Meat Consumption Scale

1. Abstract

The Meat Consumption Scale (MCS) is an empirically validated psychometric instrument designed to evaluate self-reported animal protein intake and forward-looking dietary behavioral intentions. Developed in response to escalating planetary health crises and chronic disease burdens associated with high meat intake, the MCS provides behavioral scientists, nutritional epidemiologists, and environmental psychologists with a standardized, brief, and psychometrically robust measurement tool. Comprising 12 operational items, the multidimensional scale captures both retrospective behavior across a two-week window and prospective behavioral intentions over an equivalent future timeframe. The behavioral dimension evaluates six distinct meat categories: beef, lamb, poultry, pork/bacon/ham, other processed meats, and fish/seafood. Consumption quantification uses an interactive multiplicative algorithm combining reported intake frequency with typical portion sizes assessed on a five-point metric. The prospective behavioral intention dimension measures motivational readiness to alter intake on a bipolar nine-point continuum ranging from −4 to +4. Developed and validated in Australia among adult consumers, the MCS demonstrates robust structural validity derived via exploratory factor analysis, resolving historical measurement issues associated with lengthy food frequency questionnaires and unvalidated single-item queries. Nomological network testing confirms convergent and construct validity through significant associations with the Theory of Planned Behavior constructs, traditional masculine norm conformity, social dominance orientation, animal empathy, and habit strength. The MCS represents an essential advancement for evaluating public health and ecological dietary interventions.

2. Keywords

meat consumption, dietary intentions, psychometrics, environmental psychology, plant-based diet, scale development, behavioral change, nutritional assessment, social dominance orientation, theory of planned behavior

3. Authors

The Meat Consumption Scale was conceptualized, developed, and psychometrically validated by researchers based in Melbourne, Australia:

• Lauren Camilleri — Institute for Health and Sport, Victoria University, Melbourne, Australia. Email: [email protected]
• Andrew Jago — Institute for Health and Sport, Victoria University, Melbourne, Australia.
• Abdul Rehman — Victoria University, Melbourne, Australia.
• Peter Richard Gill — Institute for Health and Sport, Victoria University, Melbourne, Australia.

4. Purpose

Global food production systems account for over a quarter of anthropogenic greenhouse gas emissions, with livestock rearing and feed crop cultivation exerting disproportionately severe pressure on freshwater reserves, land availability, and terrestrial biodiversity. Concurrently, high epidemiological consumption of red and processed meats has been definitively linked to increased all-cause mortality, cardiovascular diseases, colorectal malignancies, and type 2 diabetes mellitus. Despite broad consensus from advisory bodies such as the EAT-Lancet Commission urging rapid global transitions toward plant-forward diets, behavioral change remains slow, culturally resisted, and difficult to quantify reliably.

Historically, researchers investigating dietary transitions have faced a difficult methodological trade-off:

• Exhaustive Food Frequency Questionnaires (FFQs) contain dozens or hundreds of line items. While comprehensive, they impose severe respondent burden, trigger cognitive fatigue, and suffer from retrospective recall decay when asking participants to aggregate intake over six or twelve months.
• Ad-hoc single-item indicators (e.g., “How often do you eat meat?” or binary “Are you a vegetarian?” items) lack granularity, fail to capture portion variances, suffer from substantial measurement error, and cannot reliably detect incremental dietary reductions.

The MCS resolves this dilemma by delivering a targeted, psychometrically validated instrument that can be completed in under five minutes. The scale serves critical functions in both basic behavioral research and applied intervention trials:

• Intervention Evaluation: Measuring subtle shifts in both consumption frequency and volume following health-framed, animal-welfare, or environmental-nudging interventions.
• Psychological Modeling: Testing structural equation models that investigate how socio-cognitive, affective, and ideological variables predict real-world dietary reduction.
• Cross-Sectional Epidemiology: Providing a standardized dependent variable to facilitate replication and meta-analytic synthesis across behavioral science labs worldwide.

