Contemporary height, weight and body mass index references for children aged 0 to adulthood in Switzerland compared to the Prader reference, WHO and neighbouring countries

Determinants of health-related quality of life in healthy children and adolescents during the COVID-19 pandemic: Results from a prospective longitudinal cohort study

Understanding health-related quality of life (HRQOL) in children and adolescents, during a pandemic and afterwards, aids in understanding how circumstances in their lives impact their well-being. We aimed to identify determinants of HRQOL from a broad range of biological, psychological, and social factors in a large longitudinal population-based sample. Data was taken from a longitudinal sample (n = 1843) of children and adolescents enrolled in the prospective school-based cohort study Ciao Corona in Switzerland. The primary outcome was HRQOL, assessed using the KINDL total score and its subscales (each from 0, worst, to 100, best). Potential determinants, including biological (physical activity, screen time, sleep, etc.), psychological (sadness, anxiousness, stress), and social (nationality, parents' education, etc.) factors, were assessed in 2020 and 2021 and HRQOL in 2022. Determinants were identified in a data-driven manner using recursive partitioning to define homogeneous subgroups, stratified by school level. Median KINDL total score in the empirically identified subgroups ranged from 68 to 83 in primary school children and from 69 to 82 in adolescents in secondary school. The psychological factors sadness, anxiousness, and stress in 2021 were identified as the most important determinants of HRQOL in both primary and secondary school children. Other factors, such as physical activity, screen time, chronic health conditions, or nationality, were determinants only in individual subscales.

CONCLUSION

Recent mental health, more than biological, physical, or social factors, played a key role in determining HRQOL in children and adolescents during pandemic times. Public health strategies to improve mental health may therefore be effective in improving HRQOL in this age group.

WHAT IS KNOWN

• Assessing health-related quality of life (HRQOL) in children and adolescents aids in understanding how life circumstances impact their well-being. • HRQOL is a complex construct, involving biological, psychological, and social factors. Factors driving HRQOL in children and adolescents are not often studied in longitudinal population-based samples.

WHAT IS NEW

• Mental health (stress, anxiousness, sadness) played a key role in determining HRQOL during the coronavirus pandemic, more than biological or social factors. • Public health strategies to improve mental health may be effective in improving HRQOL in children.

Health-Related Quality of Life and Adherence to Physical Activity and Screen Time Recommendations in Schoolchildren: Longitudinal Cohort Ciao Corona

Objectives: We investigated changes in adherence to physical activity (PA) and screen time (ST) recommendations of children and adolescents throughout the pandemic, and their association with health-related quality of life (HRQOL). Methods: 1,769 primary (PS, grades 1-6) and secondary (SS, 7-9) school children from Ciao Corona, a school-based cohort study in Zurich, Switzerland, with five questionnaires 2020-2022. HRQOL was assessed using the KINDL questionnaire. PA (≥60 min/day moderate-to-vigorous PA) and ST (≤2 h/day ST) recommendations followed WHO guidelines. Results: Adherence to PA recommendations dropped in 2020 (83%-59% PS, 77%-52% SS), but returned to pre-pandemic levels by 2022 (79%, 66%). Fewer children met ST recommendations in 2020 (74% PS, 29% SS) and 2021 (82%, 37%) than pre-pandemic (95%, 68%). HRQOL decreased 3 points between 2020 and 2022, and was 9.7 points higher (95% CI 3.0-16.3) in March 2021 in children who met both versus no recommendations. Conclusion: Adherence to WHO guidelines on PA and ST during the pandemic had a consistent association with HRQOL despite longitudinal changes in behavior.

Secular trends in motor performance in Swiss children and adolescents from 1983 to 2018

Introduction

Environmental changes, including globalization, urbanization, social and cultural changes in society, and exposure to modern digital technology undoubtedly have an impact on children’s activity and lifestyle behavior. In fact, marked reductions in children’s physical activity levels have been reported over the years and sedentary behavior has increased around the world. The question arises whether these environmental changes had an impact on general motor performance in children and adolescents. The study aimed to investigate secular trends of motor performance in Swiss children and adolescents, aged between 7 and 18 years, over a period of 35 years from 1983 to 2018.

Methods

Longitudinal data on the five motor components of the Zurich Neuromotor Assessment (ZNA) – pure motor (PM), fine motor (FM), dynamic balance (DB), static balance (SB), and contralateral associated movements (CAM) – were pooled with cross-sectional data on PM and FM from eight ZNA studies between 1983 and 2018. Regression models were used to estimate the effect of the year of birth on motor performance and body mass index (BMI) measurements. Models were adjusted for age, sex, and socioeconomic status.

