensing products, and multi-source ambient air pollution inversion data, the present study evaluated the associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations with the prevalence of obesity and abdominal obesity. We further calculated the associations in regions with different urbanicity levels characterized by both administrative classification of urban/rural regions and night light index (NLI). We found that 10 μg/m3 increments in PM2.5 at 1-year moving average and in NO2 at 5-year moving average were associated with increased prevalence of obesity [odds ratios (OR) = 1.16 (1.14, 1.19); 1.12 (1.09, 1.15), respectively] and abdominal obesity [OR = 1.08 (1.07, 1.10); 1.07 (1.05, 1.09), respectively]. People in rural regions experienced stronger adverse effects than those in urban regions. For instance, a 10 μg/m3 increment in PM2.5 was associated with stronger odds of obesity in rural regions than in urban regions [OR = 1.27 (1.23, 1.31) vs 1.10 (1.05, 1.14), P for interaction <0.001]. In addition, lower NLI values were associated with constantly amplified associations of PM2.5 and NO2 with obesity and abdominal obesity (all P for interaction <0.001). In summary, people in less urbanized regions are more susceptible to the adverse effects of ambient air pollution on obesity, suggesting the significance of collaborative planning of urbanization development and air pollution control, especially in less urbanized regions.

The health hazards of ambient ozone (O3) pollution are receiving increasing attention worldwide. However, the evidence on the association between O3 and risks of chronic kidney disease (CKD) remains insufficient and inconsistent, particularly in developing countries where there is an absence of macroscopic investigations at a large population scale. Based on data from a representative nationwide cross-sectional CKD survey in 13 Chinese provinces and a high resolution O3 air pollution inversion dataset, generalized linear models were used to evaluate the associations of O3 concentration with prevalence of CKD. The results of this study suggested that long-term O3 exposure was positively associated with the risk of CKD. A 10 μg/m3 increment in O3 concentration was associated with an increased odds of CKD prevalence [OR = 1.11 (95% CI: 1.03, 1.21)] among all the 47,086 participants. Stronger associations were found in urban regions, younger adults <65 years, and people with higher socio-economic status (income and education level). A 10 μg/m3 increment in O3 concentration was associated with a higher increased odds of CKD prevalence in urban regions [OR = 1.31 (95% CI: 1.16, 1.47)] compared to rural regions [OR = 0.95 (95% CI: 0.84, 1.08), P for subgroup difference<0.001]. A stronger association of O3 concentration with CKD prevalence was found among younger people aged <65 years [OR = 1.21 (95% CI: 1.10, 1.33)] compared to those aged ≥65 years [OR = 0.92 (95% CI: 0.79, 1.07), P for subgroup difference = 0.003]. Our study demonstrated that long-term O3 exposure may increase risk of CKD in the general Chinese population, and the findings stressed the importance of persistent efforts in air pollution prevention and control.

Background:Accumulated researches revealed that both fine particulate matter (PM2.5) and sunlight exposure may be a risk factor for obesity, while researches regarding the potential effect modification by sunlight exposure on the relationship between PM2.5 and obesity are limited. We aim to investigate whether the effect of PM2.5 on obesity is affected by sunlight exposure among the general population in China.Methods:A sample of 47,204 adults in China was included. Obesity and abdominal obesity were assessed based on body mass index, waist circumference and waist-to-hip ratio, respectively. The five-year exposure to PM2.5 and sunlight were accessed using the multi-source satellite products and a geochemical transport model. The relationship between PM2.5, sunshine duration, and the obesity or abdominal obesity risk was evaluated using the general additive model.Results:The proportion of obesity and abdominal obesity was 12.6% and 26.8%, respectively. Levels of long-term PM2.5 ranged from 13.2 to 72.1 μg/m3 with the mean of 46.6 μg/m3. Each 10 μg/m3 rise in PM2.5 was related to a higher obesity risk [OR 1.12 (95% CI 1.09-1.14)] and abdominal obesity [OR 1.10 (95% CI 1.07-1.13)]. The association between PM2.5 and obesity varied according to sunshine duration, with the highest ORs of 1.56 (95% CI 1.28-1.91) for obesity and 1.66 (95% CI 1.34-2.07) for abdominal obesity in the bottom quartile of sunlight exposure (3.21-5.34 hours/day).Conclusion:Long-term PM2.5 effect on obesity risk among the general Chinese population are influenced by sunlight exposure. More attention might be paid to reduce the adverse impacts of exposure to air pollution under short sunshine duration conditions.

