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1 Food Sustainability Index Methodology The Food Sustainability Index (FSI), developed by the Economist Intelligence Unit with the Barilla Center for Food & Nutrition (BCFN), measures the sustainability of food systems in 34 countries around three key issues outlined in the 2015 BCFN Milan Protocol and designed around the Sustainable Development Goals (SDGs): food loss and waste, sustainable agriculture and nutrition. The index looks at policies and outcome around sustainable food systems and diets through a series of key performance indicators that consider environmental, social and economic sustainability. In this study, sustainability is defined as the ability of a country’s food system to be maintained without depletion or exhaustion of its natural assets or compromises to its population’s health, and without compromising future generations’ access to food. The index seeks to address three main paradoxes identified in the 2015 BCFN Milan Food Protocol: Food loss and waste: Almost one billion people suffer from hunger, but a third of food is lost or wasted. Food waste corresponds to four times the amount needed to feed the people suffering from undernutrition worldwide. Sustainable agriculture: Climate change impacts on agricultural systems are becoming more visible yet harder to estimate. Although agriculture has the potential to capture carbon emissions and help mitigate the impact of climate change, the ecological footprint of agriculture is growing. The shift away from fossil fuels to renewable sources of energy (e.g. biofuels) reduces the surface of land available to grow food. Nutritional challenges: The hungry and the obese coexist, and rising rates of obesity strain healthcare systems to the point of economic unsustainability. For every person suffering from undernutrition there are two who are overweight or obese. The Food Sustainability Index research programme aims to raise awareness of governments, institutions and the general public around the need to address food sustainability issues and monitor progress towards addressing these issues. This project is also intended to support global efforts around the SDGs. The index is linked not only to the SDG on hunger but also to those on climate change, life on land, sustainable cities, employment, responsible consumption and production, as well as gender equality, good health, poverty, education and infrastructure. Scoring criteria and categories The three primary categories in the indexFood loss and waste, Sustainable agriculture, and Nutritional challengeswere defined in the Milan Protocol. The individual indicators and underlying metrics have been selected on the basis of Economist Intelligence Unit expert knowledge and analysis, consultation with external food sustainability and nutrition experts, and with input from BCFN and their Advisory Board members. The Index contains 35 indicators, and over 55 sub-indicators, organised across these three categories. Each category receives a score, calculated from a weighted mean of the underlying indicator scores (see “Weights”), and scores are scaled from 0 to 100, where 100 = the highest sustainability and greatest progress towards meeting environmental, societal and economic KPIs.

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Food Sustainability Index Methodology

The Food Sustainability Index (FSI), developed by the Economist Intelligence Unit with the Barilla

Center for Food & Nutrition (BCFN), measures the sustainability of food systems in 34 countries

around three key issues outlined in the 2015 BCFN Milan Protocol and designed around the

Sustainable Development Goals (SDGs): food loss and waste, sustainable agriculture and nutrition.

The index looks at policies and outcome around sustainable food systems and diets through a series

of key performance indicators that consider environmental, social and economic sustainability.

In this study, sustainability is defined as the ability of a country’s food system to be maintained

without depletion or exhaustion of its natural assets or compromises to its population’s health, and

without compromising future generations’ access to food.

The index seeks to address three main paradoxes identified in the 2015 BCFN Milan Food Protocol:

Food loss and waste: Almost one billion people suffer from hunger, but a third of food is lost or

wasted. Food waste corresponds to four times the amount needed to feed the people suffering from

undernutrition worldwide.

Sustainable agriculture: Climate change impacts on agricultural systems are becoming more

visible yet harder to estimate. Although agriculture has the potential to capture carbon emissions and

help mitigate the impact of climate change, the ecological footprint of agriculture is growing. The shift

away from fossil fuels to renewable sources of energy (e.g. biofuels) reduces the surface of land

available to grow food.

Nutritional challenges: The hungry and the obese coexist, and rising rates of obesity strain

healthcare systems to the point of economic unsustainability. For every person suffering from

undernutrition there are two who are overweight or obese.

The Food Sustainability Index research programme aims to raise awareness of governments,

institutions and the general public around the need to address food sustainability issues and monitor

progress towards addressing these issues. This project is also intended to support global efforts

around the SDGs. The index is linked not only to the SDG on hunger but also to those on climate

change, life on land, sustainable cities, employment, responsible consumption and production, as

well as gender equality, good health, poverty, education and infrastructure.

Scoring criteria and categories The three primary categories in the index—Food loss and waste, Sustainable agriculture, and

Nutritional challenges—were defined in the Milan Protocol. The individual indicators and underlying

metrics have been selected on the basis of Economist Intelligence Unit expert knowledge and

analysis, consultation with external food sustainability and nutrition experts, and with input from

BCFN and their Advisory Board members.

The Index contains 35 indicators, and over 55 sub-indicators, organised across these three

categories. Each category receives a score, calculated from a weighted mean of the underlying

indicator scores (see “Weights”), and scores are scaled from 0 to 100, where 100 = the highest

sustainability and greatest progress towards meeting environmental, societal and economic KPIs.

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2017 Overall rankings Rank Country Overall score

1 France 74.8 2 Japan 72.8 3 Germany 70.6 4 Spain 70.4 5 Sweden 69.7 6 Portugal 69.5 7 Italy 69.0 8 South Korea 69.0 9 Hungary 68.4 10 UK 68.0 11 Canada 67.1 12 Ethiopia 65.4 13 Colombia 64.4 14 Australia 63.3 15 Israel 63.1 16 Turkey 62.9 17 Russia 62.1 18 Argentina 62.0 19 South Africa 61.7 20 Greece 61.6 21 US 61.5 22 Mexico 61.2 23 China 59.8 24 Nigeria 59.6 25 Jordan 58.9 26 Saudi Arabia 57.8 27 Egypt 57.1 28 Brazil 56.6 29 Morocco 53.9 30 Tunisia 53.1 31 Lebanon 53.1 32 Indonesia 52.4 33 India 50.8 34 UAE 40.3

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Country selection The FSI evaluates food sustainability in 34 countries that were carefully selected by the Economist

Intelligence Unit and BCFN, in consultation with experts. The country choice reflects a mix of high-

income, middle-income, and low-income countries, with geographic representation. These countries

represent over 85% of global GDP and two-thirds of the global population.

Africa Asia Pacific Europe South

America Middle East

North

America

Ethiopia,

Morocco,

Nigeria, South

Africa, Tunisia

Australia,

China, India,

Indonesia,

Japan, South

Korea

France,

Germany,

Greece,

Hungary, Italy,

Portugal,

Russia, Spain,

Sweden,

Turkey, United

Kingdom

Argentina,

Brazil,

Columbia

Egypt, Jordan,

Israel,

Lebanon,

Saudi Arabia,

United Arab

Emirates

Canada,

Mexico, United

States

Weights

The weights assigned to each category and indicator can be changed in the FSI model to reflect

different assumptions about their relative importance. Four sets of weights are provided.

Expert-based weightings. The weights defined by the BCFN Advisory Board (“expert based

weightings”) are the default setting. They are based on extensive discussions between BCFN, the

Economist Intelligence Unit and the Advisory Board on the relative value of each indicator and sub-

indicator. This option uses expert judgment to assign weights to indicators and brings a real-world

perspective to an index, which is important if an index is to guide policy actions.

