# How parents' financial hardship determines the shift towards more sustainable diets: Moderating effects of motives, perceived effort and feeling of powerlessness

Basile Verdeau, Lucile Marty, Sandrine Monnery-Patris

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Basile Verdeau, Lucile Marty, Sandrine Monnery-Patris. How parents' financial hardship determines the shift towards more sustainable diets: Moderating effects of motives, perceived effort and feeling of powerlessness. 2025. hal-05482124

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# How parents' financial hardship determines the shift towards more sustainable diets: Moderating effects of motives, perceived effort and feeling of powerlessness

Verdeau Basile¹, Marty Lucile¹, Monnery-Patris Sandrine*¹

¹ Université Bourgogne Europe, Institut Agro, CNRS, INRAE, UMR CSGA, 21000 Dijon, France

*Corresponding author

Correspondence: sandrine.monnery-patris@inrae.fr

## ABSTRACT

In Western countries, a shift towards healthier and more plant-based diets is necessary to ensure a more sustainable food system, but parents experiencing financial hardship may have greater difficulty in making such changes. Drawing on the scarcity theory, this study aims to examine the influence of parents' perceived financial hardship on the intention to adopt a more plant-based diet for the family through food choice motives, perceived effort of changing habits and feeling of powerlessness on the food system. A quota sample of 498 parents living in mainland France completed an online questionnaire. Linear models were run to identify the influence of perceived financial scarcity on the different psychological constructs. A greater financial scarcity was associated with a higher importance of price and familiarity in food choices, a higher perceived effort of changing family habits and a higher feeling of powerlessness, even after adjustment for age, gender, marital status and education level. Overall, the intention to shift towards more plant-based dietary habits was low across the whole sample, but even slightly lower in parents experiencing greater financial hardship when it came to increasing legume consumption, which was partly explained by food choice motives. This study highlights the multiple barriers that parents with financial difficulties are facing when it comes to adopting healthier and environmentally-friendlier dietary patterns. Promoting more sustainable choices requires taking into account affordability but also the importance of motives and the perceived cost of changing habits, especially for legumes.

**Keywords:** sustainable diet, financial scarcity, scarcity theory, food choice motives, plant-based diet, dietary intentions, perceived cost
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# Introduction

In high-income countries, shifting towards more sustainable diets is required to safeguard both human and environmental health (Rockström et al., 2025). Compared to current habits in these countries, diets including higher amounts of fruit, vegetables, legumes, nuts, seeds and whole grains, and lower amounts of meat, have been associated with a higher nutritional quality and a reduced environmental impact (Rockström et al., 2025; Darmon et al., 2025). In France, although modest improvements in diet sustainability have been observed in the 2010s (Toujgani et al., 2024; Rochefort et al., 2025), meat consumption remains stable (Rogissart, 2023; Agreste & FranceAgriMer, 2025) while fresh fruit and vegetables purchases are declining in the 2020s (Interfel, 2024). Therefore, it is essential to explore the barriers of more sustainable food choices, which notably include lack of awareness, sensory aspects and social representations (Graça et al., 2019; Kenny et al., 2023).

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According to the FAO, sustainable diets should also be "culturally acceptable, accessible, economically fair and affordable" (FAO, 2010). These socioeconomic and sociocultural aspects of sustainability are of particular importance as a growing part of the population is experiencing financial hardship in the current context of cost-of-living crisis which particularly affects low-income households (Berland et al., 2023; Chafwehé et al., 2024). In France, monetary poverty and declared financial hardship combined represent 30 % of the population (Insee, 2025). Compared with the general population, such consumers show dietary patterns of lower nutritional quality, due to a significantly lower consumption of fruit and vegetables but equivalent environmental impact (Bocquier et al., 2015; Perignon et al., 2023). Overall, consumers experiencing financial hardship may have greater difficulty in making healthy and environmentally friendly food choices. Noticeably, there is no scientific consensus on the affordability of sustainable diets for low-income groups. Although healthy diets are known to be associated with high costs (Darmon & Drewnowski, 2015) and would be unaffordable for about 5 % of the population in France (Penne & Goedemé, 2021; FAO et al., 2025), reducing meat consumption should represent a monetary benefit and sustainable diets have been shown to be more affordable than current diets in high-income countries (Springmann et al., 2021; Darmon et al., 2025). The adoption of a healthy plant-based diet with significantly reduced environmental impact would be affordable even in populations with a low-socioeconomic position (Reynolds et al., 2019; Vellinga et al., 2025). However, optimization studies have highlighted the difficult trade-offs between the different dimensions of sustainability: sustainable diets may be mathematically affordable, but a lower cost requires substantial deviations from current habits, which would compromise acceptability (Maillot et al., 2010; Perignon et al., 2016). Beyond such models, little research has been conducted on the acceptability of more sustainable diets in populations experiencing financial hardship. More generally, research specifically addressing the determinants of sustainable food choices in low-income populations is scarce (Vermeir et al., 2020).

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Beyond economic aspects, other barriers may be critical in these populations, such as a lower food literacy (McKinnon et al., 2014), a lack of access to healthy food outlets in deprived neighbourhoods (Ravikumar et al., 2022) or social norms in low socioeconomic groups rejecting the idea of restriction and giving less importance to health prevention (Régnier & Masullo, 2009; Einhorn, 2021). We hypothesise that financial hardship could also be associated with psychological barriers. The *scarcity theory* posits that beyond a low budget, the psychological experience of a lack of resources influences cognition and behaviour through a *scarcity mindset* (Mullainathan & Shafir, 2013; de Bruijn & Antonides, 2022). As resource scarcity leads to worries and exhaustion and as human cognition is limited, all cognitive capacities are directed to solve urgent issues and risks are averted. This mindset is characterised by three correlated phenomena. First, *tunneling* consisting of an attentional narrowing on scarcity-related issues, such as price and budget. Second, *taxed mental bandwidth* corresponding to the idea of a
cognitive load caused by daily worrying, impairing decision-making and leading to a prioritisation of automatic routines. Third, present time orientation describing a lower consideration of future consequences such as the health and environmental impact of food choices, as immediate rewards and urgent issues are prioritised. Such mechanisms could hamper the adoption of more sustainable diets (Daniel, 2020; Einhorn, 2021), but little research has applied the scarcity theory in the field of food choices (van der Veer et al., 2024).

The three phenomena of the scarcity mindset applied to the adoption of more sustainable diets can be operationalised as follows. As for tunneling, food choices are more motivated by prices over other considerations such as health or the environment. Such motivational patterns have been associated with less sustainable diets (Konttinen et al., 2013; Brunin et al., 2022; Marty et al., 2022). As for taxed mental bandwidth, cognitive load implies that food choices are more motivated by habits over other considerations, and that shifting from such habits is perceived as effortful. The perceived cost of a pro-environmental behaviour (defined as the overall cost in terms of money, time, inconvenience, social approval, cognitive resources) (Diekmann & Preisendörfer, 2003; Steg & Vlek, 2009) has been identified as a mediator between financial scarcity and a lower willingness to adopt such behaviours including reducing meat consumption (Berthold et al., 2023). As for present time orientation, the consequences of food systems are considered as distant issues. Consumers facing financial hardship tend to feel disempowered towards the food system (Verdeau & Monnery-Patris, 2024) and environmental issues (Kennedy & Givens, 2019). This short-term orientation has been associated with less pro-environmental attitudes (Grandin et al., 2022) and less healthy dietary patterns (Dassen et al., 2015).

These mechanisms may be particularly true for parents, with parenthood exacerbating the scarcity mindset. In low-income families, child preferences and time scarcity represent additional constraints, leading to complex negotiations and higher cognitive load (Ravikumar et al., 2022; Schuler et al., 2024; Screti et al., 2024). Parents on a low budget tend to be more reluctant to increase plant-based food such as vegetables due to the risk of wastage (Daniel, 2016).

The aim of this study is to understand the psychological processes that could lead parents experiencing financial hardship to a lower intention to adopt a more sustainable diet through a scarcity mindset. We hypothesise that a greater perception of financial scarcity will lead to tunneling, cognitive load and powerlessness towards the food system, which then leads to a lower intention to make healthier and more plant-based food choices. We therefore make the five following hypotheses, represented on the **Figure 1**.

* H1: The more parents perceive financial scarcity, the more their choices are motivated by price.

* H2: The more parents perceive financial scarcity, the more their choices are motivated by familiarity with food (H2a) and the more they perceive changing their dietary habits as costly, in the broad sense of the term (H2b).

* H3: The more parents perceive financial scarcity, the more they feel powerless to influence the food system through their choices.

* H4: The more parents perceive financial scarcity, the lower their intention to change family habits towards a more plant-based pattern.

* H5: The link between financial scarcity and the intention to change family habits towards a more plant-based pattern is mediated by a greater importance of price and familiarity in food choices, a higher perceived cost of changing dietary habits and a higher feeling of powerlessness on the food system.

To the best of our knowledge, this is the first study to draw on scarcity theory using quantitative data and focusing on the adoption of a sustainable diet.
<figure><img src="image_2.png" /><figcaption>**Figure 1** – Mechanisms of the scarcity theory applied to the adoption of a more sustainable diet and study hypotheses.</figcaption></figure>

## Methods

### Study design

A cross-sectional design was used. Participants completed a 15-minute online questionnaire on the LimeSurvey platform (LimeSurvey GmbH, Hamburg, Germany, Version 3.24.3, https://limesurvey.com). The questionnaire was developed in French. All validated scales were translated from English through translation and back translation by two distinct bilingual researchers. Data collection took place between the 22nd January and the 4th February 2025. The survey consisted of seven different sections: Dietary habits and intention; Food choice motives; Perceived cost; Feeling of powerlessness; Price perception; Financial scarcity; Sociodemographics (the price perception section will not be detailed in this article). The protocol and the analysis plan have been preregistered before data collection (https://doi.org/10.17605/OSF.IO/7BWJM). The protocol was approved by the ethical evaluation committee of the Université Bourgogne Franche-Comté (CERUBFC-2024-04-02-011, amendment delivered on December 19th, 2024).

