Abstract

Despite years of human and financial investment in the Nigerian Health Sector, the country did not achieve the health-related millennium development goals (MDGs) by 2015. According to a 2010 UNDP MDG report, the likelihood that the country will achieve MDG 4 (reducing under-five mortality by two thirds between 1990 and 2015) and MDG 5 (reducing maternal mortality ratio by three quarters between 1990 and 2015) is average at best. Although the under-five mortality rate fell by a fifth in five years, from 201 deaths/1,000 live births in 2003 to 157 deaths/1,000 live births in 2008, and the maternal mortality ratio fell by 32 percent (800 deaths/100,000 live births in 2003 to 545 deaths/100,000 live births in 2008); these figures do not come close to the two-thirds and three quarters level set for the MDGs. The main challenges to achieving these goals have been identified as “declining resources, ensuring universal access to an essential package of care, improving the quality of healthcare services and increasing demand for health services and providing financial access especially to vulnerable groups” (UNDP 2010).

To overcome these challenges and accelerate the progress of the country to achieving the health related MDGs, innovative approaches are needed to effectively manage the Nigeria health system and improve on its efficiency to enhance the health status of the population. The World Bank and the government of Nigeria are in the process of preparing a results-based financing (RBF) project which provides incentives for improving performance at critical levels within the Nigerian health system and aims to address some of these challenges. A key feature of the RBF project in the Nigerian context is the provision of financial incentives to States and Local Government Agencies (LGA) based on results achieved. In addition, select health facilities will also receive performance incentives. This approach will also build institutional capacity for health system management while introducing a culture of performance excellence at the health facility level and higher levels of health systems management. Given the innovative nature of the proposed project interventions, the World Bank and the Government of Nigeria seek to nest a rigorous impact evaluation in the project to provide evidence that can be used to inform decisions on whether to scale up the innovations implemented under the project. The primary goal of the impact evaluation of the RBF project in Nigeria is to determine if providing financial incentives linked directly to performance increases the quantity and quality of maternal and child health (MCH) services. In addition, it is anticipated that the impact evaluation should provide answers that are generalizable to specific regions in Nigeria.

These are the endline data in support of this impact evaluation.

Geographic coverage

Urban and rural areas in the six states of Adamawa, Benue, Nasarawa, Ogun, Ondo, and Taraba.

Analysis unit

Health facility; household

Universe

• Primary and secondary health facilities in treatment states. In control states, a randomly-selected sample of primary and secondary health facilities.

• Households with recent pregnancies (in the last two years) or a currently pregnant woman from the catchment areas of the above facilities.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame for the health facility surveys comprised one randomly-chosen facility per ward from all functioning primary and secondary health facilities in each LGA (77 LGAs in total; all but one pre-pilot LGA in treatment state). For indicators that are measured at the level of the health facility, the evaluation is a two-level cluster randomized trial, that is, a study in which units are nested within clusters and the clusters are randomly assigned to the treatment or control condition. In this case, health facilities are nested within LGAs and LGAs are randomly assigned to the treatment or control condition. The referral (secondary) hospital in each LGA was also sampled.

HOUSEHOLDS: The sampling frame consists of households in the 77 LGAs that are part of the evaluation. To ensure an efficient sample, the sampling frame was limited to those households that included at least one woman who has given birth or been pregnant in the last two years. By restricting the sampling frame in such a way, we maximize the proportion of the sample that will have at least one woman who gave birth in the last two years, and the proportion of households that have at least one child under the age of five. While this sampling frame does not give us a fully representative sample of the Nigerian population, it gives a representative sample of the population of interest from this program. Sampling of households was done as follows: First, we listed all enumeration areas in the LGAs that belong to the study, and then randomly drew enumeration areas with probability based on size. Within enumeration areas, the survey firm listed all households within the enumeration area that included at least one woman who has given birth within the last 2 years. Then, 15 households were randomly drawn from that listing.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: • Office editing and coding • During data entry • Structure checking and completeness • Secondary editing • Structural checking of Stata data files

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.

