This dataset is about countries per year in Afghanistan. It has 64 rows. It features 4 columns: country, urban population living in areas where elevation is below 5 meters , and rural population.

Afghanistan Rural Land Area data was reported at 636,173.229 sq km in 2015. This records a decrease from the previous number of 637,886.976 sq km for 2000. Afghanistan Rural Land Area data is updated yearly, averaging 637,886.976 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 638,857.393 sq km in 1990 and a record low of 636,173.229 sq km in 2015. Afghanistan Rural Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.;Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.;Sum;

This dataset is about countries per year in Afghanistan. It has 64 rows. It features 4 columns: country, urban land area, and rural population.

Afghanistan Rural Population: % of Total Population data was reported at 73.067 % in 2023. This records a decrease from the previous number of 73.384 % for 2022. Afghanistan Rural Population: % of Total Population data is updated yearly, averaging 78.689 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 91.599 % in 1960 and a record low of 73.067 % in 2023. Afghanistan Rural Population: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Weighted average;

Afghanistan Rural Population Growth data was reported at 2.233 % in 2023. This records an increase from the previous number of 2.124 % for 2022. Afghanistan Rural Population Growth data is updated yearly, averaging 2.042 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 14.851 % in 1993 and a record low of -11.953 % in 1981. Afghanistan Rural Population Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Weighted average;

Afghanistan Urban Land Area data was reported at 3,993.836 sq km in 2015. This records an increase from the previous number of 2,280.089 sq km for 2000. Afghanistan Urban Land Area data is updated yearly, averaging 2,280.089 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 3,993.836 sq km in 2015 and a record low of 1,309.672 sq km in 1990. Afghanistan Urban Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Urban land area in square kilometers, based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.;Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.;Sum;

This tabular dataset provides the Afghanistan population estimation for the Persian calendar year 1395 (corresponding to the Gregorian period 21 March 2016 to 20 March 2017) disaggregated by districts and provincial centres (admin level 3), age, gender, and urban-rural settled populations. The total population of the country in 1395 is estimated to be around 29.1 million, which is inclusive of the 1.5 million nomadic population.

This dataset format was created on 15 August 2016 by the Information Management Unit (IMU) of the Office for the Coordination of Humanitarian Affairs (OCHA) Afghanistan. Since the Afghanistan Geodesy and Cartography Head Office (AGCHO) is recognized as the sole authoritative source a for administrative boundaries, the population estimates have also been matched to the administrative names and codes of the AGCHO dataset. The dataset include popluation estimates disaggregated by CSO province and district codes (including Kabul city districts), population estimates disaggreated by AGCHO district codes, and a lookup table that relates CSO, AGCHO and AIMS legacy codes. Note that the 1.5 million nomadic population is NOT included in the province and district population estimates. Estimated population disaggregated by age group and gender is calculated using proportion of the total estimated population falling under each cohort based on 2011/2012 National Risk and Vulnerability Assessment (NRVA) report. This data is only available at the province level.

This is the current version of the population estimates. The 2015/2016 projections can be found on https://data.humdata.org/dataset/estimated-population-of-afghanistan-2015-2016

Afghanistan Rural Population data was reported at 30,289,750.000 Person in 2023. This records an increase from the previous number of 29,778,377.000 Person for 2022. Afghanistan Rural Population data is updated yearly, averaging 11,560,137.000 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 30,289,750.000 Person in 2023 and a record low of 8,276,009.000 Person in 1960. Afghanistan Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Sum;

The Whole of Afghanistan Assessment (WoAA) 2024 is a multi-sectoral needs assessment conducted through in-person, household-level interviews across all provinces of Afghanistan. This dataset contains the raw data from the assessment, including all interviews conducted, along with the necessary information for the aggregation and analysis of households' sectoral and intersectoral needs across various sectors, such as health, education, nutrition, WASH, food security, and protection, among others. The data is representative of rural and urban populations, female- and male-headed households, as well as displaced population groups.

