Martin Brown

Health and economic burden of the projected obesity trends in the USA and the UK

Rising prevalence of obesity is a worldwide health concern because excess weight gain within populations forecasts an increased burden from several diseases, most notably cardiovascular diseases, diabetes, and cancers. In this report, we used a simulation model to project the probable health and economic consequences in the next two decades from a continued rise in obesity in two ageing populations--the USA and the UK. These trends project 65 million more obese adults in the USA and 11 million more obese adults in the UK by 2030, consequently accruing an additional 6-8·5 million cases of diabetes, 5·7-7·3 million cases of heart disease and stroke, 492,000-669,000 additional cases of cancer, and 26-55 million quality-adjusted life years forgone for USA and UK combined. The combined medical costs associated with treatment of these preventable diseases are estimated to increase by

The future burden of obesity-related diseases in the 53 WHO European-Region countries and the impact of effective interventions: a modelling study.

48-66 billion/year in the USA and by £1·9-2 billion/year in the UK by 2030. Hence, effective policies to promote healthier weight also have economic benefits.

High Rates of Obesity and Non-Communicable Diseases Predicted across Latin America

Objective Non-communicable diseases (NCDs) are the biggest cause of death in Europe putting an unsustainable burden on already struggling health systems. Increases in obesity are a major cause of NCDs. This paper projects the future burden of coronary heart disease (CHD), stroke, type 2 diabetes and seven cancers by 2030 in 53 WHO European Region countries based on current and past body mass index (BMI) trends. It also tests the impact of obesity interventions on the future disease burden. Setting and participants Secondary data analysis of country-specific epidemiological data using a microsimulation modelling process. Interventions The effect of three hypothetical scenarios on the future burden of disease in 2030 was tested: baseline scenario, BMI trends go unchecked; intervention 1, population BMI decreases by 1%; intervention 2, BMI decreases by 5%. Primary and secondary outcome measures Quantifying the future burden of major NCDs and the impact of interventions on this future disease burden. Results By 2030 in the whole of the European region, the prevalence of diabetes, CHD and stroke and cancers was projected to reach an average of 3990, 4672 and 2046 cases/100u2005000, respectively. The highest prevalence of diabetes was predicted in Slovakia (10u2005870), CHD and stroke—in Greece (11u2005292) and cancers—in Finland (5615 cases/100u2005000). A 5% fall in population BMI was projected to significantly reduce cumulative incidence of diseases. The largest reduction in diabetes and CHD and stroke was observed in Slovakia (3054 and 3369 cases/100u2005000, respectively), and in cancers was predicted in Germany (331/100u2005000). Conclusions Modelling future disease trends is a useful tool for policymakers so that they can allocate resources effectively and implement policies to prevent NCDs. Future research will allow real policy interventions to be tested; however, better surveillance data on NCDs and their risk factors are essential for research and policy.

Alarming predictions for obesity and non-communicable diseases in the Middle East

Non-communicable diseases (NCDs) such as cardiovascular disease and stroke are a major public health concern across Latin America. A key modifiable risk factor for NCDs is overweight and obesity highlighting the need for policy to reduce prevalence rates and ameliorate rising levels of NCDs. A cross-sectional regression analysis was used to project BMI and related disease trends to 2050. We tested the extent to which interventions that decrease body mass index (BMI) have an effect upon the number of incidence cases avoided for each disease. Without intervention obesity trends will continue to rise across much of Latin America. Effective interventions are necessary if rates of obesity and related diseases are to be reduced.

Modelling obesity trends and related diseases in Eastern Europe

OBJECTIVEnThe present study aimed to model obesity trends and future obesity-related disease for nine countries in the Middle East; in addition, to explore how hypothetical reductions in population obesity levels could ameliorate anticipated disease burdens.nnnDESIGNnA regression analysis of cross-sectional data v. BMI showed age- and sex-specific BMI trends, which fed into a micro simulation with a million Monte Carlo trials for each country. We also examined two alternative scenarios where population BMI was reduced by 1 % and 5 %.nnnSETTINGnStatistical modelling of obesity trends was carried out in nine Middle East countries (Bahrain, Egypt, Iran, Jordan, Kuwait, Lebanon, Oman, Saudi Arabia and Turkey).nnnSUBJECTSnBMI data along with disease incidence, mortality and survival data from national and sub-national data sets were used for the modelling process.nnnRESULTSnHigh rates of overweight and obesity increased in both men and women in most countries. The burden of incident type 2 diabetes, CHD and stroke would be moderated with even small reductions in obesity levels.nnnCONCLUSIONSnObesity is a growing problem in the Middle East which requires government action on the primary prevention of obesity. The present results are important for policy makers to know the effectiveness of obesity interventions on future disease burden.

Apples and oranges: a comparison of costing methods for obesity.

Obesity has increased at an alarming rate across the world and, in turn, rates of non‐communicable diseases have escalated. In Eastern Europe, this epidemic has probably occurred at a later stage than the West due to the economic transition following the demise of communism. Knowing how these trends will change is important. We used a micro‐simulation model to project obesity trends and related incidence of coronary heart disease and stroke, cancer and type 2 diabetes 20 and 40 years into the future. Where nationally representative data were available, obesity levels were shown to increase with most prominent increases seen amongst men in Latvia and Estonia, and amongst women in Croatia and Latvia. The exception was Lithuania where a decrease in overweight and obesity was observed in both men and women. We showed that interventions effective in reducing obesity would have a significant impact upon the number of new cases of each disease. It is necessary to improve surveillance of obesity and disease incidence as well as implement policies that are effective in reducing body fat.

