RESUMEN
Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 µg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.
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Contaminantes Atmosféricos , Contaminación del Aire , Demencia , Humanos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/efectos adversos , Contaminación del Aire/análisis , China , Estudios Cruzados , Exposición a Riesgos Ambientales/efectos adversos , Exposición a Riesgos Ambientales/análisis , Material Particulado/efectos adversos , Material Particulado/análisis , Anciano , Anciano de 80 o más AñosRESUMEN
The associations of hand, foot, and mouth disease (HFMD) with meteorological variables and particulate matter (PM) remain controversial, and limited evidence is available on heat index (HI) and coarse particulate (PM10-2.5). Moreover, temperature and humidity are considered major risk factors but their interaction with PM remains unclear. We combined the distributed lag non-linear and quasi-Poisson models to estimate the non-linear and lagged associations of meteorological variables and PM with HFMD based on reported HFMD during 2015-2019 in Fuzhou, China. The multiplicative term of interaction was used to explore the relationship between HFMD and meteorological variables or PM at different levels of another variable. Stratified analyses were used to identify vulnerable subpopulations. We observed inverted-V-shaped relationships between HFMD and temperature and HI, and the W- and N-shaped for relative humidity (RH) and PM, respectively. Extreme high (i.e., the 95th percentile) temperature, HI and RH increased the HFMD with relative risks (RR) of 4.00 (95% confidence interval, 2.79-5.75), 2.20 (1.71-2.83) and 1.54 (1.35-1.75) referent to the minimum effect value of 10.3 °C, 69.4 and 54.8%, respectively. Higher concentrations of PM rapidly increased the HFMD. Infants under 2 years suffered more from temperature, HI and PM. There were synergistic effects between meteorological variables and PM on HFMD. For instance, the RRs of temperature (30 °C) and RH (40%) on HFMD increased from 3.68 (2.24-6.06) to 6.44 (4.29-9.66) and from 0.45 (0.14-1.47) to 2.15 (0.90-5.12) at low (<25%) and high (>75%) categories of PM2.5, respectively. While the RRs of 70 µg/m3 of PM10 and PM10-2.5 increased from 0.65 (0.32-1.31) to 2.93 (1.63-5.26) and from 0.86 (0.23-3.21) to 3.26 (1.23-8.62) at low and high categories of HI. These findings are essential for the development a prediction and warning systems and prevention and control strategies for HFMD.
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Enfermedad de Boca, Mano y Pie , Material Particulado , Lactante , Niño , Humanos , Material Particulado/análisis , Temperatura , Calor , Enfermedad de Boca, Mano y Pie/epidemiología , Humedad , Incidencia , Factores de Riesgo , China/epidemiología , Conceptos MeteorológicosRESUMEN
Introduction: With China's rapid industrialization and urbanization, China has been increasing its carbon productivity annually. Understanding the association between carbon productivity, socioeconomics, and medical resources with cardiovascular diseases (CVDs) may help reduce CVDs burden. However, relevant studies are limited. Objectives: The study aimed to describe the temporal and spatial distribution pattern of CVDs hospitalization in southeast rural China and to explore its influencing factors. Methods: In this study, 1,925,129 hospitalization records of rural residents in southeast China with CVDs were analyzed from the New Rural Cooperative Medical Scheme (NRCMS). The spatial distribution patterns were explored using Global Moran's I and Local Indicators of Spatial Association (LISA). The relationships with influencing factors were detected using both a geographically and temporally weighted regression model (GTWR) and multiscale geographically weighted regression (MGWR). Results: In southeast China, rural inpatients with CVDs increased by 95.29% from 2010 to 2016. The main groups affected were elderly and women, with essential hypertension (26.06%), cerebral infarction (17.97%), and chronic ischemic heart disease (13.81%) being the leading CVD subtypes. The results of LISA shows that central and midwestern counties, including Meilie, Sanyuan, Mingxi, Jiangle, and Shaxian, showed a high-high cluster pattern of CVDs hospitalization rates. Negative associations were observed between CVDs hospitalization rates and carbon productivity, and positive associations with per capita GDP and hospital beds in most counties (p < 0.05). The association between CVDs hospitalization rates and carbon productivity and per capita GDP was stronger in central and midwestern counties, while the relationship with hospital bed resources was stronger in northern counties. Conclusion: Rural hospitalizations for CVDs have increased dramatically, with spatial heterogeneity observed in hospitalization rates. Negative associations were found with carbon productivity, and positive associations with socioeconomic status and medical resources. Based on our findings, we recommend low-carbon development, use of carbon productivity as an environmental health metric, and rational allocation of medical resources in rural China.
