Population ages 15-64 (% of total population) in Nigeria was reported at 55.48 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 15-64 (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Population ages 0-14, female (% of female population) in Nigeria was reported at 41.36 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 0-14, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Graph and download economic data for Age Dependency Ratio: Older Dependents to Working-Age Population for Nigeria (SPPOPDPNDOLNGA) from 1960 to 2023 about 64 years +, Nigeria, working-age, ratio, and population.

Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 82.602 % in 2017. This records a decrease from the previous number of 82.925 % for 2016. Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 82.468 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 87.186 % in 1987 and a record low of 74.878 % in 1960. Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Young 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. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Nigeria NG: Age Dependency Ratio: % of Working-Age Population data was reported at 87.767 % in 2017. This records a decrease from the previous number of 88.092 % for 2016. Nigeria NG: Age Dependency Ratio: % of Working-Age Population data is updated yearly, averaging 87.752 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 92.743 % in 1987 and a record low of 79.958 % in 1960. Nigeria NG: Age Dependency Ratio: % of Working-Age Population 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. Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: this indicator implies the dependency burden that the working-age population bears in relation to children and the elderly. Many times single or widowed women who are the sole caregiver of a household have a high dependency ratio.

Nigeria NG: Population: Female: Ages 35-39: % of Female Population data was reported at 5.484 % in 2017. This records an increase from the previous number of 5.468 % for 2016. Nigeria NG: Population: Female: Ages 35-39: % of Female Population data is updated yearly, averaging 5.280 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 5.587 % in 1960 and a record low of 4.995 % in 1991. Nigeria NG: Population: Female: Ages 35-39: % of Female Population 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: Population and Urbanization Statistics. Female population between the ages 35 to 39 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Age dependency ratio (% of working-age population) in Nigeria was reported at 80.25 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Age dependency ratio (% of working-age population) - actual values, historical data, forecasts and projections were sourced from the World Bank on May of 2025.

Graph and download economic data for Population ages 65 and above for Nigeria (SPPOP65UPTOZSNGA) from 1960 to 2024 about 65-years +, Nigeria, and population.

Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Old data was reported at 5.165 % in 2017. This records a decrease from the previous number of 5.167 % for 2016. Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Old data is updated yearly, averaging 5.255 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 5.563 % in 1988 and a record low of 5.080 % in 1960. Nigeria NG: Age Dependency Ratio: % of Working-Age Population: Old 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: Population and Urbanization Statistics. Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

NG: Population: Male: Ages 80 and Above: % of Male Population data was reported at 0.197 % in 2017. This records an increase from the previous number of 0.188 % for 2016. NG: Population: Male: Ages 80 and Above: % of Male Population data is updated yearly, averaging 0.170 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 0.197 % in 2017 and a record low of 0.109 % in 1960. NG: Population: Male: Ages 80 and Above: % of Male Population 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. Male population between the ages 80 and above as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Population ages 00-04, male (% of male population) in Nigeria was reported at 14.73 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 0-4, male (% of male population) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Population ages 15-64, total in Nigeria was reported at 126428565 Persons in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 15-64, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Graph and download economic data for Population Ages 0 to 14 for Nigeria (SPPOP0014TOZSNGA) from 1960 to 2023 about 0 to 14 years, Nigeria, and population.

Nigeria NG: Population: Female: Ages 20-24: % of Female Population data was reported at 8.638 % in 2017. This records an increase from the previous number of 8.629 % for 2016. Nigeria NG: Population: Female: Ages 20-24: % of Female Population data is updated yearly, averaging 8.662 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.205 % in 2003 and a record low of 8.320 % in 1988. Nigeria NG: Population: Female: Ages 20-24: % of Female Population 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: Population and Urbanization Statistics. Female population between the ages 20 to 24 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Nigeria NG: Population: Male: Ages 55-59: % of Male Population data was reported at 2.204 % in 2017. This records an increase from the previous number of 2.199 % for 2016. Nigeria NG: Population: Male: Ages 55-59: % of Male Population data is updated yearly, averaging 2.377 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.502 % in 1975 and a record low of 2.158 % in 2011. Nigeria NG: Population: Male: Ages 55-59: % of Male Population 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: Population and Urbanization Statistics. Male population between the ages 55 to 59 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Population ages 05-09, female (% of female population) in Nigeria was reported at 13.9 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 5-9, female (% of female population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Nigeria NG: Population: Female: Ages 25-29: % of Female Population data was reported at 7.385 % in 2017. This records a decrease from the previous number of 7.426 % for 2016. Nigeria NG: Population: Female: Ages 25-29: % of Female Population data is updated yearly, averaging 7.424 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.756 % in 2008 and a record low of 7.049 % in 1987. Nigeria NG: Population: Female: Ages 25-29: % of Female Population 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: Population and Urbanization Statistics. Female population between the ages 25 to 29 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Population ages 65 and above, female in Nigeria was reported at 3627550 Persons in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Population ages 65 and above, female - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

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

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National Coverage. Sample excludes the states of Adamawa, Borno, and Yobe because of security concerns. These states represent 4.5% of the population.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in Nigeria was 1,000 individuals.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.