{"doc_desc":{"title":"NCLS_2022","idno":"DDI-NGA-NBS-NCLS-2022-v01","producers":[{"name":"National Bureau of Statistics","abbr":"NBS","affiliation":"Federal Government of Nigeria ","role":"Producer"}],"prod_date":"2024-05-15","version_statement":{"version":"Version 1.0"}},"study_desc":{"title_statement":{"idno":"NGA-NBS-NCLS-2022-v01","title":"Nigeria Child Labour Survey 2022","sub_title":"First round","alternate_title":"NCLS 2022"},"authoring_entity":[{"name":"National Bureau of Statistics (NBS)","affiliation":"Federal Government of Nigeria (FGN)"}],"oth_id":[{"name":"Government of the Netherlands","affiliation":"","email":"","role":"Funding"},{"name":"United States Department of Labor (USDOL)","affiliation":"","email":"","role":"Funding"}],"production_statement":{"producers":[{"name":"International Labour Organization","abbr":"ILO","affiliation":"","role":"Funding and Technical Support"},{"name":"Federal Ministry of Labour and Employment","abbr":"FMLE","affiliation":"Federal Government of Nigeria (FGN)","role":"Technical Support"}],"copyright":"(c) 2024, National Bureau of Statistics","funding_agencies":[{"name":"International Labour Organization","abbr":"ILO","role":"Funding"}]},"distribution_statement":{"contact":[{"name":"Prince Adeyemi Adeniran","affiliation":"National Bureau of Statistics (NBS)","email":"sg@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"},{"name":"Mr. Fafunmi E.A","affiliation":"National Bureau of Statistics (NBS)","email":"biyifafunmi@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"},{"name":"Mr. Mustapha","affiliation":"National Bureau of Statistics (NBS)","email":"mdazeez@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"},{"name":"Abiola Aronsanyin","affiliation":"National Bureau of Statistics (NBS)","email":"avarosanyin@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"},{"name":"Saheed Bakare","affiliation":"National Bureau of Statistics (NBS)","email":"ssbakare@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"}]},"series_statement":{"series_name":"Child Labor Survey [hh\/cls]"},"version_statement":{"version":"v1.0 anonymized microdata","version_date":"2022-05-08","version_notes":"This dataset is the cleaned anonymized dataset of the Nigeria Child labour Survey 2022."},"study_info":{"keywords":[{"keyword":"Economic Activities","vocab":"","uri":""},{"keyword":"Hazardous Work","vocab":"","uri":""},{"keyword":"Child Labour","vocab":"","uri":""}],"topics":[{"topic":"Child Labour","vocab":"ILO","uri":""}],"abstract":"This  report aims  to assess the prevalence of child labour in Nigeria and analyse the interaction between child  labour, schooling and children's well-being. Using data collected by the National  Bureau of Statistics in collaboration with the ILO and the Federal Ministry of Labour and Employment of Nigeria in the Nigeria Child Labour and Forced Labour Survey (NCFLS) 2022, this report also examines  the patterns of child employment, the conditions of this employment and the key household  characteristics that may contribute to child employment and child labour.\n\nMore than 62.9 million children 5 to 17 years old live in Nigeria,  representing 30.3 per cent of the population. The NCFLS data was collected from a nationally representative sample of 16,418 households. The survey shows that more children live in rural areas than urban areas: 62.4 per cent (39,252,721) reside in rural areas compared to 37.6 per cent (23,647,758) in urban areas.\n\nThe current survey allowed for the classification of children 5 to 17 years old into four  mutually exclusive categories: children who are exclusively working, children who are exclusively in school, children who  are working and  in school, and children who neither work nor go to school. The survey indicates that among the 5-14 age group,\n42.3 per cent are full time students who are not engaged  in any form of economic  activity, 35.3 per cent are in school and working simultaneously, and 11.2 per cent are working only. Among the  15-17 age group, a  larger proportion of children are working only, at 21.9 per cent of the population of that age. Furthermore, only 24.7 per cent are exclusively  in school and 45.3 per cent are working and in school.\nSince one of the survey's main objectives is to measure child  labour, it is important to understand the legislative structure surrounding child labour in Nigeria. In the country, the Child Rights Act (2003)  prohibits children  in the 5-11  age group  from engaging in any economic  activity but allows children  12 to 14 years olds to engage in light work, while those in the 15-17 age group are allowed to be involved in economic activities that are not hazardous.\n\nThe survey shows that 24,673,485 children  5 to,17 years old (39.2 per cent) are in child labour; of children in child labour, 60.8 per cent (14,990,674) are in the 5-11  age group, 20.8 per cent(5,132,574) are in the 12-14 age group  and  18.4 per cent (4,550,237) are in the 15-17 age group  (table A.7). A slight percentage difference can be seen in the prevalence of child labour between  males (39.6 per cent) and females (38.8 per cent). The disparity between children residing  in rural and urban areas is high; while 44.8 per cent of children in rural areas are involved in child labour, 30.0 per cent of children in urban areas are involved in child labour.\n\nSubstantial differences are evident by age group in children's involvement in economic  activity, child labour and hazardous work. Overall, of children 5 to 17 years old, 50.5 per cent (31,756,302 children) are engaged  in economic activity, 39.2 per cent (24,673,485) are involved in child labour and 22.9 per cent (14,390,353) are involved  in hazardous work. For the 5-11  age group, 40.7 per cent (14,990,674) are in economic  activity and, therefore, the same number  and percentage of children of that age are in child  labour as children under the age of 11  cannot work,' and 15.8 per cent (5,824,667) are in hazardous work. For children in the 12-14 age group, 61.9 per cent (8,583,312) are in economic activity, 37.0 per cent (5,132,574) are in child labour and 29.0 per cent (4,015,447) are in hazardous work. Among  the children in the 15-17 age group, 67.1  per cent (8,182,316) are in economic activity and 37.3 per cent (4,550,237) are in child labour since, for this age group, only children that are in hazardous work are considered as being  in child  labour. Therefore, 37.3 per cent (4,550,237) also represents the percentage of 15- to 17-year-olds in hazardous work.