### Recruitment

Eligible participants were adults living with at least one child aged 3 to 11 years old, living in mainland France and partly or fully responsible for household food purchases. As previously done in the literature (Schuster et al., 2019), this age range for children was chosen as it represents elementary school years and a period when parents are fully responsible for children's diet (before increasing autonomy in adolescence) (Neufeld et al., 2022) and when children's diets are similar to parent's diets, following the period of early childhood. To be as representative as possible of the French parent population, we conducted a quota sampling based on family type and income, using data from the National Institute for Statistics and Economic Studies (Insee). We aimed to recruit 21 % large families (at least three children), 25 % single-parent families (Insee, 2021b) and at least 50 % with a total disposable household income below the median in the parent population in France, distinguishing single-parent and two-parent
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households (Insee, 2024). Furthermore, in order to reach parents experiencing financial hardship, we decided to include at least 10 % participants with an income below the 1st decile.

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Participants were recruited through a private panel of ca. 500.000 consumers living in France (Panelabs, MIS Group, 85 rue Nationale, 59800 Lille, https://panelabs.com). The quota sampling was conducted by the panel company through a pre-questionnaire. Only participants meeting the inclusion criteria could proceed to the LimeSurvey questionnaire, where they accessed an information document and were asked to tick a box indicating that they accepted to be part of the study. One attention check was included in the LimeSurvey questionnaire and participants who failed were excluded from the analyses.

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## Measures

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### Food habits and intentions

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For 8 different food groups, participants were asked to assess their usual consumption frequency at home over the past 6 months and that of their child(ren) aged 3-11 (using an average in the case of several children in this age group), on a 6-point scale from *Never or less than once a month* to *Two servings a day or more*. Then, participants had to indicate their intention to change their consumption over the next 6 months on a 5-point scale from “Decrease a lot” to “Increase a lot” (also for their child(ren)). The 8 food groups were chosen according to their relevance in the dietary shift towards more sustainable patterns in Western countries (Willett et al., 2019; Steenson & Buttriss, 2021): vegetables, fruit, nuts and seeds, whole grains, legumes (including tofu, plant-based steaks, soy proteins), processed meat, poultry and red meat. This response method was used to avoid the mention of “meat reduction” or “plant-based diet” which carries social norms, and to limit desirability bias.

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Participants were also asked to indicate their frequency of meals prepared outside the home (both for them and for their child(ren) aged 3-11) on a 6-point scale from *Never or less than once a month* to *9 times a week or more*.

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### Financial scarcity

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The *Perceived Economic Scarcity Scale* was used to measure the participant's perception of financial scarcity (Auger et al., 2024). The scale has been previously validated and includes 8 items such as “My income is not sufficient to make a decent living” and “I cannot help but think about lack of money”. Participants had to rate their agreement with each item on a 7-point Likert-scale (from *Strongly disagree* to *Strongly agree*). A financial scarcity score was calculated as the average score of the 8 answers (continuous, [1;7]).

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### Food choice motives

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Food choice motives were assessed using a French version of the *Food Choice Questionnaire* (Steptoe et al., 1995; Marty et al., 2022). The questionnaire included ten different subscales with 3 items each: health, convenience, price, environment, natural content, mood, weight control, sensory appeal, familiarity and satiation. The satiation subscale was added to the original scale to better reflect the importance of this dimension in food choices of low-income parents (Burns et al., 2013) and was measured through 3 items adapted from *The Eating Motivation Survey* questionnaire (Renner et al., 2012). Participants rated the importance of each item for the family (“It is important for us that the food we eat…” on a 4-point scale (from *Not at all important for us* to *Very important for us*). The three items for the price subscale were: “Is good value for the money”, “Is not expensive” and “Is cheap or on special offer”. An absolute score for each subscale was calculated by averaging ratings for the three items (continuous, [1;4]).

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### Perceived cost

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The perceived behavioural cost to change dietary habits was assessed using a 7-item scale inspired from previous works on *sunk costs* and *perceived risks* in the literature on the psychological barriers of pro-environmental behaviours (Gifford & Chen, 2017; Lacroix et al.,

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2019). Participants were asked to think about the idea of changing family dietary habits, such as eating more fruit and vegetables, less meat or more wholegrains. Seven types of behavioural costs were included: monetary cost ("These issues are important but it would be too expensive to change our habits"), time cost ("I'm concerned that changing what we eat will take up too much of our time"), cognitive cost ("It's too complicated for us to think about changing what we eat"), hedonic cost ("We haven't changed our habits because we may not enjoy it in terms of taste"), social cost ("Making these changes would be criticized by others (in particular my children)"), habit cost ("We can't change what we eat because we're attached to our current habits") and overall effort ("It's too difficult for us to change what we eat"). Participants had to rate to what extent each item applied to their family on a 6-point Likert scale (from *Not at all true for us* to *Very true for us*).

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## Feeling of powerlessness

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A modified version of a scale measuring individual sense of efficacy over climate change was used to assess the participant's feeling of powerlessness to protect the environment through food choices (Hornsey et al., 2021). The scale included 8 items such as "I believe my food choices have an influence on environmental protection" (reversed) or "I cannot influence environmental protection through my food choices, because it rests in the hands of industry". Participants had to rate their agreement with each item on a 6-point Likert-scale (from Strongly disagree to Strongly agree).

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## Sociodemographics

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Participants were asked to report their gender, age, marital status (single or in a relationship), level of education, living area and employment status (and the one of the partner if applicable). A discrete assessment of the financial situation was carried out on a 5-level scale. They also indicated the number of adults and children (in different age groups) living in the household. They were asked if some members of the household were vegetarian, vegan or only very rarely consuming animal-based foods and if some foods were avoided in the household due to food allergies or intolerances.

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## Statistical analyses

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We followed a preregistered analysis plan, with a few exceptions detailed in this section. From the 589 participants who entirely completed the survey, 91 were excluded as they were considered inattentive (5 % fastest participants; failing the attention check; no child aged 3-11 in the household; consistency in inconsistent scales; consecutive strings of the same answer), following methods suggested in the literature (Vecchio et al., 2020).

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## Variable processing

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For each food group, usual consumption frequency was analysed as a discrete variable, grouping certain responses to ensure at least n=20 in each response category for the analyses. For the same reason, out-of-home meal frequency variables were capped at *Three to five times a week or more*.

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The intention scores were not calculated as planned in the preregistered analysis due to low variability (i.e., more than 80 % participants declared no intention to change meat consumption). Thus, for each food group, we decided to treat intentions as binary variables (1 if the participant intended to increase consumption for healthy plant-based foods or to decrease consumption for animal-based foods, else 0). A total intention score was calculated as the sum of the 8 food group intention binary variables, and capped at 5 to ensure at least n=20 in each response category (integer variable, [0-5]).

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Exploratory and confirmatory factor analyses were conducted to confirm the unidimensionality of the perceived cost and feeling of powerlessness scales (Hair et al., 2019). Based on factor loadings, interpretability and fit indices, both scales were considered unidimensional (see Supplementary Information). For the feeling of powerless scale, only seven items were retained
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as removing one item slightly improved the fit. Scores of perceived cost and feeling of powerlessness were calculated by averaging item scores (continuous variables, [1;7]).

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For all psychometric scales, internal consistency was checked using the Cronbach's α. Consistency was excellent for financial scarcity (α = 0.94), good for perceived cost and feeling of powerlessness (α = 0.84) and satisfying for all motives (from α = 0.64 for sensory appeal to α = 0.85 for convenience).

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To better reflect the negotiation process of food choice motives (Sobal & Bisogni, 2009), the relative importance of each motive was computed by dividing the absolute score by the participant's average score on all thirty items (continuous, [0-4]), as it has been previously done in the literature (Konttinen et al., 2013).

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### Statistical tests

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First, the association between financial scarcity and sociodemographic characteristics was analysed using ANOVA for discrete variables (with Bonferroni *post hoc* tests) and Pearson correlation test for age. For each of the 8 food groups, we also assessed the association between financial scarcity and usual consumption frequency at home using ordinal logistic regressions, adjusted for parent's age and gender (not preregistered, Bonferroni correction). As sensitivity analyses, we also adjusted for parent's education level and marital status, and parent's or children's out-of-home meals frequency.

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For hypotheses H1 to H3, linear models were conducted with financial scarcity as the independent variable and the relative importance of price (H1), the relative importance of familiarity (H2a), the perceived cost (H2b) and the feeling of powerlessness (H3) as dependent variables. Each model was adjusted for age and gender. As sensitivity analyses, we also adjusted for education level and marital status. As an exploratory analysis, we repeated these models for the 8 remaining food choice motives (applying Bonferroni correction). We also explored the type of perceived cost associated with financial scarcity using 7 ordinal logistic regressions with each item of the perceived cost scale as dependent variable (applying Bonferroni correction).

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For hypothesis H4, 16 models of logistic regression were conducted with binary intention (8 for the parent, 8 for the child(ren)) as dependent variable and financial scarcity as independent variable. Each model was first adjusted on parent's age and gender. As sensitivity analysis, we also adjusted for parent's education level and marital status, and parent's or children's current consumption frequency of the food group. We also realised two negative binomial regression models for the total intention score (for the parent and for the children), adjusted for age and gender.

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For hypothesis H5, we considered only food groups for which a significant association with financial scarcity was previously observed. We ran mediation models with the intention binary variables as outcomes, financial scarcity as predictor and the relative importance of price and familiarity, the perceived cost and the feeling of powerlessness as mediators. We also examined as mediators other food choice motives significantly associated with financial scarcity (not preregistered, Bonferroni correction). Indirect effects were estimated for each mediation model using 5000 bootstrap samples. The mediation models were adjusted on age and gender. A second adjustment for education level, marital status and current consumption frequency of the food group was conducted only if an association had been observed previously with this adjustment (H4).

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In all models including education level as covariable, collinearity between education level and financial scarcity was examined using the general variance inflation factor (GVIF). As GVIF^(1/2*degrees of freedom) was below to 2 in all regression models (equivalent to GVIF below 4), we considered that there was no collinearity (Baudry et al., 2023). Contrary to what

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was planned in the analysis plan, models were not adjusted for living area and employment status. Indeed, data on living area was deemed unreliable (less than 14 % of the participants declared living in a large urban area, against 47 % in the French general population) (Insee, 2020). Employment status appeared difficult to compare between single-parent and two-parent families and was considered too correlated to financial scarcity and little informative about socio-professional groups. We did not exclude participants who declared eating meals prepared outside home more than 6 times a week as they were few of them (n=11 for parents and n=15 for children). We adjusted for current consumption frequency rather than for compliance with public health recommendations, as such recommendations could hardly apply to our non-quantitative food frequency data.

