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Meat consumption is rising annually as human populations grow and affluence increases. Godfray et al. review this trend, which has major negative consequences for land and water use and environmental change. Although meat is a concentrated source of nutrients for low-income families, it also enhances the risks of chronic ill health, such as from colorectal cancer and cardiovascular disease. Changing meat consumption habits is a challenge that requires identifying the complex social factors associated with meat eating and developing policies for effective interventions. Science , this issue p. eaam5324 Both the global average per capita consumption of meat and the total amount of meat consumed are rising, driven by increasing average individual incomes and by population growth. The consumption of different types of meat and meat products has substantial effects on people’s health, and livestock production can have major negative effects on the environment. Here, we explore the evidence base for these assertions and the options policy-makers have should they wish to intervene to affect population meat consumption. We highlight where more research is required and the great importance of integrating insights from the natural and social sciences.

Background Reducing meat consumption can help prevent non-communicable diseases and protect the environment. Interventions targeting conscious determinants of human behaviour are generally acceptable approaches to promote dietary change, but little is known about their effectiveness to reduce the demand for meat. Objective To evaluate the effectiveness of interventions targeting conscious determinants of human behaviour to reduce the demand for meat. Methods We searched six electronic databases on the 31st of August 2017 with a predefined algorithm, screened publicly accessible resources, contacted authors, and conducted forward and backward reference searches. Eligible studies employed experimental designs to evaluate interventions targeting conscious determinants of human behaviour to reduce the consumption, purchase, or selection of meat in comparison to a control condition, a baseline period, or relative to other eligible interventions. We synthesised results narratively and conducted an exploratory crisp-set Qualitative Comparative Analysis to identify combinations of intervention characteristics associated with significant reductions in the demand for meat. Results We included 24 papers reporting on 59 interventions and 25,477 observations. Self-monitoring interventions and individual lifestyle counselling led to, or were associated with reduced meat consumption. Providing information about the health or environmental consequences of eating meat was associated with reduced intentions to consume and select meat in virtual environments, but there was no evidence to suggest this approach influenced actual behaviour. Education about the animal welfare consequences of eating meat was associated with reduced intentions to consume meat, while interventions implicitly highlighting animal suffering were not. Education on multiple consequences of eating meat led to mixed results. Tailored education was not found to reduce actual or intended meat consumption, though few studies assessed this approach. Conclusion Some interventions targeting conscious determinants of human behaviour have the potential to reduce the demand for meat. In particular, self-monitoring interventions and individual lifestyle counselling can help to reduce meat consumption. There was evidence of effectiveness of some educational messages in reducing intended consumption and selection of meat in virtual environments. Protocol registration CRD42017076720 .

Obesity is a common cause of non-communicable disease. Guidelines recommend that physicians screen and offer brief advice to motivate weight loss through referral to behavioural weight loss programmes. However, physicians rarely intervene and no trials have been done on the subject. We did this trial to establish whether physician brief intervention is acceptable and effective for reducing bodyweight in patients with obesity. In this parallel, two-arm, randomised trial, patients who consulted 137 primary care physicians in England were screened for obesity. Individuals could be enrolled if they were aged at least 18 years, had a body-mass index of at least 30 kg/m2 (or at least 25 kg/m2 if of Asian ethnicity), and had a raised body fat percentage. At the end of the consultation, the physician randomly assigned participants (1:1) to one of two 30 s interventions. Randomisation was done via preprepared randomisation cards labelled with a code representing the allocation, which were placed in opaque sealed envelopes and given to physicians to open at the time of treatment assignment. In the active intervention, the physician offered referral to a weight management group (12 sessions of 1 h each, once per week) and, if the referral was accepted, the physician ensured the patient made an appointment and offered follow-up. In the control intervention, the physician advised the patient that their health would benefit from weight loss. The primary outcome was weight change at 12 months in the intention-to-treat population, which was assessed blinded to treatment allocation. We also assessed asked patients' about their feelings on discussing their weight when they have visited their general practitioner for other reasons. Given the nature of the intervention, we did not anticipate any adverse events in the usual sense, so safety outcomes were not assessed. This trial is registered with the ISRCTN Registry, number ISRCTN26563137. Between June 4, 2013, and Dec 23, 2014, we screened 8403 patients, of whom 2728 (32%) were obese. Of these obese patients, 2256 (83%) agreed to participate and 1882 were eligible, enrolled, and included in the intention-to-treat analysis, with 940 individuals in the support group and 942 individuals in the advice group. 722 (77%) individuals assigned to the support intervention agreed to attend the weight management group and 379 (40%) of these individuals attended, compared with 82 (9%) participants who were allocated the advice intervention. In the entire study population, mean weight change at 12 months was 2·43 kg with the support intervention and 1·04 kg with the advice intervention, giving an adjusted difference of 1·43 kg (95% CI 0·89–1·97). The reactions of the patients to the general practitioners' brief interventions did not differ significantly between the study groups in terms of appropriateness (adjusted odds ratio 0·89, 95% CI 0·75–1·07, p=0·21) or helpfulness (1·05, 0·89–1·26, p=0·54); overall, four (<1%) patients thought their intervention was inappropriate and unhelpful and 1530 (81%) patients thought it was appropriate and helpful. A behaviourally-informed, very brief, physician-delivered opportunistic intervention is acceptable to patients and an effective way to reduce population mean weight. The UK National Prevention Research Initiative.

