Background: Cigarette smoking exacerbates the estimated glomerular filtration rate (eGFR) decline in nondiabetic chronic kidney disease (CKD) despite the kidney p

/pdf/cigarette-smoking-attenuates-kidney-protection-by-3bmqyouwde.pdf

Cigarette Smoking Attenuates Kidney Protection by Angiotensin-Converting Enzyme Inhibition in Nondiabetic Chronic Kidney Disease

Introduction 
The aim of this study was to identify factors associated with the results of smoking cessation attempts.


Methods 
Data were collected in Clermont-Ferrand from a smoking cessation clinic between 1999 and 2009 (1,361 patients). Smoking cessation was considered a success when patients were abstinent 6 months after the beginning of cessation. Multivariate logistic regression was used to investigate the association between abstinence and different factors.


Results 
The significant factors were a history of depression (ORadjusted = 0.57, p = 0.003), state of depression at the initial consultation (ORa = 0.64, p = 0.005), other psychoactive substances (ORa = 0.52, p<0.0001), heart, lung and Ear-Nose-Throat diseases (ORa = 0.65, p = 0.005), age (ORa = 1.04, p<0.0001), the Richmond test (p<0.0001; when the patient’s motivation went from insufficient to moderate, the frequency of abstinence was twice as high) and the Prochaska algorithm (p<0.0001; when the patient went from the ‘pre-contemplation’ to the ‘contemplation’ level, the frequency of success was four times higher). A high score in the Richmond test had a greater impact on success with increasing age (significant interaction: p = 0.01). In exclusive smokers, the contemplation level in the Prochaska algorithm was enough to obtain a satisfactory abstinence rate (65.5%) whereas among consumers of other psychoactive substances, it was necessary to reach the preparation level in the Prochaska algorithm to achieve a success rate greater than 50% (significant interaction: p = 0.02).


Conclusion 
The psychological preparation of the smoker plays a critical role. The management of smoking cessation must be personalized, especially for consumers of other psychoactive substances and/or smokers with a history of depression.

Success rates in smoking cessation: psychological preparation plays a critical role and interacts with other factors such as psychoactive substances

Concerns about postcessational weight gain might hamper rather than encourage smokers to quit smoking. We conducted a comprehensive multi-institutional smoking cessation program for health care and industrial workers (n = 654) employed at University Hospital Basel (Switzerland) and two local health industry companies (Novartis International AG, F. Hoffmann-La Roche AG). The program contained counselling with an option of pharmacological support. Changes in body weight were observed during 24 months of follow-up. Factors associated with longitudinal weight gain (>5 % of baseline weight) were identified by cox-regression analysis. In 51 % of permanent quitters no significant changes of mean body weight were observed after 12 (0.52 kg, SD ±2.87 kg) and 24 months (0.40 kg, SD ± 2.99 kg). Marked weight gain following smoking cessation was characterized by a wide margin of changes. In more than a half of former smokers (58 %) weight increases were moderate ( 10 kg) were seen in only 10 % of quitters. Lower baseline BMI (HR 0.60, 95 % CI 0.40- 0.80, p = 0.03), daily consumption of less than ten cigarettes (HR 0.53, 95 % CI 0.27- 0.63, p = 0.04) and ischemic cardiopathy (HR 0.21, 95 % CI 0.07-0.62; p < 0.01) were associated with a lower risk for weight gain. Employees with lower educational levels (HR 2.60, 95 % CI 1.60-5.50, p < 0.01), diabetes mellitus (HR 3.05, 95 % CI 2.20-8.06, p = 0.02) and those smoking to reduce boredom in life (HR 1.68, 95 % CI 1.21-2.33, p < 0.01) were at highest risk. Marked postcessational weight gain occurs less often than expected, but remains difficult to be predicted. Our findings might be helpful to alleviate weight concerns in the average smoker willing to quit.

/pdf/predictors-of-marked-weight-gain-in-a-population-of-health-3to0b7ijba.pdf

Predictors of marked weight gain in a population of health care and industrial workers following smoking cessation

For the past 30 years, research examining predictors of successful smoking cessation treatment response has focused primarily on clinical variables, such as levels of tobacco dependence, craving, and self-efficacy. However, recent research has begun to determine biomarkers (such as genotype, nicotine and metabolite levels, and brain imaging findings) that may have utility in predicting smoking cessation. For genotype, genes associated with nicotinic acetylcholine receptors (nAChRs) and related proteins have been found to predict response to first-line medications (e.g. nicotine replacement therapy [NRT], bupropion, or varenicline) or quitting over time without a controlled treatment trial. For nicotine and metabolite levels, function of the cytochrome P450 2A6 liver enzyme, which can be assessed with the nicotine metabolite ratio or via genotype, has been found to predict response, with slow nicotine metabolizers having less severe nicotine dependence and a greater likelihood of quitting with NRT than normal metabolizers. For brain imaging, decreased activation of brain regions associated with emotion regulation and increased connectivity in emotion regulation networks, increased responsiveness to pleasant cues, and altered activation with the Stroop effect have been found in smokers who quit with the first-line medications listed above or counseling. In addition, our group recently demonstrated that lower pre-treatment brain nAChR density is associated with a greater chance of quitting smoking with NRT or placebo. Several of these studies found that specific biomarkers may provide additional information for predicting response beyond subjective symptom or rating scale measures, thereby giving an initial indication that biomarkers may, in the future, be useful for guiding smoking cessation treatment intensity, duration, and type.

/pdf/biomarkers-of-response-to-smoking-cessation-15iqx6l1zq.pdf

Biomarkers of Response to Smoking Cessation Pharmacotherapies: Progress to Date.

No previous studies have investigated whether additional telephone follow-up counseling sessions after face-to-face counseling can increase quitting in China, and whether this strategy is feasible and effective for promoting smoking cessation is still unclear.

/pdf/effectiveness-of-additional-follow-up-telephone-counseling-4u5l604qoj.pdf

Effectiveness of additional follow-up telephone counseling in a smoking cessation clinic in Beijing and predictors of quitting among Chinese male smokers

Background: The effectiveness of worksite interventions to reduce smoking is debatable. Objectives: A comprehensive smoking cessation intervention was implemented in a community of more than 17,000 employees at three different health care companies. The primary endpoint was abstinence at 24 months (self-reported and confirmed by exhaled carbon monoxide ≤6 parts per million). Predictors of long-term abstinence were analysed by multivariable regression analysis. Methods: The study was designed as an investigator-initiated and investigator-driven, open, multicentre, cohort study; 887 smokers were enrolled in the programme. The intervention included intensive individual counselling as well as nicotine replacement and/or bupropion according to individual preferences. Re-interventions for relapse were offered during the 24-month follow-up. Results: The abstinence rate was 37% at 24 months and did not differ among the various medication groups (p > 0.05 for all). Predictors of successful cessation were higher age (odds ratio, OR 1.47, 95% confidence interval, CI 1.08-2.00, p Conclusion: A comprehensive smoking cessation intervention at the workplace achieves high, stable, long-term abstinence rates. Elderly, well-educated employees with breathlessness on exertion have higher odds of quitting smoking. In contrast, those with high physical dependency and more intense craving, and those reporting use of antidepressant medication or sputum production have poorer chances to quit.

/pdf/predictors-of-success-for-smoking-cessation-at-the-workplace-2zgkfi3l71.pdf

Predictors of success for smoking cessation at the workplace: a longitudinal study.

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Predictors of success for smoking cessation at the workplace: a longitudinal study.