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Association of the components of ambient fine particulate matter (PM2.5) and chronic kidney disease prevalence in China
Abstract
Previous research has implicated PM2.5 as a potential environmental risk factor for CKD, but little is known about the associations between its components and CKD. We conducted a nationwide cross-sectional study using the updated air pollution data in the nationwide population (N = 2,938,653). Using generalized additive models, we assessed the association between long-term exposure to PM2.5 and its components (i.e., black carbon [BC], organic matter [OM], nitrate [NO3-], ammonium [NH4+], sulfate [SO42-]), and CKD prevalence. The air pollution data was estimated using high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. Besides, we adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM2.5 constituents on CKD prevalence. The average concentration of PM2.5 was 78.67 ± 22.5 μg/m3, which far exceeded WHO AQG. In the fully adjusted generalized additive model, at a 10 km × 10 km spatial resolution, the ORs per IQR increase in previous 1-year average PM2.5 exposures was 1.380 (95%CI: 1.345-1.415), for NH4+ was 1.094 (95%CI: 1.062-1.126), for BC was 1.604 (95%CI: 1.563-1.646), for NO3- was 1.094 (95%CI: 1.060-1.130), for SO42- was 1.239 (95%CI: 1.208-1.272), and for the OM was 1.387 (95%CI: 1.354-1.421), respectively. Subgroup analysis showed females, younger, and healthier were more vulnerable to this effect. In the further exploration of the joint effect of PM2.5 compositions (OR 1.234 [95%CI 1.222-1.246]) per quartile increase in all 5 PM2.5 components, we found that PM2.5SO42- contributed the most. These findings provide important evidence for the positive relationship between long-term exposure to PM2.5 and its chemical constituents and CKD prevalence in a Chinese health check-up population, and identified PM2.5SO42- has the highest contribution to this relationship. This study provides clinical and public health guidance for reducing specific air particle exposure for those at risk of CKD.
... Another study based on the Chinese health check-up population showed that long-term exposure to all five PM 2.5 components were associated with decreased kidney function (eGFR < 60 mL/min/1.73 m 2 ) (Zhang et al., 2023). This present study revealed that long-term exposure to BC, OM, and SO 4 2− was associated with greater odds of CKD prevalence in the general population. ...
... Stratified analyses and sensitivity analyses further highlighted our findings. Our results are partly in line with the findings of earlier studies (Zhang et al., 2023;Zhao et al., 2020). However, the results of PM 2.5 component-associated health effects differ because of variations in study population, pollution sources, and methods of assessment for PM 2.5 exposure. ...
... In our study, only long-term SO 4 2− exposure was observed to be related with higher CKD prevalence, while no significant association for NO 3 − or NH 4 + with CKD prevalence was found at the exposure metrics. SO 4 2− was also identified as the most significant contributor to the association between longterm exposure to PM 2.5 and reduced kidney function in a health check-up population (Zhang et al., 2023). However, our findings differ from those of another study involving pregnant Chinese women that reported positive associations of NO 3 − and NH 4 + with decreased eGFR (Zhao et al., 2020). ...
Objectives
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.
Methods
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.
Results
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% CI 1.07, 1.54), 1.23 (95% CI 1.03, 1.45), and 1.23 (95% CI 1.02, 1.47), respectively. We did not detect any significant association of the other two PM2.5 components [nitrate (NO3⁻) or ammonium (NH4⁺)] with CKD prevalence. Stratified analyses revealed no differences (P ≥ 0.05) in the effect estimates of subgroups based on administrative region, sex, age, and other demographic characteristics. For instance, along with an IQR increment in BC at a 4-year moving average, the ORs of CKD prevalence among males and females were 1.30 (95% CI 0.98, 1.73) and 1.29 (95% CI 1.01, 1.65), respectively. The odds of CKD were generally higher with increasing PM2.5 composition concentration.
Conclusions
Our study demonstrated that long-term exposure to specific PM2.5 components including BC, SO4²⁻, and OM increased CKD risk in the general population. This study could provide new insights into source-directed PM2.5 control and CKD prevention.
... The study's sample sizes were in the range of 2,083 to 2,938,653, with a total of 7,967,388 samples included in the meta-analysis. Three studies were conducted in North America (all in the USA) [22][23][24] , five in European countries (Sweden, the United Kingdom) [25][26][27][28][29] , and fourteen in Asia countries (China, Korea, Taiwan) [30][31][32][33][34][35][36][37][38][39][40][41][42][43] . These studies yielded a total sample of three continents (Asia: 48.6%, North America: 32.6%, and Europe: 18.8%). ...
... In the included studies, there are three main methods for assessing levels of PM 2.5 exposure. The first one is obtained directly average air pollutant monitoring measurements from monitoring stations 32,37 ; the second one is to use built models to make predictions [22][23][24][25][26][27][28][29][30][31][33][34][35][36][37][39][40][41][42] ; and the last one is to use a machine-learning model 38,43 . Furthermore, the period of sampling encompassed the years 1987 to 2019, and the period of exposure assessment also varied across the included studies. ...
Several studies have reported an increased risk of chronic kidney disease (CKD) outcomes after long-term exposure (more than 1 year) to particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5). However, the conclusions remain inconsistent. Therefore, we conducted this meta-analysis to examine the association between long-term PM2.5 exposure and CKD outcomes. A literature search was conducted in PubMed, Scopus, Cochrane Central Register of Controlled trials, and Embase for relevant studies published until August 10, 2023. The main outcomes were incidence and prevalence of CKD as well as incidence of end-stage kidney disease (ESKD). The random-effect model meta‐analyses were used to estimate the risk of each outcome among studies. Twenty two studies were identified, including 14 cohort studies, and 8 cross-sectional studies, with a total of 7,967,388 participants. This meta-analysis revealed that each 10 μg/m³ increment in PM2.5 was significantly associated with increased risks of both incidence and prevalence of CKD [adjusted odds ratio (OR) 1.31 (95% confidence interval (CI) 1.24 to 1.40), adjusted OR 1.31 (95% CI 1.03 to 1.67), respectively]. In addition, the relationship with ESKD incidence is suggestive of increased risk but not conclusive (adjusted OR 1.16; 95% CI 1.00 to 1.36). The incidence and prevalence of CKD outcomes had a consistent association across all subgroups and adjustment variables. Our study observed an association between long-term PM2.5 exposure and the risks of CKD. However, more dedicated studies are required to show causation that warrants urgent action on PM2.5 to mitigate the global burden of CKD.
Although epidemiological studies have evaluated the association between ambient air pollution and chronic kidney disease (CKD), the results remain mixed. To clarify the nature of the association, we conducted a comprehensive systematic review and meta‐analysis to assess the global relationship between air pollution and CKD. The Web of Science, PubMed, Embase and Cochrane Library databases systematically were searched for studies published up to July 2023 and included 32 studies that met specific criteria. The random effects model was used to derive overall risk estimates for each pollutant. The meta‐analysis estimated odds ratio (ORs) of risk for CKD were 1.42 (95% confidence interval [CI]: 1.31–1.54) for each 10 μg/m ³ increase in PM 2.5 ; 1.20 (95% CI: 1.14–1.26) for each 10 μg/m ³ increase in PM 10 ; 1.07 (95% CI: 1.05–1.09) for each 10 μg/m ³ increase in NO 2 ; 1.03 (95% CI: 1.02–1.03) for each 10 μg/m ³ increase in NO X ; 1.07 (95% CI: 1.01–1.12) for each 1 ppb increase in SO 2 ; 1.03 (95% CI: 1.00–1.05) for each 0.1 ppm increase in CO. Subgroup analysis showed that this effect varied by gender ratio, age, study design, exposure assessment method, and income level. Furthermore, PM 2.5 , PM 10 , and NO 2 had negative effects on CKD even within the World Health Organization‐recommended acceptable concentrations. Our results further confirmed the adverse effect of air pollution on the risk of CKD. These findings can contribute to enhance the awareness of the importance of reducing air pollution among public health officials and policymakers.
Background
Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported.
Methods
A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity.
