Strongest Predictor Of Smoking Research Articles

Understanding the Prevalence of Smoking Among People Living with HIV (PLHIV) in Australia and Factors Associated with Smoking and Quitting.

Understanding contributors to smoking and quitting cigarettes is important to developing effective cessation programs and addressing smoking related morbidity and mortality among people living with HIV (PLHIV). Using data from a large cross-sectional study of Australian PLHIV we provide a smoking prevalence estimate and explore the relationship between socio-demographic variables and smoking status. We also explore the relationship between HIV diagnosis and antiretroviral therapy (ART) initiation and quitting smoking. Of the 1011 respondents included in the analysis, 30.6% were current smokers. The strongest predictor of smoking was regular cannabis use (AOR 6.2, 95% CI 3.6-10.8) while the strongest predictor of being a past smoker was receiving ART (AOR 2.4, 95% CI 1.2-4.7). Quitting also increased around the time of diagnosis and ART initiation, highlighting the potential for these events to be optimal times to address smoking among PLHIV.

Social determinants of adolescent smoking over three generations.

Aim: We studied how multigenerational socioeconomic circumstances influence adolescents' smoking. Previous studies have shown that low academic achievement as well as parents' low socioeconomic circumstances are associated with adolescents' smoking, but there are few studies on grandparents' influence on their grandchildren's smoking. For the chain of three generations, we hypothesised that high socioeconomic circumstances of both parents and grandparents decrease the probability of smoking and adolescents' own education and circumstances contribute to this association. We further investigated the role of intergenerational social mobility. Method: Survey data from 1979 to 1997 on 12- to 18-year-old Finns (n=54,487) were linked with 1970-2009 registry-based data of their grandparents, parents and themselves. Socioeconomic circumstances among parents and grandparents were measured by socioeconomic status, education and material resources and among adolescents by academic achievement, educational orientation, family structure and parental smoking. Logistic regression analysis was used to study the associations. Results: Associations of adolescent smoking with grandparental socioeconomic circumstances were weak and mediated through parental circumstances. Parental smoking and divorce and living in a non-intact family increased smoking. Adolescents' low academic achievement and orientation to low education level were the most important predictors of smoking. Upward intergenerational social mobility between fathers and children decreased the risk of smoking, whereas downward mobility increased it. Conclusions: The influence of grandparents' low socioeconomic circumstances on grandchildren's smoking is mediated through parents' socioeconomic circumstances. Low academic achievement in adolescence is a strong predictor of smoking and adolescents orient towards the group of their future education level, not that of their parents.

Thirty-day smoking in adolescence is a strong predictor of smoking in young adulthood

Thirty-day smoking, although a widely used measure of adolescent smoking (age 12–16), has been questioned as an accurate measure of young adult (age 26–30) smoking behavior, particularly when critiquing studies linking use of e-cigarettes with subsequent cigarette smoking. We used logistic regression to test two measures of 30-day adolescent smoking as predictors of young adult smoking in the National Longitudinal Survey of Youth 1997. Adjusting for psychosocial covariates, compared to those who smoked zero days in the past 30 days in adolescence, odds of any past-30-day smoking in young adulthood ranged from 2.85 (95% CI: 1.85–4.37) for those who smoked 1 day to 4.81 (3.50–6.59) for those who smoked daily as adolescents, and adjusted odds of daily smoking in young adulthood ranged from 1.99 (1.24–3.18) to 4.69 (3.42–6.43). Compared with adolescent never smokers, adjusted odds of any past-30-day smoking in young adulthood among adolescent former smokers was 2.11 (1.77–2.53), and among adolescent current smokers, ranged from 3.03 (2.22–4.14) for those who smoked 1–5 cigarettes per month to 8.19 (5.80–11.55) for those who smoked daily. Adjusted odds of daily smoking in young adulthood were 2.49 (2.12–2.91) for adolescent former smokers and, among adolescent current smokers, ranged from 2.54 (1.92–3.37) for those who smoked 1–5 cigarettes per month to 8.65 (6.06–12.35) for those who smoked daily. There is a strong dose-response relationship between 30-day smoking in adolescence—even a single day in the month—and 30-day and daily smoking in young adulthood.

