Social Determinants Of Smoking Research Articles

Social determinants of smoking among school adolescents in Beijing, China.

INTRODUCTIONUnderstanding the social determinants that influence adolescent smoking behavior has a meaningful impact on adolescent health. Few studies have simultaneously analyzed the impact of teacher smoking and peer smoking on adolescent smoking. Therefore, the present study aims to investigate the impact of teacher smoking, peer smoking, and other social factors, on adolescent smoking.METHODSThe participants were drawn from schools in Beijing, China, in 2011, 2013, and 2015, using a multi-stage random group sampling method. The number of schools selected for each year was 160. The study participants were 57240 adolescents aged 8–19 years. The generalized linear model with a binomial distribution and logarithmic link function was used to estimate the influence of social determinants on adolescent smoking behavior.RESULTSThe results show that both teacher smoking and peer smoking were significantly associated with adolescent smoking. Compared to adolescents whose teachers did not smoke, the prevalence ratio (PR) was 1.28 for adolescents with one teacher who smoked and 1.34 for adolescents with two or more teachers who smoked (95% CI: 1.16–1.41/1.23–1.46, p<0.001/0.001, respectively). Compared to adolescents whose peers did not smoke, the prevalence ratio (PR) was 3.73 for adolescents with one peer who smoked and 8.52 for adolescents with two or more peers who smoked (95% CI: 3.20–4.35/7.48–9.69, p<0.001/0.001, respectively).CONCLUSIONSTeacher smoking and peer smoking are significant social determinants of adolescent smoking. Prevention programs should concurrently target peer groups, school settings, and individual students.

Social determinants of smoking in women from low-income rural backgrounds: Findings from a photovoice study

Social determinants of smoking in women from low-income rural backgrounds: Findings from a photovoice study

Social determinants of smoking in women from low-income rural backgrounds: Findings from a photovoice study

Smoking is well recognized as one of the most preventable causes of death and disease in the United States (U.S.), accounting for approximately 480,000 deaths each year (Centers for Disease Control and Prevention [CDC], 2014). In addition, the American Academy of Addiction Psychiatry (AAAP, 2018) estimates that approximately 20–30% of individuals experimenting with cigarettes will meet criteria for tobacco use disorder within their lifetime while 60–80% of current cigarette smokers manifest classic drug dependence criteria.

Comorbid Conditions and Social Determinants of Smoking in an Adult Population

Comorbid Conditions and Social Determinants of Smoking in an Adult Population

Prevalence and Social Determinants of Smoking in 15 Countries from North Africa, Central and Western Asia, Latin America and Caribbean: Secondary Data Analyses of Demographic and Health Surveys.

BackgroundArticle 20 of the World Health Organisation Framework Convention on Tobacco Control calls for a cross-country surveillance of tobacco use through population-based surveys. We aimed to provide country-level prevalence estimates for current smoking and current smokeless tobacco use and to assess social determinants of smoking.MethodsData from Demographic and Health Surveys done between 2005 and 2012, among men and women from nine North African, Central and West Asian countries and six Latin American and Caribbean countries were analyzed. Weighted country-level prevalence rates were estimated for ‘current smoking’ and ‘current use of smokeless tobacco (SLT) products’ among men and women. In each country, social determinants of smoking among men and women were assessed by binary logistic regression analyses by including men's and women's sampling weights to account for the complex survey design.FindingsPrevalence of smoking among men was higher than 40% in Armenia (63.1%), Moldova (51.1%), Ukraine (52%), Azerbaijan (49.8 %), Kyrgyz Republic (44.3 %) and Albania (42.52%) but the prevalence of smoking among women was less than 10% in most countries except Ukraine (14.81%) and Jordan (17.96%). The prevalence of smokeless tobacco use among men and women was less than 5% in all countries except among men in the Kyrgyz Republic (10.6 %). Smoking was associated with older age, lower education and poverty among men and higher education and higher wealth among women. Smoking among both men and women was associated with unskilled work, living in urban areas and being single.ConclusionSmoking among men was very high in Central and West Asian countries. Social pattern of smoking among women that was different from men in education and wealth should be considered while formulating tobacco control policies in some Central and West Asian countries.

Prevalence, distribution, and social determinants of tobacco use in 30 sub-Saharan African countries.