Results
Each 10 µg/m ³ increment in lag 0–1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM 1 , 0.49% (95% CI: 0.10% to 0.88%) for PM 2.5 , 0.32% (95% CI: 0.08% to 0.57%) for PM 10 , 1.26% (95% CI: 0.29% to 2.24%) for NO 2 , and 2.9% (95% CI: 1.68% to 4.15%) for SO 2 .
Conclusions
Our study suggests that short-term exposure to ambient PM 1 , PM 2.5 , PM 10 , NO 2 , and SO 2 might be important environmental risk factors for death due to kidney diseases in China.
PM2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM2.5 data. PM2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.
Background
Emerging evidence suggests that early-life (in-utero and first-year since birth) exposure to ambient PM2.5 is a risk factor for asthma onset and exacerbation among children, while the hazards caused by PM2.5 compositions remain largely unknown.
Objective
To examine potential associations of early-life exposures to PM2.5 mass and its major chemical constituents with childhood asthma and wheezing.
Methods
By conducting the Phase II of the China, Children, Homes, Health study, we investigated 30,325 preschool children aged 3–6 years during 2019–2020 in mainland China. Early-life exposure to PM2.5 mass and its constituents (i.e., black carbon [BC], organic matter [OM], nitrate, ammonium, sulfate) were calculated based on monthly estimates at a 1 km × 1 km resolution from satellite-based models. We adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM2.5 constituents on childhood asthma/wheezing.
Results
The average PM2.5 concentrations during in-utero and the first year since birth were 64.7 ± 10.6 and 61.8 ± 10.5 µg/m³, respectively. Early-life exposures to a mixture of major PM2.5 constituents were significantly associated with increased risks of asthma and wheezing, while no evident compositions-wheezing associations were found in the first year. Each quintile increases in all five PM2.5 components exposures in utero was accordingly associated with an odds ratio of 1.18 [95% confidence interval: 1.07–1.29] for asthma and 1.08 [1.01–1.16] for wheezing. BC, OM and SO4²⁻ contributed more to risks of asthma and wheezing than the other PM2.5 constituents during early life, wherein the effects of BC were only observed during pregnancy. Sex subgroup analyses suggested stronger associations among girls of first-year exposures to PM2.5 components with childhood asthma.
Conclusion
Early-life exposures to ambient PM2.5, particularly compositions of BC, OM and SO4²⁻, are associated with an increased risk of childhood asthma.
Following publication of the original article [1], the authors identified an error in Fig. 2. The correct figure is given below. The original article has been corrected.
The manuscript analyzes the levels of PM2.5 in 47 cities from all over the world using data from WHO Air Quality Reports from 2014, 2016 and 2018, and compares to the previous and the new WHO Air Quality Guidelines. Cities were divided in groups of lower and higher air pollution levels. Many of the lower air pollution ones were already above the previous guidelines, while just two of them, Porto and Stockholm, already complied with the new guidelines considering 2018 data. Even in this group of cities, many will need to reduce PM2.5 concentrations between 50% to more than 70% to be under the new WHO guidelines. Among the cities with higher air pollution levels, most of them will need to decrease PM2.5 concentrations more than 90% to meet new WHO guidelines, including Beijing, Riyadh, Karachi, Ulaanbaatar and New Delhi.
The purpose of this paper was to highlight the importance of the revision of the values for these new Air Quality Guidelines as well as the challenge that will mean for many cities/countries to comply with them. These new Air Quality Guidelines along with the simultaneous pressure to reduce the use of fossil fuels to mitigate climate change, with many countries stablishing goals for reduction of CO2 emissions to comply to the Paris Agreement, will sure be essential for the transition to a decarbonized world, contributing to save millions of lives.
Link to Supplementary appendix:
https://www.thelancet.com/cms/10.1016/S2542-5196(21)00287-4/attachment/80dca813-706f-4294-b932-626b0f21f442/mmc1.pdf
Background
Current equations for estimated glomerular filtration rate (eGFR) that use serum creatinine or cystatin C incorporate age, sex, and race to estimate measured GFR. However, race in eGFR equations is a social and not a biologic construct.
Methods
We developed new eGFR equations without race using data from two development data sets: 10 studies (8254 participants, 31.5% Black) for serum creatinine and 13 studies (5352 participants, 39.7% Black) for both serum creatinine and cystatin C. In a validation data set of 12 studies (4050 participants, 14.3% Black), we compared the accuracy of new eGFR equations to measured GFR. We projected the prevalence of chronic kidney disease (CKD) and GFR stages in a sample of U.S. adults, using current and new equations.
Results
In the validation data set, the current creatinine equation that uses age, sex, and race overestimated measured GFR in Blacks (median, 3.7 ml per minute per 1.73 m² of body-surface area; 95% confidence interval [CI], 1.8 to 5.4) and to a lesser degree in non-Blacks (median, 0.5 ml per minute per 1.73 m²; 95% CI, 0.0 to 0.9). When the adjustment for Black race was omitted from the current eGFR equation, measured GFR in Blacks was underestimated (median, 7.1 ml per minute per 1.73 m²; 95% CI, 5.9 to 8.8). A new equation using age and sex and omitting race underestimated measured GFR in Blacks (median, 3.6 ml per minute per 1.73 m²; 95% CI, 1.8 to 5.5) and overestimated measured GFR in non-Blacks (median, 3.9 ml per minute per 1.73 m²; 95% CI, 3.4 to 4.4). For all equations, 85% or more of the eGFRs for Blacks and non-Blacks were within 30% of measured GFR. New creatinine–cystatin C equations without race were more accurate than new creatinine equations, with smaller differences between race groups. As compared with the current creatinine equation, the new creatinine equations, but not the new creatinine–cystatin C equations, increased population estimates of CKD prevalence among Blacks and yielded similar or lower prevalence among non-Blacks.
Conclusions
New eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.)
Background:
Fine particulate matter (PM2.5) is an important environmental risk factor for cardiopulmonary diseases. However, the association between PM2.5 and risk of CKD remains under-recognized, especially in regions with high levels of PM2.5, such as China.
Methods:
To explore the association between long-term exposure to ambient PM2.5 and CKD prevalence in China, we used data from the China National Survey of CKD, which included a representative sample of 47,204 adults. We estimated annual exposure to PM2.5 before the survey date at each participant's address, using a validated, satellite-based, spatiotemporal model with a 10 km×10 km resolution. Participants with eGFR <60 ml/min per 1.73 m2 or albuminuria were defined as having CKD. We used a logistic regression model to estimate the association and analyzed the influence of potential modifiers.
Results:
The 2-year mean PM2.5 concentration was 57.4 μg/m3, with a range from 31.3 to 87.5 μg/m3. An increase of 10 μg/m3 in PM2.5 was positively associated with CKD prevalence (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.22 to 1.35) and albuminuria (OR, 1.39; 95% CI, 1.32 to 1.47). Effect modification indicated these associations were significantly stronger in urban areas compared with rural areas, in males compared with females, in participants aged <65 years compared with participants aged ≥65 years, and in participants without comorbid diseases compared with those with comorbidities.
Conclusions:
These findings regarding the relationship between long-term exposure to high ambient PM2.5 levels and CKD in the general Chinese population provide important evidence for policy makers and public health practices to reduce the CKD risk posed by this pollutant.
Fine particulate matter with aerodynamic diameters ≤2.5 µm
(PM2.5) has adverse effects on human health and the atmospheric
environment. The estimation of surface PM2.5 concentrations has made
intensive use of satellite-derived aerosol products. However, it has been a great challenge to obtain high-quality and high-resolution PM2.5 data from both ground and satellite observations, which is essential to monitor air pollution over small-scale areas such as metropolitan regions. Here, the space–time
extremely randomized trees (STET) model was enhanced by integrating updated
spatiotemporal information and additional auxiliary data to improve the
spatial resolution and overall accuracy of PM2.5 estimates across
China. To this end, the newly released Moderate Resolution Imaging
Spectroradiometer Multi-Angle Implementation of Atmospheric Correction AOD product, along with meteorological, topographical and land-use data and
pollution emissions, was input to the STET model, and daily 1 km PM2.5
maps for 2018 covering mainland China were produced. The STET model performed
well, with a high out-of-sample (out-of-station) cross-validation coefficient
of determination (R2) of 0.89 (0.88), a low root-mean-square error of
10.33 (10.93) µg m−3, a small mean absolute error of 6.69 (7.15) µg m−3 and a small mean relative error of 21.28 % (23.69 %).