\nThe involvement in economic activity of children in child labour can be broken  down  into three distinct  non-mutually exclusive forms of work: employment, own-use  production and unpaid trainee work. Of the children in child labour, 24.2 per cent are in employment, 93.8 per cent are involved in own-use  production and 11.3 per cent are involved in unpaid trainee work.\n\nFocusing  on children in  child labour who are  in the form of work qualified as employment allows an analysis of their involvement in child labour by the branch of economic activity in which they are employed (agriculture, industry or services). Most of the  children  5 to 17 years  old in  child labour who are in employment work in the agriculture sector (56.8 per cent). Of the remaining  children in employment and child labour, 25.8 per cent are employed  in the service sector and 17.4 per cent are employed in the industry sector.\n\nThis survey also provides  information on how school attendance interacts with child labour. The results show that school attendance is negatively affected  by child labour. A total  of 81.4 per cent of children 6 to 14 years old not in child labour attend school, while this figure falls to 75.1  per cent for children in child labour.\n\nA final  important facet of the survey is the information it provides on the instance of injury among children in child labour. Of these children, 16.3 per cent have experienced an injury in the workplace. This reveal that many children experience direct harm from their involvement in child labour.","coll_dates":[{"start":"2022-04-07","end":"2022-04-20","cycle":""}],"nation":[{"name":"Nigeria","abbreviation":"NGA"}],"geog_coverage":"The survey was carried out to produce estimates at the national, regional and state levels.","analysis_unit":"Children that are between 5 to 17 years of age in Nigeria\u2019s Households","universe":"The target population comprises Children in Nigeria's households primarily concerned with children's activities and child labour topics, characterized by its single-subject focus.","data_kind":"Sample survey data [ssd]","notes":"The Child Labour Survey covered the following subject areas:\n\u2022\tIdentification\n\u2022\tHousehold Roster and Demographic\n\u2022\tEducation\n\u2022\tForms of Work\n\u2022\tHazardous Work\n\u2022\tHousehold Tasks\n\u2022\tHousing"},"method":{"data_collection":{"data_collectors":[{"name":"National Bureau of Statistics","abbr":"NBS","role":"","affiliation":"Federal Government of Nigeria (FGN)"}],"sampling_procedure":"The sample design for the survey was based on the National Integrated Survey of Households (NISH) master sample design developed by the NBS. This was developed from the frame of EAs demarcated by the National Population Commission for the 2006 housing and population census. The NISH design employed a replicated sampling design, a technique by which many samples (replicates) were selected independently\nfrom a population such that each replicate sample represents the population.\nBasically, the NISH sample design is a two-stage, replicated and rotated cluster sample design with EAs as the primary sampling units, and households as the secondary sampling units. Generally, for each Nigerian state and the FCT, the NISH master sample is made up of 200 EAs drawn into 20 replicates. A replicate consists of ten EAs.\n\nThe calculation of the sample size used the design effect of 1.2. Other parameters for the sample size calculation included the predicted value of the prevalence rate (40 per cent); the relative margin of error at 95 per cent confidence (5 per cent); the proportion of the target population in the base population (36.07 per cent); the average household size (5.06); and the expected response rate of households (95 per cent). The sample size of the survey was designed to provide state estimates of the prevalence of child labour with standard errors of about 1 per cent [r*RME\/2 = 40%*5%\/2 = 1%] under simple random sampling (RME = relative margin of error).\n\nThe sample design of the survey was based on a stratified two-stage sampling technique. In the first stage of sampling, 30 EAs were selected as part of a master sample in each of the 36 states and the FCT. In total, 1,110 EAs formed the primary sampling units of the survey. In the second stage, 15 households were systematically selected in each of the EAs. The target sample size was 16,650 households. All children 5 to 17 years\nold living in the households were interviewed.","sampling_deviation":"The sample of the 2022 NCLS was targeted at 16,650 households but the number of households interviewed was slightly lower than anticipated (16,418)  due to relocation and unavailability of some households.","coll_mode":["Computer Assisted Personal Interview [capi]"],"research_instrument":"The questionnaire followed the model developed by ILO, comprised of three main parts. The first part covered all household members\u2019 socio-demographic characteristics, economic activities and perceptions of children\u2019s parents or guardians about child labour. The second part collected information on housing and accommodation, while the third part focused on children\u2019s education, working status, health and welfare in employment as well as their safety in the workplace.