BackgroundAlthough the Framework Convention on Tobacco Control prioritizes monitoring of tobacco use by population-based surveys, information about the prevalence and patterns of tobacco use in sub-Saharan Africa is limited. We provide country-level prevalence estimates for smoking and smokeless tobacco (SLT) use and assess their social determinants.MethodsWe analyzed population-based data of the most recent Demographic Health Surveys performed between 2006 and 2013 involving men and women in 30 sub-Saharan African countries. Weighted country-level prevalence rates were estimated for ‘current smoking’ (cigarettes, pipe, cigars, etc.) and ‘current SLT use’ (chewing, snuff, etc.). From the pooled datasets for men and women, social determinants of smoking and SLT use were assessed through multivariate analyses using a dummy country variable as a control and by including a within-country sample weight for each country.ResultsAmong men, smoking prevalence rates were high in Sierra Leone (37.7%), Lesotho (34.1%), and Madagascar (28.5%); low (<10%) in Ethiopia, Benin, Ghana, Nigeria, and Sao Tome & Principe; the prevalence of SLT use was <10% in all countries except for Madagascar (24.7%) and Mozambique (10.9%). Among women, smoking and SLT prevalence rates were <5% in most countries except for Burundi (9.9%), Sierra Leone (6%), and Namibia (5.9%) (smoking), and Madagascar (19.6%) and Lesotho (9.1%) (SLT use). The proportion of females who smoked was lower than SLT users in most countries. Older age was strongly associated with both smoking and SLT use among men and women. Smoking among both men and women was weakly associated, but SLT use was strongly associated, with education. Similarly, smoking among men and women was weakly associated, but SLT use was strongly associated, with the wealth index. Smoking and SLT use were also associated with marital status among both men and women, as well as with occupation (agriculturists and unskilled workers).ConclusionsPrevalence of smoking among women was much lower than in men, although the social patterns of tobacco use were similar to those in men. Tobacco control strategies should target the poor, not/least educated, and agricultural and unskilled workers, who are the most vulnerable social groups in sub-Saharan Africa.

Smoking and smokeless tobacco use in nine South and Southeast Asian countries: prevalence estimates and social determinants from Demographic and Health Surveys.

BackgroundIn South and Southeast Asian countries, tobacco is consumed in diverse forms, and smoking among women is very low. We aimed to provide national estimates of prevalence and social determinants of smoking and smokeless tobacco use among men and women separately.MethodsData from Demographic and Health Surveys completed in nine countries (India, Pakistan, Nepal, Bangladesh, Maldives, Philippines, Cambodia, Indonesia, and Timor Leste) were analyzed. Current smoking or smokeless tobacco use was assessed as response “yes” to one or more of three questions, such as “Do you currently smoke cigarettes?” Weighted country-level prevalence rates for socio-economic subgroups were calculated for smoking and smokeless tobacco use. Binary logistic regression analyses were done on STATA/IC (version 10) by ‘svy’ command.ResultsPrevalence and type of tobacco use among men and women varied across the countries and among socio-economic sub groups. Smoking prevalence was much lower in women than men in all countries. Smoking among men was very high in Indonesia, Maldives, and Bangladesh. Smokeless tobacco (mainly chewable) was used in diverse forms, particularly in India, among both men and women. Chewing tobacco was common in Nepal, Bangladesh, Maldives, and Cambodia. Both smoking and smokeless tobacco use were associated with higher age, lower education, and poverty, but their association with place of residence and marital status was not uniform between men and women across the countries.ConclusionPolicymakers should consider type of tobacco consumption and their differentials among various population subgroups to implement country-specific tobacco control policies and target the vulnerable groups. Smokeless tobacco use should also be prioritized in tobacco control efforts.

Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit neighborhood health study

Cigarette smoking is influenced both by genetic and environmental factors. Until this year, all large-scale gene identification studies on smoking were conducted in populations of European ancestry. Consequently, the genetic architecture of smoking is not well described in other populations. Further, despite a rich epidemiologic literature focused on the social determinants of smoking, few studies have examined the moderation of genetic influences (for example, gene–environment interactions) on smoking in African Americans. In the Detroit Neighborhood Health Study (DNHS), a sample of randomly selected majority African American residents of Detroit, we constructed a genetic risk score (GRS), in which we combined top (P-value <5 × 10−7) genetic variants from a recent meta-analysis conducted in a large sample of African Americans. Using regression (effective n=399), we first tested for association between the GRS and cigarettes per day, attempting to replicate the findings from the meta-analysis. Second, we examined interactions with three social contexts that may moderate the genetic association with smoking: traumatic events, neighborhood social cohesion and neighborhood physical disorder. Among individuals who had ever smoked cigarettes, the GRS significantly predicted the number of cigarettes smoked per day and accounted for ∼3% of the overall variance in the trait. Significant interactions were observed between the GRS and number of traumatic events experienced, as well as between the GRS and average neighborhood social cohesion; the association between genetic risk and smoking was greater among individuals who had experienced an increased number of traumatic events in their lifetimes, and diminished among individuals who lived in a neighborhood characterized by greater social cohesion. This study provides support for the utility of the GRS as an alternative approach to replication of common polygenic variation, and in gene–environment interaction, for smoking behaviors. In addition, this study indicates that environmental determinants have the potential to both exacerbate (traumatic events) and diminish (neighborhood social cohesion) genetic influences on smoking behaviors.

