The effect of work environment and heavy smoking on the social inequalities in smoking cessation

Predicting the first smoking lapse during a quit attempt: A machine learning approach

BACKGROUND

Just-in-time adaptive interventions (JITAI) aim to prevent smoking lapse using tailored support delivered via mobile technology in the moments when it is most needed. Effective smoking cessation JITAI rely on the development of accurate decision rules that determine when someone is most likely to lapse. The primary goal of the present study was to identify the strongest predictors of first lapse among smokers undergoing a quit attempt.

METHODS

Smokers attending a clinic-based smoking cessation program (n = 74) were asked to complete ecological momentary assessments five times daily on study-provided smartphones for 4 weeks post-quit. A three-stage modeling process utilized Cox proportional hazards regression to examine time to lapse a function of 31 predictors. First, univariate models evaluated the relationship between each predictor and time to lapse. Second, the elastic net machine learning algorithm was used to select the best predictors. Third, backwards elimination further reduced the set of predictors to optimize parsimony.

RESULTS

Univariate models identified seven predictors significantly related to time to lapse. The elastic net algorithm retained five: perceived odds of smoking today, confidence in ability to avoid smoking, motivation to avoid smoking, urge to smoke, and cigarette availability. The reduced model demonstrated inadequate approximation to the non-penalized baseline model.

CONCLUSIONS

Accurate estimation of moments of high risk for smoking lapse remains an important goal in the development of JITAI. These results demonstrate the utility of exploratory data-driven approaches to variable selection. The results of this study can inform future JITAI by highlighting targets for intervention.

Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse

Introduction

Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological momentary assessment (EMA). Understanding these predictors may aid in developing interventions for smoking lapse prevention.

Methods

In a randomized-controlled smoking cessation trial, smartphone-based EMAs were collected from 92 participants following a scheduled quit date. This secondary analysis utilized elastic net-penalized cox proportional hazards regression and model approximation via backward elimination to (1) optimize a predictive model of time to first lapse and (2) simplify that model to its core constituent predictors to maximize parsimony and generalizability.

Results

Elastic net proportional hazards regression selected 17 of 26 possible predictors from 2065 EMAs to model time to first lapse. The predictors with the highest magnitude regression coefficients were having consumed alcohol in the past hour, being around and interacting with a smoker, and having cigarettes easily available. This model was reduced using backward elimination, retaining five predictors and approximating to 93.9% of model fit. The retained predictors included those mentioned above as well as feeling irritable and being in areas where smoking is either discouraged or allowed (as opposed to not permitted).

Conclusions

The strongest predictors of smoking lapse were environmental in nature (e.g., being in smoking-permitted areas) as opposed to internal factors such as psychological affect. Interventions may be improved by a renewed focus of interventions on these predictors.

Implications

The present study demonstrated the utility of machine learning algorithms to optimize the prediction of time to smoking lapse using EMA data. The two models generated by the present analysis found that environmental factors were most strongly related to smoking lapse. The results support the use of machine learning algorithms to investigate intensive longitudinal data, and provide a foundation for the development of highly tailored, just-in-time interventions that can target on multiple antecedents of smoking lapse.

The prevalence of and factors associated with urinary cotinine-verified smoking in Korean adults: The 2008-2011 Korea National Health and Nutrition Examination Survey

Background

Smoking rate based on self-reporting questionnaire might be underestimated. Cotinine is the principal metabolite of nicotine and is considered an accurate biomarker of exposure to cigarette smoke.

Objectives

This study evaluated the prevalence of and factors associated with urinary cotinine-verified smoking in Korean adults.

Methods

We analyzed data from 12,110 adults in the 2008–2011 Korea National Health and Nutrition Examination Survey (KNHANES), using three threshold levels of urinary cotinine ≥100ng/ml, ≥50ng/ml, and ≥30ng/ml.

