6 datasets found
  1. Population and Housing Census 2006 - Nigeria

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    Updated Mar 29, 2019
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    National Population Commission (2019). Population and Housing Census 2006 - Nigeria [Dataset]. https://catalog.ihsn.org/catalog/3340
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Population Commissionhttps://nationalpopulation.gov.ng/
    Time period covered
    2006
    Area covered
    Nigeria
    Description

    Abstract

    The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA.

    Geographic coverage

    National

    Analysis unit

    Individuals Households

    Kind of data

    Census/enumeration data [cen]

    Mode of data collection

    Face-to-face [f2f]

    Cleaning operations

    Census 2006 Processing: The Technology and Methodology:-

    Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method.

    OMR/OCR/ICR Technology

    Definition of terms

    • OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents.
    • OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires.
    • ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents.

    Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs.

    (a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC.

    (b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch.

    (c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms.

    The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system.

    Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving.

    Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation.

    Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja.

    Data appraisal

    Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables.

    Activities of the Data Validation unit (DVU):-

    Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

  2. w

    Nigeria - Demographic and Health Survey 1990 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Nigeria - Demographic and Health Survey 1990 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/nigeria-demographic-and-health-survey-1990
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The 1990 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey conducted by the Federal Office of Statistics with the aim of gathering reliable information on fertility, family planning, infant and child mortality, maternal care, vaccination status, breastfeeding, and nutrition. Data collection took place two years after implementation of the National Policy on Population and addresses issues raised by that policy. Fieldwork for the NDHS was conducted in two phases: from April to July 1990 in the southern states and from July to October 1990 in the northern states. Interviewers collected information on the reproductive histories of 8,781 women age 15-49 years and on the health of their 8,113 children under the age of five years. OBJECTIVES The Nigeria Demographic and Health Survey (NDHS) is a national sample survey of women of reproductive age designed to collect data on socioeconomic characteristics, marriage patterns, history of child bearing, breastfeeding, use of contraception, immunisation of children, accessibility to health and family planning services, treatment of children during episodes of illness, and the nutritional status of children. The primary objectives of the NDHS are: (i) To collect data for the evaluation of family planning and health programmes; (ii) To assess the demographic situation in Nigeria; and (iii) To support dissemination and utilisation of the results in planning and managing family planning and health programmes. MAIN RESULTS According to the NDHS, fertility remains high in Nigeria; at current fertility levels, Nigerian women will have an average of 6 children by the end of their reproductive years. The total fertility rate may actually be higher than 6.0, due to underestimation of births. In a 1981/82 survey, the total fertility rate was estimated to be 5.9 children per woman. One reason for the high level of fertility is that use of contraception is limited. Only 6 percent of married women currently use a contraceptive method (3.5 percent use a modem method, and 2.5 percent use a traditional method). These levels, while low, reflect an increase over the past decade: ten years ago just 1 percent of Nigerian women were using a modem family planning method. Periodic abstinence (rhythm method), the pill, IUD, and injection are the most popular methods among married couples: each is used by about 1 percent of currently married women. Knowledge of contraception remains low, with less than half of all women age 15-49 knowing of any method. Certain groups of women are far more likely to use contraception than others. For example, urban women are four times more likely to be using a contraceptive method (15 percent) than rural women (4 percent). Women in the Southwest, those with more education, and those with five or more children are also more likely to be using contraception. Levels of fertility and contraceptive use are not likely to change until there is a drop in desired family size and until the idea of reproductive choice is more widely accepted. At present, the average ideal family size is essentially the same as the total fertility rate: six children per woman. Thus, the vast majority of births are wanted. The desire for childbearing is strong: half of women with five children say that they want to have another child. Another factor leading to high fertility is the early age at marriage and childbearing in Nigeria. Half of all women are married by age 17 and half have become mothers by age 20. More than a quarter of teenagers (women age 15-19 years) either are pregnant or already have children. National statistics mask dramatic variations in fertility and family planning between urban and rural areas, among different regions of the country, and by women's educational attainment. Women who are from urban areas or live in the South and those who are better educated want and have fewer children than other women and are more likely to know of and use modem contraception. For example, women in the South are likely to marry and begin childbearing several years later than women in the North. In the North, women continue to follow the traditional pattern and marry early, at a median age of 15, while in the South, women are marrying at a median age of 19 or 20. Teenagers in the North have births at twice the rate of those in the South: 20 births per 1130 women age 15-19 in the North compared to 10 birdas per 100 women in the South. Nearly half of teens in the North have already begun childbearing, versus 14 percent in South. This results in substantially lower total fertility rates in the South: women in the South have, on average, one child less than women in the North (5.5 versus 6.6). The survey also provides information related to maternal and child health. The data indicate that nearly 1 in 5 children dies before their fifth birthday. Of every 1,000 babies born, 87 die during their first year of life (infant mortality rate). There has been little improvement in infant and child mortality during the past 15 years. Mortality is higher in rural than urban areas and higher in the North than in the South. Undemutrition may be a factor contributing to childhood mortality levels: NDHS data show that 43 percent of the children under five are chronically undemourished. These problems are more severe in rural areas and in the North. Preventive and curative health services have yet to reach many women and children. Mothers receive no antenatal care for one-third of births and over 60 percent of all babies arc born at home. Only one-third of births are assisted by doctors, trained nurses or midwives. A third of the infants are never vaccinated, and only 30 percent are fully immunised against childhood diseases. When they are ill, most young children go untreated. For example, only about one-third of children with diarrhoea were given oral rehydration therapy. Women and children living in rural areas and in the North are much less likely than others to benefit from health services. Almost four times as many births in the North are unassisted as in the South, and only one-third as many children complete their polio and DPT vaccinations. Programmes to educate women about the need for antenatal care, immunisation, and proper treatment for sick children should perhaps be aimed at mothers in these areas, Mothers everywhere need to learn about the proper time to introduce various supplementary foods to breastfeeding babies. Nearly all babies are breastfed, however, almost all breastfeeding infants are given water, formula, or other supplements within the first two months of life, which both jeopardises their nutritional status and increases the risk of infection.

