The nutritional quality of foods carrying health-related claims in Germany, The Netherlands, Spain, Slovenia and the United Kingdom

Backgroung/Objectives:

Compares the nutritional quality of pre-packaged foods carrying health-related claims with foods that do not carry health-related claims.

Subject/Methods:

Cross-sectional survey of pre-packaged foods available in Germany, The Netherlands, Spain, Slovenia and the United Kingdom in 2013. A total of 2034 foods were randomly sampled from three food store types (a supermarket, a neighbourhood store and a discounter). Nutritional information was taken from nutrient declarations present on food labels and assessed through a comparison of mean levels, regression analyses and the application of a nutrient profile model currently used to regulate health claims in Australia and New Zealand (Food Standards Australia New Zealand's Nutrient Profiling Scoring Criterion, FSANZ NPSC).

Results:

Foods carrying health claims had, on average, lower levels, per 100 g, of the following nutrients, energy—29.3 kcal (P<0.05), protein—1.2 g (P<0.01), total sugars—3.1 g (P<0.05), saturated fat—2.4 g (P<0.001), and sodium—842 mg (P<0.001), and higher levels of fibre—0.8 g (P<0.001). A similar pattern was observed for foods carrying nutrition claims. Forty-three percent (confidence interval (CI) 41%, 45%) of foods passed the FSANZ NPSC, with foods carrying health claims more likely to pass (70%, CI 64%, 76%) than foods carrying nutrition claims (61%, CI 57%, 66%) or foods that did not carry either type of claim (36%, CI 34%, 38%).

Conclusions:

Foods carrying health-related claims have marginally better nutrition profiles than those that do not carry claims; these differences would be increased if the FSANZ NPSC was used to regulate health-related claims. It is unclear whether these relatively small differences have significant impacts on health.

Nutritional risk of European elderly

BACKGROUND/OBJECTIVES

The elderly constitute a population group with a high prevalence of non-communicable chronic diseases and high risk of malnutrition. The aim of this study was to identify factors associated to nutritional risk in free-living European elderly.

SUBJECTS/METHODS

The sample included 644 European citizens, free living in the community, aged 65 years or more. The sample was quota controlled for age groups (65-74, ≥75 years), gender (male/female) and living circumstances (living alone/with others). Logistic regression was performed to identify factors associated with nutritional risk.

RESULTS

Several variables regarding socio-demographic characteristics, food choice, health status and the satisfaction with food-related life were included in the analysis. According to the recoded score of the 'Determine your nutritional health' (NSI checklist), 53% of the elderly were at nutritional risk. Nutritional risk was more likely to occur in elderly who considered that it was more important to choose foods 'easy to chew'; with lower average number of fruit and vegetables (F&V) intake episodes and lower score for general health. It was also found in non-married participants; those that did not identify changes in their appetite; and those that felt changes in health status. In this sample, the lowest nutritional risk was found for body mass index (BMI) around 18.5 kg/m(2). Country of residence, gender and age were not found to have a significant effect on nutritional risk.

CONCLUSIONS

Attention should be drawn to the living circumstances, changes in appetite or health, the general heath perception, F&V intake, choice of foods easy to chew and having a low or high BMI.

Problems in identifying predictors and correlates of weight loss and maintenance: implications for weight control therapies based on behaviour change

Weight management is a dynamic process, with a pre-treatment phase, a treatment (including process) phase and post-treatment maintenance, and where relapse is possible during both the treatment and maintenance. Variability in the statistical power of the studies concerned, heterogeneity in the definitions, the complexity of obesity and treatment success, the constructs and measures used to predict weight loss and maintenance, and an appreciation of who and how many people achieve it, make prediction difficult. In models of weight loss or maintenance: (i) predictors explain up to 20-30% of the variance; (ii) many predictors are the sum of several small constituent variables, each accounting for a smaller proportion of the variance; (iii) correlational or predictive relationships differ across study populations; (iv) inter-individual variability in predictors and correlates of outcomes is high and (v) most of the variance remains unexplained. Greater standardization of predictive constructs and outcome measures, in more clearly defined study populations, tracked longitudinally, is needed to better predict who sustains weight loss. Treatments need to develop a more individualized approach that is sensitive to patients' needs and individual differences, which requires measuring and predicting patterns of intra-individual behaviour variations associated weight loss and its maintenance. This information will help people shape behaviour change solutions to their own lifestyle needs.

Compilation of food composition data sets: an analysis of user needs through the Use Case approach

BACKGROUND/OBJECTIVES

The objective of this study was to identify the common requirements of users involved in the compilation of food composition data sets with a view to informing the development of a common access system to food composition data, within the European Food Information Resource (EuroFIR) project.

SUBJECTS/METHODS

A number of examples of food composition data set compilation have been examined using the Use Case approach, namely the compilation of a data set for a national nutrition survey, for a cross-national nutrition study and for a nutritional software programme.

RESULTS

The key user requirement identified from the compilation step analysed by the Use Case approach is the increased availability of and access to more detailed food composition data on a wider range of foods and nutrients.

CONCLUSIONS

Food composition data serve a variety of purposes, and different user groups will often have both common needs and more individual or specific needs of their data sets. The development of Use Cases for specific processes effectively identifies the needs of users, highlighting any similarities and/or differences in those needs. The application of the Use Case approach to support the software development activities within EuroFIR will ensure that user needs are effectively identified and captured in a systematic and documented way.

Patterns of healthy lifestyle and positive health attitudes in older Europeans

OBJECTIVES

To determine (i) the extent to which recommended lifestyle healthy behaviors are adopted and the existence of positive attitudes to health; (ii) the relative influence of socio-demographic variables on multiple healthy lifestyle behaviors and positive attitudes to health; (iii) the association between healthy lifestyle behaviors and positive attitudes to health.

DESIGN

Two distinct healthy behavioral measures were developed: (i) healthy lifestyles based on physical activity, no cigarette smoking, no/moderate alcohol drinking, maintaining a "healthy" weight and having no sleeping problems and (ii) positive health attitudes based on having positive emotional attitudes, such as: self-perceived good health status, being calm, peaceful and happy for most of the time, not expecting health to get worse and regular health check-ups. A composite healthy lifestyle index, ranging from 0 (none of behaviors met) to 5 (all behaviors met) was calculated by summing up the individual's scores for the five healthy lifestyle items. Afterwards, each individual's index was collapsed into three levels: 0-2 equivalent to 'level 1' (subjectively regarded as 'too low'), a score of 3 equivalent to 'level 2' ('fair') and 4-5 as 'level 3' satisfactory 'healthy lifestyle' practices. The same procedure was applied to the positive health attitudes index. Multinomial logistic regression analyses by a forward selection procedure were used to calculate the adjusted odds ratio (OR) with 95% confidence interval (95% CI).

PARTICIPANTS

A multi-national sample consisting of 638 older Europeans from 8 countries, aged 65-74 and 75+, living alone or with others.

RESULTS AND CONCLUSIONS

Maintaining a "healthy" weight was the most frequently cited factor in the healthy lifestyles index and therefore assumed to be the most important to the older Europeans in the study; positive attitudes to health were relatively low; participants achieved a 'satisfactory' level for healthy lifestyles index (level 3) more frequently than a satisfactory level for positive attitudes to health; having a satisfactory 'healthy lifestyle' was directly related to having a satisfactory level of positive attitudes to health based on the positive health attitudes index; income and geographical location in Europe appeared to be key predictors for meeting both the recommended healthy lifestyle factors in the index and having positive health attitudes however, the composition and nature of the study sample should be taken into consideration when considering the impact of the location on healthy lifestyles and attitudes to health across Europe.