Keywords: Obesity, Food, Environment, Policy

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/m 2 , the hazard ratio (HR) was 1.42 (95% confidence interval 1.20 to 1.68), and for BMI ≥ 35 kg/m 2 , 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/m 2 had an HR of 1.09 (95% CI 0.99 to 1.21), and BMI ≥ 35 kg/m 2 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.

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; HR total CVD 1.40, 95% CI 1.31–1.50, and HR all-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 [HR total CVD 1.14, 95% CI 1.07–1.22; HR all-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.

Background Waterpipe smoking is becoming popular among western students. The aim was to understand the appeal to students of this form of smoking when other forms of smoking are becoming less common. Methods Waterpipe smokers were identified by snowball sampling and interviewed following a semi-structured schedule in waterpipe cafes and in their homes. Constant comparative analysis was used to derive themes for the analysis. Results Waterpipe smokers saw smoking as an alternative to more expensive nights out in bars. The appeal was related to the communal activity and the novelty of the experience. Respondents had not thought deeply about the health risks and reasoned that if no warnings about waterpipe smoking were apparent (unlike cigarette smoking) then it was probably safe. These observations were reinforced by observations about the mildness of the smoke, the fruit flavours, and beliefs about the filtering of the water. Waterpipe smokers felt no pressure to stop smoking and therefore had not tried to do so, but felt it might be something they did not continue after university. Waterpipe smoking was not linked in students' minds to other forms of smoking except in one individual who was using waterpipe smoking to help quit cigarettes. Conclusion In the absence of public health information, students have fallen back on superficial experiences to form views that waterpipe smoking is less harmful than other forms of smoking and it is currently much more acceptable in student society than other forms of smoking.

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.

