Background: Missing data is a common problem in epidemiological studies, while it becomes more critical, when the missing data concern a multi-item instrument, since lack of information in even one of its items, leads to the inability to calculate the total score of the instrument. The aim was to investigate the socio-demographic, lifestyle and clinical determinants of low response rate in two self-rating multi item scales, estimating the individuals' nutritional habits and psychological disorders, as well as, to compare different missing data handling techniques regarding the imputation of missing values in this context. Methods: The sample from ATTICA epidemiological study was used, with complete baseline information (2001-2002) regarding their demographic characteristics [n = 2194 subjects (1364 men: 64 years old (SD = 12 years) and 830 women: 66 years old (SD = 12 years))]. Adherence to the Mediterranean diet and depressive symptomatology were assessed at baseline, with the MedDietScore scale and the Zung's Self-rating Depression Scale (SDS), respectively. Logistic and Poisson regression analysis were used, in order to explore the low response's determinants in each scale. Seven missing data handling techniques were compared in terms of the estimated regression coefficients and their standard errors, under different scenarios of missingness, in the context of a multivariable logistic regression model examining the association of each scale with the participants' likelihood of being hypertensive.

Background Recent meta-analyses suggest the use of technology-based interventions as a treatment option for obesity in adulthood. Similar meta-analytic approaches for children are scarce. Objective The aim of this meta-analysis is to examine the effect of technology-based interventions on overweight and obesity treatment in children and adolescents. Methods A systematic literature search was performed using MEDLINE (PubMed), Scopus, and Cochrane Library for randomized clinical trials to identify interventional studies published between January 2000 and February 2021. Results In total, 9 manuscripts from 8 clinical trials of 582 children or adolescents were considered eligible. BMI, BMI z-score, and other BMI-related baseline metrics during and after intervention were considered as primary outcomes. In 7 of 8 studies, a technology-based intervention was applied in addition to conventional care. Of the 8 studies, 6 studies were conducted in the United States, 1 in Australia, and 1 in northwestern Europe. In total, 5 studies included adolescents, whereas the rest addressed children aged 9 to 12 years. Intervention duration ranged from 3 to 24 months. Significant differences between groups in BMI metric changes were reported by 5 of the 8 studies. Pooled analysis revealed an overall significant decrease in BMI metrics in the intervention group (standardized mean difference –0.61, 95% CI –1.10 to –0.13; P=.01). Subgroup analysis revealed that significance was lost in case of no parental involvement (standardized mean difference –0.36, 95% CI –0.83 to 0.11; P=.14). The small number of clinical trials found, the varying study quality, and the study heterogeneity are some limitations of this review. Conclusions The studies reported herein describe functional and acceptable technology-based approaches, in addition to conventional treatments, to enhance weight loss in young populations.

No abstract

Background To explore the effect of household food insecurity on dietary patterns of children and adolescents participating in a school food-aid programme in regions of Greece with low socioeconomic status. Methods A cross-sectional study was conducted during the school year 2013–14, among 406 schools in low socioeconomic status regions of Greece. Dietary habits and sociodemographic characteristics of students and their families were recorded. Factor analysis was used in order to derive children’s and adolescents’ dietary patterns and analysis of covariance was performed to examine the effect of households’ food insecurity level on those patterns. A total of 31 399 students participated in the study; 16 652 children (5–11 years) and 14 747 adolescents (12–18 years). Results Factor analysis identified five dietary patterns in both age groups, explaining the 49.1% (children) and 53.0% (adolescents) of the total variation in intake. After adjusting for various factors, the household’s food insecurity was significantly associated with the majority of the derived patterns in both age groups, with most pronounced differences being observed for the consumption of red meat, poultry and fish, fruits, as well as red processed meat, cereals and dairy products, which was lower among children and adolescents with food insecurity. Children with food insecurity consumed significantly more unhealthy food, such as chips, fast food, sugared drinks, sweets, French fries and mayonnaise sauce. Conclusions Promotion of healthy eating to households facing food insecurity is of crucial importance, giving emphasis in the design of low cost, yet highly nutritious programmes.

No abstract