Results

The weighted prevalence of urinary cotinine levels of ≥100, ≥50, and ≥30 ng/mL in the whole study population was 34.7%, 37.1%, and 41.1%, respectively. Male sex, younger age, elementary school graduation, household income in the ≤24th percentile, service and sales workers and assembly workers, and high-risk alcohol drinking were associated with a higher prevalence of urinary cotinine level of ≥ 50 or 30 ng/mL, after we adjusted for age, sex, education level, number of family members, household income, occupation, and alcohol drinking.

Logistic regression analyses were performed using the aforementioned variables as covariates to identify factors independently associated with cotinine-verified smoking. Men had a higher risk than women of having a urinary cotinine level of ≥50 ng/mL (OR 4.67, 95% CI 4.09–5.32, p < 0.001). When subjects ages 19–29 years were used as controls, adults ages 30–39 years had a 1.19-fold (CI 1.02–1.39, p = 0.026) higher risk of having a urinary cotinine level of ≥50 ng/mL. College graduates had a 32% lower risk of having a urinary cotinine level of ≥50 ng/mL than elementary school graduates (p < 0.001).

A household income in the 25–49th percentile (OR 0.82, 95% CI 0.69–0.98, p = 0.026), 50–74th percentile (OR 0.64, 95% CI 0.53–0.76, p < 0.001), or ≥75th percentile (OR 0.64, 95% CI 0.53–0.77, p < 0.001) was associated with a lower risk of having a urinary cotinine level of ≥50 ng/mL compared to a household income in the ≤24th percentile. High-risk (OR 2.75, 95% CI 2.37–3.18, p < 0.001) and intermediate-risk (OR 2.04, 95% CI 1.82–2.30, p < 0.001) alcohol drinking were associated with having a urinary cotinine level of ≥50 ng/mL compared to low-risk alcohol drinking. Similar to the results of the logistic regression analyses of urinary cotinine ≥50 ng/mL, male sex, younger age, elementary school education, household income in the ≤24th percentile, and high-risk alcohol drinking were significantly associated with having a urinary cotinine level of ≥30 ng/mL. Service and sales workers (OR 1.22, 95% CI 1.01–1.48, p = 0.041) had a significantly higher risk of having a urinary cotinine level of ≥30 ng/mL.

Conclusions

Based on a threshold urinary cotinine level of 50 ng/mL, the prevalence of cotinine-verified smoking in a representative sample of Korean adults was 37.1% (men 52.7%, women 15.4%). Younger age, male sex, low education level, service and sales workers, low household income, and high-risk alcohol drinking were associated with the risk of smoking.

Income-related inequality in smoking cessation among adult patients with cardiovascular disease: a 5-year follow-up of an angiography intervention in Luxembourg

BACKGROUND

Smoking contributes to cardiovascular diseases (CVD), a leading cause of death and a large source of healthcare costs in Western countries. We examined the association between income and smoking cessation among smokers who underwent coronary angiography at the National Institute for Cardiac Surgery and Interventional Cardiology in Luxembourg.

METHODS

Data were derived from a follow-up study conducted in 2013/2014 among 4391 patients (of which 1001 patients were smokers) at the time of coronary angiography in 2008/2009. Four logistic regression models were applied. In three models, the predictor was income and the covariates were sex, age, nationality, marital status, diagnosis, body mass, physical activity, and awareness of tobacco as a cardiovascular (CV) risk factor. In the other model, the predictor was an interaction term composed of income and awareness of tobacco as a CV risk factor; the other variables were covariates.

RESULTS

Among patients who were current smokers at baseline, 43.2% were current smokers at follow-up and 56.8% had quit smoking. In the multivariate logistic models, quitting smoking was associated with income even after controlling for socio-demographic, diagnostic, and behavioural risk factors. In the full model, the odds of quitting smoking among patients in the two highest income categories remained significant when compared to patients in the lowest income category: odds ratio (OR) = 2.8; 95% confidence interval (CI), 1.3-6.1 and OR = 2.8; 95% CI, 1.2-6.5, respectively. In the full model with an interaction term, quitting smoking was only associated with income when patients knew tobacco was a CV risk factor. The odds of smoking cessation were 5.62 (95% CI: 2.13-14.86) and 3.65 (95% CI: 1.51-8.86) times for patients with annual incomes of 36,000-53,999€ and ≥54,000€, respectively), compared to those for patients with an annual income of <36,000€.

