Researching health inequalities in adolescents: The development of the Health Behaviour in School-Aged Children (HBSC) Family Affluence Scale

Currie, Candace; Molcho, Michal; Boyce, William; Holstein, Bjørn Evald; Torsheim, Torbjørn; Richter, Michael

doi:10.1016/j.socscimed.2007.11.024

Cited by 1,356 publications

(1,209 citation statements)

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“…Family SES was measured using three variables in order to capture different dimensions of SES; namely: (i) Family Affluence Scale (FAS) 18, (ii) Subjective Social Status (SSS) 19 and (iii) paternal and maternal education level.…”

Section: Methodsmentioning

confidence: 99%

“…The FAS represents the material wealth of the family, and ranges between 0 (lowest) and 7 (highest) 18. It was designed to reflect material living conditions, and its link with adolescents' health and health behaviour, including with smoking, was observed 18, 20.…”

Section: Methodsmentioning

confidence: 99%

“…It was designed to reflect material living conditions, and its link with adolescents' health and health behaviour, including with smoking, was observed 18, 20. The SSS was conceived to capture the subjective internalized perception of social status 19, and was shown to be linked strongly to several health measures among adolescents 21, including smoking 22.…”

Section: Methodsmentioning

confidence: 99%

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The association between personal income and smoking among adolescents: a study in six European cities

Perelman¹,

Alves²,

Pfoertner

et al. 2017

Addiction

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AimsThis study investigates the link between personal income and smoking among adolescents, and aims to answer the following questions: (i) to what extent is personal income related to smoking, independent of family socio‐economic status (SES) and (ii) does the association between personal income and smoking apply to different subpopulations?DesignCross‐sectional study.SettingSix cities from European countries (Amersfoort, the Netherlands; Coimbra, Portugal; Hannover, Germany; Latina, Italy; Namur, Belgium; Tampere, Finland) in 2013.ParticipantsA school‐based sample of 10 794 adolescents aged 14–17 years.MeasurementsWe modelled smoking experimentation, weekly smoking, daily smoking and (among daily smokers) smoking intensity as function of personal income, adjusting for age, sex, family SES, parental smoking and country. We tested interactions between personal income and covariates. Stratification analyses were performed for the variables for which interactions were significant.FindingsAdolescents in the highest income quintile were more likely to be smoking experimenters [odds ratio (OR) = 1.87; P < 0.01], weekly smokers (OR = 3.51; P < 0.01) and daily smokers (OR = 4.55; P < 0.01) than those in the lowest quintile. They also consumed more cigarettes per month (β = 0.79; P < 0.01). Adjusting for family SES did not modify the significance of relationships, and increased the magnitude of the association for daily smoking. None of the interactions between covariates and personal income was significant for smoking measures. For the intensity of smoking, the interaction was significant for SES. The stratified analysis showed a non‐significant association between smoking intensity and personal income among the oldest adolescents and those with the lowest SES background, while significant among younger and higher SES backgrounds.ConclusionIn the Netherlands, Portugal, Germany, Italy, Belgium and Finland, adolescents' personal income is related positively to smoking behaviours independent of family socio‐economic status (SES). However, among low socio‐economic status adolescent daily smokers, the association between the intensity of smoking and personal income is weaker.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

The association between personal income and smoking among adolescents: a study in six European cities

Perelman¹,

Alves²,

Pfoertner

et al. 2017

Addiction

Self Cite

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show abstract

“…We assessed intake of bread, potatoes (fried and not fried), rice, pasta, grains, vegetables, fruits, juices, dairy products, legumes, meat, fish, eggs, nuts, soft drinks, chips, milk-based desserts, pastries, sweets and cold meat. The questionnaire included information about age, socioeconomic status (Family Affluence Scale-FAS [18]), weight (kg) and height (cm) measured objectively by staff from the Public Health Agency of Barcelona. The POIBA-HDWE FFQ can be accessed at: http://www.aspb.cat/poiba/ …”

Section: Methodsmentioning

confidence: 99%

“…FAS is an individual socioeconomic index that reflects the affluence of a family by asking about the number of holidays per year, the number of computers and cars at home and the availability of a private bedroom. Subjects are classified in categories of low, middle and high socioeconomic status [18]. …”

Section: Methodsmentioning

confidence: 99%

Validation of ‘POIBA-How do we eat?’ questionnaire in 9-10 years old schoolchildren

Ariza

Arechavala

Valmayor³

et al. 2017

Food & Nutrition Research

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Background: It is difficult to obtain good food reports with Food Frequency Questionnaires (FFQ) among children. In addition, validated questionnaires are scarce. Objective: The aim of this study was to validate the ‘POIBA-How do we eat?’ (POIBA-HDWE) FFQ and whether it could be administered to children under 10 years of age. Design: We validated the FFQ POIBA-HDWE as part of the Childhood Obesity Prevention Program (POIBA project) in Barcelona. Forty-two out of 63 primary school students (9–10 years old) answered three questionnaires: FFQ POBA-HDWE; another questionnaire, ‘POIBA-How do our children eat?’ (POIBA-HDOCE), which was administered to the children’s parents; and the 24-h recall computer program ‘Young Adolescents’ Nutrition Assessment on Computer’ (YANA-C), which was used on three different days as a gold standard. We tested for correlations using the Spearman test for non-parametric variables. Results: We found low compliance with food recommendations (<50%). The POIBA-HDWE and POIBA-HDOCE questionnaires showed a moderate correlation for soft drinks (r = 0.49; p < 0.01), nuts (r = 0.59; p < 0.01), dairy products (r = 0.41; p < 0.01) and juices (r = 0.49; p < 0.01). There were moderate correlations between POIBA-HDWE and YANA-C for fried potatoes (r = 0.42; p = 0.01), dairy products (r = 0.53; p < 0.01), juices (r = 0.41; p < 0.01), and grains(r = 0.50; p < 0.01). Food frequency questions showed a homogeneity of 0.69, and a sensitivity of over 60% for all food items except chips (37.5%) and sweets (51.7%). Conclusions: The POIBA-HDWE FFQ showed moderate correlations with the gold standard, high sensitivity for most food types and acceptable internal consistency. It is an easy and affordable tool for recording food frequency in children under 10 years old.

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Associations of Television Viewing With Eating Behaviors in the 2009 Health Behaviour in School-aged Children Study

Lipsky

Iannotti²

2012

Arch Pediatr Adolesc Med

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Participants: A total of 12 642 students in grades 5 to 10 (mean [SD] age, 13.4[0.09] years; 86.5% participation). Main Exposures: Television viewing (hours per day) and snacking while watching television (days per week).Main Outcome Measures: Eating (Ն1 instance per day) fruit, vegetables, sweets, and sugary soft drinks; eating at a fast food restaurant (Ն1 d/wk); and skipping breakfast (Ն1 d/wk). Conclusion:Television viewing was associated with a cluster of unhealthy eating behaviors in US adolescents after adjustment for socioeconomic and behavioral covariates.

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Researching health inequalities in adolescents: The development of the Health Behaviour in School-Aged Children (HBSC) Family Affluence Scale

Cited by 1,356 publications

References 38 publications

The association between personal income and smoking among adolescents: a study in six European cities

The association between personal income and smoking among adolescents: a study in six European cities

Validation of ‘POIBA-How do we eat?’ questionnaire in 9-10 years old schoolchildren

Associations of Television Viewing With Eating Behaviors in the 2009 Health Behaviour in School-aged Children Study

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