Health Promotion and Human Behavior (Professional Degree Course / Latter Doctral Course)
Kosuke Inoue, MD, PhD
In this department, we generate evidence to advance health promotion by applying analytical methods such as causal inference and machine learning to randomized controlled trials and observational data, while also incorporating perspectives from behavioral science.
Regardless of your specialty or background, if you are interested in exploring questions such as “Why does a particular intervention or policy improve health?” and “For whom is it most effective?”, please feel free to reach out to us.
Research and Education
We integrate causal inference and machine learning to advance next-generation personalized strategies for prevention and health promotion. Beyond the traditional “high-risk approach,” we propose a “high-benefit approach” that leverages treatment effect heterogeneity to improve resource allocation and reduce health disparities. Our research extends from lifestyle-related and other chronic diseases to broader social and environmental determinants, with the goal of establishing a new framework for personalized public health. We also pursue practical research that bridges clinical medicine, public health, and social implementation, including optimizing interventions informed by health behavior theory and behavioral economics, supporting behavior change through smartphone applications, and evaluating intervention effectiveness via international collaborations.
In education, we focus on cultivating expertise that connects epidemiology, clinical medicine, and basic sciences. Graduate students are guided from research design to publication in leading journals, with several theses published internationally. Through active collaboration and researcher exchange with institutions such as UCLA, Harvard, and Yale, we foster the next generation of leaders in public health and epidemiology in Japan and worldwide.
Keywords
- Application of causal inference and machine learning
- Elucidation of causal mechanisms
- Epidemiology of endocrine-metabolic and cardiovascular diseases
- Health services research
- Personalized medicine and public health
- International collaborative research
https://amzn.asia/d/hrxqXp9
- Japanese：https://www.youtube.com/watch?v=V6jibdooExc
- English：https://youtu.be/R1laez0kcFY
Key Publications
- Inoue K, Athey S, Baicker K, Tsugawa Y. Heterogeneous effects of Medicaid coverage on cardiovascular risk factors: secondary analysis of randomized controlled trial. BMJ. 2024; 386: e079377.
- Inoue K, Athey S, Tsugawa Y. Machine-learning-based high-benefit approach versus conventional high-risk approach in blood pressure management. Int J Epidemiol. 2023;52(4):1243-1256
- Inoue K, Seeman T, Horwich T, Budoff M, Watson KE. Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine Learning Approach in the MESA Study. Circulation. 2022;147(2):132-141
- Inoue K, Saliba D, Gotanda H, Moin T, Mangione CM, Klomhaus AM, Tsugawa Y. Glucagon-Like Peptide-1 Receptor Agonists and Incidence of Dementia Among Older Adults With Type 2 Diabetes : A Target Trial Emulation. Ann Intern Med. 2025. Online ahead of print.
- Furukawa TA, Tajika A, Toyomoto R, Sakata M, Luo Y, Horikoshi M, Akechi T, Kawakami N, Nakayama T, Kondo N, Fukuma S, Kessler RC, Christensen H, Whitton A, Nahum-Shani I, Lutz W, Cuijpers P, Wason JMS, Noma H. Cognitive behavioral therapy skills via a smartphone app for subthreshold depression among adults in the community: the RESiLIENT randomized controlled trial. Nat Med. 2025 Jun;31(6):1830-1839.
Health Promotion and Human Behavior
Professor: Kosuke Inoue
Associate Professor: Aran Tajika
Assistant Professor: Rie Toyomoto
TEL: 075-753-9491
FAX: 075-753-4641
Email: 
URL:https://endoepi.net/