The number of children in labor worldwide amounted to 160 million in 2020. In the same year 79 million children globally were working in hazardous work environment.

In 2020, 60 percent of children in labor in Sub-Saharan Africa were aged between five and eleven years. The share of working 15 to 17 year olds in the same region was at 16.4 percent. Worldwide, 55.8 percent of working children were aged five to 11 years old.

Chad TD: Average Working Hours of Children: Working Only: Male: Aged 7-14: Hours per Week data was reported at 13.046 Hour in 2015. This records an increase from the previous number of 8.800 Hour for 2010. Chad TD: Average Working Hours of Children: Working Only: Male: Aged 7-14: Hours per Week data is updated yearly, averaging 10.923 Hour from Dec 2010 (Median) to 2015, with 2 observations. The data reached an all-time high of 13.046 Hour in 2015 and a record low of 8.800 Hour in 2010. Chad TD: Average Working Hours of Children: Working Only: Male: Aged 7-14: Hours per Week data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Labour Force. Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.;Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.;;

As of 2023, among the child population in El Salvador, the sector with the lowest number of children engaged in labor was the one that adhered to regulations and did not involve hazardous work. This comparison highlights the issue of child labor, particularly the presence of children involved in dangerous occupations.

In 2020, 72.1 percent of children in labor worldwide were contributing family workers. In Latin America and the Carribean 42.1 percent of employed five to 17 year olds were working for someone else outside of their family.

Abstract

The Royal Government of Cambodia has placed the issue of child labour 2001 high on its agenda, and in recent years has made a large number of interventions, in cooperation with international, regional organizations, NGOs, and other partners. For Cambodia, like the rest of the world, there are many issues that need to be addressed in order to ensure the effective abolition of child labour. Eliminating child labour in Cambodia is one of the most urgent challenges of our time.

Geographic coverage

National (24 provinces) - Phnom Penh, Other Urban and Other Rura

• Urban/Rural

Analysis unit

households, individuals and children aged 5-17 years

Universe

The survey covered all household members and children aged 5 to 17 years residing in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for CCLS 2001 was a stratified sample selected in two stages. At the first stage, the villages (primary sampling units or PSUs) were selected from the list of villages for every stratum within the domains listed in order of: province/city, district, commune and village. The method of circular systematic sampling with the probability of inclusion of a village proportional to its size (CSS-PPS) was used to select the villages. In addition to the code for the above, the sampling frame contained identification particulars: the name of the villages as well as the number of households in the village as known at that time. The number of households in the village identified in the sampling frame was taken as its size. The actual number of households in selected villages was obtained later by direct listing. In this method, the actual number of households was generally different from the number recorded in the sampling frame. To avoid ambiguity, the number of households in a village as recorded in the sampling frame will always be referred to as its size. In other words, the number of households in the village was used as the measure of size. Sample village selection was done through the use of a computer program.

At the second stage of selection, for each sample village, or PSU (except for large villages), a field listing operation was undertaken. Large villages comprising about 210 households, based on the current household estimates by the village leaders, were segmented first. A segment was then chosen randomly and a complete listing of households was prepared. This entailed carrying out a complete canvass of the PSU in order to make a current and complete listing of households contained within. The procedure involved creating a sketch map of the PSU where physical boundaries in the village and the location of each household were sketched. Canvassing entailed a systematic covering of the entire village following a prescribed path of travel in order to make sure that all housing units in which the households reside were accounted for. After the listing operation was completed, a fixed sample size of 20 households was selected in each PSU. The selection was carried out using circular systematic random sampling with a random start (CSS).

Detailed discussion is provided in Sampling.pdf document.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Cambodia Child Labour survey 2001 used three forms:

Form 1: Questionnaire for Households

Form 2: Questionnaire for Parents/Guardians of Children Ages 5 to 17 in the Household

Form 3: Questionnaire for Children Ages 5 to 17 in the Household

The household questionnaire (Form 1) included demographic characteristics of all household members, migration status of the household (in the last five years), migration status of children 5 to 17 years of age, housing conditions, household income and expenditures, usual economic activity of household members 5 years old and over during the last 12 months, current economic activity of household members 5 years and over during the past 7 days, earnings and hours of work of household members 5 years old and over who worked (according to the main activity during the past 7 days and other activities during the past 7 days).

In the questionnaire about children aged 5 to 17 in the households (Form 2), queries all children 5 to 17 years old were addressed to parents, guardians, or responsible proxies in the household where the child usually resides. This form contained questions on housekeeping activities/household chores of children 5 to 17 years old; children 5 to 17 years old who were idle/did not do anything during the past 7 days; health and safety of children 5 to 17 years old who had worked at any time; place of work/employer of children 5 to 17 years of age currently working; children 5 to 17 years working as employees for someone else for payment in cash or in kind or without any payment; perception of parents/guardians or other relatives with whom the working child usually resides.

