Offals — Residuals 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
Offals — Residuals is currently reported for 67 countries. The highest value is 3 1000 t in Guatemala; the lowest is -355 1000 t in Poland.
The median across all reporting countries is 0 1000 t, and the mean is -12.57 1000 t.
Over the past decade 6 countries rose and 25 fell. The largest increase was in Mongolia (up 100.0%), and the largest decrease in Poland (down 35,400.0%).
Offals — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Guatemala | 3 1000 t | 2023 | — | volatile |
| 2 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Sweden | 0 1000 t | 2023 | — | volatile |
| 2 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 2 | Russia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Romania | 0 1000 t | 2023 | — | volatile |
| 2 | Oman | 0 1000 t | 2023 | — | volatile |
| 2 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Norway | 0 1000 t | 2023 | — | volatile |
| 2 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 2 | Mongolia | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Latvia | 0 1000 t | 2023 | — | volatile |
| 2 | Lithuania | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 2 | Russian Federation | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | China, mainland | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Viet Nam | 0 1000 t | 2023 | — | volatile |
| 2 | Thailand | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Vietnam | 0 1000 t | 2023 | — | volatile |
| 2 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | United States | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Angola | 0 1000 t | 2023 | — | volatile |
| 2 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 2 | Czechia | 0 1000 t | 2023 | — | volatile |
| 2 | Chile | 0 1000 t | 2023 | — | volatile |
| 2 | Algeria | 0 1000 t | 2023 | — | volatile |
| 2 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 2 | Brazil | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Estonia | 0 1000 t | 2023 | — | volatile |
| 2 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | France | 0 1000 t | 2023 | — | volatile |
| 2 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Iceland | 0 1000 t | 2023 | — | volatile |
| 2 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 172 | Uruguay | -1 1000 t | 2023 | unchanged | volatile |
| 172 | Germany | -1 1000 t | 2023 | down 114.3% | volatile |
| 172 | Slovenia | -1 1000 t | 2023 | — | volatile |
| 172 | Ireland | -1 1000 t | 2023 | — | volatile |
| 172 | South Africa | -1 1000 t | 2023 | down 100.8% | volatile |
| 172 | Ethiopia | -1 1000 t | 2023 | unchanged | volatile |
| 178 | Spain | -2 1000 t | 2023 | — | volatile |
| 178 | Bulgaria | -2 1000 t | 2023 | down 166.7% | volatile |
| 180 | Slovakia | -3 1000 t | 2023 | — | volatile |
| 181 | Italy | -4 1000 t | 2023 | down 500.0% | volatile |
| 182 | Finland | -5 1000 t | 2023 | — | volatile |
| 182 | Hungary | -5 1000 t | 2023 | — | volatile |
| 184 | Canada | -11 1000 t | 2023 | — | volatile |
| 185 | China, Hong Kong SAR | -15 1000 t | 2023 | — | volatile |
| 185 | China | -15 1000 t | 2023 | down 200.0% | volatile |
| 187 | Austria | -21 1000 t | 2023 | — | volatile |
| 188 | Belgium | -33 1000 t | 2023 | down 1,000.0% | volatile |
| 189 | United Kingdom | -48 1000 t | 2023 | — | volatile |
| 189 | United Kingdom of Great Britain and Northern Ireland | -48 1000 t | 2023 | — | volatile |
| 191 | Denmark | -63 1000 t | 2023 | — | volatile |
| 192 | Netherlands (Kingdom of the) | -72 1000 t | 2023 | — | volatile |
| 193 | India | -137 1000 t | 2023 | — | volatile |
| 194 | Poland | -355 1000 t | 2023 | down 35,400.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Central America 3 1000 t
- United States of America 0 1000 t
- Western Asia 0 1000 t
- South-Eastern Asia 0 1000 t
- Middle Africa 0 1000 t
- Northern Africa 0 1000 t
- Central Asia 0 1000 t
- Oceania 0 1000 t
- Africa -1 1000 t
- Southern Africa -1 1000 t
- Land Locked Developing Countries (LLDCs) -1 1000 t
- Low Income Food Deficit Countries (LIFDCs) -1 1000 t
- Eastern Africa -1 1000 t
- Least Developed Countries (LDCs) -1 1000 t
- Net Food Importing Developing Countries (NFIDCs) -1 1000 t
- South America -1 1000 t
- Southern Europe -7 1000 t
- Americas -9 1000 t
- Northern America -11 1000 t
- Eastern Asia -15 1000 t
- Northern Europe -117 1000 t
- Western Europe -126 1000 t
- Southern Asia -137 1000 t
- Asia -152 1000 t
- Eastern Europe -366 1000 t
- European Union (27) -567 1000 t
- Europe -616 1000 t
- World -778 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.