Abstract

The 2013 Nigeria Demographic and Health Survey (NDHS) was designed to provide data to monitor the population and health situation in Nigeria with an explicit goal of providing reliable information about maternal and child health and family planning services. The primary objective of the 2013 NDHS was to provide up-to-date information on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, child feeding practices, nutritional status of women and children, adult and childhood mortality, awareness and attitudes regarding HIV/AIDS, and domestic violence. This information is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving health and family planning services in the country.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample for the 2013 NDHS was nationally representative and covered the entire population residing in non-institutional dwelling units in the country. The survey used as a sampling frame the list of enumeration areas (EAs) prepared for the 2006 Population Census of the Federal Republic of Nigeria, provided by the National Population Commission. The sample was designed to provide population and health indicator estimates at the national, zonal, and state levels. The sample design allowed for specific indicators to be calculated for each of the six zones, 36 states, and the Federal Capital Territory, Abuja.

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 census enumeration areas. The primary sampling unit (PSU), referred to as a cluster in the 2013 NDHS, is defined on the basis of EAs from the 2006 EA census frame. The 2013 NDHS sample was selected using a stratified three-stage cluster design consisting of 904 clusters, 372 in urban areas and 532 in rural areas. A representative sample of 40,680 households was selected for the survey, with a minimum target of 943 completed interviews per state.

A complete listing of households and a mapping exercise were carried out for each cluster from December 2012 to January 2013, with the resulting lists of households serving as the sampling frame for the selection of households. All regular households were listed. The NPC listing enumerators were trained to use Global Positioning System (GPS) receivers to calculate the coordinates of the 2013 NDHS sample clusters.

A fixed sample take of 45 households were selected per cluster. All women age 15-49 who were either permanent residents of the households in the 2013 NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed. In a subsample of half of the households, all men age 15-49 who were either permanent residents of the households in the sample or visitors present in the households on the night before the survey were eligible to be interviewed. Also, a subsample of one eligible woman in each household was randomly selected to be asked additional questions regarding domestic violence.

For further details on sample size and design, see Appendix B of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire.

The Household Questionnaire was used to list all of the usual members of and visitors to the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, marital status, education, and relationship to the head of the household. Information on other characteristics of household members was collected as well, including current school attendance and survivorship of parents among those under age 18. If a child in the household had a parent who was sick for more than three consecutive months in the 12 months preceding the survey or a parent who had died, additional questions related to support for orphans and vulnerable children were asked. Furthermore, if an adult in the household was sick for more than three consecutive months in the 12 months preceding the survey or an adult in the household had died, questions were asked relating to support for sick people or people in households where a member had died.

The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water; type of toilet facilities; materials used for the floor of the house; ownership of various durable goods; ownership of agricultural land; ownership of livestock, farm animals, or poultry; and ownership and use of mosquito nets and long-lasting insecticidal nets. The Household Questionnaire was further used to record height and weight measurements for children age 0-59 months and women age 15-49. In addition, data on the age and sex of household members in the Household Questionnaire were used to identify women and men who were eligible for individual interviews.

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 (age, religion, education, literacy, media exposure, etc.) • Reproductive history and childhood mortality • Knowledge, source, and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Child immunisation and childhood illnesses • Marriage and sexual activity • Women’s work and husbands’ background characteristics • Malaria prevention and treatment • Women’s decision making • Awareness of AIDS and other sexually transmitted infections • Maternal mortality • Domestic violence

The Man’s Questionnaire was administered to all men age 15-49 in every second household in the 2013 NDHS sample. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.

Cleaning operations

The processing of the 2013 NDHS data began simultaneously with the fieldwork. Completed questionnaires were edited in the field immediately by the field editors and checked by the supervisors before being dispatched to the data processing centre in Abuja. The questionnaires were then edited and entered by 26 data processing personnel specially trained for this task. Data were entered using the CSPro computer package, and all data were entered twice to allow 100 percent verification. The concurrent processing of the data offered a distinct advantage because of the assurance that the data were error free and authentic. Moreover, the double entry of data enabled easy comparisons and identification of errors and inconsistencies. Inconsistencies were resolved by tallying results with the paper questionnaire entries. Secondary editing of the data was completed in the last week of July 2013. The final cleaning of the data set was carried out by the ICF data processing specialist and completed in August.

Response rate

A total of 40,320 households were selected from 896 sample points, of which 38,904 were found to be occupied at the time of the fieldwork. Of the occupied households, 38,522 were successfully interviewed, yielding a household response rate of 99 percent. In view of the security challenges in the country, this response rate is highly encouraging and appears to be the result of a well-coordinated team effort.

In the interviewed households, a total of 39,902 women age 15-49 were identified as eligible for individual interviews, and 98 percent of them were successfully interviewed. Among men, 18,229 were identified as eligible for interviews, and 95 percent were successfully interviewed. As expected, response rates were slightly lower in urban areas than in rural areas.