Results

The secular trend estimates in standard deviation scores (SDS) per 10 years were − 0.06 [−0.33; 0.22, 95% Confidence Interval] for PM, −0.11 [−0.41; 0.20] for FM, −0.38 [−0.66; −0.09] for DB (−0.42 when controlled for BMI), −0.21 [−0.47; 0.06] for SB, and − 0.01 [−0.32; 0.31] for CAM. The mean change in BMI data was positive with 0.30 SDS [0.07; 0.53] over 10 years.

Discussion

Despite substantial societal changes since the 1980s, motor performance has remained relatively stable across generations. No secular trend was found in FM, PM, SB, and CAM over a period of 35 years. A secular trend in DB was present independent of the secular trend in body mass index.

Age and body mass index affect fit of spirometry GLI references in schoolchildren

Background

References from the Global Lung Function Initiative (GLI) are widely used to interpret children's spirometry results. We assessed fit for healthy schoolchildren.

Methods

LuftiBus in the School was a population-based cross-sectional study undertaken in 2013–2016 in the canton of Zurich, Switzerland. Parents and their children aged 6–17 years answered questionnaires about respiratory symptoms and lifestyle. Children underwent spirometry in a mobile lung function lab. We calculated GLI-based z-scores for forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC), FEV₁/FVC and forced expiratory flow for 25–75% of FVC (FEF_25–75) for healthy White participants. We defined appropriate fit to GLI references by mean values between +0.5 and −0.5 z-scores. We assessed whether fit varied by age, body mass index, height and sex using linear regression models.

Results

We analysed data from 2036 children with valid FEV₁ measurements, of whom 1762 also had valid FVC measurements. The median age was 12.2 years. Fit was appropriate for children aged 6–11 years for all indices. In adolescents aged 12–17 years, fit was appropriate for FEV₁/FVC z-scores (mean±sd −0.09±1.02), but not for FEV₁ (−0.62±0.98), FVC (−0.60±0.98) and FEF_25–75 (−0.54±1.02). Mean FEV₁, FVC and FEF_25–75 z-scores fitted better in children considered overweight (−0.25, −0.13 and −0.38, respectively) than normal weight (−0.55, −0.50 and −0.55, respectively; p-trend <0.001, 0.014 and <0.001, respectively). FEV₁, FVC and FEF_25–75 z-scores depended on both age and height (p-interaction 0.033, 0.019 and <0.001, respectively).

Conclusion

GLI-based FEV₁, FVC, and FEF_25–75 z-scores do not fit White Swiss adolescents well. This should be considered when using reference equations for clinical decision-making, research and international comparison.

This study suggests GLI-based FEV₁, FVC and FEF_25–75% z-scores over-detect abnormal lung function in Swiss adolescents, and more so among slimmer adolescents, which has important implications for clinical care, research and international comparisonshttps://bit.ly/3sbGtAS

The increase in child obesity in Switzerland is mainly due to migration from Southern Europe - a cross-sectional study

Background

Novel height, weight and body mass index (BMI) references for children in Switzerland reveal an increase in BMI compared to former percentile curves. This trend may be the result of children with parents originating from Southern European countries having a higher risk of being overweight compared to their peers with parents of Swiss origin. We examined the association of generational, migration-related and socioeconomic factors on BMI in Switzerland and expect the results to lead to more targeted prevention programs.

Methods

From contemporary cross-sectional data, we calculated subgroup-specific BMI percentiles for origin. Results for children of Swiss origin were compared with historical BMI data from Zurich. We tested for the association of overweight and obesity with origin and compared the distributions of BMI percentile ranks. Logistic regression analyses were applied to predict probabilities of being overweight or obese by origin and the Swiss neighborhood index of socioeconomic position (SSEP).

Results

Compared to the BMI from two generations ago, the newly calculated BMI increased only slightly for children with both parents from Switzerland; 1.2% of these girls and 1.6% of these boys are obese. In the Swiss population, 13% of the children have parents from Southern Europe and the proportion of obesity is 57 and 42% in these boys and girls, respectively. Their BMI medians correspond to those of their parents’ countries of origin. For the probability of being overweight or obese, the SSEP differences are less important than the status of origin.

Conclusion

We identified children with both parents from Southern Europe as the main influence driving the increase in BMI in Switzerland over the past 50 years. A differentiated consideration of the proportions of various migrant groups within cross-sectional samples is essential when monitoring BMI. Ignoring fluctuations can lead to false conclusions.