Lifetime high occupational physical activity and total and cause-specific mortality among 320 000 adults in the NIH-AARP study: a cohort study

ObjectivesWe examined the associations of history and duration in high occupational physical activity (OPA) with long-term total and cause-specific mortality.MethodsThe sample included 322 126 participants (135 254 women) from the National Institutes of Health–AARP Diet and Health Study, established in 1995–1996. History and duration in high OPA were reported by participants. All-cause, cardiovascular, cancer and other cause mortality records available through 31 December 2011.ResultsThe prevalence of high OPA was 52.1% in men and 16.1% in women. During 13.6 years (SD, 3.3) of follow-up, 73 563 participants (25 219 women) died. In age-adjusted models, the risk of death was higher among men (HR 1.14, 95% CI 1.12 to 1.16) and women (HR 1.22, 95% CI 1.18 to 1.26) with a history of high OPA. However, these associations were substantially attenuated in women (HR 1.04, 95% CI 1.00 to 1.07, an 81.8% attenuation) and eliminated in men (HR 1.02, 95% CI 0.99 to 1.04, 85.7% attenuation) after multivariable adjustments. Similar important attenuation results were found when examining duration in high OPA, as well as using cause-specific deaths as the outcomes. Educational attainment and smoking patterns were the main contributors in the excess mortality among people working in highly physically active jobs in both men and women.ConclusionParticipating in high OPA was not consistently associated with a higher mortality risk, after adjustments for education and smoking factors. Workers in high OPA should be aware that they might not be getting all well-known health benefits of being physically active if they are only very active at work.

Cigarette smoking patterns among U.S. military service members before and after separation from the military

U.S. military Service members have consistently smoked more than the general population and the prevalence of smoking is even higher among U.S. veterans. Our study examined cigarette smoking patterns among Service members before and after military separation to better understand the disproportionate rate of smoking among veterans. Data from the Millennium Cohort Study were used. All study participants were in the military at baseline and some transitioned from the military to civilian life during the observation period. We investigated any impact of military separation on smoking, as well as other potential risk factors for smoking. Overall, we observed higher smoking prevalence among veterans than Service members. Additionally, we found that Service members smoked more while approaching their separation from the military. Longitudinal analysis revealed military separation was not a risk factor for smoking, as we had hypothesized. Baseline smoking was the most influential predictor of current smoking status. Other significant factors included alcohol consumption, life stressors, and mental health conditions, among others. Military separation was not a risk factor for smoking. However, Service members in the process of transitioning out of the military, as well as high alcohol consumers and Service members with mental health conditions, may be at higher risk of smoking. Including smoking prevention/cessation programs in pre-separation counseling sessions and developing smoking screening and cessation programs targeting specific high-risk subgroups may reduce smoking among Service members and veterans.

The Greek smoking epidemic from a life-course perspective

Background Smoking rates in Greece are the highest recorded among OECD countries, but the historical and life-course evolution of smoking patterns is largely unknown. The present paper addresses this gap. Methods We produce nationally representative life-course trajectories of smoking and related mortality of eight generations of Greek men and women. We estimate the smoking–mortality correlation conditional on several confounders and project the estimates forward. Results We show that smoking prevalence among Greek men has plateaued at >60% for all but the youngest generation. For women, smoking prevalence is relatively lower, lags by several generations and follows a hump-shaped pattern. Smoking-attributable mortality is currently peaking for men (nearing 40% of total deaths) and is rising for women. We estimate that it takes ~20 years of smoking to maximize the smoking–mortality correlation (at 0.48 for men and 0.32 for women). Based on this estimation, we forecast that mortality rates will begin falling within the current decade. Conclusions The breadth of the Greek smoking epidemic has been high by international standards, reflecting the ineffective tobacco control efforts in the country. While smoking popularity fell during the Great Recession, policy vigilance is necessary to prevent a relapse once the economy recovers.

Risk of lung cancer among women in relation to lifetime history of tobacco smoking: A population-based case-control study in France (the WELCA study)

BACKGROUND This study aims to provide new insights on the role of smoking patterns and cigarette dependence in female lung cancer, and to examine differences by histological subtype. METHODS We conducted a population-based case-control study in the great Paris area among women including 716 incident cases diagnosed between 2014 and 2017 and 757 age-matched controls. Detailed data on smoking history was collected during in-person interviews to assess intensity and duration of tobacco smoking, time since cessation, smoking habits (depth of smoke inhalation, use of filter, type of tobacco, and type of cigarettes) and Fagerström test for cigarette dependence. The comprehensive smoking index (CSI), a score modelling the combined effects of intensity, duration and time since quitting smoking was determined for each subject. Multivariable logistic regression models were fitted to calculate odds ratios (ORs) and their confidence intervals (95%CI) of lung cancer associated with smoking variables. RESULTS Lung cancer risk increased linearly with intensity and duration of tobacco smoking while it decreased with time since cessation, to reach the risk in never-smokers after 20 years of abstinence. The combined effect of intensity and duration of tobacco smoking was more than multiplicative (p-interaction 0.012). The OR in the highest vs the lowest quartile of CSI was 12.64 (95%CI 8.50; 18.80) (p-trend < 0.001). The risk of small cell or squamous cell carcinomas increased with the CSI more sharply than the risk of adenocarcinomas. Deep smoke inhalation, dark vs blond tobacco, conventional vs light cigarettes, and unfiltered vs filtered cigarettes, as well as having mixed smoking habits, were found to be independent risk factors. Having high cigarette addiction behaviours also increased the risk after adjusting for CSI. CONCLUSION This study provides additional insights on the effects of tobacco smoking patterns on lung cancer risk among women.