Note: See summarized response rates by residence (urban/rural) in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 2013 Nigeria DHS (NDHS) to minimize this type of error, non-sampling 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 2013 NDHS 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 selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population’s welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained.

Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey.

Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA.

Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet

Nigeria NG: Refugee Population: by Country or Territory of Origin data was reported at 238,942.000 Person in 2017. This records an increase from the previous number of 229,311.000 Person for 2016. Nigeria NG: Refugee Population: by Country or Territory of Origin data is updated yearly, averaging 14,036.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 238,942.000 Person in 2017 and a record low of 16.000 Person in 1990. Nigeria NG: Refugee Population: by Country or Territory of Origin data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;

Abstract

The survey was conducted in Nigeria between April 2014 and February 2015 as part of Enterprise Surveys roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

In Nigeria, data from 2,676 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. The establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, region and size.

• Industry stratification For panel firms, the universe was stratified into manufacturing industries and two service sectors (retail and other services). For fresh firms, the universe was stratified into seven manufacturing industries (food & beverage, garments, fabricated metal products, non-metallic mineral products, furniture, publishing, and other manufacturing) and six service sectors (retail, wholesale, transport, hotels & restaurants, repair of motor vehicles, and other services).

• Regional stratification 19 states: Abia, Abuja, Anambra, Cross River, Enugu, Gombe, Jigawa, Kaduna, Kano, Katsina, Kebbi, Kwara, Lagos, Nasarawa, Niger, Ogun, Oyo, Sokoto, Zamfara.

• Size stratification Small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

For the Nigeria ES, two sample frames were used. The fresh sample frame was built using data compiled from the NBS, as well as local and municipal business registries. Due to the fact that the previous round of surveys utilized different stratification criteria in the 2007 and 2009 survey samples, the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the panel.

The sample design for the Nigeria Enterprise Survey was generated with the aim of obtaining interviews at 2,640 establishments.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The eligible manufacturing industries have been surveyed using the Manufacturing Module Questionnaire (includes a common set of core variables, plus manufacturing specific questions). Eligible service establishments have been covered using the Services Module Questionnaire. Each variation of the questionnaire is identified by the index variable, a0.

All variables are named using, first, the letter of each section and, second, the number of the variable within the section, i.e. a1 denotes section A, question 1 (some exceptions apply due to comparability reasons). Variable names proceeded by a prefix "NG" indicate questions specific to Nigeria, therefore, they may not be found in the implementation of the rollout in other countries. All other suffixed variables are global and are present in all country surveys over the world. All variables are numeric with the exception of those variables with an "x" at the end of their names. The suffix "x" denotes that the variable is alpha-numeric.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of interviews per contacted establishments was 0.49. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.13.

Abstract

The documented dataset covers Enterprise Survey (ES) panel data collected in Nigeria in 2007, 2009 and 2014, as part of Africa Enterprise Surveys rollout, an initiative of the World Bank.

New Enterprise Surveys target a sample consisting of longitudinal (panel) observations and new cross-sectional data. Panel firms are prioritized in the sample selection, comprising up to 50% of the sample in the current wave. For all panel firms, regardless of the sample, current eligibility or operating status is determined and included in panel datasets.

Nigeria ES 2014 was conducted between April 2014 and February 2015, and Nigeria ES 2007 was carried out between September 2007 and February 2008. The objective of the Enterprise Survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

Data from 13,764 establishments was analyzed: 1,893 businesses were from 2014 ES only, 2,847 - from 2009 ES only, 1,914 - from 2007 ES, 946 firms were from both 2007 and 2014 panels, and 620 - from 2009 and 2014 panels.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively measure characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the Nigeria ES, two sample frames were used. The fresh sample frame was built using data compiled from the NBS, as well as local and municipal business registries.

Due to the fact that the previous round of surveys utilized different stratification criteria in the 2007 and 2009 survey samples, the presence of panel firms was limited to a maximum of 50% of the achieved interviews in each stratum. That sample is referred to as the panel.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments were used for Nigeria ES 2014: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth. There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

The following survey instruments were used for Nigeria ES 2007: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72]

The "Core Questionnaire" is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the "Core Questionnaire + Manufacturing Module" and the "Core Questionnaire + Retail Module."