Uniform weightings. The second weighting option, called uniform or neutral weights, assumes equal

importance of all indicators and sub-indicators and evenly distributes weights on that basis. This

scheme has the advantage of simplicity and does not involve subjective judgment. A disadvantage

of these options is that they assume that all indicators are equally significant.

Policy-driven weightings. The third option, policy-driven weighting, focuses on the importance of

those indicators in the model that can be addressed through policy changes. In this scheme, the

policy-driven indicators and sub-indicators hold more weight than other metrics in the model,

allowing users to identify countries that have adopted the strongest policies to address food

sustainability issues.

Outcome-based weightings. The fourth option is outcome-based weightings, which focuses on how

countries are doing on each food sustainability pillar, rather than on the policies to improve

sustainability. This weighting scheme prioritises metrics that show progress towards meeting food

sustainability goals and objectives. It highlights countries that already have minimised food waste

and loss, built sustainable agriculture practices, and improved nutrition.

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Food Sustainability Index expert-based weightings

CATEGORIES Weight %

A) FOOD LOSS AND WASTE 33.3%

B) SUSTAINABLE AGRICULTURE 33.3%

C) NUTRITIONAL CHALLENGES 33.3%

INDICATORS Weight %

A) FOOD LOSS AND WASTE

1.1) Food loss 28.0%

1.2) Policy response to food loss 24.0%

1.3) Causes of distribution-level loss 26.0%

1.4) Solutions to distribution-level loss 22.0%

2.1) Food waste at end-user level 53.8%

2.2) Policy response to food waste 46.2%

B) SUSTAINABLE AGRICULTURE

3.1) Environmental impact of agriculture on water 22.4%

3.2) Sustainability of water withdrawal 17.9%

3.3) Water scarcity 14.9%

3.4) Water management 19.4%

3.5) Trade impact 13.4%

3.6) Sustainability of fisheries 11.9%

4.1) Environmental impact of agriculture on land 12.3%

4.2) Land use 8.8%

4.3) Impact on land of animal feed and biofuels 7.0%

4.4) Land ownership 8.8%

4.5) Agricultural subsidies 8.8%

4.6) Animal welfare policies 6.6%

4.7) Diversification of agricultural system 11.0%

4.8) Environmental biodiversity 11.0%

4.9) Agro-economic indicators 8.8%

4.10) Productivity 8.8%

4.11) Land-users 7.9%

5.1) Environmental impact of agriculture on the atmosphere 53.8%

5.2) Climate change mitigation 46.2%

C) NUTRITIONAL CHALLENGES

6.1) Prevalence of malnourishment 40.0%

6.2) Micronutrient deficiency 31.4%

6.3) Enabling factors 28.6%

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7.1) Health life expectancy 26.5%

7.2) Prevalence of over-nourishment 30.1%

7.3) Impact on health 24.1%

7.4) Physical activity 19.3%

8.1) Diet composition 26.9%

8.2) Number of people per fast food restaurant 24.4%

8.3) Economic determinant of dietary patterns 20.5%

8.4) Policy response to dietary patterns 28.2%

SUB-INDICATORS Weight %

1.1) Food loss

1.1.1) Food lost (% of country's total food production) 100.0%

1.2) Policy response to food loss

1.2.1) Quality of policies to address food loss 100.0%

1.3) Causes of distribution-level loss

1.3.1) Quality of road infrastructure 100.0%

1.4) Solutions to distribution-level loss

1.4.1) Investment in transport with private participation 100.0%

2.1) Food waste at end-user level

2.1.1) Food waste per capita (per year) 100.0%

2.2) Policy response to food waste

2.2.1) Quality of policy response to food waste 100.0%

3.1) Environmental impact of agriculture on water

3.1.1) Water footprint 100.0%

3.2) Sustainability of water withdrawal

3.2.1) Agricultural water withdrawals (% of total renewable water resources) 100.0%

3.3) Water scarcity

3.3.1) Monthly freshwater scarcity 100.0%

3.4) Water management

3.4.1) Initiatives to recycle water for agricultural use 100.0%

3.5) Trade impact

3.5.1) Virtual Blue Water Net Imports 100.0%

3.6) Sustainability of fisheries

3.6.1) Fish stocks 100.0%

4.1) Environmental impact of agriculture on land

4.1.1) Nitrogen Use Efficiency 31.7%

4.1.2) Agricultural land lost yearly to desertification & pollution (%) 36.5%

4.1.3) Average carbon content of soil (% of weight) 31.7%

4.2) Land use

4.2.1) Arable land under organic agriculture (% of agricultural land) 29.8%

4.2.2) Utilised agricultural area (% of total agricultural area) 29.8%

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4.2.3) Existence of sustainable urban farming initiatives 40.4%

4.3) Impact on land of animal feed and biofuels

4.3.1) First and second generation biofuel production 31.7%

4.3.2) Land diverted to animal feed and biofuels 36.5%

4.3.3) Biodiesel imports 31.7%

4.4) Land ownership

4.4.1) Land owned / under concession in foreign countries (% of domestic arable land)

29.9%

4.4.2) Degree of property rights protection 35.1%

4.4.3) Existence of laws to protect smallholders against land grabbing 35.1%

4.5) Agricultural subsidies

4.5.1) Quality of agricultural subsidies 100.0%

4.6) Animal welfare policies

4.6.1) Quality of animal welfare regulation 100.0%

4.7) Diversification of agricultural system

4.7.1) Top 3 crops (% of total agriculture production) 100.0%

4.8) Environmental biodiversity

4.8.1) Environmental biodiversity 52.6%

4.8.2) Deforestation (ha/year) 47.4%

4.9) Agro-economic indicators

4.9.1) Average education level of farmers 36.5%

4.9.2) Total private & public agricultural sciences R&D expenditure (as % of GDP)

31.7%

4.9.3 ) Public support to R&D 31.7%

4.10) Productivity

4.10.1) Total factor productivity (TFP) growth rate 100.0%

4.11) Land-users

4.11.1) Participation rate of women in farming 26.0%

4.11.2) Participation rate of youth in farming 26.0%

4.11.3) Average age of farmers 22.1%

4.11.4) Working conditions of agricultural workers along the value chain 26.0%

5.1) Environmental impact of agriculture on the atmosphere

5.1.1) GHG emissions from agriculture 23.0%

5.1.2) Animal emissions (% total agriculture emissions) 31.0%

5.1.3) Fertilizer emissions (% total agriculture emissions) 26.4%

5.1.4) Land use net emissions/removals (% total, CO2 eq) 19.5%

5.2) Climate change mitigation

5.2.1) Implementation of agricultural techniques for climate change mitigation and adaptation 100.0%

6.1) Prevalence of malnourishment

6.1.1) Prevalence of undernourishment (% of population) 26.3%

6.1.2) Prevalence of stunting (% of children under 5, height for age) 23.7%

6.1.3) Prevalence of wasting (% of children under 5, weight for height) 23.7%

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6.1.4) Prevalence of underweight (% of children under 5, weight for age) 26.3%

6.2) Micronutrient deficiency

6.2.1) Vitamin A deficiency (% of general population) 50.0%

6.2.2) Iodine deficiency (% of general population) 50.0%

6.3) Enabling factors

6.3.1) Babies under 6 months old exclusively breastfed (% total) 50.0%

6.3.2) Access to improved water source 50.0%

7.1) Health life expectancy

7.1.1) Life expectancy at birth, total (years) 46.0%

7.1.2) Healthy life expectancy (HALE) 54.0%

7.2) Prevalence of over-nourishment

7.2.1) Prevalence of overweight in children (5-19 years of age) 46.0%

7.2.2) Prevalence of overweight in adults (body mass index >= 25) 54.0%

7.3) Impact on health

7.3.1) Disability Adjusted Life Years (DALYs) from nutritional deficiencies 100.0%