All statistical analyses were performed using RStudio (R Core Team, version 4.4.1, 2024, Vienna, Austria) with the packages *ordinal* for ordinal logistic regressions and *mediation* for mediation models. The level of significance was set at p<0.05 except when Bonferroni correction was applied.

## Sample size calculation

We aimed to reach a sample size of 500 participants to detect small effects (f=0.02) in linear regression models with financial scarcity as independent variable and age and gender as covariables, at power 0.80 (G\*Power 3.1, Faul et al., 2009).

# Results

## Participant's characteristics, food habits and financial scarcity

The sociodemographic characteristics of the 498 participants included in the study are presented in the **Table 1**. After exclusion, quotas were reached for large families (21 %), households with an income below the 1st decile (16 % for two-parent households, 27 % for single-parent households) and households with an income below the median (69 % for two-parent households, 76 % for single-parent households) and almost reached for single-parent families (23.5 %). 110 participants (22.1 %) declared having a difficult financial situation (struggling or not being able to make ends meet without going into debt).

The association between financial scarcity and sociodemographic characteristics is reported in the **Table 1**. A higher perceived financial scarcity was observed in mothers compared to fathers, in single parents compared to parents in a relationship, in parents with no higher education compared to parents with a higher education (*post hoc* test), in parents with part-time or no employment compared to parents with a full-time employment (*post hoc* test) and in parents declaring a more difficult financial situation (all pairwise differences were significant in the *post hoc* test after Bonferroni correction). Parents living in household with at least one vegetarian or vegan perceived a lower financial scarcity (3.9 (1.4) vs 4.4 (1.4), *p* = 0.02). Financial scarcity was also associated with the frequency of meals prepared outside the home in parents (*p* = 0.0002) and in children (*p* = 0.0009). Indeed, a higher financial scarcity was observed among parents who reported never or almost never eating meals prepared outside the home compared to others, and among parents who reported that their children aged 3-11 never or almost never ate meals prepared outside the home compared to those who reported that their children ate at least 3 times a week outside the home (*post hoc* tests). Financial scarcity was not associated with age, number of children in the household or food avoidance due to allergies and intolerances.

For parents, financial scarcity was associated with a lower frequency consumption at home for fruit (β = -0.23, *p* = 0.0001), vegetables (β = -0.28, *p* < 0.0001), nuts and seeds (β = -0.26, *p* < 0.0001) and a higher frequency for processed meat (β = 0.25, *p* = 0.0001) (ordinal logistic
regressions, Bonferroni correction applied). After adjustment for education level, marital status and out-of-home consumption frequency, the association was not significant anymore for fruit (p = 0.022), but a higher frequency consumption was observed for red meat (β = - 0.20, p = 0.004) and poultry (β = 0.20, p = 0.005). For children's consumption, financial scarcity was associated with a lower consumption of vegetables (β = - 0.24, p = 0.0001) and nuts and seeds (β = - 0.31, p < 0.0001), and a higher consumption of processed meat (β = 0.18, p = 0.0047). After adjustment for out-of-home consumption frequency and parent's education level and marital status, the association was significant only for nuts and seeds.

<table><caption>**Table 1** – Sociodemographic characteristics of the parents included in the sample (n=498).</caption><thead><tr><th></th><th>Mean (standard deviation)</th><th>Pearson correlation coefficient (95 % CI)</th><th>p</th></tr><tr><th></th><th>n (%)</th><th>Average financial scarcity score (standard deviation)</th><th>p (ANOVA)</th></tr></thead><tbody><tr><td><strong>Age (years)</strong></td><td>40.3 (6.3)</td><td>- 0.07 (- 0.2 ; 0.2)</td><td>0.1</td></tr><tr><td><strong>Gender</strong></td><td></td><td></td><td>0.001</td></tr><tr><td>Female</td><td>281 (56.4)</td><td>4.52 (1.36)</td><td></td></tr><tr><td>Male</td><td>217 (43.6)</td><td>4.12 (1.33)</td><td></td></tr><tr><td><strong>Marital status</strong></td><td></td><td></td><td>0.002</td></tr><tr><td>Single</td><td>117 (23.5)</td><td>4.69 (1.37)</td><td></td></tr><tr><td>Couple</td><td>381 (76.5)</td><td>4.24 (1.28)</td><td></td></tr><tr><td><strong>Number of children aged &lt;18</strong></td><td></td><td></td><td>0.5</td></tr><tr><td>1</td><td>170 (34.1)</td><td>4.49 (1.34)</td><td></td></tr><tr><td>2</td><td>239 (48.0)</td><td>4.23 (1.32)</td><td></td></tr><tr><td>3</td><td>70 (14.1)</td><td>4.36 (1.50)</td><td></td></tr><tr><td>4 or more</td><td>19 (3.8)</td><td>4.51 (1.53)</td><td></td></tr><tr><td><strong>Education level</strong></td><td></td><td></td><td>&lt;0.0001</td></tr><tr><td>&lt; High school diploma, vocational qualification</td><td>96 (19.3)</td><td>5.08 (1.24)</td><td></td></tr><tr><td>High school diploma (professional or general)</td><td>121 (24.3)</td><td>4.65 (1.34)</td><td></td></tr><tr><td>Higher education (1 or 2 years)</td><td>123 (24.7)</td><td>4.06 (1.31)</td><td></td></tr><tr><td>Higher education (3 years or more)</td><td>158 (31.7)</td><td>3.90 (1.25)</td><td></td></tr><tr><td><strong>Employment</strong></td><td></td><td></td><td>&lt;0.0001</td></tr><tr><td>Full-time job</td><td>374 (75.1)</td><td>4.16 (1.34)</td><td></td></tr><tr><td>Part-time job</td><td>57 (11.4)</td><td>4.71 (1.26)</td><td></td></tr><tr><td>Unemployed</td><td>34 (6.8)</td><td>5.07 (1.28)</td><td></td></tr><tr><td>Other (disabled, retired, at-home, student)</td><td>33 (6.6)</td><td>5.14 (1.26)</td><td></td></tr><tr><td><strong>Financial situation (discrete variable)</strong></td><td></td><td></td><td>&lt;0.0001</td></tr><tr><td>Comfortable</td><td>25 (5.0)</td><td>2.38 (1.07)</td><td></td></tr><tr><td>It is OK</td><td>141 (28.3)</td><td>3.22 (0.94)</td><td></td></tr><tr><td>Tight, need to be careful</td><td>222 (44.6)</td><td>4.53 (0.86)</td><td></td></tr><tr><td>Struggling</td><td>81 (16.3)</td><td>5.71 (0.79)</td><td></td></tr><tr><td>Cannot make ends without going into debt</td><td>29 (5.8)</td><td>6.29 (0.70)</td><td></td></tr></tbody></table>

Financial scarcity is a continuous variable ranging from 1 to 7.

## H1, H2 and H3 hypotheses

The four more important food choice motives in the sample were sensory appeal (mean = 3.44/4, std. dev. = 0.46), satiation (mean = 3.14/4, std. dev. = 0.57), health (mean = 3.07/4, std. dev. = 0.61) and natural content (mean = 3.05/4, std. dev. = 0.72). The average perceived cost of changing dietary habits was moderate (mean = 3.05/6, std. dev. = 0.91), as the average feeling of powerlessness on environmental protection through food choices (3.37/6, std. dev. = 0.94).

The results of the linear regression models are presented in the Table 2.

<table><caption>**Table 2** – Associations between perceived financial scarcity and the psychological constructs of the scarcity mindset.</caption><thead><tr><th rowspan="2"></th><th colspan="3">a*</th><th colspan="3">b**</th></tr><tr><th>β (std. error)</th><th>partial η<sup>2</sup></th><th>p</th><th>β (std. error)</th><th>partial η<sup>2</sup></th><th>p</th></tr></thead><tbody><tr><td>H1. Relative importance of price</td><td>0.06 (0.007)</td><td>0.12</td><td><strong>&lt;0.0001</strong></td><td>0.06 (0.007)</td><td>0.12</td><td><strong>&lt;0.0001</strong></td></tr><tr><td>H2a. Relative importance of familiarity</td><td>0.02 (0.007)</td><td>0.02</td><td><strong>0.003</strong></td><td>0.02 (0.007)</td><td>0.02</td><td><strong>0.03</strong></td></tr><tr><td>H2b. Perceived cost of changing habits</td><td>0.14 (0.03)</td><td>0.04</td><td><strong>&lt;0.0001</strong></td><td>0.13 (0.03)</td><td>0.04</td><td><strong>&lt;0.0001</strong></td></tr></tbody></table>
<table><tr><td>H3. Feeling of powerlessness</td><td>0.09 (0.03)</td><td>0.01</td><td><strong>0.003</strong></td><td>0.08 (0.03)</td><td>0.01</td><td><strong>0.02</strong></td></tr></table>

Results of 8 linear regression models with financial scarcity as independent variable

* a: Models are adjusted for age and gender. ** b: Models are adjusted for age, gender, education level and marital status.

The first three hypotheses were confirmed. A higher perceived financial scarcity predicted a greater relative importance of price with a large effect (partial η² = 0.12) and a greater relative importance of familiarity, a higher perceived cost of changing dietary habits and a higher feeling of powerlessness to protect the environment through food choices with a small to medium effect (partial η² = 0.01 to 0.04). All associations remained significant after adjustment for education level and marital status (adjustment b).

In exploratory analyses, a higher financial scarcity was also associated with a lower relative importance of *natural content* (β = - 0.04, partial η² = 0.06, *p* < 0.0001), *weight control* (β = - 0.03, partial η² = 0.05, *p* < 0.0001) and *health* (β = - 0.02, partial η² = 0.02, *p* = 0.005). After adjustment for education level and marital status, there was a significant association only for *natural content* and *weight control* (Bonferroni correction). The items of the perceived cost scale associated with financial scarcity were the overall effort (β = 0.2, *p* = 0.0003), the monetary cost (β = 0.6, *p* < 0.0001) and the cognitive cost (β = 0.2, *p* = 0.001). After adjustment for education level and marital status, all associations remained significant.

