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Characterising meat consumption in Switzerland across socio-demographic, lifestyle and anthropometric groups.
Representative national data from the menuCH survey (two 24-hour dietary recalls, anthropometric measurements and a lifestyle questionnaire) were used to analyse the total average daily intake of meat and main meat categories. Energy-standardised average intake (g/1000 kcal) was calculated and its association with 12 socio-demographic, lifestyle and anthropometric variables was investigated using multivariable linear regression.
Totally, 2057 participants aged 18–75 years.
Average total meat intake was 109 g/d, which included 43 g/d of processed meat, 37 g/d of red meat and 27 g/d of white meat. Energy-standardised meat intake was highest for men, the Italian-language region and the youngest age group (18–29 years). Regression results showed significantly lower total meat and red meat consumption (g/1000 kcal) for women than men. However, there were no sex-specific differences for white meat. Total meat and white meat consumption were positively associated with the 18–29 age group, compared with 30–44 years, non-Swiss compared with Swiss participants and one-parent families with children compared with couples without children. Consumption of all categories of meat showed positive associations for BMI > 25 kg/m2 compared with BMI 18·5–25 kg/m2 and for French- and Italian-language regions compared with German-language region.
The current study reveals that there are significant differences in the amounts and types of meat consumed in Switzerland, suggesting that evidence-based risks and benefits of these categories need to be emphasised more in meat consumption recommendations.
To describe and analyse the sociodemographic, anthropometric, behavioural and dietary characteristics of different types of Swiss (no-)meat eaters.
No-, low-, medium- and high-meat eaters were compared with respect to energy and total protein intake and sociodemographic, anthropometric and behavioural characteristics.
National Nutrition Survey menuCH, the first representative survey in Switzerland.
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.
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.
This study identified important differences in sociodemographic, anthropometric, behavioural and dietary factors between menuCH participants with different meat-eating habits.
Processed meat (PM) has an important role in diet of the Swiss population, but increasingly regarded as a food group of concern due to epidemiological evidence for its association with colorectal cancer (CRC) and other chronic diseases. Data on CRC incidence for men and women and by region is available in Switzerland, but cannot be linked with PM intake.
This secondary analysis aimed to describe PM consumption in Switzerland, using data from the National Nutritional Survey menuCH, to investigate associations between PM intake and sociodemographic and lifestyle factors, and to examine CRC incidence in Switzerland for any similar regional patterns to PM consumption.
Intakes of total PM and of categories ham, bacon, sausage and other PM types were described by means and standard errors (SEM). Multiple regression analysis was used to investigate associations between meat intake (total meat and PM, assessed separately, g/1000 kcal) and the following sociodemographic and lifestyle factors: sex, language-speaking region, age-category, nationality, education, gross household income, household status, smoking status, overall health status (self-reported), and currently following a weight-loss diet. Data were weighted for age, sex, marital status, major areas of Switzerland, nationality and household size, and for consumption data, also season and weekday.
Results show PM was consumed by approximately 70% of the population with mean total intake of 42.7 (SEM 1.2 g/d). Sausage intake was highest with 16.8 g/day, followed by ham, other PM and bacon, 12.4, 10.6, and 2.0 g/day, respectively. Sex was significantly associated with total meat and PM intake; women consumed 10.1 g/1000 kcal less total meat [95% CI: -13.60; -6.64], and 4.70 g /1000 kcal less PM [95% CI: -6.73; -2.68] than men. For both variables, total meat and PM intake, positive associations were observed for overweight, obesity and current smoking; and negative associations observed for tertiary education and following a diet. The later was significant only for PM intake. The ecological data for CRC incidence revealed much higher rates for men than women, over 24 years; but the data shown by language region did not reveal any particular pattern.
This study is the first to describe intakes of total and different PM types, based on national representative data. Positive associations between PM intake and smoking and obesity merit careful monitoring. More regular data collection by methods enabling separate quantification of meat and PM, as well as relevant health biomarkers are needed in future studies.
Today'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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