BackgroundOlder adults are the most sedentary segment of society and high sedentary time is associated with poor health and wellbeing outcomes in this population. Identifying determinants of sedentary behaviour is a necessary step to develop interventions to reduce sedentary time.MethodsA systematic literature review was conducted to identify factors associated with sedentary behaviour in older adults. Pubmed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between 2000 and May 2014. The search strategy was based on four key elements: (a) sedentary behaviour and its synonyms; (b) determinants and its synonyms (e.g. correlates, factors); (c) types of sedentary behaviour (e.g. TV viewing, sitting, gaming) and (d) types of determinants (e.g. environmental, behavioural). Articles were included in the review if specific information about sedentary behaviour in older adults was reported. Studies on samples identified by disease were excluded. Study quality was rated by means of QUALSYST. The full review protocol is available from PROSPERO (PROSPERO 2014: CRD42014009823). The analysis was guided by the socio-ecological model framework.ResultsTwenty-two original studies were identified out of 4472 returned by the systematic search. These included 19 cross-sectional, 2 longitudinal and 1 qualitative studies, all published after 2011. Half of the studies were European. The study quality was generally high with a median of 82 % (IQR 69–96 %) using Qualsyst tool. Personal factors were the most frequently investigated with consistent positive association for age, negative for retirement, obesity and health status. Only four studies considered environmental determinants suggesting possible association with mode of transport, type of housing, cultural opportunities and neighbourhood safety and availability of places to rest. Only two studies investigated mediating factors. Very limited information was available on contexts and sub-domains of sedentary behaviours.ConclusionFew studies have investigated determinants of sedentary behaviour in older adults and these have to date mostly focussed 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-015-0292-3) contains supplementary material, which is available to authorized users.

BackgroundTo date, the scientific literature on socioeconomic correlates and determinants of physical activity behaviours has been dispersed throughout a number of systematic reviews, often focusing on one factor (e.g. education or parental income) in one specific age group (e.g. pre-school children or adults). The aim of this umbrella review is to provide a comprehensive and systematic overview of the scientific literature from previously conducted research by summarising and synthesising the importance and strength of the evidence related to socioeconomic correlates and determinants of PA behaviours across the life course.MethodsMedline, Embase, ISI Web of Science, Scopus and SPORTDiscus were searched for systematic literature reviews and meta-analyses of observational studies investigating the association between socioeconomic determinants of PA and PA itself (from January 2004 to September 2017). Data extraction evaluated the importance of determinants, strength of evidence, and methodological quality of the selected papers. The full protocol is available from PROSPERO (PROSPERO2014:CRD42015010616).ResultsNineteen reviews were included. Moderate methodological quality emerged. For adults, convincing evidence supports a relationship between PA and socioeconomic status (SES), especially in relation to leisure time (positive relationship) and occupational PA (negative relationship). Conversely, no association between PA and SES or parental SES was found for pre-school, school-aged children and adolescents.ConclusionsAvailable evidence on the socioeconomic determinants of PA behaviour across the life course is probable (shows fairly consistent associations) at best. While some evidence is available for adults, less was available for youth. This is mainly due to a limited quantity of primary studies, weak research designs and lack of accuracy in the PA and SES assessment methods employed. Further PA domain specific studies using longitudinal design and clear measures of SES and PA assessment are required.

on behalf of the IDEFICS consortium OBJECTIVES: The aim of this study is to present age-and sex-specific reference values of insulin, glucose, glycosylated haemoglobin (HbA1c) and the homeostasis model assessment to quantify insulin resistance (HOMA-IR) for pre-pubertal children. METHODS: The reference population consists of 7074 normal weight 3-to 10.9-year-old pre-pubertal children from eight European countries who participated in at least one wave of the IDEFICS ('identification and prevention of dietary-and lifestyle-induced health effects in children and infants') surveys (2007)(2008)(2009)(2010) and for whom standardised laboratory measurements were obtained. Percentile curves of insulin (measured by an electrochemiluminescence immunoassay), glucose, HbA1c and HOMA-IR were calculated as a function of age stratified by sex using the general additive model for location scale and shape (GAMLSS) method. RESULTS: Levels of insulin, fasting glucose and HOMA-IR continuously show an increasing trend with age, whereas HbA1c shows an upward trend only beyond the age of 8 years. Insulin and HOMA-IR values are higher in girls of all age groups, whereas glucose values are slightly higher in boys. Median serum levels of insulin range from 17.4 and 13.2 pmol l − 1 in 3-< 3.5-year-old girls and boys, respectively, to 53.5 and 43.0 pmol l − 1 in 10.5-< 11-year-old girls and boys. Median values of glucose are 4.3 and 4.5 mmol l − 1 in the youngest age group and 49.3 and 50.6 mmol l − 1 in the oldest girls and boys. For HOMA-IR, median values range from 0.5 and 0.4 in 3-< 3.5-year-old girls and boys to 1.7 and 1.4 in 10.5-< 11-year-old girls and boys, respectively. CONCLUSIONS: Our study provides the first standardised reference values for an international European children's population and provides the, up to now, largest data set of healthy pre-pubertal children to model reference percentiles for markers of insulin resistance. Our cohort shows higher values of Hb1Ac as compared with a single Swedish study while our percentiles for the other glucose metabolic markers are in good accordance with previous studies.

