Healthy diets positively associated with health-related quality of life in children and adolescents from low socioeconomic areas: Findings from the Greek Food Aid Program, DIATROFI

OBJECTIVES

To assess the relationship of diet with health-related quality of life (HRQoL) in vulnerable children and adolescents.

METHODS

Data included 6583 children and adolescents (aged 3-18 years old) from the Greek Food-Aid DIATROFI Program in the 2015 to 2016 and 2017 to 2018 school years. HRQoL was measured with the Pediatric Quality of Life Inventory questionnaire and diet with food frequency questionnaires. The healthy plant-based diet index (hPDI), animal score, and dietary patterns were investigated.

RESULTS

The hPDI and animal score were associated with good HRQoL (odds ratio [OR] [95% confidence interval], 10-unit increase: ORhPDI = 1.28 [1.05, 1.57], ORanimal = 1.51 [1.14, 2.00]) and physical (ORanimal = 1.62 [1.23, 2.13]), emotional (ORhPDI = 1.30 [1.07, 1.58], ORanimal = 1.41 [1.08, 1.85]) and school function (ORhPDI = 1.32 [1.09, 1.59], ORanimal = 1.46 [1.12, 1.89]). Dietary patterns of fruits, raw vegetables, and cheese were associated with good HRQoL (OR of 1-unit increase: 1.22 [1.13, 1.32]), and physical OR = 1.18 [1.09, 1.27]) and emotional function (OR = 1.09 [1.02, 1.18]). Starchy foods and sweetened beverages were associated with poor HRQoL (OR = 0.75 [0.63, 0.90]), and emotional (OR = 0.80 [0.68, 0.95]) and school function (OR = 0.72 [0.61, 0.85]).

CONCLUSION

Healthy diets and dietary patterns were positively associated with the HRQoL of vulnerable children and adolescents, which may offer opportunities for prevention.

Pediatric metabolic syndrome definitions impact prevalence and socioeconomic gradients

Background

The choice of pediatric metabolic syndrome (MetS) definition influences prevalence estimates, but further implications, especially on the association with socioeconomic status (SES), are not well-known. This hampers a synthesis of the evidence to help guide the relevant stakeholders. For this reason, we aim to assess the impact of alternative definitions on the prevalence of MetS, the children that are identified, and the association between SES and MetS.

Methods

Data were used from the Lifelines Cohort Study, a prospective multigenerational cohort in the Netherlands. At baseline 9,754 children participated, of which 5,085 (52.1%) were included in the longitudinal analyses. We computed the prevalence of MetS according to five published definitions and measured the observed positive agreement between pairs of definitions, indicating the proportion of agreement across the average number of MetS cases. Logistic regression was used to assess the association between SES and MetS. All models were adjusted for age and sex; the longitudinal models were also adjusted for baseline MetS status.

Results

The prevalence rates of MetS varied between definitions (0.7-3.0% at baseline), but positive agreement between MetS definitions was generally fair to good ranging from 0.34 (95% confidence interval (CI) 0.28; 0.41) to 0.66 (95%CI 0.58; 0.75) at baseline. At both assessments, we found an inverse association between baseline SES and MetS, which ranged from 0.81 (95%CI 0.70; 0.93) to 0.92 (95%CI 0.86; 0.98) per definition in the longitudinal analyses with a mean follow-up (SD) of 3.0 (0.75) years.

Conclusions

Alternative definitions of MetS lead to differing prevalence estimates, and they agreed on 50% of the average number of cases of MetS. The alternative definitions also lead to similar socioeconomic gradients; regardless of which definition was used we concluded low SES was a risk factor for developing MetS.

Key messages

Evidence regarding different definitions of metabolic syndrome in children can be combined because the agreement among definitions is generally fair to good. As low socioeconomic status is a consistent risk factor for developing metabolic syndrome, preventive interventions should preferentially target children from low socioeconomic backgrounds.

Postnatal screening and care for non-medical risk factors by preventive child healthcare in deprived and non-deprived neighbourhoods

Background

Children born in families with non-medical risk factors, such as deprivation, have higher odds of preterm birth (< 37 weeks of gestation) or being born small for gestational age (birth weight < 10th percentile). In addition, growing up they are at risk for growth and developmental problems. Preventive Child Healthcare (PCHC) monitors growth and development of babies and children. Early identification of children at risk could result in early interventions to prevent growth and developmental problems in later life. Therefore, we aimed to assess current practices in postnatal risk screening and care for non-medical risk factors and the collaboration with other healthcare professionals, in both deprived and non-deprived neighbourhoods in the Netherlands.

Methods

Eight out of ten invited PCHC organisations, from different areas in the Netherlands, consented to participate in this study. A questionnaire was designed and digitally distributed to professionals working at these organisations, where 370 physicians and nurses were employed. Data was collected between June and September 2016. Descriptive statistics, chi square tests and t-tests were applied.

Results

Eighty-nine questionnaires were eligible for analyses. Twenty percent of the respondents were working in a deprived neighbourhood and 70.8% of the respondents were employed as nurse. Most of them performed screening for non-medical risk factors in at least 50% of their consultations. PCHC professionals working in deprived neighbourhoods encountered significantly more often families with non-medical risk factors and experienced significantly more communication problems than their colleagues working in non-deprived neighbourhoods. 48.2% of the respondents were satisfied with the current form of postnatal risk screening in their organisation, whereas 41.2% felt a need for a structured postnatal risk assessment. Intensified collaboration is preferred with district-teams, general practitioners and midwifes, concerning clients with non-medical risk factors.

Conclusion

This study shows that postnatal screening for non-medical risk factors is part of current PCHC practice, regardless the neighbourhood status they are deployed. PCHC professionals consider screening for non-medical risk factors as their responsibility. Consequently, they felt a need for a structured postnatal risk assessment and for an intensified collaboration with other healthcare professionals.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3243-2) contains supplementary material, which is available to authorized users.

The validity of the 4-Skills Scan A double-validation study

Adequate gross motor skills are an essential aspect of a child's healthy development. Where physical education (PE) is part of the primary school curriculum, a strong curriculum-based emphasis on evaluation and support of motor skill development in PE is apparent. Monitoring motor development is then a task for the PE teacher. To fulfill this task, teachers need adequate tools. The 4-Skills Scan is a quick and easily manageable gross motor skill instrument; however, its validity has never been assessed. Therefore, the purpose of this study was to assess the construct and concurrent validity of both 4-Skills Scans (version 2007 and version 2015). A total of 212 primary school children (6-12 years old) was requested to participate in both versions of the 4-Skills Scan. For assessing construct validity, children covered an obstacle course with video recordings for observation by an expert panel. For concurrent validity, a comparison was made with the M-ABC-2, by calculating Pearson correlations. Multivariable linear regression analyses were performed to determine the contribution of each subscale to the construct of gross motor skills, according to the M-ABC-2 and the expert panel. Correlations between the 4-Skills Scans and expert valuations were moderate, with coefficients of .47 (version 2007) and .46 (version 2015). Correlations between the 4-Skills Scans and the M-ABC-2 (gross) were moderate (.56) for version 2007 and high (.64) for version 2015. It is concluded that both versions of the 4-Skills Scans are satisfactory valid instruments for assessing gross motor skills during PE lessons.