Over ** percent of Nigerian households reported being able to access necessary maternal as well as pregnancy healthcare when needed. However, over ** percent said they were unable to gain necessary vaccination services. In fact, vaccinations were the medical service harder to access in Nigeria. Nevertheless, over ** percent of adults and ** percent of children were medically taken care of when needed.

Nigeria NG: Current Health Expenditure: % of GDP data was reported at 3.565 % in 2015. This records an increase from the previous number of 3.331 % for 2014. Nigeria NG: Current Health Expenditure: % of GDP data is updated yearly, averaging 3.461 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 4.453 % in 2003 and a record low of 2.143 % in 2002. Nigeria NG: Current Health Expenditure: % of GDP 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: Health Statistics. Level of current health expenditure expressed as a percentage of GDP. Estimates of current health expenditures include healthcare goods and services consumed during each year. This indicator does not include capital health expenditures such as buildings, machinery, IT and stocks of vaccines for emergency or outbreaks.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

Nigeria NG: Domestic Private Health Expenditure: % of Current Health Expenditure data was reported at 73.729 % in 2015. This records a decrease from the previous number of 74.393 % for 2014. Nigeria NG: Domestic Private Health Expenditure: % of Current Health Expenditure data is updated yearly, averaging 76.836 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 84.515 % in 2003 and a record low of 73.146 % in 2013. Nigeria NG: Domestic Private Health Expenditure: % of Current Health Expenditure 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: Health Statistics. Share of current health expenditures funded from domestic private sources. Domestic private sources include funds from households, corporations and non-profit organizations. Such expenditures can be either prepaid to voluntary health insurance or paid directly to healthcare providers.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

As of 2018, about ** percent of people surveyed in Nigeria did not have any health insurance. People with a health insurance mainly had an employer-based coverage. Specifically, ***** percent of men and *** percent of women were provided with an employed based health insurance. Privately purchased insurances were notably uncommon. In total, only about ***** percent of individuals had a health insurance.

In 2019, Nigerian households spent on average 6.1 percent of their total annual expenditure on health. This share was lower in South South and South West, whereas the expenditure peaked at 10.3 percent in the South Eastern states. Data on health insurance coverage show that only 1.4 percent of people living in rural areas had a health insurance. Overall, insurance coverage in Nigeria is very low. In particular, among individuals without education the coverage was below one percent.

📝 Dataset Overview: This dataset provides a comprehensive view into patient care and hospital operations at Eko Hospital, Lagos. It captures both clinical and financial details — including patient demographics, diagnoses, treatment procedures, and billing data.

It is a powerful tool for health data analysts, students, and researchers to explore real-world healthcare delivery in a Nigerian context.

🔍 Dataset Features: Column Name Description Patient_ID Unique patient identifier (anonymized) Name Patient's name (consider anonymizing further before public use) Age Age of the patient Gender Gender identity Department Medical department visited (e.g., Pediatrics, Cardiology) Doctor Name of the attending physician Diagnosis Medical condition diagnosed Admission_Date Date of hospital admission Discharge_Date Date the patient was discharged Bill_Amount (₦) Total cost incurred (in Nigerian Naira) Lab_Tests_Conducted Number or type of lab tests carried out Medications_Administered Types or count of drugs administered Nurses_Assigned Number of nurses responsible during care Surgery_Cost (₦) Cost of any surgical procedures performed

🎯 Ideal Use Cases: Create interactive Power BI dashboards for patient flow or billing breakdowns

Analyze treatment cost per diagnosis

Predict length of stay or discharge patterns using machine learning

Monitor resource allocation (nurses, doctors)

Understand clinical performance across departments

🧰 Tools to Use: Python (Pandas, Scikit-learn, Seaborn)

Power BI / Tableau for dashboarding

R (Shiny, ggplot2)

Excel pivot tables and charts

📌 Important Notes: Please ensure patient names are anonymized before full public sharing.

Excellent for portfolio projects, capstone work, or public health exploration.

👤 Created By: Fatolu Peter (Emperor Analytics) Healthcare analytics specialist working on real Nigerian datasets to bridge the gap between clinical care and data intelligence. This marks Project 10 in my growing analytics journey 🚀

✅ LinkedIn Post: 🩺 New Healthcare Dataset Alert 📊 Eko Hospital Patient Care Analytics – Now Live on Kaggle 🔗 Check it out here

Looking to sharpen your healthcare analytics or build a project with real-world medical data?