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

Abstract

In the past decades, Nigeria has experienced substantial gaps in producing adequate and timely data to inform policy making. In particular, the country is lagging behind in producing sufficient and accurate agricultural production statistics. The current set of household and farm surveys conducted by the NBS covers a wide range of sectors. Except for the Harmonized National Living Standard Survey (HNLSS) which covers multiple topics, these different sectors are usually covered in separate surveys none of which is conducted as a panel. As part of the efforts to continue to improve data collection and usability, the NBS has revised the content of the annual General household survey (GHS) and added a panel component. The GHS-Panel is conducted every 2 years covering multiple sectors with a focus to improve data from the agriculture sector.

The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.

The objectives of the survey are as follows 1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures 2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics 3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS 4. Developing an innovative model for collecting agricultural data 5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria. 6. Active dissemination of agriculture statistics

The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Agricultural farming household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is designed to be representative at the national level as well as at the zonal (urban and rural) levels. The sample size of the GHS-Panel (unlike the full GHS) is not adequate for state-level estimates.

The sample is a two-stage probability sample:

First Stage: The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs. A total of 500 EAs were selected using this method.

Second Stage: The second stage was the selection of households. Households were selected randomly using the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.

Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.

In all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states had different samples sizes depending on the total number of EAs in each state.

Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data Entry This survey used a concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers, the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA

The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was, as explained above, designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the state to the head office of NBS where a second stage of data cleaning was undertaken.

During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level data sets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. This was also done for crop- by-plot information as well.

Response rate

The response rate was very high. Response rate after field work was calculated to be 93.9% while attrition rate was 6.1% for households. During the tracking period, 52.4% of the attrition was tracked while at the end of the whole exercise, the response rate was: Post Harvest: 97.1%

Sampling error estimates

No sampling error

The data in this asset assess whether PPMVs correctly recommend ORS and zinc after training. Health indicators in Nigeria are some of the worst in Africa. The country has one of the fastest growing populations globally. With its rapidly growing population and development challenges, the country drags down the socioeconomic indicators for the entire African continent.

The COVID-19 pandemic has been an historic challenge to public health and behavior change programs. In low -and middle-income countries (LMICs) such as Nigeria, there have been challenges in promoting vaccination. Vaccine hesitancy and social norms related to vaccination may be important factors in promoting or inhibiting not only COVID vaccination, but other routine vaccinations as well. The aim of this study was to conduct a national-level quasi-experimental evaluation of a social media based COVID-19 vaccination promotion campaign in Nigeria run in 2022. We followed a longitudinal cohort of Nigerians (at baseline) drawn from all 37 states in Nigeria over a 10-month period. This was done at 3 time points to evaluate psychosocial predictors of vaccination and vaccination outcomes following a theory of change based on Diffusion of Innovations, Social Norms Theory, and the Motivation, Opportunity, Ability (MOA) Framework. In a quasi-experimental design, participants in 6 Nigerian states where the social media campaign was run (treatment) were compared to participants from non-treatment states. This study highlights new social media-based data collection techniques. The study found that vaccination rates increased in treatment states compared to non-treatment states, and that these effects were strongest between baseline and first follow up (December 2021 to March 2022). We also found that more pro-vaccination social norms at one time point are associated with higher vaccination rates at a later time point. Social media campaigns are a promising approach to increasing vaccination at scale in LMICs, and social norms are an important factor in promoting vaccination, which is consistent with the Social Norms Theory. We describe implications for future vaccination campaigns and identify future research priorities in this area.

Inflation Rate in Nigeria decreased to 23.18 percent in February from 24.48 percent in January of 2025. This dataset provides - Nigeria Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

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.

Geographic coverage

The 1990 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey. The sample was constructed so as to provide national estimates as well as estimates for the four Ministry of Health regions.

Analysis unit

• Household
• Women age 15-49
• Children under five years

Universe

The population covered by the 1990 DHS is defined as the universe of all women age 15-49 in Nigeria.

Kind of data

Sample survey data

Sampling procedure

The NDHS Sample was drawn from the National Master Sample for the 1987/1992 National Integrated Survey of Households (NISH) programme being implemented by the Federal Office of Statistics (FOS). NISH, as part of the United Nations National Household Survey Capability Programme, is a multi- subject household-based survey system.

The NISH master sample was created in 1986 on the basis of the 1973 census enumeration areas (EA). Within each state, EAs were stratified into three sectors (urban, semiurban, and rural), from which an initial selection of approximately 8C0 EAs was made from each state. EAs were selected at this stage with equal probability within sectors. A quick count of households was conducted in each of the selected EAs, and a final selection of over 4,000 EAs was made over the entire country, with probability proportional to size. This constitutes the NISH master sample from which the NDHS EAs were subsampled.

