02/06/2020
The Human Resources Strategy for Researchers

PhD contract in the field of human nutrition and statistics and multivariate data analysis financed during 3 years by the University Clermont Auvergne

This job offer has expired


  • ORGANISATION/COMPANY
    Université Clermont Auvergne
  • RESEARCH FIELD
    Biological sciences
    Mathematics
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    28/06/2020 00:00 - Europe/Brussels
  • LOCATION
    France › Saint Genès Champanelle
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35 H
  • OFFER STARTING DATE
    01/10/2020
  • REFERENCE NUMBER
    UCA/ANR/002
  • IS THE JOB RELATED TO STAFF POSITION WITHIN A RESEARCH INFRASTRUCTURE?
    Yes

OFFER DESCRIPTION

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

(France)

Email and phone: sylvie.rousset@inrae.fr, Tel : 04 73 62 46 79 ou 06 74 40

20 52

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.

Skills:

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.

Keywords:

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,

128-124.

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

Sylvie Rousset

Email : sylvie.rousset@inrae.fr

Tel : 04 73 62 46 79 ou 06 74 40 20 52

INRAe Unité de Nutrition Humaine UMR 1019 route de Theix 63122 Saint

Genès Champanelle

 
 
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More Information

Benefits

 

 
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Eligibility criteria

 
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Selection process

 

 
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Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Other: Master Degree or equivalent

Skills/Qualifications

 

 
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Work location(s)
1 position(s) available at
Human Nutrition Unit (UNH)
France
Région Auvergne Rhône-Alpes
Saint Genès Champanelle
63122
1019 route de Theix

Open, Transparent, Merit based Recruitment procedures of Researchers (OTM-R)

Know more about it at Université Clermont Auvergne

Know more about OTM-R

EURAXESS offer ID: 528408

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