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Enfermedades Cardiovasculares , Isquemia Miocárdica , Humanos , Femenino , Anciano , Enfermedades Cardiovasculares/epidemiología , Factores Socioeconómicos , Hospitalización , Análisis Espacio-TemporalRESUMEN
Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010-2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reï¬ection of the burden associated with AT. The heat effect appeared at lag 0-1 days, with 19% (95% CI, 11-26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0-28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents' per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.
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Enfermedades Cardiovasculares , Enfermedades Cardiovasculares/epidemiología , China/epidemiología , Hospitalización , Calor , Humanos , TemperaturaRESUMEN
Purpose: Chronic obstructive pulmonary disease (COPD) is a major cause of chronic diseases causing considerable social and economic burden globally. Despite substantial evidence on temperature-COPD association, few studies have investigated the acute effect of temperature variability (TV), a potential trigger of exacerbation of COPD disease, and it remains unknown what fraction of the disease burden of COPD is attributable to TV. Patients and Methods: Based on 71,070 COPD hospitalizations during 2013-2015 in Guangzhou, China, we conducted a time-series analysis using quasi-Poisson regression to assess the association between TV and hospital admission for COPD after adjusting for daily mean temperature. Short-term TV was captured by the standard deviation of hourly or daily temperatures across various exposure days. We also provided the fraction (total number) of COPD attributable to TV. Stratified analyses by admission route, sex, age, occupation, marital status and season were performed to identify vulnerable subpopulations. Results: We found a linear relationship between TV and COPD hospitalization, with a 1°C increase in hourly TV and daily TV associated with 4.3% (95%CI: 2.2-6.4) and 4.0% (2.3-5.8) increases in COPD, respectively. The greater relative risks of TV identified males, people aged 0-64 years, blue collar, and divorced/widowed people as vulnerable population. There were 12.0% (8500 cases) of COPD hospitalization attributable to hourly TV during the study period. Daily TV produced similar estimates of relative effects (relative risk) but grater estimates of absolute effects (attributable fraction) than hourly TV. Conclusion: We concluded that TV was an independent risk factor of COPD morbidity, especially among the susceptible subgroups. These findings would be helpful to guide the development of targeted public intervention.