  3. Malaria Indicator Survey 2015 - Nigeria

    • microdata.worldbank.org
    • catalog.ihsn.org
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    Updated Jun 5, 2017
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    National Malaria Elimination Programme (NMEP) (2017). Malaria Indicator Survey 2015 - Nigeria [Dataset]. https://microdata.worldbank.org/index.php/catalog/2727
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    Dataset updated
    Jun 5, 2017
    Dataset provided by
    National Malaria Eradication Program
    National Bureau of Statistics (NBS)
    National Population Commission (NPopC)
    Time period covered
    2015
    Area covered
    Nigeria
    Description

    Abstract

    The primary objectives of the 2015 NMIS are to provide information on malaria indicators and malaria prevalence, both at the national level and in each of the country’s 36 states and the Federal Capital Territory. The secondary objectives are to improve knowledge regarding best practices in implementing the survey and enhance the skills of survey-implementing partners in the areas of survey design, training, logistics, data collection monitoring, data processing, laboratory testing, analysis, report drafting, and data dissemination.

    Other key objectives of the 2015 Nigeria Malaria Indicator Survey are to: • Measure the extent of ownership and use of mosquito nets • Assess the coverage of preventive treatment programmes for pregnant women • Identify practices used to treat malaria among children under age 5 and the use of specific antimalarial medications • Measure the prevalence of malaria and anaemia among children age 6-59 months • Assess knowledge, attitudes, and practices regarding malaria in the general population

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Women age 15-49
    • Children age 0-5

