Socioeconomic inequalities in accumulation of multimorbidity in England from 2019 to 2049: a microsimulation projection study.

BACKGROUND: There are socioeconomic inequalities in the prevalence of multimorbidity and its accumulation across the life course. Estimates of multimorbidity prevalence in English primary care increased by more than two-thirds from 2004 to 2019. We developed a microsimulation model to quantify current and projected multimorbidity inequalities in the English adult population. METHODS: We used primary care data for adults in England from the Clinical Practice Research Datalink Aurum database between 2004 and 2019, linked to the 2015 English Index of Multiple Deprivation (IMD), to model time individuals spent in four health states (healthy, one chronic condition, basic multimorbidity [two or more chronic conditions], and complex multimorbidity [three or more chronic conditions affecting three or more body systems]) by sex, age, IMD quintile, birth cohort, and region. We applied these transition times in a stochastic dynamic continuous-time microsimulation model to Office for National Statistics population estimates for adults aged 30-90 years. We calculated projected prevalence and cumulative incident cases from 2019 to 2049 by IMD quintile, age group (younger than 65 years vs 65 years and older), and years to be lived without multimorbidity at age 30 years. FINDINGS: Under the assumption that all chronic conditions were lifelong, and that once diagnosed there was no recovery, we projected prevalence of multimorbidity (basic or complex) increases by 34% from 53·8% in 2019 to 71·9% (95% uncertainty interval 71·8-72·0) in 2049. This rise equates to an 84% increase in the number of people with multimorbidity: from 19·2 million in 2019 to 35·3 million in 2049 (35·3 million to 35·4 million). This projected increase is greatest in the most deprived quintile, with an excess 1·07 million (1·04 million to 1·10 million) cumulative incident basic multimorbidity cases and 0·70 million (0·67 million to 0·74 million) complex multimorbidity cases over and above the projected cases for the least deprived quintile, largely driven by inequalities in those younger than 65 years. The median expected number of years to be lived without multimorbidity at age 30 years in 2019 is 15·12 years (14·62-16·01) in the least deprived IMD quintile and 12·15 years (11·61-12·60) in the most deprived IMD quintile. INTERPRETATION: The number of people living with multimorbidity will probably increase substantially in the next 30 years, a continuation of past observed increases partly driven by changing population size and age structure. Inequalities in the multimorbidity burden increase at each stage of disease accumulation, and are projected to widen, particularly among the working-age population. Substantial action is needed now to address population health and to prepare health-care and social-care systems for coming decades. FUNDING: University of Liverpool and National Institute for Health and Care Research School for Public Health Research.

Effect of calorie labelling in the out-of-home food sector on adult obesity prevalence, cardiovascular mortality, and social inequalities in England: a modelling study.

BACKGROUND: England implemented a menu calorie labelling policy in large, out-of-home food businesses in 2022. We aimed to model the likely policy impact on population-level obesity and cardiovascular disease mortality, as well as the socioeconomic equity of estimated effects, in the adult population in England. METHODS: For this modelling analysis, we built a comparative assessment model using two scenarios: the current implementation scenario refers to actual deployment only in large (≥250 employees), out-of-home food businesses, whereas the full implementation scenario refers to deployment in every out-of-home food business. We compared each scenario with a counterfactual: the scenario in which no intervention is implemented (ie, baseline). For both scenarios, we modelled the impact of the policy through assumed changes in energy intake due to either consumer response or product reformulation by retailers. We used data from the Office for National Statistics and the National Diet and Nutrition Survey 2009-19, and modelled the effect over 20 years (ie, 2022-41) to capture the long-term impact of the policy and provided mid-period results after 10 years. We used the Monte Carlo approach (2500 iterations) to estimate the uncertainty of model parameters. For each scenario, the model generated the change in obesity prevalence and the total number of deaths prevented or postponed. FINDINGS: The current implementation scenario was estimated to reduce obesity prevalence by 0·31 percentage points (absolute; 95% uncertainty interval [UI] 0·10-0·35), which would prevent or postpone 730 cardiovascular disease deaths (UI 430-1300) of the 830 000 deaths (UI 600 000-1 200 000) expected over 20 years. However, the health benefits would be increased if calorie labelling was implemented in all out-of-home food businesses (2·65 percentage points reduction in obesity prevalence [UI 1·97-3·24] and 9200 cardiovascular disease deaths prevented or postponed [UI 5500-16 000]). Results were similar in the most and the least deprived socioeconomic groups. INTERPRETATION: This study offers the first modelled estimation of the impact of the menu calorie labelling regulation on the adult population in England, although we did not include a cost-effectiveness analysis. Calorie labelling might result in a reduction in obesity prevalence and cardiovascular disease mortality without widening health inequalities. However, our results emphasise the need for the government to be more ambitious by applying this policy to all out-of-home food businesses to maximise impact. FUNDING: European Research Council.

