From a public health perspective, determinants of diets are crucial to identify, but they remain unclear in Switzerland. Hence, we sought to define current dietary patterns and their sociodemographic and lifestyle determinants using the national nutrition survey menuCH (2014–2015, n = 2057). First, we applied multiple factorial analysis and hierarchical clustering on the energy-standardised daily consumption of 17 food categories. Four dietary patterns were identified (“Swiss traditional”: high intakes of dairy products and chocolate, n = 744; “Western 1”: soft drinks and meat, n = 383; “Western 2”: alcohol, meat and starchy, n = 444; and “Prudent”: n = 486). Second, we used multinomial logistic regression to examine the determinants of the four dietary patterns: ten sociodemographic or lifestyle factors (sex, age, body mass index, language region, nationality, marital status, income, physical activity, smoking status, and being on a weight-loss diet) were significantly associated with the dietary patterns. Notably, belonging to the French- and Italian-speaking regions of Switzerland increased the odds of following a “Prudent” diet (Odds ratio [95% confidence interval]: 1.92 [1.45–2.53] and 1.68 [0.98–2.90], respectively) compared to the German-speaking regions. Our findings highlight the influence of sociodemographic and lifestyle parameters on diet and the particularities of the language regions of Switzerland. These results provide the basis for public health interventions targeted for population subgroups.

Sociodemographic differences in dietary consumption were observed in different populations. The current study aimed to identify sociodemographic and lifestyle determinants of diet quality and to investigate the differences in diet quality between the three main language regions of Switzerland. Using data of the Swiss National Nutrition Survey menuCH (n = 2057), two diet quality scores—Alternate Healthy Eating Index and Mediterranean Diet Score—were computed. Linear regression models were used to investigate the determinants of diet quality and chi-square tests were used to test for differences in single score components between language regions. Significantly higher diet quality scores were observed for individuals who were female, older, normal weight, non-Swiss, with tertiary education or moderate-to-high physical activity level. Additionally, residents of the French- and Italian-speaking parts of Switzerland scored higher than residents of the German-speaking region. More specifically, the higher diet quality observed in the French- and Italian-speaking regions was mediated by higher scores in the components of alcohol, dairy products, fat, fish, sugar-sweetened beverages and whole grains. The present results may help to better characterize population groups requiring specific dietary recommendations, enabling public health authorities to develop targeted interventions.

Since high-sweet beverage intake is associated with health risks, defining what this term encompasses is relevant to the strategies confronting this problem. This study assessed both the sociodemographic factors associated with sweet beverage consumption in Switzerland and the amount consumed. According to the current definition in Switzerland (SB–CUR), sweet beverages include soft drinks, juices with added-sugar, and low-calorie sweet beverages. Using this definition and the representative menuCH survey (n = 2057; ages 18–75), the average daily sweet beverage intake was determined and compared with a new sweet beverage definition (SB–NEW), which included all beverages with free sugars and low-calorie sweeteners. A generalized linear model was used to investigate correlates of sweet beverage consumption. Sweet beverage consumption under the SB–CUR and SB–NEW definition was 240.6 g/day and 329.7 g/day, respectively, with 100% juice consumption accounting for 66% of the difference. Carbonated drinks (sodas), low-calorie sweet beverages, and 100% juices were the highest contributors, each around 60 g/day. SB–NEW intake was higher in individuals who were male, young adults (aged 18–29), from German-speaking regions, obese, or had a lower level of education. As sweet beverage consumption was much higher under the SB–NEW definition, this could have implications for health policies aimed at reducing sugar intake.

The aim of the study was to investigate the associations between dietary patterns and chronic disease mortality in Switzerland using an ecologic design and to explore the spatial dependence of these associations, i.e. the tendency of near locations to present more similar values than randomly expected and distant locations to present more different values. Data of the cross-sectional National Nutrition Survey menuCH (n = 2,057) 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 were linked to dietary data by the participants’ place of residence. Quasipoisson regression models were fitted to investigate the associations between dietary patterns and chronic disease mortality; Moran’s I statistics were used to explore the spatial dependence. Compared to the first, the fifth AHEI quintile (representing the highest diet quality) was associated with district-level SMR (95% confidence interval) of 0.95 (0.93-0.97) for cardiovascular disease, 0.91 (0.88-0.95) for ischemic heart disease, 0.97 (0.95-0.99) for stroke, 0.99 (0.98-1.00) for all-cancer, 0.98 (0.96-0.99) for colorectal cancer, and 0.93 (0.89-0.96) for diabetes. Additionally, the Swiss traditional and Western-like patterns were associated with significantly higher district-level SMR for cardiovascular disease, ischemic heart disease, stroke, and diabetes (ranging from 1.02 to 1.08) compared to the Prudent pattern. Finally, significant global and local spatial dependence was identified, with very similar results observed across hypothesis- and data-driven dietary patterns. To conclude, significant associations were observed between dietary patterns and mortality from various chronic diseases, and chronic disease mortality clustered locally, with high similarities between hypothesis- and data-driven dietary patterns. Further analyses including spatial components in regression models would allow to better understand local factors influencing diet-disease associations and to identify regions where nutritional interventions are needed the most.

Processed meat (PM) intake is associated with health risks, but data are lacking in Switzerland. Using national representative data from a recent menuCH Survey, we first aimed to quantify intake of PM and its subtypes, and second to investigate associations with sociodemographic and lifestyle factors by multivariable regression analysis. PM was consumed by 72% of the population, and mean daily intake was 42.7 g/day (standard error of the mean (SEM) 1.2 g/day), ranging considerably across PM subtypes: highest intake of sausages 18.1 g/day (SEM 0.7 g/day) and lowest of bacon 2.0 g/day (SEM 0.2 g/day). PM intake by women was 4.7 g/1000 kcal lower than men (95% confidence interval (CI): −6.7; −2.7) and 2.9 g/1000 kcal lower in the French- language region compared with the German region (95% CI: 2.4; 8.7). Among sociodemographic and lifestyle factors examined, BMI (obese vs. normal: 5.5 g/1000 kcal, 95% CI: 2.4; 8.7) and current smoking (vs. never smoked: 3.1 g/kcal, 95% CI: 0.6; 5.6) were independently associated with PM intake. The results are a first description of PM intake, separate from other meat types, and which identified associations with two unhealthy lifestyle factors in Switzerland. Such data will contribute to better nutritional recommendations and guidance for public health interventions.