Dataset Information

Socioeconomic Inequalities in Smoking and Smoking Cessation Due to a Smoking Ban: General Population-Based Cross-Sectional Study in Luxembourg.

ABSTRACT: This study aimed to measure changes in socioeconomic inequalities in smoking and smoking cessation due to the 2006 smoking ban in Luxembourg. Data were derived from the PSELL3/EU-SILC (Panel Socio-Economique Liewen Zu Letzebuerg/European Union--Statistic on Income and Living Conditions) survey, which was a representative survey of the general population aged ?16 years conducted in Luxembourg in 2005, 2007, and 2008. Smoking prevalence and smoking cessation due to the 2006 smoking ban were used as the main smoking outcomes. Two inequality measures were calculated to assess the magnitude and temporal trends of socioeconomic inequalities in smoking: the prevalence ratio and the disparity index. Smoking cessation due to the smoking ban was considered as a positive outcome. Three multiple logistic regression models were used to assess social inequalities in smoking cessation due to the 2006 smoking ban. Education level, income, and employment status served as proxies for socioeconomic status. The prevalence of smoking decreased by 22.5% between 2005 and 2008 (from 23.1% in 2005 to 17.9% in 2008), but socioeconomic inequalities in smoking persisted. Smoking prevalence decreased by 24.2% and 20.2% in men and women, respectively; this difference was not statistically significant. Smoking cessation in daily smokers due to the 2006 smoking ban was associated with education level, employment status, and income, with higher percentages of quitters among those with a lower socioeconomic status. The decrease in smoking prevalence after the 2006 law was also associated with a reduction in socioeconomic inequalities, including differences in education level, income, and employment status. Although the smoking ban contributed to a reduction of such inequalities, they still persist, indicating the need for a more targeted approach of smoke-free policies directed toward lower socioeconomic groups.

SUBMITTER: Tchicaya A

PROVIDER: S-EPMC4839754 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Socioeconomic Inequalities in Smoking and Smoking Cessation Due to a Smoking Ban: General Population-Based Cross-Sectional Study in Luxembourg.

Tchicaya Anastase A Lorentz Nathalie N Demarest Stefaan S

PloS one 20160421 4

This study aimed to measure changes in socioeconomic inequalities in smoking and smoking cessation due to the 2006 smoking ban in Luxembourg. Data were derived from the PSELL3/EU-SILC (Panel Socio-Economique Liewen Zu Letzebuerg/European Union--Statistic on Income and Living Conditions) survey, which was a representative survey of the general population aged ≥16 years conducted in Luxembourg in 2005, 2007, and 2008. Smoking prevalence and smoking cessation due to the 2006 smoking ban were used a ...[more]

PMID: 27100293

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Project description:ObjectiveThe contribution of smoking to socioeconomic inequalities in health is increasing worldwide, including in Brazil. Youth smoking may play an important role in the increasing social inequalities related to smoking. This study investigates social determinants of smoking among 15-year-old to 19-year-old individuals.DesignCross-sectional study.SettingThe study uses data of 3536 participants aged 15-19 years of age of the Global Adult Tobacco Survey (GATS) and the National Household Sample Survey (Pesquisa Nacional por Amostragem de Domicilio, PNAD) obtained from household interviews. Smoking was defined as currently smoking tobacco products, regardless of frequency. Household socioeconomic indicators included per capita income, the educational level and sex of the head of the household, the presence of smoking restrictions and the number of smokers (excluding adolescents). Adolescent social factors included years of delaying school and social status (full-time student, working, and neither working nor studying). The hierarchical logistic regression analysis considered the effect of the complex sampling design.ResultsFrom 3536 participants, 6.2% were smokers (95% CI 5.4 to 7.1). More men than women had the habit of smoking (7.2%; 5.9 to 8.6 vs 3.6%; 2.7 to 4.6). The likelihood of smoking was significantly greater for men and older teens. There was an upward trend in the OR of smoking according to the number of smokers in the house. Adolescents living in households with no smoking restrictions had a greater likelihood of being smokers. OR of smoking rose as the number of years of delaying school increased, being about three times greater among adolescents who were working and five times greater among those who were neither studying nor working.ConclusionsResults demonstrate that socioeconomic inequality in smoking is established at younger ages and that school delay as well as school abandonment may contribute to increased smoking-related inequalities. Smoking restrictions at home were protective against adolescents becoming smokers. Living with other smokers was a strong predictor of adolescents becoming smokers.