Health, economic, and equity consequences of future tobacco control policies in England: a microsimulation study.

BACKGROUND: Smoking still generates a huge, costly, and inequitable burden of disease. The UK tobacco-free generation target to reduce smoking prevalence to below 5% by 2030 will be missed if current trends continue. We aimed to determine whether additional policies could speed progress towards meeting the tobacco-free generation target. METHODS: We developed, calibrated, and validated a microsimulation model, IMPACTHINT simulating English adults aged 30-89 years from 2023 to 2072. The model included a detailed smoking history and quantified policy health outcomes including smoking prevalence and smoking-related diseases, economics, and equity. We simulated five scenarios: (1) baseline trends; (2) increasing the minimum age of access to tobacco to 21 years (MinAge21); (3) a 30% increase in tobacco duty (TaxUP); (4) improved smoking cessation services (ServicesUP); and (5) a combination of TaxUP and ServicesUP. We estimated the smoking prevalence, smoking-related diseases and cumulative cases prevented or postponed, and deaths. We evaluated the scenario cost-effectiveness from the societal perspective. Lastly, we analysed the results by deprivation quintile. We present in our findings cumulative cases prevented or postponed over 50 years. FINDINGS: None of the scenarios would reduce overall smoking prevalence to below 5% by 2030. However, that goal could be reached by 2035 under the TaxUP and the combination of TaxUP and ServicesUP scenarios, by 2037 under the ServicesUP scenario, or by 2038 under the MinAge21 and the baseline scenarios. By 2072, the combined scenario might reduce smoking-related diseases by 160 000 cases (95% CI 140 000-200 000), greatly exceeding the reductions by 140 000 cases (120 000-180 000) with TaxUP, 69 000 cases (53 000-86 000) with MinAge21, or 22 000 cases (14 000-31 000) with ServicesUP. Some 50% of all disease-years reduced by TaxUP would occur in the most deprived quintile. The most affluent quintile could reach the 5% goal sooner than the most deprived quintile (by 2032 for the least deprived vs 2038 for the most deprived), and it could reach the 5% target by 2030 under the combined TaxUP and ServicesUP scenario. Finally, all policies would save costs compared with the baseline trend. INTERPRETATION: Affluent groups will achieve the 5% tobacco-free goal a decade sooner than the most deprived. However, that goal could be achieved in all groups by 2035 through a 30% increase in tax and enhanced smoking cessation services. Our limitations included the uncertainties of any 50-year forecast. However, that long time-horizon can capture the potential policy benefits for younger age groups. FUNDING: Economic and Social Research Council.

Projected health and economic impacts of sugar-sweetened beverage taxation in Germany: A cross-validation modelling study.