Prior to the NDHS selection of EAs, the urban and semiurban sectors of NISH were combined into one category, while the rural retained the NISH classification. A sample of about 10,000 households in 299 EAs was designed with twofold oversampling of the urban stratum, yielding 132 urban EAs and 167 rural EAs. The sample was constructed so as to provide national estimates as well as estimates for the four Ministry of Health regions.

The NDHS conducted its own EA identification and listing operation; a new listing of housing units and households was compiled in each of the selected 299 EAs. For each EA, a list of the names of the head of households was constructed, from which a systematic sample of 34 households was selected to be interviewed. A fixed number of 34 households per EA was taken in order to have better control of the sample size (given the variability in EA size of the NISH sample). Thus, the NDHS sample is a weighted sample, maintaining the twofold over sampling of the urban sector.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used in the main fieldwork for the NDHS: a) the household questionnaire, b) the individual questionnaire, and c) the service availability questionnaire. The first two questionnaires were adapted from the DHS model B questionnaire, which was designed for use in countries with low contraceptive prevalence. The questionnaires were developed in English, and then translated into six of the major Nigerian languages: Efik, Hausa, Igbo, Kanuri,

Nigeria NG: Refugee Population: by Country or Territory of Asylum data was reported at 1,900.000 Person in 2017. This records an increase from the previous number of 1,367.000 Person for 2016. Nigeria NG: Refugee Population: by Country or Territory of Asylum data is updated yearly, averaging 7,235.000 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 10,124.000 Person in 2008 and a record low of 1,239.000 Person in 2014. Nigeria NG: Refugee Population: by Country or Territory of Asylum data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of asylum is the country where an asylum claim was filed and granted.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;

Abstract copyright UK Data Service and data collection copyright owner. The purpose of this study was to explore the way of life of ordinary urban residents in cities of varying sizes and types in various parts of Nigeria, especially in regard to social networks and activities, occupational and migration careers, and attitudes toward urban life, education and members of ethnic groups. Main Topics: Variables Dr Peil's study was designed as a comparative study of the daily life of people living in cities in various parts of Nigeria, these cities differing in size and composition. Data were collected by oral interviewing, supplemented by observation, mapping, recording of schools, churches, health facilities, government services, craftsmen, etc. Only the interviewing data (from cities Ajegunle, Kikuri, Abeokuta and Aba) have been supplied to the Archive. To quote from Dr Peil's report: 'Investigation of social networks provides a framework for testing hypotheses about social change and modernity, adjustment to urban life and the social effects of various types of housing and various kinds of employment. Identical studies of several cities permit analysis of the effects of city size, heterogeneity and social structure on the lives of the inhabitants. . . . The 'quality of life' measured in this study is concerned with items which can be easily reported by individuals rather than with official statistics. . . . It was also hoped that this study would be useful to urban planners, who generally have very little information on what the average family makes of its life in town. What are their expectations and their aspirations? What amenities do they most appreciate and most miss? How much urban experience have they had and how long can they be expected to stay, especially in the face of unemployment? How much unemployment is there and how are the unemployed supported?. . .' Hence, there is detailed demographic information for a general picture of the population of the four cities. The housing section collects details on household composition, overcrowding, landlords and inter-ethnic mixing. Marriage and kinship information indicates the numbers and location of wives and children, attitudes and practices in educating children, contacts with relatives in town and at home, and plans for returning home. A social life section deals with membership in associations, and contacts with co-tenants, workmates and friends. Information is also collected on how urban dwellers handle problems, and there is detailed occupational and migration career data. Approximately 100 houses were taken in each city, by systematic sampling from a series of random starts, designed to represent all parts of the community being studied. About 200 interviews were completed in each city, the individuals being chosen from census sheets on a quota basis to ensure the inclusion of men and women in various age, occupational, educational, ethnic and religious and migratory categories Face-to-face interview

Abstract

The Nigerian General Household Survey (GHS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program and was revised in 2010 to include a panel component (GHS-Panel). The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, inter-institutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of 5,000 households, which are also representative of the geopolitical zones (at both the urban and rural level). The households included in the GHS-Panel are a sub-sample of the overall GHS sample households (22,000). This survey is the third wave of the GHS-Panel, and was implemented in 2015-2016.