7.4) Physical activity

7.4.1) Population reaching recommended physical activity per week (%) 56.7%

7.4.2) Hours of inactivity, fixed screen time per week 43.3%

8.1) Diet composition

8.1.1) Percentage of sugar in diets 37.5%

8.1.2) Meat consumption levels 25.0%

8.1.3) Saturated fat consumption 16.3%

8.1.4) Salt consumption 21.3%

8.2) Number of people per fast food restaurant

8.2.1) Number of people per fast food restaurant 100.0%

8.3) Economic determinant of dietary patterns

8.3.1) Proportion of population living below the national poverty line 46.5%

8.3.2) GINI Coefficient 53.5%

8.4) Policy response to dietary patterns

8.4.1) Quality of policy response to dietary patterns 50.0%

8.4.2) Nutrition education 50.0%

Data modelling Indicator scores are normalised and then aggregated across categories to enable a comparison of

broader concepts across countries. Normalisation rebases the raw indicator data to a common unit

so that it can be aggregated. All indicators in this model are normalised to a 0 to 100 scale,

where 100 indicates the highest sustainability and 0 represents the lowest.

Most indicators are transformed on the basis of a min/max normalisation, where the minimum and

maximum raw data values across the 34 countries are used to bookend the indicator scores. The

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indicators for which a higher value indicates a more favourable environment have been normalised

on the basis of:

x = (x - Min(x)) / (Max(x) - Min(x))

where Min(x) and Max(x) are, respectively, the lowest and highest values in the 34 countries for any

given indicator. The normalised value is then transformed from a 0-1 value to a 0-100 score to make

it directly comparable with other indicators. This in effect means that the country with the highest raw

data value will score 100, while the lowest will score 0 for all indicators in the Index.

For the indicators for which a high value indicates an unfavourable environment, the normalisation

function takes the form of:

x = (x - Max(x)) / (Max(x) - Min(x))

where Min(x) and Max(x) are, respectively, the lowest and highest values in the 34 countries for any

given indicator. The normalised value is then transformed into a positive number on a scale of 0-100

to make it directly comparable with other indicators.

Data limitations The Economist Intelligence Unit employed country experts and regional specialists with a wide

variety of necessary linguistic skills to undertake the research from its global network of more than

350 analysts and contributors. Researchers were asked to gather data from primary legal texts;

government and academic publications; and websites of government authorities, international

organisations, and non-governmental organisations. In some cases, the Economist Intelligence Unit

research was constrained by data availability.

Investment in sustainable agriculture. Non-government investment in sustainable agriculture is an

important component of the FSI framework. The Economist Intelligence Unit undertook an extensive

review of existing data sources, including data sets from the FAO, OECD, World Resources Institute,

the Conservation Finance Network, Climatescope, the Climate Bonds Initiative, the Climate Policy

Initiative, the Sustainable Stock Exchanges Initiative and Bloomberg. Though some indicators

captured specific elements of investment in sustainable agriculture (for example, green bonds that

are primarily funnelled into renewable energy), there was no indicator that covers the majority of the

34 countries in the FSI and also comprehensively explores the range of investment options for

sustainable agriculture. There are a number of studies that look specifically at sustainable agriculture

and land use investment in individual countries, but these studies do not cover all of the countries in

the FSI and do not allow us to provide like-for-like comparisons across the 34 countries in the index.

We propose to develop a qualitative indicator for the 2018 FSI that allows us to assess the wide-

range of financing options for sustainable agriculture and their uptake across the countries included

in the FSI scope.

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Micronutrients and diet composition. Metrics that measure micronutrient deficiencies and diet composition are not updated frequently. This can make it difficult to measure progress towards addressing nutritional challenges. These indicators have proved particularly challenging, as there are substantial data gaps in many of the data sets that cover micronutrients and diets. Finding robust metrics with complete country coverage has been difficult.

In particular, questions have arisen around measuring salt consumption in diets. The Economist

Intelligence Unit intended to use the World Bank’s iodized salt consumption (% of households) data

in the 2016 FSI. However, there were significant data gaps in the proposed data set. Conversations

with a medical doctor helped us identify the most robust micronutrient deficiency indicators that the

WHO publishes. These discussions led us to incorporate iodine concentration in urine and a

measurement of average grams of sodium consumed per day.

All of the indicators on micronutrient deficiencies included in the Food Sustainability Index were

selected with the help of a medical doctor.

Regional nuances. The value of an index is that it produces like for like comparisons across a set of

geographies. It is important to note, however, that not all sustainability issues and metrics are

equally important in every geography.

For example, climate has an impact on the amount of food loss during harvest. In warmer countries

(for example, the Mediterranean), food degradation occurs more rapidly. This rapid degradation and

the risk the climate poses to food supply in a country make managing food loss and waste more

important in warmer countries. The index cannot distinguish between those countries where climate

poses a higher threat to food loss and waste and those where climate is more conducive to

minimising degradation.

Furthermore, road infrastructure and investment in transport, though important components of

mitigating loss throughout the supply chain, do not fully encompass the set of solutions that

countries can employ to address food loss and waste. Data around adoption and development of

post-harvest technologies to address food loss and waste issues is needed to fill this gap and create

a more robust assessment of food supply chain issues.

It is necessary to interpret the sustainable agriculture category results carefully. For example, water

inputs to crops increase with decreasing latitude due to evaporation and poor soil water retention. So

in warmer countries, this evaporation and poor retention result in a greater water consumption to

obtain the same yields. The same is true with nutrient inputs—poor soil conditions necessitate more

inputs to sustain yields. There index does not capture this nuances, which results in many

Mediterranean countries where water resources are scare and soil conditions are poor rising to the

top of the rankings. In the future, the BCFN and EIU will consider developing an indicator that takes

into account water use and GHG emissions per average yield to better capture these nuances.

The FSI model provides an adjustable weightings functionality that allows users to assign more or

less importance to themes and indicators that they deem to be more relevant. Using this functionality

can help users who are interested in regional analysis better understand country performance

across areas of interest.

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For those users who are interested in understanding how climate or lack of natural resources impact

food sustainability, the FSI data provides a jumping off point. Metrics and data from the FSI can be

adjusted based on other factors using simple calculations to create data that takes climate or natural

resource factors into account.

Sources and definitions All of the quantitative and qualitative data in the Food Sustainability Index was collected and

analysed by the Economist Intelligence Unit project team. Data was gathered from reputable

international, national and industry sources including the Economist Intelligence Unit’s internal

databases. In cases where data was incomplete or missing, Economist Intelligence Unit analysts

developed custom estimation models that aggregate proxy data series and use statistical analysis to

estimate data points, where appropriate.

The main sources used in the FSI are the Economist Intelligence Unit, Food and Agriculture

Organisation of the United Nations, World Bank Group, Central Intelligence Agency (CIA), World

Health Organisation, Eurostat, OECD, the Yale Environmental Performance Index, African

Development Bank, BP Statistical Review of World Energy, World Trade Organisation, UN

Comtrade, Land Matrix, the Animal Protection Index, USDA, ASTI, ITUC Global Rights Index, journal

articles and studies by respected academics.

