ABSTRACT
In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.
ABSTRACT
The novel coronavirus disease 2019 (COVID-19) has been the biggest public health problem of the present world. As the number of people suffering from the pandemic is rising, it is likely to claim more life and worsen the global health and economy. Nepal, one of the developing countries in the south Asia has been strongly influenced by the pandemic and struggling to contain it with multiple interventions, however, spatiotemporal dynamics of the epidemic and its linkage with various intervention strategies has not been studied yet. Here, we employed the prospective spatial-temporal analysis with SaTScan assessing dynamics of the COVID-19 cases from 23 January to 31 August 2020 at district level in Nepal. The results revealed that COVID-19 dynamics in the early stage of transmission was slower and confined in certain districts. However, from the third week of April, transmission spread rapidly across districts of Province No. 2 and Sudoorpaschim Province, primarily introduced by Nepalese citizens returning from India. Despite nationwide lockdown, nine statistically significant active and emerging clusters were detected between 23 January and 21 July 2020, whereas ten emerging clusters were observed for extended period to 31 August. The population density and population inflow from India crossing the sealed border had significant effects on the elevated risk of the epidemic. The capital city Kathmandu has become the highest-risk active cluster since August when travel restriction has been suspended. Movement restriction appears to be the most effective non-pharmaceutical intervention against the COVID-19 for resource-scarce countries with limited health care facilities. Our findings could be valuable to the health authorities within Nepal and beyond to better allocate resources and improve interventions on the pandemic for containing it efficiently.
ABSTRACT
The current explosive outbreak of coronavirus (COVID-19) is posing serious threats to public health and economy around the world. To clarify the coupling mechanism between this disease and economy, a new dynamical system is established. It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determines the stability of the disease-free and endemic equilibria. Further results indicate the existence of interaction and mutual restraint among the transmission, intervention and economy, in which strong coupling of COVID-19 and economy would trigger disease outbreak and form poverty trap, while adaptive isolation of at-risk population could effectively reduce morbidity at the cost of least economic loss. Our findings can offer new insights to improve the intervention strategies against COVID-19.
ABSTRACT
ImportanceA large number of healthcare workers (HCWs) were infected by SARS-CoV-2 during the ongoing outbreak of COVID-19 in Wuhan, China. Hospitals are significant epicenters for the human-to-human transmission of the SARS-CoV-2 for HCWs, patients, and visitors. No data has been reported on the details of hospital environmental contamination status in the epicenter of Wuhan. ObjectiveTo investigate the extent to which SARS-CoV-2 contaminates healthcare settings, including to identify function zones of the hospital with the highest contamination levels and to identify the most contaminated objects, and personal protection equipment (PPE) in Wuhan, China. DesignA field investigation was conducted to collect the surface swabs in various environments in the hospital and a laboratory experiment was conducted to examine the presence of the SARS-CoV-2 RNA. SettingSix hundred twenty-six surface samples were collected within the Zhongnan Medical Center in Wuhan, China in the mist of the COVID-19 outbreak between February 7 - February 27, 2020. ParticipantsDacron swabs were aseptically collected from the surfaces of 13 hospital function zones, five major objects, and three major personal protection equipment (PPE). The SARS-CoV-2 RNAs were detected by reverse transcription-PCR (RT-PCR). Main Outcomes and MeasuresSARS-CoV-2 RNAs ResultsThe most contaminated zones were the intensive care unit specialized for taking care of novel coronavirus pneumonia (NCP) (31.9%), Obstetric Isolation Ward specialized for pregnant women with NCP (28.1%), and Isolation Ward for NCP (19.6%). We classified the 13 zones into four contamination levels. The most contaminated objects are self-service printers (20.0%), desktop/keyboard (16.8%), and doorknob (16.0%). Both hand sanitizer dispensers (20.3%) and gloves (15.4%) were most contaminated PPE. Conclusions and RelevanceMany surfaces were contaminated with SARS-CoV-2 across the hospital in various patient care areas, commonly used objects, medical equipment, and PPE. The 13 hospital function zones were classified into four contamination levels. These findings emphasize the urgent need to ensure adequate environmental cleaning, strengthen infection prevention training, and improve infection prevention precautions among HCWs during the outbreak of COVID-19. The findings may have important implications for modifying and developing urgently needed policy to better protect healthcare workers during this ongoing pandemic of SARS-CoV-2. Key PointsO_ST_ABSQuestionC_ST_ABSWhat was the hospital setting contamination status, the most contaminated objects and PPE of SARS-CoV-2 during the outbreak of COVID-19 in Wuhan, China? FindingsThe most contaminated zones were the intensive care unit for novel coronavirus pneumonia (NCP) (31.9%), Obstetric Isolation Ward specialized for pregnant women with NCP (28.1%), and Isolation Ward for NCP (19.6%). The most contaminated objects and PPE are self-service printers (20.0%), hand sanitizer dispensers (20.3%), and gloves (15.4%). MeaningThe findings may have important implications for modifying and developing urgently needed policy to better protect healthcare workers during this ongoing pandemic of SARS-CoV-2.