5. Psychological Construct

The MCS operationalizes meat consumption not as an immutable demographic trait or a crude binary status, but as a continuous, dynamic psychological and behavioral construct comprising two core dimensions:

1. Retrospective Consumption Behavior

Dietary impact is fundamentally a function of both behavioral frequency and volumetric mass. The MCS calculates actual consumption as the continuous product of behavioral frequency (number of eating occasions across a standardized 14-day window) and typical portion size (graded from very small to very large on a five-point scale) across six distinct animal protein categories:

• Beef: High-emissions mammalian red meat.
• Lamb: Small ruminant red meat with high agricultural greenhouse gas intensity.
• Poultry: Avian meat (chicken, turkey, duck) representing high-volume global consumption.
• Pork, Bacon, and Ham: Consolidated swine products combining unprocessed cuts with cured variants.
• Other Processed Meats: Cured, smoked, or chemically preserved animal products (e.g., sausages, salami, hot dogs) carrying established epidemiological risks.
• Fish and Seafood: Marine and freshwater vertebrates and invertebrates, addressing marine resource depletion and blue carbon ecological impacts.

2. Prospective Behavioral Intention

Grounded in social cognitive theory, behavioral intention represents an individual’s conscious motivational readiness, resolve, and subjective probability of performing a target behavior. Rather than measuring vague “willingness” or passive openness to plant-based diets, the MCS evaluates concrete commitments to alter animal protein intake over the upcoming two-week timeframe. By utilizing a bipolar nine-point continuum centered at zero (−4 = strong intention to decrease intake drastically, 0 = intention to maintain current consumption, +4 = strong intention to increase intake drastically), the scale captures both downward dietary transitions and defensive or compensatory dietary escalations.

6. Theoretical Framework

The conceptual architecture of the MCS draws upon several foundational theories in psychology and sociology:

Theory of Planned Behavior (TPB)

Formulated by Icek Ajzen, the TPB posits that behavioral execution is directly determined by behavioral intention, which in turn is driven by:

• Attitudes: Personal evaluative judgments regarding whether consuming or reducing meat is advantageous, healthy, pleasant, or ethical.
• Subjective Norms: Perceptions of social expectations from significant others and broader cultural reference groups.
• Perceived Behavioral Control (PBC): Self-efficacy and perceived ease or difficulty in sourcing, cooking, and sustaining lower-meat dietary alternatives.

The MCS directly implements the TPB paradigm by measuring behavioral intention as the proximal cognitive precursor to action, while establishing standardized temporal equivalence between past performance and future intention.

The Transtheoretical Model of Behavior Change (TTM)

Developed by James O. Prochaska and Carlo DiClemente, the TTM conceptualizes health behavior modification through distinct stages: precontemplation, contemplation, preparation, action, and maintenance. The MCS’s bipolar intention structure allows researchers to segment participants along this continuum, differentiating unmotivated individuals (neutral/zero score) from those actively preparing to reduce consumption (negative intention scores).

Sociological and Ideological Frameworks: Masculinity, Dominance, and Dissonance

Meat consumption is deeply embedded in social identity, gender performance, and intergroup ideology:

• Hegemonic Masculinity: Sociological research highlights meat—particularly red meat—as a cultural signifier of virility, power, and physical strength. Adherence to traditional masculine norms frequently acts as a barrier to meat reduction.
• Social Dominance Theory (SDT): Endorsement of hierarchical group arrangements and human dominance over the natural world and non-human animals correlates strongly with meat consumption and hostility toward vegan/vegetarian lifestyles.
• The Meat Paradox and Cognitive Dissonance: The psychological tension experienced by omnivores who care about animal welfare while simultaneously consuming animal flesh is often resolved through defensive dietary justifications (the 4Ns: natural, normal, necessary, nice).