This dataset features:

Admissions & discharges

Diagnosis, medications, surgeries

Billing info (₦), lab tests, and staffing

You can use it to: ✅ Build Power BI dashboards ✅ Train ML models to predict outcomes or costs ✅ Analyze treatment patterns by age, gender, or department

Let’s use data to improve healthcare outcomes. If you build anything with it, tag me — I’d love to share and learn from you.

KaggleDataset #HealthcareAnalytics #PowerBI #PublicHealth #NigerianData #DataScience #FatoluPeter #EmperorAnalytics #Project10 #RealWorldData #PatientCare #HospitalAnalytics

Comprehensive Nigeria Health Analysis

Exploring Disease, Policy, Financing, Technologies, and SDG Indicators

By Humanitarian Data Exchange [source]

About this dataset

This dataset contains health indicators for Nigeria sourced from the World Health Organization's data portal, covering a variety of topics such as mortality and global health estimates, sustainable development goals, child health, infectious diseases, health financing, public health and environment, substance use and mental health, injuries and violence, HIV/AIDS and other STIs. The indicators explore service organization and delivery of treatment capacity against preventative programs in Nigeria according to sex levels across respective income groups.

Questions related to financial protection or youth utilization are also addressed in this dataset. Additional epidemiological aspects of the data include observations on neglected tropical diseases as well as drug resistance to insecticides. Additionally included is information on medical equipment accessibility; utilizing ICD codes alongside sexual reproductive heath status variables which offer insight into UHC (Universal Health Coverage).

Overall this collection paints an all-encompassing picture that helps decipher patterns influencing population wellbeing regarding the current state of healthcare services in Nigeria along with any necessary decisions that may need to be taken

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How to use the dataset

This dataset provides comprehensive indicators regarding the health levels of Nigeria. It contains data from World Health Organization (WHO) covering a variety of subjects such as Mortality, Sustainable Development Goals, Public Health and Environmental issues, Child Health, Infectious Disease, Non-Communicable Diseases and Mental Health.

The dataset includes information such as the GHO code and display name for each indicator as well as region codes for Nigeria’s state regions. Additionally the year that data was collected is also listed along with item specific information like wealth quintiles or sex type. Research objectives can be reached quickly by leveraging these types of indicators to tell an overall story about health conditions in Nigeria over time.

To get started with this dataset you can begin by exploring the columns available at first glance two columns provide already a great insight on health condition in Nigeria: Education Level Code and Wealth Quintile Code which means one can explore how equitable access to education is based on different areas of country or are there any direct connection between affluence level which is indicated by Wealth Quintile Code column itself and other health related matters like increased mortality rate?

To explore this idea further we could look at mortality rates in detail using GHO code values found within our dataset - particularly if we are interested in certain diseases associated with mortality rates we could use our query engine to filter out relevant indicators from all that have been included here - filtering down core details associated with each indicator e.g mortality rate . We could then drill down into more detailed information using additional filters like year range , sex type , region etc thus preceding to make more meaningful comparisons about conditions over time but also observe situations qualitatively following trends / deviations where applicable .

Finally when delving into deeper analysis it might be important stop evaluate metrics objectively based off real world parameters here - viewing raw numbers may not always give us clear understanding so its important at times to view sample size being used particularly when working with less or highly dispersed demographics not even mentioned here e.g remote villages should also be evaluated here too since it would require extra effort/resources/time triangulate similar type findings present within this set itself

Research Ideas

• Creating visualizations to compare health indicators over time for different regions in Nigeria, such as crude mortality rates, journey-related deaths and suicide rate.
• Analyzing the distribution and trends of different diseases across Nigerian regions, such as cases of tuberculosis in an effort to better target areas at risk in the nation.
• Studying the income and education level correlations with specific disease prevalence, to gain deeper insights into health disparities within Nigeria

Acknowledgements

If you use this dataset in your research, please credit the original authors. [Data Source](https://da...

