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Master Thesis: Swiss FoodTracker – App Validation Study
We plan to validate a salt/sodium intake tracking app called "Swiss FoodTracker". The app was completed in 2017 and during this thesis, we will compare its salt intake estimate versus state of the art instruments, such as paper-based and urine-sampling based methods and measure the app's accuracy.
Today, diet-related non-communicable diseases account for more deaths than all non-diet-related mortality causes combined. In Switzerland, 94% of men and 77% of women exceed the World Health Organization’s recommendation of 5g Salt per day – Swiss men consume on average 10.6 g (112% above 5 g/day), women 8.1 g/day (62% above 5 g/day) respectively. The consequences are dramatic: As sodium is a key driver for cardiovascular diseases, excessive salt intake can trigger hypertension, heart failure, kidney and other sodium-related diseases which take a significant toll on patients and the health-care system. Our project “Swiss FoodTracker” aims to estimate a per-son’s salt intake based on self-reported dietary intake, thereby promising better affordability and scalability when compared to existing measurement instruments, such as paper surveys & urine sampling. Patients enter their diet within the app – the app will then return an estimation for the user’s dietary salt intake and whether the respective value is healthy, increased, or unhealthy. We want to validate, how accurately “Swiss FoodTracker” can estimate a user’s salt intake.
Today, diet-related non-communicable diseases account for more deaths than all non-diet-related mortality causes combined. In Switzerland, 94% of men and 77% of women exceed the World Health Organization’s recommendation of 5g Salt per day – Swiss men consume on average 10.6 g (112% above 5 g/day), women 8.1 g/day (62% above 5 g/day) respectively. The consequences are dramatic: As sodium is a key driver for cardiovascular diseases, excessive salt intake can trigger hypertension, heart failure, kidney and other sodium-related diseases which take a significant toll on patients and the health-care system. Our project “Swiss FoodTracker” aims to estimate a per-son’s salt intake based on self-reported dietary intake, thereby promising better affordability and scalability when compared to existing measurement instruments, such as paper surveys & urine sampling. Patients enter their diet within the app – the app will then return an estimation for the user’s dietary salt intake and whether the respective value is healthy, increased, or unhealthy. We want to validate, how accurately “Swiss FoodTracker” can estimate a user’s salt intake.
The “Swiss FoodTracker” app has been completed in 2017 and its validity to estimate sodium intake has already been successfully shown in multiple small pre-studies. Now it is our task to validate the app in a larger setup (N > 50): Therefore, we will recruit volunteers for a validation study: The users will i) track their diet in the app and ii) on paper and iii) in addition participate in a urine sampling study, as this is the state-of-the-art method for salt intake measurement. We will then compare the i) app’s estimate versus ii) the paper’s and iii) the urine sample’s intake assessment. You will compile a quantitative validation of the mobile app versus both existing state-of-the-art sodium intake assessments. You have the chance to become a co-author of a scientific paper in a top conference or journal.
You are
- interested in medicine, health and technology
- you are familiar with statistical concepts, e.g.: Boxplots, Bland Altman, Forest plot, Linear Regression
- capable of reading scientific articles & motivated to participate on current research
The “Swiss FoodTracker” app has been completed in 2017 and its validity to estimate sodium intake has already been successfully shown in multiple small pre-studies. Now it is our task to validate the app in a larger setup (N > 50): Therefore, we will recruit volunteers for a validation study: The users will i) track their diet in the app and ii) on paper and iii) in addition participate in a urine sampling study, as this is the state-of-the-art method for salt intake measurement. We will then compare the i) app’s estimate versus ii) the paper’s and iii) the urine sample’s intake assessment. You will compile a quantitative validation of the mobile app versus both existing state-of-the-art sodium intake assessments. You have the chance to become a co-author of a scientific paper in a top conference or journal.
You are - interested in medicine, health and technology - you are familiar with statistical concepts, e.g.: Boxplots, Bland Altman, Forest plot, Linear Regression - capable of reading scientific articles & motivated to participate on current research
Klaus Fuchs
ETH Zürich, D-MTEC
Weinbergstrasse 56/58
8092 Zürich
Phone: +41 44 633 89 15
fuchsk@ethz.ch
www.autoidlabs.ch
www.im.ethz.ch
Klaus Fuchs ETH Zürich, D-MTEC Weinbergstrasse 56/58 8092 Zürich