7. Validity

The MCS was subjected to construct, convergent, and discriminant validation against a comprehensive nomological network of established instruments:

Nomological Network and Convergent Validation

In the validation study conducted by Camilleri and colleagues, bivariate correlations demonstrated clear theoretical coherence:

• Attitude toward Eating Meat: Strongly positively correlated with MCS consumption and intention scores, confirming that favorable hedonic and utilitarian appraisals predict greater intake.
• Subjective Norms: Significant positive correlations showed that perceived social approval reinforces regular meat-eating habits.
• Perceived Behavioral Control: Correlated significantly with dietary self-regulation and intention stability.
• Self-Report Habit Index (SRHI – Meat): High habit automaticity correlated robustly with retrospective consumption, highlighting the automatic nature of dietary routines.
• Meat-Eating Justifications (MEJ): Strong positive associations with belief systems framing meat as natural, necessary, normal, and nice.
• Conformity to Masculine Norms Inventory (CMNI-SF): Demonstrated significant positive associations with red and processed meat intake among men.
• Short Social Dominance Orientation (SSDO): Positively correlated with meat consumption, supporting ideological models of interspecies hierarchy.

Discriminant and Divergent Associations

• Animal Empathy: Exhibited strong, statistically significant inverse correlations with MCS consumption scores, confirming that affective sensitivity to animal suffering suppresses meat intake.
• Food Disgust Scale (Animal Flesh Disgust Subscale): Strongly and negatively associated with meat consumption frequency and portion volume.
• Willingness to Reduce Meat Scale: Showed substantial negative correlations with MCS intention scores, verifying that higher willingness aligns with intentions to decrease meat consumption.

8. Reliability

The MCS was engineered to minimize measurement error and cognitive recall bias inherent in long-term food frequency measures:

• Temporal Recall Window: By restricting retrospective recall to a 14-day (two-week) window, the MCS balances situational stability with episodic memory accuracy, avoiding the significant recall decay observed in 6- to 12-month FFQ recall windows.
• Multi-Item Reliability: Assessing six distinct food types separately avoids the severe variance compression and measurement error typical of single-item dietary questions.
• Internal Consistency of Validation Battery: In the validation sample, comparator scales exhibited strong reliability coefficients: Animal Empathy Scale (α = .93), Subjective Norms Scale (α = .86), Conformity to Masculine Norms (α = .83), Attitude toward Meat (α = .82), and Social Dominance Orientation (α = .80).
• Composite Score Stability: The summed frequency-by-portion algorithms demonstrated high internal consistency across meat categories, establishing stable indices for both total meat intake and distinct protein subcategories (e.g., ruminant red meat vs. white meat vs. seafood).

9. Factor Analysis

The structural integrity and latent factor configuration of the scale were evaluated using Exploratory Factor Analysis (EFA):

Exploratory Factor Analysis (EFA) Strategy and Refinement

• Initial Item Pool: The initial development phase included 24 items assessing varied animal protein foods, food preparation styles, and behavioral intentions.
• Factor Extraction and Rotation: Principal axis factoring and oblique rotation methods were utilized to accommodate anticipated correlations between dietary intake dimensions.
• Empirical Category Merging: EFA item loadings and cross-loading patterns revealed substantial conceptual and empirical overlap between standalone pork items and cured pork products (bacon and ham). Merging these items into a single “Pork, bacon, and ham” category significantly improved model parsimony and eliminated cross-loading distortions.
• Finalized 12-Item Structure: The final instrument retained 12 items: six retrospective behavioral items (capturing frequency and portion size across six categories) and six corresponding prospective intention items.
• Factor Interpretation: The resulting two-factor solution clearly delineated: Factor 1: Past Behavioral Intake (accounting for the majority of observed variance in volumetric consumption) and Factor 2: Prospective Behavioral Intention.