Whilst every effort has been taken to verify the accuracy of this information, neither The Economist Intelligence Unit

Ltd. nor the BCFN can accept any responsibility or liability for reliance by any person on this report or any of the

information, opinions or conclusions set out in the report.

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Detailed indicator list The indicators and sub-indicators included in the Food Sustainability Index are:

Indicator Def init ion Source Year*

OVERALL

SCORE

Aggregate of the under l y ing 3 category scores : A)

Food loss and waste

B) Susta inable agr icul ture

C) Nut r i t ional chal l enges

A) FOOD LOSS

AND W ASTE

Aggregate of the under l y ing 6 i ndicator scores :

1.1) Food loss

1.2) Pol icy response to food loss

1.3) Causes of d is t r i but ion - level l oss

2.1) End-user waste

2.2) Pol icy response to food waste

1.1) Food loss Aggregate of under ly ing 1 sub - indicator score:

1.1.1) Food los t (% of count r y 's tota l f ood

product ion)

1.1.1) Food los t

(% of count r y 's

tota l food

product ion)

Food loss as a percentage of tota l f ood product ion

of t he count r y

FAO 2013

1.2) Pol icy

response to food

loss

Aggregate of under ly ing 1 sub - indicator score:

1.2.1) Qual i t y of pol ic ies to address food loss

1.2.1) Qual i t y of

po l ic ies to

address food

loss

Compos i te indicator : I f a count r y has less than 3%

food loss (see 1.1.1) , i t r eceives the h ighes t score

on th is i ndicator , as pol ic ies for food loss are not

needed in the count ry. I f a count ry has less than

5% food loss (but more than 3%), i t received the

second highest score, i nd icat ing that some

progress s t i l l needs to be made.

Q1. Is there a nat ional p lan/s t rategy dedicated to

reduc ing food loss?

0 = No

1 = Yes, i t ' s a general p lan/ law about reduc ing

food loss (pre -consumer l evel ) but doesn' t address

i t a t spec i f ic s tages of t he supply chain

2 = Yes, and i t addresses spec i f ica l l y the d i f f erent

s tages of the supply chain

Q2. Is there an NGO or in ternat ional organisat ion

do ing any programme wi t h smal lholders to help

them reduce food loss at farm level by provid ing

safe s torage solut i ons?

0 = No

1 = Yes

EIU research -

1.3) Causes of

d is t r ibut i on- level

loss

Aggregate of under ly ing 1 sub - indicator score:

1.3.1) Qual i t y of road inf ras t ruc ture

1.3.1) Qual i t y of

road

inf ras t ruc ture

W hat is the r isk that the road network wi l l prove

inadequate to bus iness needs?

EIU Risk

Br ief i ng

2017

1.4) Solut ions to

d is t r ibut i on- level

loss

Aggregate of under ly ing 1 sub - indicator score:

1.4.1) Inves tment i n t ranspor t wi th pr i vate

par t ic ipat i on

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1.4.1)

Inves tment i n

t ranspor t wi th

pr ivate

par t ic ipat i on

Inves tment i n t ranspor t w i th pr ivate par t ic ipat ion

(as a % of GDP)

W or ld Bank;

OECD

-

2.1) Food waste

at end-user

level

Aggregate of under ly ing 1 sub- indicator score:

2.1.1) Food waste per capi ta (per year )

2 .1.1) Food

waste per capi ta

(per year )

Amount of f ood wasted per head per year EIU research -

2.2) Pol icy

response to food

waste

Aggregate of under ly ing 1 sub - indicator score:

2.2.1) Qual i t y of pol icy response to food waste

2.2.1) Qual i t y of

po l icy response

to food waste

Compos i te indicator :

Q1. Is there a food waste nat ional s t rategy in

p lace?

0 = No nat iona l p lan or s t rategy

1 = Food waste is i nc luded in other nat iona l p lans

or s t rategies ( e.g. in waste management p lans)

2 = Food waste has i ts own nat ional

p lan/s t rategy/ leg is lat i on/ regulat i on

Q2. Are there any reduct ion or prevent ion

quant i t at i ve targets or KPI s on end-user level f ood

waste?

0 = No

1 = Somewhat ( l ocal or reg ional l evel set by the

government or nat ional - l eve l i f set by char i t y

sec tor )

2 = Yes (nat ional - l eve l )

Q3. Does the count r y have market -based

ins t ruments for end-user l evel f ood waste?

0 = No

1 = Pay-per - throw taxat ion

2 = Tax reduct ions for food donat i ons

3 = two or more ins t ruments are i n p lace

Q4. Does the count r y have laws, regulat i ons , and

regulatory i ns t ruments for end -user l evel food

waste?

0 = No

1 = No nat iona l level l eg i s lat ion but c i ty - l evel

d i rec t i ves and/or regional d i rec t i ves OR a law

prevent ing food waste f rom being sent to l andf i l l

2 = Nat ional l egis lat i on and/or regulat i ons to

recyc le food waste

3 = Good Samar i tan - t ype of l aw ( reduc ing l iabi l i t y

of supermarkets for donat ing food )

4 = Nat ional l egis lat i on prevent ing supermarkets

f rom throwing away food waste and ins tead

ob l ig ing them to donate i t

Q5. Are there any government i ns t i tu t i ons to

superv ise the implementa t ion of f ood waste

solut i ons?

0 = No

1 = Government ins t i t u t i on(s ) ex is t

2 = Government ins t i t u t i on(s ) ac t i ve l y promote the

EIU research -

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13

implementat ion of solut i ons v ia nat ional media

campaigns and/or prac t ical pro jec ts

Q6. Are there any voluntary agreements to deal

wi th food waste ( reduc t ion, reuse, recyc le)?

0 = No

1 = Informal agreements ( i .e . pr ivate sec tor is

responding to c i t i zens ' ac t ions or takes measures

wi thout formal agreement )

2 = Yes ( formal agreements)

Q7. Are there any pr ivate and/or th i rd -sec tor

ins t i tu t i ons to deal wi th food waste? (e.g. f ood

banks , char i t i es , reta i l ers redis t r i but i ng food or

recyc l i ng i t )

0 = No

1 = Local / regional i ns t i t u t ions

2 = Nat ional i ns t i tu t ions

Q8. Is there any research be ing done by nat ional -

level i ns t i t u t i ons such as un ivers i t i es or th ink tanks

in order to advance knowledge on food waste

reduct ion, prevent ion, and management?

0 = No

1 = Yes

Q9. Does the count r y respect the food recovery

h ierarchy?

0 = No

1 = Yes

B)

SUSTAINABLE

AGRICULTURE

Aggregate of the under l y ing 19 ind icator scores :

3.1) Env i ronmenta l impac t of agr icul ture on water

3.2) Sus ta inab i l i ty of water wi thdrawal

3.3) W ater scarc i ty

3.4) W ater management

3.5) Trade impact

3.6) Sus ta inab i l i ty of f i sher ies

4.1) Env i ronmenta l impac t of agr icul ture on land

4.2) Land use

4.3) Impact on land of animal feed and biofuels

4.4) Land ownersh ip

4.5) Agr icul tura l subs id ies

4.6) Animal wel fare pol ic ies

4.7) Divers i f i cat i on of agr icul tura l sys tem

4.8) Env i ronmenta l b iodivers i ty

4.9) Agro-economic i ndicators

4.10) Product iv i ty

4.11) Land-users

5.1) Env i ronmenta l impac t of agr icul ture on the

atmosphere

5.2) Cl imate change mi t i gat i on

3.1)

Envi ronmental

impact of

agr icul ture on

water

Aggregate of under ly ing 1 sub - indicator score:

3.1.1) W ater footpr int

3 .1.1) W ater

footpr int

W ater footpr int of ma in c rops and l ives tock Mekonnen,

M.M. and

Hoeks t ra, A.Y.