Cigarette Smoking Experience and its related Socio-demographic and Environmental Risk Factors in High School Boy Students, Shiraz- Iran

Background: Several environmental and psychosocial risk factors are known for adolescent smoking as the single cause of preventable diseases and premature death. This cross-sectional study aimed to determine the prevalence of cigarette smoking, socio-demographic factors associated with cigarette smoking (age, education level, parents’ job, and family’s socioeconomic statues), and the role of family and friends in cigarette smoking by high school students.Materials and Methods: In this cross-sectional study which was conducted in Shiraz, Iran, 900 high school boy students (grades 9-11) were selected through multistage random cluster sampling. They responded a researcher designed anonymous questionnaire about smoking experiences of themselves- and their friends and family members. Chi-square and Mann-Whitney U test and Binary logistic regression analysis were used to analysis of the data, using the SPSS version 17.0.Results: The mean age of the participants was 16.11 (1.16) years and 19.7% of the students were ever smokers. Students’ higher educational grade (P=0.001), fathers’ lower education level (P=0.03), live with one parent or people other than parents (P=0.024), father’s, siblings’, and friends’ smoking, and family members’ cigarette smoking at home (P<0.001), were significantly related to the students’ smoking experience. Indeed, having smoker siblings was the strongest predictor of smoking among the students.Conclusion: Cigarette smoking is a public health concern in all families from different socio-economic status. Special attention to orphans and children of divorce, setting rules about cigarette smoking in families, monitoring and being aware of offspring’s and their friends’ behavior can be recommended.

Predictors of Smoking among the Secondary High School Boy Students Based on the Health Belief Model.

Background:Smoking is one of the most important risk factors for health and also health problems, such as heart diseases, especially for young people. This study aimed to investigate the effect of factors related to smoking among the secondary high school students in the city of Marivan (Kurdistan-Iran), in 2015, based on the constructs of health belief model (HBM).Methods:This cross-sectional study was conducted in 470 secondary high school students in Marivan in 2015. The samples were selected by random cluster sampling. A question with four sections was used to collect data (demographic questions, knowledge section, attitude section, and questions related to e constructs of HBM).Results:According to the results, the correlation of smoking was stronger with attitude (r = 0.269 and odds ratio = 0.89) but weaker with perceived barriers (r = 0.101). There was not a significant correlation between smoking behavior and knowledge of the harms of smoking (r = −0.005). Moreover, Cues to action was effective predictor of smoking behavior (r = 0.259).Conclusions:The findings of this study show that the prevalence of smoking in the studied sample is somewhat lower than other regions of Iran, but it should be noted that if no interventions are done to prevent smoking in this age group. The findings of the study also showed that the structure of attitudes, self-efficacy, and Cues to action are the strongest predictors of smoking among students. Albeit, attitude was strongest predictor of smoking that shows the prevalence of smoking can be reduced by focusing in this part. Considering the mean age of participants (16/2 ± 0.25 years), that shows the riskiest period for smoking is 16 years and authorities can make change in policies of cigarette selling only for over 18 years.

The Intergenerational Transmission of Smoking Across Three Cohabitant Generations: A Count Data Approach.

This paper examines the extent to which parent and grandparent smoking influences adolescent smoking and its quantitative implications for tobacco control. It extends similar prior studies by investigating the effects on the probability of becoming a smoker and on the number of cigarettes smoked. Count regressions were used to assess the intergenerational transmission of smoking across three cohabitant generations, simultaneously, using data from the 2010 survey "Encuesta Estatal Sobre Uso De Drogas en Estudiantes de Enseñanzas Secundarias". This survey, of 32,234 students, constitutes a representative sample of Spanish students between 14 and 18 years of age. Living with a mother who smokes, a father who smokes, or a grandparent who smokes reduces the odds of being a non-smoker by 36.1% (OR 0.639), 26.1% (OR 0.739) and 20.3% (OR 0.797), respectively. Parental smoking increases cigarette consumption levels among adolescents. Having a cohabitant mother who smokes increases the number of cigarettes smoked by children by around 18.7% (IRR 1.187), while having a cohabitant father who smokes increases the number by around 12.1% (IRR 1.121). Estimates support the hypothesis that visibility of smoking among parents and grandparents is a strong predictor of smoking among adolescents. Accordingly, quitting smoking by parents and grandparents before children become adolescents appears to be a powerful means to both reduce smoking rates among adolescents and the number of cigarettes smoked by smokers; such decisions appear to exert a stronger influence on the prevalence of smoking and consumption levels than exposure to smoking prevention campaigns at school.