In particular, the model captured well the PM2.5 concentrations at both
regional and individual site scales. The North China Plain, the Sichuan
Basin and Xinjiang Province always featured high PM2.5 pollution
levels, especially in winter. The STET model outperformed most models
presented in previous related studies, with a strong predictive power (e.g.,
monthly R2=0.80), which can be used to estimate historical
PM2.5 records. More importantly, this study provides a new approach
for obtaining high-resolution and high-quality PM2.5 dataset across mainland
China (i.e., ChinaHighPM2.5), important for air pollution studies
focused on urban areas.
Background:
Chronic kidney disease (CKD) is a serious global public health challenge, but there is limited information on the connection between air pollution and risk of CKD.
Objective:
The aim of this study was to investigate the association between long-term exposure to particulate matter (PM) with an aerodynamic diameter of less than [Formula: see text] ([Formula: see text]) and the development of CKD in a large cohort.
Methods:
A total of 100,629 nonCKD Taiwanese residents age 20 y or above were included in this study between 2001 and 2014. Ambient [Formula: see text] concentration was estimated at each participant's address using a satellite-based spatiotemporal model. Incident CKD cases were identified by an estimated glomerular filtration rate (eGFR) of less than [Formula: see text]. We collected information on a wide range of potential confounders/modifiers during the medical examinations. Cox proportional hazard regression was applied to calculate hazard ratios (HRs).
Results:
During the follow-up, 4,046 incident CKD cases were identified, and the incidence rate was 6.24 per 1,000 person-years. In contrast with participants with the first quintile exposure of [Formula: see text], participants with the fourth and fifth quintiles exposure of [Formula: see text] had increased risk of CKD development, adjusting for age, sex, educational level, smoking, drinking, body mass index, systolic blood pressure, fasting glucose, total cholesterol, and self-reported heart disease or stroke, with an HR [95% confidence interval (CI)] of 1.11 (1.02, 1.22) and 1.15 (1.05, 1.26), respectively. A significant concentration-response trend was observed ([Formula: see text]). Every [Formula: see text] increment in the [Formula: see text] concentration was associated with a 6% higher risk of developing CKD (HR: 1.06, 95% CI: 1.02, 1.10). Sensitivity and stratified analyses yielded similar results.
Conclusions:
Long-term exposure to ambient [Formula: see text] was associated with an increased risk of CKD development. Our findings reinforce the urgency to develop global strategies of air pollution reduction to prevent CKD. https://doi.org/10.1289/EHP3304.
Elevated levels of fine particulate matter <2.5 µm in aerodynamic diameter (PM2.5) are associated with increased risk of cardiovascular outcomes and death, but their association with risk of CKD and ESRD is unknown. We linked the Environmental Protection Agency and the Department of Veterans Affairs databases to build an observational cohort of 2,482,737 United States veterans, and used survival models to evaluate the association of PM2.5 concentrations and risk of incident eGFR <60 ml/min per 1.73 m(2), incident CKD, eGFR decline ≥30%, and ESRD over a median follow-up of 8.52 years. County-level exposure was defined at baseline as the annual average PM2.5 concentrations in 2004, and separately as time-varying where it was updated annually and as cohort participants moved. In analyses of baseline exposure (median, 11.8 [interquartile range, 10.1-13.7] µg/m(3)), a 10-µg/m(3) increase in PM2.5 concentration was associated with increased risk of eGFR<60 ml/min per 1.73 m(2) (hazard ratio [HR], 1.21; 95% confidence interval [95% CI], 1.14 to 1.29), CKD (HR, 1.27; 95% CI, 1.17 to 1.38), eGFR decline ≥30% (HR, 1.28; 95% CI, 1.18 to 1.39), and ESRD (HR, 1.26; 95% CI, 1.17 to 1.35). In time-varying analyses, a 10-µg/m(3) increase in PM2.5 concentration was associated with similarly increased risk of eGFR<60 ml/min per 1.73 m(2), CKD, eGFR decline ≥30%, and ESRD. Spline analyses showed a linear relationship between PM2.5 concentrations and risk of kidney outcomes. Exposure estimates derived from National Aeronautics and Space Administration satellite data yielded consistent results. Our findings demonstrate a significant association between exposure to PM2.5 and risk of incident CKD, eGFR decline, and ESRD.
Background
Particulate matter exposure is associated with respiratory and cardiovascular system dysfunction. Recently, we demonstrated that fine particles, also named PM2.5, modify the expression of some components of the angiotensin and bradykinin systems, which are involved in lung, cardiac and renal regulation. The endocrine kidney function is associated with the regulation of angiotensin and bradykinin, and it can suffer damage even as a consequence of minor alterations of these systems. We hypothesized that exposure to PM2.5 can contribute to early kidney damage as a consequence of an angiotensin/bradykinin system imbalance, oxidative stress and/or inflammation.
Results
After acute and subchronic exposure to PM2.5, lung damage was confirmed by increased bronchoalveolar lavage fluid (BALF) differential cell counts and a decrease of surfactant protein-A levels. We observed a statistically significant increment in median blood pressure, urine volume and water consumption after PM2.5 exposure. Moreover, increases in the levels of early kidney damage markers were observed after subchronic PM2.5 exposure: the most sensitive markers, β-2-microglobulin and cystatin-C, increased during the first, second, sixth and eighth weeks of exposure. In addition, a reduction in the levels of specific cytokines (IL-1β, IL-6, TNF-α, IL-4, IL-10, INF-γ, IL-17a, MIP-2 and RANTES), and up-regulated angiotensin and bradykinin system markers and indicators of a depleted antioxidant response, were also observed. All of these effects are in concurrence with the presence of renal histological lesions and an early pro-fibrotic state.
Conclusion
Subchronic exposure to PM2.5 induced an early kidney damage response that involved the angiotensin/bradykinin systems as well as antioxidant and immune imbalance. Our study demonstrates that PM2.5 can induce a systemic imbalance that not only affects the cardiovascular system, but also affects the kidney, which may also overall contribute to PM-related diseases.
Electronic supplementary material
The online version of this article (doi:10.1186/s12989-016-0179-8) contains supplementary material, which is available to authorized users.
The effect of air pollution on the changing pattern of glomerulopathy has not been studied. We estimated the profile of and temporal change in glomerular diseases in an 11-year renal biopsy series including 71,151 native biopsies at 938 hospitals spanning 282 cities in China from 2004 to 2014, and examined the association of long-term exposure to fine particulate matter of <2.5 μm (PM2.5) with glomerulopathy. After age and region standardization, we identified IgA nephropathy as the leading type of glomerulopathy, with a frequency of 28.1%, followed by membranous nephropathy (MN), with a frequency of 23.4%. Notably, the adjusted odds for MN increased 13% annually over the 11-year study period, whereas the proportions of other major glomerulopathies remained stable. During the study period, 3-year average PM2.5 exposure varied among the 282 cities, ranging from 6 to 114 μg/m(3) (mean, 52.6 μg/m(3)). Each 10 μg/m(3) increase in PM2.5 concentration associated with 14% higher odds for MN (odds ratio, 1.14; 95% confidence interval, 1.10 to 1.18) in regions with PM2.5 concentration >70 μg/m(3) We also found that higher 3-year average air quality index was associated with increased risk of MN. In conclusion, in this large renal biopsy series, the frequency of MN increased over the study period, and long-term exposure to high levels of PM2.5 was associated with an increased risk of MN.
Background/aims:
Epidemiological evidence indicates that patients with chronic kidney diseases have increased susceptibility to adverse outcomes related to long-term exposure to particulate air pollution. However, mechanisms underlying these effects are not fully understood.
