Measuring age-specific variations in income-related inequalities in smoking behavior in Germany

Siegel, Martin

doi:10.1080/21642850.2014.891946

Cited by 9 publications

(4 citation statements)

References 34 publications

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“…Current smoking rate increased with age and was highest in the 30s age group, and then decreased with age. 21 22 On the other hand, the rate of smoking cessation increased with age. In addition to age, various other factors have been reported to be associated with current smoking.…”

Section: Discussionmentioning

confidence: 99%

Heavy smoking rate trends and related factors in Korean occupational groups: analysis of KNHANES 2007–2012 data

et al. 2015

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ObjectivesThe present study was designed to investigate the smoking and heavy smoking trends and identify possible related factors among Korean male workers from 2007 to 2012 by occupational groups.MethodsThe data were derived from the fourth (2007–2009) and fifth (2010–2012) waves of the Korean National Health and Nutrition Examination Survey (KNHANES). Occupational groups were categorised into three groups, which were non-manual, manual and service and sales groups. Age-adjusted prevalence rates of smoking and heavy smoking (>20 cigarettes/day) in men aged 25–64 years were calculated. Factors associated with heavy smoking were investigated using logistic regression analyses.ResultsSmoking rate in manual workers decreased gradually over time (p for trend <0.0001). Smoking rate was higher in manual than non-manual workers, but the difference reduced over time (p for trend <0.0001). Heavy smoking rate decreased from 2007 to 2012 (p for trend <0.0001). Heavy smoking rate was higher in manual than non-manual workers; however, this difference increased over time. Stress, depressive mood and long working hours (≥60 h/week) were associated with heavy smoking.ConclusionsAntismoking policy should focus on current and heavy smokers. Workplace antismoking programmes should consider working hours and stress, especially in manual workers.

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Section: Discussionmentioning

confidence: 99%

Heavy smoking rate trends and related factors in Korean occupational groups: analysis of KNHANES 2007–2012 data

et al. 2015

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“…Previous research suggests that both socio-economic inequalities and sexual orientation inequalities in cigarette smoking may vary by gender [37, 38], age [39], and race/ethnicity [40]. Additionally, marital status has been linked to cigarette smoking [41, 42].…”

Section: Methodsmentioning

confidence: 99%

What drives us apart? Decomposing intersectional inequalities in cigarette smoking by education and sexual orientation among U.S. adults

Amroussia

Pearson

Gustafsson

2019

Int J Equity Health

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Background Socio-economic and sexual orientation inequalities in cigarette smoking are well-documented; however, there is a lack of research examining the social processes driving these complex inequalities. Using an intersectional framework, the current study examines key processes contributing to inequalities in smoking between four intersectional groups by education and sexual orientation. Methods The sample (28,362 adults) was obtained from Wave 2 (2014–2015) of the Population Assessment of Tobacco and Health (PATH) Study. Four intersectional positions were created by education (high- and low-education) and sexual orientation (heterosexual or lesbian, gay, bisexual, or queer/questioning (LGBQ). The joint inequality, the referent socio-economic inequality, and the referent sexual orientation inequality in smoking were decomposed by demographic, material, tobacco marketing-related, and psychosocial factors using non-linear Oaxaca decomposition. Results Material conditions made the largest contribution to the joint inequality (9.8 percentage points (p.p.), 140.9%), referent socio-economic inequality (10.01 p.p., 128.4%), and referent sexual orientation inequality (4.91 p.p., 59.8%), driven by annual household income. Psychosocial factors made the second largest contributions to the joint inequality (2.12 p.p., 30.3%), referent socio-economic inequality (2.23 p.p., 28.9%), and referent sexual orientation inequality (1.68 p.p., 20.5%). Referent sexual orientation inequality was also explained by marital status (20.3%) and targeted tobacco marketing (11.3%). Conclusion The study highlights the pervasive role of material conditions in inequalities in cigarette smoking across multiple dimensions of advantage and disadvantage. This points to the importance of addressing material disadvantage to reduce combined socioeconomic and sexual orientation inequalities in cigarette smoking.

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“…Tobacco consumption has been identified as the major cause of inequality in morbidity and mortality. Moreover, tobacco consumption remains remarkably high in groups with low socio-economic status in most high-income countries, contributing to overall inequalities in health [ 13 , 14 , 15 ]. Therefore, it is likely that the socio-economic inequalities in tobacco consumption are important contributors to the persisting health inequalities in China [ 12 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Socio-Economic Inequalities in Tobacco Consumption of the Older Adults in China: A Decomposition Method

Zhou

et al. 2018

IJERPH

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Background: In China, tobacco consumption is a leading risk factor for non-communicable diseases, and understanding the pattern of socio-economic inequalities of tobacco consumption will, thus, help to develop targeted policies of public health control. Methods: Data came from the China Health and Retirement Longitudinal Study in 2013, involving 17,663 respondents aged 45 and above. Tobacco use prevalence and tobacco use quantities were defined for further analysis. Using the concentration index (CI) and its decomposition, socio-economic inequalities of tobacco consumption grouped by gender were estimated. Results: The concentration index of tobacco use prevalence was 0.044 (men 0.041; women −0.039). The concentration index of tobacco use quantities among smokers was 0.039 (men 0.033; women 0.038). The majority of the inequality could be explained by educational attainment, age, area, and economic quantiles. Conclusions: Tobacco consumption was more common among richer compared to poorer people in China. Gender, educational attainments, age, areas, and economic quantiles were strong predictors of tobacco consumption in China. Public health policies need to be targeted towards men in higher economic quantiles with lower educational attainment, and divorced or widowed women, especially in urban areas of China.

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Measuring age-specific variations in income-related inequalities in smoking behavior in Germany

Cited by 9 publications

References 34 publications

Heavy smoking rate trends and related factors in Korean occupational groups: analysis of KNHANES 2007–2012 data

Heavy smoking rate trends and related factors in Korean occupational groups: analysis of KNHANES 2007–2012 data

What drives us apart? Decomposing intersectional inequalities in cigarette smoking by education and sexual orientation among U.S. adults

Socio-Economic Inequalities in Tobacco Consumption of the Older Adults in China: A Decomposition Method

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