(2011)

1996-

2005

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14

ht tp : / /www.wat

er footpr int .org/

Repor ts /Repor t

50-

Nat ionalW aterF

ootpr ints -

Vol1.pdf

3.2)

Sus ta inabi l i t y of

water wi thdrawal

Aggregate of under ly ing 1 sub - indicator score:

3.2.1) Agr icul tura l water wi thdrawals (% of tota l

renewable water resources)

3.2.1)

Agr icul tura l

water

wi thdrawals (%

of tota l

renewable water

resources)

W ater wi thdrawn for i r r i gat i on i n a g iven year ,

expressed in percent of t he tota l renewable water

resources (TRW R).

FAO Aquastat -

3.3) W ater

scarc i ty

Aggregate of under ly ing 1 sub- indicator score:

3.3.1) Monthl y f reshwater scarc i ty

3.3.1) Monthl y

f reshwater

scarc i ty

Monthly Blue water scarc i ty measured by the

number of months per year that a bas in faces

severe water scarc i ty

Hoeks t ra, A.Y.

and Mekonnen,

M.M. (2011)

Global water

scarc i ty :

monthly b lue

water footpr int

compared to

b lue water

avai l abi l i t y for

the wor ld ’s

major r i ver

bas ins , Value

of W ater

Research

Repor t Ser ies

No. 53,

UNESCO-IHE,

Del f t , t he

Nether lands .

ht tp : / /www.wat

er footpr int .org/

Repor ts /Repor t

53-

GlobalBlueW at

erScarc i ty .pdf

2011

3.4) W ater

management

Aggregate of under ly ing 1 sub - indicator score:

3.4.1) In i t i a t i ves to recyc le water for agr icul tura l

use

3.4.1) In i t i a t i ves

to recyc le water

for agr icul tura l

use

Are there any in i t ia t i ves to recyc le water for

agr icul tura l use?

In i t i a t ives can inc lude the col lec t i on of ra in water

f rom bu i ld ings and us ing that water to i r r i gate

agr icul tura l lands , or the recyc l i ng of runof f water .

These pro jec ts can take p lace at t he farm level as

vo luntary in i t i a t i ves by the fa rmers or can be

government - l ed ac t ions or programmes by

EIU research -

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15

in ternat ional development organisat ions

encouraging farmers to adopt these prac t ices .

0 = No

1 = Yes

3.5) Trade

impact

Aggregate of under ly ing 1 sub - indicator score:

3.5.1) Vi r tual Blue W ater Net Impor ts

3.5.1) Vi r tual

Blue W ater Net

Impor ts

Tota l net impor ts of v i r t ual b lue water f rom crop

and animal products .

Mekonnen,

M.M. and

Hoeks t ra, A.Y.

(2011) Nat ional

water footpr int

accounts : The

green, b lue and

grey water

footpr int of

product ion and

consumpt ion,

Value of W ater

Research

Repor t Ser ies

No. 50,

UNESCO-IHE,

Del f t , t he

Nether lands .

ht tp : / /www.wat

er footpr int .org/

Repor ts /Repor t

50-

Nat ionalW aterF

ootpr ints -

Vol1.pdf

1996-

2005

3.6)

Sus ta inabi l i t y of

f i sher ies

Aggregate of under ly ing 1 sub- indicator score:

3.6.1) F ish s tocks

3.6.1) F ish

s tocks

Percentage of f i sh ing s tocks overexp lo i ted and

col lapsed f rom EEZ

Yale

Envi ronmental

Per formance

Index 2016

2016

4.1)

Envi ronmental

impact of

agr icul ture on

land

Aggregate of under ly ing 3 sub- indicator scores :

4.1.1) Ni t rogen Use Ef f ic iency

4.1.2) Agr icul tura l land los t year l y to

deser t i f i cat ion & pol l ut i on (%)

4.1.3) Average carbon content of so i l (% of weight )

4.1.1) Ni t rogen

Use Ef f ic iency

Rat io of n i t rogen inputs to outputs Yale

Envi ronmental

Per formance

Index 2016

2010

4.1.2)

Agr icul tura l l and

los t year l y to

deser t i f i cat ion &

po l lut i on (%)

Average land degradat ion in GLASOD eros ion

degree

FAO 1991

4.1.3) Average

carbon content

of soi l (% of

weight )

Average carbon content i n the topsoi l as a % in

weight

FAO 2008

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16

4.2) Land use Aggregate of under ly ing 3 sub - indicator scores :

4.2.1) Arable l and under organic agr icul ture (% of

agr icul tura l land)

4.2.2) Ut i l i sed agr icul tura l area (% of tota l

agr icul tura l area)

4.2.3) Exis tence of sus ta inable urban farming

in i t i a t i ves

4.2.1) Arable

land under

organic

agr icul ture (% of

agr icul tura l

land)

Organic agr icul ture as % of tota l agr icul tura l area FAO 2014

4.2.2) Ut i l i sed

agr icul tura l area

(% of tota l

agr icul tura l

area)

% of ut i l i sed agr icul tura l area of t ota l agr icul tura l

area

FAO 2014

4.2.3) Exis tence

of sus ta inable

urban farming

in i t i a t i ves

Are there any sus ta in able urban farming

in i t i a t i ves?

0 = No

1 = Yes (only a handful of smal l c i t i es , not very

widespread)

2 = Yes (major c i t i es and widespread)

EIU research -

4.3) Impact on

land of animal

feed and

biofuels

Aggregate of under ly ing 3 sub - indicator scores :

4.3.1) F i rs t and second generat ion b iofuel

product ion

4.3.2) Land di ver ted to animal feed and biofuels

4.3.3) Biodiesel impor ts

4.3.1) F i rs t and

second

generat ion

b iofuel

product ion

Total b iofuel product ion (KBOE/D) BP Stat is t ica l

Review of

W or ld Energy

2017; Af r ican

Development

Bank; EIU

research

2016;

2012

4.3.2) Land

di ver ted to

an imal feed and

biofuels

% of arable l and dedicated to cul t i vat ing cereals

and other c rops for animal feed (exc luding

pas tures and graze land) as measured by the tota l

area of green maize and soybeans div ided by the

tota l arable land

FAO; Euros tat 2014;

2015

4.3.3) Biodiesel

impor ts

Impor ts in US$ of commodi t y code 382600

(Miscel laneous chemical products / / B iodiesel and

mixtures thereof , not conta in ing or contain ing less

than 70 % by weight of pet ro leum oi ls or o i ls

obta ined f rom bi tuminous minerals . / / B iodiesel and

mixtures thereof , not conta in ing or contain ing less

than 70 % by weight of pet ro leum oi ls or o i ls

obta ined f rom bi tuminous minerals ) f rom the wor ld.

