Coconut Oil — Food 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
Coconut Oil — Food is currently reported for 144 countries. The highest value is 254 1000 t in India; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 1 1000 t, and the mean is 9.68 1000 t.
Over the past decade 27 countries rose and 24 fell. The largest increase was in United Arab Emirates (up 500.0%), and the largest decrease in Armenia (down 100.0%).
Coconut Oil — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 254 1000 t | 2023 | down 4.2% | falling |
| 2 | China | 187 1000 t | 2023 | up 36.5% | falling |
| 3 | China, mainland | 182 1000 t | 2023 | up 38.9% | falling |
| 4 | Philippines | 126 1000 t | 2023 | down 72.0% | volatile |
| 5 | Viet Nam | 98 1000 t | 2023 | up 25.6% | rising |
| 6 | Malaysia | 68 1000 t | 2023 | up 100.0% | rising |
| 7 | Sri Lanka | 45 1000 t | 2023 | up 114.3% | volatile |
| 8 | Republic of Korea | 34 1000 t | 2023 | down 44.3% | falling |
| 9 | Thailand | 31 1000 t | 2023 | up 3.3% | falling |
| 10 | Mozambique | 26 1000 t | 2023 | up 52.9% | rising |
| 11 | Bangladesh | 24 1000 t | 2023 | up 20.0% | rising |
| 11 | Caribbean | 24 1000 t | 2023 | up 14.3% | rising |
| 13 | Russian Federation | 18 1000 t | 2023 | — | rising |
| 14 | United Kingdom of Great Britain and Northern Ireland | 16 1000 t | 2023 | — | volatile |
| 15 | Brazil | 15 1000 t | 2023 | up 400.0% | volatile |
| 15 | Poland | 15 1000 t | 2023 | — | volatile |
| 15 | United Republic of Tanzania | 15 1000 t | 2023 | up 25.0% | falling |
| 18 | Jamaica | 14 1000 t | 2023 | up 16.7% | rising |
| 19 | Iran (Islamic Republic of) | 12 1000 t | 2023 | up 71.4% | rising |
| 20 | Melanesia | 11 1000 t | 2023 | down 45.0% | falling |
| 21 | Canada | 10 1000 t | 2023 | — | volatile |
| 21 | Indonesia | 10 1000 t | 2023 | down 96.5% | volatile |
| 21 | Cambodia | 10 1000 t | 2023 | up 11.1% | flat |
| 21 | Côte d'Ivoire | 10 1000 t | 2023 | down 16.7% | falling |
| 25 | Switzerland | 8 1000 t | 2023 | up 14.3% | rising |
| 25 | Dominican Republic | 8 1000 t | 2023 | up 14.3% | rising |
| 25 | Türkiye | 8 1000 t | 2023 | up 33.3% | volatile |
| 28 | Nigeria | 7 1000 t | 2023 | down 36.4% | falling |
| 28 | Uzbekistan | 7 1000 t | 2023 | up 133.3% | rising |
| 30 | United Arab Emirates | 6 1000 t | 2023 | up 500.0% | rising |
| 30 | Ghana | 6 1000 t | 2023 | down 14.3% | falling |
| 30 | Madagascar | 6 1000 t | 2023 | down 25.0% | falling |
| 30 | Papua New Guinea | 6 1000 t | 2023 | down 62.5% | volatile |
| 34 | Saudi Arabia | 5 1000 t | 2023 | up 150.0% | volatile |
| 34 | Venezuela (Bolivarian Republic of) | 5 1000 t | 2023 | down 37.5% | flat |
| 36 | Egypt | 4 1000 t | 2023 | down 20.0% | rising |
| 36 | Iraq | 4 1000 t | 2023 | — | volatile |
| 36 | Kenya | 4 1000 t | 2023 | unchanged | rising |
| 36 | Tunisia | 4 1000 t | 2023 | unchanged | rising |
| 36 | China, Taiwan Province of | 4 1000 t | 2023 | down 33.3% | falling |
| 41 | Algeria | 3 1000 t | 2023 | up 50.0% | flat |
| 41 | Solomon Islands | 3 1000 t | 2023 | up 50.0% | rising |
| 41 | Micronesia | 3 1000 t | 2023 | up 200.0% | volatile |
| 44 | Argentina | 2 1000 t | 2023 | down 50.0% | falling |
| 44 | Guinea | 2 1000 t | 2023 | up 100.0% | rising |
| 44 | Jordan | 2 1000 t | 2023 | — | volatile |
| 44 | Oman | 2 1000 t | 2023 | up 100.0% | rising |
| 44 | El Salvador | 2 1000 t | 2023 | up 100.0% | flat |
| 44 | Serbia | 2 1000 t | 2023 | unchanged | rising |
| 44 | Vanuatu | 2 1000 t | 2023 | unchanged | flat |
| 44 | Polynesia | 2 1000 t | 2023 | up 100.0% | rising |
| 52 | Australia | 1 1000 t | 2023 | down 66.7% | volatile |
| 52 | Azerbaijan | 1 1000 t | 2023 | — | volatile |
| 52 | Bahrain | 1 1000 t | 2023 | — | flat |
| 52 | Belarus | 1 1000 t | 2023 | unchanged | falling |
| 52 | Cameroon | 1 1000 t | 2023 | unchanged | flat |
| 52 | Fiji | 1 1000 t | 2023 | unchanged | flat |
| 52 | Georgia | 1 1000 t | 2023 | — | volatile |
| 52 | Grenada | 1 1000 t | 2023 | — | volatile |
| 52 | Honduras | 1 1000 t | 2023 | — | volatile |
| 52 | Israel | 1 1000 t | 2023 | unchanged | rising |
| 52 | Kazakhstan | 1 1000 t | 2023 | down 50.0% | falling |
| 52 | Kyrgyzstan | 1 1000 t | 2023 | unchanged | rising |
| 52 | Kiribati | 1 1000 t | 2023 | unchanged | flat |
| 52 | Lithuania | 1 1000 t | 2023 | unchanged | volatile |
| 52 | Qatar | 1 1000 t | 2023 | — | flat |
