Objective: To describe and analyse the sociodemographic, anthropometric, behavioural and dietary characteristics of different types of Swiss (no-)meat eaters. Design: No-, low-, medium- and high-meat eaters were compared with respect to energy and total protein intake and sociodemographic, anthropometric and behavioural characteristics. Setting: National Nutrition Survey menuCH, the first representative survey in Switzerland. Participants: 2057 participants, aged 18–75 years old, who completed two 24-h dietary recalls (24-HDR) and a questionnaire on dietary habits, sociodemographic and lifestyle factors. Body weight and height were measured by trained interviewers. No-meat eaters were participants who reported meat avoidance in the questionnaire and did not report any meat consumption in the 24-HDR. Remaining study participants were assigned to the group of low-, medium- or high-meat eaters based on energy contributions of total meat intake to total energy intake (meat:energy ratio). Fifteen percentage of the participants were assigned to the low- and high-meat eating groups, and the remaining to the medium-meat eating group. Results: Overall, 4·4 % of the study participants did not consume meat. Compared with medium-meat eaters, no-meat eaters were more likely to be single and users of dietary supplements. Women and high-educated individuals were less likely to be high-meat eaters, whereas overweight and obese individuals were more likely to be high-meat eaters. Total energy intake was similar between the four different meat consumption groups, but no-meat eaters had lowest total protein intake. Conclusions: This study identified important differences in sociodemographic, anthropometric, behavioural and dietary factors between menuCH participants with different meat-eating habits.

AbstractToday's high interest for no- or low-meat diets is driven by evidence-based associations between high meat consumption and unhealthy lifestyle factors as well as increased risk of various chronic diseases. This study aims to characterize no-, low- and high-meat consumers and describe their protein intake using data from the Swiss nutrition survey menuCH.This first national survey assessed descriptive factors by a questionnaire and dietary intake by 24-hour dietary recall (24 HDR) across all three linguistic regions, German, French and Italian of Switzerland (N = 2057). Data from the questionnaire (food avoidance) and two 24 HDRs were used to categorize total participants (N) into four subgroups: no meat (4.4%); low (15%), medium (65.6%), or high-meat eaters (15%), based on meat-energy contributions of 0; 0–2.4; 2.4–18.7; 18.7–48.4, respectively. Contributions of overall macronutrients and protein from the different food groups were described for each subgroup to identify quantitative and qualitative differences. Multinomial logistic regression analysis was applied to predict the probability of belonging to one of the four subgroups according to the following sociodemographic and behavioral variables: sex, language region, age, nationality, marital status, education, gross household income, BMI, physical activity, smoking, dietary supplements and overall health status. The subgroups differed in protein intake with 11.5%, 12.8%, 15.4% and 19.1% of total energy intake for no-, low-,medium- and high-meat diets, respectively, weighted for sampling design, non-response, weekdays and season. In general, no- and low-meat consumers included a greater variety of foods contributing to protein intake than meat consumers, including more dairy products and meat-alternatives. None of the subgroups met the Swiss Food-based Dietary Guidelines of three portions of dairy products per day. The regression analysis showed that sex, taking dietary supplements or not and BMI were important determinants of the subgroups: women had a higher predicted probability than men to be no- and low-meat eaters and for these same subgroups, individuals showed higher probabilities for taking dietary supplements. Overweight and obese participants showed higher probabilities to be high-meat eaters.These findings show considerable differences in protein intake and in variety of protein-food selections, between extremes of meat intake (no- to high meat consumption). Future surveys should include frequency methods to allow conclusions about habitual meat intake or avoidance and health status screening to analyse individuals health data.

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