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Costo de Enfermedad , Enfermedad Pulmonar Obstructiva Crónica , Temperatura , Adolescente , Adulto , Niño , Preescolar , China/epidemiología , Exposición a Riesgos Ambientales/análisis , Femenino , Hospitalización , Hospitales , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico , Enfermedad Pulmonar Obstructiva Crónica/epidemiología , Enfermedad Pulmonar Obstructiva Crónica/terapia , Estaciones del Año , Poblaciones Vulnerables , Adulto JovenRESUMEN
BACKGROUND: Individualized prediction of mortality risk can inform the treatment strategy for patients with COVID-19 and solid tumors and potentially improve patient outcomes. We aimed to develop a nomogram for predicting in-hospital mortality of patients with COVID-19 with solid tumors. METHODS: We enrolled patients with COVID-19 with solid tumors admitted to 32 hospitals in China between December 17, 2020, and March 18, 2020. A multivariate logistic regression model was constructed via stepwise regression analysis, and a nomogram was subsequently developed based on the fitted multivariate logistic regression model. Discrimination and calibration of the nomogram were evaluated by estimating the area under the receiver operator characteristic curve (AUC) for the model and by bootstrap resampling, a Hosmer-Lemeshow test, and visual inspection of the calibration curve. RESULTS: There were 216 patients with COVID-19 with solid tumors included in the present study, of whom 37 (17%) died and the other 179 all recovered from COVID-19 and were discharged. The median age of the enrolled patients was 63.0 years and 113 (52.3%) were men. Multivariate logistic regression revealed that increasing age (OR=1.08, 95% CI 1.00 to 1.16), receipt of antitumor treatment within 3 months before COVID-19 (OR=28.65, 95% CI 3.54 to 231.97), peripheral white blood cell (WBC) count ≥6.93 ×109/L (OR=14.52, 95% CI 2.45 to 86.14), derived neutrophil-to-lymphocyte ratio (dNLR; neutrophil count/(WBC count minus neutrophil count)) ≥4.19 (OR=18.99, 95% CI 3.58 to 100.65), and dyspnea on admission (OR=20.38, 95% CI 3.55 to 117.02) were associated with elevated mortality risk. The performance of the established nomogram was satisfactory, with an AUC of 0.953 (95% CI 0.908 to 0.997) for the model, non-significant findings on the Hosmer-Lemeshow test, and rough agreement between predicted and observed probabilities as suggested in calibration curves. The sensitivity and specificity of the model were 86.4% and 92.5%. CONCLUSION: Increasing age, receipt of antitumor treatment within 3 months before COVID-19 diagnosis, elevated WBC count and dNLR, and having dyspnea on admission were independent risk factors for mortality among patients with COVID-19 and solid tumors. The nomogram based on these factors accurately predicted mortality risk for individual patients.
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Infecciones por Coronavirus/mortalidad , Mortalidad Hospitalaria , Neoplasias/terapia , Nomogramas , Neumonía Viral/mortalidad , Factores de Edad , Anciano , Área Bajo la Curva , Betacoronavirus , COVID-19 , China/epidemiología , Estudios de Cohortes , Infecciones por Coronavirus/sangre , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/fisiopatología , Disnea/fisiopatología , Fatiga/fisiopatología , Femenino , Frecuencia Cardíaca , Humanos , Recuento de Leucocitos , Modelos Logísticos , Neoplasias Pulmonares/complicaciones , Neoplasias Pulmonares/terapia , Recuento de Linfocitos , Masculino , Persona de Mediana Edad , Análisis Multivariante , Estadificación de Neoplasias , Neoplasias/complicaciones , Neoplasias/patología , Neutrófilos , Pandemias , Neumonía Viral/sangre , Neumonía Viral/complicaciones , Neumonía Viral/fisiopatología , Enfermedad Pulmonar Obstructiva Crónica/complicaciones , Curva ROC , Estudios Retrospectivos , Medición de Riesgo , SARS-CoV-2RESUMEN
Some researches have shown the associations between air pollution and hospital-based emergency department visits, while the evidence about the acute effects of air pollution on emergency ambulance dispatches for the whole population is rarely available, especially on an hourly time scale. This paper aimed to investigate the effects of hourly concentrations of ambient air pollution on hourly number of ambulance emergency call-outs (AECOs) in Shenzhen, China. AECO data were collected from Shenzhen Emergency Center from January 2013 to December 2016. A time-stratified case-crossover design with conditional Poisson regression was performed to fit the relationship between hourly air pollution and AECOs. The distributed lag model was applied to determine lag structure of the effects of air pollutants. There were a total of 502,862 AECOs during the study period. The significant detrimental effects of SO2, PM2.5, and PM10 appeared immediately with a following harvesting effect after 5 h and the effects lasted for about 96 h. The cumulative effect estimates of four pollutants over 0-96 h were 13.99% (95% CI 7.52-20.85%), 2.07% (95% CI 0.72-3.43%), 1.20% (95% CI 0.54-1.87%), and 2.46% (95% CI 1.63-3.29%), respectively. We did not observe significant effects of O3. This population-based study quantifies the adverse effects of air pollution on ambulance dispatches and provides evidence of the lag structure of the effects on an hourly time scale.