## H4 hypothesis

Less than half of the parents declared that they had the intention to increase their consumption of fruit (44 %) and vegetables (42 %) or to increase their children's consumption (46 % for fruit, 49 % for vegetables) over the next 6 months. About one quarter planned to increase the family consumption of legumes (26 % for parents, 28 % for children) or nuts and seeds (24 % for parents and children). Fewer participants declared that they had the intention to increase the family consumption of whole grains (16 % for parents, 17 % for children) and to decrease the family consumption of charcuterie (14 % for parents and children) or red meat (13 % for parents, 10 % for children). Very few participants had the intention to decrease the consumption of poultry (5 % for parents and children). In total, 137 participants (28 %) declared no intention to shift towards a more sustainable pattern (122 (24 %) regarding their children's diet) and 78 participants (16 %) declared at least 4 intentions to shift towards more sustainable patterns (91 (18 %) regarding their children's diet).

The results of the logistic regression models are presented in the Table 3.

<table><caption>**Table 3** – Associations between perceived financial scarcity and the intention to shift towards a more plant-based dietary pattern.</caption><thead><tr><th rowspan="2"></th><th colspan="4">Parent</th><th colspan="4">Children aged 3-11</th></tr><tr><th>OR<br>(95% CI)</th><th>a<br>p</th><th>OR<br>(95% CI)</th><th>b<br>p</th><th>OR<br>(95% CI)</th><th>a<br>p</th><th>OR<br>(95% CI)</th><th>b<br>p</th></tr></thead><tbody><tr><td>Fruit</td><td>1.14<br>(0.99 - 1.30)</td><td>0.06</td><td>1.10<br>(0.94 - 1.27)</td><td>0.2</td><td>1.13<br>(0.99 - 1.29)</td><td>0.08</td><td>1.11<br>(0.96 - 1.30)</td><td>0.1</td></tr><tr><td>Vegetables</td><td><strong>1.15</strong><br>(<strong>1.01 - 1.32</strong>)</td><td><strong>0.04</strong></td><td>1.14<br>(0.99 - 1.33)</td><td>0.08</td><td><strong>1.16</strong><br>(<strong>1.01 - 1.32</strong>)</td><td><strong>0.03</strong></td><td>1.12<br>(0.96 - 1.29)</td><td>0.1</td></tr><tr><td>Legumes</td><td><strong>0.81</strong><br>(<strong>0.70 - 0.94</strong>)</td><td><strong>0.007</strong></td><td><strong>0.84</strong><br>(<strong>0.71 - 0.99</strong>)</td><td><strong>0.03</strong></td><td><strong>0.85</strong><br>(<strong>0.73 - 0.98</strong>)</td><td><strong>0.03</strong></td><td>0.87<br>(0.75 - 1.03)</td><td>0.1</td></tr><tr><td>Nuts and seeds</td><td>0.96<br>(0.83 - 1.13)</td><td>0.6</td><td>1.02<br>(0.86 - 1.21)</td><td>0.8</td><td>1.03<br>(0.88 - 1.19)</td><td>0.8</td><td>1.09<br>(0.92 - 1.29)</td><td>0.3</td></tr><tr><td>Whole grains</td><td>1.09<br>(0.91 - 1.30)</td><td>0.4</td><td>1.14<br>(0.93 - 1.40)</td><td>0.2</td><td>0.97<br>(0.82 - 1.16)</td><td>0.8</td><td>1.01<br>(0.83 - 1.22)</td><td>0.9</td></tr><tr><td>Charcuterie</td><td>0.98<br>(0.81 - 1.18)</td><td>0.8</td><td>0.98<br>(0.79 - 1.18)</td><td>0.7</td><td>0.97<br>(0.80 - 1.17)</td><td>0.7</td><td>0.94<br>(0.76 - 1.15)</td><td>0.5</td></tr><tr><td>Red meat</td><td>0.91<br>(0.75 - 1.10)</td><td>0.3</td><td>0.97<br>(0.78 - 1.19)</td><td>0.7</td><td>0.91<br>(0.73 - 1.13)</td><td>0.4</td><td>0.98<br>(0.77 - 1.25)</td><td>0.9</td></tr><tr><td>Poultry</td><td>0.89<br>(0.66 - 1.20)</td><td>0.5</td><td>0.91<br>(0.66 - 1.26)</td><td>0.6</td><td>0.99<br>(0.72 - 1.36)</td><td>0.9</td><td>1.01<br>(0.72 - 1.44)</td><td>0.9</td></tr><tr><td>Total intention</td><td>1.01</td><td>0.8</td><td></td><td></td><td>1.03</td><td>0.4</td><td></td><td></td></tr></tbody></table>
(0.95 – 1.07)

(0.95 – 1.07)

Results of 16 logistic regression models and 2 negative binomial regression models with financial scarcity as independent variable. * a: Models are adjusted for parent's age and gender. ** b: Models are adjusted for parent's age, gender, education level and marital status, and parent's or children's current consumption frequency.

A higher perceived financial scarcity was associated with a higher probability to declare an intention to increase vegetable consumption and a lower probability to declare an intention to increase legume consumption (both for the parent and for the children). Notably, 48 % of parents declaring a difficult financial situation (n=110) had the intention to increase their vegetable consumption and 56 % of them had the intention to increase their children's vegetable consumption; but only 15 % had the intention to increase their legume consumption and 16 % had the intention to increase their children's legume consumption (twice as low as among parents with a comfortable or tight financial situation). After adjustment for education level, marital status and consumption frequency, there was a significant association only for legumes in parents. Financial scarcity was not associated with the total intention score after adjustment by parent's age and gender.

## H5 hypothesis

Mediation models were conducted with two different outcomes: intention to increase legume consumption for the parent and for the children. No mediation model was conducted for the intention to increase vegetable as it was not hypothesised that financial scarcity would be associated with a higher intention and this association was not supposed to be mediated by the scarcity mindset (indeed, the higher intention among participants perceiving a higher financial scarcity was explained by a lower baseline consumption of vegetables).

The results of the mediation models are presented in the Table 4 and Figure 2.

<table><caption>**Table 4** – Direct and indirect effects in the mediation models between financial scarcity and intention to shift towards more plant-based dietary patterns.</caption><thead><tr><th>Outcome</th><th>Mediator</th><th>Direct effect</th><th>Indirect effect</th><th>Proportion of the effect mediated (%)</th></tr></thead><tbody><tr><td rowspan="4">Intention to increase legume consumption</td><td>Relative importance of price</td><td><strong>- 0.05**</strong></td><td>- 0.0003</td><td>0</td></tr><tr><td>Relative importance of familiarity</td><td><strong>- 0.04*</strong></td><td><strong>- 0.007*</strong></td><td>13*</td></tr><tr><td>Perceived cost of changing habits</td><td><strong>- 0.05*</strong></td><td>- 0.001</td><td>2</td></tr><tr><td>Feeling of powerlessness</td><td><strong>- 0.05*</strong></td><td>- 0.005</td><td>9</td></tr><tr><td rowspan="4">Intention to increase children's legume consumption</td><td>Relative importance of price</td><td><strong>- 0.04*</strong></td><td>0.002</td><td>0</td></tr><tr><td>Relative importance of familiarity</td><td>- 0.04</td><td><strong>- 0.005*</strong></td><td>13</td></tr><tr><td>Perceived cost of changing habits</td><td><strong>- 0.04*</strong></td><td>- 0.0005</td><td>1</td></tr><tr><td>Feeling of powerlessness</td><td><strong>- 0.04*</strong></td><td>- 0.003</td><td>8</td></tr></tbody></table>

Results of 8 mediation models, adjusted for parent's age and gender. *p <0.05

**p<0.01. Models are adjusted by age and gender.

The association between financial scarcity and a lower intention to increase legume consumption was significantly explained by a higher importance of familiarity in food choices (13 % of the total effect). This mediation was almost significant for children's legume consumption (p = 0.05).

In an exploratory analysis, the relative importance of health appeared to be a significant mediator of the association between financial scarcity and the intention to consume more legumes (indirect effect β = - 0.008, p = 0.004, 15 % of the total effect). The relative importance of natural content and weight control played no role in the association between financial scarcity and intention.
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After adjustment for education level, marital status and current legume consumption frequency, the indirect effect of the familiarity motive remained significant (indirect effect $\beta$ = -0.005, $p$ = 0.04, 11 % of the total effect).

<figure><img src="image_3.png" /></figure>

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<caption>**Figure 2** – Graphical representations of the mediation models.
*p < 0.05 **p<0.01. Models are adjusted by age and gender.</caption>

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The aim of this study was to understand the effects of perceived financial scarcity on parents' intention to adopt a more sustainable diet. Our results contribute to the literature on the link between socioeconomic position and dietary determinants by showing that, within parents, perceived financial scarcity is indeed associated with a higher importance of price and familiarity in food choices, a higher perceived cost of changing dietary habits and a higher feeling of powerlessness to influence the food system through food choices. Moreover, parents facing greater financial hardship tend to show lower intention to increase their legume consumption, which is partially explained by the importance of the familiarity motive. However, the intention to reduce meat consumption is overall low among the population, regardless of the financial situation.

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The scarcity mindset applied to food choices

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To our knowledge, few studies have applied the scarcity theory in an observational study to explore food choice processes (van der Veer et al., 2024). Here, we have modelized the different mechanisms described in this theory by specific variables applied to food choices: *tunneling* by a greater importance of price in food choices, *taxed mental bandwidth* by a greater importance of familiarity in food choices and a greater perceived cost to shift from habits, and *present time orientation* by a feeling of powerlessness to influence the environment through individual choices. Our results confirmed our hypotheses H1, H2 and H3, showing that financial scarcity is indeed associated with a scarcity mindset influencing food choice processes.

