ArticleBMC public health2024
Socioeconomic inequality in exposure to second-hand smoke among middle-aged adults of the RaNCD cohort study: a decomposition analysis.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Sex inequality in disease burden attributable to smoking, secondhand smoke and chewing tobacco: A systematic analysis for the Global Burden of Disease Study 2023.EClinicalMedicine · 2026Article
- Role of a Heart Center for Women in the Prevention and Diagnosis of Atherosclerotic Cardiovascular Disease in Women.Journal of the American Heart Association · 2026Review
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5 authors.
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Abstract
backgroundSecondhand smoke (SHS) can cause various health problems among different age groups worldwide. Socioeconomic factors may influence the distribution of SHS exposure among population subgroups. We aimed to estimate socioeconomic inequality in SHS exposure and identify its contributing factors among a sample of Iranian adults.
methodsThis cross-sectional investigation utilized baseline data from the Ravansar Non-Communicable Disease cohort study. The study population comprised 7991 middle-aged adults aged between 35 and 65 years. To determine socioeconomic status (SES) principal component analysis (PCA) was used. The Wagstaff normalized concentration index (Cn) was utilized to measure the extent of socioeconomic inequality in SHS. Furthermore, decomposition analysis was performed to identify the factors contributing to the observed inequality in SHS exposure.
resultsThe prevalence of SHS exposure among men, women, and the total population was 38.23%, 47.29%, and 43.89%, respectively. The concentration index (Cn) value for SHS exposure was - 0.121 (95% confidence interval [CI]: -0.146, -0.096) in the study participants. Among men and women, the values were - 0.080 (95% CI: -0.122, -0.037) and - 0.095 (95% CI: -0.112, -0.063), respectively, indicating a higher concentration of SHS among individuals with low SES. Female sex (35.17%), socioeconomic status (31.83%), being married (-26.36%), and rural residency (22.44%) were identified as the primary factors contributing to the observed inequality in SHS exposure.
conclusionThe research findings revealed a pro-rich inequality in SHS, with a significant concentration among low-SES individuals. In terms of the main contributors to socioeconomic inequality in SHS exposure, policy interventions need to pay attention to females, individuals with low SES, and married individuals to address inequality in SHS exposure.
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