The Afghanistan Mortality Survey (AMS) 2010 was designed to measure mortality levels and causes of death, with a special focus on maternal mortality. In addition, the data obtained in the survey can be used to derive mortality trends by age and sex as well as sub-national estimates. The study also provides current data on fertility and family planning behavior and on the utilization of maternal and child health services. OBJECTIVES The specific objectives of the survey include the following: National estimates of maternal mortality; causes and determinants of mortality for adults, children, and infants by age, sex, and wealth status; and other key socioeconomic background variables; Estimates of indicators for the country as a whole, for the urban and the rural areas separately, and for each of the three survey domains of North, Central, and South, which were created by regrouping the eight geographic regions; Information on determinants of maternal health; Other demographic indicators, including life expectancy, crude birth and death rates, and fertility rates. ORGANIZATION OF THE SURVEY The AMS 2010 was carried out by the Afghan Public Health Institute (APHI) of the Ministry of Public Health (MoPH) and the Central Statistics Organization (CSO) Afghanistan. Technical assistance for the survey was provided by ICF Macro, the Indian Institute of Health Management Research (IIHMR) and the World Health Organization Regional Office for the Eastern Mediterranean (WHO/EMRO). The AMS 2010 is part of the worldwide MEASURE DHS project that assists countries in the collection of data to monitor and evaluate population, health, and nutrition programs. Financial support for the survey was received from USAID, and the United Nations Children’s Fund (UNICEF). WHO/EMRO’s contribution to the survey was supported with funds from USAID and the UK Department for International Development and the Health Metrics Network (DFID/HMN). Ethical approval for the survey was obtained from the institutional review boards at the MoPH, ICF Macro, IIHMR, and the WHO. A steering committee was formed to coordinate, oversee, advise, and make decisions on all major aspects of the survey. The steering committee comprised representatives from various ministries and key stakeholders, including MoPH, CSO, USAID, ICF Macro, IIHMR, UNICEF, UNFPA, WHO, and local and international NGOs. A technical advisory group (TAG) made up of experts in the field of mortality and health was also formed to provide technical guidance throughout the survey, including reviewing the questionnaires, the tabulation plan for this final report, the final report, and the results of the survey.

Afghanistan Urban Population data was reported at 11,165,011.000 Person in 2023. This records an increase from the previous number of 10,800,465.000 Person for 2022. Afghanistan Urban Population data is updated yearly, averaging 2,719,222.500 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 11,165,011.000 Person in 2023 and a record low of 759,034.000 Person in 1960. Afghanistan Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Sum;

Abstract

The primary objective of NRVA 2005 is to collect information at community and household level to better understand livelihoods of Kuchi (nomadic pastoralists), rural and urban households throughout the country, and to determine the types of risks and vulnerabilities they face. National and international stakeholders can benefit from the summarized findings of the report or the data set made available for in-depth analysis to develop strategies to address the short, medium, and long-term needs of the nomadic, rural and urban populations through better informed and timely policy development and intervention strategies.

The 2005 Assessment takes into account a series of recommendations made by several stakeholders during a workshop held in June 2004 when the preliminary NRVA 2003 results were discussed. The assessment includes urban households allowing a more comprehensive appreciation of the status of the country in the summer of 2005.

Geographic coverage

The survey covered 34 provinces excluding 6 districts.

Analysis unit

Community (Shura), Households, and Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 30,822 households from 34 provinces (1,735 Kuchi, 23,220 rural and 5,867 urban) was drawn excluding 6 districts that were not enumerated (as CSO household listing data was not available at the time of sampling the Livestock Census [FAO, 2003] data was used). Twelve districts were enumerated only by male surveyors in all Zabul (11 districts) and Maruf district in Kandahar due to security restrictions; however, in the se districts the food consumption part of the female questionnaire was filled out by male enumerators interviewing male respondents.

Rural and Urban Settled Households

The analytical domain, the unit at which the data are statistically representative, is at the level of 34 rural provinces; in contrast to NRVA 2003, the province of Uruzgan was split into smaller Uruzgan and Daykundi; the same happened to Parwan, which was split into Parwan and Panjsher. In addition to these 34 provincial analytical domains, there are 10 urban areas with populations larger than 10,000 households.

