Characteristics and structural imbalances of biomedical academicians in China: policy implications for the governance of leading medical talents
4 affiliations
- 1Department of Ultrasound Medicine, Tianyou Hospital Affiliated to Wuhan University of Science and Technology
- 2Management School, Sheffield University
- 3School of Law and Economics, Wuhan University of Science and Technology
- 4Health Examination Center, Tianyou Hospital Affiliated to Wuhan University of Science and Technology
Abstract
Background: Against the backdrop of intense global competition in biomedical science, leading biomedical talents constitute core determinants of national strategic science and technology capacity and effective health workforce governance. Nevertheless, large-sample empirical research on career trajectories and structural disparities among China’s elite biomedical academics remains limited, constraining evidence-based talent policy refinement.
Methods: This retrospective study included 284 biomedical academicians listed on the official websites of the Chinese Academy of Sciences (CAS) and the Chinese Academy of Engineering (CAE) as of July 1, 2025. Drawing on publicly available data on demographics, educational background, mentorship, and institutional affiliations, it systematically characterized the distribution of top-tier talent and the factors influencing age at election, using descriptive statistics, hypothesis testing, and multiple linear regression analysis.
Results: The average age at election for CAS biomedical academicians was significantly lower than that for CAE academicians ( p < 0.001). Female academicians constituted only 12.68% (36/284) of the total sample. A significant geographical clustering was observed in the birthplaces and upbringing regions of the academicians. Univariate analysis showed that academicians holding overseas doctoral degrees or supervised by academicians were elected at younger ages. However, after adjustment for confounders in multiple linear regression, overseas doctoral degree was not independently associated with age at election (β = −0.109, p = 0.071). In contrast, highest degree attainment and supervised by academicians remained statistically significant predictors. Over half of the academicians were employed by universities, revealing an imbalance in the ratio of Basic Medical Sciences to Clinical Medicine talent. The educational attainment of academicians in the <50 and 50–65 age groups was significantly higher than that of those over 65 ( p < 0.05).
Conclusion: Chinese biomedical academician cohort exhibits substantial structural imbalances across gender, geography, age, and academic career trajectories. Drawing on the WHO global health workforce governance framework, this study proposes governance insights across three dimensions: national top-level policy design, institutional platform development, and early-career talent cultivation. These findings may inform future policy research and empirical evaluation.
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BibTeX
@article{liu2026characteristics,
title = {{Characteristics and structural imbalances of biomedical academicians in China: policy implications for the governance of leading medical talents}},
author = {Rong Liu and De Fei Huang and Tao Huang and Tian Lan Hu},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1944514},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1944514/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Characteristics and structural imbalances of biomedical academicians in China: policy implications for the governance of leading medical talents
AU - Rong Liu
AU - De Fei Huang
AU - Tao Huang
AU - Tian Lan Hu
PY - 2026
DA - 2026/10/23
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1944514
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1944514/full
AB - Background: Against the backdrop of intense global competition in biomedical science, leading biomedical talents constitute core determinants of national strategic science and technology capacity and effective health workforce governance. Nevertheless, large-sample empirical research on career trajectories and structural disparities among China’s elite biomedical academics remains limited, constraining evidence-based talent policy refinement. Methods: This retrospective study included 284 biomedical academicians listed on the official websites of the Chinese Academy of Sciences (CAS) and the Chinese Academy of Engineering (CAE) as of July 1, 2025. Drawing on publicly available data on demographics, educational background, mentorship, and institutional affiliations, it systematically characterized the distribution of top-tier talent and the factors influencing age at election, using descriptive statistics, hypothesis testing, and multiple linear regression analysis. Results: The average age at election for CAS biomedical academicians was significantly lower than that for CAE academicians ( p < 0.001). Female academicians constituted only 12.68% (36/284) of the total sample. A significant geographical clustering was observed in the birthplaces and upbringing regions of the academicians. Univariate analysis showed that academicians holding overseas doctoral degrees or supervised by academicians were elected at younger ages. However, after adjustment for confounders in multiple linear regression, overseas doctoral degree was not independently associated with age at election (β = −0.109, p = 0.071). In contrast, highest degree attainment and supervised by academicians remained statistically significant predictors. Over half of the academicians were employed by universities, revealing an imbalance in the ratio of Basic Medical Sciences to Clinical Medicine talent. The educational attainment of academicians in the <50 and 50–65 age groups was significantly higher than that of those over 65 ( p < 0.05). Conclusion: Chinese biomedical academician cohort exhibits substantial structural imbalances across gender, geography, age, and academic career trajectories. Drawing on the WHO global health workforce governance framework, this study proposes governance insights across three dimensions: national top-level policy design, institutional platform development, and early-career talent cultivation. These findings may inform future policy research and empirical evaluation.
SN - 2296-2565
ER -