NBS Website | Register | Login
Login
NATIONAL BUREAU OF STATISTICS
An Online Microdata Catalog
  • Home
  • Microdata Catalog
  • Contact
    Home / Central Data Catalog / NGA-NBS-NTUS-2024-V1.0.
central

Nigeria Time Use Survey 2024
First round

Nigeria, 2024 - 2025
Get Microdata
Reference ID
NGA-NBS-NTUS-2024-v1.0.
Producer(s)
National Bureau of Statistics
Collections
SOCIAL AND DEVELOPMENTAL STATISTICS
Metadata
DDI/XML JSON
Created on
Jan 16, 2026
Last modified
Jan 16, 2026
Page views
3319
Downloads
22
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data processing
  • Data appraisal
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    NGA-NBS-NTUS-2024-v1.0.

    Title

    Nigeria Time Use Survey 2024

    Subtitle

    First round

    Abbreviation or Acronym

    NTUS 2024

    Translated Title

    No translation

    Country
    Name Country code
    Nigeria NGA
    Study type

    Other Household Survey [hh/oth]

    Abstract

    The Nigeria Time Use Survey (NTUS) 2024 marks a significant milestone as the country's first stand-alone effort to systematically measure how individualsallocate their time across paid and unpaid work, personal care, and leisure activities.The exercise provides robust empirical evidence to inform gender-sensitive policy design,development planning, and the implementation of global and national commitments,particularly to Sustainable Development Goal (SDG) 5.4.1 on unpaid care and domestic work.

    The International Classification of Time Use Statistics (ICATUS) 2016 was followed to make the time use statistics comparableand standard. The NTUS employed a three stage stratified sampling design, covering a total of 3,600 households and yielding data from 6,431 individuals aged 15 years and above. Data was collected through a faceto-face personal interview using Computer Assisted Personal Interviewing (CAPI) devices.

    The survey revealed that 28.1% of participating households were located in rural areas, while 71.9% were in urban areas. Across the studied states, the household headship breakdown showed that 81.9% of households were headed by males while 18.1% were headed by females.Furthermore, among households headed by females, 81.0% were situated in urban areas, while 19.0% were in rural areas. Similarly,households headed by males, 69.9% live in urban areas and 30.1% live in rural areas.

    On average, people aged 15 years and above spent 12.5% of their day (3 hours) on unpaid domestic and care work.Disaggregated by sex, women dedicated 21.0% of their day (5 hours) to unpaid domestic and care work, while men spent 4.1% of their day (roughly 1 hour). The gender disparity is pronounced across both urban and rural areas. Rural women spent higher proportion of time (24.1% - almost 6 hours) on unpaid domestic and care work, compared to rural men (3.7% - less than an hour). Similarly, urban women spent more time (19.8% - almost 5 hours) than urban men (4.3% - one hour). These differences highlight deeply rooted gender roles and unequal distribution of unpaid work within households, which shows that women consistently spent more time on unpaid domestic and care work than men among the studied states.

    The result further reveals that, women spent 5.9% of their day compared to 1.2% by men in unpaid care services. Also, in unpaid domestic work, women spent higher time 15.1% compared to men with 2.9%. In all, women spent five times the hours that men spent on unpaid domestic and care work in the four surveyed states. This pattern was held across urban and rural locations and across wealth quintiles.

    The data shows level of participation of men and women in broad activities. Men participated more in SNA productive activities (80.3%) than women with 73.7%. In contrast, women engaged more in non-SNA activities (97.1%) than men with 66.6%.The participation rate in learning was more for men with 15.2%, while women had 10.5%. The trend remains the same in both urban and rural areas. There exists a significant disparity in the time spent by men and women on SNA and non-SNA productive activities. While men spent more time than women on SNA activities, the reverse is the case for non- SNA activities. For instance, men spent372.6 minutes on SNA activities, and women spent 234 minutes on the same activity. On the other hand, men spent 79.3 minutes on non-SNA activity while women spent 314.3 minutes.In addition, women and men spent slightly different amounts of time on learning activities. Men spent 46.1 minutes, and women spent 31.5 minutes. Even thoughmen and women spent a significantproportion of their time on other nonproductive activities such as sleeping, relaxing, socializing, religious activities, etc.,time spent on them was still higher for men.

    In conclusion, Time Use Survey 2024 offers a disaggregated portrait of how individuals allocate their time in the four (4) studied states, with a special focus on unpaid care and domestic work. The results emphasize the need for targeted investments in care infrastructure, gender equality reforms, and policies that recognize and redistribute unpaid work. The integration of time-use statistics into Nigeria's regular statistical reporting will enhance the country's ability to monitor progress on inclusive development and gender equality.

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    Individual

    Version

    Version Description

    v1.0 anonymized microdata

    Version Date

    2025-03-10

    Version Notes

    This dataset is the anonymized version of the cleaned dataset of the Nigeria Time Use Survey, 2024.