Background We aimed to explore the association between long-term exposure to particulate matter ≤ 2.5 µm (PM 2.5 ) and metabolic syndrome (MetS) and its components including fasting blood glucose (FBG), blood pressure, triglyceride (TG), high-density lipoprotein cholesterol (HDL-c) and waist circumference among adults and elderly in south China. Methods We surveyed 6628 participants in the chronic disease and risk factors surveillance conducted in 14 districts of Guangdong province in 2015. MetS was defined based on the recommendation by the Joint Interim Societies’ criteria. We used the spatiotemporal land-use regression (LUR) model to estimate the two-year average exposure of ambient air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 ) at individual levels. We recorded other covariates by using a structured questionnaire. Generalized linear mixed model was used for analysis. Results A 10-μg/m 3 increase in the two-year mean PM 2.5 exposure was associated with a higher risk of developing MetS [odd ratio (OR): 1.17, 95% confidence interval (CI): 1.01, 1.35], increased risk of fasting blood glucose level. (OR: 1.18, 95% CI: 1.02, 1.36), and hypertriglyceridemia (OR: 1.36, 95% CI: 1.18, 1.58) in the adjusted/unadjusted models (all P < 0.05). We found significant interaction between PM 2.5 and the region, exercise on the high TG levels, and an interaction with the region, age, exercise and grain consumption on FBG ( P interaction < 0.05). Conclusions Long-term exposure to PM 2.5 was associated with MetS, dyslipidemia and FBG impairment. Efforts should be made for environment improvement to reduce the burden of MetS-associated non-communicable disease.

Forests are important for the global carbon cycle, hydrothermal balance, and climate change. Human activities can exert a significant impact on forest ecosystems, thereby having the potential to alter their physical and chemical properties and thus affecting carbon, water, and heat budgets, and climate change. The historical reconstruction of the disturbance of global forests can help us understand the processes and patterns of human activities and global change. In this paper, we construct a deforestation prediction model using a Spearman correlation coefficient and implement the XGBoost method, using Python 3.6, for the reconstruction of deforestation intensity data from 2000 to 2019. Secondly, the selection of the driver indicators is done by using extreme difference regularization to unify the magnitude, and the potential deforestation area risk index is calculated in the form of equal weights. Finally, the actual deforestation data were used for optimization and validation. The model shows that the deforestation hotspots are mainly concentrated in the southern and southeastern regions of China and that there are large differences in deforestation in different provinces. In the future, the fine spatial and temporal patterns of deforestation in China during the historical period can be quantitatively reconstructed, which can provide some reference information for forest disaster prevention and forest management in China.

[背景]已有数项研究提示大气细颗粒物(PM2.5)长期暴露可能增加慢性肾脏病(CKD)患病风险,但对二氧化氮(NO2)的相关研究仍然有限.[目的]探究大气NO2长期暴露与我国成人CKD患病风险的关联.[方法]基于2007年1月-2010年10月期间"中国慢性肾脏病流行病学调查"健康数据,进行环境暴露数据采集与匹配.利用广义相加模型探究大气NO2长期暴露对我国成人CKD患病风险的估计效应.基于性别,年龄,体重指数(BMI),受教育程度,人月均收入,城乡,吸烟、饮酒情况,高血压、糖尿病、心肌梗死/脑卒中病史等因素进行亚组分析.建立双污染物敏感性分析,检验上述结果的稳定性.[结果]研究纳入我国13个省(自治区、直辖市)共47 204名研究对象.大气NO2长期暴露与我国成人CKD患病风险增加的关联具有统计学意义,且在5年时达到最大.NO2的5年滑动平均值每增加10μg.m-3,CKD患病风险比值比(OR)为1.15(95％CI:1.11～1.19).亚组分析结果提示:男性,65岁及以上,超重及肥胖,初中以上学历,人月均收入500元及以下,农村,每天吸烟,偶尔或经常饮酒,无高血压、糖尿病、心肌梗死/脑卒中病史的人群CKD患病风险与NO2长期暴露的关联更强:NO2暴露每增加10μg·m-3,男性人群CKD患病的OR为1.30(95％CI:1.24～1.37),高于女性(OR=1.04,95％CI:1.00～1.09)(交互项P＜0.01);农村地区人群CKD 患病的OR为 1.57(95％CI:1.33～1.85),高于城市人群(OR=1.09,95％CI:0.99～1.21)(交互项P＜0.01);非糖尿病患病人群CKD患病的OR为1.21(95％CI:1.16～1.26),高于糖尿病患病人群(OR=1.01,95％CI:0.95～1.07)(交互项P＜0.01).敏感性分析结果显示,在控制同期PM2.5的混杂后,NO2长期暴露与CKD患病风险的关联仍然稳定.[结论]大气NO2长期暴露与我国成人CKD患病风险增加有关.男性,65岁及以上,超重及肥胖,初中以上学历,人月均收入500元及以下,农村地区,每天吸烟,偶尔或经常饮酒,无高血压、糖尿病、心肌梗死/脑卒中病史可能是NO2长期暴露对肾脏健康影响的易感因素.