Evidence exist that primary care referral to an open-group behavioural programme is an effective strategy for management of obesity, but little evidence on optimal intervention duration is available. We aimed to establish whether 52-week referral to an open-group weight-management programme would achieve greater weight loss and improvements in a range of health outcomes and be more cost-effective than the current practice of 12-week referrals. In this non-blinded, parallel-group, randomised controlled trial, we recruited participants who were aged 18 years or older and had body-mass index (BMI) of 28 kg/m2 or higher from 23 primary care practices in England. Participants were randomly assigned (2:5:5) to brief advice and self-help materials, a weight-management programme (Weight Watchers) for 12 weeks, or the same weight-management programme for 52 weeks. We followed-up participants over 2 years. The primary outcome was weight at 1 year of follow-up, analysed with mixed-effects models according to intention-to-treat principles and adjusted for centre and baseline weight. In a hierarchical closed-testing procedure, we compared combined behavioural programme arms with brief intervention, then compared the 12-week programme and 52-week programme. We did a within-trial cost-effectiveness analysis using person-level data and modelled outcomes over a 25-year time horizon using microsimulation. This study is registered with Current Controlled Trials, number ISRCTN82857232. Between Oct 18, 2012, and Feb 10, 2014, we enrolled 1269 participants. 1267 eligible participants were randomly assigned to the brief intervention (n=211), the 12-week programme (n=528), and the 52-week programme (n=528). Two participants in the 12-week programme had been found to be ineligible shortly after randomisation and were excluded from the analysis. 823 (65%) of 1267 participants completed an assessment at 1 year and 856 (68%) participants at 2 years. All eligible participants were included in the analyses. At 1 year, mean weight changes in the groups were −3·26 kg (brief intervention), −4·75 kg (12-week programme), and −6·76 kg (52-week programme). Participants in the behavioural programme lost more weight than those in the brief intervention (adjusted difference −2·71 kg, 95% CI −3·86 to −1·55; p<0·0001). The 52-week programme was more effective than the 12-week programme (−2·14 kg, −3·05 to −1·22; p<0·0001). Differences between groups were still significant at 2 years. No adverse events related to the intervention were reported. Over 2 years, the incremental cost-effectiveness ratio (ICER; compared with brief intervention) was £159 per kg lost for the 52-week programme and £91 per kg for the 12-week programme. Modelled over 25 years after baseline, the ICER for the 12-week programme was dominant compared with the brief intervention. The ICER for the 52-week programme was cost-effective compared with the brief intervention (£2394 per quality-adjusted life-year [QALY]) and the 12-week programme (£3804 per QALY). For adults with overweight or obesity, referral to this open-group behavioural weight-loss programme for at least 12 weeks is more effective than brief advice and self-help materials. A 52-week programme produces greater weight loss and other clinical benefits than a 12-week programme and, although it costs more, modelling suggests that the 52-week programme is cost-effective in the longer term. National Prevention Research Initiative, Weight Watchers International (as part of an UK Medical Research Council Industrial Collaboration Award).

Background Action on smoking, obesity, excess alcohol, and physical inactivity in primary care is effective and cost-effective, but implementation is low. The aim was to examine the effectiveness of strategies to increase the implementation of preventive healthcare in primary care. Methods CINAHL, CENTRAL, The Cochrane Database of Systematic Reviews, Dissertations & Theses – Global, Embase, Europe PMC, MEDLINE and PsycINFO were searched from inception through 5 October 2023 with no date of publication or language limits. Randomised trials, non-randomised trials, controlled before-after studies and interrupted time series studies comparing implementation strategies (team changes; changes to the electronic patient registry; facilitated relay of information; continuous quality improvement; clinician education; clinical reminders; financial incentives or multicomponent interventions) to usual care were included. Two reviewers screened studies, extracted data, and assessed bias with an adapted Cochrane risk of bias tool for Effective Practice and Organisation of Care reviews. Meta-analysis was conducted with random-effects models. Narrative synthesis was conducted where meta-analysis was not possible. Outcome measures included process and behavioural outcomes at the closest point to 12 months for each implementation strategy. Results Eighty-five studies were included comprising of 4,210,946 participants from 3713 clusters in 71 cluster trials, 6748 participants in 5 randomised trials, 5,966,552 participants in 8 interrupted time series, and 176,061 participants in 1 controlled before after study. There was evidence that clinical reminders (OR 3.46; 95% CI 1.72–6.96; I 2  = 89.4%), clinician education (OR 1.89; 95% CI 1.46–2.46; I 2  = 80.6%), facilitated relay of information (OR 1.95, 95% CI 1.10–3.46, I 2  = 88.2%), and multicomponent interventions (OR 3.10; 95% CI 1.60–5.99, I 2  = 96.1%) increased processes of care. Multicomponent intervention results were robust to sensitivity analysis. There was no evidence that other implementation strategies affected processes of care or that any of the implementation strategies improved behavioural outcomes. No studies reported on interventions specifically designed for remote consultations. Limitations included high statistical heterogeneity and many studies did not account for clustering. Conclusions Multicomponent interventions may be the most effective implementation strategy. There was no evidence that implementation interventions improved behavioural outcomes. Trial registration PROSPERO CRD42022350912.