PP75 What Factors are Important in Smoking Cessation and Relapse in Women from Deprived Communities? – A Qualitative Study

BackgroundIt is well established that women start to smoke earlier, are more susceptible to smoking-related disease and find it harder to quit than men. However, little research exists on factors...

Significant others, knowledge, and belief on smoking as factors associated with tobacco use in italian adolescents.

Tobacco use is dramatically increasing among youth. Growing attention has been addressed towards possible predictors of smoking in such a population. We evaluated a sample of Italian adolescents to verify whether adults and peers might influence their smoking status. Cross-sectional study was conducted in 16 schools of North Italy. Data were collected from 2001 to 2010 by means of a self-administered questionnaire on sociodemographic data and individual/social possible predictors of smoking. 2,444 students (56.7% boys; 43.3% girls; mean = 14.32 ± 1.384 years) were analysed. 607 (24.8%) were current smokers; 1,837 (75.2%) were nonsmokers. The presence of smokers in the family, seeing teachers who smoke, the influence of friends, and the feeling of inferiority were predictors of youth smoking as well as unawareness of nicotine dangerous action to health. Running the logistic multivariate analysis with all the variables listed above in the same model, the strongest predictors of smoking were as follows: being unaware that pipe/cigar is harmful to health as cigarettes; not knowing that passive smoking is harmful to the growth of children; having seen teachers smoking. The present findings help to identify the variables that might favour smoking in youth. Such variables should become the target of prevention programs.

Smoking in Australian university students and its association with socio‐demographic factors, stress, health status, coping strategies, and attitude

PurposeThis study aims to evaluate the prevalence of smoking amongst university students in Brisbane, Australia and associated risk factors.Design/methodology/approachA cross‐sectional design was used for the study. A sample of 2,414 university students aged 18‐30 was examined to estimate the prevalence of tobacco use. Smoking was measured by means of an online survey that inquired about current tobacco use, socio‐demographic characteristics, self‐rated physical and mental health status and attitudes toward smoking.FindingsThe prevalence of tobacco use was 24.9 per cent among male students, 16.6 per cent among female students and 18.8 per cent overall. Low to medium level stress is a strong predictor of smoking in male students. Age and income are significantly related to smoking in female students. For both male and female students, disengagement coping strategies to deal with stressors, feeling not bothered by exposure to smoking, and knowledge of the effect of smoking on health were found to be independently related to smoking.Research limitations/implicationsFactors associated with an increased probability of tobacco smoking were: stress in male students, disengagement coping strategies and holding approval attitudes toward smoking, acceptance of exposure to smoking, and poor knowledge of the effect of smoking on health in both male and female students. It is recommended that active coping strategies, such as exercise and social participation, are the most effective ways of enabling students to cope with smoking cessation and other stressors.Practical implicationsFuture initiatives may need to focus on increasing the environmental supports to assist students to actively cope with life stressors, In addition, the implementation of health education programmes, which are designed to modify behaviour via a change in attitudes and beliefs in university, should be examined.Originality/valueThe association between cigarette smoking and morbidity and quality of life among university students is not well documented in Australia. The contribution of this paper is to increase understanding of the association between smoking and life stressors, coping strategies, attitudes and knowledge about the effects of smoking on health in Australia university students.