Risk of lung cancer among women in relation to lifetime history of tobacco smoking: a population-based case-control study in France (the WELCA study)

Background This study aims to provide new insights on the role of smoking patterns and cigarette dependence in female lung cancer, and to examine differences by histological subtype. Methods We conducted a population-based case-control study in the great Paris area among women including 716 incident cases diagnosed between 2014 and 2017 and 757 age-matched controls. Detailed data on smoking history was collected during in-person interviews to assess intensity and duration of tobacco smoking, time since cessation, smoking habits (depth of smoke inhalation, use of filter, type of tobacco, and type of cigarettes) and Fagerström test for cigarette dependence. The comprehensive smoking index (CSI), a score modelling the combined effects of intensity, duration and time since quitting smoking was determined for each subject. Multivariable logistic regression models were fitted to calculate odds ratios (ORs) and their confidence intervals (95%CI) of lung cancer associated with smoking variables. Results Lung cancer risk increased linearly with intensity and duration of tobacco smoking while it decreased with time since cessation, to reach the risk in never-smokers after 20 years of abstinence. The combined effect of intensity and duration of tobacco smoking was more than multiplicative (p-interaction 0.012). The OR in the highest vs the lowest quartile of CSI was 12.64 (95%CI 8.50; 18.80) (p-trend < 0.001). The risk of small cell or squamous cell carcinomas increased with the CSI more sharply than the risk of adenocarcinomas. Deep smoke inhalation, dark vs blond tobacco, conventional vs light cigarettes, and unfiltered vs filtered cigarettes, as well as having mixed smoking habits, were found to be independent risk factors. Having high cigarette addiction behaviours also increased the risk after adjusting for CSI. Conclusion This study provides additional insights on the effects of tobacco smoking patterns on lung cancer risk among women.

Investigating smoking and nicotine dependence among people with severe mental illness during the COVID-19 pandemic: analysis of linked data from a UK Closing the Gap cohort

Summary Smoking rates are higher for people who use mental health services, which contributes substantially to health inequalities. Smoking can lead to worse COVID-19 outcomes, yet it remains unclear whether smoking has changed for people who use mental health services. We examined smoking patterns in a large clinical cohort of people with severe mental illness, before and during the pandemic. We found high levels of nicotine dependence and heavier patterns of smoking. Although some people had reported quitting, it is likely that smoking inequalities have become further entrenched. Mental health services should seek to mitigate this modifiable risk and source of poor health.

Cigarette and E-Cigarettes Dual Users, Exclusive Users and COVID-19: Findings from Four UK Birth Cohort Studies

Introduction: The relationship between current cigarette and electronic cigarette (e-cigarette) dual use, exclusive use and COVID-19-related measures are still unclear. This study aims to assess the association between different tobacco use patterns and coronavirus disease 2019 (COVID-19) symptoms, testing, self-reported infection and social distancing behaviors in the United Kingdom (UK). Methods: Data come from the first wave of the Centre for Longitudinal Studies (CLS) COVID-19 survey, comprising four birth cohorts (N = 13,077, aged 20–63 years) surveyed between 2 to 31 May 2020, during the COVID-19 pandemic. Sociodemographic characteristics and COVID-19-related outcomes (symptoms, testing, diagnosis and social distancing behaviors) were compared across different product user groups (non-users, exclusive cigarette users, exclusive e-cigarettes users and dual use) using Cochran–Mantel–Haenszel χ2 test. Multivariable logistic regression models were used to explore associations between COVID-19-related outcomes and different smoking patterns. Results: Across all four cohorts, 12.6% and 4.9% of the respondents were current exclusive cigarette and e-cigarette users, respectively, with approximately 3% of the respondents being dual users. Significant differences in prevalence were observed between different tobacco use patterns and COVID-19 symptoms (p = 0.02), self-reported infection (p = 0.04) and social distancing behaviors (p < 0.001). Current cigarette and e-cigarette dual use was associated with 2.15-fold higher odds for reporting COVID-19 infection (aOR = 2.15; CI [1.15–4.05]). Compliance of social distancing behaviors were the lowest for current dual users (aOR = 0.58; CI [0.41–0.83]) and exclusive cigarette users (aOR = 0.72; CI [0.63–0.92]). Conclusions: The findings highlight dual users’ higher prevalence of having COVID-19 symptoms, infection and incompliance of social distancing behaviors. Self-reported infection was associated with dual product use; dual users and exclusive cigarette users were linked to poor adherence to social distancing behaviors. Smoking cessation support and further monitoring on multiple tobacco use among these populations should be reinforced as preventive measures to tackle the pandemic.

