Tshewang Gyeltshen

Tshewang Gyeltshen

Doctoral Candidate in Global Health Policy, School of International Health, The University of Tokyo

Basic Tools of Population Health Research

Graduate Level International Health Course, The University of Tokyo, School of International Health, Department of Global Health Policy, 2025

Teaching Assistant, Spring 2025The University of Tokyo, School of International Health, Department of Global Health Policy

I facilitated a class for the course “Basic Tools of Population Health Research” offered by the Department of Global Health Policy, School of International Health, The University of Tokyo.

This intensive module is designed to introduce students to the fundamental principles of epidemiology and medical statistics, with a strong emphasis on applying these tools in public health research.

My Role

  • Facilitated both conceptual lectures and applied practical sessions.
  • Guided students in key areas such as confounding, stratification, and effect modification.
  • Supported integration of statistical software (R) in hands-on exercises, helping students run analyses, interpret outputs, and troubleshoot coding issues.
  • Encouraged students to critically engage with epidemiological methods, interpret population health data, and build foundational skills essential for evidence-based research.

Course Outline

Measuring Health and Disease

Measures of incidence, prevalence, and risk.

Descriptive, Ecological, and Cross-sectional Studies

Study designs and measures of effect.

Confounding and Effect Modification

Identification and methods to address them.

Bias, Precision, and Causality

Understanding systematic error and principles of causal inference.

Intervention Studies

Designs and evaluation.

Cohort and Case-Control Studies

Comparative strengths and limitations.

Sampling Methods and Sample Size Calculation

Survey designs and statistical planning.

Statistical Methods

  • Data distributions and probability
  • Hypothesis testing
  • Chi-square test, t-test, ANOVA
  • Correlation and regression (linear, logistic, multiple)
  • Introduction to statistical modelling

Applied R Training

Integration of R programming for epidemiological and statistical analysis.

Final Presentations and Assessment

Group presentations, quizzes, and final assessment combining multiple-choice and open-ended questions.

Readings

Required

  • Celentano DD, Szklo M. Gordis Epidemiology (6th ed., 2018).
  • Kirkwood BR, Sterne JAC. Essential Medical Statistics (2nd ed., 2001).

Recommended

  • Bonita R, Beaglehole R, Kjellstrom T. Basic Epidemiology (2nd ed., WHO, 2006).
  • Lash TL, VanderWeele TJ, Haneuse S, Rothman KJ. Modern Epidemiology (4th ed., 2021).
  • Additional references from WHO, IARC, and Oxford University Press.