Background: Nigeria’s healthcare system faces significant challenges in financing and quality, impacting the delivery of services to its growing population. This study investigates healthcare workers’ perceptions of these challenges and their implications for healthcare policy and practice. Methods: A cross-sectional survey was conducted with 600 healthcare professionals from eight states across Nigeria, representing a variety of healthcare occupations. Participants completed a questionnaire that assessed their perceptions of healthcare financing, quality of care, job satisfaction, and motivation using a 5-point Likert scale, closed- and open-ended questions. Descriptive statistics, Chi-squared test, and regression analysis were used to analyze the data. Results: The findings revealed that healthcare workers were generally not satisfied with the current state of healthcare financing and system quality in Nigeria. Poor funding, inadequate infrastructure, insufficient staffing, and limite..., Research Design This study employed a quantitative cross-sectional survey design to assess healthcare workers’ perceptions of quality, challenges, and best financing interventions within the Nigerian healthcare system over the preceding period. Population and Scope The research focuses on healthcare workers in Nigeria, a West African nation (Figure 1) with a population exceeding 220 million as of 2024 (Worldometer, 2024). The nine States selected for the study have a combined population of 72,025,500. Nigeria has an overall estimated healthcare worker density of 19.97 per 10,000 individuals (WHO, 2023). Therefore, the target population for the study was 143,835 healthcare workers in addition to some non-clinical healthcare workers who are working in Nigerian government health facilities currently or within the last year  (WHO, 2023). Healthcare workers were sampled from two randomly selected representative States in each of five geopolitical zones (except one for the South-east, the sm..., , # Perceptions of Healthcare Finance and System Quality Among Nigerian Healthcare Workers

https://doi.org/10.5061/dryad.b8gtht7mn

Description of the data and file structure

• This is the healthcare workers' part of our nationwide research.
• You can open the file using Microsoft Excel, Google Spreadsheet, or any other spreadsheet processor.
• Data Set 1 is the survey responses:
  • This Excel spreadsheet contains the data from a survey that spanned nine states from five geopolitical zones in Nigeria from June to August 2023.
  • It contains participants' responses about their social demographics, perceptions towards the healthcare systems, and their opinions regarding the quality of the healthcare system.Â

Files and variables

File: Data_1.xlsx

Description:

This is the healthcare workers' part of our nationwide cross-sectional survey on healthcare quality.

Variables:

Variables include the following

• State
• Years...

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Nigeria SDI Health survey team visited a sample of 2,385 health facilities across Nigeria between July 2013 and January 2014. The survey team collected rosters covering 21,318 workers for absenteeism and assessed 5,017 health workers for competence using patient case simulations. The data is representative at the state level. The sample included 12 of 36 states in Nigeria due to logistical constraints.

Geographic coverage

Twelve states of Nigeria (Anambra, Bauchi, Bayelsa, Cross River, Ekiti, Imo, Kaduna, Kebbi, Kogi, Niger, Osun and Taraba)

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care in these twelve states.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.

Sampling deviation

The sample in Nigeria is not nationally representative, including 12 of 36 states.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules and weights:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

Nigeria NG: Physicians: per 1000 People data was reported at 0.395 Ratio in 2010. This records an increase from the previous number of 0.376 Ratio for 2009. Nigeria NG: Physicians: per 1000 People data is updated yearly, averaging 0.192 Ratio from Dec 1960 (Median) to 2010, with 19 observations. The data reached an all-time high of 0.395 Ratio in 2010 and a record low of 0.017 Ratio in 1960. Nigeria NG: Physicians: per 1000 People 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: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;

The study assesses the impacts of the Nigerian Health Systems on COVID-19 fatalities. The researchers evaluated the association between healthcare system capability and mortality rate of COVID-19 patients through adjustments for healthcare spending as a proportion of the GDP, population density, and the proportion of the population that are 65 years and above across the 36 States and the Federal Capital Territory (FCT), Abuja.

GlobalData, the industry analysis specialist, has released its latest report “Nigeria – Healthcare, Regulatory and Reimbursement Landscape”. The report is an essential source of information on analysis of the healthcare, regulatory and reimbursement landscape in Nigeria. It identifies the key trends in the country’s healthcare market and provides insights into its demographic, regulatory and reimbursement landscape, and healthcare infrastructure. Most importantly, the report provides valuable insights into the trends and segmentation of its pharmaceutical and medical device markets. It uses data and information sourced from proprietary databases, secondary research, and in-house analysis by GlobalData’s team of industry experts. Read More

Abstract

Nigeria has one of the largest stocks of human resources for health (HRH) in Africa. However, great disparities in health status and access to health care exist among the six geo-political zones, and between rural and urban areas. This assessment measures the size, skills mix, distribution, and growth rate of HRH in the public health sector in Nigeria. The assessment also quantifies the increase in HRH requirements in the public health sector necessary for reaching key PEPFAR targets and the health Millennium Development Goals. The findings are based on a survey conducted in April-May 2006 in 290 public health facilities representing all levels of care (primary, secondary, and tertiary). The study data enabled us to estimate the total number of doctors, nurses, midwives, lab and pharmacy staff, and community health workers currently employed in the public sector. The distribution of health workers by level of care, and HRH availability in rural and urban areas was also quantified.Staff attrition rates, measuring the number of those leaving the public sector as percent of total staff, were determined among all staff categories. The annual growth in HRH in the public sector from new graduates was also measured.

