In this study, the data of pediatric diarrhea clinic of Gansu Provincial Maternal and Child Health Hospital from January 1, 2014 to December 31, 2018 and Tianshui First Hospital from January 1, 2015 to December 31, 2018 were collected. Standardized precipitation index (SPI) and meteorological drought composite index (MCI) were used as drought indicators. Quasi-Poisson generalized additive model was used to analyze the correlation between drought and pediatric diarrhea outpatient visits. During the study period, the dry days in Lanzhou city and Tianshui city were 298 and 379 days according to SPI-1, 303 and 398 days according to MCI, respectively. There were 57 147 and 18 703 cases of diarrhea in children aged 0-6 years in Gansu Provincial Maternal and Child Health Hospital and Tianshui First Hospital, respectively. MCI and SPI (SPI-1) based on monthly precipitation were negatively correlated with the number of pediatric diarrhea outpatients. Compared with the non-drought period, SPI-1 showed the strongest correlation between middle drought and pediatric diarrhea outpatients, with an increase of 13.4% (95%CI: 7.9%-19.3%) and 20.0% (95%CI: 12.7%-27.8%) in Lanzhou city and Tianshui city, respectively. According to MCI, the outpatients with diarrhea in Tianshui children increased by 60.5% (95%CI: 3.4%-149.0%) due to extreme drought.
Child ; Humans ; Outpatients ; Diarrhea/epidemiology* ; Cities ; China/epidemiology*

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19), human mobility restriction measures have raised controversies, partly because of the inconsistent findings. An empirical study is promptly needed to reliably assess the causal effects of the mobility restriction. The purpose of this study was to quantify the causal effects of human mobility restriction on the spread of COVID-19. METHODS: Our study applied the difference-in-difference (DID) model to assess the declines of population mobility at the city level, and used the log-log regression model to examine the effects of population mobility declines on the disease spread measured by cumulative or new cases of COVID-19 over time after adjusting for confounders. RESULTS: The DID model showed that a continual expansion of the relative declines over time in 2020. After 4 weeks, population mobility declined by -54.81% (interquartile range, -65.50% to -43.56%). The accrued population mobility declines were associated with the significant reduction of cumulative COVID-19 cases throughout 6 weeks (ie, 1% decline of population mobility was associated with 0.72% [95% CI: 0.50%-0.93%] reduction of cumulative cases for 1 week, 1.42% 2 weeks, 1.69% 3 weeks, 1.72% 4 weeks, 1.64% 5 weeks, and 1.52% 6 weeks). The impact on the weekly new cases seemed greater in the first 4 weeks but faded thereafter. The effects on cumulative cases differed by cities of different population sizes, with greater effects seen in larger cities. CONCLUSIONS Persistent population mobility restrictions are well deserved. Implementation of mobility restrictions in major cities with large population sizes may be even more important.
COVID-19 ; China/epidemiology* ; Cities ; Humans ; SARS-CoV-2

