Clinical and cost-effectiveness of nurse-delivered sleep restriction therapy for insomnia in primary care (HABIT): a pragmatic, superiority, open-label, randomised controlled trial.

BACKGROUND: Insomnia is prevalent and distressing but access to the first-line treatment, cognitive behavioural therapy (CBT), is extremely limited. We aimed to assess the clinical and cost-effectiveness of sleep restriction therapy, a key component of CBT, which has the potential to be widely implemented. METHODS: We did a pragmatic, superiority, open-label, randomised controlled trial of sleep restriction therapy versus sleep hygiene. Adults with insomnia disorder were recruited from 35 general practices across England and randomly assigned (1:1) using a web-based randomisation programme to either four sessions of nurse-delivered sleep restriction therapy plus a sleep hygiene booklet or a sleep hygiene booklet only. There was no restriction on usual care for either group. Outcomes were assessed at 3 months, 6 months, and 12 months. The primary endpoint was self-reported insomnia severity at 6 months measured with the insomnia severity index (ISI). The primary analysis included participants according to their allocated group and who contributed at least one outcome measurement. Cost-effectiveness was evaluated from the UK National Health Service and personal social services perspective and expressed in terms of incremental cost per quality-adjusted life year (QALY) gained. The trial was prospectively registered (ISRCTN42499563). FINDINGS: Between Aug 29, 2018, and March 23, 2020 we randomly assigned 642 participants to sleep restriction therapy (n=321) or sleep hygiene (n=321). Mean age was 55·4 years (range 19-88), with 489 (76·2%) participants being female and 153 (23·8%) being male. 580 (90·3%) participants provided data for at least one outcome measurement. At 6 months, mean ISI score was 10·9 (SD 5·5) for sleep restriction therapy and 13·9 (5·2) for sleep hygiene (adjusted mean difference -3·05, 95% CI -3·83 to -2·28; p<0·0001; Cohen's d -0·74), indicating that participants in the sleep restriction therapy group reported lower insomnia severity than the sleep hygiene group. The incremental cost per QALY gained was £2076, giving a 95·3% probability that treatment was cost-effective at a cost-effectiveness threshold of £20 000. Eight participants in each group had serious adverse events, none of which were judged to be related to intervention. INTERPRETATION: Brief nurse-delivered sleep restriction therapy in primary care reduces insomnia symptoms, is likely to be cost-effective, and has the potential to be widely implemented as a first-line treatment for insomnia disorder. FUNDING: The National Institute for Health and Care Research Health Technology Assessment Programme.

How has the COVID-19 pandemic affected the delivery of preventive healthcare? An interrupted time series analysis of adults in English primary care from 2018 to 2022.

OBJECTIVE: Offering advice and support for smoking, obesity, excess alcohol, and physical inactivity is an evidence-based component of primary care. The objective was to quantify the impact of the pandemic on the rate of advice or referral for these four risk factors. METHODS: A retrospective cohort study using primary care data from 1847 practices in England and 21,191,389 patients contributing to the Oxford Clinical Informatics Digital Hub. An interrupted time series analysis was undertaken with a single change point (March 2020). Monthly trends were modelled from 1st January 2018 - 30th June 2022 using segmented linear regression. RESULTS: There was an initial step reduction in advice and referrals for smoking, obesity, excess alcohol, and physical inactivity in March 2020. By June 2022, advice on smoking (slope change -0.02 events per hundred patient years/month (EPH/month); 95% confidence interval (CI) -0.17, 0.21), obesity (0.06 EPH/month; 95% CI 0.01, 0.12), alcohol (0.02 EPH/month; 95% CI -0.01, 0.05) and physical inactivity (0.05 EPH/month; 95% CI 0.01, 0.09) had not returned to pre-pandemic levels. Similarly, smoking cessation referral remained lower (0.01 EPH/month; 95% CI -0.01, 0.09), excess alcohol referral returned to similar levels (0.0005 EPH/month; 95% CI 0.0002, 0.0008), while referral for obesity (0.14 EPH/month; 95% CI 0.10, 0.19) and physical inactivity (0.01 EPH/month; 95% CI 0.01, 0.02) increased relative to pre-pandemic rates. CONCLUSION: Advice and support for smoking, and advice for weight, excess alcohol and physical inactivity have not returned to pre-pandemic levels. Clinicians and policy makers should prioritise preventive care in COVID-19 recovery plans.

Relationship Between Clinician Language and the Success of Behavioral Weight Loss Interventions : A Mixed-Methods Cohort Study.

BACKGROUND: International guidelines recommend that primary care clinicians recognize obesity and offer treatment opportunistically, but there is little evidence on how clinicians can discuss weight and offer treatment in ways that are well received and effective. OBJECTIVE: To examine relationships between language used in the clinical visit and patient weight loss. DESIGN: Mixed-methods cohort study. SETTING: 38 primary care clinics in England participating in the Brief Intervention for Weight Loss trial. PARTICIPANTS: 246 patients with obesity seen by 87 general practitioners randomly sampled from the intervention group of the randomized clinical trial. MEASUREMENTS: Conversation analysis of recorded discussions between 246 patients with obesity and 87 clinicians regarding referral to a 12-week behavioral weight management program offered as part of the randomized clinical trial. Clinicians' interactional approaches were identified and their association with patient weight loss at 12 months (primary outcome) was examined. Secondary outcomes included patients' agreement to attend weight management, attendance, loss of 5% body weight, actions taken to lose weight, and postvisit satisfaction. RESULTS: Three interactional approaches were identified on the basis of clinicians' linguistic and paralinguistic practices: creating a sense of referrals as "good news" related to the opportunity of the referral (n = 62); "bad news," focusing on the harms of obesity (n = 82); or neutral (n = 102). Outcome data were missing from 57 participants, so weighted analyses were done to adjust for missingness. Relative to neutral news, good news was associated with increased agreement to attend the program (adjusted risk difference, 0.25 [95% CI, 0.15 to 0.35]), increased attendance (adjusted risk difference, 0.45 [CI, 0.34 to 0.56]), and weight change (adjusted difference, -3.60 [CI, -6.58 to -0.62]). There was no evidence of differences in mean weight change comparing bad and neutral news, and no evidence of differences in patient satisfaction across all 3 approaches. LIMITATIONS: Data were audio only, so body language and nonverbal cues could not be assessed. There is potential for selection bias and residual confounding. CONCLUSION: When raising the topic of excess weight in clinical visits, presenting weight loss treatment as a positive opportunity is associated with greater uptake of treatment and greater weight loss. PRIMARY FUNDING SOURCE: National Institute for Health and Care Research School for Primary Care Research and the Foundation for the Sociology of Health and Illness.

