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Institute of Evolutionary Medicine (IEM) Anthropometrics & Historical Epidemiology ☛ Prof. Kaspar Staub

Population health then and now: Historical epidemiology, body height, excess weight

Historical Epidemiology: Morbidity and mortality, 1850-1950

This strand of research unites under one umbrella smaller sub-projects on the spread of the Spanish Flu in the Canton of Bern 1918/1919, on sanitary reforms and the reduction of typhoid fever in Swiss cities 1876-1930, on hunger and its traces in the human body during World War 1, on cholera epidemics in Basel and Zürich 1850-1860, and on endemic iodine deficiency in Switzerland and its impact on health during the first half of the 20th century. The common goal of these subprojects is to learn from past experiences for modern public health.

Monitoring excess weight in Switzerland from an evolutionary perspective

This research strand is focused on overweight and obesity (excess weight) in Switzerland. By adding the evolutionary perspective, we want to better understand the reasons behind this health issue (life-history theory, etc.). We analyse modern population monitoring data (schoolchildren and conscripts) and population-based surveys (e.g., menuCH) and identify groups at risk. A special focus is given to small-area patterns, also in combination with other data sets (Swiss Food Panel, Migros sales data, etc.

Changing body height over the past 200 years

In this project we analyse secular trends in height and growth in Switzerland (and other countries) over the past 200 years. We combine monitoring data (size at birth, schoolchildren, conscripts) and survey data. We are particularly interested in socioeconomic/regional differences, inter-generational effects, and various determinants/consequences of human height. We are currently also developing an online teaching tool, which is dedicated to height.

3D full body surface scans as a new technique to monitor body shape

3D laser-based photonic full body scans create a detailed surface image of the human body consisting of up to 300 data points per cmwithin 10-12 seconds. The technique provides automatic information on a number of whole body or body-part circumferences, surfaces and volumes as well as body height and weight in a fast, non-invasive and comfortable way for patients. We are working on the following questions: What can we learn from the 3D point cloud as a whole to predict body composition and thus disease risk? Are there systematic differences compared to manual anthropometry? Which is the best way to compare follow-up scans from an individual over time? The medium-termed goal is to use 3D scans as a valuable asset in running or future panel/cohort studies and to enhance basic knowledge about the technique before smart phones will be able to take 3D full body scans in the near future.

Link to our 3D Body Scan Lab.