2.Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China.
Yizhang XIA ; Chunli SHI ; Yang LI ; Shijuan RUAN ; Xianyan JIANG ; Wei HUANG ; Yu CHEN ; Xufang GAO ; Rong XUE ; Mingjiang LI ; Hongying SUN ; Xiaojuan PENG ; Renqiang XIANG ; Jianyu CHEN ; Li ZHANG
Environmental Health and Preventive Medicine 2024;29():1-1
BACKGROUND:
There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden.
METHODS:
Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status.
RESULTS:
A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status.
CONCLUSIONS
Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.
Female
;
Humans
;
China/epidemiology*
;
Cities
;
Cold Temperature
;
Hot Temperature
;
Mortality
;
Temperature
;
Time Factors
;
Middle Aged
;
Male
5.Moving Epidemic Method for Surveillance and Early Warning of Hand, Foot, and Mouth Disease in Beijing, China.
Shuai Bing DONG ; Yu WANG ; Da HUO ; Hao ZHAO ; Bai Wei LIU ; Ren Qing LI ; Zhi Yong GAO ; Xiao Li WANG ; Dai Tao ZHANG ; Quan Yi WANG ; Lei JIA ; Peng YANG
Biomedical and Environmental Sciences 2023;36(12):1162-1166
6.Study on the relationship between indexes of different abnormal weight and dyslipidemia in adults in Beijing City.
Ai Juan MA ; Zhong DONG ; Kun QI ; Bo JIANG ; Chen XIE
Chinese Journal of Preventive Medicine 2023;57(3):400-405
Objective: To analyze the relationship and consistency between indexes of different abnormal weight and dyslipidemia in adults in Beijing City. Methods: From August to December of 2017, 4 975 residents aged 18 to 79 years old in 5 districts of Beijing were randomly selected as subjects by using a multi-stage stratified cluster sampling method. Questionnaire, physical examination and laboratory tests were conducted. The prevalence of overweight/obesity, high body fat rate, central obesity, and high waist-to-height ratio was calculated. Partial correlation was used to analyze the correlation of blood lipid with body mass index (BMI), body fat rate, waist circumference and waist-height ratio. Logistic regression analysis for complex sampling was used to analyze the relationship between indexes of different abnormal weight and dyslipidemia after controlling for relevant risk factors, including age, sex, smoking status, drinking, insufficiency intake of vegetable and fruit, physical inactivity. Kappa value was computed to analyze the consistency between indexes of different abnormal weight. Results: The weighted prevalence of dyslipidemia was 30.48%, and it was higher in men than that in women (40.16% vs. 20.52%, P<0.01). The weighted rate of overweight/obesity, high body fat rate, central obesity, and high waist-to-height ratio was 56.65%, 47.52%, 42.48% and 59.45%, respectively. BMI, body fat rate, waist circumference and waist-to-height ratio were positively correlated with the level of total cholesterol, triglyceride, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol, and negatively correlated with high-density lipoprotein cholesterol. Logistic regression analysis for complex sampling showed that the high body fat rate (OR=1.67, 95%CI: 1.35-2.07), overweight/obesity (OR=1.65, 95%CI: 1.26-2.14) and high waist-to-height ratio (OR=1.46, 95%CI: 1.09-1.96) were associated with dyslipidemias. Kappa values of high body fat rate with overweight/obesity, high waist-to-height ratio and central obesity were 0.65, 0.53 and 0.58, respectively (P<0.05). Conclusion: In 2017, the prevalence of dyslipidemia in adults in Beijing City is high, especially in men. Overweight/obesity, high body fat rate and high waist-to-height ratio are associated with dyslipidemia. The high body fat rate is most associated with dyslipidemia.
Male
;
Adult
;
Humans
;
Female
;
Adolescent
;
Young Adult
;
Middle Aged
;
Aged
;
Overweight/complications*
;
Obesity, Abdominal/epidemiology*
;
Beijing
;
Obesity/complications*
;
Body Mass Index
;
Risk Factors
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Cholesterol
;
Dyslipidemias/epidemiology*
;
Waist Circumference
7.Analysis of the epidemiological characteristics of scarlet fever in Yantai City, Shandong Province from 2015 to 2019.
