Tobacco smoking as a social justice issue: Advances in research
Notice bibliographique
Résumé
Smoking has been found to be the strongest mediator of social inequality in all-cause mortality when a range of health behaviours are considered 1. A social gradient in smoking exists whereby smoking prevalence rates rise as one moves down the socioeconomic scale in developed countries including Australia, the USA and the UK, regardless of how social status is defined 2. Clearly, understanding why the social gradient exists and developing effective strategies for reducing smoking among socially disadvantaged groups is a major public health priority. This special issue begins with an article by Paul et al. 3 describing the opinions of the Australian and New Zealand tobacco control community on how tobacco control resources should be used. The results provide a backdrop of support, measured by consensus expert opinion, for increased resourcing of mass media campaigns and tobacco control research budgets towards addressing tobacco use in disadvantaged groups. In this issue, Passey and colleagues 4 and Stewart and colleagues 5 examine factors associated with health and smoking among Aboriginal and Torres Strait Islander clients of two types of health services: antenatal services 4 and Aboriginal Community Controlled Health Services 5. The surveys found high smoking rates (46% and 51% respectively) compared with the national adult smoking rates in Australia of 15% 6 and identify ways that smoking could be addressed within the health services. Other high-smoking-prevalence groups outlined in the special issue include prisoners 7, young people in custody 8 and people in residential drug and alcohol rehabilitation 9. Each paper highlights the promise of system-level changes to de-normalise smoking and reduce smoking rates in settings that are frequented by smokers 10. The complexity of the relative contributions of area-level and individual factors in understanding the social gradient in smoking and quitting is shown in research by Turrell and colleagues 11, and also that by Partos and colleagues 12. First, Turrell et al. 11 report the results of a multilevel longitudinal study of 6915 Brisbane residents surveyed in 2007 and 2009. The study found that smokers from socioeconomically disadvantaged areas are significantly less likely to quit smoking than those in more affluent areas, after adjusting for individual socioeconomic factors including household income, education and occupation. The study provides valuable insights into the potential beneficial effects that social, neighbourhood and community improvements could have on health. In contrast, Partos et al. 12, who analysed data from 3503 participants from the Australian arm of the International Tobacco Control Four-Country Survey, found no associations between area-level disadvantage and smoking cessation after controlling for a range of individual-level factors. These authors recommend further research into the individual factors such as links between smoking cessation and psychological distress. No doubt, smoking cessation needs to be addressed at both the area level and at an individual level. Only limited data are available on the impact of whole-of-population approaches such as mass media, pricing and smoke-free policies on the smoking behaviours of socially disadvantaged groups. Four papers in this special issue explore these approaches. In a comprehensive systematic and methodological review of the effectiveness of mass media campaigns on smoking cessation among selected socially disadvantaged groups, Guillaumier et al. 13 failed to find robust evidence. In an international study of smokers in Australia, the USA, the UK and Canada, Siahpush et al. 14 found that higher expenditure on cigarettes leads to smoking-induced deprivation, which can increase financial stress. The authors conclude that this ‘implies that the policy of increasing the price of tobacco might promote financial burden among smokers’ and suggest that prospective studies need to be conducted to better understand the effect of tobacco price policies on financial burden, particularly among lower socioeconomic groups. In a qualitative study, Hehir et al. 15 found promising results among patients in a forensic mental health hospital with a newly implemented smoke-free policy—although a majority of participants smoked when they entered the hospital, most indicated that the smoke-free environment had a positive effect on their health and that it encouraged their continued cessation at discharge. Taking population approaches one step further, Dalton 16 explores the end game scenario proposing a total ban of retail tobacco sales with an invited response from Lawn 17 who encourages caution. While it is important to implement and monitor the effect of whole-of-population tobacco control strategies with socially disadvantaged groups, there is also a need for more evidence regarding targeted approaches 18. A number of pilot studies of novel smoking cessation programs are reported in the special issue targeting prisoners 7, homeless people 19 and clients of social and community service organisations 20, 21. Each of them shows the feasibility and acceptability of targeted approaches and calls for further rigorous trials. Providing a unique perspective, Baker et al. 22 describe the possibilities for harm reduction strategies for smokers with mental health or substance abuse problems. The need for innovative approaches to reduce the high rate of smoking among socially disadvantaged groups is clear. Murray and McNeill 23 provide a UK perspective, outlining some of the lessons learnt so far from the newly established National Health Service Stop Smoking Services and other Department of Health pilot projects. While engagement with health professionals is a key component of UK efforts, in the landmark Tackling Tobacco Program in Australia is extending smoking cessation efforts to non-health settings such as community and social service organisations, which provide welfare support to highly disadvantaged individuals and families 24. This program recognises the need to build the capacity of social support organisations to address tobacco use with their disadvantaged clients. Action taken to reduce the health inequities associated with high rates of smoking among socially disadvantaged groups will result in health, economic and social benefits for the whole of society 25. One of the key policy recommendations made by the World Health Organization Commission on the Social Determinants of Health is ‘Focusing public health interventions such as smoking cessation programs and alcohol reduction on reducing the social gradient’ (p. 32) 26. This special issue provides cause for optimism by showcasing advances made in meeting that recommendation.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».