Smoking patterns, quit behaviors, and smoking environment of workers in small manufacturing companies

Tobacco Quitline utilization compared with cigarette smoking prevalence in Virginia across rurality and Appalachian Status, 2011-2019

Introduction

While cigarette smoking rates have declined, rural and Appalachian populations in the United States have not seen similar decreases. Quitline programs are promising strategies in reducing disparities in these areas, but research on their usage is limited.

Methods

We employed Small Area Estimation on the Virginia Behavioral Risk Factor Surveillance System (2011-2019) to estimate county-level smoking prevalence and utilized The Quit Now Virginia Quitline data (2011-2019) to estimate Quitline users. We analyzed differences in Quitline utilization by rurality and Appalachian status using statistical t-tests. Stepwise regression assessed the absolute estimate of county features, including poverty rate, tobacco retailer density, physician availability, coal mining industry, and tobacco agriculture, on Quitline usage.

Results

While the average smoking rate overall was 15.3 %, only 7.4 % of smokers accessed Quitline services from 2011 to 2019. Appalachian regions exhibited higher smoking rates (20.9 %) and lower quitline usage (4.8 %) compared to non-Appalachian areas (14 % smoking prevalence, 8 % quitline usage). Rural regions had higher smoking prevalence (19.0 %) than urban areas (12.9 %), but no significant difference in Quitline utilization (7.6 % vs. 7.2 %, p = 0.7). Stepwise regression revealed counties with more tobacco agriculture had 3.2 % (p = 0.04) lower Quitline utilization. Also, more physicians availability in the county was associated with 3.9 % higher Quitline usage (p = 0.03) and Appalachian counties exhibited a 3.6 % lower Quitline usage rate compared to non-Appalachian counties.

Conclusion

A significant gap exists between cigarette smoking prevalence and Quitline utilization, particularly in underserved rural and Appalachian areas, despite no clear barriers to accessing this remote cessation resource.

Implication

The study underscores persistent disparities in smoking rates, with rural and Appalachian regions in the United States facing higher smoking prevalence and limited utilization of Quitline services. Despite no clear barriers to access, the gap between smoking prevalence and Quitline usage remains significant, particularly in underserved areas. Tailoring interventions to address regional disparities and factors like tobacco agriculture and physician availability is essential to reduce smoking rates and improve Quitline utilization in these communities.

Occupational Health Nurses' Self-Efficacy in Implementing Smoking Cessation Interventions for Workers: A Manufacturing Company Quality Improvement Project

BACKGROUND

Effective smoking cessation interventions (SCIs) are urgently needed for the working population where smoking continues at high rates. Occupational health nurses (OHNs) could be effective in providing SCI, but self-efficacy was found to be a major barrier. The purpose of this study was to improve the delivery of SCI to those who smoke in the workplace and to explore nurse self-efficacy.

METHODS

Pretest and posttest were conducted on two groups, OHNs (n = 5) and smokers (n = 11) working at U.S. manufacturing facilities. OHNs were trained on motivational interviewing (MI) techniques who then recruited smokers to help them practice their newly acquired skills. The two groups were measured by Likert-type scale for OHN self-efficacy and smoker level of change toward quitting.

FINDINGS

Paired t-tests detected statistically significant differences in OHN's preintervention and postintervention self-efficacy scores, t(4) = -4.46, p < .001,; d = 2.92) and smokers' preintervention and postintervention stage of change toward quitting scores, t(10) = -9.07, p < .001,; d = 2.09), suggesting that the training and MI intervention were effective in increasing OHN self-efficacy and smokers' motivation to change.

CONCLUSION/APPLICATION TO PRACTICE

This quality improvement (QI) project indicated smokers can be successfully recruited and counseled using MI techniques, while simultaneously improving OHN self-efficacy toward helping patients. Theory-based applications brought OHNs and smokers together in a new paradigm resulting in positive changes for both. Secondary findings in the reverse nurse-patient role revealed success in an innovative recruitment method for smoking cessation.

What is the most important determinant of cardiometabolic risk in 60-65-year-old subjects: physical activity-related behaviours, overall energy expenditure or occupational status? A cross-sectional study in three populations with different employment status in Poland

OBJECTIVES

The aim of the study was to determine whether cardiovascular risk factors may differ according to occupational status and whether physical activity related to total energy expenditure (PA-EE) and related to health-related behaviours (PA-HRB) is associated with common cardiovascular risk factors or metabolic syndrome in pre-elderly subjects.