ABSTRACT
The outbreak of pneumonia caused by a novel coronavirus (2019-nCoV) in Wuhan City of China obtained global concern, the population outflow from Wuhan has contributed to spatial expansion in other parts of China. We examined the effects of population outflow from Wuhan on the 2019-nCoV transmission in other provinces and cities of China, as well as the impacts of the city closure in Wuhan. We observed a significantly positive association between population movement and the number of cases. Further analysis revealed that if the city closure policy was implemented two days earlier, 1420 (95% CI: 1059, 1833) cases could be prevented, and if two days later, 1462 (95% CI: 1090, 1886) more cases would be possible. Our findings suggest that population movement might be one important trigger of the 2019-nCoV infection transmission in China, and the policy of city closure is effective to prevent the epidemic.
ABSTRACT
Objective@#To examine the association between long-term exposure to ambient PM2.5 combined with indoor air pollution and handgrip strength among people aged 50 and over.@*Methods@#Data were from the first wave of World Health Organization Study on global AGEing and adult health in China. Ambient annual concentration of PM2.5 was estimated by using the satellite data we also investigated the use of fuels and chimneys as indoor air pollution. A two-level (individual level and community level) linear model was applied to examine the association between long-term exposure to ambient PM2.5 combined with indoor air pollution and the handgrip strength.@*Results@#A total of 13 175 individuals aged 50 years and over were included for analysis. The handgrip strength was (26.67±0.54) kg. Ambient PM2.5 was found to be significantly associated with the risk of decreased handgrip strength. Outdoor PM2.5 concentration was negatively correlated with handgrip strength (β=-0.23, 95%CI: -0.31 - -0.14) decrease in handgrip strength after adjusting for gender, age, residence, education, household assets, intake of vegetables and fruits, smoking and drinking, physical activity. In rural area, compared to those who used solid fuel, use of clean fuel increased (β=1.41, 95%CI: 0.36-2.46) handgrip strength. But in urban area, we did not find any statistically significant association between the use of clean fuel and handgrip strength (β=0.19, 95%CI: -0.95-1.32).@*Conclusion@#This study found that long-term exposure to ambient PM2.5 combined with indoor air pollution was significantly associated with low handgrip strength among people aged 50 years and over, this suggested that ambient PM2.5 might serve as one of the risk factors for low physical function seen in the people aged 50 years and over.
ABSTRACT
Objective To estimate the effect of daily diurnal temperature range (DTR) on mortality in different areas in China.Methods A time series study using the data collected from 66 areas in China was conducted,and Meta-analysis was used to analyze the estimates of associations between DTR and daily mortality.Modifying effects of extremely low and high DTR-mortality relationship by season and socioeconomic status (SES) were also evaluated respectively.Cumulative excess risk (CER) was used as an index to evaluate the effects.Results The information about 1 260 913 registered deaths were collected between 1 January 2006 and 31 December 2011,we found the relationship between extreme DTR and mortality was non-linear in all regions and the exposure-response curve was J-shaped.In central and south areas of China,the result indicated the obvious acute effect of extremely high DTR,and the mortality effect in central area (CER=5.1％,95％CI:2.4％-7.9％) was significant higher than that in south area (CER=4.5％,95％CI:1.7％-7.3％).Regarding to the modification of seasons,the cumulative mortality effect of DTR in cold season (CER=5.8％,95％CI:2.5％-9.2％) was higher than that in hot season (CER=3.1％,95％CI:1.1％-5.1％).Generally,deaths among the elderly (≥75 years) were associated more strongly with extremely high DTR.Conclusions The mortality effects of extremely DTR in different areas and seasons showed different characteristics,that in central area and in cold season it was significantly stronger.After modified by season and SES,DTRs were the greatest threat to vulnerable population,especially to the elderly (≥75 years).Therefore,more attention should be paid to vulnerable groups and protection measures should be taken according to the local and seasonal conditions.
