Are we overlooking alcohol use by younger children?

Kiguli, Juliet; Engebretsen, Ingunn Marie S.; Skylstad, Vilde; Kühl, Melf-Jakob; Nalugya, Joyce; Skar, Ane‐Marthe Solheim; Babirye, Juliet N.

doi:10.1136/bmjpo-2021-001242

Cited by 6 publications

(5 citation statements)

References 38 publications

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“…This review underlines early alcohol initiation among children with high SES, which is often influenced by parental drinking behavior ( 132 ). Thus, parental discretion in alcohol consumption around children is pivotal in preventing negative alcohol-related behavior ( 133 ). Therefore, this study suggests that parents should take care while drinking alcohol in front of their children to prevent them from developing bad alcohol-related behavior.…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic status and health behavior in children and adolescents: a systematic literature review

Gautam,

Dessie,

Rahman

et al. 2023

Front. Public Health

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Socioeconomic status affects individuals’ health behaviors and contributes to a complex relationship between health and development. Due to this complexity, the relationship between SES and health behaviors is not yet fully understood. This literature review, therefore, aims to assess the association between socioeconomic status and health behaviors in childhood and adolescence. Preferred Reporting for Systematic Review and Meta-Analysis protocol guidelines were used to conduct a systematic literature review. The electronic online databases EBSCO Host, PubMed, Web of Science, and Science Direct were utilized to systematically search published articles. The Joanna Briggs Institute’s critical appeal tool was used to assess the quality of included studies. Eligibility criteria such as study context, study participants, study setting, outcome measures, and key findings were used to identify relevant literature that measured the association between socioeconomic status and health behaviors. Out of 2,391 studies, only 46 met the final eligibility criteria and were assessed in this study. Our review found that children and adolescents with low socioeconomic status face an elevated risk of unhealthy behaviors (e.g., early initiation of smoking, high-energy-dense food, low physical activity, and involvement in drug abuse), in contrast to their counterparts. Conversely, children and adolescents from higher socioeconomic backgrounds exhibit a higher prevalence of health-promoting behaviors, such as increased consumption of fruit and vegetables, dairy products, regular breakfast, adherence to a nutritious diet, and engagement in an active lifestyle. The findings of this study underscore the necessity of implementing specific intervention measures aimed at providing assistance to families from disadvantaged socioeconomic backgrounds to mitigate the substantial disparities in health behavior outcomes in children and adolescents.

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Section: Discussionmentioning

confidence: 99%

Socioeconomic status and health behavior in children and adolescents: a systematic literature review

Gautam,

Dessie,

Rahman

et al. 2023

Front. Public Health

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“…While alcohol use among children younger than 10 occurs, is under‐researched and has a detrimental impact [ 23 ], we decided to focus this review on adolescence since this is a period characterised by a rapid increase of alcohol use. Papers that targeted adolescents, defined—in line with WHO guidance [ 24 ]—as individuals aged between 10 and 19 were included.…”

Section: Methodsmentioning

confidence: 99%

Measuring alcohol use among adolescents in Africa: A systematic scoping review of consumption, screening and assessment tools

Seekles

Briegal

Biggane

et al. 2023

Drug and Alcohol Review

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IssuesGlobally, adolescent drinking is a major public health concern. Alcohol measurements are influenced by local consumption practices, patterns and perceptions of alcohol‐related harm. This is the first review to examine what tools are used to measure alcohol consumption, or screen for or assess harmful use in African adolescents, and how these tools take into account the local context.ApproachA systematic scoping review was conducted in line with the Arksey and O'Malley framework. A search in MEDLINE, CINAHL, Global Health and the Cochrane Database covered the period of 2000–2020.Key FindingsThe search identified 121 papers across 25 African countries. A range of single‐ and multi‐item tools were identified. Very few adaptations of existing questions were specified, and this search identified no tools developed by local researchers that were fundamentally different from established tools often designed in the USA or Europe. Inconsistencies were found in the use of cut‐off scores; many studies used adult cut‐off scores.Implications and ConclusionThe possible impact of African drinking practices and culture on the accuracy of alcohol screening tools is currently unknown, but is also not taken into account by most research. This, in combination with a limited geographical distribution of alcohol‐related research across the continent and inconsistent use of age‐ and gender‐specific cut‐off scores, points towards probable inaccuracies in current data on adolescent alcohol use in Africa.

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“…Many adolescents resort to smoking or drinking as coping mechanisms for stress or emotional turmoil. [28,29] These initial coping behaviors may prompt adolescents to seek stronger stimuli for more intense experiences, potentially resulting in substance addiction or misuse. [30] Our study further emphasized the relationship between BMI and substance use, as another predictor of adolescent substance use.…”

Section: Feature Importancementioning

confidence: 99%

Machine learning-based prediction of substance use in adolescents: Derivation and validation in multinational datasets in South Korea, USA, and Norway (Preprint)

Lee,

Kim,

Kim

et al. 2024

Preprint

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BACKGROUND We aimed to address gaps in global understanding of cultural and social variations by employing a high-performance machine learning model to predict adolescent substance use across three national datasets. OBJECTIVE This study aims to develop a predictive model for adolescent substance use using multinational datasets and machine learning(ML). METHODS The study utilized the Korea Youth Risk Behavior Web-Based Survey(KYRBS) from South Korea(n=1,145,178) to train ML models. For external validation, we employed the Youth Risk Behavior Survey(YRBS) from the USA(n=1,690,108) and Norwegian nationwide Ungdata surveys(Ungdata) from Norway(n=793,879). After developing diverse tree-based models, we further evaluated feature importance. RESULTS The study utilized nationwide adolescent datasets for ML model development and validation, analyzing data from 1,145,178 KYRBS adolescents, 54,709 YRBS Asian subset participants, and 720,812 from Ungdata. The random forest model was the top performer on the KYRBS, achieving an AUROC of 80.8%(95% CI, 80.7-80.8) with sensitivity of 72.9%(72.8-73.0), specificity of 72.9%(72.9-73.0), accuracy of 72.9%(72.8-73.0), and balanced accuracy of 72.9%(72.8-73.0). The model's AUROC scores were 73.2% for YRBS and 75.7% for Ungdata in external validation. The top features for predicting substance use were smoking status, body mass index (BMI), and alcoholic consumption. CONCLUSIONS With multinational datasets from South Korea, USA, and Norway, the findings of this study underscore the potential efficacy of ML models in predicting adolescent substance use with smoking status, body mass index, and alcoholic consumption identified as key predictors. The random forest model exhibited notable performance in this prediction. These findings could be a basis for future studies exploring more comprehensive factors influencing adolescent substance use or developing intervention strategies based on these predictors.

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Are we overlooking alcohol use by younger children?

Cited by 6 publications

References 38 publications

Socioeconomic status and health behavior in children and adolescents: a systematic literature review

Socioeconomic status and health behavior in children and adolescents: a systematic literature review

Measuring alcohol use among adolescents in Africa: A systematic scoping review of consumption, screening and assessment tools

Machine learning-based prediction of substance use in adolescents: Derivation and validation in multinational datasets in South Korea, USA, and Norway (Preprint)

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