6th CEN Conference

Session

Methods in epidemiology 1

20 May 2026, 10:45

Room 12

Conveners

Methods in epidemiology 1

• Werner Vach (Basel Academy for Quality and Research in Medicin)

156. Inferring the causal effect direction in genetic association studies: An application to broad depression, obesity, and asthma

Sharon Lutz (Harvard Medical School)

20/05/2026, 10:45

oral presentation

In genetic association studies, Mendelian Randomization (MR) is a popular tool for inferring causal relationships between traits using genetic variants as instrumental variables. Recent methods have been proposed as tools that can infer the causal direction between two phenotypes including MR Steiger, bidirectional MR, causal direction-ratio, causal direction-Egger, and causal direction-GLS....

144. Methodological and Practical Challenges in Developing a Cardiac Allocation Score

Leonie Lenz-Seraphin (Medical University Vienna, Center for Medical Data Science, Institute of Clinical Biometrics)

20/05/2026, 11:03

oral presentation

Heart transplantation is widely regarded as the gold standard for the treatment of end-stage heart failure. However, shortages of donor hearts necessitate the implementation of waiting lists and allocation algorithms. The German Transplantation Law stipulates the allocation of donor hearts based on urgency of and the benefit from a transplantation. This can be summarized into a single score,...

177. Timeliness of Polio Vaccination during 2019-21 in India: A finite mixture modeling analysis

Sumit Das (Scientist - I, All India Institute of Medical Sciences (AIIMS))

20/05/2026, 11:21

oral presentation

Background: Childhood immunization influences directly and indirectly fourteen out of the seventeen sustainable development goals (SDGs). Timely receipt of vaccines protects children from deadly diseases and increases the overall future productivity of the population. With the largest and most heterogeneous population of under-five children, the delay in receiving polio vaccination has not...

70. Advancing mixed-effects random forests to predict BMI development in children and adolescents based on multi-cohort data

Jiumeng Zhang (Leibniz-Institute for Prevention Research and Epidemiology - BIPS)

20/05/2026, 11:39

oral presentation

Mixed-effects models (MEMs) are widely used in epidemiology to analyze data not being independent and identically distributed (i.i.d.) like longitudinal data. However, MEMs rely on parametric assumptions and require predefined interactions among predictors. In contrast, machine learning (ML) methods such as random forests (RF) assume i.i.d. data but are more flexible in capturing nonlinear...

180. Estimating prevalence of micronutrient deficiency across multiple biomarkers: Approaches for generalized linear and linear mixed models

Steffen Hadasch (National Institute of Public Health, University of Southern Denmark)

20/05/2026, 11:57

oral presentation

Assessing micronutrient status is essential in nutritional research (Allen, 2025) and typically involves estimating the population wide prevalence of micronutrient deficiencies using biomarker data collected across multiple regions. In such studies, several biomarkers are commonly analyzed to estimate the prevalence of any deficiency, defined as the probability that at least one of the...