UN Comtrade 2015;

2016

4.4) Land

ownership

Aggregate of under ly ing 3 sub - indicator scores :

4.4.1) Land owned / under concess ion in fore ign

count r i es (% of domest ic arable l and)

4.4.2) Degree of proper t y r ights protec t i on

4.4.3) Exis tence of l aws to protec t smal lholders

agains t l and grabbing

4.4.1) Land Land owned or under concess ion in fore ign Land Mat r i x ; 2017;

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17

owned / under

concess ion in

fore ign

count r i es (% of

domest ic arabl e

land)

count r i es as a % of domest ic arable land FAO 2014

4.4.2) Degree of

proper t y r ights

protec t i on

EIUs Bus iness Envi ronment Rank ings quant i f y the

at t rac t i veness of the bus iness envi ronment . The

degree of proper t y r i ghts protec t i on rat i ng scores

count r i es between 0 and 4, wi th 0 being very l ow

and 4 being very h igh.

EIU BER 2017

4.4.3) Exis tence

of l aws to

protec t

smal lho lders

agains t l and

grabbing

Compos i te index :

Q1. "Are there formal or cus tomary l and r i ghts

granted to communi t i es or ind iv idual smal lholders?

0 = No

1 = Yes

Q2. "Are there any laws to protec t smal lholders

agains t l and grabbing (a l so cal l ed land

acquis i t i on)?

0 = No

1 = Somewhat

2 = Yes

EIU research -

4.5) Agr icul tura l

subs id ies

Aggregate of under ly ing 1 sub - indicator score:

4.5.1) Qual i t y of agr icul tu ra l subs id ies

4.5.1) Qual i t y of

agr icul tura l

subs id ies

Compos i te indicator :

Q1. IF the count r y has agr icul tura l subs id ies , are

these subs id ies permanent?

0 = Yes

1 = No or the count r y doesn' t have subs id ies

Q2. IF the count r y has agr icul tura l subs id ies , are

these subs id ies capped a t a maximum of $300,000

per farmer?

0 = No

1 = Yes (under €300,000 per farmer or the count r y

doesn' t have subs id ies )

Q3. IF the count r y has agr icul tura l subs id ies , are

these subs id ies regress i ve af ter 30ha?

0 = No

1 = Yes or the count ry doesn' t have subs id ies

EIU research -

4.6) Animal

wel fare pol ic ies

Aggregate of under ly ing 1 sub - indicator score:

4.6.1) Qual i t y of animal wel fare regulat i on

4.6.1) Qual i t y of

an imal wel fare

regulat i on

Overal l a lphabet ical score f rom API (A

represent ing the h ighes t scor ing and G the most

room for improvement ) conver ted into numer ical

scores .

Animal

Protec t i on

Index

2014

4.7)

Divers i f i cat i on

of agr icul tura l

sys tem

Aggregate of under ly ing 1 sub - indicator score:

4.7.1) Top 3 c rops (% of tota l agr icul ture

product ion)

4 .7.1) Top 3

c rops (% of tota l

agr icul ture

product ion)

Share of t op 3 c rops of t o ta l agr icul ture product ion FAO 2014

4.8)

Envi ronmental

b iodivers i ty

Aggregate of under ly ing 2 sub - indicator scores :

4.8.1) Envi ronmental b iod ivers i ty

4.8.2) Defores tat i on (ha/year )

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18

4.8.1)

Envi ronmental

b iodivers i ty

Propor t ion of l ocal breeds c lass i f ied as be ing at

r isk of ext i nc t ion

UN 2017

4.8.2)

Defores tat i on

(ha/year )

Hectares of t ree cover l oss by count r y f rom 2001-

2015 (10% canopy cover )

W RI 2001-

15

4.9) Agro-

economic

indicators

Aggregate of under ly ing 3 sub - indicator scores :

4.9.1) Average educat ion level of f armers

4.9.2) To ta l pr i vate & pub l ic agr icul tura l sc iences

R&D expendi ture (as % of GDP)

4.9.3 ) Publ ic suppor t t o R&D

4.9.1) Average

educat ion level

of f armers

Educat ion level :

0 = no educat ion at a l l

1 = pr imary school

2 = secondary school

3 = above secondary schoo l

EIU research -

4.9.2) To ta l

pr ivate & publ ic

agr icul tura l

sc iences R&D

expendi ture (as

% of GDP)

Publ ic spending on R&D ASTI ; OECD;

EIU

-

4.9.3) Publ ic

suppor t to R&D

Publ ic suppor t to R&D:

Q1. Publ ic sec tor suppor t : are there any publ ic

agenc ies for research and technical ass is tance for

producers?

0 = No

1 = Yes

Q2. F inanc ing: is there any f inanc ing avai l able for

agr icul tura l innovat ion?

0 = No

1 = Yes

Q3. Is there a publ ic i ns t i tu t i on for f i nanc ing

agr icul tura l innovat ion?

0 = No

1 = Yes , sub-nat iona l

2 = Yes, nat ional

Q4. Tra in ing: are there any nat ional or semi -

nat ional t ra in ing programmes for new farmers i n

sus ta inable agr icul tura l p rac t ices?

0 = No

1 = Yes, sub-nat iona l

2 = Yes, nat ional

EIU research -

4.10)

Product iv i t y

Aggregate of under ly ing 1 sub - indicator score:

4.10.1) Tota l f ac tor product iv i ty (TFP) growth rate

4.10.1) Tota l

fac tor

product iv i ty

(TFP) growth

rate

Total f ac tor product i v i t y (TFP) growth rate between

2001-2013

USDA 2001-

2013

4.11) Land-

users

Aggregate of under ly ing 4 sub - indicator scores :

4.11.1) Par t ic ipat ion rate of women in farming

4.11.2) Par t ic ipat ion rate of youth i n farming

4.11.3) Average age of f a rmers

4.11.4) W ork ing condi t i ons of agr icu l tura l workers

a long the value chain

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19

4.11.1)

Par t ic ipat ion

rate of women in

farming

Employment d is t r ibut i on, agr icul ture, f emale FAO 2013

4.11.2)

Par t ic ipat ion

rate of youth i n

farming

% of youth i n farming (aged 15 -24) EIU research -

4.11.3) Average

age of f armers

Average age of f armers ( years) EIU research -

4.11.4) W ork ing

condi t i ons of

agr icul tura l

workers a long

the value chain

Overal l score ITUC Global

Rights Index

2014

5.1)

Envi ronmental

impact of

agr icul ture on

the atmosphere

Aggregate of under ly ing 4 sub - indicator scores :

5.1.1) GHG emiss ions f rom agr icul ture

5.1.2) An imal emiss ions (% tota l agr icul ture

emiss ions)

5.1.3) Fer t i l i zer emiss ions (% tota l agr icul ture

emiss ions)

5.1.4) Land use net emiss ions / removals (% tota l ,

CO2 eq)

5.1.1) GHG

emiss ions f rom

agr icul ture

Emiss ions (CO2eq) , agr icul ture tota l FAO 2014

5.1.2) An imal

emiss ions (%

tota l agr icul ture

emiss ions)

Emiss ions (CO2eq) f rom CH4/GHG emiss ions f rom

agr icul ture

FAO 2014

5.1.3) Fer t i l i zer

emiss ions (%

tota l agr icul ture

emiss ions)

Emiss ions (CO2eq) f rom N2O/GHG emiss ions f rom

agr icul ture

FAO 2014

5.1.4) Land use

net

emiss ions / remov

als (% tota l ,

CO2 eq)

Net emiss ions / removals (CO2eq) f rom land use

tota l . A negat i ve f i gure shows that the l and use

ac ts as a carbon s ink , i .e . i t capture greenhouse

gas emiss ions

FAO 2015

5.2) Cl imate

change

mi t igat i on

Aggregate of under ly ing 1 sub - indicator score:

5.2.1) Implementat ion of agr icul tura l techn iques fo r

c l imate change mi t igat i on and adaptat i on

5.2.1)

Implementat ion

of agr icul tura l

techniques for

c l imate change

mi t igat i on and

adaptat ion

Does the count r y have any in i t ia t ives of

agr icul tura l techn iques fo r c l imate change

mi t igat i on and adaptat i on?