\n\nThe questionnaire comprised eight sections:\n-Section A: Identification\n-Section B: Household roster and demographics\n-Section C: Education\n-Section D: Forms of work\n-Section E: Hazardous work\n-Section F: Household tasks\n-Section G: Forced labour\n-Section H: Housing","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"Two levels of training were organized. The first level was the training of trainers conducted from 28 to 30 March 2022. At this level, the participants trained were NBS and Federal Ministry of Labour and Employment staff and other members of the technical committee, who served as trainers for the second level of training as well as monitors\/quality assurance officers during the fieldwork.The participants included 74 trainers, 12 coordinatorsand other stakeholders. The training lasted three days.\n\nThe second level of the training was the training of field personnel carried out from 4 to 6 April 2022. At this level, the training of field personnel took place in the 36 states and the FCT. In total,444 field personnel (111 team leads and 333 teammates), 37 state officers and six zonal controllers were trained nationwide. To ensure quality data collection, experienced field staff were engaged due to the sensitivity and peculiarity of the survey.Training sessions for the field personnel included an overview of the survey and its objectives, techniques for interviewing, a detailed description of all questionnaire sections, computer-assisted personal interviewing (CAPI) training and mock interviews. The training lasted three days.\n\nThe selection criteria considered during the recruitment process were education level (having at least a National Diploma), knowledge of the local language and experience of data collection in similar national surveys.\nA total of 12 field personnel were engaged in each state and the FCT. Three teams comprising three teammates and one team lead were constituted. The teams worked in a roving manner by completing interviews in one EA before moving to the next, until the ten EAs assigned to each team were completed. The fieldwork lasted 12 days including travelling time from one EA to the next and from one local government area to another as well as the time for callbacks to the households from 7 to 20 April 2022. Data was collected using CAPI devices and transmitted to the NBS server in real time online","act_min":"Adequate physical monitoring and spot-checks were carried out by Monitors both from the National Bureau of Statistics (NBS) and Federal Ministry of Labour and Employment (FMLE).The monitoring of fieldwork  started concurrently with the commencement of data collection to ensure a smooth start to the data collection effort.\n\nThe activities carried out included:\n\u00b7\tVisitation of different teams in various States\n\u00b7\tResolving observable challenges that called for urgent attention.\n\u00b7\tCollaborating with the state officers to reach out to enumerators, and discuss observations, comments and to proffer solutions where necessary.\n\u00b7\tSpot-checking of  Householdss where enumerators visited and interviewed\n\u00b7\tOnline real-time data monitoring and immediate feedback.","weight":"The probability weight of the household was produced by taking the inverse of the probability to select the household (probability products obtained at each sampling stage). Weights were calculated by multiplying the probability of selection of EAs by the probability of selecting the households within the EAs and then taking the inverse of the product. An adjustment was made for non-responses before the final weight was applied to the dataset. Final weight values were further calibrated to follow the national population distribution by state.","cleaning_operations":"The questionnaire was programmed using the Census and Survey Processing System software (Cspro) and CAPI for data capturing. A team responsible for data quality protocols was established for real- time online data checks, comprising a data administrator, who ensured the connectivity of CAPI devices to the server and monitored the downloading and uploading of data to and from enumerators in the field, as well as data editors, who checked for errors in the data downloaded from the server and communicated any corrections or requested clarification from the enumerators."},"method_notes":"After the data was downloaded from the webbased system, a process of data cleaning was performed to prepare the data for the statistical analysis. This process implied the creation of unique datasets including household and individual information to allow for an analysis of children\u2019s activities by variables describing the household\u2019s context. Data cleaning was performed by an expert using Stata statistical software. Moreover, the results in this report accounted for the complex sampling strategy by considering clustering, stratification and weighting. According to the sampling strategy, estimates and standard errors were adjusted using the survey weights.","analysis_info":{"response_rate":"NCLS 2022 was targeted at 16,650 households but in total 16,418 households were visited and interviewed, which represents a response rate of 98.6 per cent.","sampling_error_estimates":"Given the sample design, sampling errors were estimated through simple random sampling approach."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The confidentiality of the individual respondent is protected by law (Statistical Act 2007)\nThis 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.","required":"yes","form_no":"","form_uri":""}],"contact":[{"name":"National Bureau of Statistics (NBS)","affiliation":"Federal Government of Nigeria (FGN)","email":"feedback@nigerianstat.gov.ng","uri":"www.nigerianstat.gov.ng"}],"cit_req":"National Bureau of Statistics, Nigeria, Nigeria Child Labour and Forced Labour Survey (NCLS 2022)-v1.0","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.","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."}}},"schematype":"survey"}