OBJECTIVE: To analyze the distribution characteristics of emerging and reemerging Oncomelania hupensis snails after the criteria for transmission control of schistosomiasis were achieved in China, so as to provide insights into assessment of schistosomiasis transmission risk and formulation of snail control strategies during the elimination phase. METHODS: O. hupensis survey data in China from 2015 to 2021 were collected from the National Schistosomiasis Pevention and Control Information Management System, and the distribution characteristics of emerging and reemerging O. hupensis snails were descriptively analyzed. RESULTS: Emerging and reemerging O. hupensis snails were identified in China each year from 2015 to 2021, with relatively larger areas with emerging and reemerging O. hupensis snail habitats in 2016 and 2021, and relatively higher numbers of counties (districts) where emerging and reemerging O. hupensis snails were detected in 2016 and 2021. A total of 4 586.30 hm² of emerging O. hupensis snail habitats were found in 10 schistosomiasis-endemic provinces of China (except Fujian and Yunnan Provinces) from 2015 to 2021, with 96.80% in Anhui, Hunan and Hubei provinces, where marshland and lake endemic foci were predominant. A total of 21 023.90 hm² of reemerging O. hupensis snail habitats were found in 12 schistosomiasis-endemic provinces of China from 2015 to 2021, with 97.67% in six provinces of Hubei, Sichuan, Jiangxi, Jiangsu, Yunnan and Anhui, where marshland and lake and hilly endemic regions were predominant. Emerging snail habitats were found in 15.08% of all schistosomiasisendemic counties (districts) in China from 2015 to 2021, and 78.75% of all emerging snail habitats were identified in 11 schistosomiasis-endemic counties (districts), with the largest area of emerging snail habitats found in Lixian County, Hunan Province (645.00 hm²). Reemerging snail habitats were found in 47.67% of all schistosomiasis-endemic counties (districts) in China from 2015 to 2021, and 43.29% of all reemerging snail habitats were identified in 11 schistosomiasis-endemic counties (districts), with the largest area of reemerging snail habitats found in Weishan Li and Hui Autonomous County of Hunan Province (1 579.70 hm²). CONCLUSIONS Emerging and reemerging O. hupensis snails were identified in China each year from 2015 to 2021, with much larger areas of reemerging snail habitats than emerging snail habitats, and larger numbers of schistosomiasis-endemic provinces and counties (districts) with reemerging snails were found that those of provinces and counties (districts) with emerging snails. Specific snail control interventions are required tailored to the causes of emerging and reemerging snail habitats. Both emergence and reemergence of O. hupensis snails should be paid attention to in marshland and lake endemic areas, and Guangxi Zhuang Autonomous Region, Shanghai Municipality and Zhejiang Province where schistosomiasis had been eliminated, and reemergence of O. hupensis snails should be given a high priority in hilly areas. In addition, monitoring of O. hupensis snails should be reinforced in snail-free areas after flooding.
Humans ; China/epidemiology* ; Schistosomiasis/prevention & control* ; Cities ; Ecosystem ; Lakes

OBJECTIVES: To explore and analyze the epidemic features of coronavirus disease 2019 (COVID-19) in Hunan Province from January 21, 2020 to March 14, 2020, as well as to investigate the COVID-19 epidemics in each city of Hunan Province. METHODS: The epidemic data was obtained from the official website of Hunan Province's Health Commission. The data of each city of Hunan Province was analyzed separately. Spatial distribution of cumulative confirmed COVID-19 patients and the cumulative occurrence rate was drawn by ArcGIS software for each city in Hunan Province. Some regional indexes were also compared with that in the whole country. RESULTS: The first patient was diagnosed in January 21, sustained patient growth reached its plateau in around February 17. Up to March 14, the cumulative confirmed COVID-19 patients stopped at 1 018. The cumulative occurrence rate of COVID-19 patients was 0.48 per 0.1 million person. The number of cumulative severe patients was 150 and the number of cumulative dead patients was 4. The mortality rate (0.39%) and the cure rate (99.6%) in Hunan Province was significantly lower and higher respectively than the corresponding average rate in the whole country (0.90% and 96.2%, Hubei excluded). The first 3 cities in numbers of the confirmed patients were Changsha, Yueyang, and Shaoyang. While sorted by the cumulative occurrence rate, the first 3 cities in incidence were Changsha, Yueyang, and Zhuzhou. CONCLUSIONS The epidemic of COVID-19 spread out smoothly in Hunan Province. The cities in Hunan Province implement anti-disease strategies based on specific situations on their own and keep the epidemic in the range of controllable.
Betacoronavirus ; China ; epidemiology ; Cities ; epidemiology ; Coronavirus Infections ; epidemiology ; mortality ; Humans ; Pandemics ; Pneumonia, Viral ; epidemiology ; mortality

Objective: To understand the distribution and characteristics of suspected occupational chronic lead poisoning reported online by Jiangsu Province, and to track the final diagnosis of suspected cases. Methods: The suspected occupational chronic lead poisoning cases in Jiangsu Province reported online from 2014 to 2018 were collected as the survey objects. Based on the reporting of the Occupational Disease Report Card from January 1, 2014 to November 5, 2019, the distribution characteristics and reporting institutions of suspected cases and final confirmed cases were analyzed. Results: From 2014 to 2018, 312 cases of suspected occupational chronic lead poisoning were reported online in Jiangsu Province. There were significant differences in the number of online reported cases of occupational chronic lead poisoning, online reported cases of suspected occupational chronic lead poisoning and confirmed cases of suspected occupational chronic lead poisoning in different years (P<0.05) , especially in 2015. Among the suspected occupational lead poisoning cases reported online, 236 cases (75.6%) were male, mainly distributed in the manufacturing industry, and 246 cases (79.1%) were operators. All the suspected occupational chronic lead poisoning cases reported online were concentrated in private enterprises, 229 cases (73.4%) in small and medium-sized enterprises. The top three cities were Suqian with 111 cases (35.6%) , Yangzhou with 79 cases (25.3%) and Huai'an with 50 cases (16.0%) . From 2014 to 2018, 19 suspected cases of occupational chronic lead poisoning were finally confirmed in Jiangsu Province, with a diagnosis rate of 6.1%. Conclusion: The majority of suspected occupational chronic lead poisoning cases reported online in Jiangsu Province are men, manufacturing and small and medium-sized enterprises, and the final diagnosis rate of suspected occupational chronic lead poisoning cases reported online is low.
China/epidemiology* ; Cities ; Female ; Humans ; Lead ; Lead Poisoning/epidemiology* ; Male ; Manufacturing Industry ; Occupational Diseases/epidemiology*