0 = No

1 = Yes

EIU research -

C)

NUTRITIONAL

CHALLENGES

Aggregate of the under l y ing 11 ind icator scores :

6.1) Prevalence of malnour ishment

6.2) Mic ronut r ient def ic iency

6.3) Enabl i ng fac tors

7.1) Heal th l i f e expectancy

7.2) Prevalence of over -nour ishment

7.3) Impact on heal th

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20

7.4) Phys ical ac t iv i t y

8.1) Diet compos i t i on

8.2) Number of people per fas t food res taurant

8.3) Economic determinant o f d ietary pat terns

8.4) Pol icy response to d ietary pat terns

6.1) Prevalence

of

malnour ishment

Aggregate of under ly ing 4 sub - indicator scores :

6.1.1) Prevalence of undernour ishment (% of

populat i on)

6.1.2) Prevalence of s tun t ing (% of chi l dren under

5, height for age)

6.1.3) Prevalence of wast ing (% of chi l dren under

5, weight for height )

6.1.4) Prevalence of underweight (% of chi l dren

under 5, weight for age)

6.1.1)

Prevalence o f

undernour ishme

nt (% of

populat i on)

Populat ion below minimum level of d ietary energy

consumpt ion (a lso refer red to as prevalence of

undernour ishment ) shows the percentage of t he

populat i on whose food intake is i nsuf f ic ient to meet

d ietary energy requi rements cont inuous ly. Data

showing as 2 .5 is used as an es t imate for h igh -

income count r i es where f i gures are not repor ted.

W or ld Bank 2015

6.1.2)

Prevalence o f

s tunt ing (% of

chi ldren under

5, height for

age)

Prevalence o f s tunt ing is the percentage of

chi ldren under age 5 whose heigh t for age is more

than two s tandard deviat i ons below the median for

the internat ional reference populat i on ages 0-59

months . For chi l dren up to two years o ld height is

measured by recumbent l ength. For o lder chi l dren

he ight is measured by s ta ture whi le s tand ing. The

data are based on the W HO's new chi l d growth

s tandards re leased in 2006.

W or ld Bank;

EIU es t imates

-

6.1.3)

Prevalence o f

wast ing (% of

chi ldren under

5, weight for

he ight )

Prevalence o f wast ing is the propor t i on of chi l dren

under age 5 whose we igh t for height is more than

two s tandard deviat ions below the median for the

internat ional reference p opu lat i on ages 0 -59.

W or ld Bank;

EIU es t imates

-

6.1.4)

Prevalence o f

underweight (%

of chi l dren

under 5, weight

for age)

Prevalence o f underweight chi ldren is the

percentage of chi l dren under age 5 whose weight

for age is more than two s tandard deviat i ons below

the median for the i nternat ional reference

populat i on ages 0 -59 months . The data are based

on the W HO's new chi l d g rowth s tandards re leased

in 2006.

W or ld Bank;

EIU es t imates

-

6.2)

Mic ronut r i ent

def ic iency

Aggregate of under ly ing 2 sub- indicator scores :

6.2.1) Vi tamin A def ic iency (% of general

populat i on)

6.2.2) Iodine def ic iency (% of general popula t ion)

6.2.1) Vi tamin A

def ic iency (% of

general

populat i on)

Prevalence o f ret i nol <0.70 µmol /L. Nat ional , both

sexes , Nat ional : Pre-SAC: Total .

W HO 2014

6.2.2) Iodine

def ic iency (% of

general

populat i on)

Prevalence o f ur inary i odine < 100 ug/L. Local ,

both sexes , Buenos Ai res c i ty : SAC.

W HO -

6.3) Enabl i ng Aggregate of under ly ing 2 sub - indicator scores :

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fac tors 6.3.1) Babies under 6 months o ld exc lus ivel y

breas t fed (% tota l )

6.3.2) Access to improved water source

6.3.1) Babies

under 6 months

o ld exc lus ivel y

breas t fed (%

tota l )

Percentage of babies under 6 months o ld

exc lus i vel y breas t fed

W or ld Bank;

W HO; UNICEF;

EIU es t imate

-

6.3.2) Access to

improved water

source

Access to an improved water source refers to the

percentage of the populat ion us ing an improved

dr ink ing water source. The improved dr ink ing water

source inc ludes p iped water on premises (p iped

household water connect ion located ins ide the

user ’s dwel l i ng, p lot or yard) , and other improved

dr ink ing water sources (pub l ic taps or s tandpipes ,

tube we l ls or boreholes , protec ted dug wel ls ,

protec ted spr ings , and ra inwater col l ec t i on) .

W or ld Bank 2015

7.1) Heal th l i f e

expectancy

Aggregate of under ly ing 2 sub - indicator scores :

7.1.1) L i fe expectancy at b i r th, tota l ( years)

7.1.2) Heal thy l i f e expectancy (HALE)

7.1.1) L i fe

expectancy at

b i r th, tota l

(years)

L i fe expectancy at b i r th i nd icates the number of

years a new-born infant wou ld l i ve i f prevai l i ng

pat terns of mor ta l i t y at t he t ime of i ts b i r th were to

s tay the same throughout i ts l i fe .

W or ld Bank 2015

7.1.2) Heal thy

l i fe expectancy

(HALE)

Heal thy l i fe expectancy (HALE) W HO 2015

7.2) Prevalence

of over -

nour ishment

Aggregate of under ly ing 2 sub - indicator scores :

7.2.1) Prevalence of overweight i n chi l dren (5 -19

years of age)

7.2.2) Prevalence of overweight i n adul ts (body

mass index >= 25)

7.2.1)

Prevalence o f

overweight i n

chi ldren (5-19

years of age)

Prevalence o f overweight among chi l dren and

adolescents , BMI > +1 s tandard deviat ions above

the median (c rude es t imate) (%) (5 -19 years of

age)

W HO 2016

7.2.2)

Prevalence o f

overweight i n

adul ts (body

mass index >=

25)

Prevalence o f overweight among adu l ts , BMI &

Greater Equal ; 25 (age-s tandardized es t imate) (%)

(18+)

W HO 2016

7.3) Impact on

heal th

Aggregate of under ly ing 1 sub - indicator score:

7.3.1) Disabi l i t y Ad jus ted L i fe Years (DALYs) f rom

nut r i t ional def ic ienc ies

7.3.1) Disabi l i t y

Ad jus ted L i fe

Years (DALYs)

f rom nut r i t ional

def ic ienc ies

Disabi l i t y Ad jus ted L i fe Year (DALY) due to

nut r i t ional def ic ienc ies . DALYs f rom nut r i t i ona l

def ic ienc ies overal l and f rom diabetes and

cardiovascular issues .

