Dataset Information

Clustering of health-related behaviours within children aged 11-16: a systematic review.

ABSTRACT:

Objective

We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11-16?year olds.

Method

A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11-16?year olds in high-income countries. Health-related behaviours of interest were substance use (alcohol, cigarettes and other drug use) and other behavioural risk indicators (diet, physical activity, gambling and sexual activity).

Results

The review identified 41 studies, which reported 198 clusters of health-related behaviours of interest. The behaviours of interest reported within clusters were used to define eight behavioural archetypes. Some included studies only explored substance use, while others considered substance use and/or other health-related behaviours. Consequently, three archetypes were comprised by clusters reporting substance use behaviours alone. The archetypes were: (1) Poly-Substance Users, (2) Single Substance Users, (3) Substance Abstainers, (4) Substance Users with No/Low Behavioural Risk Indicators, (5) Substance Abstainers with Behavioural Risk Indicators, (6) Complex Configurations, (7) Overall Unhealthy and (8) Overall Healthy.

Conclusion

Studies of youth health behavioural clustering typically find both a 'healthy' cluster and an 'unhealthy' cluster. Unhealthy clusters are often characterised by poly-substance use. Our approach to synthesising cluster analyses may offer a means of navigating the heterogeneity of method, measures and behaviours of interest in this literature.

SUBMITTER: Whitaker V

PROVIDER: S-EPMC7807795 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Clustering of health-related behaviours within children aged 11-16: a systematic review.

Whitaker Victoria V Oldham Melissa M Boyd Jennifer J Fairbrother Hannah H Curtis Penny P Meier Petra P Holmes John J

BMC public health 20210114 1

<h4>Objective</h4>We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11-16 year olds.<h4>Method</h4>A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11-16 year olds in high-income countries. Hea ...[more]

PMID: 33446174

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Project description:BackgroundMeeting physical activity and screen time guidelines has been associated with improved health in children. Research has shown that lifestyle behaviours happen in combination and can be tracked into later life. Thus, a complex approach is needed to identify the effects of physical activity and screen time altogether. This study aims to identify clusters of both behaviours in a cohort of Irish 3-year-old children (n = 8833) and determine the association with sociodemographic characteristics and behaviours at age 5 and 7-8.MethodsData from the "Growing Up in Ireland" study collected between 2010 and 2016 was used in this study. Two-step cluster analysis was used to understand how physical activity and recreational screen time behaviours group together among 3-year-old children. Binary logistic regressions were conducted to examine if cluster placement at age 3 determined physical activity and recreational screen time behaviours at age 5 and 7-8 years, while controlling for gender of child, gender, age and employment status of the primary caregiver.ResultsSix clusters were identified in 9771 (49.3% female) 3-year-old children with the majority falling into a "High Active & Mixed Screen Time" (23.2%). Those in the "High Active & Mixed Screen Time" cluster at age 3 were more likely to engage in all physical activities reported at age 5 (p < 0.01) and age 7-8 (p < 0.01) when compared to a "Low Active & Screen Time Exceed" cluster. Children categorised in a "Moderate Active & Screen Time Below" and "Moderate Active & Screen Time Exceed" were more likely to engage in the same physical activities at age 5 and 7-8 (p < 0.05 - p < 0.01). However, children in the latter cluster were also more likely (p < 0.05) to play on a computer or tablet device.ConclusionsThis paper highlights the importance of establishing positive health-related behaviours during early childhood, as this predicts future engagement in health-promoting activities. Regardless of screen time level, being part of a cluster with moderate or high levels of physical activity positively influences a child's future physical activity at age 5 and again at age 7 -8 years. The multiple layers of influence on a child's development should be leveraged to support the adoption of health-enhancing behaviours.

Project description:OBJECTIVES:To describe the distribution of health-related quality of life (HRQL) in a national sample of Australian children aged 11-12 years and their parents, and examine associations within parent-child dyads. DESIGN:The Child Health CheckPoint, a population-based cross-sectional study nested between waves 6 and 7 of the Longitudinal Study of Australian Children (LSAC). SETTING:Assessment centres in seven Australian cities and eight regional towns, or home visit; February 2015 to March 2016. PARTICIPANTS:Of all participating CheckPoint families (n=1874), 1853 children (49.0% girls) and 1863 parents (87.7% mothers) with HRQL data were included (1786 pairs). OUTCOME MEASURES:HRQL was self-reported using preference-based (Child Health Utility 9Dimension, CHU9D) and non-preference-based (Pediatric Quality of Life, PedsQL V.4.0) measures for children and preference-based measures for parents (CHU9D; Assessment of Quality of Life 8 Dimension, AQoL-8D). Utility scores from preference-based measures were calculated using existing Australian algorithms to present a score on a 0-1 scale, where 1 represents full health. Parent-child concordance was assessed using Pearson's correlation coefficients and adjusted linear regression models. Survey weights and methods were applied to account for LSAC's complex sample design, stratification and clustering within postcodes. RESULTS:Children's means and SD were 0.81 (SD 0.16) for CHU9D and 78.3 (SD 13.03) for PedsQL. In adults, mean HRQL for AQoL-8D and CHU9D were 0.78 (SD 0.16) and 0.89 (SD 0.10), respectively. Mean HRQL was similar for boys and girls, but slightly higher for fathers than mothers. The Pearson correlation coefficient for parent-child CHU9D values was 0.13 (95% CI 0.09 to 0.18). Percentiles and concordance are presented for both samples for males and females separately and together. CONCLUSIONS:We provide Australian paediatric population values for HRQL measures, and the first national CHU9D values for mid-life adults. At age 11-12 years in this relatively healthy sample, parent-child concordance in HRQL was small.