Project description:BackgroundLow back pain is an important public health issue across the world. However, it is unclear whether socioeconomic status (SES) is associated with low back pain. This study determines an association between SES and low back pain among older people.MethodsWe used cross-sectional data derived from the year 2013 across 30 Japanese municipalities. The survey was conducted between October 2013 to December 2013. Functionally independent community-dwelling older adults aged 65 and above (n = 26,037) were eligible for the study. Multilevel Poisson regression analysis with a robust variance estimator was used to examine the association between SES and low back pain. Self-reported low back pain in the past year was used as a dependent variable. Educational attainment, past occupation, equivalized household income, wealth, and subjective economic situation represented SES and were separately analyzed as independent variables, adjusted for covariates including age and sex.ResultsThe prevalence of low back pain was 63.4%. Overall, lower SES were more likely to suffer from low back pain compared with that for the highest. First, as for the educational attainment, the prevalence ratio (PR) (95% credible interval (CI)) for the lowest level was 1.07 (1.02-1.12). Second, as for the past occupation, the PR (95% CI) for the blue-collared workers compared with professionals was 1.06 (1.01-1.11). Third, as for the equalized household income, the PRs (95% CI) for lower middle and the lowest income levels were 1.08 (1.02-1.13) and 1.16 (1.10-1.23), respectively. Fourth, as for the wealth, the PRs (95% CI) for lower middle and the lowest wealth levels were 1.11 (1.04-1.19) and 1.18 (1.11-1.27), respectively. Fifth, as for the subjective economic situation, the PRs (95% CI) for lower middle and the lowest financial conditions were 1.18 (1.10-1.26) and 1.32 (1.22-1.44), respectively.ConclusionsSignificant socioeconomic inequalities were observed in low back pain among older individuals in Japan. Policymakers and clinicians must understand the nature of these inequalities.

Project description:BACKGROUND: Consistent evidence has demonstrated that smoking ban policies save lives, but impacts on health inequalities are uncertain as few studies have assessed post-ban effects by socioeconomic status (SES) and findings have been inconsistent. The aim of this study was to assess the effects of the national Irish smoking ban on ischemic heart disease (IHD), stroke, and chronic obstructive pulmonary disease (COPD) mortality by discrete and composite SES indicators to determine impacts on inequalities. METHODS: Census data were used to assign frequencies of structural and material SES indicators to 34 local authorities across Ireland with a 2000-2010 study period. Discrete indicators were jointly analysed through principal component analysis to generate a composite index, with sensitivity analyses conducted by varying the included indicators. Poisson regression with interrupted time-series analysis was conducted to examine monthly age and gender-standardised mortality rates in the Irish population, ages ?35 years, stratified by tertiles of SES indicators. All models were adjusted for time trend, season, influenza, and smoking prevalence. RESULTS: Post-ban mortality reductions by structural SES indicators were concentrated in the most deprived tertile for all causes of death, while reductions by material SES indicators were more equitable across SES tertiles. The composite indices mirrored the results of the discrete indicators, demonstrating that post-ban mortality decreases were either greater or similar in the most deprived when compared to the least deprived for all causes of death. CONCLUSIONS: Overall findings indicated that the national Irish smoking ban reduced inequalities in smoking-related mortality. Due to the higher rates of smoking-related mortality in the most deprived group, even equitable reductions across SES tertiles resulted in decreases in inequalities. The choice of SES indicator was influential in the measurement of effects, underscoring that a differentiated analytical approach aided in understanding the complexities in which structural and material factors influence mortality.

Project description:Background and aimsAdvice from a general practitioner (GP) can encourage smokers to quit. This study aimed to estimate the prevalence and correlates of receipt of GP advice on smoking, what type of advice and support was offered and characteristics and quitting activity associated with different types of advice.Design/settingData were collected between 2016 and 2019 in a series of monthly cross-sectional surveys of representative samples of the adult population in England.ParticipantsA total of 11 588 past-year smokers.MeasurementsParticipants reported whether they had received advice or offer of support for smoking cessation from their GP in the last year. Socio-demographic and behavioural characteristics and past-year quit attempts and cessation were also recorded.FindingsOne in two [47.2%, 95% confidence interval (CI) = 46.1-48.3%] past-year smokers who reported visiting their GP in the last year recalled receiving advice on smoking, and one in three (30.1%, 95% CI = 29.1-31.1%) reported being offered cessation support. The most common form of support offered was stop smoking services (16.5%, 95% CI = 15.7-17.3%) followed by prescription medication (8.1%, 95% CI = 7.5-8.7%); 3.7% (95% CI = 3.3-4.1%) reported having been recommended to use e-cigarettes. Smokers who were older, non-white, more addicted, and smoked five or more cigarettes/day had consistently higher odds of receiving advice or support. There were some differences by region, housing tenure, presence of children in the home and high-risk drinking in the types of advice/support received. There were no significant differences by sex, occupational social grade, disability, type of cigarettes smoked, or survey year. Advice with any offer of support was associated with higher odds of attempting to quit than advice alone [adjusted odds ratio (ORadj ) = 1.52, 95% CI = 1.30-1.76]. Advice alone was associated with higher odds of quit attempts than no advice in smokers with higher (ORadj = 1.34, 95% CI = 1.10-1.64) but not lower occupational social grade (ORadj = 0.90, 95% CI = 0.75-1.08).ConclusionsIn England, a minority of smokers receive support from their GP to stop smoking. Those who do are more likely to be older, non-white and more addicted to cigarettes. Advice plus offer of support appears to be associated with increased odds of making a quit attempt, while advice without offer of support appears only to be associated with increased odds of making a quit attempt in higher occupational social grade smokers.

Dataset Information

Socioeconomic Inequalities in Smoking and Smoking Cessation Due to a Smoking Ban: General Population-Based Cross-Sectional Study in Luxembourg.

Publications

Socioeconomic Inequalities in Smoking and Smoking Cessation Due to a Smoking Ban: General Population-Based Cross-Sectional Study in Luxembourg.

Similar Datasets

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