1.Smoking status among grassroots healthcare workers in Shaoxing City
Journal of Preventive Medicine 2024;36(2):181-184
Objective:
To investigate the prevalence and influencing factors of smoking among grassroots healthcare workers in Shaoxing City, Zhejiang Province, so as to provide insights into effective implementation of tobacco control measures in primary healthcare organizations.
Methods:
Grassroots healthcare workers of community health service centers (health institutes) were sampled from four streets (townships) in each of 6 counties (cities, districts) in Shaoxing City using a stratified cluster sampling method from May to June 2023. Participants' demographics, current smoking and quit smoking information were collected through questionnaire surveys, and factors affecting current smoking among grassroots healthcare workers were identified using a multivariable logistic regression model.
Results:
Totally 2 801 questionnaires were allocated, and 2 595 valid questionnaires were recovered, with an effective recovery rate of 92.65%. Participants included 719 men (27.71%) and 1 876 women (72.29%), with a mean age of (39.39±10.11) years. There were 119 current smokers and the prevalence of current smoking was 4.59%. The median number of cigarettes smoked per day was 10.00 (interquartile range, 14.25) and the median duration of smoking was 20.00 (interquartile range, 15.00) years. There were 52 people with intention to quit smoking (43.70%), and 51 people with attempts to quit smoking (42.86%). Multivariable logistic regression analysis identified men (OR=22.998, 95%CI: 10.912-48.473), alcohol consumption (OR=3.907, 95%CI: 2.528-6.037) and length of service (15 years and more, OR=3.115, 95%CI: 1.305-7.434) as factors affecting current smoking among grassroots healthcare workers.
Conclusions
The prevalence of current smoking among grassroots healthcare workers in Shaoxing City is 4.59%, and there is low willingness to quit smoking. Current smoking status may be affected by gender, alcohol consumption and length of service.
2.Visualized Citation Analysis of Evidence in Research Fields of Clinical Pharmacy
Mingzhi WU ; Yang JIANG ; Jian GONG
China Pharmacist 2015;(3):503-505
Objective:To analyze the visualized citation of evidence in the research fields of clinical pharmacy. Methods: The visualized citation analysis tool HistCite was used, and science citation index-expanded core collections in Web of Science was applied to obtain the data. Biliometric analysis, citation analysis and visualization technology were used to investigate the number and year-dis-tribution, country and region, distribution of research institutions and core authors of the literatures in clinical pharmacy research fields. Results:During 2002 to 2013, the number of literatures of clinical pharmacy was increased year by year. The literatures were published mainly in 62 countries and regions, especially in the United States of America. The major research institutions were college of pharmacy in university. Conclusion: Over the past decade, the research on clinical pharmacy is increased rapidly. The software HistCite can reveal the development track of clinical pharmacy research fields quickly and visually.
3.Smoking status among residents in Shaoxing City
JIAN Mingzhi ; LU Di ; CHEN Jie ; JIANG Tingting
Journal of Preventive Medicine 2024;36(9):817-820,824
Objective:
To investigate the status and identify the influencing factors of smoking among residents in Shaoxing City, Zhejiang Province, so as to provide insights into tobacco control.
Methods:
Permanent residents aged 15 to 69 years in Shaoxing City were recruited using the stratified multistage random sampling method from June to December 2022, and smoking behaviors and health literacy were collected using the National Questionnaire for Surveillance on Healthy Literacy in Chinese Residents. Factors affecting smoking were identified using a multivariable logistic regression model.
Results:
Totally 4 156 questionnaires were allocated, and 4 055 valid questionnaires were recovered, with an effective recovery rate of 97.57%. There were 1 899 men (46.83%), 2 073 residents in rural areas (51.12%), and 3 256 married residents (80.30%). There were 805 smokers, and the rate of smoking was 19.85%. Multivariable logistic regression analysis showed that male (OR=169.861, 95%CI: 92.335-312.481), age (25-<35 years, OR=8.768, 95%CI: 2.964-25.937; 35-<45 years, OR=9.271, 95%CI: 3.077-27.933; 45-<55 years, OR=10.467, 95%CI: 3.498-31.327; 55-<65 years, OR=8.880, 95%CI: 2.964-26.608; 65-69 years, OR=6.115, 95%CI: 1.992-18.774), marital status (divorced, OR=2.035, 95%CI: 1.260-3.287; widowed, OR=2.317, 95%CI: 1.337-4.016), educational level (illiterate or semi-literate, OR=2.724, 95%CI: 1.515-4.898; primary school, OR=2.734, 95%CI: 1.823-4.100; junior high school, OR=2.003, 95%CI: 1.423-2.820; high school/vocational high school /technical secondary school, OR=1.625, 95%CI: 1.148-2.299), self-rated health status (general, OR=0.788, 95%CI: 0.623-0.996; relatively poor, OR=0.343, 95%CI: 0.191-0.617) and lack of basic health skills (OR=1.290, 95%CI: 1.007-1.653) were associated with smoking.
