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Population monitoring of lifestyle behaviours that are crucial as risk and protective factors for major chronic diseases is vital for the identification of priority areas for public health. In this study, we aimed to investigate the prevalence of adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations in Switzerland, overall and by selected sociodemographic and lifestyle characteristics. Data from the population-based, cross-sectional survey menuCH were used. We constructed a score reflecting adherence to the 2018 WCRF/AICR cancer prevention recommendations. Multinomial logistic regression models were fitted to investigate the association of sociodemographic and lifestyle characteristics with the level of adherence to the WCRF/AICR cancer prevention recommendations. The least frequently met cancer prevention recommendations were the ones on fibre intake (met by 13·7 %), red and processed meat (25·4 %), and ultra-processed food (33·3 %) consumption, while the recommendation on physical activity was met by almost 80 %. Women and individuals with tertiary education were more likely to have a score of ≥ 5 (as a reflection of adherence to the cancer prevention recommendations), compared with men or those who completed secondary education, respectively. Current smokers were less likely to have a score of ≥ 5, compared with never smokers. A high proportion of the population in Switzerland was found to not adhere closely to the WCRF/AICR cancer prevention recommendations. Differences were detected based on sociodemographic characteristics. Education and policy actions are needed to facilitate the adoption of a cancer-protective lifestyle.
Different methods of dietary intake assessment are frequently used to assess a population’s diet. In this study, we aimed to compare the adherence to Swiss food-based dietary guidelines as depicted in two Swiss population-based surveys using different methods of dietary assessment.
Two population-based, cross-sectional surveys were compared. In the Swiss Health Survey (SHS), diet was assessed via a short set of questions on specific food groups, while in menuCH by two non-consecutive 24-h dietary recall interviews.
To compare the diet depicted in these surveys, we used the Swiss food-based dietary guidelines on vegetable, fruit, dairy product, meat and meat product, fish and alcohol. The weighted proportion of responders meeting these guidelines was calculated for both surveys and was compared overall and by selected characteristics.
Residents of Switzerland, selected from a stratified random sample of the non-institutionalised residents, who agreed to participate in the respective survey. To ensure comparability between the surveys, the age of the study populations was restricted to 18–75 years.
In menuCH, approximately 2 % of responders met ≥4 of the selected Swiss food-based dietary guidelines. In the SHS, using a cruder dietary assessment, the corresponding percentage was 20 %. In both surveys, more women and never smokers were meeting ≥4 food-based dietary guidelines compared to men and current or former smokers, respectively.
Our study comparing the diet in two population-based, representative surveys detected large variations in guideline adherence depending on the dietary assessment method used.
We investigated the associations between dietary patterns and chronic disease mortality in Switzerland using an ecological design and explored their spatial dependence, i.e. the tendency of near locations to present more similar and distant locations to present more different values than randomly expected. Data of the National Nutrition Survey menuCH (n 2057) were used to compute hypothesis- (Alternate Healthy Eating Index (AHEI)) and data-driven dietary patterns. District-level standardised mortality ratios (SMR) were calculated using the Swiss Federal Statistical Office mortality data and linked to dietary data geographically. Quasipoisson regression models were fitted to investigate the associations between dietary patterns and chronic disease mortality; Moran’s I statistics were used to explore spatial dependence. Compared with the first, the fifth AHEI quintile (highest diet quality) was associated with district-level SMR of 0·95 (95 % CI 0·93, 0·97) for CVD, 0·91 (95 % CI 0·88, 0·95) for ischaemic heart disease (IHD), 0·97 (95 % CI 0·95, 0·99) for stroke, 0·99 (95 % CI 0·98, 1·00) for all-cancer, 0·98 (95 % CI 0·96, 0·99) for colorectal cancer and 0·93 (95 % CI 0·89, 0·96) for diabetes. The Swiss traditional and Western-like patterns were associated with significantly higher district-level SMR for CVD, IHD, stroke and diabetes (ranging from 1·02 to 1·08) compared with the Prudent pattern. Significant global and local spatial dependence was identified, with similar results across hypothesis- and data-driven dietary patterns. Our study suggests that dietary patterns partly contribute to the explanation of geographic disparities in chronic disease mortality in Switzerland. Further analyses including spatial components in regression models would allow identifying regions where nutritional interventions are particularly needed.
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.
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