Sugar & Sweeteners — Losses by country
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Sugar & Sweeteners — Losses is currently reported for 57 countries. The highest value is 25 1000 t in Myanmar; the lowest is 0 1000 t in Peru.
The median across all reporting countries is 1 1000 t, and the mean is 3.19 1000 t.
Over the past decade 7 countries rose and 19 fell. The largest increase was in Republic of Korea (up 100.0%), and the largest decrease in Dominican Republic (down 100.0%).
Sugar & Sweeteners — Losses: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Myanmar | 25 1000 t | 2023 | up 8.7% | rising |
| 2 | China | 24 1000 t | 2023 | unchanged | flat |
| 3 | China, mainland | 23 1000 t | 2023 | unchanged | rising |
| 4 | Bangladesh | 12 1000 t | 2023 | down 25.0% | falling |
| 5 | Indonesia | 11 1000 t | 2023 | down 8.3% | flat |
| 6 | Turkey | 5 1000 t | 2023 | up 25.0% | rising |
| 6 | Venezuela (Bolivarian Republic of) | 5 1000 t | 2023 | down 61.5% | falling |
| 6 | Türkiye | 5 1000 t | 2023 | up 25.0% | rising |
| 6 | Ethiopia | 5 1000 t | 2023 | up 66.7% | rising |
| 10 | Argentina | 4 1000 t | 2023 | unchanged | rising |
| 10 | Hungary | 4 1000 t | 2023 | down 20.0% | falling |
| 10 | India | 4 1000 t | 2023 | up 33.3% | rising |
| 13 | Ukraine | 3 1000 t | 2023 | down 25.0% | falling |
| 13 | Mexico | 3 1000 t | 2023 | unchanged | flat |
| 13 | Sierra Leone | 3 1000 t | 2023 | — | volatile |
| 13 | Brazil | 3 1000 t | 2023 | up 50.0% | rising |
| 13 | Russian Federation | 3 1000 t | 2023 | down 25.0% | falling |
| 13 | Russia | 3 1000 t | 2023 | down 25.0% | falling |
| 19 | United States | 2 1000 t | 2023 | down 95.5% | volatile |
| 19 | Canada | 2 1000 t | 2023 | down 50.0% | falling |
| 19 | Romania | 2 1000 t | 2023 | down 81.8% | volatile |
| 19 | Republic of Korea | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | United Republic of Tanzania | 2 1000 t | 2023 | unchanged | flat |
| 19 | Spain | 2 1000 t | 2023 | unchanged | flat |
| 25 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 25 | Caribbean | 1 1000 t | 2023 | down 94.1% | volatile |
| 25 | Iran (Islamic Republic of) | 1 1000 t | 2023 | down 75.0% | volatile |
| 25 | Viet Nam | 1 1000 t | 2023 | unchanged | flat |
| 25 | Australia and New Zealand | 1 1000 t | 2023 | down 50.0% | rising |
| 25 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | — | volatile |
| 25 | Italy | 1 1000 t | 2023 | — | volatile |
| 25 | Angola | 1 1000 t | 2023 | unchanged | flat |
| 25 | Australia | 1 1000 t | 2023 | unchanged | flat |
| 25 | Bulgaria | 1 1000 t | 2023 | unchanged | rising |
| 25 | Chile | 1 1000 t | 2023 | unchanged | rising |
| 25 | Cuba | 1 1000 t | 2019 | — | volatile |
| 25 | Germany | 1 1000 t | 2023 | unchanged | flat |
| 25 | France | 1 1000 t | 2023 | unchanged | flat |
| 25 | United Kingdom | 1 1000 t | 2023 | — | volatile |
| 25 | Greece | 1 1000 t | 2023 | unchanged | flat |
| 25 | Croatia | 1 1000 t | 2023 | — | volatile |
| 25 | Kenya | 1 1000 t | 2023 | — | volatile |
| 25 | New Zealand | 1 1000 t | 2023 | unchanged | flat |
| 25 | Panama | 1 1000 t | 2023 | down 50.0% | falling |
| 25 | Vietnam | 1 1000 t | 2023 | unchanged | flat |
| 25 | Poland | 1 1000 t | 2023 | unchanged | flat |
| 25 | Portugal | 1 1000 t | 2023 | unchanged | volatile |
| 25 | Uruguay | 1 1000 t | 2023 | unchanged | falling |
| 25 | Thailand | 1 1000 t | 2023 | — | volatile |
| 50 | Dominican Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 50 | Czechia | 0 1000 t | 2023 | — | volatile |
| 50 | China, Hong Kong SAR | 0 1000 t | 2018 | down 100.0% | volatile |
| 50 | Colombia | 0 1000 t | 2023 | down 100.0% | volatile |
| 50 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 50 | Serbia | 0 1000 t | 2023 | — | volatile |
| 50 | Israel | 0 1000 t | 2023 | — | volatile |
| 50 | Peru | 0 1000 t | 2023 | down 100.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 152 1000 t
- Asia 88 1000 t
- Net Food Importing Developing Countries (NFIDCs) 58 1000 t
- Least Developed Countries (LDCs) 50 1000 t
- South-Eastern Asia 38 1000 t
- Europe 25 1000 t
- Eastern Asia 25 1000 t
- Americas 23 1000 t
- Southern Asia 17 1000 t
- European Union (27) 16 1000 t
- Eastern Europe 15 1000 t
- Africa 15 1000 t
- Low Income Food Deficit Countries (LIFDCs) 14 1000 t
- South America 14 1000 t
- Land Locked Developing Countries (LLDCs) 8 1000 t
- Eastern Africa 8 1000 t
- Western Asia 7 1000 t
- Southern Europe 6 1000 t
- Northern America 4 1000 t
- Central America 4 1000 t
- Western Africa 3 1000 t
- Northern Europe 2 1000 t
- Middle Africa 2 1000 t
- United States of America 2 1000 t
- Western Europe 2 1000 t
- Small island developing States (SIDS) 1 1000 t
- Oceania 1 1000 t
- Northern Africa 1 1000 t
- Central Asia 1 1000 t
About this data
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per capita food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.