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Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ambulancias , China , Servicio de Urgencia en Hospital , Material Particulado/análisisRESUMEN
BACKGROUND: Although road traffic casualty (RTC) is preventable, it remains the eighth leading cause of death globally, especially in developing countries. Previous studies suggested the association between RTC and monthly or daily weather conditions, while the acute effects of weather conditions on an hourly timescale remains unknown. This study aims to quantify hourly effects of precipitation and temperature on RTC. METHODS: Using ambulance records on RTC during 2010-2016 for the whole population in Shenzhen, China, we conducted a time-stratified case-crossover design which can inherently control for hour of the day, day of the week, seasonality, time trends and potential time-invariant confounders. Conditional quasi-Poisson regression with distributed lag nonlinear model was used to determine the effects of hourly precipitation and temperature on RTC. RESULTS: Light and heavy precipitation increased RTC in current and following 2 h by 8.09% (95% CI: 4.20-12.12%) and 11.62% (95% CI: 5.93-17.62%), respectively. A J-shaped temperature-RTC curve revealed that each 1 °C increment above 17 °C were associated with a 0.87% (0.52-1.22%) increase in RTC. High temperature accounted for 6.44% (95% CI: 3.95-8.91%) of all RTC, with a high fraction of 10.64% (95% CI: 4.33-15.96%) during warm season and 8.30% (95% CI: 4.26-12.66%) in traffic peak hours. Precipitation contributed to 0.68% (95% CI: 0.44-0.92%) of RTC within 3 h. The middle-aged and female suffered more from precipitation-associated RTC, and the younger suffered more from high temperature-associated RTC. CONCLUSIONS: High temperature increased substantially hourly RTC. Precipitation was also a risk factor of RTC and the adverse effect lasted for 3 h. The findings would be helpful to guide the development of targeted intervention to accelerate progress in road traffic safety.
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Tiempo (Meteorología) , Accidentes de Tránsito , China , Estudios Cruzados , Femenino , Humanos , Persona de Mediana Edad , Estaciones del Año , TemperaturaRESUMEN
BACKGROUND: Longer ambulance response time (ART) delaying treatment would worsen conditions of seriously ill or injured patients, but limited evidence is available on the effects of weather factors on ART. This study aims to assess precipitation- and temperature-ART associations and their potential lagged effects using a novel modeling strategy. METHODS: Based on 779,156 emergency records during 2010-2016 from the whole population in Shenzhen, China, we creatively combined quantile regression with distributed-lag nonlinear models to examine the non-linear and lagged effects of hourly precipitation and temperature on ART at the 50th and 90th percentiles. RESULTS: A linear precipitation-ART association with a delay of 9.01 (95%CI, 7.82-10.20) seconds at median ART for a 1 mm increase in hourly precipitation, and the effects lasted for 5 h with the greatest effect at the current hour. A two linear thresholds temperature-ART association revealed 1 °C decrease below 19 °C caused 1.68 (95%CI, 0.92-2.44) seconds delay in total ART over lag 0-7 h, and 1 °C increase above 24 °C caused 2.44 (95%CI, 1.55-3.33) seconds delay. The hourly call volumes exceeding 54 calls caused 8.79 (95%CI, 8.71-8.86) seconds delay in total ART for 1 more call, but not affected the effects of weather factors. The internal ART suffered more from the hourly call volumes, while the external ART suffered more from precipitation and temperature. The effects were apparently greater on ART at the 90th percentile than median. CONCLUSIONS: Precipitation and temperature are independent risk factors for ambulance services performance, and their lagged effects are notable. The external ART and patients with long ART are vulnerable. More attention should be paid to weather and ART, and these findings may have implications for effective policies to reduce ART to protect public health.