Weight regain after behavioural weight management programmes and its impact on quality of life and cost effectiveness: Evidence synthesis and health economic analyses.

AIMS: We used data from a recent systematic review to investigate weight regain after behavioural weight management programmes (BWMPs, sometimes referred to as lifestyle modification programmes) and its impact on quality-of-life and cost-effectiveness. MATERIALS AND METHODS: Trial registries, databases and forward-citation searching (latest search December 2019) were used to identify randomized trials of BWMPs in adults with overweight/obesity reporting outcomes at ≥12 months, and after programme end. Two independent reviewers screened records. One reviewer extracted data and a second checked them. The differences between intervention and control groups were synthesized using mixed-effect, meta-regression and time-to-event models. We examined associations between weight difference and difference in quality-of-life. Cost-effectiveness was estimated from a health sector perspective. RESULTS: In total, 155 trials (n > 150 000) contributed to analyses. The longest follow-up was 23 years post-programme. At programme end, intervention groups achieved -2.8 kg (95%CI -3.2 to -2.4) greater weight loss than controls. Weight regain after programme end was 0.12-0.32 kg/year greater in intervention relative to control groups, with a between-group difference evident for at least 5 years. Quality-of-life increased in intervention groups relative to control at programme end and thereafter returned to control as the difference in weight between groups diminished. BWMPs with this initial weight loss and subsequent regain would be cost-effective if delivered for under £560 (£8.80-£3900) per person. CONCLUSIONS: Modest rates of weight regain, with persistent benefits for several years, should encourage health care practitioners and policymakers to offer obesity treatments that cost less than our suggested thresholds as a cost-effective intervention to improve long-term weight management. REGISTRATION: The review is registered on PROSPERO, CRD42018105744.

Development and initial evaluation of a behavioural intervention to support weight management for people with serious mental illness: an uncontrolled feasibility and acceptability study.

BACKGROUND: The rates of obesity and associated health problems are higher in people with serious mental illness (SMI), such as schizophrenia and bipolar disorder, than the general population. A primary care referral to a behavioural weight management programme can be an effective intervention, but people with SMI have reported barriers to engaging with them and bespoke options are rarely provided in routine practice. It is possible that adjunct support addressing these specific barriers could help. Here we report the development, feasibility and acceptability of an intervention to improve uptake and engagement with a mainstream weight management programme for people with SMI. METHODS: We worked with people with a lived-experience of SMI and used the person-based approach to develop the 'Weight cHange for people with sErious mEntal iLlness' (WHEEL) intervention. It comprised a referral to a mainstream weight management programme (WW®) to be attended once a week, in-person or online, for 12-weeks. The adjunct support comprised a one-off, online consultation called Meet Your Mentor and weekly, telephone or email Mentor Check Ins for 12-weeks. We assessed the feasibility of WHEEL through the number of programme and adjunct support sessions that the participants attended. We analysed the acceptability of WHEEL using a thematic analysis of qualitative interviews conducted at baseline and at 12-week follow-up. Our exploratory outcome of clinical effectiveness was self-reported weight at baseline and at end-of-programme. RESULTS: Twenty participants were assessed for eligibility and 17 enrolled. All 17 participants attended Meet Your Mentor and one was lost to follow-up (94% retention). Nine out of 16 attended ≥50% of the weekly programme sessions and 12/16 attended ≥50% of the weekly check-ins. Participants reported in the interviews that the adjunct support helped to establish and maintain a therapeutic alliance. While some participants valued the in-person sessions, others reported that they preferred the online sessions because it removed a fear of social situations, which was a barrier for some participants. The mean change in self-reported weight was - 4·1 kg (SD: 3·2) at 12-weeks. CONCLUSIONS: A mainstream weight management programme augmented with brief and targeted education and low-intensity check-ins generated sufficient engagement and acceptability to warrant a future trial.

Pharmacological and electronic cigarette interventions for smoking cessation in adults: component network meta-analyses.