BACKGROUND: Taxes on sugar-sweetened beverages (SSBs) have been implemented globally to reduce the burden of cardiometabolic diseases by disincentivizing consumption through increased prices (e.g., 1 peso/litre tax in Mexico) or incentivizing industry reformulation to reduce SSB sugar content (e.g., tiered structure of the United Kingdom [UK] Soft Drinks Industry Levy [SDIL]). In Germany, where no tax on SSBs is enacted, the health and economic impact of SSB taxation using the experience from internationally implemented tax designs has not been evaluated. The objective of this study was to estimate the health and economic impact of national SSBs taxation scenarios in Germany. METHODS AND FINDINGS: In this modelling study, we evaluated a 20% ad valorem SSB tax with/without taxation of fruit juice (based on implemented SSB taxes and recommendations) and a tiered tax (based on the UK SDIL) in the German adult population aged 30 to 90 years from 2023 to 2043. We developed a microsimulation model (IMPACTNCD Germany) that captures the demographics, risk factor profile and epidemiology of type 2 diabetes, coronary heart disease (CHD) and stroke in the German population using the best available evidence and national data. For each scenario, we estimated changes in sugar consumption and associated weight change. Resulting cases of cardiometabolic disease prevented/postponed and related quality-adjusted life years (QALYs) and economic impacts from healthcare (medical costs) and societal (medical, patient time, and productivity costs) perspectives were estimated using national cost and health utility data. Additionally, we assessed structural uncertainty regarding direct, body mass index (BMI)-independent cardiometabolic effects of SSBs and cross-validated results with an independently developed cohort model (PRIMEtime). We found that SSB taxation could reduce sugar intake in the German adult population by 1 g/day (95%-uncertainty interval [0.05, 1.65]) for a 20% ad valorem tax on SSBs leading to reduced consumption through increased prices (pass-through of 82%) and 2.34 g/day (95%-UI [2.32, 2.36]) for a tiered tax on SSBs leading to 30% reduction in SSB sugar content via reformulation. Through reductions in obesity, type 2 diabetes, and cardiovascular disease (CVD), 106,000 (95%-UI [57,200, 153,200]) QALYs could be gained with a 20% ad valorem tax and 192,300 (95%-UI [130,100, 254,200]) QALYs with a tiered tax. Respectively, €9.6 billion (95%-UI [4.7, 15.3]) and €16.0 billion (95%-UI [8.1, 25.5]) costs could be saved from a societal perspective over 20 years. Impacts of the 20% ad valorem tax were larger when additionally taxing fruit juice (252,400 QALYs gained, 95%-UI [176,700, 325,800]; €11.8 billion costs saved, 95%-UI [€6.7, €17.9]), but impacts of all scenarios were reduced when excluding direct health effects of SSBs. Cross-validation with PRIMEtime showed similar results. Limitations include remaining uncertainties in the economic and epidemiological evidence and a lack of product-level data. CONCLUSIONS: In this study, we found that SSB taxation in Germany could help to reduce the national burden of noncommunicable diseases and save a substantial amount of societal costs. A tiered tax designed to incentivize reformulation of SSBs towards less sugar might have a larger population-level health and economic impact than an ad valorem tax that incentivizes consumer behaviour change only through increased prices.

Quantifying the mental health and economic impacts of prospective Universal Basic Income schemes among young people in the UK: a microsimulation modelling study.

OBJECTIVE: Universal Basic Income (UBI)-a largely unconditional, regular payment to all adults to support basic needs-has been proposed as a policy to increase the size and security of household incomes and promote mental health. We aimed to quantify its long-term impact on mental health among young people in England. METHODS: We produced a discrete-time dynamic stochastic microsimulation that models a close-to-reality open cohort of synthetic individuals (2010-2030) based on data from Office for National Statistics and Understanding Society. Three UBI scheme scenarios were simulated: Scheme 1-Starter (per week): £41 per child; £63 per adult over 18 and under 65; £190 per adult aged 65+; Scheme 2-Intermediate (per week): £63 per child; £145 per adult under 65; £190 per adult aged 65+; Scheme 3-Minimum Income Standard level (per week): £95 per child; £230 per adult under 65; £230 per adult aged 65+. We reported cases of anxiety and depression prevented or postponed and cost savings. Estimates are rounded to the second significant digit. RESULTS: Scheme 1 could prevent or postpone 200 000 (95% uncertainty interval: 180 000 to 210 000) cases of anxiety and depression from 2010 to 2030. This would increase to 420 000(400 000 to 440 000) for Scheme 2 and 550 000(520 000 to 570 000) for Scheme 3. Assuming that 50% of the cases are diagnosed and treated, Scheme 1 could save £330 million (£280 million to £390 million) to National Health Service (NHS) and personal social services (PSS), over the same period, with Scheme 2 (£710 million (£640 million to £790 million)) or Scheme 3 (£930 million (£850 million to £1000 million)) producing more considerable savings. Overall, total cost savings (including NHS, PSS and patients' related costs) would range from £1.5 billion (£1.2 billion to £1.8 billion) for Scheme 1 to £4.2 billion (£3.7 billion to £4.6 billion) for Scheme 3. CONCLUSION: Our modelling suggests that UBI could substantially benefit young people's mental health, producing substantial health-related cost savings.