Humans ; Temperature ; Cities/epidemiology* ; Hot Temperature ; Cardiovascular Diseases/epidemiology* ; China/epidemiology* ; Mortality

Objective: To explore the impact of environmental temperature exposure on eczema visits. Methods: Eczema clinic data from January 1, 2016 to December 31, 2019 were collected from the Huizhou Dermatology Hospital, and data on meteorological factors (average daily temperature and relative humidity) for the same period were derived from 86 meteorological stations of the Guangdong Provincial Climate Center. A distributed lag nonlinear model (DLNM) was used to assess the lagged effect of environmental temperature exposure on eczema, and a natural smooth spline function was used to control the nonlinear confounding of humidity. Results: There were 254 053 eczema outpatient visits at the Huizhou Dermatology Hospital within four years, with an average of 173.89 visits per day. The relationship between daily average temperature and the number of visits was non-linear (U shape). The risk of eczema increased by 2.20% (1.19%-3.21%) for every 1 ℃ decrease for the low temperature, and increased by 2.35% (1.24%-3.5%) for every 1 ℃ increase for the high temperature. The effect of high temperature was greater than that of low temperature. In all cases, 1.60% (0.44%-2.68%) of eczema outpatient visits were attributed to low temperature and the attributable number was 4 065 (1 128-6 798), while 6.33% (1.40%-10.87%) of eczema outpatient visits were due to high temperature and the attributable number was 16 082 (3 557-27 616). Conclusion: Both high temperature and low temperature are associated with increased risk of eczema.
Humans ; Air Pollution/adverse effects* ; Temperature ; Outpatients ; Cities ; Eczema/epidemiology* ; China/epidemiology* ; Air Pollutants/analysis*

OBJECTIVETo describe the nationwide prevalence of childhood overweight/obesity, and their group variations and trends over the past 20 years in the Chinese urban population.

METHODSData sets of boys and girls at the age of 7-18 years collected from the series of Chinese national surveillance on students' constitution and health (CNSSCH) between 1985 and 2000 were divided into five socioeconomic and demographic groups, while BMI classification reference proposed by Working Group on Obesity in China (WGOC) was used as screening reference to calculate the prevalence and trends of overweight/obesity in these groups.

RESULTSIn 2000, the prevalence of obesity and overweight in boys aged 7-18 years was 11.3% and 6.5% in Beijing, 13.2% and 4.9% in Shanghai, 9.9% and 4.5% in coastal big cities, and 5.8% and 2.0% in coastal medium/small-sized cities, respectively, while the prevalence of of obesity and overweight in girls of the same age group was 8.2% and 3.7% in Beijing, 7.3% and 2.6% in Shanghai, 5.9% and 2.8% in coastal big cities, and 4.8% and 1.7% in coastal medium/small-sized cities, respectively. The prevalence of obesity was low in most of the inland cities at an early stage of epidemic overweight. The epidemic manifested a gradient distribution in groups, which was closely related to socioeconomic status (SES) of the study population. However, a dramatic and steady increasing trend was witnessed among all sex-age subgroups in the five urban groups, and such a trend was stronger in boys than in girls, and much stronger in children than in adolescents.

CONCLUSIONAlthough China is at an early stage of epidemic obesity by and large, the prevalence of obesity in her urban population, particularly in coastal big cities has reached the average level of developed countries. The increasing trend has been rapid since early 1990s, and the increments in obesity and overweight are exceptionally high. The prospect of epidemic obesity in China is in no way optimistic. Therefore, preventive program should be focused on the improvement of the balance between caloric intake and energy expenditure, and interventions aimed at changing children's life styles.

