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Enregistrement W4281752507 · doi:10.1016/j.lanwpc.2022.100489

The burden of nicotine-dependent smokers in China: The role of primary healthcare providers

2022· article· en· W4281752507 sur OpenAlexaboutno aff
Chandrashekhar T Sreeramareddy

Notice bibliographique

RevueThe Lancet Regional Health - Western Pacific · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueSmoking Behavior and Cessation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésChinaMedicineHealth literacyPopulationLiteracyGovernment (linguistics)Survey data collectionEnvironmental healthTobacco harm reductionHealth careDemographyTobacco useEconomic growthPolitical scienceSociology

Résumé

récupéré en direct d'OpenAlex

In their article in The Lancet Regional Health – Western Pacific, Liu, and colleagues1Liu Z. Li Y.H. Cui Z.Y. et al.Prevalence of tobacco dependence and associated factors in China: Findings from nationwide China Health Literacy Survey during 2018-19.Lancet Reg Health West Pac. 2022; 24: 100464Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar have reported the prevalence, distribution, and burden of current cigarette smoking and the burden of tobacco-dependent smokers among Chinese adults aged 20–69 years using a nationally representative China Health Literacy survey data (2018/19). The study emphasizes the importance of assessing tobacco dependence in population-based surveys. The data from 84,839 participants aged 20–69 years shows that nearly one in four were currently smoking and nearly half of them were tobacco-dependent. The rate of prevalence and dependence is a challenge for policymakers and clinicians to achieve the targeted 20% smoking prevalence in 2030 set by the Chinese government.2Zeng Z. Liu J. The Central Committee of the Communist Party of China and the State Council issued the outline of healthy China 2030.The communique of the State Council of the People's Republic of China. 2016; 32: 5-20Google Scholar Data from the China Health Literacy survey are also not surprising. High levels of tobacco dependence as shown by this study are supported by the sequential Global Adult Tobacco Survey (GATS) data.3Sreeramareddy C.T. Aye S.N. Changes in adult smoking behaviors in ten global adult tobacco survey (GATS) countries during 2008–2018 - a test of ‘hardening’ hypothesis.BMC Public Health. 2021; 21: 1209https://doi.org/10.1186/s12889-021-11201-0Crossref PubMed Scopus (5) Google Scholar About half of the current smokers had not made any quit attempts in the past 12 months and a majority (>80%) of them had no intention to quit during the next 12 months. Smoking prevalence and the mean number of cigarettes smoked per day had also not improved between two rounds of GATS in 2010 and 2018. In China about a third of all current smokers were hardcore smokers. Low quit ratios (the ratio of former smokers to ever smokers) were seen in both years. GATS shows that less than 5% of all current smokers had tried any recommended quit methods.3 The WHO's Framework Convention on Tobacco Control recommends cessation interventions be provided to reduce the dependence.4World Health OrganizationWHO Framework Convention on Tobacco Control. World Health Organization, 2003Google Scholar However, the findings of a national survey in all 31 provinces of China show that 3/4th of the cessation clinics were in the hospitals mainly in respiratory departments. Over 90% of the facilities provided counseling with just 40% of them providing medication.5Lin H. Xiao D. Liu Z. Shi Q. Hajek P. Wang C. National survey of smoking cessation provision in China.Tob Induc Dis. 2019; 17: 25https://doi.org/10.18332/tid/104726Crossref PubMed Scopus (13) Google Scholar However, behavioral counseling and telephone-based quitlines are convenient, population-based, cost-effective cessation strategies and more effective when combined.6Choi H.K. Ataucuri-Vargas J. Lin C. Singrey A. The current state of tobacco cessation treatment.Clevel Clin J Med. 2021; 88: 393-404Crossref PubMed Google Scholar There is a lack of data if these smoking cessation services are provided in China. Given the high level of tobacco dependence, more efforts are to be made to provide medications such as nicotine replacement therapy, varenicline, and buprenorphine at the cessation clinics and expand the cessation clinics in primary care settings to improve accessibility to smokers closer to their community.7Papadakis S. Cole A.G. Reid R.D. et al.Increasing rates of tobacco treatment delivery