BACKGROUND: Tobacco smoking is the leading preventable cause of death and disease worldwide. Stopping smoking can reduce this harm and many people would like to stop. There are a number of medicines licenced to help people quit globally, and e-cigarettes are used for this purpose in many countries. Typically treatments work by reducing cravings to smoke, thus aiding initial abstinence and preventing relapse. More information on comparative effects of these treatments is needed to inform treatment decisions and policies. OBJECTIVES: To investigate the comparative benefits, harms and tolerability of different smoking cessation pharmacotherapies and e-cigarettes, when used to help people stop smoking tobacco. SEARCH METHODS: We identified studies from recent updates of Cochrane Reviews investigating our interventions of interest. We updated the searches for each review using the Cochrane Tobacco Addiction Group (TAG) specialised register to 29 April 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs), cluster-RCTs and factorial RCTs, which measured smoking cessation at six months or longer, recruited adults who smoked combustible cigarettes at enrolment (excluding pregnant people) and randomised them to approved pharmacotherapies and technologies used for smoking cessation worldwide (varenicline, cytisine, nortriptyline, bupropion, nicotine replacement therapy (NRT) and e-cigarettes) versus no pharmacological intervention, placebo (control) or another approved pharmacotherapy. Studies providing co-interventions (e.g. behavioural support) were eligible if the co-intervention was provided equally to study arms. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening, data extraction and risk of bias (RoB) assessment (using the RoB 1 tool). Primary outcome measures were smoking cessation at six months or longer, and the number of people reporting serious adverse events (SAEs). We also measured withdrawals due to treatment. We used Bayesian component network meta-analyses (cNMA) to examine intervention type, delivery mode, dose, duration, timing in relation to quit day and tapering of nicotine dose, using odds ratios (OR) and 95% credibility intervals (CrIs). We calculated an effect estimate for combination NRT using an additive model. We evaluated the influence of population and study characteristics, provision of behavioural support and control arm rates using meta-regression. We evaluated certainty using GRADE. MAIN RESULTS: Of our 332 eligible RCTs, 319 (835 study arms, 157,179 participants) provided sufficient data to be included in our cNMA. Of these, we judged 51 to be at low risk of bias overall, 104 at high risk and 164 at unclear risk, and 118 reported pharmaceutical or e-cigarette/tobacco industry funding. Removing studies at high risk of bias did not change our interpretation of the results. Benefits We found high-certainty evidence that nicotine e-cigarettes (OR 2.37, 95% CrI 1.73 to 3.24; 16 RCTs, 3828 participants), varenicline (OR 2.33, 95% CrI 2.02 to 2.68; 67 RCTs, 16,430 participants) and cytisine (OR 2.21, 95% CrI 1.66 to 2.97; 7 RCTs, 3848 participants) were associated with higher quit rates than control. In absolute terms, this might lead to an additional eight (95% CrI 4 to 13), eight (95% CrI 6 to 10) and seven additional quitters per 100 (95% CrI 4 to 12), respectively. These interventions appeared to be more effective than the other interventions apart from combination NRT (patch and a fast-acting form of NRT), which had a lower point estimate (calculated additive effect) but overlapping 95% CrIs (OR 1.93, 95% CrI 1.61 to 2.34). There was also high-certainty evidence that nicotine patch alone (OR 1.37, 95% CrI 1.20 to 1.56; 105 RCTs, 37,319 participants), fast-acting NRT alone (OR 1.41, 95% CrI 1.29 to 1.55; 120 RCTs, 31,756 participants) and bupropion (OR 1.43, 95% CrI 1.26 to 1.62; 71 RCTs, 14,759 participants) were more effective than control, resulting in two (95% CrI 1 to 3), three (95% CrI 2 to 3) and three (95% CrI 2 to 4) additional quitters per 100 respectively. Nortriptyline is probably associated with higher quit rates than control (OR 1.35, 95% CrI 1.02 to 1.81; 10 RCTs, 1290 participants; moderate-certainty evidence), resulting in two (CrI 0 to 5) additional quitters per 100. Non-nicotine/placebo e-cigarettes (OR 1.16, 95% CrI 0.74 to 1.80; 8 RCTs, 1094 participants; low-certainty evidence), equating to one additional quitter (95% CrI -2 to 5), had point estimates favouring the intervention over control, but CrIs encompassed the potential for no difference and harm. There was low-certainty evidence that tapering the dose of NRT prior to stopping treatment may improve effectiveness; however, 95% CrIs also incorporated the null (OR 1.14, 95% CrI 1.00 to 1.29; 111 RCTs, 33,156 participants). This might lead to an additional one quitter per 100 (95% CrI 0 to 2). Harms There were insufficient data to include nortriptyline and non-nicotine EC in the final SAE model. Overall rates of SAEs for the remaining treatments were low (average 3%). Low-certainty evidence did not show a clear difference in the number of people reporting SAEs for nicotine e-cigarettes, varenicline, cytisine or NRT when compared to no pharmacotherapy/e-cigarettes or placebo. Bupropion may slightly increase rates of SAEs, although the CrI also incorporated no difference (moderate certainty). In absolute terms bupropion may cause one more person in 100 to experience an SAE (95% CrI 0 to 2). AUTHORS' CONCLUSIONS: The most effective interventions were nicotine e-cigarettes, varenicline and cytisine (all high certainty), as well as combination NRT (additive effect, certainty not rated). There was also high-certainty evidence for the effectiveness of nicotine patch, fast-acting NRT and bupropion. Less certain evidence of benefit was present for nortriptyline (moderate certainty), non-nicotine e-cigarettes and tapering of nicotine dose (both low certainty). There was moderate-certainty evidence that bupropion may slightly increase the frequency of SAEs, although there was also the possibility of no increased risk. There was no clear evidence that any other tested interventions increased SAEs. Overall, SAE data were sparse with very low numbers of SAEs, and so further evidence may change our interpretation and certainty. Future studies should report SAEs to strengthen certainty in this outcome. More head-to-head comparisons of the most effective interventions are needed, as are tests of combinations of these. Future work should unify data from behavioural and pharmacological interventions to inform approaches to combined support for smoking cessation.

Acceptability of integrating smoking cessation treatment into routine care for people with mental illness: A qualitative study.

INTRODUCTION: Improving Access to Psychological Therapies (IAPTs) Services could offer smoking cessation treatment to improve physical and psychological outcomes for service users, but it currently does not. This study aimed to understand participants' views and experiences of receiving a novel smoking cessation intervention as part of the ESCAPE trial (intEgrating Smoking Cessation treatment As part of usual Psychological care for dEpression and anxiety). We used the Capability, Opportunity and Motivation Model of Behaviour (COM-B) to understand the (i) acceptability of the integrated smoking cessation treatment, (ii) views of psychological well-being practitioners' (PWPs) ability to deliver the smoking cessation treatment and (iii) positive and negative impacts of smoking cessation treatment. METHODS: This was a qualitative study embedded within a feasibility randomized-controlled trial (ESCAPE) in primary care services in the United Kingdom (IAPT). Thirty-six participants (53% female) from both usual care and intervention arms of the ESCAPE trial, including both quitters and nonquitters, were interviewed using semi-structured interviews. Data were analysed using a framework approach to thematic analysis, using the COM-B as a theoretical frame. RESULTS: Psychological Capability: Integrated smoking cessation treatment was acceptable and encouraged participants to reflect on their mental health. Some participants found it difficult to understand nicotine withdrawal symptoms. MOTIVATION: Participants were open to change during the event of presenting to IAPT. Some described being motivated to take part in the intervention by curiosity, to see whether quitting smoking would help their mental health. Physical Opportunity: IAPT has a natural infrastructure for supporting integrated treatment, but there were some barriers such as session duration and interventions feeling segmented. Social Opportunity: Participants viewed PWPs as having good interpersonal skills to deliver a smoking cessation intervention. CONCLUSION: People with common mental illness generally accepted integrated smoking cessation and mental health treatment. Smoking cessation treatment fits well within IAPT's structure; however, there are barriers to implementation. PATIENT OR PUBLIC CONTRIBUTION: Before data collection, we consulted with people with lived experience of smoking and/or mental illness and lay public members regarding the aims, design and interview schedules. After analysis, two people with lived experience of smoking and mental illness individually gave feedback on the final themes and quotes.

Effectiveness of Motivational Interviewing in Managing Overweight and Obesity : A Systematic Review and Meta-analysis.