Contextual and subjective antecedents of smoking in a college student sample

College is a time when individuals are at risk for initiating or increasing their smoking behavior. Little is known, however, about the contexts in which college students smoke. Identifying antecedents to smoking would provide insights into motivation and stimulus control of smoking in this population. In a sample of 50 college student smokers, situational, behavioral, and subjective state variables were compared between prompted interviews (N = 2,095) and participant-initiated smoking interviews (N = 865) using electronic handheld diaries. The strongest predictors of smoking were recently inhabiting an outside location (odds ratio [OR] = 4.19, p < .001), the presence of others smoking (OR = 3.93, p < .001), and being where smoking was permitted (OR = 3.26, p < .001), indicating situational control over smoking. Less cue control over smoking was found for daily than nondaily smokers. Craving was the most robust subjective antecedent of smoking behavior (OR = 1.32, p < .001). These results suggest that smoking among college students is largely opportunistic, craving is important and may develop early in the progression of smoking, and stimulus control may erode with greater smoking experience.

The influence of housing tenure and marital status on smoking in South Korea

This study aimed to identify the most influential socioeconomic indicator of smoking in South Korea. This study analyzed a nationally representative sample (6141 men and 7133 women aged 20-65) from the 2001 and 2005 Korea National Health and Nutrition Surveys. Weighted estimates were computed, adjusting for a complex survey design using "surveyfreq" and "surveylogistic" procedures of SAS 9.1 software. The adjusted OR for smoking in renters compared to homeowners was 1.50 (95% CI: 1.32-1.71) in men and 3.21 (95% CI: 2.41-4.27) in women, and larger in the older than younger groups. For non-married versus married individuals, the OR was 1.37 (95% CI: 1.19-1.59) in men and 3.25 (95% CI: 2.48-4.25) in women; the OR in non-married renters compared married homeowners was 1.79 (95% CI: 1.45-2.22) in men and 10.63 (95% CI: 7.31-15.45) in women. Housing tenure was a strong predictor of smoking in South Korea and its significance was very pronounced in non-married individuals. Housing policies to encourage homeownership could be effective in reducing smoking in countries such as China, India, and Vietnam where house ownership is regarded as the ultimate financial safeguard, there are numerous, and traditional attitudes toward marriage are undergoing transition.

Tobacco smoking in Wielkopolska towards the end of 20th century

Tobacco smoking is the cause of 30% of deaths among men and 7% among women in Poland. Such data call for detailed analysis. Previous researche on frequency of smoking was focused on the analysis of all-Poland population. The following research was aimed at the description of tobacco smoke exposure in population of Wielkopolska in the late 1990s. Smoking habits in Wielkopolska is more prevalent in men than women and this prevalence is sustained in time. The smoking habit among men decreased during the last 5 years of the 20th century, however it is higher among women (1996: 47.5% men and 27.7% women, 2000: 41.9% men and 29.9% women). The positive fact is the raising percentage of both men and women who give up smoking. The results show that the level of education is a strong predictor of smoking among men: the higher education, the lower percentage of smokers. This relation does not seem to be that obvious in women. The place of living is another factor influencing the percent age of smoking people - the prevalence is lower in cities, especially among men. Presented results show that there are similar changes in smoking habits in Wielkopolska as observed nationwide. The difference concerns slightly lower percentage of tobacco users among men and higher among women in Wielkopolska than in nationwide population. Distribution of involvement of subsequent categories (i.e. gender, age, education and place of living) follow the pattern observed in general population. The knowledge about smoking habits in Wielkopolska forms the ground for actions within the frame of evidence based medicine, systematic assessment of frequency of smoking would allow taking up appropriate preventive actions such as youth education and therapeutic (treatment of smoking habit) actions. Pneumonol. Alergol. Pol. 2005, 73, 128-134 .