| 52 | Trinidad and Tobago | 1 1000 t | 2023 | — | volatile |
| 52 | Samoa | 1 1000 t | 2023 | unchanged | volatile |
| 52 | Yemen | 1 1000 t | 2023 | unchanged | falling |
| 52 | China, Hong Kong SAR | 1 1000 t | 2023 | unchanged | flat |
| 52 | Syrian Arab Republic | 1 1000 t | 2023 | unchanged | volatile |
| 52 | Australia and New Zealand | 1 1000 t | 2023 | down 66.7% | volatile |
| 52 | Micronesia (Federated States of) | 1 1000 t | 2023 | — | flat |
| 74 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 74 | Angola | 0 1000 t | 2023 | — | volatile |
| 74 | Armenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 74 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Bahamas | 0 1000 t | 2023 | — | flat |
| 74 | Belize | 0 1000 t | 2023 | — | flat |
| 74 | Barbados | 0 1000 t | 2023 | — | flat |
| 74 | Bhutan | 0 1000 t | 2023 | — | flat |
| 74 | Botswana | 0 1000 t | 2023 | — | flat |
| 74 | Congo | 0 1000 t | 2023 | — | flat |
| 74 | Colombia | 0 1000 t | 2023 | — | flat |
| 74 | Comoros | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 74 | Cuba | 0 1000 t | 2019 | — | flat |
| 74 | Djibouti | 0 1000 t | 2023 | — | flat |
| 74 | Estonia | 0 1000 t | 2023 | — | flat |
| 74 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 74 | Gabon | 0 1000 t | 2023 | — | flat |
| 74 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 74 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Haiti | 0 1000 t | 2023 | — | flat |
| 74 | Iceland | 0 1000 t | 2023 | — | flat |
| 74 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 74 | Lebanon | 0 1000 t | 2023 | — | flat |
| 74 | Liberia | 0 1000 t | 2023 | — | flat |
| 74 | Libya | 0 1000 t | 2023 | — | volatile |
| 74 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 74 | Lesotho | 0 1000 t | 2023 | — | flat |
| 74 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 74 | Morocco | 0 1000 t | 2023 | — | volatile |
| 74 | Maldives | 0 1000 t | 2023 | — | flat |
| 74 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 74 | Malta | 0 1000 t | 2023 | — | flat |
| 74 | Myanmar | 0 1000 t | 2023 | — | flat |
| 74 | Montenegro | 0 1000 t | 2023 | — | flat |
| 74 | Mongolia | 0 1000 t | 2023 | — | flat |
| 74 | Mauritania | 0 1000 t | 2018 | down 100.0% | volatile |
| 74 | Mauritius | 0 1000 t | 2023 | — | flat |
| 74 | Malawi | 0 1000 t | 2023 | — | volatile |
| 74 | Namibia | 0 1000 t | 2023 | — | flat |
| 74 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 74 | Niger | 0 1000 t | 2023 | — | flat |
| 74 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Norway | 0 1000 t | 2023 | — | volatile |
| 74 | Nepal | 0 1000 t | 2023 | — | flat |
| 74 | Nauru | 0 1000 t | 2023 | — | flat |
| 74 | Panama | 0 1000 t | 2023 | — | flat |
| 74 | Peru | 0 1000 t | 2023 | — | flat |
| 74 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 74 | Rwanda | 0 1000 t | 2023 | — | flat |
| 74 | Senegal | 0 1000 t | 2023 | — | flat |
| 74 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 74 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 74 | Suriname | 0 1000 t | 2023 | — | volatile |
| 74 | Sweden | 0 1000 t | 2023 | — | flat |
| 74 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 74 | Seychelles | 0 1000 t | 2023 | — | flat |
| 74 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 74 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 74 | Tonga | 0 1000 t | 2023 | — | flat |
| 74 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 74 | Uganda | 0 1000 t | 2023 | — | volatile |
| 74 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 74 | Zambia | 0 1000 t | 2023 | — | flat |
| 74 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 74 | Timor-Leste | 0 1000 t | 2023 | down 100.0% | flat |
| 74 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 74 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 74 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 74 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,286 1000 t
- Asia 975 1000 t
- South-eastern Asia 343 1000 t
- Southern Asia 335 1000 t
- Eastern Asia 252 1000 t
- Net Food Importing Developing Countries (NFIDCs) 200 1000 t
- Americas 127 1000 t
- Africa 99 1000 t
- Least Developed Countries (LDCs) 97 1000 t
- Northern America 78 1000 t
- Low Income Food Deficit Countries (LIFDCs) 72 1000 t
- United States of America 68 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.