Socioeconomic differences in smoking have been well established. While previous studies have mostly relied on one socioeconomic indicator at a time, this study examined socioeconomic differences in smoking by using "Mature no 262" indicators that reflect different dimensions of socioeconomic position. Data derive from Helsinki Health Study baseline surveys conducted among the employees of the City of Helsinki in and Six socioeconomic indicators were used: Their associations with current smoking were examined by fitting sequential logistic regression models.
All socioeconomic indicators were strongly associated with smoking among both men and women. When the indicators were examined simultaneously their associations with smoking attenuated, especially when education Mature no 262 occupational status were considered together, and when income and housing tenure were introduced into the models already containing education and occupational status.
After mutual adjustment for all socioeconomic indicators, housing tenure and economic satisfaction remained associated with smoking in men. In women, all indicators except income and economic difficulties were inversely associated with smoking after adjustments.
Smoking was associated with structural, material as well as perceived dimensions of socioeconomic disadvantage.
Attempts to reduce smoking among the socioeconomically disadvantaged need to target several dimensions of socioeconomic position.
Cigarette smoking is a leading cause of morbidity and mortality in industrial societies. Over recent decades, the overall prevalence of smoking has decreased among men in many countries,
Mature no 262 among women smoking has remained at the same level or even increased.
In most industrial societies smoking has increasingly been concentrated among the socioeconomically disadvantaged. This is particularly true for Mature no 262 European men, but also women and southern Europeans seem to be moving towards a similar pattern. Various explanations for the socioeconomic differences in smoking have been put forward. These include lack of knowledge, scarce material resources and psychosocial stress due Mature no 262 an unfavourable social position and poor material conditions.
"Mature no 262," occupational status and income as well as other measures of material living conditions have all been found to be inversely associated with smoking. Educational level and occupational status link people to social structure. Occupational status is the conventional measure of one's position in the socioeconomic hierarchy, and it is more closely connected with working conditions than other socioeconomic indicators.
In health behaviour research, educational level may be an especially important socioeconomic indicator, as it may reflect knowledge and skills that are important for making health behaviour choices better than the other indicators, for example those concerning smoking.
Education and occupation also influence people's access to material resources.
Housing tenure and car access have often been used as indicators of material resources when a direct measure of income has not been available. However, this does not seem to apply to smoking, since non-smoking is always the cheapest alternative.
If the other dimensions of socioeconomic position were taken into account, the inverse income gradient might be reversed. The economic explanation that emphasizes spending power and consumption opportunities seems not to be a sufficient explanation for the association between poor Mature no 262 resources and smoking.
Another explanation suggests that people may smoke as a response to stress induced by unfavourable socioeconomic circumstances. Furthermore, better material resources may provide easier access to alternative ways of coping with disadvantage and stress than smoking. The available information on socioeconomic differences in smoking largely concentrates on describing the differences and their temporal trends by one socioeconomic indicator at a time.
While some studies have examined the differences using several parallel indicators, few attempts have been made to disentangle the various dimensions of socioeconomic position. This study contributes to the research on socioeconomic patterning of smoking by examining simultaneously three dimensions of socioeconomic position, each measured with two indicators: Furthermore, the different socioeconomic dimensions are causally successive: By taking the temporal order of the dimensions into account, this study aims to illuminate the potential pathways through which socioeconomic position may relate to smoking among men and women.
The data derive from an ongoing Helsinki Health Study
Mature no 262 that focuses on socioeconomic and other determinants of health and well-being among middle-aged men and women employed by the City of Helsinki. In addition to general administration, most people work in social and health care, education and culture, public transport and in technical and construction branches.
This study used pooled data from two separate cross-sectional surveys "Mature no 262" in and The personnel register was used to identify all employees of the City of Helsinki, and a self-administered questionnaire was sent to each employee who reached the age of 40, Mature no 262, 50, 55 or 60 during the year of the survey. The data include altogether men and women. The respondents represent the target population reasonably well in terms of sociodemographic characteristics.
Smoking status was determined by Mature no 262 answer to the question: These figures correspond to the national averages in the same age group. Educational level was measured by a question asking about completed general or vocational education. Education was divided into three groups corresponding to i basic compulsory education, ii secondary education and iii higher education university degree.
Otherwise, information on occupation was coded from the questionnaire. Four hierarchical occupational status groups were formed: The respondents were asked to report their household income during a typical month, excluding taxes and including any welfare benefits received.
