Evaluation of the Effect of the "Eat Less Meat" One-month Challenge on Meat Consumption Among French University Students
Phase: NA
Conditions: Diet, Healthy, Food Habits
Sponsor: Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

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Evaluation of the effect of the “Eat Less Meat” one-month challenge on meat consumption among 
French university students 
 
Date: January 31st, 2023 
Principal Investigator: Lucile Marty 
 
 

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Description: 
In a context where meat consumption should be dramatically reduced in western countries to 
improve both population and planet health, the “Eat Less Meat” one-month challenge is a new 
behavioural intervention that aims (i) to weaken meat consumption habit and (ii) to enhance 
intrinsic motivation to eat less meat to trigger long-term reduction in meat consumption. The 
present registration focusses on the quantitative evaluation of the effect of this challenge on 
university student’s meat consumption. 
 
STUDY INFORMATION 
Hypotheses 
Main hypothesis: 
H1: The “Eat Less Meat” challenge will have decreased meat consumption in participants during 
the challenge and 3 months after challenge completion compared to before. 
Secondary hypotheses:  
H2: The “Eat Less Meat” challenge will have increased (resp. decreased) nutritional quality (resp. 
environmental impact) of the diet in participants during the challenge and 3 months after 
challenge completion compared to before. 
H3: The “Eat Less Meat” challenge will have weakened meat consumption habits in participants 
during the challenge and 3 months after challenge completion compared to before. 
H4: The “Eat Less Meat” challenge will have increased health, ethics and animal welfare 
motivations for food choices in participants during the challenge and 3 months after challenge 
completion compared to before. 
Study design 
Parallel two-arm randomized controlled trial with repeated measures (online questionnaires) 
pre-, during- and post-intervention. All the participants will be recruited to take part in the “Eat 
Less Meat” challenge for one month. Participants in the control group will take part in the 
challenge 3 months after the participants in the intervention group. Participants in both groups 
will complete the online questionnaires at the exact same time, i.e., pre-, during- and post-
intervention measures will take place before the control group starts the challenge. A figure 
summarizing the study design is available in Appendix 1. 
Randomization 
A 1:1 randomisation sequence will be generated before recruitment using the Random 
Allocation software1 to allocate each participant to one of the experimental arm (control or 
intervention). 
 
SAMPLING PLAN 
Data collection procedures 
                                                          
1 Mahmood Saghaei, ‘Random Allocation Software for Parallel Group Randomized Trials’, BMC Medical 
Research Methodology, 4 (2004), 1–6 <https://doi.org/10.1186/1471-2288-4-26>. 

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Inclusion criteria. 
- 
Aged ≥ 18 
- 
BMI ≥ 18.5 
- 
University student in ‘Bourgogne Franche-Comté’ 
- 
Fluent in French 
- 
Available email address 
- 
Available Instagram profile 
- 
Not vegetarian or vegan or pescatarian 
- 
Not pregnant/breastfeeding 
- 
No iron deficiency 
Brief description of the “Eat Less Meat” challenge. 
Participants will be recruited through social media, emails, flyers and posters on campus to take 
part in the “Eat Less Meat” challenge; recruitment materials will mention that the challenge is 
part of a research study. Eligible participants that will give their informed consent will be able to 
choose their goal for the challenge for one month: (i) no meat, (ii) meat 3 times a week, (iii) 
meat 6 times a week (which will need to be lower than current consumption) and will be 
enrolled in the challenge. The ‘meat category’ includes all red meat and poultry but not fish or 
other animal-sourced food products (eggs, dairy, etc.). The first day of the challenge, the 
participants will receive by email a cookbook of easy-to-prepare and cheap meat-free recipes 
and a starter kit with advices and motivational tips, then they will receive an email each week 
with more advices and motivational tips. Participants will be also asked to follow the Instagram 
account of the challenge where during one month (i) one post will be posted each day, (ii) 
engaging stories requiring interactions will be posted regularly, (iii) participants can ask their 
questions to the research team, (iv) participants can interact with each other’s. The Instagram 
posts will cover three main topics: (i) knowledge about meat and its impact on health and 
environment, (ii) tips for meat-free cooking, (iii) social/contextual pressure to eat meat and how 
to avoid it. Emails and posts will aim at keeping the participants engaged in the one-month 
challenge and to enhance their intrinsic motivation to eat less meat. 
Data collection for evaluation. 
Eligible participants will be informed that their participation will involve completing a first online 
questionnaire on sociodemographics at the point of inclusion (10 min) and then three other 
online questionnaires at three time points: pre-, during- and post-intervention (30 min each 
time, 10€ compensation).  
Sample size 
As a minimum, we will aim to recruit 200 university students willing to take part in the 
challenge but we will include in the study all voluntary students that will register. Registrations 
will close the day before the challenge starts for the intervention group. 
Sample size rationale 
The sample size was determined based on a power analysis (GPower v3.1) to detect a small 
effect size of f=0.10 for a within-between interaction in a mixed model with 3 repeated 
measures. A total sample size of 164 participants was necessary to reach 0.80 power at 0.05 
alpha. Considering an attrition rate in between 15 and 20%, we will aim to recruit 200 
university students willing to take part in the challenge. 
 
