Sweeteners, Other — Stock Variation 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...
Countries reporting
181
Highest
214 1000 t
Ukraine
Lowest
-141 1000 t
Netherlands (Kingdom of the)
Median
0 1000 t
Years covered
14
2010–2023
Data points
3,033
What the numbers show
Sweeteners, Other — Stock Variation is currently reported for 181 countries. The highest value is 214 1000 t in Ukraine; the lowest is -141 1000 t in Netherlands (Kingdom of the).
The median across all reporting countries is 0 1000 t, and the mean is 5.89 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 58 countries rose and 64 fell. The largest increase was in United Kingdom (up 9,000.0%), and the largest decrease in Jordan (down 4,900.0%).
Sweeteners, Other — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Ukraine | 214 1000 t | 2023 | up 4,380.0% | volatile |
| 2 | United States | 170 1000 t | 2023 | up 580.0% | volatile |
| 3 | France | 152 1000 t | 2023 | — | volatile |
| 4 | United Kingdom | 89 1000 t | 2023 | up 9,000.0% | volatile |
| 4 | United Kingdom of Great Britain and Northern Ireland | 89 1000 t | 2023 | up 9,000.0% | volatile |
| 6 | Iran (Islamic Republic of) | 87 1000 t | 2023 | up 328.9% | volatile |
| 7 | Egypt | 69 1000 t | 2023 | up 360.0% | volatile |
| 8 | Vietnam | 57 1000 t | 2023 | up 159.1% | volatile |
| 8 | Viet Nam | 57 1000 t | 2023 | up 159.1% | volatile |
| 10 | Ecuador | 50 1000 t | 2023 | up 5,100.0% | volatile |
| 11 | Philippines | 46 1000 t | 2023 | up 4,500.0% | volatile |
| 12 | Caribbean | 45 1000 t | 2023 | up 381.2% | volatile |
| 13 | Germany | 41 1000 t | 2023 | — | volatile |
| 14 | Turkey | 35 1000 t | 2023 | — | volatile |
| 14 | Türkiye | 35 1000 t | 2023 | — | volatile |
| 16 | India | 30 1000 t | 2023 | up 100.0% | volatile |
| 16 | Luxembourg | 30 1000 t | 2023 | up 25.0% | volatile |
| 18 | Cote d'Ivoire | 29 1000 t | 2023 | up 1,350.0% | volatile |
| 18 | Thailand | 29 1000 t | 2023 | up 133.3% | volatile |
| 18 | Côte d'Ivoire | 29 1000 t | 2023 | up 1,350.0% | volatile |
| 21 | Guatemala | 28 1000 t | 2023 | up 2,700.0% | volatile |
| 22 | Bulgaria | 24 1000 t | 2023 | up 214.3% | volatile |
| 22 | Slovenia | 24 1000 t | 2023 | — | volatile |
| 22 | Trinidad and Tobago | 24 1000 t | 2023 | — | volatile |
| 25 | Eswatini | 20 1000 t | 2023 | up 1,100.0% | volatile |
| 26 | Bangladesh | 18 1000 t | 2023 | up 1,000.0% | volatile |
| 26 | Barbados | 18 1000 t | 2023 | — | volatile |
| 26 | Colombia | 18 1000 t | 2023 | up 1,700.0% | volatile |
| 29 | Namibia | 17 1000 t | 2023 | up 240.0% | volatile |
| 29 | Uzbekistan | 17 1000 t | 2023 | up 1,600.0% | volatile |
| 29 | China, Taiwan Province of | 17 1000 t | 2023 | up 1,800.0% | volatile |
| 32 | Kyrgyzstan | 16 1000 t | 2023 | down 68.0% | volatile |
| 33 | Lithuania | 14 1000 t | 2023 | up 380.0% | volatile |
| 33 | Mongolia | 14 1000 t | 2023 | up 180.0% | volatile |
| 33 | Republic of Korea | 14 1000 t | 2023 | down 66.7% | volatile |
| 36 | Ireland | 13 1000 t | 2023 | — | volatile |
| 36 | Morocco | 13 1000 t | 2023 | up 225.0% | volatile |
| 36 | China, Hong Kong SAR | 13 1000 t | 2023 | up 30.0% | volatile |
| 39 | South Africa | 12 1000 t | 2023 | down 92.1% | volatile |
| 40 | Montenegro | 10 1000 t | 2023 | up 600.0% | volatile |
| 41 | Botswana | 8 1000 t | 2023 | up 366.7% | volatile |
| 41 | Czechia | 8 1000 t | 2023 | — | volatile |
| 41 | Sweden | 8 1000 t | 2023 | — | volatile |
| 44 | Argentina | 7 1000 t | 2023 | down 12.5% | volatile |
| 44 | Brazil | 7 1000 t | 2023 | unchanged | volatile |
| 44 | Denmark | 7 1000 t | 2023 | up 187.5% | volatile |
| 44 | Mauritius | 7 1000 t | 2023 | up 133.3% | volatile |
| 48 | Australia | 6 1000 t | 2023 | — | volatile |
| 48 | Libya | 6 1000 t | 2023 | down 72.7% | volatile |
