Yang SUN

Dr. Yang SUN

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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1 January 2017 in International Journal of Cardiology
Verified
Journal Article
Closed access
CJChang Jie
Chang Jie
Xin LiuXin Liu
Xin Liu
YSYang SUN
Yang SUN

31 August 2018 in Social Psychiatry and Psychiatric Epidemiology
Verified
Journal Article
Closed access
PDF file
XCXinguang Chen
Xinguang Chen
YSYang SUN
Yang SUN
ZLZhi Li
Zhi Li
BYBin Yu
Bin Yu
GGGe Gao
Ge Gao
PWPeigang Wang
Peigang Wang

21 July 2015 in Human Resources for Health
Verified
Journal Article
Open access
PDF file
XLXiaoyun Liu
Xiaoyun Liu
LDLixia Dou
Lixia Dou
HZHuan Zhang
Huan Zhang
YSYang SUN
Yang SUN
BYBeibei Yuan
Beibei Yuan
Current literature systematically reports that interventions to attract and retain health workers in underserved areas need to be context specific but rarely defines what that means. In this systematic review, we try to summarize and analyse context factors influencing the implementation of interventions to attract and retain rural health workers. We searched online databases, relevant websites and reference lists of selected literature to identify studies on compulsory rural service programmes and financial incentives. Forty studies were selected. Information regarding context factors at macro, meso and micro levels was extracted and synthesized. Macro-level context factors include political, economic and social factors. Meso-level factors include health system factors such as maldistribution of health workers, growing private sector, decentralization and health financing. Micro-level factors refer to the policy implementation process including funding sources, administrative agency, legislation process, monitoring and evaluation. Macro-, meso- and micro-level context factors can play different roles in agenda setting, policy formulation and implementation of health interventions to attract and retain rural health workers. These factors should be systematically considered in the different stages of policy process and evaluation.

CJChang Jie
Chang Jie
BLBoyang Li
Boyang Li
JLJingjing Li
Jingjing Li
YSYang SUN
Yang SUN
In contrast with most developed countries, mortality due to ischemic heart disease (IHD) continues to rise in China. We examined the effects of age, period, and cohort on IHD mortality in urban and rural populations from 1987 to 2013 to identify the drivers of this trend. Region-specific data on annual IHD mortality among adults aged 20 to 84 years and corresponding population statistics were collected. We then tested for age, period, and cohort effects using the Intrinsic Estimator approach. Our results indicated that IHD mortality in China increased significantly over the three decades studied. There was a log-linear increase in the age effect on IHD mortality as those aged 80–84 showed 277 and 161 times greater IHD mortality risk than those aged 20–24 in urban and rural populations, respectively. While there was an upward trend in the period effect in both populations, the influence of the cohort effect on mortality decreased over time for those born from 1904 to 1993. The age, period, and cohort effects on mortality in China were generally comparable between urban and rural populations. The results suggest that population aging is a major driver behind the rapid rise in IHD mortality. Increased exposure to air pollution may also have played a role in driving the period effect

24 March 2017 in Journal of International Medical Research
Verified
Journal Article
Open access
JLJingjing Li
Jingjing Li
BLBoyang Li
Boyang Li
FZFengfan Zhang
Fengfan Zhang
YSYang SUN
Yang SUN
Objective: To evaluate effects attributable to age, time period and birth cohort, on stroke mortality data from urban and rural regions in China between 1988 and 2013. Methods: Mortality data were obtained from the Chinese Health Statistics Annual Report (1987–2001) and Chinese Health Statistics Yearbooks (2003–2014). Population data were obtained from population censuses (i.e. 1982, 1990, 2000 and 2010). Data were analysed using an age-period-cohort (APC) model and intrinsic estimation (IE) method. Results: The age effect suggested that all older residents had higher stroke mortality risk than younger residents. Period effect showed that compared with figures for 1988, stroke mortality in 2013 was 1.8 times higher for urban regions and 2.4 times higher for rural regions. After controlling for age and period effects, cohorts born before the Chinese economic reform had a steady decline in stroke mortality. However, mortality rates increased and fluctuated in post-reform cohorts. Conclusions: This APC-IE analysis identified a modest period effect with large age and cohort contributions to both the overall mortality and the disparity between urban and rural stroke mortality. Identifying early life and cumulative risk factors for stroke, improving equality in stroke prevention and care are needed to reduce the stroke mortality in China.