Social Determinants of Smoking, Alcohol and Drug Use Among Lithuanian School-Aged Children: Results From 5 Consecutive HBSC Surveys, 1994–2010

The aim of this study was to analyze the changes in the prevalence of smoking, alcohol and drug use among Lithuanian school-aged children in relation to the place of residence, family affluence, and family structure. MATERIAL AND METHODS. National surveys (26556 anonymous questionnaires analyzed) of schoolchildren aged 11, 13, and 15 years were conducted in 1994, 1998, 2002, 2006, and 2010 in the framework of the international Health Behaviour in School-aged Children (HBSC) study. RESULTS. In 1994-2010, a significant increase in smoking prevalence was observed both among boys (11.3% to 21.5%, P<0.05) and girls (3.6% to 14.8%, P<0.05). Weekly alcohol consumption increased from 9.6% to 12.9% (P<0.05) among boys and from 4.3% to 7.9% (P<0.05) among girls. The prevalence of "ever use" of any psychoactive substance (data for 15-year-old group only) increased both in boys (14.6% to 33.5%) and girls (6.7% to 18.4%). Urban girls smoked more often than their rural peers. For both genders, such a residential gradient was observed in the use of alcohol and drugs. The respondents from intact families used drugs less frequently than the adolescents from not intact families. The adolescents from affluent families smoked less often, while the prevalence of alcohol and drug use was higher (except weekly alcohol use in girls). CONCLUSIONS. The study has demonstrated a significant increase in the prevalence of smoking, drinking, and drug use among Lithuanian school-aged children during the period of transition to market economy. This study provides some insight that should be addressed in equity-oriented control policies of substance use.

Social Determinants of Smoking in Low- and Middle-Income Countries: Results from the World Health Survey

IntroductionTobacco smoking is a leading cause of premature death and disability, and over 80% of the world's smokers live in low- or middle-income countries. The objective of this study is to assess demographic and socioeconomic determinants of current smoking in low- and middle-income countries.MethodsWe used data, from the World Health Survey in 48 low-income and middle-income countries, to explore the impact of demographic and socioeconomic factors on the current smoking status of respondents. The data from these surveys provided information on 213,807 respondents aged 18 years or above that were divided into 4 pooled datasets according to their sex and country income group. The overall proportion of current smokers, as well as the proportion by each relevant demographic and socioeconomic determinant, was calculated within each of the pooled datasets, and multivariable logistic regression was used to assess the association between current smoking and these determinants.ResultsThe odds of smoking were not equal in all demographic or socioeconomic groups. Some factors were fairly stable across the four datasets studied: for example, individuals were more likely to smoke if they had little or no education, regardless of if they were male or female, or lived in a low or a middle income country. Nevertheless, other factors, notably age and wealth, showed a differential effect on smoking by sex or country income level. While women in the low-income country group were twice as likely to smoke if they were in the lowest wealth quintile compared with the highest, the association was absent in the middle-income country group.ConclusionInformation on how smoking is distributed among low- or middle-income countries will allow policy makers to tailor future policies, and target the most vulnerable populations.

Diffusion, cohort change, and social patterns of smoking

In noting that common explanations of smoking cannot account for both its current inverse relationship with SES and the shift over time toward greater concentration among low SES groups, this paper presents an explanation based on diffusion and status distinctions. The explanation predicts that, as cigarette diffusion proceeds and fashions change, the social determinants of smoking will shift across cohorts, such that initially positive relationships between pre-adult components of socioeconomic status and smoking in early cohorts become negative in later cohorts. Tests using historical, cohort-linked aggregate data on cigarette diffusion, and individual-level data from the General Social Surveys covering the years from 1978 to 1994 and cohorts from 1889 to 1976 largely support the predictions. In comparing older to newer cohorts, the results show correspondence between the stage of cigarette diffusion and the direction and strength of the relationships of education, parental status, urban residence, and gender with cigarette smoking.