CONCLUSIONS

This study highlights the influence of income on behaviours regarding CVD risk factors after a major CVD event. Patients in the highest income groups were more likely to quit smoking, although only when they were aware of tobacco as a CV risk factor. Therefore, intervention strategies targeting lower income groups should be implemented in major health facilities.

Clustering of chronic disease risk factors with tobacco smoking habits among adults in the work place in Sousse, Tunisia

Introduction

The aim of our study was to explore the major non-communicable risk factors (unhealthy diet, sedentarily, alcohol consumption) of smokers and nonsmokers in workplaces.

Methods

A cross-sectional study was derived from an initial assessment in workplaces which was part of a community-based intervention to prevent chronic disease risk factors conducted in 2009 in the region of Sousse, Tunisia. The surveyed subjects were employees in six factories spread across three delegations in the region. Overall, 1770 of 2250 employees participated in the assessment. In this study, the clustering of non-communicable diseases risk factors with smoking habits was made only for male employees including in this study 1099 among 2250. Data were collected at worksites by a questionnaire, via interview or self-report. The main items assessed socio-demographics characteristics, smoking status, eating habits, level of physical activity and alcohol use of the participants.

Results

The percentage of male smokers was 54.0%(n=594). Their average age of daily smoking initiation was 19.22 (±4.24 years). The percentage of male smokers consuming 5 fruits and vegetables per day was significantly lower than nonsmokers (57.2% vs 63.5%, p=0.04). The proportion of male smokers consuming alcohol was about three times that of nonsmokers (16.5% vs 5.8%, p=0.001). The proportion of male employees who agree with anti-smoking laws in work places was higher for nonsmokers than for smokers.

Conclusion

A strong association existed between smoking and risky lifestyles factors in the work place. Such findings are potentially useful in directing intervention efforts regarding smoking cessation in occupational settings.

Understanding socio-cultural influences on smoking among older Greek-Australian smokers aged 50 and over: facilitators or barriers? A qualitative study

Smokers of all ages can benefit by quitting, but many smokers continue to smoke. Older Greek-Australian smokers, one of the largest ethnic groups in Australia, have higher rates of smoking than other groups of older Australians. This qualitative study aimed to explore older Greek-Australians’ views about socio-cultural influences on their smoking. A snowball sampling technique was used to identify twenty Greek–Australian smokers (12 males and eight females), aged ≥ 50 years. They were recruited through the Greek Orthodox Community Center of South Australia (GOCSA). Qualitative data were collected using semi-structured face-to-face interviews. The audio-taped interviews were translated and transcribed, and then analysed using content analysis. Results suggested that smoking was considered as the “norm” by older Greek-Australian smokers. There were four groups embedded in the participants’ social networks that were reported to be important in relation to either encouraging smoking or, smoking abstinence. These support groups included: family members, friends, the Greek community, and physicians. Smokers’ family members (brothers) and friends were identified as facilitators of smoking whereas non-smoker family members (children and spouses) were reported as providing barriers to smoking. Different approaches were used by supporter groups to assist smokers to quit smoking—both planned and unplanned. Knowledge, planning of social and cultural supports, and addressing barriers to smoking cessation are a important part of health planning for older Greek-Australians. Social norms, including those arising from social interactions, and predisposing traits can influence smoking behaviour. Addressing the specific barriers to smoking cessation of older Greek-Australians is critical to addressing the risk for chronic disease in this group.

Home matters: work and household predictors of smoking and cessation among blue-collar workers

OBJECTIVE

This study examined the joint influence of work- and household-related variables on smoking behavior among a population representative sample of blue-collar workers with live-in partners.

METHODS

The study used data on 1389 blue-collar workers from the Tobacco Use Supplement to the United States Current Population Survey 2002 to 2003 longitudinal overlap sample. Unadjusted and adjusted logistical regression analyses, which employed sampling and replicate weights to account for sampling design, were run to estimate independent and joint effects of the predictors.

