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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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  • 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 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

  • 8

    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.

  • 9

    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.

  • 10

    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.

  • 11

    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

  • 12

    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 -

  • 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

  • 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 -

  • 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

  • 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;

  • 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 )

  • 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

  • 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

  • 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

  • 21

    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

  • 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

  • 23

    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

  • 24

    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.