In the questionnaire for children (Form 3), the questions were addressed to children 5 to 17 years of age: hours actually worked, economic activities, age started to work for the first time, currently or usually worked, health and safety of working children, working conditions and perceptions of working children.

The statistical information on hazardous child labour was collected through an establishment survey. Selection of establishments was based on the results of the household-based child labour survey, and establishments found to employ child labour were identified for a follow-up survey by interviewers with the employers and the children identified as child workers.

Cleaning operations

Data editing took place at the following stages of data processing:

1. On the field: Manual editing on the done by supervisors.

2. Questionnaire reception at NIS: Manual editing and coding done by 15 manual editing personnels at NIS.

3. During data entry: Re-entry of data in the questionnaires to confirm legitimacy of the entries.

4. Correctness, completeness, range validity and consistency checking: An editing program was developed to check and valiadate data files and produce error printouts from modification.

5. Verification of database with other sources

6. Data quality tabulation: With the preliminary tables generated, data validation work was carried out and range checks built were reviewed.

Processing of CCLS 2001, from data entry to tabulations, was done with the use of the Integrated Microcomputer Processing System (IMPS) of the US Bureau of Census. Twenty (20) Machine Encoders (including 2 Supervisors) were trained before the start of machine encoding activities.

Response rate

Not Computed

Sampling error estimates

Since most of the estimates from the survey are in the form of weighted ratios, variances for ratio estimates were thus presented.

Please see Appendix A in the report on Cambodia Child Labour Survey 2001.

In accordance with the ICLS resolutions,14 child labour can be measured on the basis of the production boundary set by the United Nations System of National Accounts (SNA) or on the basis of the general production boundary. The former limits the frame of reference to economic activity, while the latter extends it to include both economic activity and unpaid household services, that is, the production of domestic and personal services by a household member for consumption within their own household, commonly called household chores.

Following from this, two indicators are used for measuring child labour for the purpose of SDG reporting, the first based on the SNA production boundary and the second on the general production boundary.

Indicator 1: Proportion and number of children aged 5 to 17 years engaged in economic activities at or above age-specific hourly thresholds (SNA production boundary basis): Child labour for the 5 to 11 age range: children working one hour or more per week in economic activity; Child labour for the 12 to 14 age range: children working 14 hours or more per week in economic activity; Child labour for the 15 to 17 age range: children working 43 hours or more per week in economic activity.

Indicator 2: Proportion and number of children aged 5 to 17 years engaged in economic activities and household chores at or above age-specific hourly thresholds (general production boundary basis): Child labour for the 5 to 11 age range: children working one hour or more per week in economic activity and/or involved in unpaid household services for 21 hours or more per week; Child labour for the 12 to 14 age range: children working 14 hours or more per week in economic activity and/or involved in unpaid household services for 21 hours or more per week; Child labour for the 15 to 17 age range: children working 43 hours or more per week in economic activity (no hourly threshold is set for household chores for ages 15-17).

The concept of child labour also includes the worst forms of child labour other than hazardous (18th ICLS paragraphs 33 to 34) as well as hazardous work (18th ICLS paragraphs 21 to 32). The worst forms of child labour include all forms of slavery or similar practices such as trafficking and the recruitment and use of child soldiers, the use or procurement of children for prostitution or other illicit activities, and other work that is likely to harm children’s health, safety or well-being.

Benin BJ: Average Working Hours of Children: Study and Work: Aged 7-14: Hours per Week data was reported at 10.600 Hour in 2012. Benin BJ: Average Working Hours of Children: Study and Work: Aged 7-14: Hours per Week data is updated yearly, averaging 10.600 Hour from Dec 2012 (Median) to 2012, with 1 observations. The data reached an all-time high of 10.600 Hour in 2012 and a record low of 10.600 Hour in 2012. Benin BJ: Average Working Hours of Children: Study and Work: Aged 7-14: Hours per Week data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Benin – Table BJ.World Bank.WDI: Labour Force. Average working hours of children studying and working refer to the average weekly working hours of those children who are attending school in combination with economic activity.;Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.;;

This map shows the percent of children who have no residential parent in the civilian labor force - neither working nor actively looking for work. For children living with one parent, this means that residential parent is not in the civilian labor force. For children living with two parents, this means that neither parent is in the civilian labor force. "Children" include biological, step, and adopted children under 18 years who are living with at least one parent (children living in group homes, juvenile halls, or other institutional facilities, as well as teens living in dorms, on their own, with roommates, or unmarried partners are not included in these percentages). Children whose parents are not in the labor force are at risk, as family economic security and child well-being are closely linked. Children who face economic hardship and prolonged poverty are at risk for poor outcomes in terms of physical and emotional health, education, and even adult employment. This map shows where to bolster opportunities to improve family economic security, either through opportunities linked to employment (Earned Income Tax Credit expansions, minimum wage increases, etc.), through safety net programs (nutritional programs such as WIC and SNAP, health care programs, etc.), or a combination of both.Map opens at tract-level in Kansas City. Use the bookmarks or the search bar to explore other cities. County- and state-level data display when zoomed out. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