Methods:
Presently, we assessed the effect of prolonged exposure to diesel exhaust particles (DEP) on chronic renal failure induced by adenine (0.25% w/w in feed for 4 weeks), which is known to involve inflammation and oxidative stress. DEP (0.5m/kg) was intratracheally (i.t.) instilled every 4th day for 4 weeks (7 i.t. instillation). Four days following the last exposure to either DEP or saline (control), various renal endpoints were measured.
Results:
While body weight was decreased, kidney weight increased in DEP+adenine versus saline+adenine or DEP. Water intake, urine volume, relative kidney weight were significantly increased in adenine+DEP versus DEP and adenine+saline versus saline. Plasma creatinine and urea increased and creatinine clearance decreased in adenine+DEP versus DEP and adenine+saline versus saline. Tumor necrosis factor α, lipid peroxidation and reactive oxygen species were significantly increased in adenine+DEP compared with either DEP or adenine+saline. The antioxidant calase was significantly decreased in adenine+DEP compared with either adenine+saline or DEP. Notably, renal DNA damage was significantly potentiated in adenine+DEP compared with either adenine+saline or DEP. Similarly, systolic blood pressure was increased in adenine+DEP versus adenine+saline or DEP, and in DEP versus saline. Histological evaluation revealed more collagen deposition, higher number of necrotic cell counts and dilated tubules, cast formation and collapsing glomeruli in adenine+DEP versus adenine+saline or DEP.
Conclusion:
Prolonged pulmonary exposure to diesel exhaust particles worsen renal oxidative stress, inflammation and DNA damage in mice with adenine-induced chronic renal failure. Our data provide biological plausibility that air pollution aggravates chronic renal failure.
Missing laboratory data is a common issue, but the optimal method of imputation of missing values has not been determined. The aims of our study were to compare the accuracy of four imputation methods for missing completely at random laboratory data and to compare the effect of the imputed values on the accuracy of two clinical predictive models.
Retrospective cohort analysis of two large data sets.
A tertiary level care institution in Ann Arbor, Michigan.
The Cirrhosis cohort had 446 patients and the Inflammatory Bowel Disease cohort had 395 patients.
Non-missing laboratory data were randomly removed with varying frequencies from two large data sets, and we then compared the ability of four methods-missForest, mean imputation, nearest neighbour imputation and multivariate imputation by chained equations (MICE)-to impute the simulated missing data. We characterised the accuracy of the imputation and the effect of the imputation on predictive ability in two large data sets.
MissForest had the least imputation error for both continuous and categorical variables at each frequency of missingness, and it had the smallest prediction difference when models used imputed laboratory values. In both data sets, MICE had the second least imputation error and prediction difference, followed by the nearest neighbour and mean imputation.
MissForest is a highly accurate method of imputation for missing laboratory data and outperforms other common imputation techniques in terms of imputation error and maintenance of predictive ability with imputed values in two clinical predicative models.
Particulate sulfate is one of the most important components in the atmosphere. The observation of rapid sulfate aerosol production during haze events provoked scientific interest in the multiphase oxidation of SO2 in aqueous aerosol particles. Diverse oxidation pathways can be enhanced or suppressed under different aerosol acidity levels and high ionic strength conditions of atmospheric aerosol. The importance of ionic strength to sulfate multiphase chemistry has been verified under laboratory conditions, though studies in the actual atmosphere are still limited. By utilizing online observations and developing an improved solute strength-dependent chemical thermodynamics and kinetics model (EF-T&K model, EF is the enhancement factor that represents the effect of ionic strength on an aerosol aqueous-phase reaction), we provided quantitative evidence that the H2O2 pathway was enhanced nearly 100 times and dominated sulfate formation for entire years (66%) in Tianjin (a northern city in China). TMI (oxygen catalyzed by transition-metal ions) (14%) and NO2 (14%) pathways got the second-highest contributions. Machine learning supported the result that aerosol sulfate production was more affected by the H2O2 pathway. The collaborative effects of atmospheric oxidants and SO2 on sulfate aerosol production were further investigated using the improved EF-T&K model. Our findings highlight the effectiveness of adopting target oxidant control as a new direction for sustainable mitigation of sulfate, given the already low SO2 concentrations in China.
Rationale & Objective
Increasing evidence has linked ambient fine particulate matter (PM2.5) to chronic kidney disease (CKD) but their association has not been fully elucidated, especially in regions with high levels of PM2.5 pollution. This study aimed to investigate the long-term association of high PM2.5 exposure on incident kidney function in mainland China.
Study Design
Prospective cohort study.
Setting
& Participants: 72,425 participants (≥ 18 years) without CKD were recruited from 121 counties in Hunan Province, China.
Exposure
Annual mean PM2.5 concentration at the residence of each participant derived from a long-term, full-coverage, high-resolution (1×1 km²), and high-quality datasets of ground-level air pollutants in China.
Outcomes
Incident CKD during the interval between the baseline examination of each participant (2Correspondence to: 005-2017) and the end of follow-up before 2018.
Analytical Approach
Cox proportional hazards models were used to estimate the independent association of PM2.5 with incident CKD and the joint association of PM2.5 with temperature or humidity on the development of PM2.5-related CKD. Restricted cubic splines were used to model exposure-response relationships.
Results
Over a median follow-up of 3.79 years (IQR, 2.03-5.48), a total of 2,188 participants with incident CKD were identified. Greater PM2.5 was associated with incident CKD with an adjusted hazard ratio (HR) of 1.70 (95% confidence interval [CI], 1.58-1.85) per 10 μg/m³ increase in long-term exposure. Multiplicative interactions between PM2.5 and humidity or temperature on incident CKD were detected (all P-interaction < 0.001), whereas an additive interaction was only detected for humidity (relative risk due to interaction [RERI], 3.59; 95% CI, 0.97-6.21).
Limitations
Lack of information on participants’ activity patterns such as time spent outdoors.
Conclusions
Greater long-term greater ambient PM2.5 pollution is associated with incident CKD in high PM2.5 exposure environments. Ambient humidity has a potentially synergetic effect on PM2.5’s association with the development of CKD.
Background
Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear.
Methods
A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM1), ≤2.5 μm (PM2.5) or ≤10 μm (PM10), nitrogen dioxide (NO2)) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots.
Results
Exposure to single air pollutant (PM1, PM2.5, PM10 or NO2) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed.
Conclusion
Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect.
Atmospheric oxidation of sulfur dioxide (SO2) forms sulfate-containing aerosol particles that impact air quality, climate, and human and ecosystem health. It is well-known that in-cloud oxidation of SO2 frequently dominates over gas-phase oxidation on regional and global scales. Multiphase oxidation involving aerosol particles, fog, and cloud droplets has been generally thought to scale with liquid water content (LWC) so multiphase oxidation would be negligible for aerosol particles due to their low aerosol LWC. However, recent field evidence, particularly from East Asia, shows that fast sulfate formation prevails in cloud-free environments that are characterized by high aerosol loadings. By assuming that the kinetics of cloud water chemistry prevails for aerosol particles, most atmospheric models do not capture this phenomenon. Therefore, the field of aerosol SO2 multiphase chemistry has blossomed in the past decade, with many oxidation processes proposed to bridge the difference between modeled and observed sulfate mass loadings. This review summarizes recent advances in the fundamental understanding of the aerosol multiphase oxidation of SO2, with a focus on environmental conditions that affect the oxidation rate, experimental challenges, mechanisms and kinetics results for individual reaction pathways, and future research directions. Compared to dilute cloud water conditions, this paper highlights the differences that arise at the molecular level with the extremely high solute strengths present in aerosol particles.