First, financial hardship affects motivations: parents experiencing greater financial hardship put greater emphasis on price and familiarity when making food choices. This observation is in accordance with previous quantitative studies using income as a socioeconomic variable (Steptoe et al., 1995; Steenhuis et al., 2011; Konttinen et al., 2013, 2021) and with previous
qualitative research showing that parents on a low budget tend to prioritise cheap and familiar foods (Wiig Dammann & Smith, 2009; Burns et al., 2013; Ravikumar et al., 2022). In contrast, food choices were less motivated by health, weight control and natural content. Several studies have observed this trend based on income (Konttinen et al., 2013; DiSantis et al., 2014; Robinson et al., 2022), but most studies have used absolute ratings of food choice motives and not relative importance. A recent study conducted in the United Kingdom also observed an association between household food insecurity (defined as a lack of access to acceptable and nutritionally adequate food in acceptable ways) (Anderson, 1990) and a higher importance of price but also a lower importance of health through psychological distress (Evans et al., 2025). Such a motivational pattern has been associated with a less sustainable diet among adults (Allès et al., 2017; Konttinen et al., 2013; Marty et al., 2022; Evans et al., 2025) and children (Roos et al., 2012; Oellingrath et al., 2013; Russell et al., 2015).

Second, our results show that parents experiencing financial hardship not only tend to choose more familiar foods, but they also perceive a shift from their habits as more costly in terms of monetary cost, cognitive cost and overall difficulty. This highlights that consumers experiencing financial hardship do not only perceive a dietary change as expensive, but also as cognitively effortful. This result is coherent with literature documenting a higher risk aversion and a preference for habitual decision-making in low-income populations (Haushofer & Fehr, 2014) and in particular in low-income families (Daniel, 2016). To the best of our knowledge, few studies have quantitatively assess the perceived cost of changing habits. In France, one study assessed the cost of sustainable food practices but the items explicitly mentioned sustainability in a broad meaning, focusing on overall difficulty rather than on multiple types of cost (Innocent et al., 2023). Our results are coherent with previous research showing that a higher feeling of financial hardship is associated with a higher perceived effort to carry out pro-environmental behaviours, such as reducing meat consumption and consuming fruits and vegetables with flaws (Berthold et al., 2023).

Third, parents experiencing financial hardship tend to feel disempowered regarding the impact of the food system on the environment. This results is coherent with a previous study conducted with consumers experiencing food insecurity in France (Verdeau & Monnery-Patris, 2024). Several qualitative studies have highlighted the lack of future perspectives of consumers facing financial hardship when it comes to food choices (van der Veer et al., 2024). Our result echoes the eco-powerlessness of lower-status consumers, who are concerned by environmental issues but feel frustrated and resigned (Kennedy & Givens, 2019).

## A lower intention to increase legume consumption

Moreover, we found that parents experiencing financial hardship were half as likely to intend to increase their legume consumption. This association was observed even after adjustment for education level and declared legume consumption. In Finland, perceived financial hardship was associated with a lower intention to increase plant-based meat alternatives, but not legumes (Kuosmanen et al., 2023). Moreover, in that study, participants experiencing greater financial hardship cited more often high price, lack of familiarity and tedious preparation as barriers. In contrast, in our study, both food groups were considered as a whole: our result may be partly explained by the higher price perception of plant-based meat alternatives (tofu, plant-based steaks...), and not legumes, who constitute one of the cheapest food groups in France (Vieux et al., 2025).

Our mediation analysis revealed that more than 10 % of this association was explained by a higher importance of familiarity in food choice motives. As legumes currently play a negligible role in the average French diet (Darmon et al., 2025), parents who seek to maintain habitual choices could be reluctant to increase exposure to unfamiliar foods. A lower importance of health also contributed to this association, which is consistent with the fact that health is the main motivation to consume legumes in France, especially among wealthier consumers (Reuzé et al., 2022).
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Other mechanisms could contribute to this reluctance. Legumes carry the negative image of “poor man’s meat” (Palmer et al., 2018), which low-income consumers could wish to avoid. Legumes can also be labelled as “food for vegetarians” (Melendrez-Ruiz et al., 2019), which could be identified as a higher socioeconomic status value (Einhorn, 2021); in our study, parents experiencing greater financial scarcity were less likely to declare the presence of vegetarians or vegans in their household. However, in France, vegetarians tend to be overrepresented in middle-income rather than in high-income groups (de Gavelle et al., 2019). Contrary to our hypothesis, perceived cost did not mediate the association between financial scarcity and low intention to shift towards a more plant-based diet. This is in contrast with previous literature on the cost of pro-environmental behaviours (Tobler et al., 2012; Gifford & Chen, 2017; Berthold et al., 2023), which has been identified as a strong mediator between attitudes and behaviours. This may be linked to a difference in the study design, as we measured the intention for specific food groups and not for other pro-environmental behaviours such as organic food purchases or food waste reduction behaviours.

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## Overall low intention to shift towards more plant-based dietary patterns

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Overall, the feeling of financial hardship did not predict the intention to shift towards a more sustainable diet, leading to reject our hypothesis H4 (except for legumes). In different studies, the intention to shift towards more sustainable diets was not associated with income (Lehmann et al., 2025), food insecurity or perceived financial hardship (van der Velde et al., 2022). In New Zealand, meat “reducers” were more likely to have higher incomes while “occasional meat eaters” were more likely to have lower incomes (Kemper et al., 2023). Its seems that income does not predict the intention to cut down on meat consumption, but the intention to reduce meat consumption may be a choice motivated by health and environmental considerations for wealthier consumers, whereas an occasional meat consumption may be an economic constraint for less well-off consumers. Previous research has shown that curtailment behaviours (i.e. reducing meat) are more common among individuals with a low income while product choice (i.e. choosing products with sustainability labels) are more common among individuals with a higher income (Verain et al., 2015). In order to reduce desirability biases, our intention assessment did not distinguish these two mechanisms as it did not explicitly mention the idea of meat “reduction”. Thus, we may have observed these two trends simultaneously, masking the effect of financial hardship. We did not observe any effect of perceived financial scarcity on the intention, but intention was low in the whole sample. Indeed, few parents declared an intention to decrease their meat consumption (less than 15 %). This is consistent with a study conducted in 2018 in France, with 73 % of a representative sample of adults declaring not being flexitarian and not considering eating meat and fish only very rarely (de Gavelle et al., 2019). Just as parents experiencing financial hardship, better well-off parents had a low intention to shift towards more sustainable patterns, which is coherent with previous literature identifying that an association between high income and low willingness for pro-environmental behaviours is mediated by an optimistic perception of future natural resources (Berthold et al., 2023).

Notably, parents experiencing greater financial hardship were more inclined to increase their fruit and vegetable consumption. However, this association was not observed anymore after adjustment for current consumption, as they were consuming less frequently these foods. This result is consistent with previous literature showing that low-income consumers are aware that their fruit and vegetable intake is suboptimal and intend to consume more, but face several barriers, leading to frustration (van der Heijden et al., 2021; Bell et al., 2022; Ravikumar et al., 2022; Screti et al., 2024).

Overall, our results show that the more difficult the financial situation, the more parents make food choices based on prices and habits and perceive dietary changes as a costly effort for themselves and of no benefit to the environment, but this little affects the intention to shift towards a more plant-based diet, which is low in the general population. The scarcity mindset could influence food choices without a mediation by intention, but our results do not provide
evidence to support this. Although this was not hypothesised in our study, financial hardship was associated with a less sustainable dietary pattern (less frequent consumption of fruit, vegetables, nut and seeds, more frequent consumption of meat). These observations are consistent with literature, although meat consumption has been little associated with income in France (Bocquier et al., 2015; Perignon et al., 2023). Although our non-quantitative food frequency questionnaire does not provide precise data, this trend indicates that families experiencing greater financial hardship face more barriers to adopt more sustainable diets, without necessarily having a lower intention to do so. Financial hardship also seems to have less influence on food choices when it comes to children, whether in terms of intention or consumption frequency. This is consistent with previous literature showing that low-income parents tend to sacrifice themselves (Attree, 2005; Burns et al., 2013; Bell et al., 2022), which has a protective effect on children's diet quality (Hanson & Connor, 2014). However, financial scarcity predicted the frequency of meals prepared outside the home both for parents and for children, which is coherent with previous literature in France, especially since children from low socioeconomic families are less often registered for school meals (Caillavet et al., 2009; ANSES, 2017; Cnesco, 2017). This result confirms that the opportunity to promote more sustainable diets through school meals, for instance by introducing weekly vegetarian meals (Dahmani et al., 2024), remains limited in terms of socioeconomic equality.

## 617 Strengths and limitations

Our study has several strengths. To the best of our knowledge, this is the first study to show an association between financial situation and food choice motives in France using quantitative scales. We have used an innovative approach to assess financial scarcity, with a recently validated 8-item scale (Auger et al., 2024) whereas previous research often used 1 to 3-item scales (Conklin et al., 2014; van der Velde et al., 2022; Berthold et al., 2023). The observed associations with gender, marital status, education level, employment and food frequency consumption contribute to reinforce the external validity of this scale. Our study is one of the first observational and quantitative studies drawing on the scarcity theory, and the results contribute to the reflexion on the mechanisms involved in the socioeconomic gradient of food consumption (Darmon & Drewnowski, 2015).

Our study also has different limitations. All data were self-reported and thus subject to desirability bias. Participants were members of an online panel, with a slightly overrepresentation of employed (Drees, 2024) and higher-educated parents (Insee, 2021a). However, 22 % of the sample declared a difficult or very difficult financial situation, which is coherent with data on general population (Insee, 2025). Online self-administered surveys present risks of low data quality due to respondent's inattention (Vecchio et al., 2020). However, "professional respondents" can provide good quality data (Matthijsse et al., 2015; Zhang et al., 2020) and we excluded more than 15 % of the sample to ensure better reliability. Eventually, our assessment of intention as a binary variable is limited. While reducing desirability bias, our method lacked variability, which limited the power of statistical analyses.

## 638 Conclusion

This study highlights the psychological mechanisms involved in food choices by parents experiencing a difficult financial situation. The more parents perceive financial scarcity, the more they make their choices based on price and familiarity with food, the more they perceive a dietary change as a costly effort and the more they perceive individual food choices as pointless in protecting the environment. Their motivational pattern contributes to a lower intention to increase legume consumption, despite legumes being one of the most affordable, healthy and environmentally friendly food groups. These results highlight the importance of considering the dimension of acceptability when designing interventions promoting more sustainable food choices, especially for low-income parents.
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# Acknowledgements

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The authors would like to thank all participants and the Panelabs team for its collaboration.