BackgroundEcological models are currently the most used approaches to classify and conceptualise determinants of sedentary behaviour, but these approaches are limited in their ability to capture the complexity of and interplay between determinants. The aim of the project described here was to develop a transdisciplinary dynamic framework, grounded in a system-based approach, for research on determinants of sedentary behaviour across the life span and intervention and policy planning and evaluation.MethodsA comprehensive concept mapping approach was used to develop the Systems Of Sedentary behaviours (SOS) framework, involving four main phases: (1) preparation, (2) generation of statements, (3) structuring (sorting and ranking), and (4) analysis and interpretation. The first two phases were undertaken between December 2013 and February 2015 by the DEDIPAC KH team (DEterminants of DIet and Physical Activity Knowledge Hub). The last two phases were completed during a two-day consensus meeting in June 2015.ResultsDuring the first phase, 550 factors regarding sedentary behaviour were listed across three age groups (i.e., youths, adults and older adults), which were reduced to a final list of 190 life course factors in phase 2 used during the consensus meeting. In total, 69 international delegates, seven invited experts and one concept mapping consultant attended the consensus meeting. The final framework obtained during that meeting consisted of six clusters of determinants: Physical Health and Wellbeing (71 % consensus), Social and Cultural Context (59 % consensus), Built and Natural Environment (65 % consensus), Psychology and Behaviour (80 % consensus), Politics and Economics (78 % consensus), and Institutional and Home Settings (78 % consensus). Conducting studies on Institutional Settings was ranked as the first research priority. The view that this framework captures a system-based map of determinants of sedentary behaviour was expressed by 89 % of the participants.ConclusionThrough an international transdisciplinary consensus process, the SOS framework was developed for the determinants of sedentary behaviour through 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-016-0409-3) contains supplementary material, which is available to authorized users.

1,11 on behalf of the IDEFICS consortium INTRODUCTION:To characterise the nutritional status in children with obesity or wasting conditions, European anthropometric reference values for body composition measures beyond the body mass index (BMI) are needed. Differentiated assessment of body composition in children has long been hampered by the lack of appropriate references. OBJECTIVES: The aim of our study is to provide percentiles for body composition indices in normal weight European children, based on the IDEFICS cohort (Identification and prevention of Dietary-and lifestyle-induced health Effects in Children and infantS). METHODS: Overall 18 745 2.0-10.9-year-old children from eight countries participated in the study. Children classified as overweight/obese or underweight according to IOTF (N = 5915) were excluded from the analysis. Anthropometric measurements (BMI (N = 12 830); triceps, subscapular, fat mass and fat mass index (N = 11 845-11 901); biceps, suprailiac skinfolds, sum of skinfolds calculated from skinfold thicknesses (N = 8129-8205), neck circumference (N = 12 241); waist circumference and waist-to-height ratio (N = 12 381)) were analysed stratified by sex and smoothed 1st, 3rd, 10th, 25th, 50th, 75th, 90th, 97th and 99th percentile curves were calculated using GAMLSS. RESULTS: Percentile values of the most important anthropometric measures related to the degree of adiposity are depicted for European girls and boys. Age-and sex-specific differences were investigated for all measures. As an example, the 50th and 99th percentile values of waist circumference ranged from 50.7-59.2 cm and from 51.3-58.7 cm in 4.5-to < 5.0-year-old girls and boys, respectively, to 60.6-74.5 cm in girls and to 59.9-76.7 cm in boys at the age of 10.5-10.9 years. CONCLUSION: The presented percentile curves may aid a differentiated assessment of total and abdominal adiposity in European children.