Exposure to fine particulate matter (PM2.5) can significantly harm human health and increase the risk of death. Satellite remote sensing allows for generating spatially continuous PM2.5 data, but current datasets have overall low accuracies with coarse spatial resolutions limited by data sources and models. Air pollution levels in China have experienced dramatic changes over the past couple of decades. However, country-wide ground-based PM2.5 records only date back to 2013. To reveal the spatiotemporal variations of PM2.5, long-term and high-spatial-resolution aerosol optical depths, generated by the Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle implementation of Atmospheric Correction (MAIAC) algorithm, were employed to estimate PM2.5 concentrations at a 1-km resolution using our proposed Space-Time Extra-Trees (STET) model. Our model can capture well variations in PM2.5 concentrations at different spatiotemporal scales, with higher accuracies (i.e., cross-validation coefficient of determination, CV-R2 = 0.86–0.90) and stronger predictive powers (i.e., R2 = 0.80–0.82) than previously reported. The resulting PM2.5 dataset for China (i.e., ChinaHighPM2.5) provides the longest record (2000 to 2018) at a high spatial resolution of 1 km, enabling the study of PM2.5 variation patterns at different scales. In most places, PM2.5 concentrations showed increasing trends around 2007 and remained high until 2013, after which they declined substantially, thanks to a series of government actions combating air pollution in China. While nationwide PM2.5 concentrations have decreased by 0.89 μg/m3/yr (p < 0.001) during the last two decades, the reduction has accelerated to 4.08 μg/m3/yr (p < 0.001) over the last six years, indicating a significant improvement in air quality. Large improvements occurred in the Pearl and Yangtze River Deltas, while the most polluted region remained the North China Plain, especially in winter. The ChinaHighPM2.5 dataset will enable more insightful analyses regarding the causes and attribution of pollution over medium- or small-scale areas.
Background:
Exposure mixtures frequently occur in data across many domains, particularly in the fields of environmental and nutritional epidemiology. Various strategies have arisen to answer questions about exposure mixtures, including methods such as weighted quantile sum (WQS) regression that estimate a joint effect of the mixture components.
Objectives:
We demonstrate a new approach to estimating the joint effects of a mixture: quantile g-computation. This approach combines the inferential simplicity of WQS regression with the flexibility of g-computation, a method of causal effect estimation. We use simulations to examine whether quantile g-computation and WQS regression can accurately and precisely estimate the effects of mixtures in a variety of common scenarios.
Methods:
We examine the bias, confidence interval (CI) coverage, and bias-variance tradeoff of quantile g-computation and WQS regression and how these quantities are impacted by the presence of noncausal exposures, exposure correlation, unmeasured confounding, and nonlinearity of exposure effects.
Results:
Quantile g-computation, unlike WQS regression, allows inference on mixture effects that is unbiased with appropriate CI coverage at sample sizes typically encountered in epidemiologic studies and when the assumptions of WQS regression are not met. Further, WQS regression can magnify bias from unmeasured confounding that might occur if important components of the mixture are omitted from the analysis.
Discussion:
Unlike inferential approaches that examine the effects of individual exposures while holding other exposures constant, methods like quantile g-computation that can estimate the effect of a mixture are essential for understanding the effects of potential public health actions that act on exposure sources. Our approach may serve to help bridge gaps between epidemiologic analysis and interventions such as regulations on industrial emissions or mining processes, dietary changes, or consumer behavioral changes that act on multiple exposures simultaneously. https://doi.org/10.1289/EHP5838.
Background and objectives:
Exposure to particulate matter (PM) <2.5 μm in aerodynamic diameter (PM2.5) has been linked to detrimental health effects. This study aimed to describe the relationship between long-term PM2.5 exposure and kidney disease, including eGFR, level of albuminuria, and incident CKD.
Design, setting, participants, & measurements:
The study included 10,997 participants from the Atherosclerosis Risk in Communities cohort who were followed from 1996-1998 through 2016. Monthly mean PM2.5 concentrations (μg/m3) were estimated at geocoded participant addresses using geographic information system-based, spatiotemporal generalized additive mixed models-including geospatial covariates such as land use-and then averaged over the 12-month period preceding participant examination. Covariate-adjusted, cross-sectional associations of PM2.5, baseline eGFR, and urinary albumin-creatinine ratio (UACR) were estimated using linear regression. PM2.5 and incident CKD (defined as follow-up eGFR <60 ml/min per 1.73 m2 with ≥25% eGFR decline relative to baseline, CKD-related hospitalization or death based on International Classification of Diseases 9/10 codes, or development of ESKD) associations were estimated using Cox proportional hazards regression. Modeling was stratified by study site, and stratum-specific estimates were combined using random-effects meta-analyses.
Results:
Baseline mean participant age was 63 (±6) years and eGFR was 86 (±16) ml/min per 1.73 m2. There was no significant PM2.5-eGFR association at baseline. Each 1-μg/m3 higher annual average PM2.5 was associated with higher UACR after adjusting for demographics, socioeconomic status, and clinical covariates (percentage difference, 6.6%; 95% confidence interval [95% CI], 2.6% to 10.7%). Each 1-μg/m3 higher annual average PM2.5 was associated with a significantly higher risk of incident CKD (hazard ratio, 1.05; 95% CI, 1.01 to 1.10).
Conclusions:
Exposure to higher annual average PM2.5 concentrations was associated with a higher level of albuminuria and higher risk for incident CKD in a community-based cohort.
Background:
The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias.
Methods:
We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 μm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 μm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived.
Results:
On average, an increase of 10 μg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations.
Conclusions:
Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).
The substances associated with PM2.5‐induced inflammatory response were investigated using an elimination method. PM2.5 were heated at temperatures of 120, 250, and 360°C. The results demonstrated microbial substances such as LPS and b‐glucan, and chemicals including BaP, 1,2‐NQ, and 9,10‐PQ were reduced drastically in PM2.5 heated at 120°C. On the other hand, DBA, 7,12‐BAQ, and BaP‐1,6‐Q were not noticeably reduced. Most of these substances had disappeared in PM2.5 heated at 250°C and 360°C. Metals (eg, Fe, Cu, Cr, Ni) in PM2.5 exhibited a slight thermo‐dependent increase. RAW264.7 macrophages with or without NAC were exposed to unheated PM2.5, oxidative stress‐related and unrelated inflammatory responses were induced. PM2.5‐induced lung inflammation in mice is caused mainly by thermo‐sensitive substances (LPS, b‐glucan, BaP, 1,2‐NQ, 9,10‐PQ, etc.). Also, a slight involvement of thermo‐resistant substances (DBA, 7,12‐BAQ, BaP‐1,6‐Q, etc.) and transition metals was observed. The thermal decomposition method could assist to evaluate the PM2.5‐induded lung inflammation.
According to the WHO, about 3 million people die each year due to ambient air pollution. Most of the in vivo studies on the PM2.5 effects have been done on respiratory and cardiovascular tissues. However, little is known about the effects on the tissues involved on xenobiotic removal, such as kidneys. In the present study we assess the harmful effects of sub-chronic exposure to PM2.5 on the kidney, by investigating histologic and serum alterations in healthy and hypertensive rat models. Mean PM2.5 concentrations during exposures were slightly above the daily WHO standard. Exposed animals showed fibrosis, mesangial expansion, decrease glomerular and tubular lumen volumes in kidneys, with an elevated BUN. Hypertensive animals also exhibited much more severe alterations than healthy animals. We conclude that PM2.5 induces minimal or small-scale abnormalities that can be determinant for renal health preservation. Keywords: PM2.5, Hypertension, Elemental composition, Kidney histology, BUN
An increasing number of studies have shown that air pollution containing particulate matter (PM) ≤ 2.5 µm (PM2.5) plays a significant role in the development of metabolic disorder and other chronic diseases. Inflammation and oxidative stress caused by metabolic syndrome are widely determined to be critical factors in the development of nonalcoholic fatty liver disease (NAFLD) pathogenesis. However, there is no direct evidence of this, and the underlying molecular mechanism is still not fully understood. In this study, we investigated the role of inflammation and oxidative stress caused by prolonged PM2.5 exposure in dyslipidemia-associated chronic hepatic injury, and further determined whether an increase in hepatic inflammation and oxidative stress promoted lipid accumulation in the liver, ultimately increasing the risk of NAFLD. Therefore, we studied changes in indicators of metabolic disorder and in symbolic indices of NAFLD. We confirmed increases in insulin resistance, glucose tolerance, peripheral inflammation and dysarteriotony in PM2.5-induced mice. Oxidative stress and inflammatory response in the liver caused by PM2.5 inhalation contributed to abnormal hepatic function, further promoting lipid accumulation in the liver. Moreover, we observed inhibition of oxidative stress and inflammatory response by pyrrolidine dithiocarbamate (PDTC) and N-acetyl-L-cysteine (NAC) in vitro, suggesting that oxidative stress and inflammatory in liver cells aggravated by PM2.5 contributed to hepatic injury by altering normal lipid metabolism. These results indicate a new goal for preventing and treating air pollution–induced diseases: suppression of oxidative stress and inflammatory response.