Geographic coverage

National Coverage Sector

Analysis unit

Households

Universe

Household Members

Kind of data

Sample survey data [ssd]

Sampling procedure

The GHS-Panel sample is fully integrated with the 2010 GHS Sample. The GHS sample is comprised of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs) chosen from each of the 37 states in Nigeria. This results in a total of 2,220 EAs nationally. Each EA contributes 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,000 households, 5,000 households from 500 EAs were selected for the panel component and 4,916 households completed their interviews in the first wave. Given the panel nature of the survey, some households had moved from their location and were not able to be located by the time of the Wave 3 visit, resulting in a slightly smaller sample of 4,581 households for Wave 3.

In order to collect detailed and accurate information on agricultural activities, GHS-Panel households are visited twice: first after the planting season (post-planting) between August and October and second after the harvest season (post-harvest) between February and April. All households are visited twice regardless of whether they participated in agricultural activities. Some important factors such as labour, food consumption, and expenditures are collected during both visits. Unless otherwise specified, the majority of the report will focus on the most recent information, collected during the post-harvest visit.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the state to the head office of NBS where a second stage of data cleaning was undertaken. During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level datasets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. This was also done for crop-by-plot information as well.

Nigeria Ovo Project Panorama, GlobalData’s latest release, presents a comprehensive overview of the asset. This upstream report includes detailed qualitative and quantitative information on the asset, provides a full economic assessment and reflects several parameters including (but not limited to) geological profile, asset development and specific challenges. Based on this analysis, future outlook for the asset is presented with possible trends and related scenarios identifying upside/downside potential. Read More

Nigeria Sonam Project Panorama, GlobalData’s latest release, presents a comprehensive overview of the asset. This upstream report includes detailed qualitative and quantitative information on the asset, provides a full economic assessment and reflects several parameters including (but not limited to) geological profile, asset development and specific challenges. Based on this analysis, future outlook for the asset is presented with possible trends and related scenarios identifying upside/downside potential. Read More

Abstract

The 1999 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey of 8,199 women age 15-49 and 3,082 men age 15-64, designed to provide information on levels and trends of fetility, family planning practice, maternal and child health, infant and child mortality, and maternal mortality, as well as awareness of HIV/AIDS and other sexually transmitted diseases (STDs) and female circumcision. Fieldwork for the survey took place between March and May 1999.

OBJECTIVES

The main objective of the 1999 Nigeria Demographic and Health Survey (NDHS) is to provide up-to-date information on reality and childhood mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; nutrition levels; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programmes and strategies for improving health and family planning services in Nigeria.

MAIN RESULTS

Fertility

The total fertility rate during the five years before the survey is 5.2 births per woman. This shows a drop from the level of 6.0 births per woman as reported in the 1990 NDHS and 5.4 from the 1994 Sentinel Survey. The total fertility rate may, however be higher due to evidence that some births were probably omitted in the data. Fertility is substantially higher in the Northeast and Northwest regions and lower in the Southeast, Southwest, and Central regions. Fertility rates are also lower for more educated women.

Childbearing begins early in Nigeria, with about half of women 25 years and above becoming mothers before reaching the age of 20. The median age at first birth is 20.

The level of teenage childbearing has declined somewhat, with the proportion of girls age 15-19 who have either given birth or are pregnant with their first child declining from 28 percent in 1990 to 22 percent in 1999.

Teenage childbearing is higher in rural than urban areas and for those with no education than those with education.

The data from the survey indicate that there is a strong desire for children and a preference for large families with 66 percent of married women and 71 percent of married men indicating a desire to have more children. Even among those with six or more children, 30 percent of married women and 55 percent of married men want to have more children. This indicates a decline for women from the 35 percent reported in the 1990 NDHS. Overall, women report a mean ideal number of children of 6.2, compared with 7.8 children for men.

Despite the increasing level of contraceptive use, the 1999 NDHS data show that unplanned pregnancies are common, with almost one in five births reported to be unplanned. Most of these (16 percent of births) are mistimed (wanted later), while 3 percent were unwanted at all.

Family Planning

Knowledge about family planning methods is increasing in Nigeria, with about 65 percent of all women and 82 percent of all men having heard of at least one method of contraception.

Among women, the pill is the best known method (53 percent) while among men, the condom is the best known method (70 percent). Radio is a main source of information about family planning, with 35 percent of women and 61 percent of men reporting that they heard a family planning message on the radio in the few months before interview. The proportions of women and men who have seen a television message are 23 and 40 percent, respectively. Only 17 percent of women had seen a family planning message in the print media.