Green space is associated with many health benefits, but evidence concerning the effects on chronic kidney disease (CKD) has not been investigated. Using the nationwide cross-sectional study of 47,204 adults from the China National Survey of Chronic Kidney Disease dataset and residential greenness assessed by the normalized difference vegetation index (NDVI), this study evaluated the association between residential greenness and CKD prevalence. An interquartile range increase in NDVI1000m (0.26) was associated with decreased odds of CKD for all participants with an odds ratio (OR) of 0.79 (95% confidence interval [CI]: 0.73-0.86). Subgroup analyses demonstrated more apparent inverse associations in younger adults <65 years, male participants, people in higher socio-economic status, as well as people with smoking and alcohol drinking habit. In addition, more apparent inverse associations were found in regions with higher fine particulate matter (PM2.5) concentration levels, with OR of 0.56 (95% CI: 0.49, 0.65) for higher pollution regions, and OR of 0.95 (95% CI: 0.83, 1.09) for lower pollution regions (P for interaction <0.001). The exposure-response curves captured more apparent declines in OR of CKD when in lower NDVI1000m exposure ranges (<0.6), even controlling for the PM2.5 concentration. Our results indicated that residential greenness might be beneficial for the prevention and control of CKD at the population level, suggesting the positive significance of strengthening green space construction, particularly in regions with low greenness.

An increasing number of studies have linked ambient air pollution to chronic kidney disease (CKD) prevalence. However, its potential effect modification by urbanization has not been investigated. Based on data of 47,204 adults from the China National Survey of Chronic Kidney Disease (CKSCKD) dataset, night light satellite remote sensing data and high-resolution air pollution inversion products, the present cross-sectional study investigated the association between fine particulate matter <2.5 mm in diameter (PM2.5), nitrogen dioxide (NO2), night light index (NLI) and CKD prevalence in China, and the effect modification by urbanization characterized by administrative classification and NLI on the pollutant-health associations. Our results showed that a 10-μg/m3 increase in PM2.5 at 3-year moving average, a 10-μg/m3 increase in NO2 at 5-year moving average, and a 10-U increase in NLI at 5-year moving average were significantly associated with increased odds of CKD prevalence [OR = 1.24 (95 %CI:1.14, 1.35); OR = 1.12 (95 %CI:1.09, 1.15); OR = 1.05 (95 %CI:1.02, 1.07)]. Meanwhile, the pollutant-health associations were more apparent in medium-urbanized areas compared to low- and high-urbanized areas. For instance, a 10-μg/m3 increase in PM2.5 concentration at 2-year moving average was associated with increased odds of CKD in the areas with NLI level in the second [OR = 2.78 (95 %CI:1.77, 4.36)] and third quartiles [OR = 1.49 (95 %CI:1.14, 1.95)], compared to the lowest [OR = 0.96 (95% CI: 0.73, 1.26)] and highest [OR = 0.63 (95% CI: 0.39–1.02)] quartiles. PM2.5 and NO2 were associated with increased odds of CKD prevalence, especially in areas with medium NLI levels, suggesting the necessity of strengthening environmental management in medium-urbanized regions.