Objective This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning(COP)in Guangdong,China,from 2013 to 2020.Methods Data on...Objective This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning(COP)in Guangdong,China,from 2013 to 2020.Methods Data on age-and sex-specific numbers of hospital admissions due to COP in Guangdong(2013-2020)were collected.Daily temperatures were downloaded through the China Meteorological Data Sharing Service System.We analyzed temporal trends through time series decomposition and used spatial autocorrelation analysis to detect spatial clustering.The distributed lag nonlinear model was used to quantify the effects of temperature.Results There were 48,854 COP admissions over the study period.The sex ratio(male to female)was1:1.74.The concentration ratios(M)ranged from 0.73-0.82.The highest risk occurred in January(season index=3.59).Most cases were concentrated in the northern mountainous areas of Guangdong with high-high clustering.COP in the study region showed significant spatial autocorrelation,and the global Moran’s I value of average annual hospital admission rates for COP was 0.447(P<0.05).Low temperatures were associated with high hospital admission rates for COP,with a lag lasting 7 days.With a lag of 0 days,the effects of low temperatures[5th(12℃)]on COP were 2.24-3.81,as compared with the reference temperature[median(24℃)].Conclusion COP in Guangdong province showed significant temporal and spatial heterogeneity.Low temperature was associated with a high risk of COP,and the influence had a lag lasting 7 days.展开更多
Objective To explore the association between soil selenium levels and the risk of diabetes in Chinese adults aged 35–74 years.Methods Data for this study were derived from the China Chronic Diseases and Behavioral Ri...Objective To explore the association between soil selenium levels and the risk of diabetes in Chinese adults aged 35–74 years.Methods Data for this study were derived from the China Chronic Diseases and Behavioral Risk Factors Surveillance 2010 survey.Selenium concentrations in soil were obtained from the Atlas of Soil Environmental Background Values in China.A two-level binary logistic regression model was used to determine the association between soil selenium concentrations and the risk of diabetes,with participants nested within districts/counties.Results A total of 69,332 participants aged 35–74 years,from 158 districts/counties were included in the analysis.Concentrations of selenium in soil varied greatly across the 158 districts/counties,with a median concentration of 0.219 mg/kg(IQR:0.185–0.248).The results showed that both Quartile 1(0.119–0.185 mg/kg)and Quartile 4(0.249–0.344 mg/kg)groups were positively associated with diabetes compared to a soil selenium concentration of 0.186–0.219 mg/kg(Quartile 2),crude odds ratios(ORs)(95%CI)were 1.227(1.003–1.502)and 1.280(1.048–1.563).The P values were 0.045 and 0.013,for Quartile 1 and Quartile 4 groups,respectively.After adjusting for all confounding factors of interest,the Quartile 1 group became non-significant,and the Quartile 4 group had an adjusted OR(95%CI)of 1.203(1.018–1.421)relative to the reference group(Quartile 2),the P values was 0.030.No significant results were seen for the Quartile 3 group(0.220–0.248 mg/kg)compared to the reference group.Conclusion Excessive selenium concentrations in soil could increase the risk of diabetes among Chinese adults aged 35–74 years.展开更多
Objective We aimed to investigate and interpret the associations between socioeconomic factors and the prevalence, awareness, treatment, and control of hypertension at the provincial level in China.Methods A nationall...Objective We aimed to investigate and interpret the associations between socioeconomic factors and the prevalence, awareness, treatment, and control of hypertension at the provincial level in China.Methods A nationally and provincially representative sample of 179,059 adults from the China Chronic Disease and Nutrition Surveillance study in 2015–2016 was used to estimate hypertension burden. The spatial Durbin error model was fitted to investigate socioeconomic factors associated with hypertension indicators.Results Overall, it was estimated that 29.20% of the participants were hypertensive nationwide,among whom, 34.32% were aware of their condition, 27.69% had received antihypertensive treatment,and 7.81% had controlled their condition. Per capita gross domestic product(GDP) was associated with hypertension prevalence(coefficient:-2.95, 95% CI:-5.46,-0.45) and control(coefficient: 6.35, 95% CI:1.36, 11.34) among adjacent provinces and was also associated with awareness(coefficient: 2.93, 95%CI: 1.12, 4.74) and treatment(coefficient: 2.67, 95% CI: 1.21, 4.14) in local province. Beds of internal medicine(coefficient: 2.66, 95% CI: 1.08, 4.23) was associated with control in local province. Old dependency ratio(coefficient:-3.58, 95% CI:-5.35,-1.81) was associated with treatment among adjacent provinces and with control(coefficient:-1.69, 95% CI:-2.42,-0.96) in local province.Conclusion Hypertension indicators were not only directly influenced by socioeconomic factors of local area but also indirectly affected by characteristics of geographical neighbors. Population-level strategies should involve optimizing supportive socioeconomic environment by integrating clinical care and public health services to decrease hypertension burden.展开更多
基金supported by National Institute for Occupational Health and Poison Control,Chinese Center for Disease Control and Prevention Chemical Poisoning Treatment base and Health Emergency Team Operation[131031109000160007]
文摘Objective This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning(COP)in Guangdong,China,from 2013 to 2020.Methods Data on age-and sex-specific numbers of hospital admissions due to COP in Guangdong(2013-2020)were collected.Daily temperatures were downloaded through the China Meteorological Data Sharing Service System.We analyzed temporal trends through time series decomposition and used spatial autocorrelation analysis to detect spatial clustering.The distributed lag nonlinear model was used to quantify the effects of temperature.Results There were 48,854 COP admissions over the study period.The sex ratio(male to female)was1:1.74.The concentration ratios(M)ranged from 0.73-0.82.The highest risk occurred in January(season index=3.59).Most cases were concentrated in the northern mountainous areas of Guangdong with high-high clustering.COP in the study region showed significant spatial autocorrelation,and the global Moran’s I value of average annual hospital admission rates for COP was 0.447(P<0.05).Low temperatures were associated with high hospital admission rates for COP,with a lag lasting 7 days.With a lag of 0 days,the effects of low temperatures[5th(12℃)]on COP were 2.24-3.81,as compared with the reference temperature[median(24℃)].Conclusion COP in Guangdong province showed significant temporal and spatial heterogeneity.Low temperature was associated with a high risk of COP,and the influence had a lag lasting 7 days.