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# Funding

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This research was supported by grants from the Ministère de l'Enseignement Supérieur et de la Recherche (Ecole Doctorale Environnements-Santé of the University Bourgogne Franche-Comté). This research was also supported by the Institut Olga Triballat. The funding source did not play any role in the study design, the collection and interpretation of data, the writing of the report and the decision to submit the article for publication.

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# Conflict of interest disclosure

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The authors declare that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article. The authors declare the following non-financial conflict of interest: One author is recommender and member of the managing board of PCI Nutrition: LM.

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# Data, scripts, code, and supplementary information availability

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Data and scripts are available online: https://doi.org/10.17605/OSF.IO/7BWJM (Verdeau et al., 2025).

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# CRediT Authorship contribution statement

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BV: Conceptualization, Methodology, Funding acquisition, Investigation, Data curation, Formal analysis, Writing – Original draft, Writing – Review & editing. LM: Conceptualization, Methodology, Writing – Review & editing. SMP: Supervision, Project administration, Conceptualization, Methodology, Funding acquisition, Writing – Review & editing.

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# References

671

672

673

674

Agreste, & FranceAgriMer. (2025). *En 2024, la consommation de viande de volailles rattrape celle de viande de porc* (Synthèses Conjoncturelles No. 443). https://www.franceagrimer.fr/sites/default/files/2025-07/SYN-VIA-Conso%20viande%20Fce2024_0.pdf

675

676

677

678

Allès, B., Péneau, S., Kesse-Guyot, E., Baudry, J., Hercberg, S., & Méjean, C. (2017). Food choice motives including sustainability during purchasing are associated with a healthy dietary pattern in French adults. *Nutrition Journal*, 16(1), 58. https://doi.org/10.1186/s12937-017-0279-9

679

680

681

Anderson, S. A. (1990). Core Indicators of Nutritional State for Difficult-to-Sample Populations. *The Journal of Nutrition*, 120(Suppl 11), 1555–1598. https://doi.org/10.1093/jn/120.suppl_11.1555

682

683

684

ANSES. (2017). *Étude individuelle nationale des consommations alimentaires 3 (INCA 3)*. Rapport d'expertise collective. https://www.anses.fr/fr/system/files/NUT2014SA0234Ra.pdf

685

686

687

Attree, P. (2005). Low-income mothers, nutrition and health: A systematic review of qualitative evidence. *Maternal & Child Nutrition*, 1(4), 227–240. https://doi.org/10.1111/j.1740-8709.2005.00022.x

688

689

690

Auger, V., Sommet, N., & Normand, A. (2024). The Perceived Economic Scarcity Scale: A valid tool with greater predictive utility than income. *British Journal of Social Psychology*, 63(3), 1112–1136. https://doi.org/10.1111/bjso.12719
691 Baudry, J., Allès, B., Langevin, B., Reuzé, A., Brunin, J., Touvier, M., Hercberg, S., Lairon, D., Péneau, S., Pointiereau, P., & Kesse-Guyot, E. (2023). Associations between measures of socio-economic position and sustainable dietary patterns in the NutriNet-Santé study. *Public Health Nutrition, 26*(5), 965-975. https://doi.org/10.1017/S1368980022002208

695 Bell, Z., Scott, S., Visram, S., Rankin, J., Bambra, C., & Heslehurst, N. (2022). Experiences and perceptions of nutritional health and wellbeing amongst food insecure women in Europe: A qualitative meta-ethnography. *Social Science & Medicine, 311*, 115313. https://doi.org/10.1016/j.socscimed.2022.115313

699 Berland, O., Etilé, F., & Soler, L.-G. (2023). Inflation des prix alimentaires: Quelles conséquences possibles pour les ménages modestes? *Cahiers de Nutrition et de Diététique, 58*(2), 83-85.

702 Berthold, A., Cologna, V., Hardmeier, M., & Siegrist, M. (2023). Drop some money! The influence of income and subjective financial scarcity on pro-environmental behaviour. *Journal of Environmental Psychology, 91*, 102149. https://doi.org/10.1016/j.jenvp.2023.102149

705 Bocquier, A., Vieux, F., Lioret, S., Dubuisson, C., Caillavet, F., & Darmon, N. (2015). Socio-economic characteristics, living conditions and diet quality are associated with food insecurity in France. *Public Health Nutrition, 18*(16), 2952-2961. https://doi.org/10.1017/S1368980014002912

709 Brunin, J., Allès, B., Péneau, S., Reuzé, A., Pointiereau, P., Touvier, M., Hercberg, S., Lairon, D., Baudry, J., & Kesse-Guyot, E. (2022). Do individual sustainable food purchase motives translate into an individual shift towards a more sustainable diet? A longitudinal analysis in the NutriNet-Santé cohort. *Cleaner and Responsible Consumption, 5*, 100062. https://doi.org/10.1016/j.clrc.2022.100062

714 Burns, C., Cook, K., & Mavoa, H. (2013). Role of expendable income and price in food choice by low income families. *Appetite, 71*, 209-217. https://doi.org/10.1016/j.appet.2013.08.018

716 Caillavet, F., Lecogne, C., & Nichèle, V. (2009). La consommation alimentaire: Des inégalités persistantes mais qui se réduisent. In *Cinquante ans de consommation en France* (Insee Références, pp. 49-62).

719 Chafwehé, B., Ricci, M., & Stöhlker, D. (2024). The Impact of the Cost-of-Living Crisis on European Households. *JRC Working Papers on Taxation and Structural Reforms, 01/2024*. https://doi.org/10.2139/ssrn.4834596

722 Cnesco. (2017). *Qualité de vie à l'école. Enquête sur la restauration et l'architecture scolaires* (p. 36). https://www.cnesco.fr/wp-content/uploads/2017/10/170929_Note_QdeVie_VF.pdf

724 Conklin, A. I., Forouhi, N. G., Suhrcke, M., Surtees, P., Wareham, N. J., & Monsivais, P. (2014). Variety more than quantity of fruit and vegetable intake varies by socioeconomic status and financial hardship. Findings from older adults in the EPIC cohort. *Appetite, 83*, 248-255. https://doi.org/10.1016/j.appet.2014.08.038

728 Dahmani, J., Nicklaus, S., & Marty, L. (2024). Willingness for more vegetarian meals in school canteens: Associations with family characteristics and parents' food choice motives in a French community. *Appetite, 193*, 107134. https://doi.org/10.1016/j.appet.2023.107134

731 Daniel, C. (2016). Economic constraints on taste formation and the true cost of healthy eating. *Social Science & Medicine, 148*, 34-41. https://doi.org/10.1016/j.socscimed.2015.11.025

733 Daniel, C. (2020). Is healthy eating too expensive?: How low-income parents evaluate the cost of food. *Social Science & Medicine, 248*, 112823. https://doi.org/10.1016/j.socscimed.2020.112823

736 Darmon, N., & Drewnowski, A. (2015). Contribution of food prices and diet cost to socioeconomic disparities in diet quality and health: A systematic review and analysis. *Nutrition Reviews, 73*(10), 643-660. https://doi.org/10.1093/nutrit/nuv027

739 Darmon, N., Poinsot, R., Vieux, F., Niot, I., Wilfart, A., Delarue, J., Morio, B., Granier, B., & Gazan, R. (2025). How to conciliate nutritional and environmental targets of adult diet in France while halving current meat consumption? *Cahiers de Nutrition et de Diététique, 60*(3), e1-e11. https://doi.org/10.1016/j.cnd.2024.11.001

743 Dassen, F. C. M., Houben, K., & Jansen, A. (2015). Time orientation and eating behavior: Unhealthy eaters consider immediate consequences, while healthy eaters focus on future health. *Appetite, 91*, 13-19. https://doi.org/10.1016/j.appet.2015.03.020
746

de Bruijn, E.-J., & Antonides, G. (2022). Poverty and economic decision making: A review of scarcity theory. *Theory and Decision, 92*(1), 5-37. https://doi.org/10.1007/s11238-021-09802-7

747

de Gavelle, E., Davidenko, O., Fouillet, H., Delarue, J., Darcel, N., Huneau, J.-F., & Mariotti, F. (2019). Self-declared attitudes and beliefs regarding protein sources are a good prediction of the degree of transition to a low-meat diet in France. *Appetite, 142*, 104345. https://doi.org/10.1016/j.appet.2019.104345

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

773

774

775

776

777

778

779

780

781

782

783

784

785

786

787

788

789

790

791

792

793

794

795

796

797

798

799

800

801

Drees. (2024). L'articulation entre vies familiale et professionnelle repose toujours fortement sur les mères. *Etudes et Résultats, 1298*. https://drees.solidarites-sante.gouv.fr/publications-communique-de-presse/etudes-et-resultats/larticulation-entre-vies-familiale-et

Einhorn, L. (2021). Meat consumption, classed?: The socioeconomic underpinnings of dietary change. *Österreichische Zeitschrift Für Soziologie, 46*(2), 125-146. https://doi.org/10.1007/s11614-021-00452-1

Evans, R., Christiansen, P., Bateson, M., Nettle, D., Keenan, G. S., & Hardman, C. A. (2025). Understanding the association between household food insecurity and diet quality: The role of psychological distress, food choice motives and meal patterning. *Appetite, 212*, 108007. https://doi.org/10.1016/j.appet.2025.108007

FAO. (2010). *Sustainable Diets and Biodiversity: Directions and Solutions for Policy, Research and Action*. FAO. https://www.fao.org/4/i3004e/i3004e.pdf

FAO, IFAD, UNICEF, WFP, & WHO. (2025). *The State of Food Security and Nutrition in the World 2025*. FAO; IFAD; UNICEF; WFP; WHO; https://doi.org/10.4060/cd6008en

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. *Behavior Research Methods, 41*(4), 1149-1160. https://doi.org/10.3758/BRM.41.4.1149

Gifford, R., & Chen, A. K. S. (2017). Why aren't we taking action? Psychological barriers to climate-positive food choices. *Climatic Change, 140*(2), 165-178. https://doi.org/10.1007/s10584-016-1830-y

Graça, J., Godinho, C. A., & Truninger, M. (2019). Reducing meat consumption and following plant-based diets: Current evidence and future directions to inform integrated transitions. *Trends in Food Science & Technology, 91*, 380-390. https://doi.org/10.1016/j.tifs.2019.07.046

Grandin, A., Guillou, L., Abdel Sater, R., Foucault, M., & Chevallier, C. (2022). Socioeconomic status, time preferences and pro-environmentalism. *Journal of Environmental Psychology, 79*, 101720. https://doi.org/10.1016/j.jenvp.2021.101720

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). *Multivariate Data Analysis, 8th edition*. Cengage.

