Cost of food in Canada increased 1.30 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Canada Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset contains Food Prices data for Nigeria, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

Food Price Index in World increased to 127.10 Index Points in February from 125.10 Index Points in January of 2025. This dataset includes a chart with historical data for World Food Price Index.

Food Prices for Nutrition provides indicators on the cost and affordability of a healthy diet (CoAHD) in each country, showing the population’s physical and economic access to sufficient quantities of locally available items for an active and healthy life. It also provides indicators on the cost and affordability of an energy-sufficient diet and of a nutrient-adequate diet. These indicators are explained in detail in the Food Prices for Nutrition DataHub here: https://www.worldbank.org/foodpricesfornutrition.

The database version Food Prices for Nutrition 1.0 contains indicators that were estimated in July 2022, based on 2017 global food retail price data from the International Comparison Program (ICP), when relevant affordability indicators were calculated based on the available Poverty and Inequality Platform (PIP) data from the World Bank expressed in 2011 purchasing power parity terms (PPP). These include indicators measuring the ratio between diet costs and international food poverty lines and indicators measuring the share and volume of the population unable to afford each diet, based on income distributions observed in each country. Countries' income classifications at the aggregate reporting level follow the calendar year of 2020 (the fiscal year of 2022 of the World Bank). The Cost and Affordability of a Healthy Diet indicators reported in the United Nations' State of Food Security and Nutrition in the World 2022 correspond to those in version 1.0.

The database version Food Prices for Nutrition 1.1 updates these aforementioned affordability indicators using the latest international poverty lines and PIP data expressed in 2017 PPP-based dollars.

The database version Food Prices for Nutrition 2.0, estimated in July 2023, uses the latest PIP data expressed in 2017 PPP-based dollars. Countries' income classifications at the aggregate reporting level follow the calendar year of 2021 (the fiscal year of 2023 of the World Bank). The Cost and Affordability of a Healthy Diet indicators reported in the United Nations' State of Food Security and Nutrition in the World 2023 correspond to those in version 2.0.The database version Food Prices for Nutrition 2.1 updates the affordability indicators using the latest PIP data expressed in 2017 PPP-based dollars and population data from the WDI updated in the fall of 2023.

The database version Food Prices for Nutrition 3.0, estimated in July 2024, uses the 2021 global food retail price data from the ICP and updates the methodology of calculating the affordability indicators, including indicators measuring the ratio between diet costs and international food poverty lines and indicators measuring the share and volume of the population unable to afford each diet, and they are based on the latest PIP data expressed in 2017 PPP-based dollars. For the first time, estimates for the prevalence and number of people unable to afford a healthy diet were imputed for countries with missing information based on their regional and global aggregates. Countries' income classifications at the aggregate reporting level follow the calendar year of 2022 standard (the fiscal year of 2024 of the World Bank). The Cost and Affordability of a Healthy Diet indicators reported in the United Nations' State of Food Security and Nutrition in the World 2024 correspond to those in version 3.0.

The database version Food Prices for Nutrition 3.1 updates the affordability indicators using the latest PIP data expressed in 2017 PPP-based dollars and population data from the World Population Prospect by the United Nations Department of Economic and Social Affairs (UN DESA).

Monthly average retail prices for selected products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

Cost of food in China decreased 3.30 percent in February of 2025 over the same month in the previous year. This dataset provides - China Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Cost of food in Netherlands increased 4.30 percent in February of 2025 over the same month in the previous year. This dataset provides - Netherlands Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Cost of food in India increased 3.75 percent in February of 2025 over the same month in the previous year. This dataset provides - India Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Cost of food in Georgia increased 3.70 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Georgia Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cost of food in Japan increased 7.60 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Japan Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cost of food in Egypt increased 20.80 percent in January of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Egypt Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cost of food in European Union increased 2.90 percent in February of 2025 over the same month in the previous year. This dataset provides - European Union Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Monthly indexes and percentage changes for major components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

Cost of food in Pakistan decreased 4.15 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Pakistan Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Abstract

In this report, we present data from the emergency response survey conducted via telephone among households in three conflict affected regions of Nigeria, North East, North Central and South South between August-September 2017. This round is the second round of telephone data collected from a subsample of households in the Nigeria General Household Survey (GHS). The first round collected data on conflict exposure.

The purpose of this second round of data collection was to understand food insecurity in conflict affected regions. Armed conflict can have a detrimental effect on food security. This might be due to for example reduced agricultural production, or price increases due to malfunctioning markets. Food insecurity might be permanent, such that a household living below the poverty line has a constant struggle to acquire food from the market or produce food for their own use. In situations such as armed conflict, also better endowed households might be temporarily food insecure. In this report, we find that food insecurity is a major concern in all the three regions studied:

· The mean household in all the three regions is “highly food insecure” · North East of Nigeria is the most food insecure of the three regions · Reducing meals or portion size is the most important coping strategy in all three regions · Food prices are the most important source of food insecurity in all three regions · A large majority of households rely on the market as the main source of food in all regions. Price concerns should therefore be taken very seriously by policy makers. · Households in all three regions do not report there being an inadequate supply of food in the market.

Geographic coverage

Zones States Local Government Areas (LGAs) Households

Analysis unit

Individuals, Households and Communities

Universe

The Survey covered all household members. The questionnaire was administered to only one respondent per household - most often a male household head.