The contraceptive prevalence rate in Nigeria has also increased, with 15 percent of married women and 32 percent of married men now using some method of family planning. The use of modem methods is lower at 9 percent for married women and 14 percent for men. Although traditional contraceptive methods are not actively promoted, their use is relatively high with about 6 percent of married women and 17 percent of married men reporting that they are using periodic abstinence or withdrawal. In 1990, only 6 percent of married women were using any method, with only 4 percent using a modern method.

There are significant differentials in levels of family planning use. Urban women and men are much more likely to be using a method than rural respondents. Current use among married women is higher in the Southwest regions (26 percent), Southeast (24 percent), and Central (18 percent) regions than in the Northwest and Northeast (3 percent each). The largest differences occur by educational attainment. Only 6 percent of married women with no education are using a method of contraception, compared with 45 percent of those with more than secondary school.

Users of modern contraception are almost as likely to obtain their methods from government as private sources. Forty-three percent of users obtain their methods from the public sector--mostly government hospitals and health centres--while 43 percent use private medical sources such as pharmacies and private hospitals and clinics; 8 percent get their methods from other private sources like friends, relatives, shops and non-governmental organisations.

Maternal Health

The results of the survey show that antenatal care is not uncommon in Nigeria, with mothers receiving antenatal check-ups from either a doctor, nurse or midwife for two out of three births in the three years preceding the survey. However, the content of antenatal care visits appears to be lacking in at least one respect: survey data indicate deficiencies in tetanus toxoid coverage during pregnancy. Mothers reported receiving the recommended two doses of tetanus toxoid for only 44 percent of births and one dose for I 1 percent of births. Almost 40 percent of births occurred without the benefit of a tetanus vaccination.

In Nigeria, home deliveries are still very common, with almost three in five births delivered at home. Compared with 1990, the proportion of home deliveries has declined, with more births now taking place in health facilities. Increasing the proportion of births occurring in facilities is important since they can be attended by medically trained personnel which can result in fewer maternal deaths and delivery complications. Currently, 42 percent of births are attended by doctors, nurses or midwives.

The 1999 NDHS data show that about one in four Nigerian women age 15-49 reported being circumcised. The practice of female genital cutting is more prevalent in the south and central parts of the country and is almost non-existent in the north.

Child Health

The 1999 NDHS data indicate a decline in childhood vaccination coverage, with the proportion of children fully immunised dropping from 30 percent of children age 12-23 months in 1990 to only 17 percent in 1999. Only a little over half of young children receive the BCG vaccine and the first doses of DPT and polio vaccines. Almost 40 percent of children have not received any vaccination.

Diarrhoea and respiratory illness are common causes of childhood death. In the two weeks before the survey, 11 percent of children under three years of age were ill with acute respiratory infections (ARI) and 15 percent had diarrhoea. Half of children with ARI and 37,percent of those with diarrhoea were taken to a health facility for treatment. Of all the children with diarrhoea, 34 percent were given fluid prepared from packets of oral rehydralion salts (ORS) and 38 percent received a home-made sugar-salt solution.

The infant mortality rate for the five-year period before the survey (early 1994 to early 1999) is 75 per thousand live births. The under-five mortality is 140 deaths per 1,000 births, which means that one in seven children born in Nigeria dies before reaching his/her fifth birthday. However, both these figures are probably considerably higher in reality since an in-depth examination of the data from the birth histories reported by women in the NDHS shows evidence of omission of births and deaths. For this reason, the dramatic decline observed in childhood mortality between the 1990 and 1999 NDHS surveys needs to be viewed with considerably skepticism. Based on the reported birth history information, the infant mortality rate fell from 87 to 75 deaths per 1,000 births, while the under-five mortality rate dropped from 192 to 140.

Problems with the overall levels of reported mortality are unlikely to severely affect differentials in childhood mortality. As expected, mother's level of education has a major effect on infant and child mortality. Whereas the lowest infant mortality rate was reported among children of mothers with post- secondary education (41 per thousand live births), the corresponding figure among infants of mothers with no schooling is 77 per thousand live births.

Data were also collected in the NDHS on the availability of various health services. The data indicate that the vast majority of Nigerian households live within five kilometres of a health facility, with health centres being the closest, followed by clinics and hospitals.