RESULTS

In adjusted analyses, partner smoking (OR=4.97, 95%CI=3.02-8.18) and complete and partial home smoking policy (OR=0.16, 95%CI=0.09-0.29 and OR=0.39, 95%CI=0.23-0.68, respectively) were significant predictors of smoking status, but worksite smoking policies and presence of a young child under 5 in the household were not (p>0.05). Baseline complete home smoking ban was a significant predictor of subsequent cessation (OR=3.49, 95%CI=1.19-10.23), while partner smoking status, workplace smoking policy, and the presence of a young child in the home did not predict cessation (p>0.05).

CONCLUSION

Household-related variables were significant predictors of smoking status and cessation among blue-collar workers. Current efforts to decrease smoking in this group, which are mostly focused on work-related risk factors, should consider how to incorporate household risk factors.

Psychosocial work environment factors and weight change: a prospective study among Danish health care workers

Background

Lifestyle variables may serve as important intermediate factors between psychosocial work environment and health outcomes. Previous studies, focussing on work stress models have shown mixed and weak results in relation to weight change. This study aims to investigate psychosocial factors outside the classical work stress models as potential predictors of change in body mass index (BMI) in a population of health care workers.

Methods

A cohort study, with three years follow-up, was conducted among Danish health care workers (3982 women and 152 men). Logistic regression analyses examined change in BMI (more than +/− 2 kg/m²) as predicted by baseline psychosocial work factors (work pace, workload, quality of leadership, influence at work, meaning of work, predictability, commitment, role clarity, and role conflicts) and five covariates (age, cohabitation, physical work demands, type of work position and seniority).

Results

Among women, high role conflicts predicted weight gain, while high role clarity predicted both weight gain and weight loss. Living alone also predicted weight gain among women, while older age decreased the odds of weight gain. High leadership quality predicted weight loss among men. Associations were generally weak, with the exception of quality of leadership, age, and cohabitation.

Conclusion

This study of a single occupational group suggested a few new risk factors for weight change outside the traditional work stress models.

Smoking and workers’ autonomy: A qualitative study on smoking practices in manual work

A massive amount of research has brought out the association of daily smoking with social class. Smoking remains very common in the most disadvantaged groups, but it has also maintained its popularity among manual workers. The starting point of the article is that what needs to be taken into account in explaining the social differentiation of smoking is the social context in which smoking takes place. The study is based on interviews of daily smokers, ex-smokers and occasional smokers from different occupational backgrounds. In this article, the focus is on manual workers ( N = 19), and the main interest is in the meaning of smoking in working-class contexts and how it is attached to daily routines and social settings in manual work. Theoretically, the study draws on the pragmatist idea of habits and how they are formed in accordance with the context. As a shared ritual, smoking was a self-evident part of daily routines at the workplaces under scrutiny. The study shows how smoking was a legitimate way to challenge the official rules and to make the work more bearable by increasing social contacts and a sense of belonging. Paradoxically, smoking was to a great extent an unquestioned routine, but at the same time it increased the autonomy of the workers in terms of their daily tasks.

Socioeconomic disparities in quit intentions, quit attempts, and smoking abstinence among smokers in four western countries: findings from the International Tobacco Control Four Country Survey

INTRODUCTION

Lower socioeconomic status (SES) groups have higher rates of tobacco use, are less likely to successfully quit, and may also be less likely to intend or attempt to quit. However, results are inconsistent for some outcomes, and little is known about how socioeconomic disparities vary across countries and over time.

METHODS

This study examined the associations between SES and quitting-related behaviors among representative samples of smokers in Canada, the United States, the United Kingdom, and Australia, using data from the first five waves (2002-2006/2007) of the International Tobacco Control Four Country Survey (35,532 observations from 16,458 respondents). Generalized estimating equations modeling was used to examine whether education and income were related to intentions to quit, incidence of quit attempts, and smoking abstinence. Potential differences in the associations over time and across countries were also considered.

