Identifying associations between preschool-aged children's electronic media use and their later well-being is essential to supporting positive long-term outcomes.
To investigate possible ...dose-response associations of young children's electronic media use with their later well-being.
The IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) study is a prospective cohort study with an intervention component. Data were collected at baseline from September 1, 2007, through June 30, 2008, and at follow-up from September 1, 2009, through May 31, 2010, in 8 European countries participating in the IDEFICS study. This investigation is based on 3604 children aged 2 to 6 years who participated in the longitudinal component of the IDEFICS study only and not in the intervention.
Early childhood electronic media use.
The following 6 indicators of well-being from 2 validated instruments were used as outcomes at follow-up: Peer problems and Emotional problems subscales from the Strengths and Difficulties Questionnaire and Emotional well-being, Self-esteem, Family functioning, and Social networks subscales from the KINDLR (Questionnaire for Measuring Health-Related Quality of Life in Children and Adolescents-Revised Version). Each scale was dichotomized to identify those children at risk for poorer outcomes. Indicators of electronic media use (weekday and weekend television and electronic game e-game/computer use) from baseline were used as predictors.
Associations varied between boys and girls; however, associations suggested that increased levels of electronic media use predicted poorer well-being outcomes. Television viewing on weekdays or weekends was more consistently associated with poorer outcomes than e-game/computer use. Across associations, the likelihood of adverse outcomes in children ranged from a 1.2- to 2.0-fold increase for emotional problems and poorer family functioning for each additional hour of television viewing or e-game/computer use depending on the outcome examined.
Higher levels of early childhood electronic media use are associated with children being at risk for poorer outcomes with some indicators of well-being. Further research is required to identify potential mechanisms.
•Our results suggest low HRV (=low parasympathetic activity) as stress indicator.•The HRV–stress relation was most prominent for negative emotions.•The relations of HRV with stress reports were ...sex-dependent.•HRV associated moderately with cortisol, marker of the other main stress system.•We recommend measuring both systems/markers as they might be stimulated differently.
Stress is a complex phenomenon coordinated by two main neural systems: the hypothalamic–pituitary–adrenal system with cortisol as classical stress biomarker and the autonomic nervous system with heart rate variability (HRV) as recently suggested stress marker. To test low HRV (5 minute measurements) as stress indicator in young children (5-10y), associations with self-reported chronic stress aspects (events, emotions and problems) (N=334) and salivary cortisol (N=293) were performed. Peer problems, anger, anxiety and sadness were associated with lower root mean square of successive differences (RMSSD) and high frequency power (i.e. lower parasympathetic activity). Anxiety and anger were also related to a higher low frequency to high frequency ratio. Using multilevel modelling, higher cortisol levels, a larger cortisol awakening response and steeper diurnal decline were also associated with these HRV patterns of lower parasympathetic activity. Conclusion: Low HRV (lower parasympathetic activity) might serve as stress indicator in children.
Background Short sleep duration has been suggested to lead to insulin resistance both directly by altering glucose metabolism and indirectly through obesity. This study aims to investigate ...associations between nocturnal sleep duration and insulin resistance considering abdominal obesity as a mediator. Methods We analysed data of 3 900 children aged 2-15 years participating in the second (2009/10) and third (2013/14) examination wave of the European IDEFICS/I.Family study (hereafter referred to as baseline and follow-up). Information on nocturnal sleep duration was collected by questionnaires and age-standardised (SLEEP z-score). The homeostasis model assessment (HOMA) was calculated from fasting insulin and fasting glucose obtained from blood samples; waist circumference (WAIST) was measured with an inelastic tape. HOMA and WAIST were used as indicators for insulin resistance and abdominal obesity, respectively, and transformed to age- and sex-specific z-scores. Cross-sectional and longitudinal associations between SLEEP z-score and HOMA z-score were investigated based on a path model considering WAIST z-score as a mediator adjusting for relevant confounders. Results Cross-sectionally, baseline SLEEP z-score was negatively associated with baseline WAIST z-score (unstandardised effect estimate -0.120, 95% confidence interval -0.167; -0.073). We observed no direct effect of baseline SLEEP z-score on baseline HOMA z-score but a negative indirect effect through baseline WAIST z-score (-0.042 -0.058; -0.025). Longitudinally, there was no direct effect of baseline SLEEP z-score on HOMA z-score at follow-up but a negative indirect effect through both baseline WAIST z-score and WAIST z-score at follow-up (-0.028 -0.040; -0.016). Conclusions Our results do not support the hypothesis of an association between short sleep duration and insulin resistance independent of abdominal obesity. However, longer sleep duration may exert short and long term beneficial effects on insulin resistance through its beneficial effects on abdominal obesity.