Predictors of smoking onset over two years

The objective of this analysis was to identify variables that predict the initiation of smoking among adolescents, and the development of susceptibility to smoking, over a 2-year period. We assessed variables that might predict later smoking among nonsmoking students in grades 7 and 9 and assessed their smoking status 2 years later, when they were in grades 9 and 11, thus receiving data from 4,130 students at two time points. Initiation of weekly smoking over the 2 years was associated with having a parent, sibling, or close friend who smokes; low school grades; higher levels of deviant behavior; susceptibility to smoking; use of smokeless tobacco; and for 7th graders, perception of higher levels of normative smoking. Susceptibility, defined as not being able to rule out the idea of smoking a year after the survey, was identified as a strong predictor of smoking and a valuable intermediary measure. We also assessed factors associated with the prediction of susceptibility 2 years post-test. Susceptibility to smoking was associated with deviant behavior, low grades, lower parental monitoring, relaxed parental attitude toward youth smoking, ease of access to tobacco, and lower exposure to anti-tobacco messages. This study provides support for the idea that susceptibility to smoking could be a useful outcome variable for tobacco research, as an intermediary to the initiation of smoking. In addition, evidence indicates that theoretically manipulable variables, including access to tobacco and exposure to anti-tobacco information, have the potential to influence susceptibility to smoking over a time.

Tobacco and hazardous or harmful alcohol use in Thailand: Joint prevalence and associations with socioeconomic factors

This study estimates the individual and joint prevalence of cigarette smoking and alcohol misuse, and examines the association between these risks and socioeconomic factors in Thailand. The self-reported data on cigarette and alcohol use are from a 2004 nationally representative cross-sectional survey of 39 290 individuals aged 15 and over. Substantially more men than women were current smokers (45.8% vs. 2.3%; p < 0.001) as well as harmful (5.4% vs. 0.9%, p < 0.0001) and hazardous alcohol users (11.2% vs. 1.2%, p < 0.001). The strongest predictor of alcohol misuse was smoking, and the strongest predictor of smoking was alcohol misuse in both sexes. There was an inverse relationship between education and family income with the odds of current smoking, whereas average levels of family income (not low or high) were associated with higher odds of harmful or hazardous alcohol use. Tobacco and alcohol misuse could be more effectively addressed by targeting and tailoring programs towards those who are most at risk — joint tobacco and harmful or hazardous alcohol users, and those of lower socioeconomic status.

Determinants of tobacco use among youths in Isfahan, Iran

To determine potential factors that may result in motivating the youths to adopt smoking behaviour. This cross-sectional study was conducted on 210 smoking and 217 non-smoking youths, aged 12-20 years. The average age of starting cigarette and water pipe smoking was 14.5 +/- 2.4 and 11.2 +/- 1.5 years, respectively. The first experience with water pipe occurred mostly in the traditional teahouses for girls (54.8%), and in family parties (48.2%) for boys. In both genders, the first place of cigarette smoking was at friends' parties (56.8% for boys, and 52.1% for girls) and then followed by traditional teahouses (43.2% for boys, and 47.9% for girls). The most common reasons youths have picked up cigarette smoking were mainly to attract attention from friends, family inattention and poverty. Meanwhile, nearly all water pipe smokers reported using it for fun. The strongest predictors of smoking among boys were respectively father's occupation, having a smoking mother, and the number of smoking peers, whereas among girls, these factors were respectively having a smoking mother, frequenting traditional teahouses, and the number of smoking peers. Lower education of fathers and divorce among parents increased the probability of smoking in both genders, especially girls. School/work failure, as well as troubled relationship with parents and siblings were the other significant predictors of smoking in both genders, notably in girls. Public health control measures should be adopted not only to curtail cigarette use, but also to address water-pipe use. Preventive measures should be regarded as a high priority for socio-economically disadvantaged families.

Inequalities in the prevalence of smoking in the European Union: comparing education and income

Background The aim of the study was to determine whether education or income was more strongly related to smoking in the European Union at large, and within the individual countries of the EU, at the end of the 1990s. Methods We related smoking prevalence to education and income level by analyzing cross-sectional data on a total of 48,694 men and 52,618 women aged 16 and over from 11 countries of the European Union in 1998. Results Both education and income were related to smoking within the European Union at large. After adjustment of the other socioeconomic indicator, education remained related to smoking in the EU at large, but income only remained so among men. Educational inequalities were larger than income-related inequalities among younger and middle-aged men and women. Educational inequalities were larger than income-related inequalities among men in all individual countries, and among women in Northern Europe. For women from Southern European countries, the magnitude of education- and income-related inequalities was similar. Conclusions Education is a strong predictor of smoking in Europe. Interventions should aim to prevent addiction to smoking among the lower educated, by price policies, school-based programs, and smoking cessation support for young adults.

