Modelling the implications of reducing smoking prevalence:The public health and economic benefits of achieving a 'tobacco-free' UK

IntroductionSmoking is still the most preventable cause of cancer, and a leading cause of premature mortality and health inequalities in the UK. This study modelled the health and economic impacts of achieving a ‘tobacco-free’ ambition (TFA) where, by 2035, less than 5% of the population smoke tobacco across all socioeconomic groups.MethodsA non-linear multivariate regression model was fitted to cross-sectional smoking data to create projections to 2035. These projections were used to predict the future incidence and costs of 17 smoking-related diseases using a microsimulation approach. The health and economic impacts of achieving a TFA were evaluated against a predicted baseline scenario, where current smoking trends continue.ResultsIf trends continue, the prevalence of smoking in the UK was projected to be 10% by 2035—well above a TFA. If this ambition were achieved by 2035, it could mean 97 300 +/- 5 300 new cases of smoking-related diseases are avoided by 2035 (tobacco-related cancers: 35 900+/- 4 100; chronic obstructive pulmonary disease: 29 000 +/- 2 700; stroke: 24 900 +/- 2 700; coronary heart disease: 7600 +/- 2 700), including around 12 350 diseases avoided in 2035 alone. The consequence of this health improvement is predicted to avoid £67 +/- 8 million in direct National Health Service and social care costs, and £548 million in non-health costs, in 2035 alone.ConclusionThese findings strengthen the case to set bold targets on long-term declines in smoking prevalence to achieve a tobacco ‘endgame’. Results demonstrate the health and economic benefits that meeting a TFA can achieve over just 20 years. Effective ambitions and policy interventions are needed to reduce the disease and economic burden of smoking.</jats:sec

Cost-effectiveness of bariatric surgery and non-surgical weight management programmes for adults with severe obesity : a decision analysis model

Acknowledgements We thank the REBALANCE Advisory Group for all their advice and support during this project: Margaret Watson, Lorna Van Lierop, Richard Clarke, Jennifer Logue, Laura Stewart, Richard Welbourn, Jamie Blackshaw, Su Sethi. +Current address HealthLumen, London. The REBALANCE team Elisabet Jacobsen1, Dwayne Boyers1, David Cooper3, Lise Retat2, Paul Aveyard4, Fiona Stewart3, Graeme MacLennan3, Laura Webber2, Emily Corbould2, Benshuai Xu2, Abbygail Jaccard2, Bonnie Boyle3, Eilidh Duncan3, Michal Shimonovich3, Cynthia Fraser3, Lara Kemp3, Clare Robertson3, Zoë Skea3, Marijn de Bruin6, Alison Avenell3 Funding The project was funded by the NIHR Health Technology Assessment Programme (Project number: 15/09/04). See the HTA Programme website for further project information. The Health Economics and Health Services Research Units at the University of Aberdeen are core funded by the Chief Scientists Office (CSO) of the Scottish Government Health and Social Care Directorate. Correction | Open Access | Published: 26 August 2021 Correction: Cost-effectiveness of bariatric surgery and non-surgical weight management programmes for adults with severe obesity: a decision analysis model. D. Boyers, L. Retat, E. Jacobsen, A. Avenell, P. Aveyard, E. Corbould, A. Jaccard, D. Cooper, C. Robertson, M. Aceves-Martins, B. Xu, Z. Skea, M. de Bruin & and the REBALANCE team. International Journal of Obesity (2021) The Original Article was published on 04 June 2021 Correction to: International Journal of Obesity https://doi.org/10.1038/s41366-021-00849-8Peer reviewedPublisher PD

Screening and brief intervention for obesity in primary care:cost-effectiveness analysis in the BWeL trial

This paper is closed access until 31 July 2019.Background: The Brief Intervention for Weight Loss Trial enrolled 1882 consecutively attending primary care patients who were obese and participants were randomised to physicians opportunistically endorsing, offering, and facilitating a referral to a weight loss programme (support) or recommending weight loss (advice). After one year, the support group lost 1.4 kg more (95%CI 0.9 to 2.0): 2.4 kg versus 1.0 kg. We use a cohort simulation to predict effects on disease incidence, quality of life, and healthcare costs over 20 years. Methods: Randomly sampling from the trial population, we created a virtual cohort of 20 million adults and assigned baseline morbidity. We applied the weight loss observed in the trial and assumed weight regain over four years. Using epidemiological data, we assigned the incidence of 12 weight-related diseases depending on baseline disease status, age, gender, body mass index. From a healthcare perspective, we calculated the quality adjusted life years (QALYs) accruing and calculated the incremental difference between trial arms in costs expended in delivering the intervention and healthcare costs accruing. We discounted future costs and benefits at 1.5% over 20 years. Results: Compared with advice, the support intervention reduced the cumulative incidence of weight-related disease by 722/100,000 people, 0.33% of all weight-related disease. The incremental cost of support over advice was £2.01million/100,000. However, the support intervention reduced health service costs by £5.86 million/100,000 leading to a net saving of £3.85 million/100,000. The support intervention produced 992 QALYs/100,000 people relative to advice. Conclusions: A brief intervention in which physicians opportunistically endorse, offer, and facilitate a referral to a behavioural weight management service to patients with a BMI of at least 30 kg/m2 reduces healthcare costs and improves health more than advising weight loss