Forecasting the mortality burden of coronary heart disease and stroke in Germany: National trends and regional inequalities.

BACKGROUND: The decline of cardiovascular disease (CVD) mortality has slowed in many countries, including Germany. We examined the implications of this trend for future coronary heart disease (CHD) and stroke mortality in Germany considering persistent mortality inequalities between former East and West Germany. METHODS: We retrieved demographic and mortality data from 1991 to 2019 from the German Federal Statistical Office. Using a Bayesian age-period-cohort framework, we projected CHD and stroke mortality from 2019 to 2035, stratified by sex and German region. We decomposed annual changes in deaths into three components (mortality rates, population age structure and population size) and assessed regional inequalities with age-sex-standardized mortality ratios. RESULTS: We confirmed that declines of CVD mortality rates in Germany will likely stagnate. From 2019 to 2035, we projected fewer annual CHD deaths (114,600 to 103,500 [95%-credible interval: 81,700; 134,000]) and an increase in stroke deaths (51,300 to 53,700 [41,400; 72,000]). Decomposing past and projected mortality, we showed that population ageing was and is offset by declining mortality rates. This likely reverses after 2030 leading to increased CVD deaths thereafter. Inequalities between East and West declined substantially since 1991 and are projected to stabilize for CHD but narrow for stroke. CONCLUSIONS: CVD deaths in Germany likely keep declining until 2030, but may increase thereafter due to population ageing if the reduction in mortality rates slows further. East-West mortality inequalities for CHD remain stable but may converge for stroke. Underlying risk factor trends need to be monitored and addressed by public health policy.

Projections of future coronary heart disease and stroke mortality in Japan until 2040: a Bayesian age-period-cohort analysis.

Background: We aimed to estimate the future burden of coronary heart disease (CHD) and stroke mortalities by sex and all 47 prefectures of Japan until 2040 while accounting for effects of age, period, and cohort and integrating them to be at the national level to account for regional differences among prefectures. Methods: We estimated future CHD and stroke mortality projections, developing Bayesian age-period-cohort (BAPC) models in population and the number of CHD and stroke by age, sex, and all 47 prefectures observed from 1995 to 2019; then applying these to official future population estimates until 2040. The present participants were all men and women aged over 30 years and were residents of Japan. Findings: In the BAPC models, the predicted number of national-level cardiovascular deaths from 2020 to 2040 would decrease (39,600 [95% credible interval: 32,200-47,900] to 36,200 [21,500-58,900] CHD deaths in men, and 27,400 [22,000-34,000] to 23,600 [12,700-43,800] in women; and 50,400 [41,900-60,200] to 40,800 [25,200-67,800] stroke deaths in men, and 52,200 [43,100-62,800] to 47,400 [26,800-87,200] in women). Interpretation: After adjusting these factors, future CHD and stroke deaths will decline until 2040 at the national level and in most prefectures. Funding: This research was supported by the Intramural Research Fund of Cardiovascular Diseases of the National Cerebral and Cardiovascular Center (21-1-6, 21-6-8), JSPS KAKENHI Grant Number JP22K17821, and the Ministry of Health, Labour and Welfare Comprehensive Research on Life-Style Related (Diseases Cardiovascular Diseases and Diabetes Mellitus Program), Grant Number 22FA1015.

Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework.

BACKGROUND: Policy simulation models (PSMs) have been used extensively to shape health policies before real-world implementation and evaluate post-implementation impact. This systematic review aimed to examine best practices, identify common pitfalls in tobacco control PSMs and propose a modelling quality assessment framework. METHODS: We searched five databases to identify eligible publications from July 2013 to August 2019. We additionally included papers from Feirman et al for studies before July 2013. Tobacco control PSMs that project tobacco use and tobacco-related outcomes from smoking policies were included. We extracted model inputs, structure and outputs data for models used in two or more included papers. Using our proposed quality assessment framework, we scored these models on population representativeness, policy effectiveness evidence, simulated smoking histories, included smoking-related diseases, exposure-outcome lag time, transparency, sensitivity analysis, validation and equity. FINDINGS: We found 146 eligible papers and 25 distinct models. Most models used population data from public or administrative registries, and all performed sensitivity analysis. However, smoking behaviour was commonly modelled into crude categories of smoking status. Eight models only presented overall changes in mortality rather than explicitly considering smoking-related diseases. Only four models reported impacts on health inequalities, and none offered the source code. Overall, the higher scored models achieved higher citation rates. CONCLUSIONS: While fragments of good practices were widespread across the reviewed PSMs, only a few included a 'critical mass' of the good practices specified in our quality assessment framework. This framework might, therefore, potentially serve as a benchmark and support sharing of good modelling practices.

