RESUMEN
Investigations on the chronic health effects of fine particulate matter (PM2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM2.5 levels, we aimed to estimate high-resolution, long-term PM2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R2 of 0.93 at the monthly level. For the time period outside the model training window, prediction R2 values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China.
Asunto(s)
Contaminación del Aire/estadística & datos numéricos , Exposición a Riesgos Ambientales , Mortalidad Prematura/tendencias , Material Particulado/análisis , Adulto , China , Exposición a Riesgos Ambientales/efectos adversos , Exposición a Riesgos Ambientales/estadística & datos numéricos , Monitoreo del Ambiente , Sistemas de Información Geográfica , Humanos , Aprendizaje Automático , Modelos Estadísticos , Análisis Espacio-TemporalRESUMEN
BACKGROUND: The concentration-response relationship between mortality and long-term exposure to fine particulate matter (PM2.5) has not been fully elucidated, especially at high levels of PM2.5 concentrations. OBJECTIVE: We aimed to evaluate chronic effects of ambient PM2.5 exposure on deaths among Chinese adults in high-exposure settings. METHODS: Participants of the Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR) project were included from four prospective cohorts among Chinese adults aged ≥18 years old. The overall follow-up rate of the four cohorts was 93.4% until the recent follow-up survey that ended in 2015. The average of satellite-based PM2.5 concentrations during 2000-2015 at 1-km spatial resolution was assigned to each participant according to individual residence addresses. Based on the pooled analysis of individual data from the four cohorts, a Cox proportional hazards model was used to estimate the hazard ratio (HR) and corresponding 95% confidence intervals (95% CIs) for the association of PM2.5 exposure with mortality after multivariate adjustment. RESULTS: A total of 116,821 participants were eligible in the final analysis. During a mean of 7.7 years of follow-up, 6,395 non-accidental deaths and 2,507 cardio-metabolic deaths occurred. The mean of PM2.5 concentration was 64.9 µg/m3 ranging from 31.2 µg/m3 to 97.0 µg/m3. For each 10 µg/m3 increment in PM2.5, the HR was 1.11 (95% CI: 1.08-1.14) for non-accidental mortality and 1.22 (95% CI: 1.16-1.27) for cardio-metabolic mortality. In addition, a weak exponential curve for the concentration-response association between mortality and PM2.5 was observed among Chinese adults. CONCLUSIONS: Our study provided important evidence of the long-term effects of PM2.5 exposure on deaths among Chinese adults. The findings expand our knowledge on concentration-response relationship in high-exposure environments, which is essential to address the urgent challenge of reducing the disease burden attributable to PM2.5 exposure in rapidly industrializing countries such as China.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Adulto , Contaminantes Atmosféricos/análisis , Contaminación del Aire/efectos adversos , China/epidemiología , Exposición a Riesgos Ambientales/análisis , Humanos , Mortalidad , Material Particulado/análisis , Modelos de Riesgos Proporcionales , Estudios ProspectivosRESUMEN
BACKGROUND: Evidence of the effects of long-term fine particulate matter (PM2.5) exposure on cardiovascular diseases (CVDs) is rare for populations exposed to high levels of PM2.5 in China and in other countries with similarly high levels. OBJECTIVES: The aim of this study was to assess the CVD risks associated with long-term exposure to PM2.5 in China. METHODS: A nationwide cohort study, China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China), was used, with 116,972 adults without CVD in 2000 being included. Participants were followed until 2015. Satellite-based PM2.5 concentrations at 1-km spatial resolution during the study period were used for exposure assessment. A Cox proportional hazards model with time-varying exposures was used to estimate the CVD risks associated with PM2.5 exposure, adjusting for individual risk factors. RESULTS: Annual mean concentrations of PM2.5 at the China-PAR sites ranged from 25.5 to 114.0 µg/m3. For each 10 µg/m3 increase in PM2.5 exposures, the multivariate-adjusted hazard ratio was 1.251 (95% confidence interval: 1.220 to 1.283) for CVD incidence and 1.164 (95% confidence interval: 1.117 to 1.213) for CVD mortality. The slopes of concentration-response functions of PM2.5 exposure and CVD risks were steeper at high PM2.5 levels. In addition, older residents, rural residents, and never smokers were more prone to adverse effects of PM2.5 exposure. CONCLUSIONS: This study provides evidence that elevated long-term PM2.5 exposures lead to increased CVD risk in China. The effects are more pronounced at higher PM2.5 levels. These findings expand the current knowledge on adverse health effects of severe air pollution and highlight the potential cardiovascular benefits of air quality improvement in China and other low- and middle-income countries.