Background:
China is the world's largest consumer of tobacco and has a large smoking-related chronic disease burden. In this nationwide study, we aimed to evaluate smoking prevalence and its implication on chronic diseases in the Chinese population.
Methods:
We collected data from serial cross-sectional National Health Service Surveys done in China in 2003, 2008, and 2013. These surveys cover all 31 provinces, autonomous regions, and municipalities in mainland China, and use multistage stratified cluster sampling. We divided mainland China into east, central, and west regions and then sampled counties from each region stratified by urban and rural areas. All respondents aged 15 years or older in the selected households were eligible. We analysed the variation in smoking prevalence from 2003 to 2013, further identified risk factors for smoking, and assessed the association between smoking and chronic diseases by using multiple logistic regression.
Findings:
The number of individuals interviewed and involved in the study was 153 450 in 2003, 145 223 in 2008, and 229 676 in 2013. The standardised smoking prevalence in China was consistently high, with a proportion of current smokers of 26·0% (95% CI 25·8-26·2) in 2003, 24·9% (24·8-25·1) in 2008, and 25·2% (25·1-25·4) in 2013 (p value for trend 0·5062). For men, prevalence was 48·4% (48·1-48·7) in 2003, 47·0% (46·6-47·4) in 2008, and 47·2% (46·9-47·5) in 2013. For women, prevalence was 3·1% (3·0-3·2) in 2003, 2·3% (2·2-2·5) in 2008, and 2·7% (2·6-2·8) in 2013. Smoking prevalence varied in different regions, and we identified four major patterns. While a consistently high proportion of Chinese men smoked, the standardised smoking prevalence in women younger than 40 years increased from 1·0% in 2003 to 1·6% in 2013. Moreover, the smoking prevalence among adolescent smokers aged 15-24 years increased from 8·3% in 2003 to 12·5% in 2013. Alcohol consumption was closely linked to smoking in adolescents (odds ratio 7·5, 95% CI 6·9-8·1). Risk factors for adolescent smoking were having older family members who smoke (1·9, 1·8-1·9) and low level education (1·3, 1·2-1·4). Increased risks of chronic diseases were related to smoking (1·1, 1·0-1·1), with higher risks related to early smoking initiation (1·1, 1·0-1·1) and long-term smoking (1·2, 1·2-1·3).
Interpretation:
The implementation of tobacco control policies in China since the signing of the WHO Framework Convention on Tobacco Control in 2003 has not been effective in reducing smoking prevalence. Smoking prevalence among adolescents of both genders has increased substantially and there has been a steady increase among young women. More practical and effective policies targeting adolescents and women are urgently needed. Action is needed to prevent the large and growing smoking-related chronic disease burden further increasing as China's population ages.
Funding:
National Health Commission of the People's Republic of China.
Fine particulate matter <2.5 μm (PM2.5) air pollution is the most important environmental risk factor contributing to global cardiovascular (CV) mortality and disability. Short-term elevations in PM2.5 increase the relative risk of acute CV events by 1% to 3% within a few days. Longer-term exposures over several years increase this risk by a larger magnitude (∼10%), which is partially attributable to the development of cardiometabolic conditions (e.g., hypertension and diabetes mellitus). As such, ambient PM2.5 poses a major threat to global public health. In this review, the authors provide an overview of air pollution and health, including assessment of exposure, impact on CV outcomes, mechanistic underpinnings, and impact of air pollution reduction strategies to mitigate CV risk. The review concludes with future challenges, including the inextricable link between air pollution and climate change, and calls for large-scale trials to allow the promulgation of formal evidence-based recommendations to lower air pollution–induced health risks.
Background
-Although the prevalence of hypertension (HTN) continues to increase in developing countries including China, recent data are lacking. A national wide survey was conducted from October 2012 to December 2015 to assess the prevalence of HTN in China.
Methods
-A stratified multistage random sampling method was used to obtain a nationally representative sample of 451,755 residents aged ≥18 years from 31 provinces in mainland China from October 2012 to December 2015. Blood pressure (BP) was measured after resting for 5 minutes by trained staff, using a validated oscillometric BP monitor. HTN was defined as systolic BP (SBP) ≥140 mmHg and/or /diastolic BP (DBP) ≥90 mmHg and/or use of antihypertensive medication within two weeks. Pre-HTN was defined as SBP 120-139 mmHg and DBP 80-89 mmHg without antihypertensive medication. HTN control was defined as SBP <140 mmHg and DBP<90 mm Hg. In addition, the prevalence of HTN (SBP≥130 or DBP≥80 mmHg) and control rate (SBP<130 and DBP<80 mmHg) of HTN were also estimated according to the 2017 American College of Cardiology (ACC) /American Heart Association (AHA) High Blood Pressure Guideline.
Results
-Overall, 23.2% (estimated 244.5 million) of the Chinese adult population aged ≥18 years had HTN, and another 41.3% (estimated 435.3 million) had pre-HTN according to the Chinese guideline. There were no significant differences of HTN prevalence between urban and rural residents (23.4% vs. 23.1%,P=0.819). Among individuals with HTN, 46.9% were aware of their condition, 40.7% were taking prescribed antihypertensive medications, and 15.3% had controlled HTN. Calcium channel blockers were the most commonly used antihypertensive medication (46.5%) as monotherapy; and 31.7% of treated hypertensive patients used two or more medications. The prevalence of HTN based on the 2017 ACC/AHA guideline was twice as high as that based on 2010 Chinese guideline (46.4%), while the control rate fell to 3.0%.
Conclusions
-In China, there is a high prevalence of HTN and pre-HTN; awareness, treatment and control of HTN were low. Management of medical therapy for HTN needs to improve.
Importance
Previous studies have shown increasing prevalence of diabetes in China, which now has the world’s largest diabetes epidemic.
Objectives
To estimate the recent prevalence and to investigate the ethnic variation of diabetes and prediabetes in the Chinese adult population.
Design, Setting, and Participants
A nationally representative cross-sectional survey in 2013 in mainland China, which consisted of 170 287 participants.
Exposures
Fasting plasma glucose and hemoglobin A1c levels were measured for all participants. A 2-hour oral glucose tolerance test was conducted for all participants without diagnosed diabetes.
Main Outcomes and Measures
Primary outcomes were total diabetes and prediabetes defined according to the 2010 American Diabetes Association criteria. Awareness and treatment were also evaluated. Hemoglobin A1c concentration of less than 7.0% among treated diabetes patients was considered adequate glycemic control. Minority ethnic groups in China with at least 1000 participants (Tibetan, Zhuang, Manchu, Uyghur, and Muslim) were compared with Han participants.
Results
Among the Chinese adult population, the estimated standardized prevalence of total diagnosed and undiagnosed diabetes was 10.9% (95% CI, 10.4%-11.5%); that of diagnosed diabetes, 4.0% (95% CI, 3.6%-4.3%); and that of prediabetes, 35.7% (95% CI, 34.1%-37.4%). Among persons with diabetes, 36.5% (95% CI, 34.3%-38.6%) were aware of their diagnosis and 32.2% (95% CI, 30.1%-34.2%) were treated; 49.2% (95% CI, 46.9%-51.5%) of patients treated had adequate glycemic control. Tibetan and Muslim Chinese had significantly lower crude prevalence of diabetes than Han participants (14.7% [95% CI, 14.6%-14.9%] for Han, 4.3% [95% CI, 3.5%-5.0%] for Tibetan, and 10.6% [95% CI, 9.3%-11.9%] for Muslim; P < .001 for Tibetan and Muslim compared with Han). In the multivariable logistic models, the adjusted odds ratios compared with Han participants were 0.42 (95% CI, 0.35-0.50) for diabetes and 0.77 (95% CI, 0.71-0.84) for prediabetes for Tibetan Chinese and 0.73 (95% CI, 0.63-0.85) for diabetes and 0.78 (95% CI, 0.71-0.86) for prediabetes in Muslim Chinese.