基金National Key Research and Development Programme[2018YFC1315305]China CDC’s Scientific Research Project[JY18-2-22]China CDC’s Public Health and Emergency Response Mechanism Programme[131031001000150001]。
文摘Objective To explore the association between soil selenium levels and the risk of diabetes in Chinese adults aged 35–74 years.Methods Data for this study were derived from the China Chronic Diseases and Behavioral Risk Factors Surveillance 2010 survey.Selenium concentrations in soil were obtained from the Atlas of Soil Environmental Background Values in China.A two-level binary logistic regression model was used to determine the association between soil selenium concentrations and the risk of diabetes,with participants nested within districts/counties.Results A total of 69,332 participants aged 35–74 years,from 158 districts/counties were included in the analysis.Concentrations of selenium in soil varied greatly across the 158 districts/counties,with a median concentration of 0.219 mg/kg(IQR:0.185–0.248).The results showed that both Quartile 1(0.119–0.185 mg/kg)and Quartile 4(0.249–0.344 mg/kg)groups were positively associated with diabetes compared to a soil selenium concentration of 0.186–0.219 mg/kg(Quartile 2),crude odds ratios(ORs)(95%CI)were 1.227(1.003–1.502)and 1.280(1.048–1.563).The P values were 0.045 and 0.013,for Quartile 1 and Quartile 4 groups,respectively.After adjusting for all confounding factors of interest,the Quartile 1 group became non-significant,and the Quartile 4 group had an adjusted OR(95%CI)of 1.203(1.018–1.421)relative to the reference group(Quartile 2),the P values was 0.030.No significant results were seen for the Quartile 3 group(0.220–0.248 mg/kg)compared to the reference group.Conclusion Excessive selenium concentrations in soil could increase the risk of diabetes among Chinese adults aged 35–74 years.
基金supported by National Key Research&Development Program of Ministry of Science and Technology of People’s Republic of China[2018YFC1311703,2018YFC1311706]。
文摘Objective We aimed to investigate and interpret the associations between socioeconomic factors and the prevalence, awareness, treatment, and control of hypertension at the provincial level in China.Methods A nationally and provincially representative sample of 179,059 adults from the China Chronic Disease and Nutrition Surveillance study in 2015–2016 was used to estimate hypertension burden. The spatial Durbin error model was fitted to investigate socioeconomic factors associated with hypertension indicators.Results Overall, it was estimated that 29.20% of the participants were hypertensive nationwide,among whom, 34.32% were aware of their condition, 27.69% had received antihypertensive treatment,and 7.81% had controlled their condition. Per capita gross domestic product(GDP) was associated with hypertension prevalence(coefficient:-2.95, 95% CI:-5.46,-0.45) and control(coefficient: 6.35, 95% CI:1.36, 11.34) among adjacent provinces and was also associated with awareness(coefficient: 2.93, 95%CI: 1.12, 4.74) and treatment(coefficient: 2.67, 95% CI: 1.21, 4.14) in local province. Beds of internal medicine(coefficient: 2.66, 95% CI: 1.08, 4.23) was associated with control in local province. Old dependency ratio(coefficient:-3.58, 95% CI:-5.35,-1.81) was associated with treatment among adjacent provinces and with control(coefficient:-1.69, 95% CI:-2.42,-0.96) in local province.Conclusion Hypertension indicators were not only directly influenced by socioeconomic factors of local area but also indirectly affected by characteristics of geographical neighbors. Population-level strategies should involve optimizing supportive socioeconomic environment by integrating clinical care and public health services to decrease hypertension burden.