The survey has also collected data representative of these 10 urban domains. Thus, there are 44 settled analytical domains. Because Kuchi have been considered as one national analytical domain, there are a total of 45 analytical domains for NRVA 2005. Collecting representative data with a proportional sample at the provincial level creates a challenge because of the large variation in provincial population from the smallest population in the province of Nimroz, with only 13,941 rural households, to Hirat, with 226,650 rural households. To adjust the sampling to the available budget, the province Jawzjan with 50,900 rural households, has been used as the base analytical domain for which the sampling fraction has been determined. For those domains with populations less than Jawzjan, and where the sample fraction delivered less than 350 households, further clusters were added to ensure a minimum sample size of 350 households. The sample is therefore not self-weighting.

For those provinces or districts within provinces where the sample frame was not yet available at the time of sampling (42 districts), the Livestock Census database was used to draw a sample. On arrival at a village, the number of households was determined during the male community interview. As it was difficult for the enumerators to predict the number of households within dwellings, an additional question was asked for the total number of dwellings in the village. This number was divided by 12, to create a sampling interval for households within the community. The enumerators then selected a household each time they counted the sampling interval houses. By using this method, the sampled households were randomly and spread equally throughout the village.

Kuchi households

The household listing conducted by CSO did not effectively include the migratory Kuchi population to the date of the survey; hence there was no effective sampling frame for this population. Apparently, this lack of enumeration of the Kuchi population includes those that have recently settled. This is exactly the same population that was surveyed during winter/spring 2004 by the National Multi-Sectoral Assessment for Kuchi (NMAK), i.e. the Kuchi that is still nomadic and those that have recently settled since the onset of the last drought period. This is the best estimate of the current Kuchi population. The unit of observation for the survey was the Kuchi communities in their winter location, where one or more Kuchi communities may have been located. The sample frame for the survey was created by constructing the predicted Kuchi populations in their summer location, for which information was collected from the NMAK 2004 survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The core of NRVA 2005 is being formed by the household questionnaire. The household questionnaire consisted of the following 18 sections; the first 14 were answered by the male head of household or male respondent, and the last four by the female members of the household: - Household register and education; - Housing; - Household facilities; - Drinking water; - Assets and credit; - Livestock; - Agriculture and land tenure; - Migration, remittance and social networks; - Sources of income; - Households expenditures; - Cash for work; - Food Aid and iodized salt; - Household shocks and coping strategies; - HIV/AIDS; - Food consumption; - Maternal child health; - Children 0 – 59 months; - HIV/AIDS and literacy test.

The total number of questions that were asked to the sampled households exceeded 260 but not all questions were answered because some of them were eliminated based on the responses provided (with skipping rules). The household is regarded as the unit of analysis. In Afghanistan there is a need to address the questions to males and females depending on their nature. In every sampled community 12 households have been interviewed. On average the time required to answer the household questionnaire was less than two hours. Besides the household questionnaire, information was gathered at community level. Therefore, two community questionnaires were designed – one male and one female. These two questionnaires addressed the following topics:

Male shura questionnaire: - Community information; - Access to infrastructure; - Markets access; - Health access; - Education; - Community roles and governance; - Programme activities; - Community priorities; - Water table.

Female shura questionnaire: - Health access; - Community bodies and governance; - Community priorities.

Cleaning operations

Automated data entry

Teleform Enterprise version 8 (Cardiff software, donated by WFP) was used throughout the process to scan the NRVA 2005 Teleform questionnaires filled in the field. Teleform is an electronic pre-programmed method of gathering data (optical readable software), often used for its speed and accuracy in large surveys and censuses. A scanner capable of processing 60 sheets per minute was used. Unlike NRVA 2003, where Teleform was only used for the shura and wealth group data after being transcribed by VAM and key enumerator staff into scan able formats; finally the information was scanned into a Microsoft Access database using Teleform.

The NRVA 2005 was completely designed in Teleform; then the enumerators filled in the pre-designed questionnaire sheets and the data were directly scanned into the Access database. Scanning 1.3 million data sheets took two to three months more than anticipated; the process was finally finished in February 2006. These delays were partially due to the quality of enumeration of questionnaires, computer hardware that was not powerful enough to sustain the processing required (alleviated by the loan of a high-speed server from UNOPS) and the absence of a stable electricity supply (alleviated by the loan of the power generator from WFP).