VARIABLES 

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Manipulated variables 
We will manipulate whether participants will be assigned to intervention or control group 
(challenge 3 months after the intervention group). It will be coded as a binary variable: 
‘intervention’ or ‘control’ at the participant level. 
Measured variables 
The sociodemographics questionnaire will record age, gender, scholarship status, educational 
level, field, parents’ educational level, place of living, dieting status and type of diet. 
The evaluation questionnaires will record three types of variables at the three time points: 
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Food consumption frequency 
The food frequency questionnaire (FFQ) will include 109 foods, 12 non-alcoholic drinks and 4 
alcoholic drinks with frequency assessed by a 6-item scale from “Never” to “Several times a 
day”2.  Participants will estimate their usual portion size for 75 food items using photos on a 5-
point scale derived from the SU.VI.MAX portion book3. For the 50 remaining food items, we will 
use the standard portion size. Consumption frequencies of each item will be transformed into 
daily frequencies and daily intake will be calculated by multiplying the daily frequency by the 
estimated portion size. Individual nutrients intake will then be calculated for all the participants 
before and during the lockdown by multiplying the daily intake of each food item by the 
nutritional values from the SU.VI.MAX nutrient composition database4. Participants will be asked 
about their food consumption for the month before questionnaire completion, i.e., the month 
before the challenge, the month of the challenge and the third month after the challenge for the 
intervention group (all the measures will take place before the control group start the 
challenge). 
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Meat consumption habit 
The strength of meat consumption habit will be assessed using the Self-Report Habit 
questionnaire5 including 12 items accompanied by a 6-point response scale anchored by 
‘strongly disagree’ and ‘strongly agree’ from 1 to 6. The scores will be coded such that high 
values indicated strong habits. Participants will be asked about their meat consumption habit at 
the time of questionnaire completion. 
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Food choice motives 
The food choice questionnaire (FCQ) will be the adapted French version of the Food Choice 
Questionnaire6. It includes 30 items and 10 subscales: health, mood, convenience, sensory 
appeal, natural content, price, weight control, familiarity, ethical concern and animal welfare. 
Answers to each item will range from 1 to 4: 1 = Not at all important; 2 = A little important; 3 
                                                          
2 Manik Kadawathagedara and others, ‘Diet during Pregnancy: Influence of Social Characteristics and Migration 
in the ELFE Cohort’, Maternal and Child Nutrition, 17.3 (2021), 1–13 <https://doi.org/10.1111/mcn.13140>. 
3 S Hercberg, M Deheeger, and P Preziosi, SU.VI.MAX. Portions Alimentaires : Manuel Photos Pour l’estimation 
Des Quantités, Economica (Paris, 2002). 
4 S Hercberg, Table de Composition Des Aliments SU.VI.MAX, Economica (Paris, 2006). 
5 Bas Verplanken and Sheina Orbell, ‘Reflections on Past Behavior: A Self-Report Index of Habit Strength’, 
Journal of Applied Social Psychology, 33.6 (2003), 1313–30 <https://doi.org/10.1111/j.1559-
1816.2003.tb01951.x>. 
6 Muriel C.D. Verain and others, ‘Sustainable Food Choice Motives: The Development and Cross-Country 
Validation of the Sustainable Food Choice Questionnaire (SUS-FCQ)’, Food Quality and Preference, 93 (2021), 
104267 <https://doi.org/10.1016/j.foodqual.2021.104267>; L. Marty and others, ‘Food Choice Motives and the 
Nutritional Quality of Diet during the COVID-19 Lockdown in France’, Appetite, 157 (2021), 105005 
<https://doi.org/10.1016/j.appet.2020.105005>. 

