The joint contribution of physical activity,insomnia symptoms,and smoking to the cost of short‐term sickness absence

Physical inactivity has been associated with both insomnia symptoms and smoking. Further, they are all independently associated with increased sickness absence (SA) from work. However, joint contribution of either physical activity (PA) with insomnia symptoms or with smoking to SA and, especially, their direct cost for the employer is poorly understood. Therefore, we aimed to examine these joint associations with short‐term (<15 days) SA cost. The Helsinki Health Study is a cohort of midlife employees of the City of Helsinki, Finland (baseline n = 8960, response rate 67%). During 2000‐2002, the participants were mailed a survey questionnaire that gathered information on health behavior and sociodemographic characteristics. SA, salary, and time of employment were followed up through the employer's personnel register between 2002 and 2016 for those with a written consent to the use of their register data (78% of the participants). Individual salary data were used to calculate the direct cost of short‐term SA. Data were analyzed with a two‐part model. Inactive participants with frequent insomnia symptoms had 2526€ (95% CI 1736€‐3915€) higher cost of short‐term SA than vigorously active participants without insomnia symptoms. Furthermore, inactive smokers had 4166€ (95% CI 2737€‐5595€) higher cost for the employer over the follow‐up than vigorously active non‐smokers. In conclusion, this study showed that PA and insomnia symptoms as well as PA and smoking are jointly associated with short‐term SA cost. The results emphasize encouraging employers to improve work environments so that they promote active lifestyle, good sleep, and non‐smoking in order to reduce the cost of SA.     

Electronic cigarette use in New South Wales,Australia: reasons for use,place of purchase and use in enclosed and outdoor places

Objective: To monitor patterns of use of e‐cigarettes to understand their potential impact on the New South Wales (NSW) population in Australia. Methods: A cross‐sectional online survey was carried out with a sample of adults in NSW in February 2016. Ever and past 30‐day use of e‐cigarettes, reasons for use, place of purchase and use within outdoor and enclosed public places were assessed along with sociodemographic characteristics. Results: Ever and past 30‐day use was reported by 13% and 4% of the sample, respectively. More than one‐third of participants did not purchase their own e‐cigarette (36.3%). The most frequently reported reason for using an e‐cigarette for smokers and ex‐smokers was to help quit smoking (45.3% and 44.7%, respectively) while for non‐smokers it was novelty (40%). E‐cigarettes were most commonly used at home (59.4%), in outdoor dining areas (36.8%) and in the workplace (27.8%). Conclusions: E‐cigarettes are being used by a small percentage of the NSW population. Reasons for e‐cigarette use varied with smoking status. Different sociodemographic characteristics were associated with ever and past 30‐day use of e‐cigarettes. E‐cigarettes are being used in areas that are covered by smoke‐free legislation. Implications for public health: Given e‐cigarettes are being used in smoke‐free areas, policy‐makers could take a precautionary approach by including e‐cigarette use under smoke‐free legislation.     

Perceived Discrimination as a Risk Factor for Use of Emerging Tobacco Products: More Similarities Than Differences Across Demographic Groups and Attributions for Discrimination

Background: Perceived discrimination has been associated with cigarette smoking and other substance use among members of disadvantaged minority groups. However, most studies have focused on a single minority group, have not considered the individual's attribution for the discrimination, and have not considered emerging tobacco products. Objective: This study examined the associations between perceived discrimination and use of six tobacco products (cigarettes, e-cigarettes, cigars, pipe tobacco, hookah, and smokeless tobacco) in a diverse sample of 1,068 adults in the United States. Methods: Participants were recruited on Amazon's Mechanical Turk and participated in an online survey. Logistic regression models were used to examine the association between perceived discrimination and use of each tobacco product. Interactions between discrimination and demographic characteristics, and between discrimination and perceived reasons for discrimination, were evaluated. Results: Controlling for age, sex, race/ethnicity, education, and socioeconomic status, perceived discrimination was a risk factor for current use of five of the six tobacco products. These associations were consistent across racial/ethnic groups and regardless of the individual's attribution for the reason for the discrimination. Conclusions: Results indicate that perceived discrimination is a risk factor for the use of multiple tobacco products, and that this association is not limited to particular demographic groups or types of discrimination. Public health programs could potentially reduce tobacco-related disease by teaching healthier ways to cope with discrimination.     

Prospective Longitudinal Substance Use Patterns in Patients Preparing for Hepatitis C Treatment

Objectives: This study prospectively examined the independent courses of alcohol, drugs, and smoking over 18 months in 154 patients preparing for hepatitis C virus (HCV) treatment in relation to functioning, negative coping, and satisfaction with quality of life in data collected from a randomized controlled trial of multiple-family group psychoeducation for patients preparing for HCV treatment. Patients with HCV who had consistent abstinence, consistent use, or achievement of abstinence after study entry were examined for outcomes pertaining to functioning in the context of HCV, negative coping, and satisfaction with quality of life. Methods: Of 309 patients considering treatment for HCV recruited from outpatient clinics at two major university medical centers and a Veterans Affairs medical center for a randomized controlled trial of a psychoeducation intervention, 154 completed baseline, 6-month, and 18-month assessments. The assessments included structured diagnostic interviews; questionnaires examining functioning, coping, and satisfaction with quality of life; medical record review; and urine testing for substances of abuse. For these analyses, substance use patterns were determined as consistent abstinence, consistent use, and achieving abstinence after study entry for alcohol and drug use and smoking. Results: The entire sample generally improved in all of these three outcomes over the course of the study. The course of alcohol, drugs, and smoking predicted HCV-related functioning, negative coping, and satisfaction with quality-of-life outcomes over 18 months. Three specific patterns of use (consistent abstinence, consistent use, and achievement of abstinence after study entry) of these substances diverged in association with outcomes related to functioning, negative coping, and satisfaction with quality of life, not only across trajectories over time within substance types but also among types of substances. Conclusions: This study's finding that different substances were associated with distinct clinical outcomes suggests the need to conceptually unbundle different types of substances in managing HCV. Future research is needed to examine the clinical utility of further unbundling these substances and also to further investigate effects of various amounts of use of these substances.     

A review of the evidence on smoking bans and incidence of heart disease

We update an earlier review of smoking bans and heart disease, restricting attention to admissions for acute myocardial infarction. Forty-five studies are considered. New features of our update include consideration of non-linear trends in the underlying rate, a modified trend adjustment method where there are multiple time periods post-ban, comparison of estimates based on changes in rates and numbers of cases, and comparison of effect estimates according to post-ban changes in smoking restrictiveness. Using a consistent approach to derive ban effect estimates, taking account of linear time trends and control data, the reduction in risk following a ban was estimated as 4.2% (95% confidence interval 1.8–6.5%). Excluding regional estimates where national estimates are available, and studies where trend adjustment was not possible, the estimate reduced to 2.6% (1.1–4.0%). Estimates were little affected by non-linear trend adjustment, where possible, or by basing estimates on changes in rates. Ban effect estimates tended to be greater in smaller studies, and studies with greater post-ban changes in smoking restrictiveness. Though the findings suggest a true effect of smoking bans, uncertainties remain, due to the weakness of much of the evidence, the small estimated effect, and various possibilities of bias.