ORGANISATION/COMPANYUniversité Clermont Auvergne
RESEARCH FIELDBiological sciencesMathematics
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE28/06/2020 00:00 - Europe/Brussels
LOCATIONFrance › Saint Genès Champanelle
TYPE OF CONTRACTTemporary
HOURS PER WEEK35 H
OFFER STARTING DATE01/10/2020
IS THE JOB RELATED TO STAFF POSITION WITHIN A RESEARCH INFRASTRUCTURE?Yes
Subject: Design of e-health tools dedicated to the early detection of eating
behaviours associated with body weight gain
Supervisor: Sylvie Rousset
Laboratory: Unité de Nutrition Humaine UMR 1019 Clermont-Ferrand
Email and phone: email@example.com, Tel : 04 73 62 46 79 ou 06 74 40
Co-advisor(s): Anthony Fardet & Yves Boirie
Abstract (up to 10 lines):
The aim of the thesis is to design a body weight gain risk index. To build this
index, we will use data already acquired via the WellBeNet smartphone
application and from food purchase data. WellBeNet collects food choices
and estimates energy expenditure. The first research study will consist of
evaluating the energy intake of food portions according to energy
expenditure. The 2nd study will characterize food choices and meal context
as a function of weight status. A 3rd study will establish the link between the
food choices filled in the application, purchases and a variation in weight
status. Based on all these data, a weight gain risk index will be developed.
The candidate must have a background in human nutrition. He/she should
have a strong background in statistics and multivariate data analysis.
Writing skills in French and English are also essential.
Food behavior and purchase; Food intake and energy expenditure; e-
Health; Weight gain; Machine learning; Health; Free living conditions
Description (up to 1 page):
The health trajectories of individuals depend largely, beyond genetic
determinisms, on their lifestyles (Shuval et al., 2015). Food plays a major role
in the health status of individuals. An unbalanced diet, mainly rich in ultra
processed food products over a long period of time, could induce weight gain
and lead to obesity (Fardet, 2018; Fardet et al., 2019). In epidemiological
studies, food intake is usually collected through dietary surveys. Many
studies have shown that surveys are subject to oommissions and estimation
biases (Naska et al. 2017). Our hypothesis is that indirect methods for
estimating food intake could be developed based on energy expenditure on
the one hand and food purchases on the other. Indeed, the maintenance of a
stable weight implies that food intakes cover energy requirements, and food
consumption is directly related to food purchases. These indirect methods
could be used to develop a weight gain risk index.
INRAe has a scientifically validated tool for accurately estimating energy
expenditure. This tool consists of the WellBeNet smartphone application and
a data processing and storage server. The tool allows the evaluation of
activity behaviour (eMouve) and food intake (NutriQuantic). The eMouve tab
collects accelerometry data to evaluate the duration of sedentary and
physical activity and to deduce the associated energy expenditure. These
estimates come from algorithms designed distinctly for normal-weight and
overweight adult populations and have been scientifically validated against
reference methods (Guidoux et al., 2017; Rousset et al., 2017; Rousset et al.,
2018). The NutriQuantic tab allows a quick input of the social context of food
intake (date and time, with whom and where), food choices expressed in
portions in 12 food categories (fruit, vegetables, alcohol ...).
The objective of the thesis is to design a body weight gain risk index based
on behavioral data. To build this index, we will use data already acquired via
the WellBeNet smartphone application and from food purchase data.
WellBeNet collects food choices and estimates energy expenditure. The first
research study will consist of evaluating statistically the mean energy intake
of food portions according to energy expenditure (6 months). The 2nd study
will characterize food choices and meal context (time, with whom and
where) as a function of weight status (6 months). A third study, consisting of
2 surveys 6 months apart, will establish the link between food choices made
in the application, purchases and a variation in weight status (12 months).
From all these data, a weight gain risk index will be developed (6 months).
The last 6 months will be devoted to writing the manuscript and publications.
References (up to ½ page):
Fardet A. (2018) Characterization of the degree of food processing in
relation with its health potential and effects. Adv Food Nutr Res. 85:79-129.
Fardet A, Richonnet C & Mazur A. (2019). Association between
consumption of fruit or processed fruit and chronic diseases and their risk
factors: a systematic review of meta-analyses Nutr Rev. 77(6):376-387.
Guidoux R, Duclos M, Fleury G, Lacomme P, Lamaudière N, Saboul D,
Ren L & Rousset S (2017). The eMouveRecherche application competes
with research devices to evaluate energy expenditure, physical activity and
still time in free-living conditions. Journal of Biomedical Informatics 69,
Naska A, Lagiou A, Lagiou P. (2017). Dietary assessment methods in
epidemiological research: Current state of the art and future Prospects.
Food1000Research, 926, 1:8.
Rousset S, Guidoux R, Paris L, Farigon N, Boirie Y, Lacomme P, Phan R,
Ren L, Saboul D & Duclos M. (2018). eMouveRecherche: the first scientific
application to promote light-intensity activity for the prevention of chronic
diseases. Biology, Engineering and Medicine 3, (1), 1-6.
Rousset S, Guidoux R, Paris L, Farigon N, Miolanne M, Lahaye C,
Duclos M, Boirie Y & Saboul D (2017). A novel smartphone accelerometer
application for low-intensity activity and energy expenditure estimations in
overweight and obese adults. Journal of Medical Systems 41 (117), 1-10.
Shuval K, Nguyen BT, Yaroch AL, Drope J & Gabriel KP (2015).
Accelerometer determined sedentary behavior and dietary quality among
US adults. Preventive Medicine, 78, 38-43.
How to candidate?
Contact the supervisor
Email : firstname.lastname@example.org
Tel : 04 73 62 46 79 ou 06 74 40 20 52
INRAe Unité de Nutrition Humaine UMR 1019 route de Theix 63122 Saint
REQUIRED EDUCATION LEVELOther: Master Degree or equivalent
EURAXESS offer ID: 528408
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