10. Instrument / Measurement Tool

• Test Type: Standardized self-report behavioral and intentional questionnaire.
• Target Population: Adult consumers (general population, aged 18+).
• Administration Mode: Self-administered digitally via online survey platforms or on paper.
• Administration Time: Typically under 5 minutes.
• Item Count: 12 total items (comprising 6 meat categories evaluated across past behavior and future intention).
• Evaluated Meat Categories:
  1. Beef
  2. Lamb
  3. Poultry (chicken, turkey, etc.)
  4. Pork, bacon, and ham
  5. Other processed meats (sausages, salami, hot dogs, deli slices, etc.)
  6. Fish and seafood
• Response Scale & Formats:
  • Consumption Frequency: Continuous whole number entry representing the number of eating occasions in the past 14 days (0 to 14+).
  • Portion Size: 5-point ordinal scale (1 = Very small, 2 = Small, 3 = Medium, 4 = Large, 5 = Very large).
  • Behavioral Intention: 9-point bipolar integer scale ranging from −4 to +4 (−4 = Strongly intend to decrease, 0 = Intend to keep intake the same, +4 = Strongly intend to increase).
• Scoring Algorithm:
  • Category Consumption Score: Frequency × Portion Size for each of the six meat categories.
  • Total Consumption Score: Sum of the six category consumption scores: ∑ (Frequency_i × Portion_i). Higher scores indicate greater aggregate volume of animal protein consumed over the previous two weeks.
  • Total Intention Score: Sum of the six prospective intention items. Negative overall scores indicate motivational readiness to reduce total meat intake; scores near zero reflect maintenance; positive scores reflect intentions to increase meat intake.

11. Permissions & Fee and Test Year

• Test Year: Developed and published in 2025.
• Developers: Lauren Camilleri, Andrew Jago, Abdul Rehman, and Peter Richard Gill (Victoria University, Melbourne, Australia).
• Publication Source: Published in BMC Psychology (2025).
• Permissions and Access: The complete item text, operational rating templates, and administration protocol are managed under academic copyright. Qualified researchers seeking to use the MCS for non-commercial academic investigations, epidemiological surveys, or intervention trials should contact the corresponding author, Lauren Camilleri, via email at [email protected].
• Fee: Free for non-commercial academic research upon obtaining institutional authorization from the authors.

12. References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Aleksandrowicz, L., Green, R., Joy, E. J. M., Smith, P., & Haines, A. (2016). The impacts of dietary change on greenhouse gas emissions, land use, water use, and health: A systematic review. PLoS ONE, 11(11), Article e0165797. https://doi.org/10.1371/journal.pone.0165797

Camilleri, L., Jago, A., Rehman, A., & Gill, P. R. (2025). Meat Consumption Scale. BMC Psychology, 13, Article 270. https://doi.org/10.1186/s40359-025-03270-2

Camilleri, L., Richard Gill, P., Scarfo, J., & Jago, A. (2023). Resolving the masculinity dilemma: Identifying subtypes of male meat consumers with latent profile analysis. Food Quality and Preference, 108, Article 104890. https://doi.org/10.1016/j.foodqual.2023.104890

Carfora, V., Conner, M., Caso, D., & Catellani, P. (2020). Rational and moral motives to reduce red and processed meat consumption. Journal of Applied Social Psychology, 50(12), 744–755. https://doi.org/10.1111/jasp.12710

Graça, J., Calheiros, M. M., & Oliveira, A. (2015). Attached to meat? (Un)Willingness and intentions to adopt a more plant-based diet. Appetite, 95, 113–125. https://doi.org/10.1016/j.appet.2015.06.024

Hopwood, C. J., & Bleidorn, W. (2019). Psychological profiles of people who justify eating meat as natural, necessary, normal, or nice. Food Quality and Preference, 75, 10–14. https://doi.org/10.1016/j.foodqual.2019.02.004

Rothgerber, H., & Rosenfeld, D. L. (2021). Meat-related cognitive dissonance: The social psychology of eating animals. Social and Personality Psychology Compass, 15(5), Article e12592. https://doi.org/10.1111/spc3.12592

Scarborough, P., Clark, M., Cobiac, L., Papier, K., Knuppel, A., Lynch, J., & Springmann, M. (2023). Vegans, vegetarians, fish-eaters and meat-eaters in the UK show discrepant environmental impacts. Nature Food, 4(7), 565–574. https://doi.org/10.1038/s43016-023-00795-w

Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., & Murray, C. J. L. (2019). Food in the Anthropocene: The EAT–Lancet Commission on healthy diets from sustainable food systems. The Lancet, 393(10170), 447–492. https://doi.org/10.1016/S0140-6736(18)31788-4

13. Items of the Scale