Bariatric surgery, lifestyle interventions and orlistat for severe obesity : the REBALANCE mixed-methods systematic review and economic evaluation

Funding: The National Institute for Health Research Health Technology Assessment programme. The Health Services Research Unit and Health Economics Research Unit are core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorate. Corrigendum: Bariatric surgery, lifestyle interventions and orlistat for severe obesity: the REBALANCE mixed-methods systematic review and economic evaluation. Alison Avenell, Clare Robertson, Zoë Skea, Elisabet Jacobsen, Dwayne Boyers, David Cooper, Magaly Aceves-Martins, Lise Retat, Cynthia Fraser, Paul Aveyard, Fiona Stewart, Graeme MacLennan, Laura Webber, Emily Corbould, Benshuai Xu, Abbygail Jaccard, Bonnie Boyle, Eilidh Duncan, Michal Shimonovich, Marijn de Bruin, 2020, vol. 22, issue 68, p. 247-250. Health technology assessment (Winchester, England) Link to publication in Scopus. DOI.http://dx.doi.org/10.3310/hta22680-c202005Peer reviewedPublisher PD

How could different obesity scenarios alter the burden of type 2 diabetes and liver disease in Saudi Arabia?

Introduction Obesity is a major risk factor for type 2 diabetes (T2DM) and liver disease, and obesity-attributable liver disease is a common indication for liver transplant. Obesity prevalence in Saudi Arabia (SA) has increased in recent decades. SA has committed to the WHO ‘halt obesity’ target to shift prevalence to 2010 levels by 2025. We estimated the future benefits of reducing obesity in SA on incidence and costs of T2DM and liver disease under two policy scenarios: 1) SA meets the ‘halt obesity’ target; 2) population body mass index (BMI) is reduced by 1% annually from 2020 to 2040. Methods We developed a dynamic microsimulation of working-age people (20-59 years) in SA between 2010 and 2040. Model inputs included population demographic, disease and healthcare cost data, and relative risks of diseases associated with obesity. In our two policy scenarios, we manipulated population BMI and compared predicted disease incidence and associated healthcare costs to a baseline ‘no change’ scenario. Results Adults 1.15 million combined cases of T2DM, liver disease and liver cancer could be avoided by 2040. Healthcare cost savings for the ‘halt obesity’ and 1% reduction scenarios are 46.7 and 32.8 billion USD, respectively. Discussion/Conclusion SA’s younger working-age population is set to meet the ‘halt obesity’ target, but those aged 35-59 are off-track. Even a modest annual 1% BMI reduction could result in substantial future health and economic benefits. Our findings strongly support universal initiatives to reduce population-level obesity, with targeted initiatives for working-age people ≥35 years of age

Screening and brief intervention for obesity in primary care: a parallel, two-arm, randomised trial

Background 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. Methods 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. Findings 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 ( Interpretation A behaviourally-informed, very brief, physician-delivered opportunistic intervention is acceptable to patients and an effective way to reduce population mean weight.</p

Estimating the costs of air pollution to the National Health Service and social care : An assessment and forecast up to 2035

BACKGROUND: Air pollution damages health by promoting the onset of some non-communicable diseases (NCDs), putting additional strain on the National Health Service (NHS) and social care. This study quantifies the total health and related NHS and social care cost burden due to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in England. METHOD AND FINDINGS: Air pollutant concentration surfaces from land use regression models and cost data from hospital admissions data and a literature review were fed into a microsimulation model, that was run from 2015 to 2035. Different scenarios were modelled: (1) baseline 'no change' scenario; (2) individuals' pollutant exposure is reduced to natural (non-anthropogenic) levels to compute the disease cases attributable to PM2.5 and NO2; (3) PM2.5 and NO2 concentrations reduced by 1 μg/m3; and (4) NO2 annual European Union limit values reached (40 μg/m3). For the 18 years after baseline, the total cumulative cost to the NHS and social care is estimated at £5.37 billion for PM2.5 and NO2 combined, rising to £18.57 billion when costs for diseases for which there is less robust evidence are included. These costs are due to the cumulative incidence of air-pollution-related NCDs, such as 348,878 coronary heart disease cases estimated to be attributable to PM2.5 and 573,363 diabetes cases estimated to be attributable to NO2 by 2035. Findings from modelling studies are limited by the conceptual model, assumptions, and the availability and quality of input data. CONCLUSIONS: Approximately 2.5 million cases of NCDs attributable to air pollution are predicted by 2035 if PM2.5 and NO2 stay at current levels, making air pollution an important public health priority. In future work, the modelling framework should be updated to include multi-pollutant exposure-response functions, as well as to disaggregate results by socioeconomic status

Estimating the long-term health impacts of changes in alcohol consumption in England during the COVID-19 pandemic

AKA 'The COVID Hangover'. NIHR Policy Research Programme Award ID: NIHR20271