ABSTRACT
Objective To estimate the effect of daily diurnal temperature range (DTR) on mortality in different areas in China.Methods A time series study using the data collected from 66 areas in China was conducted,and Meta-analysis was used to analyze the estimates of associations between DTR and daily mortality.Modifying effects of extremely low and high DTR-mortality relationship by season and socioeconomic status (SES) were also evaluated respectively.Cumulative excess risk (CER) was used as an index to evaluate the effects.Results The information about 1 260 913 registered deaths were collected between 1 January 2006 and 31 December 2011,we found the relationship between extreme DTR and mortality was non-linear in all regions and the exposure-response curve was J-shaped.In central and south areas of China,the result indicated the obvious acute effect of extremely high DTR,and the mortality effect in central area (CER=5.1％,95％CI:2.4％-7.9％) was significant higher than that in south area (CER=4.5％,95％CI:1.7％-7.3％).Regarding to the modification of seasons,the cumulative mortality effect of DTR in cold season (CER=5.8％,95％CI:2.5％-9.2％) was higher than that in hot season (CER=3.1％,95％CI:1.1％-5.1％).Generally,deaths among the elderly (≥75 years) were associated more strongly with extremely high DTR.Conclusions The mortality effects of extremely DTR in different areas and seasons showed different characteristics,that in central area and in cold season it was significantly stronger.After modified by season and SES,DTRs were the greatest threat to vulnerable population,especially to the elderly (≥75 years).Therefore,more attention should be paid to vulnerable groups and protection measures should be taken according to the local and seasonal conditions.
ABSTRACT
Objective To evaluate the impacts of air temperature on years of life lost(YLL) among the residents in Guangzhou and Zhuhai,Guangdong province. Methods Daily mortality and meteorology data in Guangzhou and Zhuhai were collected,and distributed lag non-linear model (DLNM)was used to evaluate the cumulative and delayed effects of daily air temperature on YLL of total non-accident mortality. The accumulative effect of air temperature on mortality under the extreme high temperature(0-1 days)and extreme low temperature(0-13 days)situation in Guangzhou and Zhuhai were analyzed respectively. Results The average YLL was 1 928.0 in Guangzhou and 202.5 in Zhuhai. The exposure-response functions seemed to be non-linear. The hot effect seemed to be acute and reached the peak at the same day,while the cold effect reached the peak at 5th days and lasted for about two weeks. Low temperature had stronger gross effect than high temperature had. The cold effect among males was greater than that among females in Guangzhou. The hot/cold effect on YLL was greater in people aged ≥65 years than in people aged <65 years and in people suffering from respiratory disease than in people suffering from cardiovascular disease in both Guangzhou and Zhuhai. Conclusion The effects of high and low temperatures on YLL were obvious,and the impact of low temperature was greater. The elderly and people suffering from respiratory disease or cardiovascular disease are the vulnerable populations.
ABSTRACT
Objective To evaluate the impacts of air temperature on years of life lost(YLL) among the residents in Guangzhou and Zhuhai,Guangdong province. Methods Daily mortality and meteorology data in Guangzhou and Zhuhai were collected,and distributed lag non-linear model (DLNM)was used to evaluate the cumulative and delayed effects of daily air temperature on YLL of total non-accident mortality. The accumulative effect of air temperature on mortality under the extreme high temperature(0-1 days)and extreme low temperature(0-13 days)situation in Guangzhou and Zhuhai were analyzed respectively. Results The average YLL was 1 928.0 in Guangzhou and 202.5 in Zhuhai. The exposure-response functions seemed to be non-linear. The hot effect seemed to be acute and reached the peak at the same day,while the cold effect reached the peak at 5th days and lasted for about two weeks. Low temperature had stronger gross effect than high temperature had. The cold effect among males was greater than that among females in Guangzhou. The hot/cold effect on YLL was greater in people aged ≥65 years than in people aged <65 years and in people suffering from respiratory disease than in people suffering from cardiovascular disease in both Guangzhou and Zhuhai. Conclusion The effects of high and low temperatures on YLL were obvious,and the impact of low temperature was greater. The elderly and people suffering from respiratory disease or cardiovascular disease are the vulnerable populations.