Breasffeeding and Nutrition

Breastfeeding is widely practiced in Nigeria, with 96 percent of children being breastfed. The median duration of breastfeeding is 19 months. Although it is recommended that children be exclusively breastfed with no supplements for the first 4 to 6 months, only 20 percent of children 0-3 months are exclusively breasffed, as are 8 percent of children 4-6 months. Two-thirds of children 4-6 months are being given supplements in addition to breast milk.

In the NDHS, interviewers weighed and measured children under three born to women who were interviewed. Unfortunately, data were either missing or implausible for more than half of these children. Of the half with plausible data, 46 percent of children under 3 are classified as stunted (low height-for-age), 12 percent are wasted (low

As of July 2024, Nigeria's population was estimated at around 229.5 million. Between 1965 and 2024, the number of people living in Nigeria increased at an average rate of over two percent. In 2024, the population grew by 2.42 percent compared to the previous year. Nigeria is the most populous country in Africa. By extension, the African continent records the highest growth rate in the world. Africa's most populous country Nigeria was the most populous country in Africa as of 2023. As of 2022, Lagos held the distinction of being Nigeria's biggest urban center, a status it also retained as the largest city across all of sub-Saharan Africa. The city boasted an excess of 17.5 million residents. Notably, Lagos assumed the pivotal roles of the nation's primary financial hub, cultural epicenter, and educational nucleus. Furthermore, Lagos was one of the largest urban agglomerations in the world. Nigeria's youthful population In Nigeria, a significant 50 percent of the populace is under the age of 19. The most prominent age bracket is constituted by those up to four years old: comprising 8.3 percent of men and eight percent of women as of 2021. Nigeria boasts one of the world's most youthful populations. On a broader scale, both within Africa and internationally, Niger maintains the lowest median age record. Nigeria secures the 20th position in global rankings. Furthermore, the life expectancy in Nigeria is an average of 62 years old. However, this is different between men and women. The main causes of death have been neonatal disorders, malaria, and diarrheal diseases.

Abstract

The primary objective of the 2018 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, female genital cutting, prevalence of malaria, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), disability, and other health-related issues such as smoking.

The information collected through the 2018 NDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The 2018 NDHS also provides indicators relevant to the Sustainable Development Goals (SDGs) for Nigeria.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-5 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 NDHS is the Population and Housing Census of the Federal Republic of Nigeria (NPHC), which was conducted in 2006 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 wards. In addition to these administrative units, during the 2006 NPHC each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2018 NDHS, is defined on the basis of EAs from the 2006 EA census frame. Although the 2006 NPHC did not provide the number of households and population for each EA, population estimates were published for 774 LGAs. A combination of information from cartographic material demarcating each EA and the LGA population estimates from the census was used to identify the list of EAs, estimate the number of households, and distinguish EAs as urban or rural for the survey sample frame. Before sample selection, all localities were classified separately into urban and rural areas based on predetermined minimum sizes of urban areas (cut-off points); consistent with the official definition in 2017, any locality with more than a minimum population size of 20,000 was classified as urban.

The sample for the 2018 NDHS was a stratified sample selected in two stages. Stratification was achieved by separating each of the 36 states and the Federal Capital Territory into urban and rural areas. In total, 74 sampling strata were identified. Samples were selected independently in every stratum via a two-stage selection. Implicit stratifications were achieved at each of the lower administrative levels by sorting the sampling frame before sample selection according to administrative order and by using a probability proportional to size selection during the first sampling stage.

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used for the 2018 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

The processing of the 2018 NDHS data began almost immediately after the fieldwork started. As data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the NPC central office in Abuja. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding the open-ended questions. The NPC data processor coordinated the exercise at the central office. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in the second week of April 2019.

Response rate

A total of 41,668 households were selected for the sample, of which 40,666 were occupied. Of the occupied households, 40,427 were successfully interviewed, yielding a response rate of 99%. In the households interviewed, 42,121 women age 15-49 were identified for individual interviews; interviews were completed with 41,821 women, yielding a response rate of 99%. In the subsample of households selected for the male survey, 13,422 men age 15-59 were identified and 13,311 were successfully interviewed, yielding a response rate of 99%.

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 2018 Nigeria Demographic and Health Survey (NDHS) to minimise 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 2018 NDHS 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 selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2018 NDHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Standardisation exercise results from anthropometry training - Height and weight data completeness and quality for children - Height measurements from random subsample of measured children - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends - Data collection period - Malaria prevalence according to rapid diagnostic test (RDT)

Note: See detailed data quality tables in APPENDIX C of the report.