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for the 2015 NMIS was designed to provide most of the survey indicators for the country as a whole, for urban and rural areas separately, and for each of the country's six geopolitical zones. Some of these indicators are provided for each of the 36 states and the FCT. Nigeria's geopolitical zones are as follows: 1. North Central: Benue, Kogi, Kwara, Nasarawa, Niger, Plateau, and FCT 2. North East: Adamawa, Bauchi, Borno,1 Gombe, Taraba, and Yobe 3. North West: Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara 4. South East: Abia, Anambra, Ebonyi, Enugu, and Imo 5. South South: Akwa Ibom, Bayelsa, Cross River, Delta, Edo, and Rivers 6. South West: Ekiti, Lagos, Ogun, Ondo, Osun, and Oyo

    The sampling frame for the 2015 NMIS was the 2006 National Population and Housing Census (NPHC) of the Federal Republic of Nigeria, conducted by the National Population Commission. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into localities. In addition to these administrative units, during the 2006 census, each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2015 NMIS, was defined on the basis of EAs from the 2006 EA census frame.

    A two-stage sampling strategy was adopted for the 2015 NMIS. In the first stage, nine clusters (EAs) were selected from each state, including the FCT. The sample selection was done in such a way that it was representative of each state. The result was a total of 333 clusters throughout the country, 138 in urban areas and 195 in rural areas.

    A complete listing of households was conducted, and a mapping exercise for each cluster was carried out in June and July 2015, with the resulting lists of households serving as the sampling frame for the selection of households in the second stage. All regular households were listed. The NPopC listing enumerators used global positioning system (GPS) receivers to record the coordinates of the 2015 NMIS sample clusters.

    In the second stage of the selection process, 25 households were selected in each cluster by equal probability systematic sampling. All women age 15-49 who were either permanent residents of the households in the 2015 NMIS sample or visitors present in the households on the night before the survey were eligible to be interviewed. In addition, all children age 6-59 months were eligible to be tested for malaria and anaemia. This sample size was selected to guarantee that key survey indicators could be produced for each of the country's six geopolitical zones, with approximately 1,338 women in each zone expected to complete interviews. In order to produce some of the survey indicators at the state level for each of the 36 states and the FCT, interviews were expected to be completed with approximately 217 women per state.

    For further details of the sample design, see Appendix A of the final report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Three questionnaires were used in the survey: the Household Questionnaire; the Woman’s Questionnaire, which was administered to all women age 15-49 in the selected households; and the Biomarker Questionnaire.

    The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. Data on age and sex were used to identify women who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership and use of mosquito nets.

    The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following main topics: • Background characteristics (e.g., education, media exposure) • Birth history and childhood mortality • Antenatal care and malaria prevention for most recent birth and pregnancy • Malaria prevention and treatment • Knowledge about malaria (symptoms, causes, prevention, drugs used in treatment)

    The Biomarker Questionnaire was used to record the results of the anaemia and malaria testing as well as the signatures of the fieldworker and the respondent who gave consent.

    Cleaning operations

    Data for the 2015 NMIS were collected through questionnaires programmed onto tablet computers. The computers were programmed by an ICF data processing specialist and loaded with the Household, and Woman’s Questionnaires in English and the three major local languages. The tablets were Bluetooth-enabled to facilitate electronic transfer of files, for example, transfer of data from the Household Questionnaires among survey team members and transfer of completed questionnaires to the team supervisor’s tablets. The field supervisors transferred data on a daily basis to the central data processing office using the Internet. To facilitate communication and monitoring, each field worker was assigned a unique identification number.

    Two data management officers were positioned at the central data office to monitor and supervise daily submission of completed interview data from teams. They also provided technical assistance on the functioning of the tablets and constantly liaised with the central coordination and ICF teams to manage data transfers from the field teams to the central office. They made intermittent visits to assist field teams with serious situations that could not be resolved at the central office, either to replace or fix the tablets.

    The Census Survey Processing (CSPro) software program was used for data editing, weighting, cleaning, and tabulation. In the NPopC central office, data received from the supervisors’ tablets were registered and checked for any inconsistencies and outliers. Data editing and cleaning included structure and internal consistency checks to ensure completeness of work in the field. Any anomalies were communicated to the respective team through field coordinators and the team supervisor. Corrected results were re-sent to the central processing unit. Data processing was completed during the first week of December 2015.