Estimating the health and economic effects of the voluntary sodium reduction targets in Brazil: microsimulation analysis.

BACKGROUND: Excessive sodium consumption is one of the leading dietary risk factors for non-communicable diseases, including cardiovascular disease (CVD), mediated by high blood pressure. Brazil has implemented voluntary sodium reduction targets with food industries since 2011. This study aimed to analyse the potential health and economic impact of these sodium reduction targets in Brazil from 2013 to 2032. METHODS: We developed a microsimulation of a close-to-reality synthetic population (IMPACTNCD-BR) to evaluate the potential health benefits of setting voluntary upper limits for sodium content as part of the Brazilian government strategy. The model estimates CVD deaths and cases prevented or postponed, and disease treatment costs. Model inputs were informed by the 2013 National Health Survey, the 2008-2009 Household Budget Survey, and high-quality meta-analyses, assuming that all individuals were exposed to the policy proportionally to their sodium intake from processed food. Costs included costs of the National Health System on CVD treatment and informal care costs. The primary outcome measures of the model are cardiovascular disease cases and deaths prevented or postponed over 20 years (2013-2032), stratified by age and sex. RESULTS: The study found that the application of the Brazilian voluntary sodium targets for packaged foods between 2013 and 2032 could prevent or postpone approximately 110,000 CVD cases (95% uncertainty intervals (UI): 28,000 to 260,000) among men and 70,000 cases among women (95% UI: 16,000 to 170,000), and also prevent or postpone approximately 2600 CVD deaths (95% UI: - 1000 to 11,000), 55% in men. The policy could also produce a net cost saving of approximately US$ 220 million (95% UI: US$ 54 to 520 million) in medical costs to the Brazilian National Health System for the treatment of CHD and stroke and save approximately US$ 71 million (95% UI: US$ 17 to170 million) in informal costs. CONCLUSION: Brazilian voluntary sodium targets could generate substantial health and economic impacts. The reduction in sodium intake that was likely achieved from the voluntary targets indicates that sodium reduction in Brazil must go further and faster to achieve the national and World Health Organization goals for sodium intake.

Tobacco Control Policy Simulation Models: Protocol for a Systematic Methodological Review.

BACKGROUND: Tobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. OBJECTIVE: The aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. METHODS: Two reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. RESULTS: Data collection is in progress. Results are expected to be completed and submitted for publication by April 2021. CONCLUSIONS: This systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26854.

Modelling tool to support decision-making in the NHS Health Check programme: workshops, systematic review and co-production with users.