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= Moderately important; 4 = Very important. Participants will be asked about their food choice 
motives for the month before questionnaire completion. 
Indices 
Three scores will be calculated based on the FFQ at each time point: 
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Meat consumption. Meat daily intake (in grams) will be calculated by summing daily 
intake for all the items of the FFQ that fall into the meat category. 
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Nutritional quality. Adherence to the French dietary guidelines will be evaluated using 
the simplified PNNS-GS27. The sPNNS-GS2 builds on the distinction between malus 
components (less healthy food groups which consumption should be limited, carrying a 
negative score, i.e., red meat, processed meat, sugary foods, sweet-tasting beverages, 
alcoholic beverages, salt) and bonus components (healthier food groups carrying a 
positive score, i.e., fruits and vegetables, nuts, legumes, whole-grain food, milk and dairy 
products, fish and seafood) reflecting established knowledge on the relationship 
between food groups consumption and non-communicable disease risk factors. sPNNS-
GS2 will computed for each participant with slight modifications to the calculation 
compared to the initial definition (range: -17 to 11.5) as in previous research8. 
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Environmental impact. Greenhouse gas emissions (GHGEs) will be derived from the 
French food environmental impact data- base Agribalyse 3.0 drawn up by the French 
Agency for Ecological Transition that includes GHGEs values for 2480 food items 
(ADEME, 2020), based on Life Cycle Analyses of food products. The items of the food 
frequency questionnaire will be associated to all the corresponding food items from 
Agribalyse 3.0. GHGEs of each item of the food frequency questionnaire will be 
calculated as the average GHGEs of individual foods from Agribalyse 3.0 associated to 
each item. GHGEs of participants’ daily diets will be calculated by multiplying the daily 
intake of each food item by its associated GHGEs per kg. 
One score will be calculated based on the Self-Report Habit questionnaire at each time point: 
- 
The Self-Report Habit Index will be computed by averaging ratings for all the individual 
items in the questionnaire. 
Ten scores will be calculated based on the FCQ at each time point: 
- 
A score for each subscale will be computed by averaging ratings for the three individual 
items in each of the ten subscales. 
 
ANALYSIS PLAN 
Statistical models 
We will use linear mixed models to investigate whether changes in measured variables pre- (T0), 
during- (T1) and post-challenge (T2) differ significantly between participants in the intervention 
and the control group. 
We will run linear mixed models with meat consumption (H1), nutritional quality (H2), 
environmental impact (H2), Self-Report Habit Index (H3), health motives (H4), ethics motives 
                                                          
7 Chaltiel and others, ‘Programme National Nutrition Santé - Guidelines Score 2 (Pnns-Gs2): Development and 
Validation of a Diet Quality Score Reflecting the 2017 French Dietary Guidelines’, British Journal of Nutrition, 
122.3 (2019), 331–42 <https://doi.org/10.1017/S0007114519001181>. 
8 Lucile Marty and others, ‘Food Choice Motives and the Nutritional Quality of Diet during the COVID-19 
Lockdown in France’, Appetite, 157.105005 (2021) <https://doi.org/10.1016/j.appet.2020.105005>. 

