The Health and Economic Benefits of Tackling Non‑Communicable Diseases

Annex B. The OECD SPHeP NCDs model

The OECD Strategic Public Health Planning for Non-Communicable Diseases (SPHeP-NCDs) model is an advanced systems modelling tool for public health policy and strategic planning. The model is used to predict the health and economic outcomes of the population of a country up to 2050. The model analyses a comprehensive set of key risk factors (e.g. obesity, alcohol use, smoking, diet, air pollution, physical activity) and their associated NCDs. The model covers 51 countries, including OECD Member countries, G20 countries, EU27 countries and OECD accession and selected partner countries.

For each of the 51 countries, the model uses demographic and risk factor characteristics by age‑ and sex-specific population groups from international databases. These inputs are used to generate synthetic populations, in which each individual is assigned demographic characteristics and a risk factor profile (Figure A B.1). The risk factors are distributed independently, and no mediators are modelled between the risk factors and the diseases. Based on these characteristics, an individual has a certain risk of developing a disease each year. These relative risks are based on the Global Burden of Disease study, amongst others. Note that the model uses population predictions to adjust the size and demographic profile of country populations in the future, but maintains current (age‑ and gender-specific) rates for risk factors. In other words, it does not predict any future trends in risk factor prevalence, other than those caused by changes in demographics.

Figure A B.1. Schematic overview of the OECD SPHeP-NCDs model

Note: This schematic is highly simplified and focusses on the disease component – it does not reflect some other components of the model (including births, immigration, emigration, death, remission and fatality).

For each year modelled, a cross-sectional representation of the population can be obtained, to calculate health status indicators such as life expectancy, disease prevalence, mortality, and disability-adjusted life years (DALYs). The disease and demographic profile of the population also form the basis for the healthcare cost, labour market and other well-being outputs. The impact of demographic changes and labour force participation and productivity are translated into a change in GDP using the Cobb-Douglas production function, consistent with the OECD long-term economic forecast model (Guillemette and Turner, 2017[1]) and other established long-term models such as the World Bank Long Term Growth Model (Pennings and Loayza, 2022[2]).

To estimate the burden of NCDs, a hypothetical scenario is modelled in which the incidence of NCDs was set to zero before age 75. To understand the progress that has been made on NCD risk factors in recent years, the risk factor levels achieved in 2022 were compared to a hypothetical scenario in which risk factors remain at the 2010 level (Figure A B.2).

Figure A B.2. Schematic overview of scenarios looking at risk factor progress since 2010

Note: Illustrative, not based on real data. Year for latest data (here 2022) varies.

These scenarios are projected into the future to be able to see the impact of the specific risk factor level on NCDs, which takes time to materialise (e.g. being overweight does not cause heart disease instantly but may do so after ten years or so). The impacts are measured over the period 2026 to 2050, with risk factor rates and survival rates that are maintained constant at either 2010 or 2022 level, throughout the modelled period. The model accounts for population ageing and the analysis is designed to avoid any misleading conclusion from demographic change.

To understand the potential for improvement, NCD risk factor prevalence rates and NCD survival rates are aligned to the top 25% rates observed across OECD countries, for each age and sex group (Figure A B.3). Rather than predetermined international policy targets, which may or may not be achievable, this approach shows what some countries have achieved and could therefore be a realistic goal for others.

Figure A B.3. Schematic overview of the Top Quartile scenarios

Note: Illustrative, not based on real data.

Since the OECD SHPeP NCDs model contains more granular risk factor data than the headline indicators generally reported, the results can, in certain cases, look counterintuitive. For example, while reports often look at the prevalence of obesity (BMI ≥ 30), the model also contains information on the prevalence of severe obesity (BMI ≥ 40). This category carries an increased risk of disease vis-à-vis a BMI between 30 and 40. This means that, even if a country saw no change in overall obesity, the incidence of disease could still increase if severe obesity increased.

The analyses presented in this study focus on six major risk factors (smoking, alcohol consumption, obesity, physical inactivity, diet and air pollution) and four major NCDs (cancer, CVD, COPD and diabetes). Diet includes fruit, vegetables, whole grains, legumes, processed meat, red meat, sugar sweetened beverages and sodium. CVDs include ischaemic heart disease/myocardial infarction, ischaemic and haemorrhagic stroke and atrial fibrillation. It is important to note that changes in risk factors will also affect other NCDs, and the impact estimated in this report is therefore an underestimation of the overall effect.

For more information on the OECD SPHeP NCDs model, see the SPHeP NCDs Technical Documentation, available at: http://oecdpublichealthexplorer.org/ncd-doc.

References

[1] Guillemette, Y. and D. Turner (2017), “The fiscal projection framework in long-term scenarios”, OECD Economics Department Working Papers, No. 1440, OECD Publishing, Paris, https://doi.org/10.1787/8eddfa18-en.

[2] Pennings, S. and N. Loayza (2022), The Long Term Growth Model : Fundamentals, Extensions, and Applications (English), World Bank Group.