W HO 2012

7.4) Phys ical

ac t iv i t y

Aggregate of under ly ing 2 sub- indicator scores :

7.4.1) Populat i on reaching recommended phys ical

ac t iv i t y per week (%)

7.4.2) Hours of inac t i v i t y , f i xed screen t ime per

week

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22

7.4.1)

Populat ion

reaching

recommended

phys ical ac t i v i t y

per week (%)

Percentage of populat i o n reaching recommended

phys ical ac t i v i t y per week

EIU research -

7.4.2) Hours of

inac t iv i t y , f i xed

screen t ime per

week

Hours spent in f ront of TV, PC, and tablet Mi l lward and

Brown,

AdReact ion

2014 repor t ;

EIU research

2014

8.1) Diet

compos i t i on

Aggregate of under ly ing 4 sub - indicator scores :

8.1.1) Percentage of sugar in d iets

8.1.2) Meat consumpt ion levels

8.1.3) Saturated fat consumpt ion

8.1.4) Sa l t consumpt ion

8.1.1)

Percentage of

sugar i n d iets

% of sugar i n d iets Nat ional

Geographic

"W hat the

wor ld eats " ;

FAO

2011;

2013

8.1.2) Meat

consumpt ion

levels

Di f ference in meat supply quant i t y (g/capi ta/day)

f rom recommended intake

FAO;

McMichae l , AJ

et a l . "Food,

l i ves tock

product ion,

energy, c l imate

change, and

heal th. "

2013

8.1.3) Saturated

fat consumpt ion

Di f ference in fat supply quant i t y (g/capi ta/day)

f rom recommended intake. Tota l animal fats .

FAO; Nat ional

Heal th Serv ice

2013

8.1.4) Sa l t

consumpt ion

Average g/day sodium consumpt ion Powles , John,

et a l . "Global ,

regional and

nat ional

sodium intakes

in 1990 and

2010: a

sys temat ic

analys is of 24

h ur inary

sodium

excret i on and

dietary surveys

wor ldw ide. "

2010

8.2) Number of

people per fas t

food res taurant

Aggregate of under ly ing 1 sub - indicator score:

8.2.1) Number of people per fas t f ood res taurant

8 .2.1) Number

of people per

fas t food

res taurant

Populat ion s i ze in 2015 d iv ided by the tota l number

of f as t food res taurants f rom the g lobal top 3

brands (McDonald 's , KFC, and Burger K ing) . Shows

penet rat ion rate of f as t f ood res taurants , as a

proxy of change towards unheal thy d iets . A h igher

f igure means that there penet rat i on rate of fas t

food res taurants is re lat ive l y low ( i . e. there aren' t

many fas t - food res taurants in the count r y)

EIU research 2015

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8.3) Economic

determinant of

d ietary pat terns

Aggregate of under ly ing 2 sub - indicator scores :

8.3.1) Propor t i on of populat i on l i v i ng below the

nat ional pover ty l ine

8.3.2) GINI Coef f ic ient

8.3.1)

Propor t ion of

populat i on l i v i ng

be low the

nat ional pover ty

l ine

% of populat i on under the nat ional pover ty

threshold (minimum level of i ncome deemed

adequate i n a par t icu lar count r y) ( var ies by

count r y)

UN; CIA W or ld

Fac tbook; EIU

research

-

8.3.2) GINI

Coef f ic ient

Stat is t ica l measure of the degree of var iat ion or

inequal i t y represented in a set of values , used

espec ia l ly i n ana lys ing income inequal i t y . Higher =

more unequal

W or ld Bank -

8.4) Pol icy

response to

d ietary pat terns

Aggregate of under ly ing 2 sub- indicator scores :

8.4.1) Qual i t y of pol icy response to d ietary

pat terns

8.4.2) Nut r i t i on educat ion

8.4.1) Qual i t y of

po l icy response

to d ietary

pat terns

Compos i te indicator :

Q1. Are there any pol ic ies and/or programmes to

promote heal thy eat ing pat terns (nat ional and c i ty

level )

0 = No

1 = Ci t y - l evel , l ocal or regional

2 = nat ional l evel

Q2. Are there any heal thy eat ing regular l y updated

(every 5 years at l eas t ) guidel i nes at nat ional

level? 0 = No

1 = Less of ten than every 5 years OR no spec i f i ed

f requency but the l ates t update is l ess than 5 years

2 = intervals of 5 years or more o f ten

Q3. Are there any taxes o f processed food?

0 = No

1 = Yes

Q4. Are there any subs id ies on inputs (sugar , corn

syrup, palm oi l , e tc . ) f or processed food?

0 = Yes

1 = No

EIU research -

8.4.2) Nut r i t i on

educat ion

Is nut r i t i on educat ion inc luded (NE) i n the nat ional

cur r icu lum (compulsory) for pr imary and/or

secondary schools?

0= No (NE is not i nc luded in the compulsory

nat ional cur r icu lum OR there are only a few local

in i t i a t i ves to i nc lude NE in schoo ls )

1 = Par t i a l ly (NE is inc luded in the nat ional

cur r icu lum in theory but i n prac t ice, most schools

don' t have NE OR NE is not i nc luded in the

compulsory cur r icu lum but in prac t ice some

schools have NE OR NE i s inc luded in the

cur r icu lum but is not compulsory)

2 = Yes (NE is inc luded in the nat ional cur r icu lum

and is ef fec t ive l y implemented in prac t ice)

EIU research -

BACKGROUND

INDICATORS

BG1) PUBLIC

AND PRIVATE

Total heal th expendi ture i s the sum of publ ic and

pr ivate heal th expendi tures as a rat i o of t ota l

W or ld Bank 2014

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HEALTHCARE

EXPENDITURE

(PER CAPITAL,

CURRENT US$)

populat i on. I t covers the provis ion of hea l th

serv ices (prevent i ve and curat i ve) , fami l y p lanning

ac t iv i t i es , nut r i t ion ac t iv i t ies , and emergency a id

des ignat ed for heal th but does not inc lude

provis ion of water and sani tat ion. Data are in

cur rent U.S. dol lars .

BG2) NEF

HAPPY PLANET

INDEX

The Happy Planet Index (HPI) is a measure of

sus ta inable wel lbeing. I t compares how ef f ic ient l y

res idents of d i f f erent count r ies are us ing natural

resources to achieve long, h igh wel lbeing l i ves .

NEF Happy

Planet Index

2016

BG3) 2027

Populat ion

Total populat i on (both sexes combined) by count r y ,

annual l y for 2027 ( thousands) , medium fer t i l i t y

var iant .

UN Populat ion 2017

BG4)

POPULATION

GROW TH (2017-

2027)

Change in tota l popu lat i on (both sexes combined)

by count r y, annual l y f rom 2017 to 2027, med i um

fer t i l i t y var iant .

UN Populat ion 2017

BG5) GROW TH

IN POPULATION

AS A

PERCENTAGE

OF GLOBAL

POPULATION

(2017-2027)

Change in tota l popu lat i on (both sexes combined)

by count r y, annual l y f rom 2017 to 2027, med ium

fer t i l i t y var iant , as a percentage of t he tota l g lobal

populat i on.

UN Populat ion 2017

BG6) GDP Gross domest ic product (GDP) at purchas ing power

par i t y (PPP) i n US$.

EIU 2017

BG7) GDP PER

HEAD

GDP at purchas ing power par i t y (PPP) IS US$,

d i v ided by populat i on.

EIU 2017

BG8) HUMAN

DEVELOPMENT

INDEX

The Human Development Index (HDI) is a summary

measure of average achievement i n key d imens ions

of human development : a long and heal thy l i f e ,

be ing knowledgeable and have a decent s tandard

of l i v ing. The HDI is the geometr ic mean of

normal ized indic es for each of t he three

d imens ions .

UNDP 2016

* In cases where a cons is tent data year is no t avai lab le for a l l 34 countr ies in the FSI , a “ - “

has been used.