RESULTS

Smokers with higher education were more likely to intend to quit, to make a quit attempt, and to be abstinent for at least 1 and 6 months; smokers with higher income were more likely to intend to quit and to be abstinent for at least 1 month. Some between-country differences were observed: U.K. and U.S. smokers were less likely to intend to quit than Australians and Canadians; and, although U.K. respondents were least likely to attempt to quit, those that did were more likely to be abstinent.

DISCUSSION

The results suggest that socioeconomic disparities exist at multiple stages in the path to smoking cessation. Potential effects on socioeconomic disparities should be considered when implementing cessation interventions.

Social inequalities in quitting smoking: what factors mediate the relationship between socioeconomic position and smoking cessation?

BACKGROUND

Smokers from lower socio-economic groups are less likely to be successful in a quit attempt than more affluent smokers, even when they access smoking cessation services.

METHODS

Data were collected from smoking cessation service users from three contrasting areas of Great Britain-Glasgow, North Cumbria and Nottingham. Routine monitoring data were supplemented with CO-validated smoking status at 52-week follow-up and survey data on socio-economic circumstances and smoking-related behaviour. Analysis was restricted to the 2397 clients aged between 25 and 59.

RESULTS

At 52-week follow-up, 14.3% of the most affluent smokers remained quit compared with only 5.3% of the most disadvantaged. After adjustment for demographic factors, the most advantaged clients at the English sites and the Glasgow one-to-one programme were significantly more likely to have remained abstinent than those who were most disadvantaged [odds ratio: 2.5, confidence interval (CI): 1.4-4.7 and 7.5 CI: 1.4-40.3, respectively). Mechanisms producing the inequalities appeared to include treatment compliance, household smokers and referral source.

CONCLUSIONS

Rather than quitting smoking, disadvantaged smokers quit treatment. More should be done to encourage them to persevere through the first few weeks. Other causes of inequalities in quitting varied with the service provided.

Impact of a statewide Internet-based tobacco cessation intervention

Background

An increasing number of people have access to the Internet, and more people are seeking tobacco cessation resources online every year. Despite the proliferation of various online interventions and their evident acceptance and reach, little research has addressed their impact in the real world. Typically, low response rates to Internet-based follow-up surveys generate unrepresentative samples and large confidence intervals when reporting results.

Objectives

The aim of this study was to achieve a high response rate on follow-up evaluation in order to better determine the impact of an Internet-based tobacco cessation intervention provided to tobacco users in Minnesota, United States.

Methods

Participants included 607 men and women aged 18 and over residing in Minnesota who self-reported current tobacco use when registering for an Internet-based tobacco cessation program between February 2 and April 13, 2004. Participants were given access to an interactive website with features including social support, expert systems, proactive email, chat sessions, and online counselors. Mixed-mode follow-up (online survey with telephone survey for online nonrespondents) occurred 6 months after registration.

Results

Of the study participants, 77.6% (471/607) responded to the 6-month follow-up survey (39.4% online and 38.2% by telephone). Among respondents, 17.0% (80/471, 95% CI = 13.6%-20.4%) reported that they had not smoked in the past 7 days (observed rate). Assuming all nonrespondents were still smoking (missing=smoking rate), the quit rate was 13.2% (80/607, 95% CI = 10.5%-15.9%).

Conclusions

This mixed-mode follow-up survey of an online smoking cessation program achieved a high response rate and provides a more accurate estimate of long-term cessation rates than has been previously reported. Quit rates for the Internet-based tobacco cessation program were higher than those expected for unassisted quit attempts and are comparable to other evidence-based behavioral interventions. The similarities between quit rates demonstrates that an Internet-based cessation program may have as great an impact as, and can have wider reach than, other cessation programs such as those delivered by telephone. With over 100000 people having visited the website and over 23000 having registered, a 6-month self-reported quit rate of 13.2% suggests that the quitplan.com program helped over 3000 Minnesotans remain tobacco free for at least 6 months. Results of this study suggest that an Internet-based cessation program is a useful tool in states’ efforts to provide comprehensive cessation tools for smokers.