Addiction to the nicotine gum in never smokers

Abstract Background Addiction to nicotine gum has never been described in never smokers or in never users of tobacco. Methods Internet questionnaire in 2004–2006 in a self-selected sample of 434 daily users of nicotine gum. To assess dependence on nicotine gum, we used modified versions of the Nicotine Dependence Syndrome Scale (NDSS), the Fagerström Test for Nicotine Dependence and the Cigarette Dependence Scale. Results Five never smokers used the nicotine gum daily. They had been using the nicotine gum for longer than the 429 ever smokers (median = 6 years vs 0.8 years, p = 0.004), and they had higher NDSS-gum Tolerance scores (median = 0.73 vs = -1.0, p = 0.03), a difference of 1.5 standard deviation units. Two never smokers had never used smokeless tobacco, both answered "extremely true" to: "I use nicotine gums because I am addicted to them", both "fully agreed" with: "after a few hours without chewing a nicotine gum, I feel an irresistible urge to chew one" and: "I am a prisoner of nicotine gum". Conclusion This is to our knowledge the first report of addiction to nicotine gum in never users of tobacco. However, this phenomenon is rare, and although the long-term effect of nicotine gum is unknown, this product is significantly less harmful than tobacco.</p

Swedish snuff and incidence of cardiovascular disease. A population-based cohort study

<p>Abstract</p> <p>Background</p> <p>The relationship between smoking and an increased incidence of cardiovascular diseases is well known. Whether smokeless tobacco (snuff) is related to myocardial infarction (MI) or stroke is still controversial. Aim of this study was to explore whether snuff users have an increased incidence of MI or stroke.</p> <p>Methods</p> <p>A total of 16 754 women and 10 473 men (aged 45–73 years), without history of cardiovascular disease (CVD), belonging to the population-based "Malmö Diet and Cancer" study were examined. Incidence of MI and stroke were monitored over 10.3 years.</p> <p>Results</p> <p>Snuff was used by 737 (7.0%) men and 75 (0.4%) women, respectively. Among men, snuff was significantly associated with low occupation level, single civil status, high BMI and with current and former smoking. In women, snuff was associated with lower systolic blood pressure. A total of 964 individuals (3.5%), i.e.544 men (5.3%) and 420 (2.5%) women suffered a MI during the follow-up period. The corresponding numbers of incident stroke cases were 1048, i.e. 553 men (5.3%) and 495 (3.0%) women, respectively. Snuff was not associated with any statistically significant increased risk of MI or stroke in men or women. The relative risks (RR) in male snuff users compared to non-users were 1.05 (95% confidence interval (CI): 0.8–1.4, p = 0.740) for incident MI and 0.97 (0.7–1.4, p = 0.878) for stroke, after taking age and potential confounders into account. In women none of the 420 (2.5%) women who were snuff users had a MI and only one suffered a stroke during the follow-up.</p> <p>Conclusion</p> <p>Several life-style risk factors were more prevalent in snuff-users than in non-users. However, the present study does not support any relationship between snuff and incidence of cardiovascular disease in men.</p

Socio-demographic, lifestyle and health characteristics among snus users and dual tobacco users in Stockholm County, Sweden

<p>Abstract</p> <p>Background</p> <p>Socio-demographic and lifestyle characteristics of snus users have not been systematically described. Such knowledge is pivotal for tobacco control efforts and for the assessment of health effects of snus use.</p> <p>Methods</p> <p>A cross-sectional study was conducted, based on the Stockholm Public Health Survey, including a population-based sample of 34,707 men and women aged 18-84 years. We examined how socio-demographic, lifestyle and health-related characteristics were associated with the prevalence of current daily snus use, smoking and dual tobacco use. Logistic regression was used to calculate odds ratios of prevalence (ORs) and 95% confidence intervals (CIs).</p> <p>Results</p> <p>Low educational level (OR = 1.60, CI = 1.41-1.81 and OR = 1.49, CI = 1.17-1.89, for men and women respectively), as well as occupational class and low income were associated with snus use. Some unfavourable lifestyle characteristics, including risky alcohol consumption (males: OR = 1.81, CI = 1.63-2.02; females: OR = 1.79, CI = 1.45-2.20), binge drinking and low consumption of fruit and vegetables were also associated with snus use. In contrast, physical inactivity and overweight/obesity were not, nor was perceived health. The prevalence of smoking followed steeper gradients for social as well as lifestyle characteristics. Overweight and obese men were however less often smokers. Perceived poor general health and psychological distress were highly related to smoking. Social disadvantage, as well as unhealthy lifestyle and self-reported poor health were strongly associated with dual use. There were limited differences between men and women.</p> <p>Conclusions</p> <p>The social, lifestyle and health profiles of exclusive snus users in Stockholm County are less favourable than those of non-users of tobacco, but more advantageous than those of exclusive smokers. This knowledge should guide tobacco control measures as well as the interpretation of health risks linked to snus use.</p

A model of the PI cycle reveals the regulating roles of lipid-binding proteins and pitfalls of using mosaic biological data

The phosphatidylinositol (PI) cycle is central to eukaryotic cell signaling. Its complexity, due to the number of reactions and lipid and inositol phosphate intermediates involved makes it difficult to analyze experimentally. Computational modelling approaches are seen as a way forward to elucidate complex biological regulatory mechanisms when this cannot be achieved solely through experimental approaches. Whilst mathematical modelling is well established in informing biological systems, many models are often informed by data sourced from multiple unrelated cell types (mosaic data) or from purified enzyme data. In this work, we develop a model of the PI cycle informed by experimental and omics data taken from a single cell type, namely platelets. We were able to make a number of predictions regarding the regulation of PI cycle enzymes, the importance of the number of receptors required for successful GPCR signaling and the importance of lipid- and protein-binding proteins in regulating second messenger outputs. We then consider how pathway behavior differs, when fully informed by data for HeLa cells and show that model predictions remain consistent. However, when informed by mosaic experimental data model predictions greatly vary illustrating the risks of using mosaic datasets from unrelated cell types