Lifestyle risks for chronic disease among Australian adolescents: a cross‐sectional survey

The aim was to develop and test a brief revised version of the family affluence scale. A total of 7120 students from Denmark, Greenland, Italy, Norway, Poland, Romania, Scotland and Slovakia reported on a list of 16 potential indicators of affluence. Responses were subject to item screening and test of dimensionality. Bifactor analysis revealed a strong general factor of affluence in all countries, but with additional specific factors in all countries. The specific factors mainly reflected overlapping item content. Item screening was conducted to eliminate items with low discrimination and local dependence, reducing the number of items from sixteen to six: Number of computers, number of cars, own bedroom, holidays abroad, dishwasher, and bathroom. The six-item version was estimated with Samejima’s graded response model, and tested for differential item functioning by country. Three of the six items were invariant across countries, thus anchoring the scale to a common metric across countries. The six-item scale correlated with parental reported income groups in six out of eight countries. Findings support a revision to six items in the family affluence scale.

This secondary analysis of data from a randomized clinical trial examines the association of screen time (via use of social media, television, video gaming, and computers) and symptoms of depression among adolescents. What is the association of various types of screen time and depression in adolescence? In this cohort study of 3826 adolescents, a within-person association, based on repeated measures, was found between social media and television use with symptoms of depression in adolescence. Use of social media and television in adolescents may enhance symptoms of depression and should therefore be taken into account when developing preventive methods. Increases in screen time have been found to be associated with increases in depressive symptoms. However, longitudinal studies are lacking. To repeatedly measure the association between screen time and depression to test 3 explanatory hypotheses: displacement, upward social comparison, and reinforcing spirals. This secondary analysis used data from a randomized clinical trial assessing the 4-year efficacy of a personality-targeted drug and alcohol prevention intervention. This study assessed screen time and depression throughout 4 years, using an annual survey in a sample of adolescents who entered the seventh grade in 31 schools in the Greater Montreal area. Data were collected from September 2012 to September 2018. Analysis began and ended in December 2018. Independent variables were social media, television, video gaming, and computer use. Symptoms of depression was the outcome, measured using the Brief Symptoms Inventory. Exercise and self-esteem were assessed to test displacement and upward social comparison hypothesis. A total of 3826 adolescents (1798 girls [47%]; mean [SD] age, 12.7 [0.5] years) were included. In general, depression symptoms increased yearly (year 1 mean [SD], 4.29 [5.10] points; year 4 mean [SD], 5.45 [5.93] points). Multilevel models, which included random intercepts at the school and individual level estimated between-person and within-person associations between screen time and depression. Significant between-person associations showed that for every increased hour spent using social media, adolescents showed a 0.64-unit increase in depressive symptoms (95% CI, 0.32-0.51). Similar between-level associations were reported for computer use (0.69; 95% CI, 0.47-0.91). Significant within-person associations revealed that a further 1-hour increase in social media use in a given year was associated with a further 0.41-unit increase in depressive symptoms in that same year. A similar within-person association was found for television (0.18; 95% CI, 0.09-0.27). Significant between-person and within-person associations between screen time and exercise and self-esteem supported upward social comparison and not displacement hypothesis. Furthermore, a significant interaction between the between-person and within-person associations concerning social media and self-esteem supported reinforcing spirals hypothesis. Time-varying associations between social media, television, and depression were found, which appeared to be more explained by upward social comparison and reinforcing spirals hypotheses than by the displacement hypothesis. Both screen time modes should be taken into account when developing preventive measures and when advising parents.

To determine whether sleep timing behaviour is associated with energy intake and diet quality in children and adolescents. Cross-sectional analysis of nationally representative survey data. A total of 2200 participants of the 2007 Australian National Children's Nutrition and Physical Activity Survey aged 9-16 years with 2 days of food intake data, 4 days of use of time data and complete anthropometry. Participants were grouped into one of four sleep-wake behaviour categories: early bed-early rise (EE); early bed-late rise (EL); late bed-early rise (LE) and late bed-late rise (LL). The four categories were compared for body mass index (BMI) z-score, energy intake and diet quality assessed using the Dietary Guideline Index for Children and Adolescents. Analyses were adjusted for survey design, sociodemographic characteristics, sleep duration and physical activity level (PAL). In adjusted multivariate regression models with sleep timing behaviour group as the independent variable, the 'LL' category compared with the 'EE' category had a higher BMI z-score (β=0.20, 95% confidence interval (CI) 0.06 to 0.34, P=0.007), and lower diet quality (β=-4.0, 95% CI -5.7 to -2.3, P<0.001). Children and adolescents who went to bed late also had a higher intake of extra foods (that is, energy-dense, nutrient-poor foods) while those whom went to bed early consumed more fruit and vegetables. Energy intake was associated with sleep duration (β=-4.5 kJ, 95% CI -6.7 to -2.4, P<0.001), but not sleep timing behaviour. Late bedtimes and late wake up times are associated with poorer diet quality, independent of sleep duration, PAL and child and sociodemographic characteristics.