Chang Lan YU ; Xiu Wei LIU ; Xiao Dong MU ; Xing Jie PAN
Chinese Journal of Preventive Medicine 2023;57(3):411-415
From 2015 to 2019, the annual average incidence rate of scarlet fever was 7.80/100 000 in Yantai City, which showed an increasing trend since 2017 (χ2trend=233.59, P<0.001). The peak period of this disease was from April to July and November to January of the next year. The ratio of male to female was 1.49∶1, with a higher prevalence among cases aged 3 to 9 years (2 357/2 552, 92.36%). Children in kindergartens, primary and middle school students, and scattered children were the high risk population, with the incidence rate of 159.86/100 000, 25.57/100 000 and 26.77/100 000, respectively. The global spatial auto-correlation analysis showed that the global Moran's I index of the reported incidence rate of scarlet fever in Yantai from 2015 to 2019 was 0.28, 0.29, 0.44, 0.48, and 0.22, respectively (all P values<0.05), suggesting that the incidence rate of scarlet fever in Yantai from 2015 to 2019 was spatial clustering. The local spatial auto-correlation analysis showed that the "high-high" clustering areas were mainly located in Laizhou City, Zhifu District, Haiyang City, Fushan District and Kaifa District, while the "low-high" clustering areas were mainly located in Haiyang City and Fushan District.
Child
;
Humans
;
Male
;
Female
;
Scarlet Fever/epidemiology*
;
Spatial Analysis
;
Cities/epidemiology*
;
Seasons
;
Risk Factors
;
Incidence
;
Cluster Analysis
;
China/epidemiology*
8.Analysis on infection sources and transmission chains of three outbreaks caused by 2019-nCoV Omicron variant in Beijing, China.
Shuang Sheng WU ; Ying SUN ; Xiang Feng DOU ; Zhen Yong REN ; Jiao Jiao ZHANG ; Lei JIA ; Peng YANG ; Xing Huo PANG
Chinese Journal of Epidemiology 2023;44(3):373-378
Objective: To investigate the infection sources and the transmission chains of three outbreaks caused by 2019-nCoV Omicron variant possibly spread through cross-border logistics in Beijing. Methods: Epidemiological investigation and big data were used to identify the exposure points of the cases. Close contacts were traced from the exposure points, and the cases' and environmental samples were collected for nucleic acid tests. Positive samples were analyzed by gene sequencing. Results: The Omicron variant causing 3 outbreaks in Beijing from January to April, 2022 belonged to BA.1, BA.1.1 and BA.2. The outbreaks lasted for 8, 12 and 8 days respectively, and 6, 42 and 32 cases infected with 2019-nCoV were reported respectively. International mail might be the infection source for 1 outbreak, and imported clothes might be the infection sources for another 2 outbreaks. The interval between the shipment start time of the imported goods and the infection time of the index case was 3-4 days. The mean incubation period (Q1, Q3) was 3 (2,4) days and the mean serial interval (Q1, Q3) was 3 (2,4)days. Conclusions: The 3 outbreaks highlighted the risk of infection by Omicron variant from international logistics-related imported goods at normal temperature. Omicron variant has stronger transmissibility, indicating that rapid epidemiological investigation and strict management are needed.
Humans
;
Beijing
;
SARS-CoV-2
;
COVID-19
;
Disease Outbreaks
;
China/epidemiology*
9.Assessment of intensity of seasonal influenza activity in Beijing-Tianjin-Hebei region, 2019-2021.