    Scope

    Notes

    The Scope of the Nigeria Time Use Survey includes:

    HOUSEHOLD QUESTIONNAIRE

    SECTION A: IDENTIFICATION INFORMATION
    SECTION 1: LIST OF HOUSEHOLD MEMBERS (all members of household)
    SECTION 1B:LIST OF HOUSEHOLD MEMBERS (For Care Household members)
    SECTION 2:HOUSEHOLD CHARACTERISTICS
    SECTION 3: AGRICULTURAL HOUSEHOLD
    SECTION 4:HOUSEHOLD EARNINGS

    INDIVIDUAL QUESTIONNAIRE

    SECTION A: IDENTIFICATION INFORMATION
    SECTION 1: EDUCATION AND ICT USE
    SECTION 2:AGRICULTURAL LAND OWNERSHIP AND TENURE RIGHTS
    SECTION 3:EMPLOYMENT STATUS (Selected members, 15 years or older)
    SECTION 4: HEALTH (Selected members, 15 years or older)
    SECTION 5:ACCESS TO SOCIAL PROTECTION PROGRAMS (Selected members, 15 years or older)
    SECTION 6: PERCEPTION BASED QUESTIONS (For the selected members, 15 years or older) (Please ask this section after the Time Diary)

    NIGERIA TIME USE DIARY QUESTIONNAIRE
    TIME IN 24 HRS BETWEEN 4:00AM YESTERDAY AND 3:59AM TODAY
    MAIN ACTIVITY
    SECONDARY ACTIVITY

    Coverage

    Geographic Coverage

    State Sector

    Universe

    Household Members

    Producers and sponsors

    Primary investigators
    Name Affiliation
    National Bureau of Statistics Federal Government of Nigeria (FGN)
    Producers
    Name Role
    United Nations Women Techinical Support
    Kenya Bureau of Statistics Techinical Support
    Funding Agency/Sponsor
    Name Abbreviation Role
    United Nations Women UN Women Funding

    Sampling

    Sampling Procedure

    The sample for the Time Use Survey (TUS) was designed to produce representative estimates for four selected states in Nigeria-Borno, Cross River, Kaduna, and Lagos-across two seasonal rounds (dry and wet seasons). In each state, 60Enumeration Areas (EAs) were selected; 30 EAs during the dry season and 30 EAs during the wet season, allowing for seasonal analysis of time-use patterns.

    From each selected EA, 15 households were sampled, resulting in 900 households per state and 3,600 households in total across the four states. This allocation provided enough sample to enable disaggregation by season and by key demographic characteristics within each state.

    The TUS employed a three-stage stratified sampling design to ensure representativeness and efficiency in data collection.
    The techniques used at each stage are as follows:

    Stage 1: Selection of Enumeration Areas (EAs)
    A total of 60 EAs were selected in each state using Probability Proportional to Size (PPS) sampling. The size measure was based on the number of households in each EA from the updated digitized Enumeration Area Demarcation (EAD) conducted by the National Population Commission (NPC) in 2023. This method ensures that larger EAs have a proportionally higher chance of being selected, preserving representativeness.

    Stage 2: Selection of Households
    In each selected EA, 15 households were drawn using Systematic Random Sampling. A household listing operation was first carried out to update the number of households in the EA. Based on this list, the sampling interval was calculated and used to systematically select households.

    Stage 3: Selection of Individuals Within each sampled household, two eligible individuals aged 15 years and above were selected using the Kish Grid Sampling Method. This approach ensured gender balance by selecting one male and one female respondent per household, unless only one gender was available. The Grid method promotes randomness while enabling balanced representation in line with time-use survey standards.

    Sampling Frame

    The sampling frame for the TUS was the master sample frame maintained by the National Bureau of Statistics (NBS). This frame was developed from the 2023 digitized Enumeration Area Demarcation (EAD) conducted by the National Population Commission (NPC) as part of the preparations for the national population and housing census. The frame provided a reliable and up-todate listing of EAs, including geospatial and household count data, from which the survey sample was drawn.

    Deviations from the Sample Design

    No Deviations

    Response Rate

    The survey achieved high response rates across both rounds and states. Detailed field supervision and effective interviewer training contributed to minimizing nonresponse.

    Replacement of household took place at all the state both in wet and dry season but individuals were not replaced.

    The household response rate are 100% and 99.7% in both dry and wet season respectively.

    Weighting

    Two sets of sampling weights were computed to ensure that survey estimates accurately reflect the population:

    Seasonal Weights: Developed separately for dry and wet seasons,these incorporate the probability of selection at each sampling stage and adjust for non-response.

    Combined Weights: A composite weight was created for pooled analysis across seasons, properly balancing the dry and wet season contributions.

    In addition, post-stratification adjustments were applied using external population totals to align the sample with known distributions by age group and gender. This improves precision and reduces bias in the final estimates.

    Survey instrument

    Questionnaires

    Three structured questionnaire were used for NTUS which are as follows:

    The Household Questionnaire was administered in each household, which collected various information on Identification, list of household members including members cared for,household characteristics,agricultural household and household earnings.