BACKGROUND: Motivational interviewing (MI) is potentially useful in management of overweight and obesity, but staff training and increased delivery time are barriers, and its effectiveness independent of other behavioral components is unclear. PURPOSE: To assess the independent contribution of MI as part of a behavioral weight management program (BWMP) in controlling weight and improving psychological well-being. DATA SOURCES: 6 electronic databases and 2 trial registries, searched from database inception through 24 September 2021. STUDY SELECTION: Randomized controlled trials in adults or adolescents aimed at weight loss or maintenance and comparing programs incorporating MI versus interventions without MI. DATA EXTRACTION: Two reviewers independently screened studies, extracted data, and assessed risk of bias. Outcomes included weight, anxiety, depression, quality of life, and other aspects of psychological well-being. Pooled mean differences or standardized mean differences were obtained using random- and fixed-effects meta-analyses. DATA SYNTHESIS: Forty-six studies involving 11 077 participants, predominantly with obesity, were included. At 6 months, BWMPs using MI were more effective than no/minimal intervention (-0.88 [95% CI, -1.27 to -0.48] kg; I 2 = 0%) but were not statistically significantly more effective than lower-intensity (-0.88 [CI, -2.39 to 0.62] kg; I 2 = 55.8%) or similar-intensity (-1.36 [CI, -2.80 to 0.07] kg; I 2 = 18.8%) BWMPs. At 1 year, data were too sparse to pool comparisons with no/minimal intervention, but MI did not produce statistically significantly greater weight change compared with lower-intensity (-1.16 [CI, -2.49 to 0.17] kg; I 2 = 88.7%) or similar-intensity (-0.18 [CI, -2.40 to 2.04] kg; I 2 = 72.7%) BWMPs without MI. Studies with 18-month follow-up were also sparse; MI did not produce statistically significant benefit in any of the comparator categories. There was no evidence of subgroup differences based on study, participant, or intervention characteristics. Too few studies assessed effects on psychological well-being to pool, but data did not suggest that MI was independently effective. LIMITATIONS: High statistical heterogeneity among studies, largely unexplained by sensitivity and subgroup analyses; stratification by comparator intensity and follow-up duration resulted in pooling of few studies. CONCLUSION: There is no evidence that MI increases effectiveness of BWMPs in controlling weight. Given the intensive training required for its delivery, MI may not be a worthwhile addition to BWMPs. PRIMARY FUNDING SOURCE: National Institute for Health Research Biomedical Research Centre. (PROSPERO: CRD42020177259).

The Basis of Patient Resistance to Opportunistic Discussions About Weight in Primary Care.

Clinicians expect that talking to patients with obesity about potential/future weight loss will be a difficult conversation, especially if it is not the reason that a patient is seeking medical help. Despite this expectation, many governments ask clinicians to take every opportunity to talk to patients about weight to help manage increasing levels of obesity. Although this is recommended, little is known about what happens in consultations when clinicians opportunistically talk to patients about weight, and if the anticipated difficulties are reality. This paper examines displays of explicit patient resistance following opportunistic weight-loss conversations initiated by GPs. We analyzed audio recordings and transcribed them for conversation analysis. We focused on the precursors of explicit resistance displays during opportunistic weight loss discussions, the format of the resistance, and the ways it was managed by GPs. We found relatively few instances of explicit resistance displays. When it did occur, rather than be related to the opportunistic nature of the advice, or the topic of weight itself, resistance was nuanced and associated to the sensitivity of the GPs managing unknown patient levels of awareness of weight loss benefits, or prior efforts to lose weight. Clinicians tended not to challenge this resistance from patients, and we suggest this tactic may be acceptable to patients and help foster the long-term collaborative relationships needed to tackle obesity. Data are in British English.

Smoking and COVID-19 outcomes: an observational and Mendelian randomisation study using the UK Biobank cohort.

BACKGROUND: Conflicting evidence has emerged regarding the relevance of smoking on risk of COVID-19 and its severity. METHODS: We undertook large-scale observational and Mendelian randomisation (MR) analyses using UK Biobank. Most recent smoking status was determined from primary care records (70.8%) and UK Biobank questionnaire data (29.2%). COVID-19 outcomes were derived from Public Health England SARS-CoV-2 testing data, hospital admissions data, and death certificates (until 18 August 2020). Logistic regression was used to estimate associations between smoking status and confirmed SARS-CoV-2 infection, COVID-19-related hospitalisation, and COVID-19-related death. Inverse variance-weighted MR analyses using established genetic instruments for smoking initiation and smoking heaviness were undertaken (reported per SD increase). RESULTS: There were 421 469 eligible participants, 1649 confirmed infections, 968 COVID-19-related hospitalisations and 444 COVID-19-related deaths. Compared with never-smokers, current smokers had higher risks of hospitalisation (OR 1.80, 95% CI 1.26 to 2.29) and mortality (smoking 1-9/day: OR 2.14, 95% CI 0.87 to 5.24; 10-19/day: OR 5.91, 95% CI 3.66 to 9.54; 20+/day: OR 6.11, 95% CI 3.59 to 10.42). In MR analyses of 281 105 White British participants, genetically predicted propensity to initiate smoking was associated with higher risks of infection (OR 1.45, 95% CI 1.10 to 1.91) and hospitalisation (OR 1.60, 95% CI 1.13 to 2.27). Genetically predicted higher number of cigarettes smoked per day was associated with higher risks of all outcomes (infection OR 2.51, 95% CI 1.20 to 5.24; hospitalisation OR 5.08, 95% CI 2.04 to 12.66; and death OR 10.02, 95% CI 2.53 to 39.72). INTERPRETATION: Congruent results from two analytical approaches support a causal effect of smoking on risk of severe COVID-19.

Association of Weight Changes With Changes in Histological Features and Blood Markers in Nonalcoholic Steatohepatitis.

BACKGROUND AND AIMS: Weight loss is recommended for patients with non-alcoholic steatohepatitis (NASH) but the impact of weight change on disease activity remains unclear. We examined the association between weight change (gain/loss) and changes in biochemical and histological features of NASH. METHODS: This was an analysis of the PIVENS and FLINT trials in adults with NASH who had liver biopsies at baseline and at either 1.5 years or 2 years. Multivariable regression models examined how weight change was associated with changes in (a) blood liver markers, (b) NASH resolution with no fibrosis worsening, (c) fibrosis improving with no NASH worsening, and (d) individual histological features. RESULTS: The BMI of the 421 participants was 34.3 kg/m2 (SD:6.5) and their mean weight change was +0.5 kg (SD:6.5). Weight change was independently and positively associated with changes in liver enzymes and the Fibrosis-4 score (all P < .001). Each kg of weight loss was associated with 7% (95% CI, 3%-10%; P < .001) increase in odds of achieving NASH resolution with no fibrosis worsening and with 5% (95% CI, 1%-8%; P = .01) increase in odds of achieving fibrosis improvement with no NASH worsening. Weight gain was associated with worsening of disease activity. For every kg of weight lost, the odds of fibrosis improving were 5% (95% CI, 2%-8%; P = .001). There was no evidence that the association between weight change and outcome depended upon pharmacological treatment, trial, body mass index, and baseline fibrosis. CONCLUSIONS: Weight change was independently and monotonically associated with changes in biochemical and histological features of NASH. Guidelines for NASH management should incorporate recommendations for both avoidance of weight gain and support to lose weight.

Obesity, metabolic risk and adherence to healthy lifestyle behaviours: prospective cohort study in the UK Biobank.