BACKGROUND: Local authorities in England commission the NHS Health Check programme to invite everyone aged 40-74 years without pre-existing conditions for risk assessment and eventual intervention, if needed. However, the programme's effectiveness, cost-effectiveness and equity impact remain uncertain. AIM: To develop a validated open-access flexible web-based model that enables local commissioners to quantify the cost-effectiveness and potential for equitable population health gain of the NHS Health Check programme. OBJECTIVES: The objectives were as follows: (1) co-produce with stakeholders the desirable features of the user-friendly model; (2) update the evidence base to support model and scenario development; (3) further develop our computational model to allow for developments and changes to the NHS Health Check programme and the diseases it addresses; (4) assess the effectiveness, cost-effectiveness and equity of alternative strategies for implementation to illustrate the use of the tool; and (5) propose a sustainability and implementation plan to deploy our user-friendly computational model at the local level. DESIGN: Co-production workshops surveying the best-performing local authorities and a systematic literature review of strategies to increase uptake of screening programmes informed model use and development. We then co-produced the workHORSE (working Health Outcomes Research Simulation Environment) model to estimate the health, economic and equity impact of different NHS Health Check programme implementations, using illustrative-use cases. SETTING: Local authorities in England. PARTICIPANTS: Stakeholders from local authorities, Public Health England, the NHS, the British Heart Foundation, academia and other organisations participated in the workshops. For the local authorities survey, we invited 16 of the best-performing local authorities in England. INTERVENTIONS: The user interface allows users to vary key parameters that represent programme activities (i.e. invitation, uptake, prescriptions and referrals). Scenarios can be compared with each other. MAIN OUTCOME MEASURES: Disease cases and case-years prevented or postponed, incremental cost-effectiveness ratios, net monetary benefit and change in slope index of inequality. RESULTS: The survey of best-performing local authorities revealed a diversity of effective approaches to maximise the coverage and uptake of NHS Health Check programme, with no distinct 'best buy'. The umbrella literature review identified a range of effective single interventions. However, these generally need to be combined to maximally improve uptake and health gains. A validated dynamic, stochastic microsimulation model, built on robust epidemiology, enabled service options analysis. Analyses of three contrasting illustrative cases estimated the health, economic and equity impact of optimising the Health Checks, and the added value of obtaining detailed local data. Optimising the programme in Liverpool can become cost-effective and equitable, but simply changing the invitation method will require other programme changes to improve its performance. Detailed data inputs can benefit local analysis. LIMITATIONS: Although the approach is extremely flexible, it is complex and requires substantial amounts of data, alongside expertise to both maintain and run. CONCLUSIONS: Our project showed that the workHORSE model could be used to estimate the health, economic and equity impact comprehensively at local authority level. It has the potential for further development as a commissioning tool and to stimulate broader discussions on the role of these tools in real-world decision-making. FUTURE WORK: Future work should focus on improving user interactions with the model, modelling simulation standards, and adapting workHORSE for evaluation, design and implementation support. STUDY REGISTRATION: This study is registered as PROSPERO CRD42019132087. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 35. See the NIHR Journals Library website for further project information.

The NHS Health Check programme is available for adults aged 40­74 years in England to find the early risk of heart disease, cancers, lung disease and dementia, and lower that risk. However, some studies have suggested that the current scheme could perhaps be improved. We systematically looked at previous studies to understand what makes a screening programme successful. We also contacted local authorities with the best NHS Health Check programmes to find out how they were being delivered so well. The most successful local authorities highlighted a wide variety of methods for achieving success. All had concrete plans in place for delivery, including different approaches for encouraging more adults to participate. We further developed our existing computer model into a web-based tool [workHORSE (working Health Outcomes Research Simulation Environment)]. This tool can help those responsible for commissioning NHS Health Checks to further improve the delivery of their local programme. We held four workshops with relevant professionals to develop the workHORSE model. These workshops resulted in a useful 'real-world' tool for local commissioners: a tool that can calculate the current and potential future benefits of different programmes. We used the model to show how commissioners can explore and compare a variety of different programmes. We found that combining several improvements can be useful. However, this provides modest benefits in improving health and value for money. At the same time, the impact on reducing inequalities is less clear and depends on the interventions used. Our results suggest that: a variety of successful approaches can be used to help increase the uptake of screening programmes such as NHS Health Checksjointly developing a computer model with end-users leads to a more user-friendly and relevant model to improve the programmethe stage is now set for further work to identify the best approach in each local area.

Inequalities in incident and prevalent multimorbidity in England, 2004-19: a population-based, descriptive study.

BACKGROUND: The increasing burden of multimorbidity and its socioeconomic gradient poses unique challenges to the provision and structure of health care. We aimed to describe inequalities and trends over time in multimorbidity prevalence, incidence, and case fatality among adults of all ages in England using primary care electronic health records. METHODS: We used a random sample of 991 243 individuals from the Clinical Practice Research Datalink Aurum database registered at participating general practices within England between Jan 1, 2004, and Dec 31, 2019, linked to the 2015 English Index of Multiple Deprivation (IMD). We used the following two outcome measures: basic multimorbidity, comprising two or more chronic conditions; and complex multimorbidity, comprising at least three chronic conditions affecting at least three body systems. We calculated crude, age-standardised, and age-sex-standardised annual incidence, prevalence, and case fatality rates, along with median age of onset for both multimorbidity types. We calculated absolute and relative inequalities for each outcome. FINDINGS: In 2004, 30·8% of our study population had basic multimorbidity and 15·1% had complex multimorbidity. This increased to 52·8% and 32·7%, respectively, in 2019. Although the overall incidence of basic multimorbidity remained stable over the 16-year study period, the incidence among people of working age and the incidence of complex multimorbidity increased gradually. Socioeconomic deprivation was associated with an increased incidence of both multimorbidity types in working-age adults. The median age at onset of complex multimorbidity was 7 years younger for the most deprived quintile of the IMD compared with the least deprived quintile. INTERPRETATION: The burden of multimorbidity in England has increased substantially over the past 16 years with persistent inequalities, which are worse in working-age adults and for complex multimorbidity. Prevention efforts to reduce the onset and slow the progression of multimorbidity are essential to reduce the increasing impact on patients and health systems alike. FUNDING: University of Liverpool and UK National Institute for Health Research School for Public Health Research.