Conclusions
The smoking rate among residents in Shaoxing City is relatively low, and might be influenced by gender, age, marital status, educational level, self-rated health status, and basic health skills.
4.Prevalence and influential factors of smoking in urban and rural residents in Shaoxing City
Mingzhi JIAN ; Jie CHEN ; Tingting JIANG
Shanghai Journal of Preventive Medicine 2023;35(5):459-465
ObjectiveTo examine the prevalence and influencing factors of smoking in urban and rural residents in Shaoxing City for providing evidences to effective tobacco control. MethodsWith stratified multistage random sampling, we conducted a face-to-face survey among 4 063 residents aged 15‒69 years in the city. A face-to-face questionnaire survey was used to collect information on smoking among urban and rural residents. ResultsAmong the 4 063 valid respondents, the rate of current smoking was 22.69%, the current smoking rate of rural residents was 24.85% and the rate of urban residents was 20.48%. The results of unconditional multivariate logistic regression analysis revealed that the following were the protective factors of smoking among urban and rural residents: having health literacy, suffering the chronic disease, being female, with poor self-evaluated health status, being a personnel of organizations/institutions, students, farmers, workers and other staffs of enterprises (P<0.05). ConclusionHealth literacy, gender, occupation, age, self-evaluation of health status and chronic diseases are the main influencing factors of current smoking behavior among urban and rural residents. Improving residents’ health literacy through health education can effectively affect residents’ smoking behavior.
5. Model informed precision dosing of warfarin: China expert consensus report (2022 version)
Jinhua ZHANG ; Maobai LIU ; Mingzhi CAI ; Yingli ZHENG ; Haiyan LAO ; Qian XIANG ; Liping DU ; Zhu ZHU ; Jing DONG ; Xiaocong ZUO ; Xingang LI ; Dewei SHANG ; Bing CHEN ; Yanrong YE ; Yuzhu WANG ; Jianjun GAO ; Jian ZHANG ; Wansheng CHEN ; Haitang XIE ; Zheng JIAO
Chinese Journal of Clinical Pharmacology and Therapeutics 2022;27(11):1201-1212
Model informed precision dosing for warfarin is to provide individualized dosing by integrating information related to patient characteristics, disease status and pharmacokinetics /pharmacodynamics of warfarin, through mathematical modeling and simulation techniques based on the quantitative pharmacology. Compared with empirical dosing, it can improve the safety, effectiveness, economy, and adherence of pharmacotherapy of warfarin. This consensus report describes the commonly used modeling and simulation techniques for warfarin, their application in developing and adjusting dosing regimens, medication adherence and economy. Moreover, this consensus also elaborates the detailed procedures for the implementation in the warfarin pharmacy service pathway to facilitate the development and application of model informed precision dosing for warfarin.
6.The Influence of Knife Sharpness on Forearm Wounds in Knife Slash Cases
Weiya HAO ; Songjunjie SHAN ; Yi SHI ; Chaopeng YANG ; Chengliang WU ; Wei HE ; Zhenfang XIN ; Jian WANG ; Mingzhi WANG
Journal of Medical Biomechanics 2020;35(5):E546-E552
Objective To quantitatively explore the influence of knife sharpness on forearm wounds in knife slash cases. Methods The finite element models of the upper limb and knives with 3 degrees of sharpness (with sharp blade, blunt blade, wide blade) were developed based on human CT images and prototype of slash knife. The slash by 3 kinds of knives on the forearm at velocity of 4 m/s and duration of 10 ms was simulated, so as to analyze changes in contact forces, wound dimensions and energy. Results During the slash by knives with sharp, blunt, wide blade, the blades reached the ulna at about 65, 85, 95 ms, respectively. The corresponding slash forces were 846, 1 064 and 1 865 N; the wound lengths were 135.64, 105.47 and 99.23 mm; the wound depths were 38.77, 27.81 and 18.74 mm. With the sharpness of blade decreasing, the wound formation was slowed, the length and depth decreased and the slash force increased. The model system for slash knife with sharp blade had obviously greater total energy and inner energy, but smaller kinetic energy, compared with slash knife with blunt blade and wide blade. Conclusions The method for quantitatively assessing wound formation in knife slash upon the forearm was developed. The research findings deepen the understanding of biomechanical mechanism of wound formation by knife slash, and provide new scientific means for forensic investigation and court trial of knife slash cases.