Hanson, K. L., & Connor, L. M. (2014). Food insecurity and dietary quality in US adults and children: A systematic review. *The American Journal of Clinical Nutrition, 100*(2), 684-692. https://doi.org/10.3945/ajcn.114.084525

Haushofer, J., & Fehr, E. (2014). On the psychology of poverty. *Science (New York, N.Y.)*, 344(6186), 862-867. https://doi.org/10.1126/science.1232491

Hornsey, M. J., Chapman, C. M., & Oelrichs, D. M. (2021). Ripple effects: Can information about the collective impact of individual actions boost perceived efficacy about climate change? *Journal of Experimental Social Psychology, 97*, 104217. https://doi.org/10.1016/j.jesp.2021.104217

Innocent, M., Guillemot, S., Gabriel, P., & Tamaro, A. (2023). Speeding up the transition to a more sustainable food system: New insights into the links in a system of practices. *Recherche et Applications En Marketing (English Edition)*, 38(3), 77-109. https://doi.org/10.1177/20515707231175756

Insee. (2020). Toujours plus d'habitants dans les unités urbaines. *Insee Focus, 210*. https://www.insee.fr/fr/statistiques/4806684
803

Insee. (2021a). 2.3 Niveau d'éducation de la population. In *France, portrait social* (pp. 142-143).

804

https://www.insee.fr/fr/statistiques/5432451?sommaire=5435421

805

Insee. (2021b). Les familles en 2020: 25 % de familles monoparentales, 21 % de familles

806

nombreuses. *Insee Focus*, 249. https://www.insee.fr/fr/statistiques/5422681

807

Insee. (2024). Revenu, niveau de vie et pauvreté en 2021. Enquête Revenus fiscaux et sociaux

808

(ERFS). Insee

Résultats.

809

https://www.insee.fr/fr/statistiques/7766287?sommaire=7766297

810

Insee. (2025). Pauvreté monétaire, privation et difficultés financières: Des situations qui ne se

811

recouvrent que partiellement. Insee

Analyses,

107.

812

https://www.insee.fr/fr/statistiques/8387882# titre-bloc-24

813

Interfel. (2024).

Bilan de

consommation

2024.

814

https://www.interfel.com/services/documentation/bilan-de-consommation-2024/

815

Kemper, J. A., Benson-Rea, M., Young, J., & Seifert, M. (2023). Cutting down or eating up:

816

Examining meat consumption, reduction, and sustainable food beliefs, attitudes, and

817

behaviors. *Food Quality and Preference*, 104, 104718.

818

https://doi.org/10.1016/j.foodqual.2022.104718

819

Kennedy, E. H., & Givens, J. E. (2019). Eco-habitus or Eco-powerlessness? Examining

820

Environmental Concern across Social Class. *Sociological Perspectives*, 62(5), 646–667.

821

https://doi.org/10.1177/0731121419836966

822

Kenny, T. A., Woodside, J. V., Perry, I. J., & Harrington, J. M. (2023). Consumer attitudes and

823

behaviors toward more sustainable diets: A scoping review. *Nutrition Reviews*, 81(12),

824

1665–1679. https://doi.org/10.1093/nutrit/nuad033

825

Konttinen, H., Halmesvaara, O., Fogelholm, M., Saarijärvi, H., Nevalainen, J., & Erkkola, M.

826

(2021). Sociodemographic differences in motives for food selection: Results from the

827

LoCard cross-sectional survey. *International Journal of Behavioral Nutrition and Physical Activity*, 18(1), 71. https://doi.org/10.1186/s12966-021-01139-2

828

Konttinen, H., Sarlio-Lähteenkorva, S., Silventoinen, K., Männistö, S., & Haukkala, A. (2013).

829

Socio-economic disparities in the consumption of vegetables, fruit and energy-dense

830

foods: The role of motive priorities. *Public Health Nutrition*, 16(5), 873–882.

831

832

https://doi.org/10.1017/S1368980012003540

833

Kuosmanen, S., Niva, M., Pajari, A.-M., Korhonen, K., Muilu, T., & Konttinen, H. (2023). Barriers

834

associated with pulse and plant-based meat alternative consumption across

835

sociodemographic groups: A Capability, Opportunity, Motivation, Behaviour model

836

approach. *Frontiers in Nutrition*, 10, 1186165. https://doi.org/10.3389/fnut.2023.1186165

837

Lacroix, K., Gifford, R., & Chen, A. (2019). Developing and validating the Dragons of Inaction

838

Psychological Barriers (DIPB) scale. *Journal of Environmental Psychology*, 63, 9–18.

839

https://doi.org/10.1016/j.jenvp.2019.03.001

840

Lehmann, J., Trübner, M., Patzina, A., Jeitler, M., Hoffmann, R., & Kessler, C. S. (2025). The

841

willingness to transition to a more plant-based diet among omnivores: Determinants and

842

socioeconomic differences. *Appetite*, 206, 107765.

843

https://doi.org/10.1016/j.appet.2024.107765

844

Maillot, M., Darmon, N., & Drewnowski, A. (2010). Are the lowest-cost healthful food plans

845

culturally and socially acceptable? *Public Health Nutrition*, 13(8), 1178–1185.

846

https://doi.org/10.1017/S1368980009993028

847

Marty, L., Chambaron, S., de Lauzon-Guillain, B., & Nicklaus, S. (2022). The motivational roots

848

of sustainable diets: Analysis of food choice motives associated to health, environmental

849

and socio-cultural aspects of diet sustainability in a sample of French adults. *Cleaner and

850

Responsible Consumption*, 5, 100059. https://doi.org/10.1016/j.clrc.2022.100059

851

Matthijsse, S. M., de Leeuw, E. D., & Hox, J. J. (2015). Internet Panels, Professional

852

Respondents, and Data

Quality. *Methodology*, 11(3),

853

81–88. https://doi.org/10.1027/1614-2241/a000094

854

McKinnon, L., Giskes, K., & Turrell, G. (2014). The contribution of three components of nutrition

855

knowledge to socio-economic differences in food purchasing choices. *Public Health

856

Nutrition*, 17(8), 1814–1824. https://doi.org/10.1017/S1368980013002036

857

Melendrez-Ruiz, J., Chambaron, S., Buatois, Q., Monnery-Patris, S., & Arvisenet, G. (2019). A

858

central place for meat, but what about pulses? Studying French consumers'
859 representations of main dish structure, using an indirect approach. *Food Research International*, **123**, 790–800. https://doi.org/10.1016/j.foodres.2019.06.004

860 Mullainathan, S., & Shafir, E. (2013). *Scarcity: Why having too little means so much* (p. 289). Times Books/Henry Holt and Co.

861 Neufeld, L. M., Andrade, E. B., Suleiman, A. B., Barker, M., Beal, T., Blum, L. S., Demmler, K. M., Dogra, S., Hardy-Johnson, P., Lahiri, A., Larson, N., Roberto, C. A., Rodríguez-Ramírez, S., Sethi, V., Shamah-Levy, T., Strömmer, S., Tumilowicz, A., Weller, S., & Zou, Z. (2022). Food choice in transition: Adolescent autonomy, agency, and the food environment. *The Lancet*, **399**(10320), 185–197. https://doi.org/10.1016/S0140-6736(21)01687-1

869 Oellingrath, I. M., Hersleth, M., & Svendsen, M. V. (2013). Association between parental motives for food choice and eating patterns of 12- to 13-year-old Norwegian children. *Public Health Nutrition*, **16**(11), 2023–2031. https://doi.org/10.1017/S1368980012004430

872 Palmer, S. M., Winham, D. M., Oberhauser, A. M., & Litchfield, R. E. (2018). Socio-Ecological Barriers to Dry Grain Pulse Consumption among Low-Income Women: A Mixed Methods Approach. *Nutrients*, **10**(8), 1108. https://doi.org/10.3390/nu10081108

875 Penne, T., & Goedemé, T. (2021). Can low-income households afford a healthy diet? Insufficient income as a driver of food insecurity in Europe. *Food Policy*, **99**, 101978. https://doi.org/10.1016/j.foodpol.2020.101978

878 Perignon, M., Masset, G., Ferrari, G., Barré, T., Vieux, F., Maillot, M., Amiot, M.-J., & Darmon, N. (2016). How low can dietary greenhouse gas emissions be reduced without impairing nutritional adequacy, affordability and acceptability of the diet? A modelling study to guide sustainable food choices. *Public Health Nutrition*, **19**(14), 2662–2674. https://doi.org/10.1017/S1368980016000653

883 Perignon, M., Vieux, F., Verger, E. O., Bricas, N., & Darmon, N. (2023). Dietary environmental impacts of French adults are poorly related to their income levels or food insecurity status. *European Journal of Nutrition*, **62**(6), 2541–2553. https://doi.org/10.1007/s00394-023-03163-3

887 Ravikumar, D., Spyreli, E., Woodside, J., McKinley, M., & Kelly, C. (2022). Parental perceptions of the food environment and their influence on food decisions among low-income families: A rapid review of qualitative evidence. *BMC Public Health*, **22**(1), 1–16. https://doi.org/10.1186/s12889-021-12414-z

891 Régnier, F., & Masullo, A. (2009). Obesity, tastes and consumption: Integrating eating norms and social membership. *Revue Française de Sociologie*, **50**, 747–+.