in primary care practice: evaluation of the Ottawa model for smoking cessation.Ann Family Med. 2016; 14: 235-243Crossref PubMed Scopus (29) Google Scholar Results that tobacco dependence was strongly associated with smoking intensity (pack-years) and the score of the Fagerstrom Test for nicotine addiction show a discouraging landscape for tobacco control in China. The current pool of smokers is very dynamic as it is influenced by those who quit or die and the addition of new smokers who join the current pool of smokers. The authors highlighted that about 50% of the current smokers were tobacco-dependent translated to a projected 183.5 million tobacco-dependent population, most of them being men.1Liu Z. Li Y.H. Cui Z.Y. et al.Prevalence of tobacco dependence and associated factors in China: Findings from nationwide China Health Literacy Survey during 2018-19.Lancet Reg Health West Pac. 2022; 24: 100464Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar These staggering numbers have enormous implications for future tobacco control strategies in China. The quantum of the population that needs treatment for dependence to reduce smoking prevalence to less than 20% is a very challenging task. Nicotine addiction is a chronic compulsive brain disorder with repeated attempts to quit and high relapse rates, while cessation is a complex decision-making process that involves a smoker's personal choices of seeking or not seeking assistance. The availability of cessation services, motivation to quit, self-efficacy, and precipitating conditions also determines the cessation decision.8Leone F.T. Baldassarri S.R. Galiatsatos P. Schnoll R. Nicotine dependence: future opportunities and emerging clinical challenges.Ann Am Thorac Soc. 2018; 15: 1127-1130Crossref PubMed Scopus (6) Google Scholar Primary healthcare providers (HCP) at primary care clinics in China have an enormous role to play, as evidence shows healthcare providers’ interventions such as brief advice are effective in promoting smoking cessation.9Stead L.F. Buitrago D. Preciado N. Sanchez G. Hartmann-Boyce J. Lancaster T. Physician advice for smoking cessation.Cochrane Database Syst Rev. 2013; Crossref Scopus (490) Google Scholar The Heaviness of Smoking Index is known to be a quick and effective means to assess nicotine dependence. HCPs should assess dependence and offer quick advice in every clinical encounter. Both behavioral and medical interventions are known to complement each other in smoking cessation and should be adopted by HCP. Text messaging and app-based interventions and hypnotherapy should also be explored. The role of electronic cigarettes as a quit-smoking tool is still debatable.6Choi H.K. Ataucuri-Vargas J. Lin C. Singrey A. The current state of tobacco cessation treatment.Clevel Clin J Med. 2021; 88: 393-404Crossref PubMed Google Scholar However, it is still a good alternative tool particularly for highly dependent perhaps hardened Chinese smokers. Evidence shows that nicotine-containing e-cigarette improves quit rates as compared to nicotine replacement therapy and electronic cigarettes alone have seldom been shown to reduce the population prevalence of smoking.10Hartmann-Boyce J. McRobbie H. Butler A.R. et al.Electronic cigarettes for smoking cessation.Cochrane Database Syst Rev. 2021; Google Scholar In conclusion, both demand and supply-side issues are to be addressed to lower the burden of dependence on smokers in China. Evidence-based cessation methods both behavioral and pharmacological should be provided and expanded peripherally to the primary care level. To improve the demand for cessation, widespread education about the harms of smoking and population-level measure tobacco control measures should complement cessation services. Healthcare providers in China need to play a greater role by integrating smoking cessation interventions into their clinical practice. The author has not any conflict of interest to declare. The author thanks Dr Anusha Manoharan, Botanic Health Clinic, Selangor, Malaysia for providing key citations and feedback on the initial draft of the manuscript. No funding was received for this work.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,158
Score d'incertitude au seuil0,314

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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.

Tête enseignante Opus0,046
Tête enseignante GPT0,316
Écart entre enseignants0,270 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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