Liying Xing

2.4k total citations · 1 hit paper
56 papers, 1.3k citations indexed

About

Liying Xing is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Liying Xing has authored 56 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Cardiology and Cardiovascular Medicine, 12 papers in Epidemiology and 11 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Liying Xing's work include Blood Pressure and Hypertension Studies (19 papers), Cardiovascular Health and Disease Prevention (19 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (10 papers). Liying Xing is often cited by papers focused on Blood Pressure and Hypertension Studies (19 papers), Cardiovascular Health and Disease Prevention (19 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (10 papers). Liying Xing collaborates with scholars based in China, United States and Italy. Liying Xing's co-authors include Alberto Avolio, Yingxian Luo, Michael F. O’Rourke, Zhe Huang, Yuanmeng Tian, Jing Li, Zhi Du, Min Lin, Qun Sun and Dong Dai and has published in prestigious journals such as Circulation, BMJ and International Journal of Cancer.

In The Last Decade

Liying Xing

50 papers receiving 1.3k citations

Hit Papers

Effects of aging on arterial distensibility in population... 1985 2026 1998 2012 1985 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liying Xing China 17 851 221 205 201 162 56 1.3k
Wook Bum Pyun South Korea 20 834 1.0× 122 0.6× 134 0.7× 137 0.7× 228 1.4× 81 1.3k
Davide Agnoletti Italy 23 1.0k 1.2× 199 0.9× 261 1.3× 169 0.8× 292 1.8× 57 1.5k
Marina Cecelja United Kingdom 16 1.2k 1.4× 165 0.7× 113 0.6× 305 1.5× 182 1.1× 40 1.8k
Ronald T. Gansevoort Netherlands 25 597 0.7× 374 1.7× 242 1.2× 241 1.2× 126 0.8× 38 2.0k
Matthew F. Yuyun United States 17 619 0.7× 321 1.5× 168 0.8× 131 0.7× 99 0.6× 45 1.2k
Jiko Yamada Japan 16 802 0.9× 162 0.7× 186 0.9× 187 0.9× 149 0.9× 25 1.1k
Yoshio Iwashima Japan 19 858 1.0× 179 0.8× 485 2.4× 357 1.8× 255 1.6× 50 1.6k
Azra Mahmud Ireland 24 1.9k 2.2× 284 1.3× 162 0.8× 353 1.8× 287 1.8× 51 2.4k
Timir K. Paul United States 18 778 0.9× 139 0.6× 132 0.6× 242 1.2× 329 2.0× 149 1.4k
Ravi R. Kasliwal India 20 754 0.9× 133 0.6× 202 1.0× 241 1.2× 419 2.6× 78 1.2k

Countries citing papers authored by Liying Xing

Since Specialization
Citations

This map shows the geographic impact of Liying Xing's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Liying Xing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liying Xing more than expected).

Fields of papers citing papers by Liying Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liying Xing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Liying Xing. The network helps show where Liying Xing may publish in the future.

Co-authorship network of co-authors of Liying Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Liying Xing. A scholar is included among the top collaborators of Liying Xing based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liying Xing. Liying Xing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Xingyi, Siming Wang, Xingyu Zhou, et al.. (2025). A village doctor-led mobile health intervention for cardiovascular risk reduction in rural China: cluster randomised controlled trial. BMJ. 389. e082765–e082765. 1 indexed citations
6.
Li, Jing, Yuanmeng Tian, Guocheng Ren, et al.. (2021). Epidemiological features of hypertension among ischemic survivors in Northeast China: insights from a population-based study, 2017–2019. BMC Public Health. 21(1). 1648–1648. 4 indexed citations
7.
Xue, Weishuang, Yuanmeng Tian, Jing Li, et al.. (2021). Sex-specific prediction value of common carotid artery diameter for stroke risk in a hypertensive population: a cross-sectional study. Quantitative Imaging in Medicine and Surgery. 12(2). 1428–1437. 2 indexed citations
8.
Guo, Rongrong, Yanxia Xie, Jia Zheng, et al.. (2020). Effects of long- and short-term body mass index changes on incident hypertension are different. Nutrition. 74. 110755–110755. 1 indexed citations
9.
Dai, Yue, Yanxia Xie, Jia Zheng, et al.. (2020). The Association of Stage 1 Hypertension Defined by the 2017 ACC/AHA Guideline with Stroke and Its Subtypes among Elderly Chinese. BioMed Research International. 2020(1). 4023787–4023787. 4 indexed citations
10.
Du, Zhi, Boqiang Zhang, Min Lin, et al.. (2020). The epidemiology of atrial fibrillation in Chinese postmenopausal women and its association with age of menopause. Maturitas. 143. 151–156. 6 indexed citations
11.
Xing, Liying, Jing Li, Yuanmeng Tian, et al.. (2020). Epidemiology of dyslipidemia and associated cardiovascular risk factors in northeast China: A cross-sectional study. Nutrition Metabolism and Cardiovascular Diseases. 30(12). 2262–2270. 42 indexed citations
12.
Du, Zhi, Liying Xing, Shuang Liu, et al.. (2020). Prevalence and determinants of metabolic syndrome based on three definitions in rural northeast China. Public Health Nutrition. 23(18). 3379–3386. 8 indexed citations
13.
Liu, Sitong, Yali Wang, Yue Dai, et al.. (2020). Putting the glass down may keep the stroke away: Results from a prospective cohort study in rural China. Nutrition Metabolism and Cardiovascular Diseases. 31(4). 1113–1120.
14.
Xing, Liying, Jing Li, Yuanmeng Tian, et al.. (2019). High prevalence of stroke and uncontrolled associated risk factors are major public health challenges in rural northeast China: A population-based study. International Journal of Stroke. 15(4). 399–411. 31 indexed citations
15.
Zheng, Jia, Yanxia Xie, Yali Wang, et al.. (2019). Short- and long-term systolic blood pressure changes have different impacts on major adverse cardiovascular events: Results from a 12.5 years follow-up study. International Journal of Cardiology. 306. 190–195. 6 indexed citations
16.
Du, Zhi, Liying Xing, Min Lin, et al.. (2019). Prevalence of first-degree atrioventricular block and the associated risk factors: a cross-sectional study in rural Northeast China. BMC Cardiovascular Disorders. 19(1). 214–214. 8 indexed citations
17.
Wang, Yali, Yue Dai, Yanxia Xie, et al.. (2019). Association between body mass index changes and short- and long-term outcomes of hypertension in a Chinese rural cohort study. Journal of Human Hypertension. 34(8). 593–601. 2 indexed citations
18.
Xing, Liying. (2010). Hypertension prevalence and its awareness,medication and control among rural residents in Liaoning province. Chinese Journal of Public Health. 2 indexed citations
19.
Chen, Fan, Philip Cole, Zhibao Mi, & Liying Xing. (1993). Corn and wheat‐flour consumption and mortality from esophageal cancer in shanxi, China. International Journal of Cancer. 53(6). 902–906. 42 indexed citations
20.
Chen, Fan, Philip Cole, Zhibao Mi, & Liying Xing. (1992). Dietary Trace Elements and Esophageal Cancer Mortality in Shanxi, China. Epidemiology. 3(5). 402–406. 26 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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