Modelling the implications of reducing smoking prevalence: the benefits of increasing the UK tobacco duty escalator to public health and economic outcomes

Obesity has escalated to epidemic proportions over the past 30 years resulting in increased disease burden and healthcare costs. The aim of this paper was to analyse different costing methods for obesity. Several databases have been searched to identify eligible literature estimating obesity cost. These were categorized into databases, patient‐attributable fraction (PAF) and modelling studies. Studies from the United States were used to explore effects of study designs on cost outcomes. Our results show that cost outcomes are largely affected by underlying study designs, such as population size, age, cost categories (medical expenditure vs. total costs), length of the data collection and body mass index cut‐offs. Three study types are likely to have an impact on reported costs, with modelling studies providing the most conservative estimates. Database studies can help to increase the overall awareness of the economic burden of obesity. PAF studies can make the obesity disease more tangible by drawing connections to diseases. Decision makers need to be aware of the different purposes and weaknesses of the studies when interpreting cost outcomes. Further research is needed to refine the existing methods and provide high‐quality data accounting for the complexity of the disease.

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

Introduction Taxing tobacco is one of the most effective ways to reduce smoking prevalence, mitigate its devastating consequential health harms and progress towards a tobacco-free society. This study modelled the health and economic impacts of increasing the existing cigarette tobacco duty escalator (TDE) in the UK from the current 2% above consumer price inflation to 5%. Methods A two-stage modelling process was used. First, a non-linear multivariate regression model was fitted to cross-sectional smoking data, creating longitudinal projections from 2015 to 2035. Second, these projections were used to predict the future incidence, prevalence and cost of 17 smoking-related diseases using a Monte Carlo microsimulation approach. A sustained increase in the duty escalator was evaluated against a baseline of continuing historical smoking trends and the existing duty escalator. Results A sustained increase in the TDE is projected to reduce adult smoking prevalence to 6% in 2035, from 10% in a baseline scenario. After increasing the TDE, only 65% of female and 60% of male would-be smokers would actually be smoking in 2035. The intervention is projected to avoid around 75u2009200 new cases of smoking-related diseases between 2015 and 2035. In 2035 alone, £49u2009m in National Health Service and social care costs and £192u2009m in societal premature mortality and morbidity costs are projected to be avoided. Conclusion Increasing the UK TDE to 5% above inflation could effectively reduce smoking prevalence, prevent diseases and avoid healthcare costs. It would deliver substantial progress towards a tobacco-free society and should be implemented by the UK Government with urgency.

Future modelling of chronic diseases: foresight and beyond

Introduction Smoking 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. Methods A 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. Results If 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 97u2009300 +/- 5 300 new cases of smoking-related diseases are avoided by 2035 (tobacco-related cancers: 35u2009900+/- 4 100; chronic obstructive pulmonary disease: 29u2009000 +/- 2 700; stroke: 24u2009900 +/- 2 700; coronary heart disease: 7600 +/- 2 700), including around 12u2009350 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. Conclusion These 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.

BY-STATE COMPARISON OF OBESITY TRENDS IN THE ADULT POPULATION OF THE UNITED STATES OF AMERICA

Abstract Background Many chronic diseases are interrelated and their effects under changing exposures need to be better understood. Policy makers and planners need to understand what the current distributions of avoidable chronic disease are, among whom, and how they are likely to develop in the future, particularly their effect on different populations, what will be the health consequences of the extrapolated trends, and how much these consequences can be attenuated with what we currently know and might come to know. Modelling the effects by evidence-based extrapolation, incorporating and attributing the epidemiology of related diseases, can give rise to straightforward estimates of incidence and death rates for the most common related conditions for the next 50 years. This modelling can be done by making basic assumptions about plausible change of risk in disease rates tracking into adulthood using established likelihoods from current trends. These rates in turn are used to compare predicted illness and mortality rates with those that arise from demographic extrapolation from existing current mortality rates. These figures can be used to revise estimates of the healthy working population, by removing death rates and accounting for sickness in a manner that incorporates known and current changes in disease incidence. The model builds on work originally developed for Foresight Tackling Obesities (UK) and subsequent work modelling obesity and related diseases in a further 36 countries. Methods A microsimulation model was used to project future health of each of possibly millions of individuals with a given demography (of any region) through to a given year, and various scenarios were simulated. Competing risks were examined in real simulated time. Related diseases and associated health-care costs were calculated on the basis of trends in risk factors distributed among these individuals. In the case of obesity, 13 diseases were considered. We simulated three hypothetical future scenarios: no reduction and 1% and 5% reductions in body-mass index (BMI). Ultimately, health and other costs incurred or saved can be compared with the costs of intervention. The simulation model was developed in discrete modules to enable radical change and updating of assumptions and parameters. We did not apply any future discounting for this project. Findings Small reductions in risk factors can have substantial effects on future burdens of disease and avoidable health-care costs. In the UK, 1% reduction in BMI rates will save £15·5 billion, whereas in the USA the medical costs will be reduced by US