BACKGROUND: Contested evidence suggests that obesity confers no risk to health in people who have a healthy lifestyle, particularly if there are no metabolic complications of obesity. The aim was to examine the association between adherence to lifestyle recommendations and the absence of metabolic complications on the incident or fatal cardiovascular disease and all-cause mortality across different categories of body mass index (BMI). METHODS: This contemporary prospective cohort study included 339,902 adults without cardiovascular disease at baseline, recruited between 2006 and 2010 from the UK Biobank and followed until 2018-2020. The main exposures were four healthy lifestyle behaviours: never smoker, alcohol intake ≤ 112g/ week, 150 min moderate physical activity or 75 min vigorous activity/week, ≥ 5 servings of fruit or vegetables/day, and we assessed these overall and across the BMI groups. Metabolic complications of excess adiposity were hypertension, diabetes and hyperlipidaemia, and we examined whether obesity was associated with increased risk in the absence of these complications. The outcomes were all-cause mortality, death from, and incident cardiovascular disease (CVD). RESULTS: Individuals who met four lifestyle recommendations but had excess weight had higher all-cause mortality; for BMI 30-34.9 kg/m2, the hazard ratio (HR) was 1.42 (95% confidence interval 1.20 to 1.68), and for BMI ≥ 35 kg/m2, HR was 2.17 (95% CI 1.71 to 2.76). The risk was lower, but still increased for people with no metabolic complications; for all-cause mortality, BMI 30-34.9 kg/m2 had an HR of 1.09 (95% CI 0.99 to 1.21), and BMI ≥ 35 kg/m2 had an HR of 1.44 (95% CI 1.19 to 1.74) for all-cause mortality. Similar patterns were found for incident and fatal CVD. CONCLUSIONS: Meeting healthy lifestyle recommendations, or the absence of metabolic complications of obesity offsets some, but not all, of the risk of subsequent CVD, and premature mortality in people with overweight or obesity. Offering support to achieve and maintain a healthy weight and to adopt healthy behaviours are likely to be important components in effective preventative healthcare.

Associations between body composition, fat distribution and metabolic consequences of excess adiposity with severe COVID-19 outcomes: observational study and Mendelian randomisation analysis.

BACKGROUND: Higher body mass index (BMI) and metabolic consequences of excess weight are associated with increased risk of severe COVID-19, though their mediating pathway is unclear. METHODS: A prospective cohort study included 435,504 UK Biobank participants. A two-sample Mendelian randomisation (MR) study used the COVID-19 Host Genetics Initiative in 1.6 million participants. We examined associations of total adiposity, body composition, fat distribution and metabolic consequences of excess weight, particularly type 2 diabetes, with incidence and severity of COVID-19, assessed by test positivity, hospital admission, intensive care unit (ICU) admission and death. RESULTS: BMI and body fat were associated with COVID-19 in the observational and MR analyses but muscle mass was not. The observational study suggested the association with central fat distribution was stronger than for BMI, but there was little evidence from the MR analyses than this was causal. There was evidence that strong associations of metabolic consequences with COVID-19 outcomes in observational but not MR analyses. Type 2 diabetes was strongly associated with COVID-19 in observational but not MR analyses. In adjusted models, the observational analysis showed that the association of BMI with COVID-19 diminished, while central fat distribution and metabolic consequences of excess weight remained strongly associated. In contrast, MR showed the reverse, with only BMI retaining a direct effect on COVID-19. CONCLUSIONS: Excess total adiposity is probably casually associated with severe COVID-19. Mendelian randomisation data do not support causality for the observed associations of central fat distribution or metabolic consequences of excess adiposity with COVID-19.

Smoking cessation for secondary prevention of cardiovascular disease.

BACKGROUND: Smoking is a leading cause of cardiovascular disease (CVD), particularly coronary heart disease (CHD). However, quitting smoking may prevent secondary CVD events in people already diagnosed with CHD.  OBJECTIVES: To examine the impact of smoking cessation on death from CVD and major adverse cardiovascular events (MACE), in people with incident CHD. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialised Register, CENTRAL, MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, and the trials registries clinicaltrials.gov and the International Clinical Trials Registry Platform. We ran all searches from database inception to 15 April 2021.  SELECTION CRITERIA: We included cohort studies, and both cluster- and individually randomised controlled trials of at least six months' duration. We treated all included studies as cohort studies and analysed them by smoking status at follow-up. Eligible studies had to recruit adults (> 18 years) with diagnosed CHD and who smoked tobacco at diagnosis, and assess whether they quit or continued smoking during the study. Studies had to measure at least one of our included outcomes with at least six months' follow-up. Our primary outcomes were death from CVD and MACE. Secondary outcomes included all-cause mortality, non-fatal myocardial infarction, non-fatal stroke, new-onset angina and change in quality of life.  DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening and data extraction.  We assessed the risk of bias for the primary outcomes using the ROBINS-I tool. We compared the incidence of death from CVD and of MACE (primary outcomes) between participants who quit smoking versus those who continued to smoke for each included study that reported these outcomes. We also assessed differences in all-cause mortality, incidence of non-fatal myocardial infarction, incidence of non-fatal stroke and new onset angina. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI). For our outcome, change in quality of life, we calculated the pooled standardised mean difference (SMD) and 95% CI for the difference in change in quality of life from baseline to follow-up between those who had quit smoking and those who had continued to smoke. For all meta-analyses we used a generic inverse variance random-effects model and quantified statistical heterogeneity using the I²statistic. We assessed the certainty of evidence for our primary outcomes using the eight GRADE considerations relevant to non-randomised studies. MAIN RESULTS: We included 68 studies, consisting of 80,702 participants. For both primary outcomes, smoking cessation was associated with a decreased risk compared with continuous smoking: CVD death (HR 0.61, 95% CI 0.49 to 0.75; I² = 62%; 18 studies, 17,982 participants; moderate-certainty evidence) and MACE (HR 0.57, 95% CI 0.45 to 0.71; I² = 84%; 15 studies, 20,290 participants; low-certainty evidence). These findings were robust to our planned sensitivity analyses. Through subgroup analysis, for example comparing adjusted versus non-adjusted estimates, we found no evidence of differences in the effect size. While there was substantial heterogeneity, this was primarily in magnitude rather than the direction of the effect estimates. Overall, we judged 11 (16%) studies to be at moderate risk of bias and 18 (26%) at serious risk, primarily due to possible confounding. There was also some evidence of funnel plot asymmetry for MACE outcomes. For these reasons, we rated our certainty in the estimates for CVD death as moderate and MACE as low.  For our secondary outcomes, smoking cessation was associated with a decreased risk in all-cause mortality (HR 0.60, 95% CI 0.55 to 0.66; I² = 58%; 48 studies, 59,354 participants), non-fatal myocardial infarction (HR 0.64, 95% CI 0.58 to 0.72; I² = 2%; 24 studies, 23,264 participants) and non-fatal stroke (HR 0.70, 95% CI 0.53 to 0.90; I² = 0%; 9 studies, 11,352 participants). As only one study reported new onset of angina, we did not conduct meta-analysis, but this study reported a lower risk in people who stopped smoking. Quitting smoking was not associated with a worsening of quality of life and suggested improvement in quality of life, with the lower bound of the CI also consistent with no difference (SMD 0.12, 95% CI 0.01 to 0.24; I² = 48%; 8 studies, 3182 participants).  AUTHORS' CONCLUSIONS: There is moderate-certainty evidence that smoking cessation is associated with a reduction of approximately one-third in the risk of recurrent cardiovascular disease in people who stop smoking at diagnosis. This association may be causal, based on the link between smoking cessation and restoration of endothelial and platelet function, where dysfunction of both can result in increased likelihood of CVD events.  Our results provide evidence that there is a decreased risk of secondary CVD events in those who quit smoking compared with those who continue, and that there is a suggested improvement in quality of life as a result of quitting smoking. Additional studies that account for confounding, such as use of secondary CVD prevention medication, would strengthen the evidence in this area.

