Nan Luo

14.8k total citations · 5 hit papers
323 papers, 9.0k citations indexed

About

Nan Luo is a scholar working on Economics and Econometrics, General Health Professions and Sociology and Political Science. According to data from OpenAlex, Nan Luo has authored 323 papers receiving a total of 9.0k indexed citations (citations by other indexed papers that have themselves been cited), including 182 papers in Economics and Econometrics, 95 papers in General Health Professions and 41 papers in Sociology and Political Science. Recurrent topics in Nan Luo's work include Health Systems, Economic Evaluations, Quality of Life (181 papers), Healthcare Policy and Management (52 papers) and Economic and Environmental Valuation (43 papers). Nan Luo is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (181 papers), Healthcare Policy and Management (52 papers) and Economic and Environmental Valuation (43 papers). Nan Luo collaborates with scholars based in Singapore, China and United States. Nan Luo's co-authors include Jeffrey Johnson, Julian Thumboo, Stephen Joel Coons, Kim Rand, James W. Shaw, Gordon Liu, Gouke J. Bonsel, Mathieu F. Janssen, Philip Yap and Zhihao Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Nan Luo

308 papers receiving 8.8k citations

Hit Papers

Estimating an EQ-5D-5L Value Set for China 2014 2026 2018 2022 2017 2016 2022 2014 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nan Luo Singapore 48 3.5k 2.1k 957 901 808 323 9.0k
Silvia Evers Netherlands 48 2.5k 0.7× 2.2k 1.0× 1.3k 1.4× 558 0.6× 1.5k 1.8× 437 10.1k
Andrew Lloyd United Kingdom 37 4.3k 1.2× 2.5k 1.2× 1.4k 1.4× 692 0.8× 1.3k 1.6× 175 13.2k
Daniel Polsky United States 47 3.4k 1.0× 3.4k 1.6× 1.1k 1.1× 340 0.4× 492 0.6× 255 8.4k
Stirling Bryan Canada 53 3.3k 0.9× 2.5k 1.2× 927 1.0× 359 0.4× 917 1.1× 267 10.4k
Darren M. Ashcroft United Kingdom 63 1.5k 0.4× 2.4k 1.2× 1.3k 1.4× 472 0.5× 1.1k 1.3× 464 17.0k
Christopher B. Forrest United States 54 1.4k 0.4× 3.1k 1.5× 1.0k 1.1× 576 0.6× 740 0.9× 264 9.9k
Todd H. Wagner United States 51 1.8k 0.5× 3.5k 1.6× 2.2k 2.3× 610 0.7× 881 1.1× 241 11.5k
Roger T. Anderson United States 45 1.5k 0.4× 2.0k 0.9× 1.3k 1.3× 487 0.5× 460 0.6× 226 8.0k
Jeff Richardson Australia 46 3.9k 1.1× 2.8k 1.3× 493 0.5× 404 0.4× 469 0.6× 261 7.1k
Howard Bergman Canada 50 2.9k 0.8× 2.8k 1.3× 1.2k 1.3× 377 0.4× 2.1k 2.6× 195 12.2k

Countries citing papers authored by Nan Luo

Since Specialization
Citations

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

Fields of papers citing papers by Nan Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nan Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Nan Luo. A scholar is included among the top collaborators of Nan Luo 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 Nan Luo. Nan Luo 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.
Luo, Nan, Ling Jie Cheng, Zhihao Yang, et al.. (2025). Developing an EQ-5D-5L Value Set for Singapore. PharmacoEconomics. 43(12). 1419–1431. 3 indexed citations
4.
Sun, Sun, Erik Stenberg, Nan Luo, et al.. (2024). SF-6D Normative Values Among Patients Undergoing Bariatric Surgery: Results Based on Real-World Evidence from the Scandinavian Obesity Surgery Registry (SOReg). Obesity Surgery. 34(2). 558–567. 2 indexed citations
5.
Li, Jing, Zhuxin Mao, Zitong Wang, et al.. (2024). Psychometric performance of EQ-5D-5L and SF-6Dv2 in patients with lymphoma in China. The European Journal of Health Economics. 25(9). 1471–1484. 5 indexed citations
6.
Cheng, Ling Jie, et al.. (2024). The Ceiling Effects of EQ-5D-3L and 5L in General Population Health Surveys: A Systematic Review and Meta-Analysis. Value in Health. 27(7). 986–997. 11 indexed citations
7.
Wu, Shuang, et al.. (2024). Care models for patients with heart failure at home: A systematic review. Journal of Clinical Nursing. 33(4). 1295–1305. 5 indexed citations
8.
Mao, Zhuxin, et al.. (2024). Developing and testing culturally relevant bolt-on items for EQ-5D-5L in Chinese populations: a mixed-methods study protocol. BMJ Open. 14(1). e081140–e081140. 5 indexed citations
9.
Gandhi, Mihir, Ravindran Kanesvaran, Dawn Q. Chong, et al.. (2024). Valuation of the EORTC Quality of Life Utility Core 10 Dimensions (QLU-C10D) in a Multi-ethnic Asian Setting: How Does Having Cancer Matter?. PharmacoEconomics. 42(12). 1413–1425. 2 indexed citations
10.
Wang, Xinghui, et al.. (2024). Development and validation of machine learning models to predict frailty risk for elderly. Journal of Advanced Nursing. 80(12). 5064–5075. 3 indexed citations
11.
Luo, Nan, et al.. (2023). Urban/rural differences in preferences for EQ-5D-5L health states: a study of a multi-ethnic region in China. Quality of Life Research. 32(8). 2329–2339. 3 indexed citations
12.
Tang, Eric Ho Man, Yu Cho Woo, Cindy Lo Kuen Lam, et al.. (2023). Psychometric properties of EQ-5D-5L for use in patients with Graves’ disease. Health and Quality of Life Outcomes. 21(1). 90–90. 4 indexed citations
13.
Cheng, Ling Jie, Nick Bansback, Xi Vivien Wu, et al.. (2023). Patient decision support interventions for candidates considering elective surgeries: a systematic review and meta-analysis. International Journal of Surgery. 109(5). 1382–1399. 5 indexed citations
15.
Zhou, Yanfeng, Xingyue Song, Xiong‐Fei Pan, et al.. (2021). Association Between Combined Lifestyle Factors and Healthy Ageing in Chinese Adults: The Singapore Chinese Health Study. The Journals of Gerontology Series A. 76(10). 1796–1805. 20 indexed citations
16.
Liu, Dongfang, Nan Luo, Tingting Liu, et al.. (2021). Key Candidate Prognostic Biomarkers Correlated with Immune Infiltration in Hepatocellular Carcinoma. SHILAP Revista de lepidopterología. Volume 8. 1607–1622. 8 indexed citations
17.
Yang, Fan, Nancy Devlin, & Nan Luo. (2018). Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments. The European Journal of Health Economics. 20(1). 99–105. 9 indexed citations
18.
Lin, Fang‐Ju, Churn‐Shiouh Gau, Nan Luo, et al.. (2018). Valuation of the EQ-5D-5L in Taiwan. PLoS ONE. 13(12). e0209344–e0209344. 49 indexed citations
19.
Gandhi, Mihir, Ru‐San Tan, Raymond Ng, et al.. (2017). Comparison of health state values derived from patients and individuals from the general population. Quality of Life Research. 26(12). 3353–3363. 13 indexed citations
20.
Luo, Nan, et al.. (2003). Identification of Factors Influencing Caregiving Experience in Caregivers of Patients with Schizophrenia. Annals of the Academy of Medicine Singapore. 32(5 Suppl). S43–S45. 1 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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