    The Individual Questionnaire which was administered two selected household member who are 15 years and above using the Kish Grid method collected information on identification.education and ICT use,Agricultural land ownwership and Tenure rights,Employment status,Health,Access to Social Protection Programmes and Perception based questions.

    The Time Use diary Questionnaire collected information on main and secondary activities that was carried out by slected household members in 24 hours from 4:am the previous day to 3:59am on the day of interview.

    Methodology notes

    The data processing activities for the mapping and listing exercise, main survey was executed using the census and survey processing software (CSPro) to develop the application for the listing data collection and main survey.

    A data cleaning team was also set up, which cleaned the data in CSPro, SPSS, and Stata prior to its analysis.

    Cleaning of the data was done by comparing the entries in the other common modules (household characteristics, education, housing, labour), and correctionfor errors on the activities’ (ICATUS) codes was done by cross checking with the descriptions provided by the interviewers such that the coded activities were compared and corrected where a wrong code was assigned to a particular description.

    Data collection

    Dates of Data Collection
    Start End
    2024-08-22 2025-03-10
    Mode of data collection
    • Face-to-face [f2f]
    Data Collectors
    Name Affiliation Abbreviation
    National Bureau of Statistics Federal Government of Nigeria (FGN) NBS
    Supervision

    The overall coordination on all aspects of the survey was carried out by the National Bureau of Statistics Directorate Members and the Technical Working Committee.

    Data Collection Notes

    Computer-assisted Personal Interviewing(CAPI) devices were used for the main survey Fieldwork. One team worked per state, each state team comprised of five (5)members (one (1) team lead & four (4) teammates.Each team covered sixty (60) Enumeration Areas, fifteen (15) HHs covered in each EA, making a total of 3600 HHs for the 4 states for both wet and dry seasons.

    During the data collection, Google Maps was used to trace the location of the Enumeration area (EA). While Google Earth was then used to trace the boundaries of the Enumeration area to avoid overcoverage and under coverage or wrong EA. The software used supported the proper mapping procedure of identifying interviewers capturing data outside the EA boundaries.

    Face-to-face interviews were conducted using the computer-assisted personal interviewing (CAPI) device

    Data processing

    Data Editing

    A team responsible for data quality protocols was established for real-time online data checks,comprising:

    1. A data administrator who ensured the connectivity of the CAPI devices to the server, monitored downloading and uploading of data to and from enumerators in the field.The administrator also ensured the smooth running of the server.

    2. CAPI Managers ensured the proper working condition of all tablets linked to the server, proffers solution to any breakdown in communication to any of the devices.

    3. HQ Supervisors aggregate the data daily and check for errors from the fieldwork. They generate an error report, which they sent to data editors to verify the true status of the error from the enumerators.They provide remote support and monitor field work via reports, etc.

    4. Data Editors are responsible for checking error reports generated from the HQ supervisors and communicating with the enumerators for any corrections or clarifications.

    5. IT Coordinators are the senior management staff whose key responsibility is to coordinate the entire activities of the data management process and ensure the smooth workflow of the system

    Data appraisal

    Data Appraisal

    A series of data quality tables are available in the report.

    Data Access

    Access authority
    Name Affiliation URL Email
    National Bureau of Statistics (NBS) Federal Government of Nigeria (FGN) www.nigerianstat.gov.ng feedback@nigerianstat.gov.ng
    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes The confidentiality of the individual respondent is protected by law (Statistical Act 2007) This is published in the Official Gazette of the Federal republic of Nigeria No. 60 vol. 94 of 11th June 2007. See section 26 para.2. Punitive measures for breeches of confidentiality are outlined in section 28 of the same Act.
    Access conditions

    A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007 outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.

    Citation requirements

    National Bureau of Statistics, Nigeria, Nigeria Time Use Survey (NTUS 2024)-v1.0

    Disclaimer and copyrights

    Disclaimer

    The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

    Copyright

    (c) 2026, National Bureau of Statistics

    Contacts

    Contacts
    Name Affiliation Email URL
    Prince Adeyemi Adeniran National Bureau of Statistics (NBS) sg@nigerianstat.gov.ng www.nigerianstat.gov.ng
    Mr Akinloye Adeyeye Elutade National Bureau of Statistics (NBS) aaelutade@nigerianstat.gov.ng www.nigerianstat.gov.ng
    Dr Salihu Siyaka Itopa National Bureau of Statistics (NBS) sisalihu@nigerianstat.gov.ng www.nigerianstat.gov.ng
    Ms Christy Umuna National Bureau of Statistics (NBS) christyumunna@nigerianstat.gov.ng www.nigerianstat.gov.ng

    Metadata production

    DDI Document ID

    DDI-NGA-NBS-NTUS-2024-v1.0

    Producers
    Name Abbreviation Affiliation
    National Bureau of Statistics NBS Federal Government of Nigeria (FGN)
    Date of Metadata Production

    2026-01-15

    Metadata version

    DDI Document version

    Version 1.0

    Back to Catalog
    National Bureau of Statistics | Microdata Catalog

    © National Bureau of Statistics | Microdata Catalog, All Rights Reserved.