| 50 | United Arab Emirates | 4 1000 t | 2023 | up 125.0% | volatile |
| 50 | Bosnia and Herzegovina | 4 1000 t | 2023 | — | volatile |
| 50 | Algeria | 4 1000 t | 2023 | up 500.0% | volatile |
| 50 | Zambia | 4 1000 t | 2023 | up 100.0% | volatile |
| 54 | Spain | 3 1000 t | 2023 | up 107.5% | volatile |
| 54 | Iceland | 3 1000 t | 2023 | — | volatile |
| 54 | Latvia | 3 1000 t | 2023 | — | volatile |
| 54 | United Republic of Tanzania | 3 1000 t | 2023 | — | volatile |
| 58 | Armenia | 2 1000 t | 2023 | down 75.0% | volatile |
| 58 | Finland | 2 1000 t | 2023 | up 150.0% | volatile |
| 58 | Kazakhstan | 2 1000 t | 2023 | down 33.3% | volatile |
| 58 | Pakistan | 2 1000 t | 2023 | up 101.3% | volatile |
| 58 | Saudi Arabia | 2 1000 t | 2023 | — | volatile |
| 63 | Antigua and Barbuda | 1 1000 t | 2023 | — | volatile |
| 63 | Bahamas | 1 1000 t | 2023 | up 114.3% | volatile |
| 63 | Cameroon | 1 1000 t | 2023 | unchanged | volatile |
| 63 | Guinea | 1 1000 t | 2023 | down 83.3% | volatile |
| 63 | Croatia | 1 1000 t | 2023 | up 108.3% | volatile |
| 63 | Israel | 1 1000 t | 2023 | down 88.9% | volatile |
| 63 | Italy | 1 1000 t | 2023 | — | volatile |
| 63 | Madagascar | 1 1000 t | 2023 | unchanged | volatile |
| 63 | Nigeria | 1 1000 t | 2023 | down 91.7% | volatile |
| 63 | Nepal | 1 1000 t | 2023 | down 92.3% | volatile |
| 63 | Peru | 1 1000 t | 2023 | unchanged | volatile |
| 63 | Paraguay | 1 1000 t | 2023 | up 150.0% | volatile |
| 63 | Zimbabwe | 1 1000 t | 2023 | down 97.1% | volatile |
| 76 | Afghanistan | 0 1000 t | 2023 | down 100.0% | flat |
| 76 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Albania | 0 1000 t | 2023 | — | volatile |
| 76 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 76 | Belize | 0 1000 t | 2023 | — | volatile |
| 76 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Congo | 0 1000 t | 2023 | — | volatile |
| 76 | Comoros | 0 1000 t | 2023 | — | volatile |
| 76 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Djibouti | 0 1000 t | 2023 | down 100.0% | flat |
| 76 | Estonia | 0 1000 t | 2023 | — | volatile |
| 76 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Ghana | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Gambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Greece | 0 1000 t | 2023 | — | volatile |
| 76 | Grenada | 0 1000 t | 2023 | — | volatile |
| 76 | Guyana | 0 1000 t | 2023 | — | flat |
| 76 | Honduras | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Haiti | 0 1000 t | 2023 | — | volatile |
| 76 | Indonesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Iraq | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Kenya | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Laos | 0 1000 t | 2023 | — | volatile |
| 76 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Liberia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Lesotho | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Maldives | 0 1000 t | 2023 | — | volatile |
| 76 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 76 | North Macedonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Myanmar | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Malawi | 0 1000 t | 2023 | — | volatile |
| 76 | Malaysia | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Niger | 0 1000 t | 2023 | — | volatile |
| 76 | Nicaragua | 0 1000 t | 2023 | down 100.0% | flat |
| 76 | Oman | 0 1000 t | 2023 | — | volatile |
| 76 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 76 | Russia | 0 1000 t | 2023 | — | volatile |
| 76 | Rwanda | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 76 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Sao Tome and Principe | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Suriname | 0 1000 t | 2023 | — | volatile |
