Shan Zheng

Dr. Shan Zheng


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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SZShan Zheng
Shan Zheng
MWMinzhen Wang
Minzhen Wang
SWShigong Wang
Shigong Wang
YTYan Tao
Yan Tao
KSKezheng Shang
Kezheng Shang
Panel studies show a consistent association between increase in the cardiovascular hospitalizations with air pollutants in economically developed regions, but little evidence in less developed inland areas. In this study, a time-series analysis was used to examine the specific effects of major air pollutants [particulate matter less than 10 microns in diameter (PM10), sulfur dioxide (SO2), and nitrogen dioxides (NO2)] on daily hospital admissions for cardio-cerebrovascular diseases in Lanzhou, a heavily polluted city in China. We examined the effects of air pollutants for stratified groups by age and gender, and conducted the modifying effect of seasons on air pollutants to test the possible interaction. The significant associations were found between PM10, SO2 and NO2 and cardiac disease admissions, SO2 and NO2 were found to be associated with the cerebrovascular disease admissions. The elderly was associated more strongly with gaseous pollutants than younger. The modifying effect of seasons on air pollutants also existed. The significant effect of gaseous pollutants (SO2 and NO2) was found on daily hospital admissions even after adjustment for other pollutants except for SO2 on cardiac diseases. In a word, this study provides the evidence for the detrimental short-term health effects of urban gaseous pollutants on cardio-cerebrovascular diseases in Lanzhou.

21 August 2025 in Scientific Reports
Verified
Journal Article
Open access
PDF file
HCHao Chen
Hao Chen
CSChen Sang
Chen Sang
JJJia Jia
Jia Jia
SZShan Zheng
Shan Zheng
MWMinzhen Wang
Minzhen Wang
Prostate cancer (PC) is a significant global health concern, particularly among older men (OM), and smoking is a well-established modifiable risk factor contributing to its incidence and mortality. However, a comprehensive assessment of the global burden of PC attributable to smoking among OM, with specific analyses by age and Socio-demographic Index (SDI) regions, is still lacking. This study utilized data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to systematically analyze the global burden of PC attributable to smoking among OM (aged 55 years and older) from 1990 to 2021. The analysis included trends in deaths and Disability-Adjusted Life Years (DALYs) across different age groups and SDI regions. The estimated annual percentage change (EAPC) and Joinpoint regression analysis were employed to assess temporal trends. From 1990 to 2021, the global burden of PC attributable to smoking among OM exhibited a significant decline, with the age-standardized death rate decreasing from 3.08 per 100,000 in 1990 to 1.80 per 100,000 in 2021 (EAPC: -2.02, 95% CI: -2.14 to -1.90). Similarly, the age-standardized DALY rate decreased from 65.28 per 100,000 in 1990 to 37.75 per 100,000 in 2021 (EAPC: -2.05, 95% CI: -2.16 to -1.94). However, disparities across SDI regions were evident. The high SDI region experienced the most substantial decline in burden. In contrast, the low-middle SDI region showed an increasing trend, highlighting enduring socioeconomic disparities. Notably, Despite the overall reduction in the global burden, the burden among the older age group, specifically 90–95 years old, remained the most severe in 2021. This study reveals a complex landscape of the global burden of PC attributable to smoking among OM, with an overall decline masking enduring socioeconomic disparities and a severe burden among the older age group. These findings underscore the need for targeted interventions and public health strategies to address these disparities. Future efforts should focus on implementing smoking cessation programs and improving healthcare access in vulnerable populations.

1 January 2011
Verified
Journal Article
Closed access
SZShan Zheng
Shan Zheng
MWMinzhen Wang
Minzhen Wang
YBYa'Na Bai
Ya'Na Bai
XHXiaobin Hu
Xiaobin Hu
RZRongqiang Zhang
Rongqiang Zhang
NCNing Cheng
Ning Cheng

1 November 2010
Verified
Journal Article
Closed access
SZShan Zheng
Shan Zheng
XHXiaobin Hu
Xiaobin Hu
MWMinzhen Wang
Minzhen Wang
LLLiansheng Li
Liansheng Li
WLWu Liu
Wu Liu
YBYa'Na Bai
Ya'Na Bai

1 May 2021 in American Journal of Hypertension
Verified
Journal Article
Closed access
PDF file
QMQian Miao
Qian Miao
SZShan Zheng
Shan Zheng
YLYan Luo
Yan Luo
MWMing-Zhen Wang
Ming-Zhen Wang
WZWen-Zhi Zhu
Wen-Zhi Zhu
YBYana Bai
Yana Bai
Background: To investigate the incidence and influencing factors of hypertension in Jinchang cohort. Methods: A prospective cohort study was conducted to collect the baseline and follow-up information of 22,826 employees from 2011 to 2015 based on the Jinchang cohort platform. The incidence of hypertension in the cohort was calculated and the influencing factors were analyzed by Cox proportional risk model. Results: The subjects were followed up for an average of 22 years, and the incidence density of hypertension was 56.31/1000 person-years. Multivariate Cox regression results showed that the main risk factors for hypertension in the population included age ≥40 years, alcohol consumption, high-salt diet, history of diabetes, family history of hypertension, overweight and obesity, baseline systolic blood pressure ≥110 mm Hg and diastolic blood pressure ≥75 mm Hg, and higher education levels (middle school, high school, and above) were a protective factor. The incidence of grade 1 hypertension was related to age, drinking, history of diabetes, family history of hypertension and baseline blood pressure levels, and the incidence of grades 2 and 3 hypertension was related to high-salt diet, family history of hypertension, overweight or obesity, and baseline blood pressure levels. Conclusions: The Jinchang cohort has a higher risk of hypertension. Age, unhealthy lifestyle, history of diabetes, family history of hypertension, obesity, and baseline blood pressure are strongly associated with the onset of hypertension. There are differences in the risk factors for the occurrence of grades 1, 2, and 3 hypertension.