FROM CAUSE TO IMPACT: MODELLING DETERMINANTS AND EFFECTS OF OBESITY May 2, 2017 Sahara Graf Andrea Feigl OECD FCAN meeting

Obesity rates will continue to rise

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Obesity will continue to rise in the OECD, with especially strong rates of increase in the US, England, Canada and Switzerland

Switzerland

Spain

Korea

Mexico

England

Note: Obesity defined as BMI≥30kg/m². OECD projections assume that BMI will continue to rise as a linear function of time. Source: OECD analysis of national health survey data.

Obesity projections in the OECD

France

Source: Department of Health (UK). Tackling obesities: future choices (2007)

- The causal chains leading to obesity are complex and interlinked - Complex problems warrant complex solutions and analysis

Inequalities of fruit and vegetable

consumption are significant in most countries

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Australia Canada Chile England France Hungary Italy Korea Mexico Spain USA

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Notes: Data refer to ages 18-64 except in Canada (15-64). Upper confidence interval truncated for Korea (2.2) Source: OECD analysis of health survey data.

Relative index of inequality by level of education

• Prevalence of low consumption is higher in those with a lower level of education

• Australia: prevalence is nearly 40% higher in women with a low level of education

• Inequalities are higher for women than for men overall

Individuals with lower socio-economic

characteristics are at highest risk

Populations at highest risk of low quality diet

Source: OECD analysis of health survey data.

Chile Korea Mexico Spain USA

Low quality diet

Aged 35-49 with medium SES

Aged under 20 with medium education

Women with medium SES and education

Women aged over 65 with medium education

Men aged 20-34, Mexican-American, with low education and normal weight

• Latent class analysis sorted individuals into classes based on health behaviours: diet quality (national guidelines), physical activity levels (WHO recommendations), Sedentarism (≥7 hours/day) • Multinomial regressions characteristics of those at highest risk

Modelling Scenarios and Policies

Price policies

Regulation/ enforcement

Education Healthcare

Diet, Physical activity, Obesity

Self-regul. advertisement

Mass media campaigns

Physician counselling

Compulsory food labelling

Physic/diet counselling

Either Risk (PA, Diet, Alcohol)

Fiscal measures to change price

(tax/subsid)

Regulation advertisement

School-based programmes

Worksite interventions

Alcohol consumption

Minimum pricing

Drink drive enforcement

Brief Intervention

Limit opening hours

Drug / psychos therapy

The New Multi-Risk Factors OECD

Platform

• Open source, developed in C++

• Modular and upgradable

• Modelling timeframe: 1900-2050

• Geographical scope: Europe, (soon OECD; and beyond)

• Major risk factors and NCDs

• Healthcare costs

• Impact on labour outcomes / economy (by 2018)

– Absenteeism & presentism

– Welfare benefits & transfer payments

– Policies’ impact on the market for specific products (revenues, cost for industry

Modelling Framework: from birth to

death

Birth/Entry

• Birth • Inward

migration

Risk Factors

• Behavioural • Physiolog. • Environm. • SES

Diseases

• Incidence • Remission • Prevalence

• QoL • (Costs)

Death/Exit

• Death by disease

• Residual mortality

• Outward migration

Risk factors: Physical activity, alcohol, tobacco salt, BMI, blood pressure, cholesterol, [pollution]. Dietary dimensions to be added

Diseases: Stroke (3 types), IHD, Cancers (stomach, colorectal, lung, liver, breast), diabetes, COPD, cirrhosis, depression, Alzheimer /dementia, Injuries (2 types), MSDs (4 types) More diseases to be added (e.g. AUDs)

Considerations for food reformulation:

labelling and content

BMI reduction:

- Food reformulation

- Salt reduction

- Portion size changes

- Nutrition labeling

- Vending machine content replacement

- Product diversification (i.e. diet sodas,

flavored waters)

- Added Sugar reduction

Weaker evidence on: - Revenue impact for higher alcohol taxes

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• Adding to the knowledge – information for OECD countries

• How consumers react – behavioural economics

• Bridging the gap with the private sector

Next steps/ collaboration

Additional Slides

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SSB taxation impact in South Africa

Health impact Impact on health expenditure

Source: OECD analysis, forthcoming

• The interventions applies the SSB tax as designed by the South African National Treasury, an increase of R2.21 per litre or R0.0221 per gram of sugar on a litre over 4g/100ml, equivalent to a 12% effective tax rate at current prices and sugar content of soft drinks and concentrates (National Treasury, 2017). The tax is assumed to pass through to customers as in the baseline scenario of Manyema et al (2014). It is also assumed that the SSB industry does not put in place any intervention to reformulate SSBs. Reformulation by the industry would lead to smaller consumption changes but greater mean BMI changes.

• The own-price elasticity for SSB consumption is -0.77 meaning the 12% effective tax rate reduces SSB consumption by approximately 9%. It is assumed that a tax increase translates almost immediately into an increase in the price of SSBs. The price increase on SSBs increases fruit juice consumption by 6% (cross-price elasticity = 0.53) and diet drink consumption by 5% (cross-price elasticity = 0.44) (National Treasury, 2017).

Effectiveness of various nutrition interventions

The Economic Impact of Tackling Obesity:

Effectiveness and Cost-Effectiveness

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Effect of food labels in selecting and healthier option

GDA

Traffic light

Other food labels

Increase (%) in people selecting a healthier option

Overall

Source: Cecchini & Warin, Ob Rev 2015