Kind of data

Sample survey data [ssd]

Sampling procedure

The food security survey was a telephone based survey conducted between August 15th and September 8th 2017. The interview was the second round of a telephone survey using a sub-set of the sample of GHS (General Household Survey) households. The first round of the telephone interview was administered during spring 2017 with 717 completed interviews with the following geographical distribution: 175 interviews in the North East, 276 in North Central and 266 in South South. The first round was focused on conflict exposure, while the second round discussed in this report focused on food insecurity in conflict affected regions.

In the three conflict affected geographical zones comprising of 16 states of Nigeria, households from LGS's that had high conflict exposure were oversampled chosen for a pilot sample, conducted before the telephone surveys. These LGS's were chosen based on the following criteria: The oversampled LGS's needed to have over 10 conflict events during 2012-14 recorded in the Armed Conflict Location & Event Data Project (ACLED) database.

The first round of the telephone survey (which took place after the pilot) first attempted to reach 742 households from the GHS panel, of which 529 could be reached and interviewed. The rest did not have phone numbers or functioning phone numbers (only 2.7 percent refused to answer). In order to increase the sample size to a level that was considered adequate for the survey, an additional 288 replacement households were included in the sample also from the GHS panel. Out of these replacement households 188 could be interviewed. Therefore altogether 1030 households were attempted to be reached, with a final sample size of 717 completed interviews.

Conflict affected areas were oversampled in order to have a large enough sample of households that in fact experienced conflict events in order to shed light on the type of events that have happened. A random sample of the zones might have given too small sample of conflict affected households and therefore restricted the analysis of the various types of conflict events. Due to the oversampling however, the sample drawn was not representative at the level of the geographical zone, as is the case in the GHS. Therefore in the analysis we use sampling weights that adjust for the propensity of being in a conflict affected LGA in order to ensure that the sample is representative at the level of the geographical zone.

During the second round of the survey 582 of the 717 households were re-interviewed on food security related issues (only the 717 were attempted to be reached). Of the 582 households 147 in the North East, 219 in North Central, and 216 in South South were interviewed. The attrition rates in our sample from round one to round two are hence 16 percent, 21 percent, and 19 percent for North East, North Central and South South, respectively. The attrition from the conflict survey round was mostly due to not being able to reach the respondents possibly due to non-functioning phone numbers. Only 3 percent of respondents refused to answer.

Similar telephone-based surveys are being conducted in six countries in Sub-Saharan Africa under the World Bank project "Listening to Africa". As a comparison, a mobile phone survey in Tanzania (see Croke et al. 2012 for details), had a high drop-out rate between the very first rounds from 550 to 458 respondents, but very low attrition for the subsequent rounds for the 458 respondents, who could reliably be reached by a mobile phone. In light of this reference point and also considering the fact that the households interviewed live in conflict affected regions, our attrition rates seem to be within reasonable limits.

Sampling deviation

No Deviation

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire is divided into 9 sections including a household roster. Information on food insecurity (the coping strategy index, CSI), food and market access, water quality, employment, income, employment and assets was collected.

Cleaning operations

Data was analyzed using descriptive statistics in Stata 15. All data analysis was tracked using comprehensive do files to ensure reproducibility. All statistics presented in this report have been adjusted with probability weights, when possible, to be representative at the level of the geopolitical zone. Demographics for each geopolitical zone were analyzed based on the complete GHS 2016 dataset.

Response rate

The first round of the telephone survey (which took place after the pilot), first attempted to reach 742 households from the GHS panel, of which 529 could be reached and interviewed. The rest did not have phone numbers or functioning phone numbers (only 2.7 per cent refused to answer). In order to increase the sample size to a level that was considered adequate for the survey, an additional 288 replacement households were included in the sample also from the GHS panel. Out of these replacement households 188 could be interviewed. Therefore altogether 1030 households were attempted to be reached, with a final sample size of 717 completed interviews. The response rate is 96%

Sampling error estimates

No Sampling Error

Data appraisal

Limitations Recall Bias In the pilot data collection, respondents were asked to report on conflict events that had taken place in their family and their community over the last six years. This extremely long recall period must be considered when drawing inferences from the data. People are likely to under-report less severe (and therefore less memorable) events, particularly those that happened to community members in larger communities. Respondents are also more likely to recall events that happened to family members than those that happened to community members. Other biases may also be at play - for example, those who have been most highly affected by conflict over the last six years may have moved to another community. These factors demonstrate the importance of implementing a regular data collection schedule, which would allow far more accurate data to be collected. Sampling Bias The GHS is a panel survey taking place over multiple rounds through a period of time. Therefore, households that are more mobile or households that are nomadic are less likely to be represented in this sample. This may be particularly relevant in circumstances where nomadic groups are named as perpetrators of conflict events. Power Dynamics There are some disadvantages to the phone system, and for this reason it should be supplemented by additional types of data collection wherever possible. In a mobile phone survey, the respondent is the person who owns a mobile phone. In many areas, particularly those highly affected by poverty and those located in rural areas, only one family member owns a mobile phone. This is generally the household head, who is most likely male. Furthermore, in many of these communities, women are not allowed to have access to mobile phones and are forbidden from speaking to outsiders, which can prohibit mobile phone-based data collection. Gender Dynamics The questionnaire was administered to only one respondent per household - most often a male household head. This means that crimes that carry stigma, especially sexual violence, are less likely to be reported. In this dataset, no sexual assault was reported despite data collected elsewhere that indicate that rape was used as a weapon by Boko Haram

Cost of food in Argentina increased 147.10 percent in November of 2024 over the same month in the previous year. This dataset provides - Argentina Food Inflation- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Cost of food in Malaysia increased 2.50 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Malaysia Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cost of food in Turkey increased 35.11 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Turkey Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.