ABSTRACT
<p><b>OBJECTIVE</b>To evaluate the impacts of air temperature on years of life lost (YLL) among the residents in Guangzhou and Zhuhai, Guangdong province.</p><p><b>METHODS</b>Daily mortality and meteorology data in Guangzhou and Zhuhai were collected, and distributed lag non-linear model (DLNM) was used to evaluate the cumulative and delayed effects of daily air temperature on YLL of total non-accident mortality. The accumulative effect of air temperature on mortality under the extreme high temperature (0-1 days) and extreme low temperature (0-13 days) situation in Guangzhou and Zhuhai were analyzed respectively.</p><p><b>RESULTS</b>The average YLL was 1 928.0 in Guangzhou and 202.5 in Zhuhai. The exposure-response functions seemed to be non-linear. The hot effect seemed to be acute and reached the peak at the same day, while the cold effect reached the peak at 5(th) days and lasted for about two weeks. Low temperature had stronger gross effect than high temperature had. The cold effect among males was greater than that among females in Guangzhou. The hot/cold effect on YLL was greater in people aged ≥ 65 years than in people aged < 65 years and in people suffering from respiratory disease than in people suffering from cardiovascular disease in both Guangzhou and Zhuhai.</p><p><b>CONCLUSION</b>The effects of high and low temperatures on YLL were obvious, and the impact of low temperature was greater. The elderly and people suffering from respiratory disease or cardiovascular disease are the vulnerable populations.</p>
Subject(s)
Aged , Female , Humans , Male , Middle Aged , Air , Cardiovascular Diseases , Epidemiology , China , Epidemiology , Extreme Cold , Extreme Heat , Mortality, Premature , Nonlinear Dynamics , Respiratory Tract Diseases , Epidemiology , Time FactorsABSTRACT
<p><b>OBJECTIVE</b>To explore the relationship between temperature and non-accidental mortality in Guangzhou, Changsha and Kunming;to evaluate the temperature-related risk of mortality; and thereby to provide scientific evidence for enacting the policy to tackle climate changes.</p><p><b>METHOD</b>Daily meteorology data and mortality data were collected in 2006-2009 in Guangzhou, Changsha and Kunming. Distributed lag non-linear model (DLNM) was established and applied in a case-crossover design, which controlled the secular trend of time, to estimate the specified effects of temperature on non-accidental mortality at conditions of lag 0-2, lag 0-18 and lag 0-27 days, respectively.</p><p><b>RESULT</b>An obvious seasonal periodicity was found in non-accidental mortality in Guangzhou, Changsha and Kunming during 2006-2009. The mortality number was comparatively high in the winters, and some high temperature days in summer; but was comparatively low in springs and autumn. An L-shaped relationship was found between temperature and mortality in Guangzhou and Kunming and a U-shaped relationship was found in Changsha. When daily mean temperature exceeded 28.2 °C, 24.5°C and 23.2°C, as average temperature increase 1°C, non-accidental mortality increased 4.56% (95%CI:2.74%-6.63%), 5.66% (95%CI:0.22%-12.65%) , -3.94% (95%CI:-32.77%-39.01%) , respectively; when daily mean temperature below 24.8°C, 20.0°C and 17.3°C, as average temperature decrease 1°C, the corresponding increase in non-accidental mortality were 3.28% (95%CI:2.41%-4.10%) (lag 0-18 days), 1.35% (95%CI:0.31%-1.77%) (lag 0-2 days) and 2.42% (95%CI:1.08%-3.27%) (lag 0-27 days) , respectively. The effects of hot weather were acute and short term; while the effects of cold weather had a several days delay, but a longer persistence.</p><p><b>CONCLUSIONS</b>Extreme cold and hot temperature could increase the risk of non-accidental mortality in Guangzhou, Changsha and Kunming. The effects of cold weather had a several days delay, but a longer persistence.</p>
Subject(s)
Humans , China , Epidemiology , Climate Change , Cross-Over Studies , Mortality , Seasons , TemperatureABSTRACT