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(H4) and animal welfare motives (H4), as dependant variables, time (T0, T1 / T0, T2), group 
(intervention, control), time*group interaction as fixed effects and participant as random effect. 
These models will be adjusted for gender, age and BMI in order to control for potential 
confounding effects. We will report adjusted mean differences between T1 and T0, and between 
T2 and T0 for the intervention and the control group. 
If we find a significant effect of the intervention on meat consumption, i.e., time*group 
interaction is significant in the models above, we will run two additional models on the 
intervention group only to investigate whether the level of the challenge (i.e., (i) no meat, (ii) 
meat 3 times a week, (iii) meat 6 times a week) differentially influence meat consumption 
reduction. The first linear mixed model will be run with meat consumption as dependant 
variable, time (T0, T1 / T0, T2), level (i, ii, iii), time*level interaction as fixed effects and 
participant as random effect. We will report adjusted mean differences between T1 and T0, and 
between T2 and T0 for each level. In the second linear mixed model, we will substitute the level 
of the challenge by the difference between baseline meat consumption frequency (in times per 
week) and the level of the challenge (continuous variable). 
All statistical analyses will be performed using SAS version 9.4 (SAS Institute, Inc., 2012 SAS® 
9.4. Cary, NC). The proc mixed will be used for mixed models. The level of significance will be 
set at p < 0.05 for all pre-registered analyses. 
Data exclusion 
Dietary outcomes (calculated from FFQ) will be coded as missing for participants considered as 
outliers for energy intake at a given time point, defined as participants in the first and last 
percentile of energy intake at a given time point. For sensitivity analyses, dietary outcomes will 
also be coded as missing for participants reporting implausible energy intake at a given time 
point, defined as being outside of the following ranges: 500–3500 kcal for females and 800–
4200 kcal for males as recommended for FFQ data9. BMI will be coded as missing for 
implausible values, i.e., >70 as in previous research10. 
Missing data 
As we expect a small extent of missing outcome data, we will not exclude any participant based 
on missing (or implausible) values11. The number of missing (or implausible values) will be 
reported for each variable and at each time point. Linear mixed models will be based on all 
                                                          
9 Jinan C. Banna and others, ‘Examining Plausibility of Self-Reported Energy Intake Data: Considerations for 
Method Selection’, Frontiers in Nutrition, 4.September (2017), 1–6 <https://doi.org/10.3389/fnut.2017.00045>; 
Lucile Marty and others, ‘Food Choice Motives and the Nutritional Quality of Diet during the COVID-19 
Lockdown in France’, Appetite, 157.105005 (2021), 105005 <https://doi.org/10.1016/j.appet.2020.105005>; 
Tess Langfield, Andrew Jones, and Eric Robinson, ‘The Impact of Increasing the Availability of Lower Energy 
Foods for Home Delivery and Socio-Economic Position: A Randomised Control Trial Examining Effects on Meal 
Energy Intake and Later Energy Intake’, British Journal of Nutrition, 17, 2022, 1–9 
<https://doi.org/10.1017/s0007114522002197>. 
10 Eric Robinson, Andrew Jones, and Lucile Marty, ‘The Role of Health-Based Food Choice Motives in Explaining 
the Relationship between Lower Socioeconomic Position and Higher BMI in UK and US Adults’, International 
Journal of Obesity, 2022, 1–7 <https://doi.org/10.1038/s41366-022-01190-4>; Eric Robinson, Steven Gillespie, 
and Andrew Jones, ‘Weight-Related Lifestyle Behaviours and the COVID-19 Crisis: An Online Survey Study of UK 
Adults during Social Lockdown’, Obesity Science and Practice, 6.6 (2020), 735–40 
<https://doi.org/10.1002/osp4.442>. 
11 Rolf H.H. Groenwold, Karel G.M. Moons, and Jan P. Vandenbroucke, ‘Analysis Randomized Trials with Missing 
Outcome Data: How to Analyze and What to Report’, Canadian Medical Association Journal, 186.15 (2014), 
1153–57. 

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available data points only. Sensitivity analyses will be conducted using multiple imputation, first 
on missing values only and then on missing and implausible values12. 
Exploratory analysis 
Any supplementary analysis that is not pre-registered here will be described as an exploratory 
analysis. 
 
 
                                                          
12 Peng Li and Elizabeth A Stuart, ‘Best (but Oft-Forgotten) Practices : Missing Data Methods in Randomized 
Controlled Nutrition Trials’, American Journal of Clinical Nutrition, 109 (2019), 504–8. 

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Appendix 1. Study design