Objective To investigate change in mental health after smoking cessation compared with continuing to smoke. Design Systematic review and meta-analysis of observational studies. Data sources Web of Science, Cochrane Central Register of Controlled Trials, Medline, Embase, and PsycINFO for relevant studies from inception to April 2012. Reference lists of included studies were hand searched, and authors were contacted when insufficient data were reported. Eligibility criteria for selecting studies Longitudinal studies of adults that assessed mental health before smoking cessation and at least six weeks after cessation or baseline in healthy and clinical populations. Results 26 studies that assessed mental health with questionnaires designed to measure anxiety, depression, mixed anxiety and depression, psychological quality of life, positive affect, and stress were included. Follow-up mental health scores were measured between seven weeks and nine years after baseline. Anxiety, depression, mixed anxiety and depression, and stress significantly decreased between baseline and follow-up in quitters compared with continuing smokers: the standardised mean differences (95% confidence intervals) were anxiety −0.37 (95% confidence interval −0.70 to −0.03); depression −0.25 (−0.37 to −0.12); mixed anxiety and depression −0.31 (−0.47 to −0.14); stress −0.27 (−0.40 to −0.13). Both psychological quality of life and positive affect significantly increased between baseline and follow-up in quitters compared with continuing smokers 0.22 (0.09 to 0.36) and 0.40 (0.09 to 0.71), respectively). There was no evidence that the effect size differed between the general population and populations with physical or psychiatric disorders. Conclusions Smoking cessation is associated with reduced depression, anxiety, and stress and improved positive mood and quality of life compared with continuing to smoke. The effect size seems as large for those with psychiatric disorders as those without. The effect sizes are equal or larger than those of antidepressant treatment for mood and anxiety disorders.

Background: Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).Methods: We conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.Results: There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.Conclusions: These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.

Background Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking. Objectives To determine the effectiveness of Internet‐based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults. Search methods We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016. Selection criteria We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no‐intervention control, a different Internet intervention, or a non‐Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer. Data collection and analysis Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six‐month follow‐up or more, reporting short‐term outcomes narratively where longer‐term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). We grouped studies according to whether they (1) compared an Internet intervention with a non‐active control arm (e.g. printed self‐help guides), (2) compared an Internet intervention with an active control arm (e.g. face‐to‐face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age. Main results We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants. There were only four RCTs conducted in adolescence or young adults that were eligible for meta‐analysis. Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non‐active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I² = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I² = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non‐active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I² = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I² = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I² = 0%); GRADE rating was moderate. Three studies compared tailored with non‐tailored Internet‐based messages, compared to non‐tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I² = 57%); GRADE rating was low. Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias. Authors' conclusions The evidence from trials in adults suggests that interactive and tailored Internet‐based interventions with or without additional behavioural support are moderately more effective than non‐active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

Objectives: To investigate the sex-specific association between smoking and lung cancer. Design: Systematic review and meta-analysis. Data sources: We searched PubMed and EMBASE from 1 January 1999 to 15 April 2016 for cohort studies. Cohort studies before 1 January 1999 were retrieved from a previous meta-analysis. Individual participant data from three sources were also available to supplement analyses of published literature. Eligibility criteria for selecting studies: Cohort studies reporting the sex-specific relative risk (RR) of lung cancer associated with smoking. Results: Data from 29 studies representing 99 cohort studies, 7 million individuals and >50 000 incident lung cancer cases were included. The sex-specific RRs and their ratio comparing women with men were pooled using random-effects meta-analysis with inverse-variance weighting. The pooled multiple-adjusted lung cancer RR was 6.99 (95% Confidence Interval (CI) 5.09 to 9.59) in women and 7.33 (95% CI 4.90 to 10.96) in men. The pooled ratio of the RRs was 0.92 (95% CI 0.72 to 1.16; I ² =89%; p<0.001), with no evidence of publication bias or differences across major pre-defined participant and study subtypes. The women-to-men ratio of RRs was 0.99 (95% CI 0.65 to 1.52), 1.11 (95% CI 0.75 to 1.64) and 0.94 (95% CI 0.69 to 1.30), for light, moderate and heavy smoking, respectively. Conclusions: Smoking yields similar risks of lung cancer in women compared with men. However, these data may underestimate the true risks of lung cancer among women, as the smoking epidemic has not yet reached full maturity in women. Continued efforts to measure the sex-specific association of smoking and lung cancer are required.

Objective: To examine the effectiveness of behavioural weight management interventions for adults with obesity delivered in primary care.Design: Systematic review and meta-analysis of randomised controlled trials.Eligibility criteria for selection of studies: Randomised controlled trials of behavioural weight management interventions for adults with a body mass index ≥25 delivered in primary care compared with no treatment, attention control, or minimal intervention and weight change at ≥12 months follow-up.Data sources: Trials from a previous systematic review were extracted and the search completed using the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021.Data extraction and synthesis: Two reviewers independently identified eligible studies, extracted data, and assessed risk of bias using the Cochrane risk of bias tool. Meta-analyses were conducted with random effects models, and a pooled mean difference for both weight (kg) and waist circumference (cm) were calculated.Main outcome measures: Primary outcome was weight change from baseline to 12 months. Secondary outcome was weight change from baseline to ≥24 months. Change in waist circumference was assessed at 12 months.Results: 34 trials were included: 14 were additional, from a previous review. 27 trials (n=8000) were included in the primary outcome of weight change at 12 month follow-up. The mean difference between the intervention and comparator groups at 12 months was −2.3 kg (95% confidence interval −3.0 to −1.6 kg, I²=88%, P<0.001), favouring the intervention group. At ≥24 months (13 trials, n=5011) the mean difference in weight change was −1.8 kg (−2.8 to −0.8 kg, I²=88%, P<0.001) favouring the intervention. The mean difference in waist circumference (18 trials, n=5288) was −2.5 cm (−3.2 to −1.8 cm, I²=69%, P<0.001) in favour of the intervention at 12 months.Conclusions: Behavioural weight management interventions for adults with obesity delivered in primary care are effective for weight loss and could be offered to members of the public.Systematic review registration: PROSPERO CRD42021275529.