    Response rate

    A total of 8,148 households were selected for the sample. This does not include six rural clusters in Borno State and one cluster in Plateau State that were dropped from the sample due to security concerns. Of the households selected, 7,841 were occupied. Of the occupied households, 7,745 were successfully interviewed, yielding a response rate of 99 percent. The response rate among households in rural areas was slightly higher (99 percent) than that among households in urban areas (98 percent). No clusters in rural areas of Borno State were visited; thus, estimates for national indicators and indicators in the North East Zone do not include rural Borno State.

    In the interviewed households, 8,106 women were identified as eligible for individual interviews. Interviews were completed with 8,034 women, yielding a response rate of 99 percent. The response rate among eligible women did not differ by residence (urban or rural).

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2015 Nigeria Malaria Indicator Survey (NMIS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2015 NMIS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample

  4. f

    Additional file 4 of Demographic dividend-favorable policy environment in...

    • springernature.figshare.com
    xlsx
    Updated Jun 6, 2023
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    Xiaomeng Chen; Neia Prata Menezes; Jean Christophe Rusatira; Carolina Cardona; Mojisola Odeku; Deanna Kioko; Jessica Castro; Charity Ibeawuchi; Joel Silas Lincoln; Deo Ng’wanansabi; Jacob Macha; Abubakar Msemo; Nazir Yusuph; Jose G. Rimon (2023). Additional file 4 of Demographic dividend-favorable policy environment in two pre-dividend African nations: review of national policies and prospects for policy amendments in Nigeria and Tanzania [Dataset]. http://doi.org/10.6084/m9.figshare.23298836.v1
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    xlsxAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    figshare
    Authors
    Xiaomeng Chen; Neia Prata Menezes; Jean Christophe Rusatira; Carolina Cardona; Mojisola Odeku; Deanna Kioko; Jessica Castro; Charity Ibeawuchi; Joel Silas Lincoln; Deo Ng’wanansabi; Jacob Macha; Abubakar Msemo; Nazir Yusuph; Jose G. Rimon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Tanzania, Africa, Nigeria
    Description

    Additional file 4. Review of national policy documents from Tanzania.

  5. Malaria Indicator Survey 2010 - Nigeria

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 5, 2017
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    National Population Commission (2017). Malaria Indicator Survey 2010 - Nigeria [Dataset]. https://microdata.worldbank.org/index.php/catalog/1966
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    Dataset updated
    Jun 5, 2017
    Dataset provided by
    National Malaria Eradication Program
    National Population Commission
    Time period covered
    2010
    Area covered
    Nigeria
    Description

    Abstract

    The 2010 Nigeria Malaria Indicator Survey (2010 NMIS) was implemented by the National Population Commission (NPC) and the National Malaria Control Programme (NMCP). ICF International provided technical assistance through the MEASURE DHS programme, a project funded by the United States Agency for International Development (USAID), which provides support and technical assistance in the implementation of population and health surveys in countries worldwide. It was carried out from October to December 2010 on a nationally representative sample of more than 6,000 households. All women age 15-49 in the selected households were eligible for individual interviews. During the interviews, they were asked questions about malaria prevention during pregnancy and the treatment of fever among their children. In addition, the survey included testing for anaemia and malaria among children age 6-59 months using finger (or heel) prick blood samples. Test results were available immediately and were provided to the children’s parents or guardians. Thick blood smears and thin blood films were also made in the field and transported to the Department of Medical Microbiology and Parasitology at the College of Medicine, University of Lagos. Microscopy was performed to determine the presence of malaria parasites and to identify the parasite species. Slide validation was carried out by the University of Calabar Teaching Hospital in Calabar.