Short sleep duration has been found to be associated with a higher risk for overweight and obesity. However, previous studies have mainly relied on subjective measures of sleep duration and other ...sleep characteristics (eg quality, timing) have often been neglected. Therefore, we aimed to investigate associations between several, mainly objectively measured sleep characteristics and body mass index (BMI). Further, we aimed to identify distinct sleep subtypes based on these sleep characteristics and to study their association with BMI.
Children aged 9–16 years participating in the European I.Family study (N = 559, 51.2% girls, 32.9% overweight/obese) wore an accelerometer for one week on their wrist and recorded their daily wake-up and lights-off times in a sleep diary. Information on sleep duration, sleep efficiency and sleep latency was derived. To identify sleep subtypes, we conducted a latent class analysis using all five sleep variables. Associations between single sleep variables, sleep subtype and age- and sex-specific BMI z-score were investigated using linear mixed-effects regression models to accommodate clustering among siblings.
No statistically significant associations were observed between the single sleep variables (sleep duration, sleep efficiency, sleep latency, wake-up and lights-off times) and BMI z-score. Four sleep subtypes were identified and children were assigned to one of the groups based on their highest probability for latent group membership: “early birds” (17.5% of the sample), “short sleep duration” (14.7%), “optimal sleep” (47.6%) and “poor sleep quality” (20.2%). Sleep subtype was not associated with BMI z-score.
Using objective sleep data, we did not find convincing evidence for associations between the sleep variables under investigation and BMI.
•Four sleep subtypes were identified based on sleep duration, quality and timing.•Subtypes: early birds, short sleep duration, optimal sleep, poor sleep quality.•No evidence for association between single sleep characteristics/subtype and BMI.
Obesity is the result of interactions between genes and environmental factors. Since monogenic etiology is only known in some obesity-related genes, a genetic risk score (GRS) could be useful to ...determine the genetic predisposition to obesity. Therefore, the aim of our study was to build a GRS able to predict genetic predisposition to overweight and obesity in European adolescents. A total of 1069 adolescents (51.3% female), aged 11-19 years participating in the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study were genotyped. The sample was divided in non-overweight (non-OW) and overweight/obesity (OW/OB). From 611 single nucleotide polymorphisms (SNP) available, a first screening of 104 SNPs univariately associated with obesity (p < 0.20) was established selecting 21 significant SNPs (p < 0.05) in the multivariate model. Unweighted GRS (uGRS) was calculated by summing the number of risk alleles and weighted GRS (wGRS) by multiplying the risk alleles to each estimated coefficient. The area under curve (AUC) was calculated in uGRS (0.723) and wGRS (0.734) using tenfold internal cross-validation. Both uGRS and wGRS were significantly associated with body mass index (BMI) (p < .001). Both GRSs could potentially be considered as useful genetic tools to evaluate individual's predisposition to overweight/obesity in European adolescents.
Childhood obesity is a worldwide epidemic. Mediterranean diet (MD) is inversely associated with childhood obesity, but the interaction with other environmental factors, such screen time, might ...influence the health benefits of a high MD adherence in adolescents. The aim of the present study was to assess whether an association between MD and screen time exists in European adolescents. Moreover, we also explored whether sedentary time has a modulatory effect on the association between MD and adiposity. Adherence to the MD (24 h recalls), screen time (questionnaire), pubertal development, body mass index (BMI), fat mass index (FMI) and waist circumference (WC) were evaluated in 2053 adolescents (54.7% females), aged 12.5-17.5 years. In females, MD adherence was associated with lower BMI and FMI only when they were exposed to less than 338 min/day of screen time (81.8% of females); MD adherence was also associated with lower WC only when females were exposed to less than 143 min/day of screen time (31.5% of females). No significant MD-screen time interaction was observed in males. In conclusion, screen-time-based sedentary behaviours had a modulatory effect in the association between MD adherence and adiposity in European female adolescents.
Evidence suggests possible synergetic effects of multiple lifestyle behaviors on health risks like obesity and other health outcomes. A better insight in the clustering of those behaviors, could help ...to identify groups who are at risk in developing chronic diseases. This study examines the prevalence and clustering of physical activity, sedentary and dietary patterns among European adolescents and investigates if the identified clusters could be characterized by socio-demographic factors.
