Table 2 Published manuscripts from DEDIPAC Thematic Area 2

 Symmank et al. [28]

Determinants

Food decision making

Across the life course

Systematic Inter-disciplinary Mapping (SIM) review

International

“After applying qualitative and quantitative analyses, this study reveals that most of the research [on food decision making] emphasizes biological, psychological, and product related predictors, whereas policy-related influences on food choice are scarcely considered”

 Condello et al. [29]

Behavioural determinants

Physical activity

Across the life course

Umbrella SLR

International

“Although the majority of the evidence was limited and most of the determinants were not associated with PA, this umbrella SLR provided a comprehensive overview of the associations between behavioural determinants and PA. Youth should be physically active in the early years and increase active transport to/from school, independent mobility, and ‘free-range activities’ without adult supervision, whilst adult PA behaviours are mostly influenced by the life events. Finally, more research is needed that incorporates prospective study designs, standardized definitions of PA, objective measurement methods of PA assessment, and the use of interactionist and mediational approached for the evaluation of different behavioural determinants influencing PA behaviours.”

 Cortis et al. [31]

Psychological determinants

Physical activity

Across the life course

Umbrella SLR

International

“This umbrella SLR provided a comprehensive overview of the associations between psychological determinants and PA. Most of the evidence resulted probable and limited, mainly due to differences in the definition of PA and of psychological determinants across reviews. Convincing evidence was found for a positive association between self-efficacy and PA in children and adolescents, and a negative association between stress and PA regardless of age. At present, there is a need of a consensus on clear definitions of relevant psychological determinants of PA to allow clear interpretations and generalizability of findings. Furthermore, it is envisaged that psychological determinants should be considered within a larger and multi-level framework of determinants to determine possible interactions or mediations of the effects.”

 Puggina et al. [32]

Policy determinants

Physical activity

Across the life course

Umbrella SLR

International

“This umbrella systematic literature review summarizes the current evidence on the policy determinants of PA across the life course at individual and population levels. The majority of the reviews resulted of moderate quality. Furthermore, none of the investigated policy determinants had a convincing level of evidence, and very few had a probable level of evidence. At individual level, a clear association between time spent outdoors and PA emerged for children, whereas a limited evidence was found for working hours negatively associated with PA in adults. At the population level, community- and street-scale urban design and land use policies were found to positively support PA levels, although levels of evidence were low. Therefore, further research is needed, preferably by using prospective study designs, standardized definitions of PA and objective measurement of PA.”

 Carlin et al. [30]

Physical environment determinants

Physical activity

Across the life course

Umbrella SLR

International

“This umbrella systematic literature review provided a comprehensive overview of the physical determinants of PA across the life course. The limited evidence available from longitudinal studies, coupled with the diverse methodologies and definitions of both PA outcomes and physical determinants/factors employed across studies, makes it difficult to draw firm conclusions. It is vital that researchers make a concerted effort to employ harmonised, objective methodologies in the future measurement of PA and its determinants.”

 Stierlin et al. [33]

Determinants

Sedentary behaviour

Youth (<18y)

SLR

International

“Multiple potential determinants were studied in only one or two studies. Determinants were found at the individual, interpersonal, environmental and policy level but few studies examined acomprehensive set of factors at different levels of influences. Evidence was found for age being positively associated with total sedentary behaviour, and weight status and baseline assessment of screen time being positively associated with screen time (at follow-up). A higher playground density and a higher availability of play and sports equipment at school were consistently related to an increased total sedentary behaviour, although these consistent findings come from single studies. Evidence was also reported for the presence of safe places to cross roads and lengthening morning and lunch breaks being associated with less total sedentary behaviour.”

 O’Donoghue et al. [34]

Determinants

Sedentary behaviour

Adults (18–65y)

SLR

International

“Results provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains.”

 Chastin et al. [35]

Determinants

Sedentary behaviour

Older adults (>65y)

SLR

International

“Few studies have investigated determinants of sedentary behaviour in older adults and these have to date mostly focused on personal factors, and qualitative studies were mostly lacking. More longitudinal studies are needed as well as inclusion of a broader range of personal and contextual potential determinants towards a systems-based approach, and future studies should be more informed by qualitative work.”

 Osei-Kwasi et al. [36]

Determinants

Dietary behaviour

Across the life course; minority groups

SLR

Cross-European

“This review identified a broad range of factors and clusters influencing dietary behaviour among ethnic minority groups. Gaps in the literature identified a need for researcher to explore the underlying mechanisms that shape dietary behaviours, which can be gleaned from more holistic, systems-based studies exploring relationships between factors and clusters. The dominance of studies exploring ‘differences’ between ethnic minority groups and the majority population in terms of the socio-cultural environment and food beliefs suggests a need for research exploring ‘similarities’. The evidence from this review will feed into developing a framework for the study of factors influencing dietary behaviours in ethnic minority groups in Europe.”

 Langøien et al. [37]

Determinants

Physical activity and sedentary behaviour

Across the life course; ethnic minority groups

SLR

Cross-European

“Physical activity and sedentary behaviour among ethnic minority groups living in Europe are influenced by a wide variety of factors, especially informed by qualitative studies. More comparative studies are needed as well as inclusion of a larger number of ethnic minority group resettled in different European countries. Few studies have investigated factors influencing sedentary behaviour. It is important in the future to address specific factors influencing physical activity and sedentary behaviour among ethnic minority groups in order to plan and implement effective interventions.”