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Ambulancias , Lluvia , China , Humanos , Tiempo de Reacción , Estaciones del Año , TemperaturaRESUMEN
BACKGROUND: People are exposed to mixtures of highly correlated gaseous, liquid and solid pollutants. However, in previous studies, the assessment of air pollution effects was mainly based on single-pollutant models or was simultaneously included as multiple pollutants in a model. It is essential to develop appropriate methods to accurately estimate the health effects of multiple pollutants in the presence of a high correlation between pollutants. METHODS: The flexible tensor product smooths of multiple pollutants was applied for the first time in a quasi-Poisson model to estimate the health effects of SO2, NO2 and PM10 on daily all-cause deaths during 2005-2012 in Guangzhou, China. The results were compared with those from three other conventional models, including the single-pollutant model and the three-pollutant model with and without first-order interactions. RESULTS: The tensor product model revealed a complex interaction among three pollutants and significant combined effects of PM10, NO2 and SO2, which revealed a 2.53% (95%CI: 1.03-4.01%) increase in mortality associated with an interquartile-range (IQR) increase in the concentrations of all three pollutants. The combined effect estimated by the single-pollutant model was 5.63% (95% CI: 3.96-7.34%). Although the conventional three-pollutant models produced combined effect estimates (2.20, 95%CI, 1.18-3.23%; 2.78, 95%CI: 1.35-4.23%) similar to those of the tensor product model, they distorted the estimates and inflated the variances of the estimates when attributing the combined health effects to individual pollutants. CONCLUSIONS: The single-pollutant model or conventional multi-pollutant model may yield misleading results in the presence of collinearity. The tensor product quasi-Poisson regression provides a novel approach to the assessment of the health impacts of multiple pollutants by flexibly fitting the interaction effects and avoiding the collinearity problem.
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Contaminantes Atmosféricos/toxicidad , Modelos Teóricos , Anciano , Femenino , Humanos , Masculino , Mortalidad , Dióxido de Nitrógeno/toxicidad , Material Particulado/toxicidad , Análisis de Regresión , Medición de Riesgo , Dióxido de Azufre/toxicidadRESUMEN
The associations between meteorological factors and mortality have been well documented worldwide, but limited evidence is available for the non-fatal health impacts of ambient temperature, particularly there are few population-based investigations on the impacts of emergency ambulance dispatches in Asia. In this study, based on 809,906 ambulance emergency call-outs (AECOs) for the total population from 2010-2016 in the subtropical city of Shenzhen, China, a Poisson regression combined with a distributed lag nonlinear model was used to simultaneously assess the nonlinear and lag effects of daily mean temperature on AECOs. Stratified analyses by age and sex were performed to identify vulnerable subpopulations. A U-shaped relationship was found between temperature and AECOs. Cold effects were delayed and persisted for 3-4 weeks, with a cumulative relative risk (RR) and 95% confidence interval (CI) of 1.23 (1.10-1.38) and 1.25 (1.16-1.35) over lag 0-28 when comparing the 1st and 5th percentile of the temperature distribution to the optimal (i.e. minimum AECOs) temperature, respectively. Hot effects were immediate and diminished quickly in 5 days, with an increase of 19% (RR = 1.19, 95%CI: 1.14-1.23) and 21% (RR = 1.21, 95%CI: 1.16-1.26) in AECOs over lag 0-5 when comparing the 95th and 99th percentile of temperature to the optimal temperature. Children and the elderly were more vulnerable to cold effects. The youth and middle-aged people suffered more from high temperature. The effects of temperature were similar between males and females. In summary, significant increases were observed in the frequency of AECOs during cold and hot days, and the weather-associated increases in AECOs are different among age groups. This information has valuable implications in ambulance demand prediction and service provision planning.