METHODS

Three hundred subjects aged 60-65 were recruited and divided into three equal groups of white-collar, blue-collar workers and unemployed subjects; 50% were women. The subjects were tested for major cardiovascular risk factors such as smoking, anthropometric indices, blood pressure, lipid levels, glucose, uric acid and homocysteine. PA-EE and PA-HRB were assessed with PA questionnaires.

RESULTS

Blue-collar workers displayed higher anthropometric indices, blood pressure and higher PA-EE in comparison with other two groups. PA-HRB had a positive impact on body mass indices, lipids, glucose, uric acid and the prevalence of metabolic syndrome, with no such relationship observed for PA-EE.

CONCLUSIONS

The greatest cardiovascular risk was observed in the blue-collar workers group. Only PA-HRB had a positive association with cardiometabolic risk profile. No relationship was observed for PA-EE. Thus, promoting everyday life and leisure time PA behaviours is crucial for preventing cardiometabolic risk in pre-elderly subjects, even in blue-collar workers with high work-related EE.

Factors associated with different smoking statuses among Malaysian adolescent smokers: a cross-sectional study

BACKGROUND

This study focused on the associations between socioeconomic status (SES) and adolescent smoking among secondary school students (13 to 17 years) in the Federal Territory of Kuala Lumpur, Malaysia. Our objective was to evaluate the relationships between adolescent demographics, socioeconomic status and smoking status.

METHODS

The survey data were based on baseline findings from a cross-sectional study (N = 422 adolescents). Chi-square test was used to assess the relationship between demographic characteristics, socioeconomic status (household monthly income and daily allowance) and adolescent smoking status. Exhaled carbon monoxide (CO) reading and the Hooked on Nicotine Checklist (HONC) were used to evaluate adolescent smoking status. A Multivariate Multinomial Logistic Regression (MMLR) was employed to test selected demographic and socioeconomic predictors of smoking status.

RESULTS

Of the 422 adolescents (M age = 15.58, SD = 1.24), more than half of the participants initiated smoking between 13 to 17 years old (59.0%). A total of 308 (73.0%) were electronic cigarette users, with more than 50% comprising of single users. The mean CO reading was 2.14 ppm with 78.0% of adolescents scoring more than 0 on the Hooked on Nicotine Checklist (HONC). Males and participants aged 15 and 16 years were at increased risks of sole CC smoking. Meanwhile, males, those who are not hooked on smoking and with a non-smoker CO reading were at increased risks of sole EC smoking. Finally, Bumiputeras were at less risk of EC smoking.

CONCLUSIONS

Demographic variables such as age, gender and ethnicity predicted smoking status predicted smoking risk, but not socioeconomic factors. The findings allow policy makers to target specific high-risk demographic groups when designing smoking cessation programs for adolescents.

Skin Cancer Prevention Behaviors Among Agricultural and Construction Workers in the United States, 2015

Introduction

Nearly 5 million people are treated for skin cancer each year in the United States. Agricultural and construction workers (ACWs) may be at increased risk for skin cancer because of high levels of ultraviolet radiation exposure from the sun. This is the first study that uses nationally representative data to assess sun-protection behaviors among ACWs.

Methods

We analyzed data from the 2015 National Health Interview Survey Cancer Control Supplement to examine the prevalence of sun-protection behaviors among ACWs. We calculated national, weighted, self-reported prevalence estimates. We used χ² tests to assess differences between ACWs by industry and occupation.

Results

Most of the 2,298 agricultural and construction workers studied were male (by industry, 72.4% in agriculture and 89.3% in construction; by occupation, 66.1% in agriculture and 95.6% in construction) and non-Hispanic white. About one-third had at least 1 sunburn in the past year. The prevalence of sunscreen use and shade seeking was low and did not significantly differ among groups, ranging from 15.1% to 21.4% for sunscreen use and 24.5% to 29.1% for shade seeking. The prevalence of wearing protective clothing was significantly higher among agricultural workers than among construction workers by industry (70.9% vs 50.7%) and occupation (70.5% vs 53.0%).

Conclusion

Our findings could be used to improve occupational health approaches to reducing skin cancer risk among ACWs and to inform education and prevention initiatives addressing skin cancer. Sun-safety initiatives may include modifying work sites to increase shade and adding sun safety to workplace policies and training. Employers can help reduce occupational health inequities and protect workers by creating workplaces that facilitate sun protection.