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Project description:BackgroundStudies combining data from digital surveys and electronic health records (EHR) can be used to conduct comprehensive assessments on COVID-19 vaccine safety.MethodsWe conducted an observational study using data from a digital survey and EHR of children aged 5-11 years vaccinated with Pfizer-BioNTech COVID-19 mRNA vaccine across Kaiser Permanente Southern California during November 4, 2021-February 28, 2022. Parents/guardians who enrolled their children were sent a 14-day survey on reactions. Survey results were combined with EHR, and medical encounters were described for children whose parents or guardians indicated seeking medical care for vaccine-related symptoms. This study describes self-reported reactions (local and systemic) and additional symptoms (chest pain, tachycardia, and pre-syncope).ResultsThe study recruited 7,077 participants aged 5-11 years who received the Pfizer-BioNTech COVID-19 mRNA vaccine. Of 6,247 participants with survey responses after dose 1, 2,176 (35 %) reported at least one systemic reaction, and 1,076 (32 %) of 3,401 respondents following dose 2 reported at least one systemic reaction. Local reactions were reported less frequently following dose 2 (1,113, 33 %) than dose 1 (3,140, 50 %). The most frequently reported reactions after dose 1 were pain at the injection site (48 %), fatigue (20 %), headache (12 %), myalgia (9 %) and fever (5 %). The most frequently reported symptoms after dose 2 were also pain at the injection site (30 %), fatigue (19 %), headache (13 %), myalgia (10 %) and fever (9 %). Post-vaccination reactions occurred most frequently-one day following vaccination. Chest pain or tachycardia were reported infrequently (1 %). EHR demonstrated that parents rarely sought care for post-vaccination symptoms, and among those seeking care, the most common symptoms documented in EHR were fever and nausea, comprising <0.5 % of children. No encounters were related to myocarditis.ConclusionWhile post-vaccination reactions to the Pfizer-BioNTech COVID-19 mRNA vaccine were common in children aged 5-11 years, our data showed that in most cases they were transient and did not require medical care.

Project description:BackgroundScreen-time and unhealthy dietary behaviours are highly pervasive in young children and evidence suggests that these behaviours often co-occur and are associated. Identifying clusters of unhealthy behaviours, and their influences early in childhood, can assist in the development of targeted preventive interventions. The purpose of this study was to examine the sociodemographic, behavioural, and home physical environmental correlates of co-occurring screen-time and unhealthy eating behaviours and to assess the clustering of screen-time and unhealthy dietary behaviours in young children.MethodsParents of 126 children, from the UK, aged 5-6 years (49% boys) completed a questionnaire which assessed their child's screen-time (ST), fruit and vegetable (FV), and energy-dense (ED) snack consumption. Categories of health behaviours were created based on frequencies of children meeting recommendations for FV and ST and median splits of frequencies for ED snacks. Parents reported on their own behaviours (ST, FV, and ED snack consumption), how often they ate meals and watched TV with their child, and on the availability and accessibility of foods within the home. An observed over expected ratio (O/E) was used to assess behavioural clustering. Multivariable multinomial logistic regression was used to examine correlates of behaviour patterns.ResultsApproximately 25% of children had two or three health risk behaviours. Correlates consistently associated with clusters included parental income, eating meals at the TV, parental ST and ED snack food consumption, and home availability of ED snack foods. Observed over expected ratios were close to 1 and ranged from 0.78 to 1.43. The three-risk behaviour combination of insufficient FV consumption, high ED snack consumption, and excessive ST occurred more frequently than expected (1.23 (95% CI 0.89, 1.58)).ConclusionsST and unhealthy dietary behaviours cluster in children as young as 5 years of age and parents' own behaviours appear to be important influencing factors. Further research into the development of behavioural clustering in young children to identify and further understand the mechanisms underlying the synergy among health behaviours is needed. Feasibility interventions promoting reductions in both screen-time and unhealthy dietary behaviours reciprocally, while simultaneously focusing on changing parental behaviours, are warranted.

Dataset Information

Clustering of health-related behaviours within children aged 11-16: a systematic review.

Objective

Method

Results

Conclusion

Publications

Clustering of health-related behaviours within children aged 11-16: a systematic review.

Similar Datasets

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