Conclusions and Relevance
Among adults in China, the estimated overall prevalence of diabetes was 10.9%, and that for prediabetes was 35.7%. Differences from previous estimates for 2010 may be due to an alternate method of measuring hemoglobin A1c.
The development of engineered nanomaterials is growing exponentially, despite concerns over their potential similarities to environmental nanoparticles that are associated with significant cardiorespiratory morbidity and mortality. The mechanisms through which inhalation of nanoparticles could trigger acute cardiovascular events are emerging, but a fundamental unanswered question remains: Do inhaled nanoparticles translocate from the lung in man and directly contribute to the pathogenesis of cardiovascular disease? In complementary clinical and experimental studies, we used gold nanoparticles to evaluate particle translocation, permitting detection by high-resolution inductively coupled mass spectrometry and Raman microscopy. Healthy volunteers were exposed to nanoparticles by acute inhalation, followed by repeated sampling of blood and urine. Gold was detected in the blood and urine within 15 min to 24 h after exposure, and was still present 3 months after exposure. Levels were greater following inhalation of 5 nm (primary diameter) particles compared to 30 nm particles. Studies in mice demonstrated the accumulation in the blood and liver following pulmonary exposure to a broader size range of gold nanoparticles (2-200 nm primary diameter), with translocation markedly greater for particles <10 nm diameter. Gold nanoparticles preferentially accumulated in inflammation-rich vascular lesions of fat-fed apolipoproteinE-deficient mice. Furthermore, following inhalation, gold particles could be detected in surgical specimens of carotid artery disease from patients at risk of stroke. Translocation of inhaled nanoparticles into the systemic circulation and accumulation at sites of vascular inflammation provides a direct mechanism that can explain the link between environmental nanoparticles and cardiovascular disease and has major implications for risk management in the use of engineered nanomaterials.
For prevention of obesity in the Chinese population, it is necessary to define the optimal range of healthy weight and the appropriate cut-off points of body mass index (BMI) and waist circumference for Chinese adults. The Working Group on Obesity in China under the support of the International Life Sciences Institute Focal Point in China organized a meta-analysis on the relationship between BMI, waist circumference and risk factors of related chronic diseases (e.g., high diabetes, diabetes mellitus, and lipoprotein disorders). Thirteen population studies in all met the criteria for enrolment, with data of 239 972 adults (20-70 years of age) surveyed in the 1990s. Data on waist circumference was available for 111 411 persons, and data on serum lipids and glucose were available for more than 80 000. The study populations were located in 21 provinces, municipalities and autonomous regions in mainland China as well as in Taiwan. Each enrolled study provided data according to a common protocol and uniform format. The Center for Data Management in the Department of Epidemiology, Fu Wai Hospital, was responsible for the statistical analysis. The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all increased with increasing levels of BMI or waist circumference. A BMI of 24 with best sensitivity and specificity for identification of the risk factors' was recommended as the cut-off point for overweight; a BMI of 28, which may identify the risk factors with specificity around 90%, was recommended as the cut-off point for obesity. A waist circumference over 85 cm for men and over 80 cm for women were recommended as the cut-off points for central obesity. Analysis of a population-attributable risk percentage illustrated that reducing the BMI to the normal range (<24) could prevent 45-50% of the clustering of risk factors. Treatment of obese persons (BMI = 28) with drugs could prevent 15-17% of clustering of risk factors. When waist circumference is controlled at under 85 cm for men and under 80 cm for women, it could prevent 47-58% of clustering of risk factors. Based on these guidelines, a classification of overweight and obesity for Chinese adults is recommended.
The MDRD study equation has many advantages. It is more accurate and precise than the Cockcroft–Gault equation for persons with a GFR less than approximately 90 mL/min per 1.73 m²(34–35). This equation predicts GFR as measured by using an accepted method (urinary clearance of ¹²⁵I-iothalamate). It was developed on a large (n > 1000) database containing persons with various kidney diseases and was tested on a validation database containing more than 500 additional patients. It does not require height or weight and has been validated in kidney transplant recipients and African-Americans with nephrosclerosis (36). Nonetheless, questions remain about the equation's generalizability because it has not been validated in diabetic kidney disease, in patients with serious comorbid conditions, in normal persons, or in persons older than 70 years of age. Clinical conditions in which it may be necessary to measure GFR by using clearance methods include extremes of age and body size, severe malnutrition or obesity, diseases of skeletal muscle, paraplegia or quadriplegia, vegetarian diet, rapidly changing kidney function, and calculation of the dose of potentially toxic drugs that are excreted by the kidneys.
Chronic kidney disease affects approximately 11% of the U.S. adult population (20 million people from 1988 to 1994). The prevalence of earlier stages of disease (10.8%) is more than 100 times greater than the prevalence of kidney failure (0.1%). Adverse outcomes of chronic kidney disease, including loss of kidney function and development of kidney failure and CVD, can often be prevented or delayed through early detection and treatment. In particular, physicians should consider using interventions to slow the progression of kidney disease in all patients with chronic kidney disease and should place patients with chronic kidney disease in the highest-risk group for CVD risk factor reduction and other treatments for CVD. Each patient with chronic kidney disease should have a clinical action plan, based on the stage of disease, as defined by the NKF K/DOQI guidelines. All patients with chronic kidney disease and persons at increased risk for chronic kidney disease should undergo measurement of proteinuria (as a marker of kidney damage) and GFR. Quantitative assessment of proteinuria is useful for detection, differential diagnosis, prognosis, and treatment of chronic kidney disease. The ratio of concentration of albumin to creatinine in untimed urine samples should be used to detect and monitor proteinuria. Glomerular filtration rate, as estimated by prediction equations based on serum creatinine concentration, age, race, sex, and body size, is useful for detecting chronic kidney disease, classifying its severity, estimating progression, managing complications, and deciding on referral to a nephrologist.
Background:
Living near major roadways has been associated with increased risk of cardiovascular events, but little is known about its impact on renal function.
Methods:
We calculated the estimated glomerular filtration rate (eGFR) for 1103 consecutive Boston-area patients hospitalised with confirmed acute ischaemic stroke between 1999 and 2004. We used linear regression to evaluate the association between eGFR and categories of residential distance to major roadway (0 to ≤50, >50 to ≤100, >100 to ≤200, >200 to ≤400, >400 to ≤1000 and >1000 m) adjusting for age, sex, race, smoking, comorbid conditions, treatment with ACE inhibitor and neighbourhood-level socioeconomic characteristics. In a second analysis, we considered the log of distance to major roadway as a continuous variable.
Results:
Patients living closer to a major roadway had lower eGFR than patients living farther away (Ptrend=0.01). Comparing patients living 50 m versus 1000 m from a major roadway was associated with a 3.9 ml/min/1.73 m(2) lower eGFR (95% CI 1.0 to 6.7; p=0.007): a difference comparable in magnitude to the reduction in eGFR observed for a 4-year increase in age in population-based studies. The magnitude of this association did not differ significantly across categories of age, sex, race, history of hypertension, diabetes or socioeconomic status.
Conclusions:
Living near a major roadway is associated with lower eGFR in a cohort of patients presenting with acute ischaemic stroke. If causal, these results imply that exposures associated with living near a major roadway contribute to reduced renal function, an important risk factor for cardiovascular events.
This article reviews flexible statistical methods that are useful for characterizing the effect of potential prognostic factors on disease endpoints. Applications to survival models and binary outcome models are illustrated.