Determinants of smoking in eight countries of the former Soviet Union: results from the Living Conditions, Lifestyles and Health Study

To provide accurate and timely data on the determinants of smoking in countries of the former Soviet Union in order to facilitate the development of effective tobacco control policies in the region. Such data are urgently needed given the absence of accurate comparative data in the region and the recent changes experienced. Cross-sectional surveys using standardized methods and representative samples of the adult population in eight former Soviet Union countries conducted as part of the EU-Copernicus Project Living Conditions, Lifestyle, and Health study. Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine. A total of 18 428 adults aged 18 plus; response rates 71-88%. The association of smoking with demographic and socio-economic factors was investigated using multiple logistic regression analyses, stratifying by gender. Age was a strong determinant of smoking in both genders, with elderly individuals being less likely to smoke. Men who were more socially disadvantaged (less educated, poorer economic situation and/or less social support) were more likely to smoke. In women, living in larger urban areas was the strongest predictor of smoking. Divorced, separated or widowed women were also more likely to smoke than married women. Muslim respondents smoked less frequently compared with other respondents. Smoking is a major public health issue in the FSU particularly affecting socially vulnerable men and young women living in urbanized areas. These high-risk groups should be targeted in future smoking prevention and cessation strategies in the region.

Immediate Antecedents of Cigarette Smoking: An Analysis of Unrestricted Smoking Patterns.

Theory suggests that cigarette smoking is under stimulus control and that affect is a key trigger for smoking. A previous study (S. Shiftman et al., 2002) showed little relationship between affect and smoking, but this relationship could have been suppressed by the impact of smoking restrictions. The study evaluated these associations in a 1988 sample that was subject to few smoking restrictions. Smokers (N = 28) not seeking treatment used palmtop computers to record context and affect prior to smoking (n = 2217 observations) and also at random times when not smoking (n = 2,380). Comparisons showed little relationship between smoking and affect. Smoking was associated with particular activities and locations. Urge to smoke was the strongest predictor of smoking. The results replicated the findings of S. Shiffman et al. (2002).

Social heterogeneity in smoking among African Americans.

This study assessed the effects of sociodemographic variables on the smoking behavior of African Americans. Data for 14,397 African-American respondents (18-64 years old) to the National Health Interview Survey in the years 1990 through 1993 were examined in multivariate models. Age was the strongest predictor of smoking, and men were at least 1.75 times as likely as women to be smokers (P < .001). The Year 2000 goal of an 18% prevalence rate among African-American adults may not be attained without major community interventions focusing on male and middle-aged African Americans.

Prevalence and patterns of smoking in Delhi: cross sectional study.

To determine the prevalence and predictors of smoking in urban India. Cross sectional. Delhi, urban India, 1985-6. Random sample of 13,558 men and women aged 25-64 years. Smoking prevalence; subjects who were currently smoking and who had smoked > or = 100 cigarettes or beedis or chuttas in their lifetime were defined as smokers. 45% (95% confidence interval 43.8 to 46.2) of men and 7% (6.4 to 7.6) of women were smokers. Education was the strongest predictor of smoking, and men with no education were 1.8 (1.5 to 2.0) times more likely to be smokers than those with college education, and women with no education were 3.7 (2.9 to 4.8) times more likely. Among smokers, 52.6% of men and 4.9% of women smoked only cigarettes while the others also smoked beedi or chutta. Compared with cigarette smokers, people smoking beedi or chutta were more likely to be older and married; have lower education, manual occupations, incomes, and body mass index; and not drink alcohol or take part in leisure exercise. There are two subpopulations of smokers in urban India, and the prevention strategy required for each may be different. The educated, white collar cigarette smoker in India might respond to measures that make non-smoking fashionable, while the less educated, low income people who smoke beedi or chutta may need strategies aimed at socioeconomic improvement.