892 Renner, B., Sproesser, G., Strohbach, S., & Schupp, H. T. (2012). Why we eat what we eat. The *Eating Motivation Survey* (TEMS). *Appetite*, **59**(1), 117–128. https://doi.org/10.1016/j.appet.2012.04.004

896 Reuzé, A., Méjean, C., Carrère, M., Sirieix, L., Druesne-Pecollo, N., Péneau, S., Touvier, M., Hercberg, S., Kesse-Guyot, E., & Allès, B. (2022). Rebalancing meat and legume consumption: Change-inducing food choice motives and associated individual characteristics in non-vegetarian adults. *International Journal of Behavioral Nutrition and Physical Activity*, **19**(1), 112. https://doi.org/10.1186/s12966-022-01317-w

901 Reynolds, C. J., Horgan, G. W., Whybrow, S., & Macdiarmid, J. I. (2019). Healthy and sustainable diets that meet greenhouse gas emission reduction targets and are affordable for different income groups in the UK. *Public Health Nutrition*, **22**(8), 1503–1517. https://doi.org/10.1017/S1368980018003774

905 Robinson, E., Jones, A., & Marty, L. (2022). 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*, **46**(10), 1818–1824. https://doi.org/10.1038/s41366-022-01190-4

909 Rochefort, G., Toujgani, H., Berthy, F., Berlivet, J., Perraud, E., Allès, B., Touvier, M., Lamarche, B., Baudry, J., & Kesse-Guyot, E. (2025). Are dietary changes over eight years in the prospective NutriNet-Santé cohort consistent with the EAT-Lancet reference diet? *The American Journal of Clinical Nutrition*, **121**(2), 324–332. https://doi.org/10.1016/j.ajcnut.2024.12.004

914 Rockström, J., Thilsted, S. H., Willett, W. C., Gordon, L. J., Herrero, M., Hicks, C. C., Mason-D'Croz, D., Rao, N., Springmann, M., Wright, E. C., Agustina, R., Bajaj, S., Bunge, A. C.,
916

Carducci, B., Conti, C., Covic, N., Fanzo, J., Forouhi, N. G., Gibson, M. F., ... DeClerck, F. (2025). The EAT-Lancet Commission on healthy, sustainable, and just food systems. *The Lancet*, **406**(10512), 1625–1700. https://doi.org/10.1016/S0140-6736(25)01201-2

917

918

919

Rogissart, L. (2023, February 21). Reducing meat consumption: Public policies a long way from sustainability objectives. *I4CE*. https://www.i4ce.org/en/publication/reducing-meat-consumption-public-policies-a-long-way-from-sustainability-objectives-climate/

920

921

922

Roos, E., Lehto, R., & Ray, C. (2012). Parental family food choice motives and children's food intake. *Food Quality and Preference*, **24**(1), 85–91. https://doi.org/10.1016/j.foodqual.2011.09.006

923

924

925

Russell, C. G., Worsley, A., & Liem, D. G. (2015). Parents' food choice motives and their associations with children's food preferences. *Public Health Nutrition*, **18**(6), 1018–1027. https://doi.org/10.1017/S1368980014001128

926

927

928

Schuler, B. R., Shipe, S. L., O'Reilly, N., Uhl, A., Vazquez, C. E., Tripicchio, G. L., & Hernandez, D. C. (2024). Balancing nutrition and budgets: Socio-ecological impacts on nutritional environments of families with low incomes. *Appetite*, **203**, 107706. https://doi.org/10.1016/j.appet.2024.107706

929

930

931

932

Schuster, R. C., Szpak, M., Klein, E., Sklar, K., & Dickin, K. L. (2019). "I try, I do": Child feeding practices of motivated, low-income parents reflect trade-offs between psychosocial- and nutrition-oriented goals. *Appetite*, **136**, 114–123. https://doi.org/10.1016/j.appet.2019.01.005

933

934

935

936

Screti, C., Edwards, K., & Blissett, J. (2024). Understanding family food purchasing behaviour of low-income urban UK families: An analysis of parent capability, opportunity and motivation. *Appetite*, **195**, 107183. https://doi.org/10.1016/j.appet.2023.107183

937

938

939

Sobal, J., & Bisogni, C. A. (2009). Constructing Food Choice Decisions. *Annals of Behavioral Medicine*, **38**(Suppl 1), s37–s46. https://doi.org/10.1007/s12160-009-9124-5

940

941

Springmann, M., Clark, M. A., Rayner, M., Scarborough, P., & Webb, P. (2021). The global and regional costs of healthy and sustainable dietary patterns: A modelling study. *The Lancet Planetary Health*, **5**(11), e797–e807. https://doi.org/10.1016/S2542-5196(21)00251-5

942

943

944

Steenhuis, I. H., Waterlander, W. E., & Mul, A. de. (2011). Consumer food choices: The role of price and pricing strategies. *Public Health Nutrition*, **14**(12), 2220–2226. https://doi.org/10.1017/S1368980011001637

945

946

947

Steenson, S., & Buttriss, J. L. (2021). Healthier and more sustainable diets: What changes are needed in high-income countries? *Nutrition Bulletin*, **46**(3), 279–309. https://doi.org/10.1111/nbu.12518

948

949

950

Steg, L., & Vlek, C. (2009). Encouraging pro-environmental behaviour: An integrative review and research agenda. *Journal of Environmental Psychology*, **29**(3), 309–317. https://doi.org/10.1016/j.jenvp.2008.10.004

951

952

953

Steptoe, A., Pollard, T. M., & Wardle, J. (1995). Development of a measure of the motives underlying the selection of food: The food choice questionnaire. *Appetite*, **25**(3), 267–284. https://doi.org/10.1006/appe.1995.0061

954

955

956

Tobler, C., Visschers, V. H. M., & Siegrist, M. (2012). Addressing climate change: Determinants of consumers' willingness to act and to support policy measures. *Journal of Environmental Psychology*, **32**(3), 197–207. https://doi.org/10.1016/j.jenvp.2012.02.001

957

958

959

Toujgani, H., Berlivet, J., Berthy, F., Allès, B., Brunin, J., Fouillet, H., Touvier, M., Lairon, D., Mariotti, F., Baudry, J., Kesse-Guyot, E., & the TRANSFood Consortium. (2024). Dietary Pattern Trajectories in French Adults of the NutriNet-Santé Cohort Over Time (2014-2022): Role of Socioeconomic Factors. *British Journal of Nutrition*, **1**–29. https://doi.org/10.1017/S0007114524002514

960

961

962

963

964

van der Heijden, A., te Molder, H., Jager, G., & Mulder, B. C. (2021). Healthy eating beliefs and the meaning of food in populations with a low socioeconomic position: A scoping review. *Appetite*, **161**, 105135. https://doi.org/10.1016/j.appet.2021.105135

965

966

967

van der Veer, A., Madern, T., & van Lenthe, F. J. (2024). Tunneling, cognitive load and time orientation and their relations with dietary behavior of people experiencing financial scarcity – an AI-assisted scoping review elaborating on scarcity theory. *International Journal of Behavioral Nutrition and Physical Activity*, **21**(1), 26. https://doi.org/10.1186/s12966-024-01576-9

968

969

970

971
972

van der Velde, L. A., van Dijk, W. W., Numans, M. E., & Kiefte-de Jong, J. C. (2022). Extending

973

the Theory of Planned Behavior for Explaining Dietary Quality: The Role of Financial

974

Scarcity and Food Insecurity Status. *Journal of Nutrition Education and Behavior*, 54(7),

975

636–646. https://doi.org/10.1016/j.jneb.2022.02.019

Vecchio, R., Caso, G., Cembalo, L., & Borrello, M. (2020). Is respondents’ inattention in online

977

surveys a major issue for research? *Economia Agro-Alimentare/Food Economy - Open*

978

Access, 22(1). https://doi.org/10.3280/ecag1-2020oa10069

Vellinga, R. E., Heerschop, S. N., Biesbroek, S., van 't Veer, P., Drijvers, J., van Bakel, M.,

980

Hollander, A., & Temme, E. H. M. (2025). Diets optimized for environmental sustainability

981

and health: Implications for diet costs across socio-economic positions for Dutch adults.

982

*Frontiers in Nutrition, 12*. https://doi.org/10.3389/fnut.2025.1667399

Verain, M. C. D., Dagevos, H., & Antonides, G. (2015). Sustainable food consumption. Product

983

choice or curtailment? *Appetite, 91*, 375–384. https://doi.org/10.1016/j.appet.2015.04.055

984

Verdeau, B., & Monnery-Patris, S. (2024). When food is uncertain, how much does sustainability

985

matter? A qualitative exploration of food values and behaviours among users of a social

986

grocery store. *Appetite, 194*, 107175. https://doi.org/10.1016/j.appet.2023.107175

Vermeir, I., Weijters, B., De Houwer, J., Geuens, M., Slabbinck, H., Spruyt, A., Van Kerckhove,

988

A., Van Lippevelde, W., De Steur, H., & Verbeke, W. (2020). Environmentally

989

Sustainable Food Consumption: A Review and Research Agenda From a Goal-Directed

990

Perspective. *Frontiers in Psychology, 11*, 1603. https://doi.org/10.3389/fpsyg.2020.01603

Vieux, F., Maillot, M., Marmonier, C., Rouault, A., Perignon, M., & Darmon, N. (2025). Relative

992

environmental impacts and monetary cost of food categories: Functional unit matters.

993

*Ecological Economics, 234*, 108620. https://doi.org/10.1016/j.ecolecon.2025.108620

Wiig Dammann, K., & Smith, C. (2009). Factors Affecting Low-income Women’s Food Choices

996

and the Perceived Impact of Dietary Intake and Socioeconomic Status on Their Health

997

and Weight. *Journal of Nutrition Education and Behavior, 41*(4), 242–253.

998

https://doi.org/10.1016/j.jneb.2008.07.003

Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., Garnett, T.,

1000

Tilman, D., DeClerck, F., Wood, A., Jonell, M., Clark, M., Gordon, L. J., Fanzo, J.,

1001

Hawkes, C., Zurayk, R., Rivera, J. A., De Vries, W., Majele Sibanda, L., ... Murray, C. J.

1002

L. (2019). Food in the Anthropocene: The EAT–Lancet Commission on healthy diets from

1003

sustainable food systems. *The Lancet, 393*(10170), 447–492.

1004

https://doi.org/10.1016/S0140-6736(18)31788-4

Zhang, C., Antoun, C., Yan, H. Y., & Conrad, F. G. (2020). Professional Respondents in Opt-in

1006

Online Panels: What Do We Really Know? *Social Science Computer Review, 38*(6),

1007

703–719. https://doi.org/10.1177/0894439319845102

1008