    The 2009-2013 National Strategic Plan for Malaria Control in Nigeria aims to massively scale up malaria control interventions in parts of the country. The 2010 Nigeria Malaria Indicator Survey (NMIS) was, therefore, designed to measure progress toward achieving the goals and targets of this strategic plan by providing data on key malaria indicators, including ownership and use of bed nets, diagnosis and prompt treatment of malaria using artemisinin-based therapy (ACT), indoor residual spraying, and behaviour change communication.

    The following are the specific objectives of the 2010 NMIS: - To measure the extent of ownership and use of mosquito bed nets - To assess the coverage of intermittent and preventive treatment programmes for pregnant women - To identify practices used to treat malaria among children under age 5 and the use of specific antimalarial medications - To measure the prevalence of malaria and anaemia among children age 6-59 months - To determine the species of plasmodium parasite most prevalent in Nigeria - To assess knowledge, attitudes, and practices regarding malaria in the general population

    Geographic coverage

    National

    Analysis unit

    • Household,
    • Individual.

    Universe

    The survey covered all de jure household members (usual residents), all women aged between 15-49 years, and all children age 6-59 months living in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The 2010 Nigeria Malaria Indicator Survey (NMIS) called for a nationally representative sample of about 6,000 households. The survey is designed to provide information on key malaria-related indicators including mosquito net ownership and use, coverage of preventive treatment for pregnant women, treatment of childhood fever, and the prevalence of anaemia and malaria among children age 6-59 months. The sample for the 2010 NMIS was designed to provide most of these indicators for the country as a whole, for urban and rural areas separately, and for each of the six zones formed by grouping the 36 states and the Federal Capital Territory (FCT). The zones are as follows: 1. North Central: Benue, FCT-Abuja, Kogi, Kwara, Nasarawa, Niger, and Plateau 2. North East: Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe 3. North West: Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara 4. South East: Abia, Anambra, Ebonyi, Enugu, and Imo 5. South South: Akwa Ibom, Bayelsa, Cross River, Delta, Edo, and Rivers 6. South West: Ekiti, Lagos, Ogun, Ondo, Osun, and Oyo

    SAMPLING FRAME The sampling frame used for the 2010 NMIS was the Population and Housing Census of the Federal Republic of Nigeria, which was conducted in 2006 by the National Population Commission (NPC). Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), and each LGA is divided into localities. In addition to these administrative units, during the 2006 Population Census, each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2010 NMIS, is defined on the basis of EAs from the 2006 EA census frame.

    Although the 2006 Population Census did not provide the number of households and population for each EA, population estimates were published for more than 800 LGA units. A combination of information from cartographic material demarcating each EA and the LGA population estimates from the census were used to identify the list of EAs, estimate the number of households, and distinguish EAs as urban or rual for the survey sample frame.

    SAMPLE ALLOCATION The 2010 NMIS sample was selected using a stratified, two-stage cluster design consisting of 240 clusters, 83 in the urban areas and 157 in the rural areas. (The final sample included 239 clusters because access to one cluster was prevented by inter-communal disturbances.) A sample of 6,240 households was selected for the survey, with a minimum target of 920 completed individual women's interviews per zone. Within each zone, the number of households was distributed proportionately among urban and rural areas. A fixed 'take' of 26 households per cluster was adopted for both urban and rural clusters.

    SAMPLING PROCEDURE AND UPDATING OF THE SAMPLING FRAME The 2010 NMIS sample is a stratified sample selected in two stages. The primary sampling units (PSUs) are the enumeration areas (EAs) from the 2006 census, and the secondary sampling units (SSUs) are the households. In the first stage of selection, the 240 EAs were selected with a probability proportional to the size of the EA, where size is the number of approximate households calculated within the sampling frame.

    A complete listing of households and a mapping exercise for each cluster was carried out from August through September 2010. The lists of households resulting from this exercise served as the sampling frame for the selection of households in the second stage. In addition to listing the households, the NPC listing enumerators used global positioning system (GPS) receivers to record the coordinates of the 2010 NMIS sample clusters.

    In the second stage of the selection process, 26 households were selected in each cluster by equal probability systematic sampling. All women age 15-49 who were either permanent residents of the households in the 2010 NMIS sample or visitors present in the households on the night before the survey were eligible to be interviewed. In addition, all children age 6-59 months were eligible to be tested for malaria and anaemia.