Asunto(s)
Enfermedades Cardiovasculares/mortalidad , Material Particulado/efectos adversos , Adulto , Enfermedades Cardiovasculares/etiología , China/epidemiología , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Material Particulado/administración & dosificación , Factores de TiempoRESUMEN
BACKGROUND: Diabetes caused substantial economic and health burden worldwide. However, the associations between air pollution and diabetes incidence were rarely reported in the developing countries, especially in China with relatively high PM2.5 concentrations. OBJECTIVES: A cohort-based study was conducted to assess the diabetes incidence associated with long-term exposure to ambient PM2.5. METHODS: We collected individual health data and risk factors from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR Project) from 15 provinces over China. Diabetes was defined as fasting glucose levels ≥7.0â¯mmol/L at the follow-ups and/or the use of insulin or oral hypoglycemic agents and/or diagnosed medical history of diabetes during 2004 to 2015. Individual-level PM2.5 exposures were estimated from satellite-based PM2.5 concentrations (10â¯km spatial resolution) during the study period. Cox proportional hazards models with random intercepts of each cohort and region were employed to estimate the diabetes incidence attributable to PM2.5, after the adjustment for age, gender, body mass index, smoking status, education, work-related physical activity level, hypertension, urbanicity, county-level averaged years of education, and long-term levels of temperature and relative humidity. RESULTS: A total of 88,397 subjects were analyzed with 580,928 person-years of follow-up after 2004, among which 6439 new cases of diabetes were observed. The mean age of the subjects was 51.7â¯years at baseline. For an increase of 10⯵g/m3 in long-term PM2.5 exposure, the multivariable-adjusted percent increase in the diabetes incidence was estimated to be 15.66% (95% confidence interval: 6.42%, 25.70%). The adverse effects of PM2.5 were larger among females, rural subjects, non-smokers, normotensives, subjects younger than 65â¯years and subjects with body mass index <25â¯kg/m2. CONCLUSIONS: Our findings provided evidence for the association of long-term exposure to PM2.5 with diabetes incidence in China. A sustained improvement of air quality will benefit the reduction for diabetes epidemic in China.
Asunto(s)
Contaminantes Atmosféricos/análisis , Diabetes Mellitus/epidemiología , Exposición a Riesgos Ambientales/análisis , Material Particulado/análisis , Adulto , China/epidemiología , Estudios de Cohortes , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Factores de RiesgoRESUMEN
BACKGROUND: Most evidences regarding ambient PM2.5 or PM10 (particulate matter of median aerodynamic diameter ≤2.5⯵m or ≤10⯵m) and preterm birth (PTB) come from western countries which has relatively low PM pollution exposure, and the results are still inconsistent. This study aims to examine whether exposure to high concentrations of PM2.5 or PM10 was associated with PTB (<37â¯weeks) and near term birth (37-38â¯weeks). METHOD: We established a birth cohort with 1,280,524 singleton pregnancies who delivered from Dec 1st, 2013 to Nov 30th, 2014 and matched their home address to PM2.5 and PM10 concentrations which were predicted with machine learning methods based satellite remote sensing, meteorological and land use information. Cox proportional hazard regression models were used to analyze the associations between PTB and exposure of PM2.5 or PM10, after controlling for individual level covariates. RESULTS: Exposure to PM2.5 or PM10 during pregnancy increases the risk of PTB and near term birth [e.g., Hazard ratios: 1.09 (95% CI: 1.09, 1.10), 1.08 (95% CI: 1.07, 1.08), 1.01 (95% CI: 1.01, 1.02), and 1.09 (95% CI: 1.08, 1.10) for each 10⯵g/m3 increase in PM2.5 for the 1st, 2nd, 3rd trimester and over the entire pregnancy, respectively]. The effects appeared to be stronger among women who come from rural areas, worked as farmers, were overweight before conception, whose mate was smoking during pregnancy, and conceived in autumn. CONCLUSION: This study provides clear evidence that exposure to PM2.5 or PM10 during pregnancy increases the risk of PTB and near term birth. Public policies regarding improvement of air quality would produce great health benefit by reducing the burden of preterm birth.