<p><b>OBJECTIVE</b>To explore the impact of the socio-economic factors on the temperature-mortality association in different cities in southern China.</p><p><b>METHODS</b>Daily mortality registration data, meteorological data and air pollution data of the cities as Changsha and Kunming during 2006-2009, and cities as Guangzhou and Zhuhai during 2006-2010, were collected to explore modifying effects, stratified by age, gender, education and place of death, of socio-economic factors on the association between temperature and mortality, by distributed lag non-linear model. The accumulative effect of temperature-mortality were separately analyzed in each city, under the high temperature (0-3 days) and low temperature (0-20 days) situation. The association between temperature and mortality was evaluated by general linear threshold model. The above process was firstly adopted to analyze the impact in single city and then Meta analysis was applied to analyze the impact in several cities by effect-combine.</p><p><b>RESULTS</b>The relationship between temperature and mortality in the four cities showed nonlinearity. The minimum mortality risk was separately 23.5 °C, 20.5 °C, 25.0 °C and 26.0 °C in Changsha, Kunming, Guangzhou and Zhuhai. The results of effect-combine showed that low-temperature (RR = 1.67, 95%CI:1.54-1.80) has a higher gross effect than high-temperature (RR = 1.11, 95%CI:1.01-1.18) on population. With the age increasing, risk of death increased both under high and low temperature situation, and the effect of low temperature was greater (RR = 1.83, 95%CI:1.65-2.04) for the elderly than it of high temperature (RR = 1.17, 95%CI:1.03-1.33). The mortality risk among females (cold and hot effects(95%CI) were 1.75(1.57-1.97) and 1.11(0.99-1.25), respectively)was higher than it among males (cold and hot effects(95%CI) were 1.59(1.45-1.77) and 1.11(1.03-1.19), respectively). Whereas the mortality risk on higher education population was significantly higher (cold and hot effects (95%CI) were 1.89(1.48-2.45)and 1.34(1.19-1.48), respectively) than it on other educated people.</p><p><b>CONCLUSION</b>Age, gender, educational level and place of death showed modifying effects on the association between temperature and mortality. The elderly, women and highly educated people were vulnerable to the temperature influence on mortality.</p>
Subject(s)
Aged , Female , Humans , Male , Air Pollution , China , Cold Temperature , Hot Temperature , Mortality , Nonlinear Dynamics , Risk , Socioeconomic FactorsABSTRACT
<p><b>OBJECTIVE</b>To understand the situation of biomass fuel use in rural Guangdong, and how it affecting the prevalence of hypertension in adult women.</p><p><b>METHODS</b>Inhabitants aged 18 and above were chosen, using multi-stage stratified cluster sampling method from 13 rural countries in Guangdong province in 2010. Questionnaire survey and blood pressure measurement were conducted. Multilevel logistic regression model was used to study the relationship between biomass fuel use and the prevalence of hypertension at both country and individual levels.</p><p><b>RESULTS</b>Of the 5794 rural families, 2 569 (44.3%) cooked with biomass fuel in the kitchen. 1233 (46.2%) and 1 436 (53.8%) out of the 2669 adult women used biomass fuel and clean energy, respectively. Results from χ² study showed that biomass users presented higher prevalence of hypertension (RR = 1.26, 95% CI: 1.04-1.52), but in multilevel model analysis, the difference was not significant. In addition, using an extractor fan when cooking seemed to have protected factor in decreasing the risk of hypertension among biomass users (RR = 0.61, 95% CI: 0.39-0.98).</p><p><b>CONCLUSION</b>Proportion of the use of biomass fuel was still high among rural families in Guangdong province. Although there was not enough evidence to verify the relationship between the use of biomass fuel and hypertension in adult women. However, concerns about the use of biomass fuel which causing the indoor air pollution, should be raised.</p>