What advice do general practitioners give to people living with obesity to lose weight? A qualitative content analysis of recorded interactions.

BACKGROUND: Guidelines recommend general practitioners (GPs) take every opportunity to talk to people living with obesity about their weight, and evidence shows even very brief advice is associated with weight loss. However, little is known about what GPs say when giving brief behavioural advice, and if it reflects evidence-based recommendations for people living with obesity. To understand what behavioural advice GPs give, we categorized the content and delivery of GPs' advice during brief interventions. METHODS: Qualitative content analysis was applied to 159 audio recordings of consultations from the Brief Interventions for Weight Loss (BWeL) trial, where GPs gave brief weight-loss advice to patients with a body mass index ≥30 kg/m2 (or ≥25 kg/m2 if Asian) in 137 UK surgeries. Similar content was grouped into descriptive clusters. RESULTS: The results comprised 4 clusters, illuminating different aspects of the advice given: (i) Content of diet and physical activity advice, showing this was highly varied; (ii) Content of "implementation tips" given to support changes, e.g. using smaller plates; (iii) Content of signposting support, either towards further clinician support, or other resources, e.g. information booklets; (iv) Style of advice delivery, showing GPs rarely gave personalized advice, or reasons for their advice. CONCLUSIONS AND IMPLICATIONS: Weight-loss advice from GPs to patients with obesity rarely included effective methods, mostly communicating a general "eat less, do more" approach. Advice was mostly generic, and rarely tailored to patients' existing knowledge and behaviours. Effectiveness of brief weight-loss advice could be improved if GPs were given clearer guidance on evidence-based recommendations.

Current guidelines strongly encourage general practitioners (GPs) to talk to people living with obesity about weight loss. Evidence has shown that conversations with a doctor about weight management can be highly effective, as even very brief advice has been associated with weight loss. In order to understand what GPs actually say when offering weight-loss advice to patients with obesity, we analysed 159 audio recordings of conversations between GPs and patients. We found that GPs gave mainly generic diet and exercise messages for example "reduce your carbohydrates" and "move more." Furthermore, weight-loss advice was often not tailored to patients' existing knowledge and behaviours. Obesity is a chronic and relapsing condition, but patients were not given specific or evidence-based advice to support them to manage this. The findings suggest that the brief weight-loss advice from GPs could be more effective if they were given clearer guidance on which methods of weight-loss evidence has shown actually works.

Combining simple blood tests to identify primary care patients with unexpected weight loss for cancer investigation: Clinical risk score development, internal validation, and net benefit analysis.

BACKGROUND: Unexpected weight loss (UWL) is a presenting feature of cancer in primary care. Existing research proposes simple combinations of clinical features (risk factors, symptoms, signs, and blood test data) that, when present, warrant cancer investigation. More complex combinations may modify cancer risk to sufficiently rule-out the need for investigation. We aimed to identify which clinical features can be used together to stratify patients with UWL based on their risk of cancer. METHODS AND FINDINGS: We used data from 63,973 adults (age: mean 59 years, standard deviation 21 years; 42% male) to predict cancer in patients with UWL recorded in a large representative United Kingdom primary care electronic health record between January 1, 2000 and December 31, 2012. We derived 3 clinical prediction models using logistic regression and backwards stepwise covariate selection: Sm, symptoms-only model; STm, symptoms and tests model; Tm, tests-only model. Fifty imputations replaced missing data. Estimates of discrimination and calibration were derived using 10-fold internal cross-validation. Simple clinical risk scores are presented for models with the greatest clinical utility in decision curve analysis. The STm and Tm showed improved discrimination (area under the curve ≥ 0.91), calibration, and greater clinical utility than the Sm. The Tm was simplest including age-group, sex, albumin, alkaline phosphatase, liver enzymes, C-reactive protein, haemoglobin, platelets, and total white cell count. A Tm score of 5 balanced ruling-in (sensitivity 84.0%, positive likelihood ratio 5.36) and ruling-out (specificity 84.3%, negative likelihood ratio 0.19) further cancer investigation. A Tm score of 1 prioritised ruling-out (sensitivity 97.5%). At this threshold, 35 people presenting with UWL in primary care would be referred for investigation for each person with cancer referred, and 1,730 people would be spared referral for each person with cancer not referred. Study limitations include using a retrospective routinely collected dataset, a reliance on coding to identify UWL, and missing data for some predictors. CONCLUSIONS: Our findings suggest that combinations of simple blood test abnormalities could be used to identify patients with UWL who warrant referral for investigation, while people with combinations of normal results could be exempted from referral.

Associations between dietary patterns and the incidence of total and fatal cardiovascular disease and all-cause mortality in 116,806 individuals from the UK Biobank: a prospective cohort study.