Geographic coverage

National

Analysis unit

Public Health Facilities

Universe

The survey focused on public health facilities representing all levels of care (primary, secondary, and tertiary).

Kind of data

Sample survey data [ssd]

Sampling procedure

Two-Stage Stratified Random Sample A survey was conducted in 290 public health facilities representing all levels of care (primary, secondary, and tertiary). The facilities were selected using two-stage stratified sampling. First, two states were selected from each of the six geo-political zones in Nigeria, with probability of selection of each state proportional to its population size. In addition, the Federal Capital Territory of Abuja (FCT) was added to the two states selected in the North Central zone. The selected states in each zone cover between 32 and 50 percent of the zone's population and in total, the 13 states included in the sample account for 40 percent of Nigeria's population. In the second stage of sampling, a sample of facilities at each level of care was chosen in each selected state. All Federal Medical Centers and teaching hospitals in the sampled states were selected with certainty. All other facilities were selected using systematic random sampling. A higher proportion of hospitals, compared to smaller facilities, were included in the sample in order to increase the number of facilities that have most of the data being collected. Primary care facilities include health centers, health clinics, maternities, and dispensaries. There was non-response from two facilities selected with certainty.

Mode of data collection

Face-to-face [f2f]

Research instrument

Data collection instrument In each of the selected facilities, a questionnaire was administered to eligible facility managers and health staff. These were staff in charge of the services included in the survey – for example, information regarding immunizations in a hospital was obtained from the nurse in charge at the hospital’s child health clinic. The questionnaire collected information on: 1. Number of staff employed in 2004, 2005, and at the time of survey (April 2006); 2. Number of incoming and outgoing staff in 2005 by reason for leaving or starting work at the facility; 3. Types of services provided at the facility for HIV/AIDS, TB, malaria, maternal and child health, and family planning; 4. Number of patients seen at the facility in the three months preceding the survey for each of these services; 5. Which types of health staff provide each service; 6. Average time spent per patient-visit for each of the services related to the five focus areas.

Cleaning operations

Data from the survey questionnaires was entered electronically using an EpiInfo database, and all data analysis was performed using Stata v.8 software.

As of 2018, health insurance coverage in Nigeria was very low. Specifically, less than *** percent of people with no education or a low education had a health insurance. Among individuals with more than a secondary education the coverage was larger, reaching **** percent of males and **** of females. People with a health insurance mainly had an employer-based coverage, whereas the percentage of individuals with specific health insurances was between zero and ***. About ** percent of the survey sample did not have a health insurance at all.

UNICEF's country profile for Nigeria, including under-five mortality rates, child health, education and sanitation data.

Background: Strengthening health systems to improve access to maternity services remains challenging for Nigeria due partly to weak and irregular in-service training and deficient data management. This paper reports the implementation of digital health tools for video training (VTR) of health workers and digitization of health data at scale, supported by satellite communications (SatCom) technology and existing 3G mobile networks.Objective: To understand whether, and under what circumstances using digital interventions to extend maternal, newborn and child health (MNCH) services to remote areas of Nigeria improved standards of healthcare delivery.Methods: From March 2017 to March 2019, VTR and data digitization interventions were delivered in 126 facilities across three states of Nigeria. Data collection combined documents review with 294 semi-structured interviews of stakeholders across four phases (baseline, midline, endline, and 12-months post-project closedown) to assess acceptability and impacts of digital interventions. Data was analyzed using a framework approach, drawing on a modified Technology Acceptance Model to identify factors that shaped technology adoption and use.Results: Analysis of documents and interview transcripts revealed that a supportive policy environment, and track record of private-public partnerships facilitated adoption of technology. The determinants of technology acceptance among health workers included ease of use, perceived usefulness, and prior familiarity with technology. Perceptions of impact suggested that at the micro (individual) level, repeated engagement with clinical videos increased staff knowledge, motivation and confidence to perform healthcare roles. At meso (organizational) level, better-trained staff felt supported and empowered to provide respectful healthcare and improved management of obstetric complications, triggering increased use of MNCH services. The macro level saw greater use of reliable and accurate data for policymaking.Conclusions: Simultaneous and sustained implementation of VTR and data digitization at scale enabled through SatCom and 3G mobile networks are feasible approaches for supporting improvements in staff confidence and motivation and reported MNCH practices. By identifying mechanisms of impact of digital interventions on micro, meso, and macro levels of the health system, the study extends the evidence base for effectiveness of digital health and theoretical underpinnings to guide further technology use for improving MNCH services in low resource settings.Trial Registration: ISRCTN32105372.

