Understanding the Meat-Masculinity Link: Traditional and Non-Traditional Masculine Norms Predicting Men’s Meat Consumption

Figures & data

Table 1. Sociodemographic Statistics of Sample.

Demographic Variable	N	%
Country Australia England Self-identified diet	313 244	56.2% 43.8%
Unrestricted meat-eater	330	59.2%
Meat-reducer	181	32.5%
Meat-avoider	46	8.3%
Age
18–29	164	29.4%
30–44	240	43.1%
45–59	103	18.5%
≥60	50	9.0%
Education
≤ Secondary school	121	21.7%
Trade/vocational training	95	17.1%
Bachelor’s degree	236	42.4%
Postgraduate degree	105	18.9%
Geographic Location
Metropolitan	440	79.0%
Rural	117	21.0%
Sexual Orientation
Heterosexual	496	89.0%
Homo/bisexual	61	11.0%
Political Views
Left-wing	281	50.4%
Centre	161	28.9%
Right-wing	115	20.6%
Religion
None	370	66.9%
Buddhism	10	1.8%
Christianity	126	22.8%
Hindu	7	1.3%
Islam	12	2.2%
Judaism	4	0.7%
Other	24	4.3%

Note. “Meat reducer” refers to self-identified pescatarians and participants who reported intentionally limiting their meat consumption; “meat avoider” refers to vegetarians and vegans. N = 557.

Table 2. Internal Consistency Reliability and Convergent Validity Evaluation of Study Constructs.

	Meat Consumption Model			RPMC Model			WRMC Model
Variable	α	CR	AVE	α	CR	AVE	α	CR	AVE
Meat consumption	0.51	0.75	0.50	—	—	—	—	—	—
Red & processed meat consumption	—	—	—	0.30	0.73	0.58	—	—	—
Willingness to reduce meat consumption	—	—	—	—	—	—	0.86	0.92	0.79
Social dominance orientation	0.82	0.88	0.65	0.82	0.88	0.65	0.82	0.88	0.65
Authenticity (NTM)	0.71	0.87	0.77	0.79	0.87	0.68	0.79	0.87	0.69
Domesticity/nurturing (NTM)	0.60	0.78	0.55	0.60	0.79	0.55	0.60	0.79	0.56
Holistic attentiveness (NTM)	0.65	0.78	0.55	0.65	0.78	0.55	0.73	0.82	0.54
QDOM (NTM)	0.75	0.86	0.67	0.75	0.86	0.67	0.75	0.86	0.67
Sensitivity to male privilege (NTM)	0.36	0.76	0.61	0.36	0.76	0.61	0.36	0.76	0.61
Emotional control (TM)	0.91	0.94	0.83	0.91	0.94	0.84	0.91	0.94	0.85
Heterosexual presentation (TM)	0.93	0.96	0.88	0.93	0.96	0.88	0.93	0.96	0.88
Importance of sex (TM)	0.83	0.90	0.75	0.83	0.90	0.75	0.83	0.90	0.75
Playboy (TM)	0.82	0.90	0.74	0.72	0.86	0.75	—	—	—
Power over women (TM)	0.78	0.87	0.70	0.78	0.87	0.70	0.78	0.87	0.69
Primacy of work (TM)	0.88	0.92	0.80	0.88	0.92	0.80	0.88	0.92	0.79
Pursuit of status (TM)	0.68	0.81	0.59	0.68	0.81	0.59	0.68	0.80	0.57
Risk-taking (TM)	0.89	0.93	0.81	0.89	0.93	0.81	0.89	0.92	0.79
Self-reliance (TM)	0.76	0.88	0.79	0.76	0.89	0.81	0.76	0.84	0.73
Toughness (TM)	0.74	0.85	0.66	0.74	0.85	0.66	0.74	0.85	0.66
Violence (TM)	0.75	0.85	0.65	0.75	0.84	0.64	0.75	0.85	0.65
Winning (TM)	0.70	0.83	0.62	0.69	0.85	0.74	0.70	0.83	0.63

Note. α = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted. α and CR should be ≥ .60 to demonstrate reliability; AVE should be ≥ .50 to demonstrate convergent validity (Hair et al. 2021). The playboy norm was not used in the willingness to reduce meat consumption model due to poor indicator reliability. RPMC = red and processed meat consumption; WRMC = willingness to reduce meat consumption; QDOM = questioning definitions of masculinity; NTM = non-traditional masculine norm; TM = traditional masculine norm.

Figure 1. PLS-SEM model predicting meat consumption, including both the measurement (outer) and structural (inner) models. Note. ***= p≤.001, **=p≤.01, *p≤.05. Significant predictors are displayed with shading and bold.

Figure 2. PLS-SEM model predicting red and processed meat consumption, including both the measurement (outer) and structural (inner) models. Note. ***= p≤.001, **=p≤.01, *p < .05. Significant predictors are displayed with shading and bold.

Figure 3. PLS-SEM model predicting willingness to reduce meat consumption, including both the measurement (outer) and structural (inner) models. Note. ***= p≤.001, **=p≤.01, *p≤.05. Significant predictors are displayed with shading and bold.

Table 3. Predictive Power of PLS-SEM Models.

Model	Model Indicators	Q^2	PLS-SEM RMSE	LM-RMSE
Meat Consumption	MC1 (beef/lamb)	0.055	14.43	15.00
	MC2 (poultry)	0.070	14.88	15.57
	MC3 (pork/bacon/ham)	0.012	11.87	12.43
Red & Processed Meat Consumption	RPMC1 (beef/lamb)	0.048	14.48	15.01
	RPMC2 (pork/bacon/ham)	0.009	11.88	12.39
Willingness to Reduce Meat Consumption	WRMC1	0.100	1.19	1.23
	WRMC2	0.081	1.22	1.27
	WRMC3	0.063	1.25	1.30

Note. To demonstrate predictive power, Q² should be > 0, and the PLS-SEM RMSE values must be lower than the LM-RMSE values. PLS-SEM<LM for no indicators = no predictive power; PLS-SEM<LM for a minority of indicators = low predictive power; PLS-SEM<LM for a majority of indicators = medium predictive power; PLS-SEM<LM for all indicators = high predictive power (Shmueli et al. 2019).

Hair, J. F., G. T. M. Hult, C. M. Ringle, M. Sarstedt, N. P. Danks, and S. Ray. 2021. Partial least squares structural equation modeling (PLS-SEM) Using R. Springer. doi:10.1007/978-3-030-80519-7.

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