Multimorbidity: the case for prevention.

Multimorbidity is of increasing concern for healthcare systems globally, particularly in the context of ageing population structures, such as in the European Union and the UK. Although there is growing attention on developing strategies to manage the health and healthcare burden of older patients with multimorbidity, little research or policy focus has been placed on how to best prevent the development of multimorbidity in future generations. In this research agenda piece, we argue for a shift from a sole focus on the management of multimorbidity in old age to a multimorbidity agenda that considers prevention and management throughout the life-course.

Evaluating stakeholder involvement in building a decision support tool for NHS health checks: co-producing the WorkHORSE study.

BACKGROUND: Stakeholder engagement is being increasingly recognised as an important way to achieving impact in public health. The WorkHORSE (Working Health Outcomes Research Simulation Environment) project was designed to continuously engage with stakeholders to inform the development of an open access modelling tool to enable commissioners to quantify the potential cost-effectiveness and equity of the NHS Health Check Programme. An objective of the project was to evaluate the involvement of stakeholders in co-producing the WorkHORSE computer modelling tool and examine how they perceived their involvement in the model building process and ultimately contributed to the strengthening and relevance of the modelling tool. METHODS: We identified stakeholders using our extensive networks and snowballing techniques. Iterative development of the decision support modelling tool was informed through engaging with stakeholders during four workshops. We used detailed scripts facilitating open discussion and opportunities for stakeholders to provide additional feedback subsequently. At the end of each workshop, stakeholders and the research team completed questionnaires to explore their views and experiences throughout the process. RESULTS: 30 stakeholders participated, of which 15 attended two or more workshops. They spanned local (NHS commissioners, GPs, local authorities and academics), third sector and national organisations including Public Health England. Stakeholders felt valued, and commended the involvement of practitioners in the iterative process. Major reasons for attending included: being able to influence development, and having insight and understanding of what the tool could include, and how it would work in practice. Researchers saw the process as an opportunity for developing a common language and trust in the end product, and ensuring the support tool was transparent. The workshops acted as a reality check ensuring model scenarios and outputs were relevant and fit for purpose. CONCLUSIONS: Computational modellers rarely consult with end users when developing tools to inform decision-making. The added value of co-production (continuing collaboration and iteration with stakeholders) enabled modellers to produce a "real-world" operational tool. Likewise, stakeholders had increased confidence in the decision support tool's development and applicability in practice.

Engaging with stakeholders to inform the development of a decision-support tool for the NHS health check programme: qualitative study.

BACKGROUND: The NHS Health Check Programme is a risk-reduction programme offered to all adults in England aged 40-74 years. Previous studies mainly focused on patient perspectives and programme delivery; however, delivery varies, and costs are substantial. We were therefore working with key stakeholders to develop and co-produce an NHS Health Check Programme modelling tool (workHORSE) for commissioners to quantify local effectiveness, cost-effectiveness, and equity. Here we report on Workshop 1, which specifically aimed to facilitate engagement with stakeholders; develop a shared understanding of current Health Check implementation; identify what is working well, less well, and future hopes; and explore features to include in the tool. METHODS: This qualitative study identified key stakeholders across the UK via networking and snowball techniques. The stakeholders spanned local organisations (NHS commissioners, GPs, and academics), third sector and national organisations (Public Health England and The National Institute for Health and Care Excellence). We used the validated Hovmand "group model building" approach to engage stakeholders in a series of pre-piloted, structured, small group exercises. We then used Framework Analysis to analyse responses. RESULTS: Fifteen stakeholders participated in workshop 1. Stakeholders identified continued financial and political support for the NHS Health Check Programme. However, many stakeholders highlighted issues concerning lack of data on processes and outcomes, variability in quality of delivery, and suboptimal public engagement. Stakeholders' hopes included maximising coverage, uptake, and referrals, and producing additional evidence on population health, equity, and economic impacts. Key model suggestions focused on developing good-practice template scenarios, analysis of broader prevention activities at local level, accessible local data, broader economic perspectives, and fit-for-purpose outputs. CONCLUSIONS: A shared understanding of current implementations of the NHS Health Check Programme was developed. Stakeholders demonstrated their commitment to the NHS Health Check Programme whilst highlighting the perceived requirements for enhancing the service and discussed how the modelling tool could be instrumental in this process. These suggestions for improvement informed subsequent workshops and model development.

