Shankuan Zhu

22.3k total citations · 1 hit paper
106 papers, 5.1k citations indexed

About

Shankuan Zhu is a scholar working on Public Health, Environmental and Occupational Health, Physiology and Epidemiology. According to data from OpenAlex, Shankuan Zhu has authored 106 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Public Health, Environmental and Occupational Health, 35 papers in Physiology and 18 papers in Epidemiology. Recurrent topics in Shankuan Zhu's work include Obesity, Physical Activity, Diet (17 papers), Nutritional Studies and Diet (16 papers) and Nutrition and Health in Aging (14 papers). Shankuan Zhu is often cited by papers focused on Obesity, Physical Activity, Diet (17 papers), Nutritional Studies and Diet (16 papers) and Nutrition and Health in Aging (14 papers). Shankuan Zhu collaborates with scholars based in China, United States and Japan. Shankuan Zhu's co-authors include Steven B. Heymsfield, Stanley Heshka, Mercedes R. Carnethon, Latha Palaniappan, ZiMian Wang, Xiaoguang Ma, David B. Allison, Xueyin Zhao, Wei He and Wei Shen and has published in prestigious journals such as Nature Communications, PLoS ONE and American Journal of Clinical Nutrition.

In The Last Decade

Shankuan Zhu

102 papers receiving 4.9k citations

Hit Papers

The Metabolic Syndrome 2003 2026 2010 2018 2003 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shankuan Zhu China 34 1.6k 1.4k 1.3k 866 655 106 5.1k
Hsing‐Yi Chang Taiwan 36 1.2k 0.7× 993 0.7× 690 0.5× 732 0.8× 520 0.8× 168 4.9k
Chongjian Wang China 42 1.1k 0.7× 865 0.6× 1.1k 0.8× 1.0k 1.2× 873 1.3× 431 7.4k
Kyungwon Oh South Korea 32 2.7k 1.7× 1.7k 1.2× 869 0.7× 652 0.8× 487 0.7× 89 6.6k
Yao He China 33 704 0.4× 977 0.7× 617 0.5× 594 0.7× 552 0.8× 254 3.9k
MaryFran Sowers United States 54 1.8k 1.1× 1.3k 1.0× 2.3k 1.7× 702 0.8× 473 0.7× 121 9.2k
Bo Xi China 46 2.7k 1.7× 1.7k 1.3× 978 0.7× 875 1.0× 1.6k 2.5× 283 8.0k
Donald M. Lyall United Kingdom 39 974 0.6× 1.6k 1.2× 417 0.3× 520 0.6× 738 1.1× 118 4.9k
Hans Ole Hein Denmark 32 1.1k 0.7× 1.4k 1.0× 895 0.7× 531 0.6× 1.1k 1.7× 88 5.0k
Yadollah Mehrabi Iran 30 2.4k 1.5× 1.2k 0.9× 1.6k 1.2× 948 1.1× 438 0.7× 224 5.9k
Nobuo Yoshiike Japan 33 1.4k 0.8× 695 0.5× 578 0.4× 436 0.5× 515 0.8× 127 3.6k

Countries citing papers authored by Shankuan Zhu

Since Specialization
Citations

This map shows the geographic impact of Shankuan Zhu'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 Shankuan Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shankuan Zhu more than expected).

Fields of papers citing papers by Shankuan Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shankuan Zhu. 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 Shankuan Zhu. The network helps show where Shankuan Zhu may publish in the future.

