Evidence map›Paper›PMID 39939948›Full record

ArticleBMC public health2025

Sociodemographic characteristics on behavioural risk factors of noncommunicable diseases in adolescents in Luxembourg.

Felipe G Mendes, Joana Lopes Ferreira, Carolina Catunda

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Felipe G MendesDepartment of Social Science, University of Luxembourg, Esch-sur-Alzette, Luxembourg. felipe.goedertmendes@uni.lu.
Joana Lopes FerreiraDepartment of Social Science, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Carolina CatundaDepartment of Social Science, University of Luxembourg, Esch-sur-Alzette, Luxembourg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-communicable diseases (NCDs) accounted for 89% of deaths in Luxembourg in 2019, aligning with Europe's figures but exceeding the global average of 74%. Behaviours play a critical role in NCD management, with unhealthy lifestyles-like poor diets, physical inactivity, tobacco use, and alcohol consumption-posing significant risks, especially when combined. The present study aims to explore sociodemographic characteristics of adolescents presenting behavioural risks for NCDs in Luxembourg.

methodsA representative sample of 8117 adolescents (11-to-18-years-old) took part in the 2022 Health Behaviour in School-aged Children (HBSC) Luxembourg survey. We measured physical inactivity, daily sugar consumption, cigarette use and alcohol consumption, and their combination (1, 2 or 3 ≥ risks). The sociodemographic characteristics investigated were sex, age, migration background, family structure and perceived wealth. Binomial logistic regression crude and adjusted were performed with sociodemographic characteristics for each risk behaviour. In addition, multinomial logistic regression crude and adjusted were used to analyse the association between the combination of risk behaviours and the sociodemographic information of the adolescents in Luxembourg.

resultsGirls had higher odds of physical inactivity (OR = 2.06) than boys, and older age groups exhibited elevated odds of physical inactivity (OR = 2.99), cigarette smoking (OR = 25.00), and alcohol consumption (OR = 35.56). Migration background emerged as a protective factor against alcohol consumption (parents' migration OR = 0.60; self-immigrated OR = 0.45) but a risk factor for physical inactivity (parents' migration OR = 1.50; self-immigrated OR = 1.72). Adolescents who did not live with both parents were more likely to be physically inactive (OR = 1.37), consume sugar daily (OR = 1.33), smoke cigarettes (OR = 1.26) and consume alcohol (OR = 1.80). Adolescents that reported their families were not well off had higher odds to be physically inactive (OR = 2.12) and to consume sugar daily (OR = 1.39). The simultaneity of risk behaviours reveals a worrying trend of increasing risk with age, highlighting the need for preventive interventions throughout adolescence. Furthermore, the results in relation to family structure and perceived wealth highlights the complexity and interrelationship of these factors in adolescent behavioural health. 

conclusionsThe study provides guidance to create more effective interventions aiming to promote healthy behaviours in adolescents.

Indexed as

Adolescent BehaviorHealth BehaviorNoncommunicable DiseasesAdolescentAlcohol DrinkingChildFemaleHumansLuxembourgMaleRisk FactorsSedentary BehaviorSociodemographic FactorsAddictive behavioursEating behavioursHBSCLuxembourgPhysical inactivity

Identifiers

PMID39939948
PMCPMC11823148

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.