Once the data were scanned, the programme logically checked if the number of responses per question was not exceeded. Unfortunately, within NRVA 2005 a decision was taken to insert the number of the response within the answer circles. This resulted in some false positive answers as a high percentage of the answer circles were already coloured. Only when a true answer was also indicated (giving two responses) the programme stopped asking for verification, if there was no response then the false positive was accepted and these responses were taken out during normal cleaning practices. Once a questionnaire was validated, the image file was deleted and the data was written to the Access database. Descriptive statistics were estimated with SPSS and Genstat. Cluster analysis using ADATTI software was used for food security profiling. Provincial statistics produced are included in the Annex; those for national, Kuchi, rural and urban categories are included in the main body of the document.

Data appraisal

Data constraints and limitations

In spite of the time spent on the design of the questionnaire and its implementation in NRVA 2005, the data gathered have the following limitations: - Seasonality. Food security assessment and household perceptions are only valid for the summer season, rather than for the whole year. - Limited data on non-food consumption. Due to the multilateral nature of the assessment most of the non-food consumptions (except communication costs) have been included as groups to avoid an exhaustive questionnaire with a strong risk of lowering the quality of data. - Income.

The Whole of Afghanistan Assessment (WoAA) 2024 is a multi-sectoral needs assessment conducted through in-person, household-level interviews across all provinces of Afghanistan. This dataset analyzes households' sectoral and intersectoral needs across various sectors, including health, education, nutrition, WASH, food security, and protection, among others. The results are representative of rural and urban populations , female- and male-headed households , as well as displaced population groups.

Abstract

Since its inception in the mid-1990s, the Multiple Indicator Cluster Surveys programme, known as MICS, has become the largest source of statistically sound and internationally comparable data on children and women worldwide. In countries as diverse as Bangladesh, Thailand, Fiji, Qatar, Cote d’Ivoire, Turkmenistan and Argentina, trained fieldwork teams conduct face-to-face interviews with household members on a variety of topics – focusing mainly on those issues that directly affect the lives of children and women. MICS is an integral part of plans and policies of many governments around the world, and a major data source for more than 30 Sustainable Development Goals (SDGs) indicators. The MICS programme continues to evolve with new methodologies and initiatives, including MICS Plus, MICS Link, MICS GIS and the MICS Tabulator.

Geographic coverage

Afghanistan The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. Subnational surveys, covering specific population groups (such as Palestinians in Lebanon) or specific geographical areas (such as selected regions of East in Afghanistan) within countries are also conducted.

Analysis unit

Household, Individual

Sampling procedure

Sample sizes vary greatly from one survey to the other, currently averaging around 12,000 households (for national surveys).

The sample for the Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for areas of residence, and for geographical locations, such as regions, governorates, or districts. A multi-stage, stratified cluster sampling approach was typickly used for the selection of the survey sample. MICS6 surveys are not self-weighting. For reporting national level results, sample weights were used. A more detailed description of the sample design can be found in Appendix A of Final Report.

Mode of data collection

Face-to-face [f2f]

Abstract

Afghanistan hosts a protracted population of Pakistani refugees, who fled North Waziristan Agency in 2014 as a result of a joint military offensive by Pakistani government forces against non-state armed groups. As of May 2017, UNHCR has biometrically registered over 50,000 refugees in Khost province and 36,000 refugees in Paktika province, where access remains a challenge. Over 16,000 of these refugees receive shelter and essential services in the Gulan camp in Khost province, while most of the others live among the host population in various urban and rural locations.

To better understand the needs of the refugees and the host communities, UNHCR and WFP agreed to conduct a joint assessment of Pakistani refugees in Khost and Paktika. The data collection commenced in May 2017 and covered 2,638 refugee households (2,198 in Khost and 440 in Paktika).

Geographic coverage

Areas hosting Pakistani refugees in Afghanistan's Khost and Paktika provinces. This includes Gulan refugee camp as well as various non-camp sites, spread across 10 districts.

Analysis unit

Household and individual

Universe

All Pakistani refugees living in Afghanistan's Khost and Paktika provinces.

UNHCR PPG: -

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey's objective was to deliver representative data of all Pakistani refugees living in Afghanistan's Khost and Paktika provinces. The total population of Pakistani refugees in these provinces at the time of the survey was estimated at around 18,000 households.