Asunto(s)
Contaminantes Atmosféricos/toxicidad , Material Particulado/toxicidad , Nacimiento Prematuro/inducido químicamente , Adulto , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Estudios de Cohortes , Femenino , Humanos , Recién Nacido , Masculino , Material Particulado/análisis , Embarazo , Tercer Trimestre del Embarazo , Medición de RiesgoRESUMEN
Severe and persistent haze accompanied by high concentrations of fine particulate matter (PM2.5) has become a great public health concern in urban China. However, research on the health effects of PM2.5 in China has been hindered by the lack of high-quality exposure estimates. In this study, we assessed the excess mortality associated with both short- and long-term exposure to ambient PM2.5 simultaneously using satellite-derived exposure data at a high spatiotemporal resolution. Adult registries of non-accidental, respiratory and cardiovascular deaths in urban Beijing in 2013 were collected. Exposure levels were estimated from daily satellite-based PM2.5 concentrations at 1â¯km spatial resolution from 2004 to 2013. Mixed Poisson regression models were fitted to estimate the cause-specific mortality in association with PM2.5 exposures. With the mutual adjustment of short- and long-term exposure of PM2.5, the percent increases associated with every 10⯵g/m3 increase in short-term PM2.5 exposure were 0.09% (95% CI: -0.14%, 0.33%; lag 01), 1.02% (95% CI: 0.08%, 1.97%; lag 04) and 0.09% (95% CI: -0.23%, 0.42%; lag 01) for non-accidental, respiratory and cardiovascular mortality, respectively; those attributable to every 10⯵g/m3 increase in long-term PM2.5 exposure (9-year moving average) were 16.78% (95% CI: 10.58%, 23.33%), 44.14% (95% CI: 20.73%, 72.10%) and 3.72% (95% CI: -3.75%, 11.77%), respectively. Both associations of short- and long-term exposure with the cause-specific mortality decreased after they were mutually adjusted. Associations between short-term exposure to satellite-based PM2.5 and cause-specific mortality were larger than those estimated using fixed measurements. Satellite-based PM2.5 predictions help to improve the spatiotemporal resolution of exposure assessments and the mutual adjustment model provide better estimation of PM2.5 associated health effects. Effects attributable to long-term exposure of PM2.5 were larger than those of short-term exposure, which should be more concerned for public health.
Asunto(s)
Contaminantes Atmosféricos/análisis , Contaminación del Aire/estadística & datos numéricos , Exposición a Riesgos Ambientales/estadística & datos numéricos , Mortalidad/tendencias , Material Particulado/análisis , Imágenes Satelitales , Adulto , Beijing/epidemiología , China , Humanos , Salud PúblicaRESUMEN
BACKGROUND: Few studies have estimated effects of maternal PM2.5 exposure on birth outcomes in China due to the lack of historical air pollution data. OBJECTIVES: We estimated the associations between maternal PM2.5 exposure and birth outcomes using gap-filled satellite estimates in Shanghai, China. METHODS: We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. PM2.5 exposures were assessed from satellite-derived estimates or central-site measurements. Linear and logistic regressions were used to estimate associations with term birth weight and term low birth weight (LBW), respectively. Logistic and discrete-time survival models were used to estimate associations with preterm birth. Effect modification by maternal age and parental education levels was investigated. RESULTS: A 10⯵g/m3 increase in gap-filled satellite-based whole-pregnancy PM2.5 exposure was associated with a -12.85â¯g (95% CI: -18.44, -7.27) change in term birth weight, increased risk of preterm birth (OR 1.27, 95% CI: 1.20, 1.36), and increased risk of term LBW (OR 1.22, 95% CI: 1.06, 1.41). Sensitivity analyses during 2013-2014, when ground PM2.5 measurements were available, showed that the health associations using gap-filled satellite PM2.5 concentrations were higher than those obtained using satellite PM2.5 concentrations without accounting for missingness. The health associations using gap-filled satellite PM2.5 had similar magnitudes to those using central-site measurements, but with narrower confidence intervals. CONCLUSIONS: The magnitude of associations between maternal PM2.5 exposure and adverse birth outcomes in Shanghai was higher than previous findings. One reason could be reduced exposure error of the gap-filled high-resolution satellite PM2.5 estimates.
Asunto(s)
Contaminantes Atmosféricos , Exposición Materna/estadística & datos numéricos , Material Particulado , Resultado del Embarazo/epidemiología , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/toxicidad , China/epidemiología , Femenino , Humanos , Material Particulado/análisis , Material Particulado/toxicidad , EmbarazoRESUMEN
Exposures to particulate matter with diameter of 2.5µm or less (PM2.5) may influence risk of birth defects. We estimated associations between maternal exposure to prenatal traffic-related air pollution and risk of cardiac, orofacial, and neural tube defects among Massachusetts births conceived 2001 through 2008. Our analyses included 2729 cardiac, 255 neural tube, and 729 orofacial defects. We used satellite remote sensing, meteorological and land use data to assess PM2.5 and traffic-related exposures (distance to roads and traffic density) at geocoded birth addresses. We calculated adjusted odds ratios (OR) and confidence intervals (CI) using logistic regression models. Generalized additive models were used to assess spatial patterns of birth defect risk. There were positive but non-significant associations for a 10µg/m(3) increase in PM2.5 and perimembranous ventricular septal defects (OR=1.34, 95% CI: 0.98, 1.83), patent foramen ovale (OR=1.19, 95% CI: 0.92, 1.54) and patent ductus arteriosus (OR=1.20, 95% CI: 0.95, 1.62). There was a non-significant inverse association between PM2.5 and cleft lip with or without palate (OR=0.76, 95% CI: 0.50, 1.10), cleft palate only (OR=0.89, 95% CI: 0.54, 1.46) and neural tube defects (OR=0.77, 95% CI: 0.46, 1.05). Results for traffic related exposure were similar. Only ostium secundum atrial septal defects displayed significant spatial variation after accounting for known risk factors.