RESUMEN
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Enfermedades Cardiovasculares , Anciano , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Enfermedades Cardiovasculares/inducido químicamente , Enfermedades Cardiovasculares/epidemiología , Femenino , Hospitalización , Hospitales , Humanos , Conceptos Meteorológicos , Material Particulado/análisisRESUMEN
Epidemiological studies found that exposure to air pollution increases cardiovascular hospitalizations. However, studies on rural-urban differences in associations between hospitalizations for cardiovascular diseases and air pollution are limited. The generalized linear model (GLM) was applied to investigate the associations between cardiovascular hospitalizations and air pollution (SO2, NO2, PM2.5, PM10, CO, and O3) in Guangxi, southwest China, in 2015 (January 1-December 31). The relative risk of pollutants (SO2, NO2) on cardiovascular hospital admissions was significantly different between urban and rural areas. The effect of SO2 on cardiovascular hospitalizations was higher in urban areas than in rural areas at lag0 to lag3 and cumulative lag01 to lag03. In urban areas, there were positive associations between NO2 and cardiovascular hospitalizations at lag0, lag1 and cumulative lag01, lag02. In contrast, the effect of NO2 on cardiovascular hospitalizations was not significant in rural areas. Urban residents were more sensitive than rural residents to SO2 and NO2. Subgroup analyses showed statistically significant differences between rural and urban areas in the association between SO2 and NO2 and cardiovascular hospitalizations for males. For age groups, people aged ≥ 65 years appeared to be more vulnerable to SO2 and NO2 in urban areas. The effects of PM2.5 PM10, CO, and O3 on cardiovascular hospitalizations were consistently negative for all groups. Our findings indicated that there were rural-urban differences in associations between cardiovascular hospitalizations and air pollutants. In rural areas, the risk of cardiovascular hospitalizations was mainly influenced by SO2. Therefore, we expect to pay attention to protecting people from air pollution, particularly for those aged ≥ 65 years in urban areas.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China/epidemiología , Hospitalización , Hospitales , Humanos , Masculino , Dióxido de Nitrógeno , Material Particulado/análisisRESUMEN
Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People's Republic of China, including NO2, SO2, and O3. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO2 and SO2 increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO2 was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O3 were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O3 was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO2 and SO2 for CVD, as well as between SO2 and O3. The synergistic effects of NO2 and SO2 on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO2-O3 and NO2-O3. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO2 and SO2 was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Enfermedades Cardiovasculares , Contaminantes Ambientales , Ozono , Anciano , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/estadística & datos numéricos , Enfermedades Cardiovasculares/inducido químicamente , Enfermedades Cardiovasculares/epidemiología , China/epidemiología , Femenino , Hospitalización , Hospitales , Humanos , Masculino , Dióxido de Nitrógeno/análisis , Ozono/análisis , Material Particulado/análisisRESUMEN
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m3 increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO2) and particulate matter (PM2.5) in multiple regions. According to the result of GAM, the adjusted R2 was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO2, SO2 or PM2.5 in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Asma , Adolescente , Adulto , Anciano , Contaminantes Atmosféricos/análisis , Asma/epidemiología , Monóxido de Carbono/análisis , Niño , Preescolar , China/epidemiología , Hospitalización/estadística & datos numéricos , Humanos , Lactante , Persona de Mediana Edad , Dióxido de Nitrógeno/análisis , Material Particulado/análisis , Adulto JovenRESUMEN
BACKGROUND: Asthma is a major public health concern throughout the world. Numerous researches have shown that the spatial-temporal patterns of asthma are inconsistent, leading to the suggestion that these patterns are determined by multiple factors. This study aims to detect spatial-temporal clusters of asthma and analyze socio-ecological factors associated with the asthma hospitalization rate in Guangxi, China. METHODS: Asthma hospitalization and socio-ecological data for 88 counties/municipal districts in Guangxi, China in 2015 was collected. Space-time scan statistics were applied to identify the high-risk periods and areas of asthma hospital admissions. We further used GeoDetector and Spearman correlation coefficient to investigate the socio-ecological factors associated with the asthma hospitalization rates. RESULTS: There were a total of 7804 asthma admissions in 2015. The high-risk period was from April to June. The age groups of 0-4 and ≥65 years were both at the highest risk, with hospital admission rates of 45.0/105 and 46.5/105, respectively. High-risk areas were found in central and western Guangxi with relative risk (RR) values of asthma hospitalizations greater than 2.0. GDP per capita and altitude were positively associated with asthma hospitalizations, while air pressure and wind speed had a negative association. The explanatory powers of these factors (i.e., GDP per capita, altitude, air pressure, wind speed) were 22%, 20%, 14% and 10%, respectively. CONCLUSIONS: The GDP per capita appears to have the strongest correlation with asthma hospitalization rates. High-risk areas were identified in central and western Guangxi characterized by high GDP per capita. These findings may be helpful for authorities developing targeted asthma prevention policies for high-risk areas and vulnerable populations, especially during high-risk periods.