Co-authorship network of co-authors of Shankuan Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Shankuan Zhu. A scholar is included among the top collaborators of Shankuan Zhu 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 Shankuan Zhu. Shankuan Zhu 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
2.
Zhu, Shankuan, et al.. (2025). Computational advances in biosynthetic gene cluster discovery and prediction. Biotechnology Advances. 79. 108532–108532. 6 indexed citations
3.
Wang, Xiaoyan, et al.. (2024). Breastfeeding in infancy and cardiovascular disease in middle-aged and older adulthood: a prospective study of 0.36 million UK Biobank participants. The journal of nutrition health & aging. 28(10). 100347–100347. 2 indexed citations
4.
Wang, Wenjie, Jiakai Zhang, Yifeng Wang, et al.. (2024). Association of dietary overall antioxidant intake with all-cause and cause-specific mortality among adults with depression: evidence from NHANES 2005–2018. Food & Function. 15(8). 4603–4613. 3 indexed citations
5.
Kan, Juntao, Wenjie Wang, Weifang Zheng, et al.. (2024). Nut consumption, gut microbiota, and body fat distribution: results of a large, community‐based population study. Obesity. 32(9). 1778–1788. 3 indexed citations
6.
Wang, Congcong, et al.. (2023). Gut Microbiota and Adipose Tissue Microenvironment Interactions in Obesity. Metabolites. 13(7). 821–821. 7 indexed citations
7.
Yang, Fei, Wen‐Hui Lin, Eleanor Frost, et al.. (2021). Association between contact with a general practitioner and depressive symptoms during the COVID-19 pandemic and lockdown: a large community-based study in Hangzhou, China. BMJ Open. 11(8). e052383–e052383. 4 indexed citations
8.
Mukherjee, Pritam, Chao Huang, Mu Zhou, et al.. (2020). CT-based Radiomic Signatures for Predicting Histopathologic Features in Head and Neck Squamous Cell Carcinoma. Radiology Imaging Cancer. 2(3). e190039–e190039. 48 indexed citations
10.
Yang, Min, Jie Lin, Xiaoguang Ma, et al.. (2016). Truncal and leg fat associations with metabolic risk factors among Chinese adults.. PubMed. 25(4). 798–809. 9 indexed citations
11.
Fu, Xiaohua, Fei Zhu, Xinyu Zhao, Xiaoguang Ma, & Shankuan Zhu. (2014). Central Fat Accumulation Associated with Metabolic Risks beyond Total Fat in Normal BMI Chinese Adults. Annals of Nutrition and Metabolism. 64(2). 93–100. 14 indexed citations
12.
Jin, Mingjuan, Bingbing Chen, Yingying Mao, et al.. (2013). Prevalence of Overweight and Obesity and Their Associations with Socioeconomic Status in a Rural Han Chinese Adult Population. PLoS ONE. 8(11). e79946–e79946. 31 indexed citations
13.
Wang, ZiMian, Steven B. Heymsfield, Zhao Chen, Shankuan Zhu, & Richard N. Pierson. (2010). Estimation of percentage body fat by dual-energy x-ray absorptiometry: evaluation byin vivohuman elemental composition. Physics in Medicine and Biology. 55(9). 2619–2635. 48 indexed citations
14.
Fu, Xiaohua, Xiaoguang Ma, Han Lu, et al.. (2010). Associations of fat mass and fat distribution with bone mineral density in pre- and postmenopausal Chinese women. Osteoporosis International. 22(1). 113–119. 86 indexed citations
15.
Zhu, Shankuan, Jong‐Eun Kim, Xiaoguang Ma, et al.. (2010). BMI and Risk of Serious Upper Body Injury Following Motor Vehicle Crashes: Concordance of Real-World and Computer-Simulated Observations. PLoS Medicine. 7(3). e1000250–e1000250. 48 indexed citations
16.
Jiang, Fan, Shankuan Zhu, Chonghuai Yan, et al.. (2009). Sleep and Obesity in Preschool Children. The Journal of Pediatrics. 154(6). 814–818. 107 indexed citations
17.
Layde, Peter M., et al.. (2009). The Association of Driver Age with Traffic Injury Severity in Wisconsin. Traffic Injury Prevention. 10(4). 361–367. 43 indexed citations
18.
Heng, Kenneth Wei Jian, et al.. (2006). The elderly and motor vehicle crashes. Zhonghua jizhen yixue zazhi. 15(1). 6–12. 3 indexed citations
19.
Heng, Kenneth Wei Jian, et al.. (2006). MODERATE ALCOHOL INTAKE AND MOTOR VEHICLE CRASHES: THE CONFLICT BETWEEN HEALTH ADVANTAGE AND AT-RISK USE. Alcohol and Alcoholism. 41(4). 451–454. 35 indexed citations
20.
Sauter, Carley, Shankuan Zhu, Shelley Allen, Stephen Hargarten, & Peter M. Layde. (2005). Increased risk of death or disability in unhelmeted Wisconsin motorcyclists.. PubMed. 104(2). 39–44. 35 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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