Weight gain in smokers after quitting cigarettes: meta-analysis

OBJECTIVE: To describe weight gain and its variation in smokers who achieve prolonged abstinence for up to 12 months and who quit without treatment or use drugs to assist cessation. DESIGN: Meta-analysis. DATA SOURCES: We searched the Central Register of Controlled Trials (CENTRAL) and trials listed in Cochrane reviews of smoking cessation interventions (nicotine replacement therapy, nicotinic partial agonists, antidepressants, and exercise) for randomised trials of first line treatments (nicotine replacement therapy, bupropion, and varenicline) and exercise that reported weight change. We also searched CENTRAL for trials of interventions for weight gain after cessation. REVIEW METHODS: Trials were included if they recorded weight change from baseline to follow-up in abstinent smokers. We used a random effects inverse variance model to calculate the mean and 95% confidence intervals and the mean of the standard deviation for weight change from baseline to one, two, three, six, and 12 months after quitting. We explored subgroup differences using random effects meta-regression. RESULTS: 62 studies were included. In untreated quitters, mean weight gain was 1.12 kg (95% confidence interval 0.76 to 1.47), 2.26 kg (1.98 to 2.54), 2.85 kg (2.42 to 3.28), 4.23 kg (3.69 to 4.77), and 4.67 kg (3.96 to 5.38) at one, two, three, six, and 12 months after quitting, respectively. Using the means and weighted standard deviations, we calculated that at 12 months after cessation, 16%, 37%, 34%, and 13% of untreated quitters lost weight, and gained less than 5 kg, gained 5-10 kg, and gained more than 10 kg, respectively. Estimates of weight gain were similar for people using different pharmacotherapies to support cessation. Estimates were also similar between people especially concerned about weight gain and those not concerned. CONCLUSION: Smoking cessation is associated with a mean increase of 4-5 kg in body weight after 12 months of abstinence, and most weight gain occurs within three months of quitting. Variation in weight change is large, with about 16% of quitters losing weight and 13% gaining more than 10 kg.</p

Autoimmune pancreatitis associated with inflammatory bowel disease: a multicentric study of the GETAID

International audienceMeeting Abstract: P25

Functional Comorbidity Index in Sleep Apnea

Objectives (1) Measure the association between the Functional Comorbidity Index (range, 0-18) and physical function health status (SF-36 Physical Function domain), general physical health status (SF-36 Physical Component Score), and general mental health status (SF-36 Mental Component Score) outcome measures in a cohort of sleep apnea patients. (2) Test if the Functional Comorbidity Index is more strongly associated (a better predictor) than the well-known Charlson Comorbidity Index (range, 0-37) with these SF-36 outcome measures. Study Design Cross-sectional study. Setting University of Washington Sleep Center. Subjects and Methods In a cohort of newly diagnosed obstructive sleep apnea patients (N = 233), we obtained scores for the Functional Comorbidity Index, Charlson Comorbidity Index, and SF-36. We calculated Spearman correlations and adjusted coefficients of determination ( R2) with multiple linear regression, adjusted for demographic and health covariates. Bootstrapping generated R2 distributions for statistical comparison. Results Functional Comorbidity Index scores (mean ± standard deviation 2.4 ± 1.7) were more widely distributed than Charlson Comorbidity Index scores (0.7 ± 1.4). The Functional Comorbidity Index was significantly correlated with SF-36 Physical Function (–0.53, P < .001), Physical Component Score (–0.44, P < .001), and Mental Component Score (–0.38, P < .001). The Functional Comorbidity Index was a better predictor than the Charlson Comorbidity Index of SF-36 Physical Function ( R2 mean ± standard error 0.27 ± 0.05 vs 0.17 ± 0.05, P < .001), Physical Component Score (0.23 ± 0.05 vs 0.17 ± 0.05, P < .001), and Mental Component Score (0.23 ± 0.05 vs 0.13 ± 0.05, P < .001). Conclusion The Functional Comorbidity Index is a more robust predictor of general health status than the Charlson Comorbidity Index in obstructive sleep apnea patients