 Stok et al. [38]

Determinants Of Nutrition and Eating (DONE) framework

Dietary behaviour

Across the life course

Multi-phase, multi-method process

International

“In the creation phase, mind mapping, knowledge mapping, and several discussion and consensus rounds were employed to generate a comprehensive, systematically structured set of determinants of nutrition and eating across the lifespan. In the evaluation phase, priorities for research were determined by rating the determinants on the dimensions of modifiability, relationship strength, and population-level effect. Furthermore, the framework’s quality, usefulness, and comprehensiveness were empirically evaluated by external experts from different disciplines and countries. In the updating phase, a pilot confirmed the feasibility of the continued evolution of the framework by requesting additional input from external experts. Moreover,

the framework was dynamically visualized and made freely available on the Internet.”

 Condello et al. [39]

European-Physical Activity Determinants (EU-PAD) framework

Physical activity

Across the life course

Concept mapping

Cross-European

“The current framework provides a preliminary overview of factors which may account for physical activity behaviour across the life course and are most relevant to the European community. These insights could potentially be a foundation for future pan-European research on how these factors might interact with each other, and assist policy makers to identify appropriate interventions to maximise physical activity behaviours and thus the health of European citizens.”

 Chastin et al. [40]

Systems Of Sedentary behaviour (SOS) framework

Sedentary behaviour

Across the life course

Concept mapping

International

“Through an international transdisciplinary consensus process, the SOS framework was developed for the determinants of sedentary behaviour across the life course. Investigating the influence of Institutional and Home Settings was deemed to be the most important area of research to focus on at present and potentially the most modifiable. The SOS framework can be used as an important tool to prioritise future research and to develop policies to reduce sedentary time.”

 Stelmach-Mardas et al. [45]

Seasonality

Food and energy intake

Adults (≥18y)

SLR

International

“The winter or the post-harvest season is associated with increased energy intake. The intake of fruits, vegetables, eggs, meat, cereals and alcoholic beverages is following a seasonal consumption pattern and at least for these foods season is a determinant of intake.”

 Schoen et al. [46]

Notified risk of type 1 diabetes

Dietary quality

Youth (<18y)

Secondary, pooled, CS

Germany

“Nutrient and food intake quality were lower at nine months of age and food intake quality was lower at 24 months of age in at-risk [for type 1 diabetes] than in not-at-risk children (p = 0.01 and p < 0.0001, respectively). The amount of added sugar was higher in at-risk children at both ages (p < 0.0001). In at-risk children, dietary quality was similar between children who were first exposed to gluten at six or 12 months of age. Despite being notified about their child’s risk of T1D, the child’s mother did not switch to healthier diets compared with not-at-risk mothers.”

 Wittig et al. [47]

Sex, age, BMI, SES and diet quality

Energy and macronutrient intake

Adults (≥18y)

Secondary, 7CS

Germany

“The presented analyses provide comprehensive descriptions of meal patterns in regard to the distribution of energy intake over the course of the day of selected population groups in Germany. With few differences within the population groups defined by sex, age, BMI, SES, and HEI-NVS-II, the traditional three-main-meal pattern was observed, a result which is also found in other studies. For old adults, meals have an important role for structuring the day as seen in distinct peaks at the three-main-meal periods. In contrast, young adults seem to have a higher variability in energy intake and a less distinct meal pattern. Further, the results show that the highest energy intake was observed in the ‘evening’ period, especially in young adults, overweight persons, and persons with a high SES, as well as men with a low dietary quality (expressed by HEI-NVS-II). Because a high energy intake in the ‘evening’ period is associated with health-related factors, such as obesity, higher hypertension prevalence, and a higher blood pressure, in the literature, the distribution of energy intake over the course of the day should be considered by recommendations for the promotion of a healthy nutritional behaviour.”

 Si Hassen et al. [48]

Socioeconomic indicators

Nutrient intake

Adults (≥18y)

Secondary, CS

France

“Low educated participants had higher protein and cholesterol intakes and lower fibre, vitamin C and beta-carotene intakes. Low income individuals had higher complex carbohydrate intakes, and lower magnesium, potassium, folate and vitamin C intakes. Intakes of vitamin D and alcohol were lower in low occupation individuals. Higher income was associated with higher intakes of fibre, protein, magnesium, potassium, beta-carotene, and folate among low educated persons only, highlighting effect modification. Lower SEP, particularly low education, was associated with lower intakes of nutrients required for a healthy diet. Each socio economic position indicator was associated with specific differences in nutrient intake suggesting that they underpin different social processes.”

 Gebremariam et al. [49]

Screen-based sedentary time

Soft drink consumption

Youth (<18y)

Secondary, CS

International

“TV viewing appears to be independently associated with soft drink consumption and this association was moderated by parental education in two countries only. Reducing TV time might therefore favorably impact soft drink consumption.”

 Totland et al. [50]

Correlates

Irregular family meal patterns

Youth (<18y)

Secondary, CS

Cross-European

“The majority of 11-year-old children regularly ate breakfast and dinner with their families. More television viewing and less vegetable consumption were associated with irregular family breakfasts and dinners, respectively. Social differences were observed in the regularity of family breakfasts. Promoting family meals across social class may lead to healthier eating and activity habits, sustainable at the population level.”

 Lakerveld et al. [51]

Correlates

Sedentary behaviour

Adults (≥18y)

Secondary, CS

Cross-European

“Higher socio-economic status subgroups were generally more likely to sit for extended time as compared to people with a lower socio-economic status. Type of occupation was the primary discriminator. In addition, gender, level or urbanization and internet use were important predictors of sitting >7.5 h/day. Gender differences depended on the specific context.”

 Loyen et al. [52]

Correlates

Sedentary behaviour

Adults (≥18y), ethnic minority groups

Secondary, CS

Netherlands

“No statistically significant differences in the levels of objectively measured sedentary time or its socio-demographic and lifestyle-related correlates were observed among five ethnic groups in Amsterdam, the Netherlands.”