Abstract

The 2024 Nigeria Demographic and Health Survey (2024 NDHS) was implemented by the National Population Commission (NPC) under the aegis of the Federal Ministry of Health and Social Welfare (FMoHSW). Data collection was conducted from 1 December 2023 to 7 May 2024.

The primary objective of the 2024 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility and contraceptive use; maternal and child health; nutrition; childhood mortality; women’s empowerment; domestic violence; female genital mutilation (FGM); fistula; disability; knowledge, awareness, and behavior regarding malaria, tuberculosis, and HIV/AIDS and other sexually transmitted infections (STIs); and other health-related issues.

The information collected through the 2024 NDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Nigeria’s population. The survey 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 to 59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2024 NDHS was designed to yield representative results for the country as a whole, for urban and rural areas separately, for all six zones, and for the 36 states and the Federal Capital Territory. The sampling frame excluded institutional populations such as persons in hotels, barracks, and prisons. The 2024 NDHS employed a stratified two-stage sample design. 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. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were drawn with probability proportional to their size within each sampling stratum. A total of 1,400 clusters were selected, 701 in urban areas and 699 in rural areas.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 30 households per cluster were selected through an equal probability systematic selection process, for a total sample size of approximately 42,000 households. For each household, Global Positioning System (GPS) data were collected at the time of listing and during interviews.

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

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2024 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

The survey data were collected using tablet computers running the Android operating system and CSPro software, jointly developed by the United States Census Bureau, ICF, and Serpro S.A. English, Hausa, Yoruba, and Igbo questionnaires were used for collecting data via CAPI. The CAPI programmes accepted only valid responses, automatically performed checks on ranges of values, skipped to the appropriate question based on the responses given, and checked the consistency of the data collected. Answers to the survey questions were entered into the tablets by each interviewer. Supervisors downloaded interview data to their tablet, checked the data for completeness, and monitored fieldwork progress.

Each day, after completion of interviews, field supervisors submitted data to the central server. Data were sent to the central office via secure internet data transfer. The data processing managers monitored the quality of the data received and downloaded data files for completed clusters into the system. ICF provided the CSPro software for data processing and offered technical assistance in the preparation of the data capture, data management, and data editing programmes. Secondary editing was conducted simultaneously with data collection. All technical support for data processing and use of the tablets was provided by ICF.

Response rate

A total of 41,115 households were selected for the NDHS sample, of which 40,314 were found to be occupied. Of the occupied households, 40,047 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 39,553 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 39,050 women, yielding a response rate of 99%. In the subsample of households selected for the men’s survey, 12,426 men age 15–59 were identified as eligible for individual interviews and 12,204 were successfully interviewed, yielding a response rate of 98%.

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 2024 Nigeria Demographic and Health Survey (2024 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 2024 NDHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 and 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2024 NDHS sample was the result of a multistage stratified cluster design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF. These programmes use the Taylor linearization method to estimate variances for survey estimates that are means, medians, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility rates and mortality rates.

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 - Age displacement at ages 14/15 - Age displacement at ages 49/50 - Pregnancy outcomes by years preceding the survey - Completeness of reporting - Standardization exercise results from anthropometry training - Height and weight data completeness and quality for children - Height measurements from random subsample of measured children - Interference in height and weight measurements of children - Interference in height and weight measurements of women - Heaping in anthropometric measurements for children (digit preference) - Observation of mosquito nets - Observation of handwashing facility - School attendance by single year of age - Vaccination cards photographed - Number of enumeration areas completed by month and zone - Prevalence of anaemia in children based on 2011 WHO guidelines - Prevalence of anaemia in women based on 2011 WHO guidelines

See details of the data quality tables in Appendix C of the final report.

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

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

Nigeria NG: Current Health Expenditure Per Capita: Current Price data was reported at 0.000 USD mn in 2015. This records a decrease from the previous number of 0.000 USD mn for 2014. Nigeria NG: Current Health Expenditure Per Capita: Current Price data is updated yearly, averaging 0.000 USD mn from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.000 USD mn in 2014 and a record low of 0.000 USD mn in 2000. Nigeria NG: Current Health Expenditure Per Capita: Current Price 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: Health Statistics. Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;