Mrs. LI Ruixiang | Epidemiology | Editorial Board Member
Professor | Affiliated Hospital of Shandong Second Medical University | China
Mrs. Li Ruixiang is an emerging researcher whose work advances maternal–child health, neonatal nutrition, and early-life growth assessment through rigorous quantitative and engineering-informed methodologies. Her scholarship includes key contributions to understanding threshold effects of third-trimester maternal vitamin A status on neonatal ponderal index, published in Food Science & Nutrition, and the development of computer-assisted methods for evaluating early physical linear growth among small-for-gestational-age infants, featured in the Journal of Healthcare Engineering. These studies demonstrate her ability to integrate biomedical knowledge with advanced analytical approaches, generating evidence that supports more precise assessment of neonatal growth patterns and micronutrient-related developmental outcomes. Mrs. Li’s collaborative work with multidisciplinary teams—comprising nutritionists, paediatric clinicians, biomedical engineers, and public health experts—reflects her commitment to methodological innovation and translational research. Although still in the early stages of her academic career, she has contributed to a growing body of literature that strengthens global understanding of neonatal anthropometry, maternal nutrition, and data-driven modelling in child health. Her findings help inform clinical decision-making, contribute to improved detection of growth abnormalities, and support public health policies aimed at reducing early-life vulnerabilities. Through her focused research agenda and evidence-based analyses, Mrs. Li Ruixiang continues to build a research profile with meaningful societal relevance and potential for long-term impact on maternal and neonatal wellbeing.
Profiles: ORCID
Featured Publications
1. Ji, J., Cui, L., Ni, J., & Li, R. (2025). Threshold Effects of Third-Trimester Maternal Vitamin A on Neonatal Ponderal Index: A Segmented Regression Analysis of 442 Mother–Infant Pairs. Food Science & Nutrition.
2. Li, R., Yin, M., Cui, L., Zheng, R., & Malik Alazzam. (2021). Early Physical Linear Growth of Small-for-Gestational-Age Infants Based on Computer Analysis Method. Journal of Healthcare Engineering. Citations: 4