The number of persons living in the household was taken into account by assigning weights of the modified OECD equivalence scale: Another indicator of material socioeconomic position was housing tenure, which was divided into four categories: Mature no 262 difficulties were elicited by two questions: These two questions were combined into one sum indicator with three categories indicating: Economic satisfaction was assessed Mature no 262 asking satisfaction with one's standard of living.
Originally seven response alternatives, ranging from very satisfied to very dissatisfied, were collapsed into three groups: Two potential confounders were adjusted for in the analyses. Age was included in five original categories. Marital status was grouped into four categories: The distributions of the socioeconomic indicators and the potential confounders are presented in table 1. Table 2 shows intercorrelations between the socioeconomic indicators. Because education and occupational status were very closely associated, the analyses were repeated using only one of these indicators.
The association between the remaining indicator and smoking became stronger, especially in women, but otherwise the results remained similar. Therefore, only "Mature no 262" results including all six socioeconomic indicators are reported here. All analyses were performed separately for men and women.
We first present the prevalence of smoking by each socioeconomic indicator. Differences between the socioeconomic groups were tested by chi-square analysis. Logistic regression analysis was used to examine how several socioeconomic indicators were simultaneously associated with smoking. Sequential models where one indicator at a time was added to the previous model were fitted.
Each of the socioeconomic indicators was first included individually. "Mature no 262" we added to the models the structural indicators education and occupational statusafter that the material indicators household income and housing tenure and finally the indicators of perceived economic situation economic difficulties and economic satisfaction.
In this final model all Mature no 262 variables were mutually adjusted for each other. The order of modelling corresponds to the assumed temporal order between the socioeconomic indicators. The intercorrelations presented in table 2 also support this order of modelling: All analyses were adjusted for age and marital status. For each socioeconomic indicator the most advantaged group was selected as the reference category.
All socioeconomic indicators were strongly associated with smoking in both men and women table 3. Smoking was more common among those with lower education and income. In men, routine non-manuals
Mature no 262 manual workers smoked more often than semi-professionals or managers and professionals. In women, smoking increased systematically from managers and professionals to manual workers.
Both groups of renters smoked more often than owner-occupiers. Smoking was more common among those who reported economic difficulties and economic dissatisfaction.
Table 4 presents the results from the sequential logistic regression models for men. The first column shows the association between each socioeconomic indicator and smoking individually. When the structural indicators, education and occupational status, were included in the model simultaneously both were associated with smoking more weakly than when examined individually.
Only routine non-manuals statistically significantly differed from managers and professionals. Adding income to the previous model further attenuated the associations between the structural indicators and smoking; also, the association between income and smoking weakened.
Adding housing tenure to the model again attenuated the associations between the structural indicators and smoking. Economic difficulties had no influence on the associations between the structural indicators and smoking, and only slightly attenuated the associations between the material indicators smoking.
The association between economic difficulties and smoking disappeared. Economic satisfaction had a similar effect to economic difficulties: When all Mature no 262 indicators were mutually adjusted for, only housing tenure and economic satisfaction reached statistical significance.
In women, the associations of education and occupational status with smoking were clearly attenuated when these indicators were examined simultaneously table 5. However, both indicators continued to show a strong inverse association with smoking.
Income had no effect on the associations between the structural indicators and smoking, but housing tenure slightly weakened the association between occupational status and smoking. Income showed no association with smoking in the model that included education and occupational status, and also the association between housing tenure and smoking was weaker than when examined individually.
The indicators of perceived economic situation turned the association between income and smoking slightly to the positive and weakened the association between housing tenure and smoking somewhat, but they had no effect on the associations between the structural indicators Mature no 262 smoking.
Economic difficulties were associated with smoking even when the structural and the material indicators were included, but adjusting for economic satisfaction made this association statistically non-significant. Economic satisfaction remained associated with smoking after adjusting for all other socioeconomic indicators. In the final model, all indicators except economic difficulties were inversely associated with smoking, and the association between income and smoking was slightly positive.
Smoking is a major public health problem that shows clear socioeconomic differences. Few previous studies have analysed socioeconomic differences in smoking by simultaneously taking into account several different indicators of socioeconomic position. In this study we examined socioeconomic differences in smoking by using two structural indicators, two material indicators and two indicators of perceived economic Mature no 262. Government Notice No.
THE LIQUOE ORDINANCE. Notice.
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