    The sampling procedures are fully described in Appendix A of "Nigeria Malaria Indicator Survey 2010 - Final Report" pp.69-71.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Two questionnaires were used in the NMIS: a Household Questionnaire and a Woman’s Questionnaire, which was administered to all women age 15-49 in the selected households. Both instruments were based on the standard Malaria Indicator Survey Questionnaires developed by the Roll Back Malaria and DHS programmes. These questionnaires were adapted to reflect the population and health issues relevant to Nigeria during a series of meetings convened with various stakeholders from the NMCP and other government ministries and agencies, nongovernmental organisations, and international donors. The questionnaires were translated into three major Nigerian languages: Hausa, Igbo, and Yoruba.

    The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women who were eligible for the individual interview and children age 6-59 months who were eligible for anaemia and malaria testing. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water; type of toilet facilities; materials used for the floor, roof, and walls of the house; ownership of various durable goods; and ownership and use of mosquito nets. In addition, the questionnaire was used to record the results of the anaemia and malaria testing as well as the signatures of the interviewer and the respondent who gave consent. Children’s temperatures were also recorded.

    The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following main topics: - Background characteristics (such as age, residence, education, media exposure, and literacy) - Birth history and childhood mortality - Antenatal care and malaria prevention for most recent birth and pregnancy - Malaria prevention and treatment - Knowledge about malaria (symptoms, causes, prevention, and drugs used in treatment)

    Cleaning operations

    The processing of data for the 2010 NMIS ran concurrently with data collection. Completed questionnaires were retrieved by the zonal coordinators or the trainers and delivered to NPC in standard envelopes, labelled with the sample ID, team number, and state name. The shipment also contained a written summary of any

  6. Youth unemployment rate in Nigeria in 2024

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Youth unemployment rate in Nigeria in 2024 [Dataset]. https://www.statista.com/statistics/812300/youth-unemployment-rate-in-nigeria/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1999 - 2024
    Area covered
    Nigeria
    Description

    In 2024, the estimated youth unemployment rate in Nigeria was at almost 5.05 percent. According to the source, the data are estimates from the International Labour Organization, an agency of the United Nations developing policies to set labor standards. Employment in Nigeria The youth unemployment rate refers to the percentage of the unemployed in the age group of 15 to 24 years as compared to the total labor force. Youth unemployment rates are often higher than overall unemployment rates, which is true in Nigeria as well: the general rate of unemployment was approximately six percent in 2018. One reason for this contrast is that many of the youth under age 24 are studying full-time and are unavailable for work due to this. Education in Nigeria Nigeria’s population has a large percentage of young inhabitants, and there is a high demand for educational opportunities for its young populace. After severe cuts in governmental aid following a nationwide recession in 2016, Nigeria’s underfunded higher education system became the focus of ongoing student protests and strikes. Other families have taken a different approach: Nigeria is the top country of origin for international students from the continent of Africa. For example, Nigeria sent over 12,600 students to the U.S. in 2017/18, the most of any African country.

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National Population Commission (2019). Population and Housing Census 2006 - Nigeria [Dataset]. https://catalog.ihsn.org/catalog/3340
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Population and Housing Census 2006 - Nigeria

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13 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 29, 2019
Dataset authored and provided by
National Population Commissionhttps://nationalpopulation.gov.ng/
Time period covered
2006
Area covered
Nigeria
Description

Abstract

The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA.

Geographic coverage

National

Analysis unit

Individuals Households

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Census 2006 Processing: The Technology and Methodology:-

Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method.

OMR/OCR/ICR Technology

Definition of terms

  • OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents.
  • OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires.
  • ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents.

Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs.

(a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC.

(b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch.

(c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms.

The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system.

Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving.

Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation.

Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja.

Data appraisal

Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables.

Activities of the Data Validation unit (DVU):-

Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

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