Mental Distress and Psychological Disorders Related to COVID-19 Mandatory Lockdown

Background: Lockdown restrictions due to COVID-19 have affected many people's lifestyles and ability to earn a living. They add further distress to the lives of people in Syria, who have already endured 9 years of war. This study evaluates distress and the major causes of concerns related to COVID-19 during the full lockdown.Methods: Online questionnaires were distributed using SPTSS, K10, and MSPSS which were used with other demographic, war- and COVID-19-related questions that were taken from The (CRISIS) V0.1 Adult Self-Report Baseline Form.Results: Our sample included 5,588 with the mean age of 26.84 ± 7.815 years. Of those, only one case of COVID-19 was confirmed. Over 42.7% had two or more positive PTSD symptoms, 42.6% had moderate or severe mental disorder, but only 14.9% had low social support. Higher PTSD and K10 scores overall were seen in female participants and with most of war variables (P &lt; 0.05). Relationships with the partner being negatively affected and distress from a decline in ability to work and provide food were the most prominent.Conclusions: The indirect effects of COVID-19 are far more than that of the pathogen itself. A reduced ability to earn and to provide food were the main concerns indicated in this study. Relationships deteriorated in participants with high K10 and PTSD scores who also had more symptoms and used more hypnotics in the last four weeks. Smoking patterns were not related to K10 and PTSD. Social support played a role in reducing stress, but when relationships were affected, lower support was observed.

Use smoking contingent surveys and context to Characterize and Model Smoking Habits Tracked by Mobile Sensors in Naturalistic Environments (Preprint)

BACKGROUND There are 1.1 billion smokers worldwide and each year more than 8 million die prematurely because of cigarette smoking. Encouragingly, more than half of current smokers make a serious quit every year. Nonetheless, 90% of unaided quitters relapse within the first 4 weeks due to the lack of limited access to cost-effective and efficient smoking cessation tools in their daily life. OBJECTIVE This research work aims to 1)enable quantified monitoring of ambulatory smoking habits 24/7 in real life by exploiting continuous and automatic measurement techniques. 2) to identify and characterize smoking patterns with contextual signals collected in a longitudinal manner. This work also intends to provide guidance and insights on the design and deployment of technology-enabled smoking cessation applications in naturalistic environments. METHODS Specifically, a 4-week observational study consisting of 46 smokers was conducted in both working and personal life environments. In the study, an electric lighter, a smartphone, and an experimental application were used for tracking smoking events and acquiring concurrent contextual signals. Besides, the mobile technology was exploited to prompt smoking-continent ecological momentary assessment (EMA) surveys, sampling ambient social context. In the data analysis part, the smoking rate was assessed based on the timestamps of smoking and linked statistically to demographics, time, EMA surveys, and physiology. A multivariate model (Poisson mixed-effects model) to predict smoking rate in one-hour windows was developed to assess the contribution of each of the predictors. RESULTS In total, 8639 cigarettes and 1839 EMA surveys were tracked over 902 subject-days. Most smokers were found to have an inaccurate and often biased estimate of their daily smoking rate, compared to measured smoking rate. Specifically, 74%(34/46 )smokers made a more than one (on average 4.7 per day) cigarette wrong estimate, and 70%(32/46) had overestimated it. Based on the timestamp of tracked smoking events, smoking rates were visualized at different hours and were found to gradually increase and peak at 6 pm in the day. Additionally, a 1 to 2 hours shift in the smoking patterns was observed between weekdays and weekends. When moderate-and-heavy smokers were compared with light smokers, their ages (P<.05), FTND(P<.05), craving level(P<.001), enjoyment of cigarettes(P<.001), difficulty to resist smoking(P<.001), emotional valence(P<.001) and arousal(P<.001) were all found to be significantly different. In the Poisson mixed-effects model, the number of cigarettes smoked in a one-hour time window is highly dependent on smokers(P <0.001) and is explained by the hour(P <0.05) and age(P <0.01) factor. CONCLUSIONS The results confirm that smokers lack a good awareness of their smoking habits which are diverse and highly dependent on the context. Quantified smoking patterns upgrade our understanding of smoking behaviors in the context. These results also validate the techniques for smoking habits monitoring, pave the way for the design and deployment of technology-enabled smoking cessation applications. INTERNATIONAL REGISTERED REPORT RR2-http://dx.doi.org/10.1136/bmjopen-2018-028284