BACKGROUND: Traditionally, studies investigating diet and health associations have focused on single nutrients. However, key nutrients co-exist in many common foods, and studies focusing solely on individual nutrients may obscure their combined effects on cardiovascular disease (CVD) and all-cause mortality. We aimed to identify food-based dietary patterns which operate through excess energy intake and explain high variability in energy density, free sugars, saturated fat, and fiber intakes and to investigate their association with total and fatal CVD and all-cause mortality. METHODS: Detailed dietary data was collected using a 24-h online dietary assessment on two or more occasions (n = 116,806). We used reduced rank regression to derive dietary patterns explaining the maximum variance. Multivariable Cox-proportional hazards models were used to investigate prospective associations with all-cause mortality and fatal and non-fatal CVD. RESULTS: Over an average of 4.9 years of follow-up, 4245 cases of total CVD, 838 cases of fatal CVD, and 3629 cases of all-cause mortality occurred. Two dietary patterns were retained that jointly explained 63% of variation in energy density, free sugars, saturated fat, and fiber intakes in total. The main dietary pattern was characterized by high intakes of chocolate and confectionery, butter and low-fiber bread, and low intakes of fresh fruit and vegetables. There was a positive linear association between the dietary pattern and total CVD [hazard ratio (HR) per z-score 1.07, 95% confidence interval (CI) 1.04-1.09; HRtotal CVD 1.40, 95% CI 1.31-1.50, and HRall-cause mortality 1.37, 95% CI 1.27-1.47 in highest quintile]. A second dietary pattern was characterized by a higher intakes of sugar-sweetened beverages, fruit juice, and table sugar/preserves. There was a non-linear association with total CVD risk and all-cause mortality, with increased risk in the highest quintile [HRtotal CVD 1.14, 95% CI 1.07-1.22; HRall-cause mortality 1.11, 95% CI 1.03-1.19]. CONCLUSIONS: We identified dietary patterns which are associated with increased risk of CVD and all-cause mortality. These results help identify specific foods and beverages which are major contributors to unhealthy dietary patterns and provide evidence to underpin food-based dietary advice to reduce health risks.

Extended follow-up of a short total diet replacement programme: results of the Doctor Referral of Overweight People to Low Energy total diet replacement Treatment (DROPLET) randomised controlled trial at 3 years.

OBJECTIVES: To test the long-term effectiveness of a total diet replacement programme (TDR) for routine treatment of obesity in a primary care setting. METHODS: This study was a pragmatic, two-arm, parallel-group, open-label, individually randomised controlled trial in adults with obesity. The outcomes were change in weight and biomarkers of diabetes and cardiovascular disease risk from baseline to 3 years, analysed as intention-to-treat with mixed effects models. INTERVENTIONS: The intervention was TDR for 8 weeks, followed by food-reintroduction over 4 weeks. Behavioural support was provided weekly for 8 weeks, bi-weekly for the next 4 weeks, then monthly for 3 months after which no further support was provided. The usual care (UC) group received dietary advice and behavioural support from a practice nurse for up to 3 months. RESULTS: Outcome measures were collected from 179 (66%) participants. Compared with baseline, at 3 years the TDR group lost -6.2 kg (SD 9.1) and usual care -2.7 kg (SD 7.7); adjusted mean difference -3.3 kg (95% CI: -5.2, -1.5), p < 0.0001. Regain from programme end (6 months) to 3 years was greater in TDR group +8.9 kg (SD 9.4) than UC + 1.2, (SD 9.1); adjusted mean difference +6.9 kg (95% CI 4.2, 9.5) P < 0.001. At 3 years TDR led to greater reductions than UC in diastolic blood pressure (mean difference -3.3 mmHg (95% CI:-6.2; -0.4) P = 0.024), and systolic blood pressure (mean differences -3.7 mmHg (95% CI: -7.4; 0.1) P = 0.057). There was no evidence of differences between groups in the change from baseline to 3 years HbA1c (-1.9 mmol/mol (95% CI: -0.7; 4.5; P = 0.15), LDL cholesterol concentrations (0.2 mmol/L (95% CI -0.3, 0.7) P = 0.39), cardiovascular risk score (QRISK2) (-0.37 (95% CI -0.96; 0.22); P = 0.22). CONCLUSIONS: Treatment of people with obesity with a TDR programme compared with support from a practice nurse leads to greater weight loss which persists to at least 3 years, but there was only evidence of sustained improvements in BP and not in other aspects of cardiometabolic risk.

What Makes Opportunistic GP Interventions Effective? An Analysis of Behavior Change Techniques Used in 237 GP-Delivered Brief Interventions for Weight Loss.

BACKGROUND: Evidence shows that clinician-delivered brief opportunistic interventions are effective in obesity, and guidelines promote their use. However, there is no evidence on how clinicians should do this, and guidelines are not based on clinical evidence. PURPOSE: A trial (Brief Interventions for Weight Loss [BWeL]) showed that brief opportunistic interventions on obesity that endorsed, offered, and facilitated referral to community weight management service (CWMS) led to 77% agreeing to attend, and 40% attending CWMS, as well as significantly greater weight loss than control at 12 months. We assessed which behavior change techniques (BCTs) doctors used that were associated with CWMS attendance. METHODS: We coded 237 recorded BWeL interventions using the behavioral change techniques version one taxonomy. We also coded the BWeL training video to examine delivery of recommended BCTs. Mixed effects logistic regression assessed the association between each BCT, the total number of BCTs, and delivery of recommended BCTs, with patient's agreement to attend and actual CWMS attendance. RESULTS: Of 237 patients, 133 (56%) agreed to attend and 109 (46%) attended. Thirteen BCTs were used more than eight times but none of the 13 were associated with increased attendance. One, "practical social support," was significantly associated with increased patient agreement (odds ratio [OR] = 4.80, 95% confidence interval [CI] = 1.15, 20.13). Delivery of recommended BCTs and the total number of BCTs used were both associated with increased agreement (OR = 1.56, 95% CI = 1.09, 2.23 and OR = 1.34, 95% CI = 1.03, 1.75, respectively), but not attendance at CWMS (OR = 1.20, 95% CI = 0.98-1.47 and OR = 1.08, 95% CI = 0.94-1.24, respectively). CONCLUSIONS: There is no evidence that particular BCT can increase the effectiveness of brief opportunistic interventions for obesity in adults. However, using more BCTs and delivery of recommended BCTs may increase agreement to attend community weight management services.

Behavioural interventions for smoking cessation: an overview and network meta-analysis.

BACKGROUND: Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness. OBJECTIVES: To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary. METHODS: This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components. MAIN RESULTS: We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies. AUTHORS' CONCLUSIONS: Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.