The study comprised a total of 2084 adolescents (45.6% male), from eight European cities participating in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. Physical activity and sedentary behavior were measured using self-reported questionnaires and diet quality was assessed based on dietary recall. Based on the results of those three indices, cluster analyses were performed. To identify gender differences and associations with socio-demographic variables, chi-square tests were executed.
Five stable and meaningful clusters were found. Only 18% of the adolescents showed healthy and 21% unhealthy scores on all three included indices. Males were highly presented in the cluster with high levels of moderate to vigorous physical activity (MVPA) and low quality diets. The clusters with low levels of MVPA and high quality diets comprised more female adolescents. Adolescents with low educated parents had diets of lower quality and spent more time in sedentary activities. In addition, the clusters with high levels of MVPA comprised more adolescents of the younger age category.
In order to develop effective primary prevention strategies, it would be important to consider multiple health indices when identifying high risk groups.
The study aimed to identify the effects of lifestyle, C-reactive protein (CRP) and non-modifiable risk factors on metabolic disturbances in the transition from childhood to adolescence.
In 3889 ...children of the IDEFICS/I.Family cohort, latent transition analysis was applied to estimate probabilities of metabolic disturbances based on waist circumference, blood pressure, blood glucose, and lipids assessed at baseline and at 2- and 6-year follow-ups. Multivariate mixed-effects models were used to assess the age-dependent associations of lifestyle, non-modifiable risk factors and CRP, with the transformed probabilities of showing abdominal obesity, hypertension, dyslipidemia, or several metabolic disturbances (reference: being metabolically healthy).
Higher maternal body mass index, familial hypertension as well as higher CRP z-score increased the risk for all four metabolic outcomes while low/medium parental education increased the risk of abdominal obesity and of showing several metabolic disturbances. Out of the lifestyle factors, the number of media in the bedroom, membership in a sports club, and well-being were associated with some of the outcomes. For instance, having at least one media in the bedroom increased the risk for showing several metabolic disturbances where the odds ratio (OR) markedly increased with age (1.30 95% confidence interval 1.18; 1.43 at age 8; 1.18 1.14; 1.23 for interaction with age; i.e., resulting in an OR of 1.30 × 1.18 = 1.53 at age 9 and so forth). Further, entering puberty at an early age was strongly associated with the risk of abdominal obesity (2.43 1.60; 3.69 at age 8; 0.75 0.69; 0.81 for interaction with age) and the risk of showing several metabolic disturbances (2.46 1.53; 3.96 at age 8; 0.71 0.65; 0.77 for interaction with age).
Various factors influence the metabolic risk of children revealing the need for multifactorial interventions. Specifically, removing media from children's bedroom as well as membership in a sports club seem to be promising targets for prevention.
To provide age- and sex-specific percentile curves of serum 25-hydroxyvitamin D (25(OH)D) by determinants from 3-<15 year-old European children, and to analyse how modifiable determinants influence ...25(OH)D.
Serum samples were collected from children of eight European countries participating in the multicenter IDEFICS/I.Family cohort studies. Serum 25(OH)D concentrations were analysed in a central lab by a chemiluminescence assay and the values from 2171 children (N = 3606 measurements) were used to estimate percentile curves using the generalized additive model for location, scale and shape. The association of 25(OH)D with time spent outdoors was investigated considering sex, age, country, parental education, BMI z score, UV radiation, and dietary vitamin D in regressions models.
The age- and sex-specific 5th and 95th percentiles of 25(OH)D ranged from 16.5 to 73.3 and 20.8 to 79.3 nmol/l in girls and boys, respectively. A total of 63% had deficient (<50 nmol/l), 33% insufficient (50-<75 nmol/l) and 3% sufficient (≥75 nmol/l) levels. 25(OH)D increased with increasing UV radiation, time spent outdoors, and vitamin D intake and slightly decreased with increasing BMI z score and age. The odds ratio (OR) for a non-deficient 25(OH)D status (reference category: deficient status) by one additional hour spent outdoors was 1.21, 95% CI 1.12-1.31, i.e., children who spent one more hour per day outdoors than other children had a 21% higher chance of a non-deficient than a deficient status.
A majority of children suffer from deficient 25(OH)D. UV radiation, outdoor time, and dietary vitamin D are important determinants of 25(OH)D.
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