Health and Climate Impacts of Scaling Adoption of Liquefied Petroleum Gas (LPG) for Clean Household Cooking in Cameroon: A Modeling Study.

BACKGROUND: The Cameroon government has set a target that, by 2030, 58% of the population will be using Liquefied Petroleum Gas (LPG) as a cooking fuel, in comparison with less than 20% in 2014. The National LPG Master Plan (Master Plan) was developed for scaling up the LPG sector to achieve this target. OBJECTIVES: This study aimed to estimate the potential impacts of this planned LPG expansion (the Master Plan) on population health and climate change mitigation, assuming primary, sustained use of LPG for daily cooking. METHODS: We applied existing and developed new mathematical models to calculate the health and climate impacts of expanding LPG primary adoption for household cooking in Cameroon over two periods: a) short-term (2017-2030): Comparing the Master Plan 58% target with a counterfactual LPG adoption of 32% in 2030, in line with current trends; and b) long-term (2031-2100, climate modeling only), assuming Cameroon will become a mature and saturated LPG market by 2100 (73% adoption, based on Latin American countries). We compared this with a counterfactual adoption of 41% by 2100, in line with current trends. RESULTS: By 2030, successful implementation of the Master Plan was estimated to avert about 28,000 (minimum=22,000, maximum=35,000) deaths and 770,000 (minimum=580,000 maximum=1 million) disability-adjusted life years. For the same period, we estimated reductions in pollutant emissions of more than a third in comparison with the counterfactual, leading to a global cooling of -0.1 milli °C in 2030. For 2100, a cooling impact from the Master Plan leading to market saturation (73%) was estimated to be -0.70 milli °C in comparison with to the counterfactual, with a range of -0.64 to -0.93 milli °C based on different fractions of nonrenewable biomass. DISCUSSION: Successful implementation of the Master Plan could have significant positive impacts on population health in Cameroon with no adverse impacts on climate. https://doi.org/10.1289/EHP4899.

Universal or targeted cardiovascular screening? Modelling study using a sector-specific distributional cost effectiveness analysis.

Distributional cost effectiveness analysis is a new method that can help to redesign prevention programmes by explicitly modelling the distribution of health opportunity costs as well as the distribution of health benefits. Previously we modelled cardiovascular disease (CVD) screening audit data from Liverpool, UK to see if the city could redesign its cardiovascular screening programme to enhance its cost effectiveness and equity. Building on this previous analysis, we explicitly examined the distribution of health opportunity costs and we looked at new redesign options co-designed with stakeholders. We simulated four plausible scenarios: a) no CVD screening, b) 'current' basic universal CVD screening as currently implemented, c) enhanced universal CVD screening with 'increased' population-wide delivery, and d) 'universal plus targeted' with top-up delivery to the most deprived fifth. We also compared assumptions around whether displaced health spend would come from programmes that might benefit the poor more and how much health these programmes would generate. The main outcomes were net health benefit and change in the slope index of inequality (SII) in QALYs per 100,000 person years. 'Universal plus targeted' dominated 'increased' and 'current' and also reduced health inequality by -0.65 QALYs per 100,000 person years. Results are highly sensitive to assumptions about opportunity costs and, in particular, whether funding comes from health care or local government budgets. By analysing who loses as well as who gains from expenditure decisions, distributional cost effectiveness analysis can help decision makers to redesign prevention programmes in ways that improve health and reduce health inequality.