ANTECEDENTES: El tabaquismo es una causa principal de enfermedad y muerte en todo el mundo. En las personas que fuman, dejar de fumar puede revertir gran parte del daño. Muchas personas utilizan intervenciones conductuales para ayudarles a dejar de fumar y estas intervenciones pueden variar considerablemente en contenido y efectividad. OBJETIVOS: Resumir la evidencia de las revisiones Cochrane que evaluaron el efecto de las intervenciones conductuales diseñadas para apoyar los intentos de abandono del hábito de fumar y realizar un metanálisis en red para determinar cómo las modalidades de prestación; la persona que administra la intervención; y la naturaleza, el enfoque y la intensidad de las intervenciones conductuales para el abandono del hábito de fumar influyen en la probabilidad de lograr la abstinencia seis meses después de intentar dejar de fumar; y si los efectos de las intervenciones conductuales dependen de otras características, como la población, el contexto y la administración de farmacoterapia. Resumir la disponibilidad y los hallazgos principales de las evaluaciones económicas de intervenciones conductuales para dejar de fumar, en términos de costes y coste­efectividad, mediante un breve comentario económico. MÉTODOS: Este artículo comprende dos elementos principales. 1. Se realizó una revisión global Cochrane de revisiones según los métodos estándar de Cochrane. Mediante una búsqueda en la Biblioteca Cochrane en julio de 2020 se identificaron las revisiones Cochrane de intervenciones conductuales (incluidas todas las intervenciones no farmacológicas, p.ej., orientación, ejercicio, hipnoterapia, materiales de autoayuda) para el abandono del hábito de fumar. La calidad metodológica de las revisiones se evaluó mediante AMSTAR 2 y los datos de las revisiones se resumieron de manera narrativa. 2. Las revisiones incluidas se utilizaron para identificar los ensayos controlados aleatorizados de intervenciones conductuales para el abandono del hábito de fumar en comparación con otras intervenciones conductuales o ninguna intervención para el abandono del hábito de fumar. Para ser incluidos, los estudios debían incluir a fumadores adultos y medir la abstinencia de fumar a los seis meses o más. La selección, la extracción de los datos y la evaluación del riesgo de sesgo siguieron los métodos Cochrane estándar. Los datos se resumieron mediante un metanálisis en red de componentes (MARC) bayesiano, y se examinaron los efectos de 38 componentes diferentes en comparación con una intervención mínima. Los componentes incluyeron elementos conductuales y motivacionales, proveedores de la intervención, modos de administración, naturaleza, enfoque e intensidad de la intervención conductual. Se utilizó la metarregresión en red de componentes (MRRC) para evaluar la influencia de las características de la población, la administración de farmacoterapia y la intensidad de la intervención sobre los efectos de los componentes. La certeza de la evidencia se evaluó mediante los dominios de GRADE. Se presupuso un efecto aditivo para los componentes individuales. RESULTADOS PRINCIPALES: Se incluyeron 33 revisiones Cochrane, de las cuales 312 ensayos controlados aleatorizados, que representaban a 250 563 participantes y 845 grupos de estudio distintos, cumplieron los criterios para su inclusión en el metanálisis en red de componentes. Esto representó 437 combinaciones diferentes de componentes. De las 33 revisiones, la confianza en los hallazgos de la revisión fue alta en cuatro y moderada en nueve, medida con la herramienta de lectura crítica AMSTAR 2. Las 20 revisiones restantes tuvieron una confianza baja o críticamente baja debido a una o más deficiencias graves, las más habituales fueron una investigación o discusión (o ambas) insuficiente acerca del impacto del sesgo de publicación. Cabe señalar que las debilidades críticas identificadas no afectaron los elementos de la búsqueda, la selección o la extracción de los datos del proceso de revisión, que mantienen una relación directa en este MARC. Entre los estudios incluidos, 125/312 tuvieron un riesgo general de sesgo bajo, 50 un riesgo de sesgo alto y el resto un riesgo de sesgo poco claro. Los análisis de las revisiones contribuyentes y de este MARC mostraron que las intervenciones conductuales para dejar de fumar pueden aumentar las tasas de abandono del hábito, pero la efectividad varía según las características del apoyo proporcionado. Hubo evidencia de certeza alta de un efecto beneficioso de la prestación de orientación (odds ratio [OR] 1,44; intervalo de credibilidad [ICr] del 95%: 1,22 a 1,70, 194 estudios, n = 72 273) y de los incentivos económicos garantizados (OR 1,46; ICr del 95% 1,15 a 1,85, 19 estudios, n = 8877). La evidencia de un efecto beneficioso se mantuvo cuando se eliminaron los estudios con alto riesgo de sesgo. Estos hallazgos fueron concordantes con los metanálisis pareados de las revisiones contribuyentes. Hubo evidencia de certeza moderada de un efecto beneficioso de las intervenciones administradas a través de mensajes de texto (la certeza se disminuyó debido a una heterogeneidad estadística inexplicada en la comparación pareada), y de los siguientes componentes en los que las estimaciones puntuales indicaron un efecto beneficioso pero los ICr no incorporaron una diferencia clínicamente significativa: personalización; contenido de la intervención con componentes motivacionales; contenido de la intervención centrado en cómo dejar de fumar. Los otros componentes de la intervención tuvieron evidencia de certeza muy baja a baja, y sus problemas principales fueron la imprecisión y el riesgo de sesgo. No hubo evidencia que indicara un aumento de los efectos perjudiciales en los grupos que recibieron apoyo conductual para dejar de fumar. Los efectos de la intervención no cambiaron al ajustar las características de la población, pero los datos fueron limitados. El aumento de la intensidad del apoyo conductual, medido a través del número de contactos, la duración de cada contacto y la duración del programa, tuvo estimaciones puntuales asociadas con un modesto aumento de las posibilidades de dejar de fumar, pero los ICr no incluyeron una diferencia. El efecto del apoyo conductual para dejar de fumar pareció ser ligeramente menos pronunciado cuando las personas ya recibían farmacoterapias para dejar de fumar. CONCLUSIONES DE LOS AUTORES: El apoyo conductual para dejar de fumar puede aumentar las tasas de abandono a los seis meses o más, sin evidencia de que este apoyo aumente los efectos perjudiciales. Esto es así tanto si se proporciona una farmacoterapia para dejar de fumar como si no, pero el efecto es ligeramente más pronunciado sin farmacoterapia. La evidencia de un efecto beneficioso es más sólida para la prestación de cualquier tipo de orientación y de incentivos económicos garantizados. La evidencia indicó un posible efecto beneficioso, pero la necesidad de realizar más estudios para evaluar: la personalización; la administración mediante mensajes de texto, correos electrónicos y grabaciones de audio; la administración por parte de un asesor de salud no profesional; y el contenido de la intervención con componentes motivacionales y centrada en cómo dejar de fumar. Se identificaron 23 evaluaciones económicas; la evidencia no indicó de manera homogénea que un tipo de intervención conductual para el abandono del hábito de fumar fuera más coste­efectiva que otra. Las revisiones futuras deberían examinar a fondo el sesgo de publicación. Se necesitan herramientas para investigar el sesgo de publicación y evaluar la certeza en MARC.