Shuo HUANG ; Sheng Hong LIN ; Cui Hong ZHANG ; Meng Jie GENG ; Fan LIN ; Yu Qing GUO ; Yuan DENG ; Jian Dong ZHENG ; Li Ping WANG
Chinese Journal of Epidemiology 2023;44(3):438-444
Objective: To explore the feasibility of moving epidemic method (MEM) in the assessment of seasonal influenza (influenza) activity intensity from the perspective of urban agglomeration, assess influenza activity intensity in the Beijing-Tianjin-Hebei region from 2019 to 2021 and evaluate the reliability of surveillance data and the effectiveness of the MEM model application. Methods: The weekly reported incidence rate (IR) of influenza and the percentage of influenza-like illness (ILI%) from 2011-2021 in Beijing-Tianjin-Hebei region were collected to establish MEM models respectively. The model fitting effect and the reliability of the two data were evaluated for the purpose of establishing an optimal model to assess the influenza activity intensity in Beijing-Tianjin-Hebei region from 2019-2021. A cross-validation procedure was used to evaluate the performance of the models by calculating the Youden's index, sensitivity and specificity. Results: The MEM model fitted with weekly ILI% had a higher Youden's index compared with the model fitted with weekly IR at both Beijing-Tianjin-Hebei region level and provincial level. The MEM model based on ILI% showed that the epidemic threshold in Beijing-Tianjin-Hebei region during 2019-2020 was 4.42%, the post-epidemic threshold was 4.66%, with medium, high and very high intensity thresholds as 5.38%, 7.22% and 7.84%, respectively. The influenza season during 2019-2020 had 10 weeks (week 50 of 2019 to week 7 of 2020). The influenza season started in week 50 of 2019, and the intensity fluctuated above and below medium epidemic level for six consecutive weeks. The high intensity was observed in week 4 of 2020, the threshold of very high intensity was excessed in week 5, and the intensity gradually declined and became lower than the threshold at the end of the influenza season in week 8. The epidemic threshold was 4.29% and the post-epidemic threshold was 4.35% during 2020-2021. Influenza activity level never excessed the epidemic threshold throughout the year, and no epidemic period emerged. Conclusions: The MEM model could be applied in the assessment of influenza activity intensity in Beijing-Tianjin-Hebei region, and the use of ILI% to assess influenza activity intensity in this region was more reliable than IR data. Influenza activity intensity in Beijing-Tianjin-Hebei region was higher during 2019-2020 but significantly lower in 2020-2021.
Humans
;
Beijing/epidemiology*
;
Influenza, Human/epidemiology*
;
Seasons
;
Reproducibility of Results
;
Epidemics
;
China/epidemiology*
10.Residents' sense of acquisition and influencing factors in China's Sanitary City Initiative.
Wen Jing ZHENG ; Hong Yan YAO ; Shi Cheng YU ; Jian Jun LIU ; Yue Hua HU ; Jing Jing WANG
Chinese Journal of Epidemiology 2023;44(3):457-462
Objective: To analyze the residents' sense of acquisition (recognition, perceptibility and satisfaction) and influencing factors in China's Sanitary City Initiative. Methods: A cross-sectional survey was conducted from December 2020 to February 2021. The data about the residents' sense of acquisition were collected by using questionnaire from 2 465 residents who were aged ≥18 years and had lived in local communities for at least one year in 31, 14 and 16 cities with national sanitary city title in eastern, central and western China the influencing factors of residents' sense of acquisition in China's Sanitary City Initiative were analyzed by using multivariate multilevel model. Results: The total score of residents' sense of acquisition in China's Sanitary City Initiative was 231.15±32.45. After converting the scores according to the 100-score standardized method, the results showed that the recognition score, perception score and the satisfaction score were 85.02, 59.08 and 61.42, respectively. The results of influencing factors analysis showed that education level, gender, marital status, age, prevalence of physical exercise and self-assessment of health status were correlated with the scores of residents' recognition (β:1.24-2.54,all P<0.05); the concentration of inhalable fine particles , the green coverage of built-up area, the level of GDP per capita and the type of residential community, prevalence of physical exercise and self-assessment of health status were correlated with the score of residents' perception (β:1.76-8.86,all P<0.05); the concentration of inhalable fine particles , the green coverage of built-up area, the level of GDP per capita and the type of residential community, education level, prevalence of physical exercise and self-assessment of health status were correlated with the score of residents' satisfaction (β:1.34-6.26,all P<0.05). Conclusions: The total score of residents' sense of acquisition in China's Sanitary City Initiative was relatively high, indicating that the policy has been widely recognized. The detailed management of policy implementation should be strengthened in the future, and more attention needs to be paid to actual needs of the residents to further improve the residents' sense of acquisition in China's Sanitary City Initiative.
Humans
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Adolescent
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Adult
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Cities
;
Cross-Sectional Studies
;
China/epidemiology*
;
Health Status
;
Exercise


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