For prevention of obesity in the Chinese population, it is necessary to define the optimal range of healthy weight and the appropriate cut-off points of body mass index (BMI) and waist circumference for Chinese adults. The Working Group on Obesity in China under the support of the International Life Sciences Institute Focal Point in China organized a meta-analysis on the relationship between BMI, waist circumference and risk factors of related chronic diseases (e.g., high diabetes, diabetes mellitus, and lipoprotein disorders). Thirteen population studies in all met the criteria for enrolment, with data of 239 972 adults (20-70 years of age) surveyed in the 1990s. Data on waist circumference was available for 111 411 persons, and data on serum lipids and glucose were available for more than 80 000. The study populations were located in 21 provinces, municipalities and autonomous regions in mainland China as well as in Taiwan. Each enrolled study provided data according to a common protocol and uniform format. The Center for Data Management in the Department of Epidemiology, Fu Wai Hospital, was responsible for the statistical analysis. The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all increased with increasing levels of BMI or waist circumference. A BMI of 24 with best sensitivity and specificity for identification of the risk factors was recommended as the cut-off point for overweight; a BMI of 28, which may identify the risk factors with specificity around 90%, was recommended as the cut-off point for obesity. A waist circumference over 85 cm for men and over 80 cm for women were recommended as the cut-off points for central obesity. Analysis of a population-attributable risk percentage illustrated that reducing the BMI to the normal range (<24) could prevent 45-50% of the clustering of risk factors. Treatment of obese persons (BMI = 28) with drugs could prevent 15-17% of clustering of risk factors. When waist circumference is controlled at under 85 cm for men and under 80 cm for women, it could prevent 47-58% of clustering of risk factors. Based on these guidelines, a classification of overweight and obesity for Chinese adults is recommended.
Chronic kidney disease is a worldwide public health problem with an increasing incidence and prevalence, poor outcomes, and high cost. Outcomes of chronic kidney disease include not only kidney failure but also complications of decreased kidney function and cardiovascular disease. Current evidence suggests that some of these adverse outcomes can be prevented or delayed by early detection and treatment. Unfortunately, chronic kidney disease is underdiagnosed and undertreated, in part as a result of lack of agreement on a definition and classification of its stages of progression. Recent clinical practice guidelines by the National Kidney Foundation 1) define chronic kidney disease and classify its stages, regardless of underlying cause, 2) evaluate laboratory measurements for the clinical assessment of kidney disease, 3) associate the level of kidney function with complications of chronic kidney disease, and 4) stratify the risk for loss of kidney function and development of cardiovascular disease. The guidelines were developed by using an approach based on the procedure outlined by the Agency for Healthcare Research and Quality. This paper presents the definition and five-stage classification system of chronic kidney disease and summarizes the major recommendations on early detection in adults. Recommendations include identifying persons at increased risk (those with diabetes, those with hypertension, those with a family history of chronic kidney disease, those older than 60 years of age, or those with U.S. racial or ethnic minority status), detecting kidney damage by measuring the albumin-creatinine ratio in untimed ("spot") urine specimens, and estimating the glomerular filtration rate from serum creatinine measurements by using prediction equations. Because of the high prevalence of early stages of chronic kidney disease in the general population (approximately 11% of adults), this information is particularly important for general internists and specialists.
End-stage renal disease substantially increases the risks of death, cardiovascular disease, and use of specialized health care, but the effects of less severe kidney dysfunction on these outcomes are less well defined.
We estimated the longitudinal glomerular filtration rate (GFR) among 1,120,295 adults within a large, integrated system of health care delivery in whom serum creatinine had been measured between 1996 and 2000 and who had not undergone dialysis or kidney transplantation. We examined the multivariable association between the estimated GFR and the risks of death, cardiovascular events, and hospitalization.
The median follow-up was 2.84 years, the mean age was 52 years, and 55 percent of the group were women. After adjustment, the risk of death increased as the GFR decreased below 60 ml per minute per 1.73 m2 of body-surface area: the adjusted hazard ratio for death was 1.2 with an estimated GFR of 45 to 59 ml per minute per 1.73 m2 (95 percent confidence interval, 1.1 to 1.2), 1.8 with an estimated GFR of 30 to 44 ml per minute per 1.73 m2 (95 percent confidence interval, 1.7 to 1.9), 3.2 with an estimated GFR of 15 to 29 ml per minute per 1.73 m2 (95 percent confidence interval, 3.1 to 3.4), and 5.9 with an estimated GFR of less than 15 ml per minute per 1.73 m2 (95 percent confidence interval, 5.4 to 6.5). The adjusted hazard ratio for cardiovascular events also increased inversely with the estimated GFR: 1.4 (95 percent confidence interval, 1.4 to 1.5), 2.0 (95 percent confidence interval, 1.9 to 2.1), 2.8 (95 percent confidence interval, 2.6 to 2.9), and 3.4 (95 percent confidence interval, 3.1 to 3.8), respectively. The adjusted risk of hospitalization with a reduced estimated GFR followed a similar pattern.
An independent, graded association was observed between a reduced estimated GFR and the risk of death, cardiovascular events, and hospitalization in a large, community-based population. These findings highlight the clinical and public health importance of chronic renal insufficiency.
The Modification of Diet in Renal Disease (MDRD) equations provide a rapid method of assessing GFR in patients with chronic kidney disease (CKD). However, previous research indicated that modification of these equations is necessary for application in Chinese patients with CKD. The objective of this study was to modify MDRD equations on the basis of the data from the Chinese CKD population and compare the diagnostic performance of the modified MDRD equations with that of the original MDRD equations across CKD stages in a multicenter, cross-sectional study of GFR estimation from plasma creatinine, demographic data, and clinical characteristics. A total of 684 adult patients with CKD, from nine geographic regions of China were selected. A random sample of 454 of these patients were included in the training sample set, and the remaining 230 patients were included in the testing sample set. With the use of the dual plasma sampling (99m)Tc-DTPA plasma clearance method as a reference for GFR measurement, the original MDRD equations were modified by two methods: First, by adding a racial factor for Chinese in the original MDRD equations, and, second, by applying multiple linear regression to the training sample and modifying the coefficient that is associated with each variable in the original MDRD equations and then validating in the testing sample and comparing it with the original MDRD equations. All modified MDRD equations showed significant performance improvement in bias, precision, and accuracy compared with the original MDRD equations, and the percentage of estimated GFR that did not deviate >30% from the reference GFR was >75%. The modified MDRD equations that were based on the Chinese patients with CKD offered significant advantages in different CKD stages and could be applied in clinical practice, at least in Chinese patients with CKD.
Representation of generalized additive models (GAM's) using penalized regression splines allows GAM's to be employed in a straightforward manner using penalized regression methods. Not only is inference facilitated by this approach, but it is also possible to integrate model selection in the form of smoothing parameter selection into model fitting in a computationally efficient manner using well founded criteria such as generalized cross-validation. The current fitting and smoothing parameter selection methods for such models are usually effective, but do not provide the level of numerical stability to which users of linear regression packages, for example, are accustomed. In particular the existing methods cannot deal adequately with numerical rank deficiency of the GAM fitting problem, and it is not straightforward to produce methods that can do so, given that the degree of rank deficiency can be smoothing parameter dependent. In addition, models with the potential flexibility of GAM's can also present practical fitting difficulties as a result of indeterminacy in the model likelihood: Data with many zeros fitted by a model with a log link are a good example. In this article it is proposed that GAM's with a ridge penalty provide a practical solution in such circumstances, and a multiple smoothing parameter selection method suitable for use in the presence of such a penalty is developed. The method is based on the pivoted QR decomposition and the singular value decomposition, so that with or without a ridge penalty it has good error propagation properties and is capable of detecting and coping elegantly with numerical rank deficiency. The method also allows mixtures of user specified and estimated smoothing parameters and the setting of lower bounds on smoothing parameters. In terms of computational efficiency, the method compares well with existing methods. A simulation study compares the method to existing methods, including treating GAM's as mixed models.
A report of the revision committee of Chinese guidelines for prevention and treatment of hypertension
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Ambient particulate air pollution and daily mortality in 652 cities
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