Adolescent ; Child ; China ; epidemiology ; Cities ; Female ; Humans ; Male ; Obesity ; epidemiology ; Overweight ; Prevalence ; Urban Population ; trends

OBJECTIVETo analyze the serum total cholesterol level and the prevalence of hypercholesterolemia and borderline high cholesterolemia among urban-resident adults in China from 2010 to 2012.

METHODSData were from Chinese Nutrition and Health Surveillance in 2010-2012. Multi-stage stratified proportion to the population cluster random sampling method was conducted to determine 54 042 adult residents in 34 big cities and 41 small and medium-sized cities. Serum total cholesterol was measured by cholesterol oxidase method. Hypercholesterolemia and borderline high cholesterolemia were evaluated by Guidelines on Prevention and Treatment of Blood Lipid Abnormality in Chinese Adults 2007 edition. Standardized cholesterol level (x ± Sx) and prevalence of hypercholesterolemia and borderline high cholesterolemia were calculated through weighted complex sampling processing by population data released by the National Bureau of Statistics in 2009.

RESULTSThe mean level of urban-resident adults's erum total cholesterol was (4.58 ± 0.05)mmol/L, (4.58 ± 0.05)mmol/L for both male and female. The cholesterol concentration level in big cities and small and medium-sized cities were (4.66 ± 0.04)mmol/L and (4.57 ± 0.06) mmol/L, respectively. It increased with age gradually from the minimum level, which was (4.18 ± 0.05)mmol/L in aged 18 to 29 group, till reached the maximum, which was (4.94 ± 0.05)mmol/L in aged 60 to 69 group, and then it declined to (4.92 ± 0.06)mmol/L in aged 70 group. The prevalence of hypercholesterolemia and borderline high cholesterolemia were 5.6%(95%CI:4.5%-6.6%) and 24.7%(95%CI:21.6%-27.9%) totally; 5.1% (95%CI:4.1%-6.1%) and 24.4% (95%CI:21.0%-27.6%) for male, 6.0% (95%CI:4.7%-7.3%) and 25.1%(95%CI:21.8%-28.4%) for female; 6.0%(95%CI: 5.0%-7.0%) and 27.7%(95%CI:24.9%-30.6%) in big cities, while 5.5%(95%CI: 4.2%-6.7%) and 24.2%(95%CI:20.5%-27.9%) in small and medium-sized cities. The minimum prevalence of hypercholesterolemia was in aged 18 to 29 group and maximum in aged 70 group, which were 2.2%(95%CI: 1.4%-3.0%) and 10.3%(95%CI: 7.1%-13.4%), respectively; while the lowest borderline high cholesterolemia prevalence was in aged 18 to 29 group and the highest in aged 60 to 69 year group, which were 12.9%(95%CI: 10.4%-15.4%) and 37.6% (95%CI: 33.6%-41.6%), respectively.

CONCLUSIONThe serum total cholesterol level and the prevalence of hypercholesterolemia and borderline high cholesterolemia were high among urban adults in China from 2010 to 2012, and more attention should be paid for high serum total cholesterol level among older adults.

Adult ; China ; epidemiology ; Cholesterol ; blood ; Cities ; Female ; Humans ; Hypercholesterolemia ; epidemiology ; Lipids ; blood ; Male ; Prevalence ; Urban Population

The health effects of climatic changes constitute an important research area, yet few researchers have reported city- or region-specific projections of temperature-related deaths based on assumptions about mitigation and adaptation. Herein, we provide quantitative projections for the number of additional deaths expected in the future, owing to the cold and heat in the city of Nanjing, China, based on 31 global circulation models (GCMs), two representative concentration pathways (RCPs) (RCP4.5 and RCP8.5), and three population scenarios [a constant scenario and two shared socioeconomic pathways (SSPs) (SSP2 and SSP5)], for the periods of 2010-2039, 2040-2069, and 2070-2099. The results show that for the period 2070-2099, the net number of temperature-related deaths can be comparable in the cases of RCP4.5/SSP2 and RCP8.5/SSP5 owing to the offsetting effects attributed to the increase of heat related deaths and the decrease of cold-related deaths. In consideration of this adaptation, we suggest that RCP4.5/SSP2 is a better future development pathway/scenario.
China ; epidemiology ; Cities ; epidemiology ; Climate Change ; Humans ; Linear Models ; Mortality ; trends ; Temperature