Low levels of physical activity (PA) are reported to contribute to the occurrence of non-communicable diseases over the life course. Although psychological factors have been identified as an important category concerning PA behavior, knowledge on psychological determinants of PA is still inconclusive. Therefore, the aim of this umbrella systematic literature review (SLR) was to summarize and synthesize the scientific evidence on psychological determinants of PA behavior across the life course. A systematic online search was conducted on MEDLINE, ISI Web of Science, Scopus, and SPORTDiscus databases. The search was limited to studies published in English from January 2004 to April 2016. SLRs and meta-analyses (MAs) of observational studies investigating the association of psychological variables and PA were considered eligible. Extracted data were evaluated based on importance of determinants, strength of evidence, and methodological quality. The full protocol is available from PROSPERO (Record ID: CRD42015010616). Twenty reviews (14 SLRs and 6 MAs), mostly of moderate methodological quality, were found eligible. Convincing evidence was found for self-efficacy (positive association with PA) in children and adolescents, and stress (negative association with PA) regardless of age. Most of the evidence revealing an association between psychological determinants and PA is probable and limited, mainly due to differences in the definition of PA and of psychological determinants across reviews. Thus, scholars are urged to reach a consensus on clear definitions of relevant psychological determinants of PA, subsuming cultural biases and allowing the possibility to obtain clear interpretations and generalizability of findings. Finally, most psychological determinants should be considered within a larger framework of other multi-level determinants that may interact or mediate some of the effects.

BackgroundPhysical activity (PA), weight-bearing exercises (WBE) and muscle strength contribute to skeletal development, while sedentary behaviour (SB) adversely affects bone health. Previous studies examined the isolated effect of PA, SB or muscle strength on bone health, which was usually assessed by x-ray methods, in children. Little is known about the combined effects of these factors on bone stiffness (SI) assessed by quantitative ultrasound. We investigated the joint association of PA, SB and muscle strength on SI in children.MethodsIn 1512 preschool (2- < 6 years) and 2953 school children (6–10 years), data on calcaneal SI as well as on accelerometer-based sedentary time (SED), light (LPA), moderate (MPA) and vigorous PA (VPA) were available. Parents reported sports (WBE versus no WBE), leisure time PA and screen time of their children. Jumping distance and handgrip strength served as indicators for muscle strength. The association of PA, SB and muscle strength with SI was estimated by multivariate linear regression, stratified by age group. Models were adjusted for age, sex, country, fat-free mass, daylight duration, consumption of dairy products and PA, or respectively SB.ResultsMean SI was similar in preschool (79.5 ± 15.0) and school children (81.3 ± 12.1). In both age groups, an additional 10 min/day in MPA or VPA increased the SI on average by 1 or 2 %, respectively (p ≤ .05). The negative association of SED with SI decreased after controlling for MVPA. LPA was not associated with SI. Furthermore, participation in WBE led to a 3 and 2 % higher SI in preschool (p = 0.003) and school children (p < .001), respectively. Although muscle strength significantly contributed to SI, it did not affect the associations of PA with SI. In contrast to objectively assessed PA, reported leisure time PA and screen time showed no remarkable association with SI.ConclusionThis study suggests that already an additional 10 min/day of MPA or VPA or the participation in WBE may result in a relevant increase in SI in children, taking muscle strength and SB into account. Our results support the importance of assessing accelerometer-based PA in large-scale studies. This may be important when deriving dose–response relationships between PA and bone health in children.

BackgroundLow levels of physical activity (PA) are a global concern and increasing PA engagement is becoming a priority in current public health policies. Despite the large number of studies and reviews available, the evidence regarding the behavioral determinants of PA is still inconclusive. Thus, the aim of this umbrella systematic literature review (SLR) was to summarize the evidence on the behavioral determinants of PA across the life course.MethodsA systematic online search was conducted on MEDLINE, ISI Web of Science, Scopus, and SPORTDiscus databases. The search was limited to studies published in English from January, 2004 to April, 2016. SLRs and meta-analyses (MAs) of observational studies that investigated the behavioral determinants of PA were considered eligible. The extracted data were assessed based on the importance of the determinants, the strength of evidence, and the methodological quality. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42015010616).ResultsSeventeen reviews on 35 behavioral determinants of PA were eligible for this umbrella SLR. Regardless of age, the most investigated determinants were those related with ‘screen use’ and ‘smoking’. For youth, probable positive evidence emerged for ‘previous PA’ and ‘independent mobility and active transport’ among children and adolescents. For the adult population, ‘transition to university’ and ‘pregnancy/having a child’ showed probable negative associations.ConclusionsAlthough 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 behavioral determinants and PA. Youth should be physically active in the early years and increase active transportation to/from school, independent mobility, and ‘free-range activities’ without adult supervision, whilst adult PA behaviors 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 approaches for the evaluation of different behavioral determinants influencing PA behaviors.