Asunto(s)
Asma , Producto Interno Bruto , Hospitalización , Asma/epidemiología , China/epidemiología , Ecología , Análisis Factorial , Humanos , Factores Socioeconómicos , VientoRESUMEN
Hand-foot-mouth disease (HFMD) is a common infectious disease in children and is particularly severe in Guangxi, China. Meteorological conditions are known to play a pivotal role in the HFMD. Previous studies have reported numerous models to predict the incidence of HFMD. In this study, we proposed a new method for the HFMD prediction using GeoDetector and a Long Short-Term Memory neural network (LSTM). The daily meteorological factors and HFMD records in Guangxi during 2014-2015 were adopted. First, potential risk factors for the occurrence of HFMD were identified based on the GeoDetector. Then, region-specific prediction models were developed in 14 administrative regions of Guangxi, China using an optimized three-layer LSTM model. Prediction results (the R-square ranges from 0.39 to 0.71) showed that the model proposed in this study had a good performance in HFMD predictions. This model could provide support for the prevention and control of HFMD. Moreover, this model could also be extended to the time series prediction of other infectious diseases.
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Enfermedad de Boca, Mano y Pie/diagnóstico , Niño , China/epidemiología , Enfermedad de Boca, Mano y Pie/epidemiología , Humanos , Incidencia , Conceptos Meteorológicos , Redes Neurales de la Computación , Pronóstico , Factores de Riesgo , Análisis Espacio-Temporal , Temperatura , VientoRESUMEN
BACKGROUND: Hand, foot and mouth disease (HFMD) incidence is a critical challenge to disease control and prevention in parts of China, particularly Guangxi. However, the association between socioeconomic factors and meteorological factors on HFMD is still unclear. METHODS: This study applied global and local Moran's I to examine the spatial pattern of HFMD and series analysis to explore the temporal pattern. The effects of meteorological factors and socioeconomic factors on HFMD incidence in Guangxi, China were analyzed using GeoDetector Model. RESULTS: This study collected 45,522 cases from 87 counties in Guangxi during 2015, among which 43,711 cases were children aged 0-4 years. Temporally, there were two HFMD risk peaks in 2015. One peak was in September with 7890 cases. The other appeared in May with 4687 cases of HFMD. A high-risk cluster was located in the valley areas. The tertiary industry, precipitation and second industry had more influence than other risk factors on HFMD incidence with explanatory powers of 0.24, 0.23 and 0.21, respectively. The interactive effect of any two risk factors would enhance the risk of HFMD. CONCLUSIONS: This study suggests that precipitation and tertiary industry factors might have stronger effects on the HFMD incidence in Guangxi, China, compared with other factors. High-risk of HFMD was identified in the valley areas characterized by high temperature and humidity. Local government should pay more attention and strengthen public health services level in this area.
Asunto(s)
Enfermedad de Boca, Mano y Pie/epidemiología , Enfermedad de Boca, Mano y Pie/etiología , Conceptos Meteorológicos , Factores Socioeconómicos , Preescolar , China/epidemiología , Ambiente , Análisis Factorial , Femenino , Calor , Humanos , Humedad , Incidencia , Lactante , Recién Nacido , Masculino , Factores de Riesgo , Análisis Espacio-TemporalRESUMEN
As the second largest economy in the world, China experiences severe particulate matter (PM) pollution in many of its cities. Meteorological factors are critical in determining both areal and temporal variations in PM pollution levels; understanding these factors and their interactions is critical for accurate forecasting, comprehensive analysis, and effective reduction of this pollution. This study analyzed areal and temporal variations in concentrations of PM2.5, PM10, and PMcoarse (PM10 - PM2.5) and PM2.5 to PM10 ratios (PM2.5/PM10) and their relationships with meteorological conditions in 366 Chinese cities from January 1, 2015 to December 31, 2017. On the national scale, PM2.5 and PM10 decreased from 48 to 42⯵g m-³ and from 88 to 84⯵g m-³, respectively, and the annual mean concentrations were 45⯵g m-³ (PM2.5) and 84⯵g m-³ (PM10) during the time period (2015-2017). In most regions, largest PM concentrations occurred in winter. However, in northern China, in spring PMcoarse concentrations were highest due to dust. The PM2.5/PM10 ratio was higher in southern than in northern China. There were large regional disparities in PM diurnal variations. Generally, PM concentrations were negatively correlated with precipitation, relative humidity, air temperature, and wind speed, but were positively correlated with surface pressure. The sunshine duration showed negative and positive impacts on PM in northern and southern cities, respectively. Meteorological factors impacted particulates of different size differently in different regions and over different periods of time.
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Contaminantes Atmosféricos/análisis , Monitoreo del Ambiente/estadística & datos numéricos , Conceptos Meteorológicos , Material Particulado/análisis , China , Ciudades , Polvo/análisis , Tamaño de la Partícula , Estaciones del AñoRESUMEN
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.