For this survey a stratified, two-stage (i.e. clustered) sample design was applied. The 10 refugee-hosting districts of Khost and Paktika were considered sampling strata, but within these the refugee-dense locations of Gulan camp and Lakan (in Maton district) were considered separate strata, resulting in 12 sampling strata overall. Within each of these strata, first a selection of villages was drawn with probability-proportional-to-size, then second a selection of households was drawn from UNHCR's registration database.

The total sample size was 2,638 refugee households.

NB: The original data collection also included a small number of households from the neighboring host communities; however, these observations were dropped from the public-release version of the dataset.

Sampling deviation

None.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The dataset presented here has undergone light checking, cleaning, and restructuring (data may still contain errors) as well as anonymization (includes removal of direct identifiers and sensitive variables and grouping values of select variables). Moreover, households interviewed from host communities were removed.

Response rate

Information unavailable.

Afghanistan Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data was reported at 0.000 % in 2015. This stayed constant from the previous number of 0.000 % for 2000. Afghanistan Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data is updated yearly, averaging 0.000 % from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 0.000 % in 2015 and a record low of 0.000 % in 2015. Afghanistan Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Urban population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.;Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. 2021. Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/d1x1-d702.;Weighted average;

Collection of exposure datasets for risk assessment purpose in Afghanistan. Includes: - Location, area and USD value of rainfed and irrigated agricultural crops. - Total exposure value of buildings for different occupancy types: urban and rural structures, residential, non-residential, and industrial area. Values expressed as replacement cost (USD), area (m2), or number of elements (count). - Location, count and USD value (when available) for the following infrastructures in Afghanistan: airports, bridges, dams, health centers, hospitals, power plants, roads, schools and universities. - Population count and GDP value in USD for three macrosectors (Industry, Agriculture and Services) in Afghanistan.

Abstract

The Global Consumption Database (GCD) contains information on consumption patterns at the national level, by urban/rural area, and by income level (4 categories: lowest, low, middle, higher with thresholds based on a global income distribution), for 92 low and middle-income countries, as of 2010. The data were extracted from national household surveys. The consumption is presented by category of products and services of the International Comparison Program (ICP) 2005, which mostly corresponds to COICOP. For three countries, sub-national data are also available (Brazil, India, and South Africa). Data on population estimates are also included.

       The data file can be used for the production of the following tables (by urban/rural and income class/consumption segment):
       - Sample Size by Country, Area and Consumption Segment (Number of Households)
       - Population 2010 by Country, Area and Consumption Segment
       - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population
       - Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population
       - Population 2010 by Country, Age Group, Sex and Consumption Segment
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in Local Currency (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in $PPP (Million)
       - Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in US$ (Million)
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$
       - Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP
       - Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent)
       - Consumption Shares 2010 by Country, Category of Products/Services, Area and Consumption Segment (Percent)
       - Consumption Shares 2010 by Country, Product/Service, Area and Consumption Segment (Percent)
       - Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)

Geographic coverage notes

For all countries, estimates are provided at the national level and at the urban/rural levels. For Brazil, India, and South Africa, data are also provided at the sub-national level (admin 1): - Brazil: ACR, Alagoas, Amapa, Amazonas, Bahia, Ceara, Distrito Federal, Espirito Santo, Goias, Maranhao, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Para, Paraiba, Parana, Pernambuco, Piaji, Rio de Janeiro, Rio Grande do Norte, Rio Grande do Sul, Rondonia, Roraima, Santa Catarina, Sao Paolo, Sergipe, Tocatins - India: Andaman and Nicobar Islands, Andhra Pradesh, Arinachal Pradesh, Assam, Bihar, Chandigarh, Chattisgarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Lakshadweep, Madya Pradesh, Maharastra, Manipur, Meghalaya, Mizoram, Nagaland, Orissa, Pondicherry, Punjab, Rajasthan, Sikkim, Tamil Nadu, Tripura, Uttar Pradesh, Uttaranchal, West Bengal - South Africa: Eastern Cape, Free State, Gauteng, Kwazulu Natal, Limpopo, Mpulamanga, Northern Cape, North West, Western Cape

Kind of data

Data derived from survey microdata