Strategy for Improving the Quality of Manufacturing in Jiangsu Province During the Thirteenth Five Period

China’s current Air Quality Index (AQI) system only considers one air pollutant which has the highest concentration value. In order to comprehensively evaluate the urban air quality of Jiangsu Province, this paper has studied the air quality of 13 cities in that province from April 2015 to March 2018 based on an expanded AQI system that includes six major air pollutants. After expanding the existing air quality evaluation standards of China, this paper has calculated the air quality evaluation scores of cities in Jiangsu Province based on the six major air pollutants by using the improved Fuzzy Comprehensive Evaluation Model. This paper has further analyzed the effectiveness of air pollution control policies in Jiangsu Province and its different cities during the study period. The findings are as follows: there are distinct differences in air quality for different cities in Jiangsu Province; except for coastal cities such as Nantong, Yancheng and Lianyungang, the southern cities of Jiangsu generally have better air quality than the northern cities. The causes of these differences include not only natural factors such as geographical location and wind direction, but also economic factors and energy structure. In addition, air pollution control policies have achieved significant results in Nantong, Changzhou, Wuxi, Yangzhou, Suzhou, Yancheng, Zhenjiang, Tai’an and Lianyungang. Among them, Nantong has seen the biggest improvement, 20.28%; Changzhou and Wuxi have improved their air quality by more than 10%, while Yangzhou, Suzhou, and Yancheng have improved their air quality by more than 5%. However, the air quality of Nanjing, Huai’an, Xuzhou, and Suqian has worsened by different degrees compared that of the last period within the beginning period, during which Suqian’s air quality has declined by 20.07% and Xuzhou’s by 16.32%.

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Genetic Analysis and Taste Quality of Main Conventional Japonica Rice Varie-ties Grown in Jiangsu Province

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2016.01083 ◽

2016 ◽

Vol 42 (7) ◽

pp. 1083

Author(s):

Hong-Bing GONG ◽

Sheng-Yuan ZENG ◽

Chuang LI ◽

Shi-Min ZUO ◽

De-Dao JING ◽

...

Keyword(s):

Genetic Analysis ◽

Taste Quality ◽

Jiangsu Province ◽

Japonica Rice

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Estimating Population Norms for the Health-Related Quality of Life of Adults in Southern Jiangsu Province, China

10.21203/rs.3.rs-672348/v1 ◽

2021 ◽

Author(s):

wei Hu ◽

Liang Zhou ◽

Jiadong Chu ◽

Na Sun ◽

Shuting Xiong ◽

...

Keyword(s):

Quality Of Life ◽

Jiangsu Province ◽

Cross Sectional Survey ◽

Population Norms ◽

Hepatic Diseases ◽

Related Quality ◽

Vas Scores ◽

Southern Jiangsu ◽

Utility Scores

Abstract PurposeHealth-related quality of life (HRQoL) population norms have been published in China but only for urban populations. Moreover, China is large and diverse in culture and social development, and regional population norms may be more appropriate than national norms. The purpose of the study was to derive the HRQoL population norms for adults in southern Jiangsu Province and explored potential influencing factors. MethodsThe data were based on a cross-sectional survey conducted in Liyang City from March 2019 to July 2020. EQ-5D-5L utility scores based on Chinese value set and EQ-VAS scores were used to assess HRQoL. The Tobit regression model and generalized linear model were performed to identify the association among potential covariates and HRQoL. ResultsThe means (95% confidence interval) of the EQ-5D-5L utility scores and VAS scores were 0.981(0.980-0.983) and 83.6(83.2-83.9), respectively. Younger people were more likely to experience problems with anxiety or depression. Lower HRQoL was associated with elderly individuals, lower socioeconomic status, no spouse, lack of regular physical activities, smoking cessation, and chronic non-communicable diseases. Subjects who declared that they were afflicted by diseases presented significantly lower utility scores, ranging from 0.823(0.766-0.880) for memory-related diseases to 0.978 (0.967-0.989) for hepatic diseases. ConclusionsRegional population norms of HRQoL are needed in the health economic study owing to the great socioeconomic differences across regions in China. The present study provides HRQoL population norms for adults in southern Jiangsu. These norm values could help policy makers better allocate limited health resources and prioritize service plans.

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Sleep quality and health in healthcare professionals fighting against COVID-19: a comparative study between high risk area (Hubei Province) and low risk area (Jiangsu Province) in China

10.21203/rs.3.rs-27217/v1 ◽

2020 ◽

Author(s):

Juan Li ◽

Xiangjing Kong ◽

Fanfan Li ◽

Bei Wu ◽

Hanzhang Xu ◽

...

Keyword(s):

Sleep Quality ◽

Healthcare Professionals ◽

Quality Of Healthcare ◽

Hubei Province ◽

Jiangsu Province ◽

Poor Sleep ◽

Poor Sleep Quality ◽

Risk Area ◽

High Risk Area

Abstract Background: Novel Coronavirus Disease 2019 (COVID-19) emerged in Wuhan, Hubei Province, China in December 2019. Since then, there was an outbreak in Wuhan and the coronavirus spread quickly nationwide. Thousands of healthcare providers fought against COVID-19 in Wuhan and other areas of China. The present study aimed to investigate the levels and related factors of sleep quality of healthcare professionals fighting against COVID-19 in high risk area (Hubei Province) and low risk area (Jiangsu Province), and association between sleep quality and health. Methods: A total of 253 healthcare professionals in Hubei Province (n=119, female 72.3%, mean age=32.13±5.50, nurse 80.7%) and Jiangsu Province(n=134, female 94.0%, mean age=30.2±5.52, nurse 96.3%) were surveyed from February to March 2020. Sleep quality (Pittsburgh sleep quality index, PSQI) and health were assessed using an internet survey.Results: The global PSQI score of Hubei sample and Jiangsu sample was 9.74±5.00 and 7.79±4.64, respectively. The global PSQI score and the scores of subjective sleep quality, sleep latency, sleep duration and use of sleep medications in Hubei sample were significantly higher than that of Jiangsu sample (p<0.05). For Hubei sample, fear of infection, fatigue in Class 3 protection and worry about family were predictors of poor sleep quality (OR=5.020, 95%CI 1.761-14.306, OR=3.859, 95%CI 1.168-12.753, OR=3.576, 95%CI 1.002-12.759, respectively), while dizziness in Class 3 protection was predictor of poor sleep quality for Jiangsu sample (OR=7.063, 95%CI 2.323-21.470). Poor sleep quality was associated with reduced self-reported health after controlling for covariates for all samples(β=-0.75, p<0.01, β=-0.52, p<0.01, respectively).Conclusions: Sleep quality of healthcare professionals in Hubei was worse than that in Jiangsu. Poor sleep quality was associated to poor health. Our findings call for systematic sleep intervention program that are specially designed to help healthcare professionals fighting against infectious disease to improve their sleep quality.

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