| 76 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Turkmenistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | East Timor | 0 1000 t | 2023 | — | flat |
| 76 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Uganda | 0 1000 t | 2023 | — | flat |
| 76 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 76 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 76 | Yemen | 0 1000 t | 2023 | up 100.0% | volatile |
| 76 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 76 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 76 | Cabo Verde | 0 1000 t | 2023 | — | volatile |
| 76 | Polynesia | 0 1000 t | 2023 | — | flat |
| 76 | Democratic Republic of the Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 76 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 76 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 76 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 76 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | volatile |
| 76 | China, Macao SAR | 0 1000 t | 2023 | up 100.0% | volatile |
| 167 | Dominican Republic | -1 1000 t | 2023 | up 75.0% | volatile |
| 167 | Saint Kitts and Nevis | -1 1000 t | 2023 | — | volatile |
| 167 | Saint Lucia | -1 1000 t | 2023 | — | flat |
| 167 | Malta | -1 1000 t | 2023 | down 133.3% | volatile |
| 167 | Mozambique | -1 1000 t | 2023 | up 97.8% | volatile |
| 167 | Slovakia | -1 1000 t | 2023 | up 98.2% | volatile |
| 173 | Cyprus | -3 1000 t | 2023 | down 50.0% | volatile |
| 174 | Moldova | -4 1000 t | 2023 | — | volatile |
| 174 | Republic of Moldova | -4 1000 t | 2023 | — | volatile |
| 176 | Tajikistan | -5 1000 t | 2023 | down 200.0% | volatile |
| 177 | Senegal | -9 1000 t | 2023 | down 400.0% | volatile |
| 177 | Australia and New Zealand | -9 1000 t | 2023 | down 125.0% | volatile |
| 179 | Belarus | -11 1000 t | 2023 | down 134.4% | volatile |
| 179 | Switzerland | -11 1000 t | 2023 | up 57.7% | volatile |
| 181 | Serbia | -12 1000 t | 2023 | down 300.0% | volatile |
| 182 | New Zealand | -15 1000 t | 2023 | down 275.0% | volatile |
| 183 | Romania | -23 1000 t | 2023 | down 330.0% | volatile |
| 184 | Norway | -33 1000 t | 2023 | down 283.3% | volatile |
| 185 | El Salvador | -36 1000 t | 2023 | down 1,900.0% | volatile |
| 186 | Fiji | -38 1000 t | 2023 | down 15.2% | volatile |
| 186 | Melanesia | -38 1000 t | 2023 | down 100.0% | volatile |
| 188 | Jordan | -50 1000 t | 2023 | down 4,900.0% | volatile |
| 189 | China | -60 1000 t | 2023 | down 57.9% | volatile |
| 190 | Hungary | -84 1000 t | 2023 | up 30.0% | volatile |
| 191 | China, mainland | -90 1000 t | 2023 | down 104.5% | volatile |
| 192 | Austria | -94 1000 t | 2023 | down 204.4% | volatile |
| 193 | Netherlands (Kingdom of the) | -141 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,107 1000 t
- Asia 406 1000 t
- Americas 290 1000 t
- Europe 236 1000 t
- Africa 221 1000 t
- Net Food Importing Developing Countries (NFIDCs) 189 1000 t
- Northern America 170 1000 t
- United States of America 170 1000 t
- Southern Asia 137 1000 t
- South-Eastern Asia 132 1000 t
- Eastern Europe 123 1000 t
- Eastern Asia 117 1000 t
- Northern Europe 105 1000 t
- Northern Africa 93 1000 t
- Land Locked Developing Countries (LLDCs) 86 1000 t
- South America 84 1000 t
- Low Income Food Deficit Countries (LIFDCs) 60 1000 t
- Southern Africa 57 1000 t
- Western Africa 54 1000 t
- Least Developed Countries (LDCs) 53 1000 t
- Southern Europe 31 1000 t
- Central Asia 29 1000 t
- Eastern Africa 16 1000 t
- Small island developing States (SIDS) 14 1000 t
- Middle Africa 1 1000 t
- Central America -8 1000 t
- Western Asia -10 1000 t
- European Union (27) -16 1000 t
- Western Europe -23 1000 t
- Oceania -46 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.