Clustering of adolescent health concerns: A latent class analysis of school students in <scp>N</scp>ew <scp>Z</scp>ealand

Noel, Hannah; Denny, Simon; Farrant, Bridget; Rossen, Fiona; Teevale, Tasileta; Clark, Terryann; Fleming, Theresa; Bullen, Pat; Sheridan, Janie; Fortune, Sarah

doi:10.1111/jpc.12397

Cited by 18 publications

(33 citation statements)

References 29 publications

(35 reference statements)

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“…This indicates that clustering analyses of adolescents’ health behaviour should include variables that describe alcohol use and smoking, as was previously suggested by Laxer et al . The results of this study indicate that smoking and alcohol use cluster together, a phenomenon which has also been recognised in other studies . This finding is concerning, as it suggests that adolescents who engage in these activities are also engaging in other risk behaviours as well .…”

Section: Discussionsupporting

confidence: 83%

“…Excessive screen time has been linked with higher BMI , emotional problems and psychological distress , low life satisfaction and less physical activity . Risk behaviours such as smoking and alcohol use have been shown to cluster together and, as such, pose a real threat to adolescents’ health and well‐being . Smoking is associated with suicidal behaviour, direct self‐injurious behaviour, anxiety, conduct problems and hyperactivity .…”

Section: Introductionmentioning

confidence: 99%

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Clusters of health behaviours and their relation to body mass index among adolescents in Northern Finland

Marttila‐Tornio

Ruotsalainen

Miettunen

et al. 2019

Scandinavian Caring Sciences

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Aims To identify clusters of health behaviours among Finnish adolescents and examine whether these clusters are associated with body mass index (BMI). Methods The data, drawn from the prospective population‐based Northern Finland Birth Cohort 1986, comprised a total of 7182 adolescents who replied to a follow‐up postal questionnaire at the age 15 to 16. The adolescents were asked about multiple health behaviours, such as physical activity, screen time, cigarette smoking, alcohol use and diet. Adolescents who answered the questions concerning all of these variables were included in the study, yielding a final sample of 4305 subjects. K‐means cluster analysis was performed to identify group of adolescents with similar health behaviours. Chi‐squared tests were performed to analyse the association between the clusters and BMI. Results Two clusters – Healthy Lifestyle and Unhealthy Lifestyle – were identified for both genders. The values of all the studied variables differed significantly between the clusters identified for both boys and girls. No significant relationship between the identified clusters and BMI was found for either boys or girls. Conclusions It is important to consider multiple lifestyle‐related behaviours and trying to identify groups that present probability for developing lifestyle diseases.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Clusters of health behaviours and their relation to body mass index among adolescents in Northern Finland

Marttila‐Tornio

Ruotsalainen

Miettunen

et al. 2019

Scandinavian Caring Sciences

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“…Previous populationbased studies have not reported such marked social and ethnic gradients with regards to the consumption of energy drinks for adolescents. 21 Data from USA estimated that one-quarter of 12th grade students consumed alcohol mixed with energy drinks in the past year. 7 It is likely that the social and ethnic gradient in energy drink consumption for New Zealand young people reflects the marketing and availability of energy drinks.…”

Section: Discussionmentioning

confidence: 99%

“…20 It is also possible that alcohol mixed with energy drinks may explain some of these findings, particularly as energy drinks are marketed as alcohol mixers, and alcohol use clusters with other health risk behaviours among adolescents. 21 Data from USA estimated that one-quarter of 12th grade students consumed alcohol mixed with energy drinks in the past year. 22 Consuming alcohol mixed with energy drinks has been previously associated with adolescent smoking, 23 adolescent unsafe driving 22 and sexual victimisation among male college students.…”

Section: Discussionmentioning

confidence: 99%

Energy drink consumption among New Zealand adolescents: Associations with mental health, health risk behaviours and body size

Utter

Denny

Teevale

et al. 2017

J Paediatrics Child Health

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“…The 'risky' group (10.8% of the sample) with higher rates of risky behaviours, but low rates of emotional concerns. The 'multiple' group (3.5% of the sample), reported high levels of both risky behaviours and emotional problems [10]. A similar LCA investigating clustering of MRB among Australians aged~18 years [11], found three classes: moderate risk (52%): moderately likely to binge drink and not eat enough fruit, high probability of insufficient vegetable intake; inactive, nonsmokers (24%): high probabilities of not meeting guidelines for physical activity, sitting time and fruit/vegetable consumption, very low probability of smoking; and smokers and binge drinkers (24%): high rates of smoking and binge drinking, poor fruit/vegetable intake.…”

Section: Introductionmentioning

confidence: 99%

Adolescent multiple risk behaviours cluster by number of risks rather than distinct risk profiles in the ALSPAC cohort

et al. 2020

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Background: Experimentation with new behaviours during adolescence is normal. However, engagement in two or more risk behaviours, termed multiple risk behaviours is associated with socioeconomic disadvantage and poor health and social outcomes. Evidence of how adolescents cluster based on their risk behaviours is mixed. Methods: Latent Class Analysis was used to study patterns of engagement in 10 self-reported risk behaviours (including substance use, self-harm and sexual health) from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort at ages 15-16 years. Data was available for 6556 adolescents. Associations between risk profile and sex were explored. Results: A 3-class model for both females and males was deemed to have acceptable fit. Whilst we found evidence of a sex difference in the risk behaviours reported within each class, the sex-specific results were very similar in many respects. For instance, the prevalence of membership of the high-risk class was 8.5% for males and 8.7% for females and both groups had an average of 5.9 behaviours. However, the classes were both statistically dubious, with class separation (entropy) being poor as well as conceptually problematic, because the resulting classes did not provide distinct profiles and varied only by quantity of risk-behaviours. Conclusion: Clusters of adolescents were not characterised by distinct risk behaviour profiles, and provide no additional insight for intervention strategies. Given this is a more complicated, software-specific method, we conclude that an equally effective, but more readily replicable approach is to use a count of the number of risk behaviours.

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Clustering of adolescent health concerns: A latent class analysis of school students in New Zealand

Cited by 18 publications

References 29 publications

Clusters of health behaviours and their relation to body mass index among adolescents in Northern Finland

Clusters of health behaviours and their relation to body mass index among adolescents in Northern Finland

Energy drink consumption among New Zealand adolescents: Associations with mental health, health risk behaviours and body size

Adolescent multiple risk behaviours cluster by number of risks rather than distinct risk profiles in the ALSPAC cohort

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