We estimate the effect of early child development on maternal labor force participation. Mothers of poorly developing children may remain at home to care for their children. Alternatively, mothers may enter the labor force to pay for additional educational and health resources. Which action dominates is the empirical question we answer in this paper. We control for the potential endogeneity of child development by using an instrumental variables approach, uniquely exploiting exogenous variation in child development associated with child handedness. We find that a one unit increase in poor child development decreases maternal labor force participation by approximately 10 percentage points. (JEL J13, J16, J22)

Ivory Coast CI: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data was reported at 22.400 Hour in 2012. Ivory Coast CI: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data is updated yearly, averaging 22.400 Hour from Dec 2012 (Median) to 2012, with 1 observations. Ivory Coast CI: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Labour Force. Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.; ; Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.; ;

Brazil BR: Average Working Hours of Children: Study and Work: Female: Aged 7-14: Hours per Week data was reported at 13.040 Hour in 2015. This records a decrease from the previous number of 14.960 Hour for 2014. Brazil BR: Average Working Hours of Children: Study and Work: Female: Aged 7-14: Hours per Week data is updated yearly, averaging 15.558 Hour from Dec 2011 (Median) to 2015, with 4 observations. The data reached an all-time high of 18.200 Hour in 2011 and a record low of 13.040 Hour in 2015. Brazil BR: Average Working Hours of Children: Study and Work: Female: Aged 7-14: Hours per Week data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Labour Force. Average working hours of children studying and working refer to the average weekly working hours of those children who are attending school in combination with economic activity.;Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.;;

As of October 2023, it was estimated that about 62 percent of working children aged five to 17 years in the Philippines were engaged in child labor. The majority of working children engaged in child labor were male.

Abstract

The 2010 Child Labour Baseline Survey in Busia, Kilifi and Kitui Districts was designed to provide estimates on the nature, extent, and causes of child labour in general. It also collected information on the worst forms of child labour, the conditions of work and how it affects the overall development (health, physical, moral, mental) of the working children in the districts.

Geographic coverage

The survey was done in Kenya and it covers three districts namely: Busia, Kilifi and Kitui.

Analysis unit

• Households
• Individuals

Universe

The basic unit of analysis was the household for individuals aged 5-17 years of age.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two–stage cluster probability sampling design was adopted for the survey. The first stage involved selection of Enumeration Areas (EAs) from the sampling frame and the second stage involved selection of the housing units. The unit of study for the survey was the housing unit defined as the dwelling unit (or units) occupied by one household.

A sampling frame for the study was based on EAs created for the 2009 Population and Housing Census. The frame was created at the demarcation of areas conducted between 2006 and 2007 during cartographic mapping prior to the census enumeration. During mapping, estates or villages were split into EAs, each having an average of 100 households with a minimum of 50 and a maximum of 149 households. The frame therefore had Enumeration Areas (EAs) as the Primary Sampling Unit (PSUs) each Measure of Size (MoS) averaging 100 households.

KNBS hired and trained personnel to undertake the listing process. The interviewers first updated the list of all the households in the selected EAs. Among the variables considered were; Number of household members, age and sex of household heads and population aged 5-17 years. The outcome of this process provided for the basis of sampling of households participating in this survey.

In the sample design, information from the 2009 Kenya Population and Housing Census was utilized to arrive at the sample size. This involved the determination of the population aged 5-17 years. A child labour preference rate of 0.5 was considered to achieve a maximum sample. A design effect of 2 was considered. Further, to determine an appropriate sample, an error margin of 3 % was considered, which resulted into 54 clusters being created in Busia District, 49 clusters being created in Kilifi District, and 55 being created in Kitui District.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

After data was collected, all the questionnaires were sent to the KNBS headquarters for processing. The questionnaire were then sorted and edited ready for data capture. The data entry was done using the Census and Survey Processing System (CSpro) version 4.0 software. The data entry screen was created with checks to ensure accurate data entry. A total of ten data entry personnel and support staff were engaged for the exercise.
The captured data was exported to the Statistical Package for Social Sciences (SPSS) for cleaning and analysis. The cleaned data was then weighted using application of inflation factors derived from the selection probabilities of the EAs and households. The results in this report are therefore based on the weighted data.

Global Single Persons without Children Working Hours Needed to Exit Poverty by Country, 2023 Discover more data with ReportLinker!

Abstract

The purpose of the 2009 child labour Baseline Survey was to facilitate the measurement of the levels and nature of child labour in the focus districts of Rakai, Mbale and Wakiso. The specific objectives were: (i) To collect information on the main characteristics of working children and those of the households they live in ( i.e. their demographic composition and details by age/ sex/ ethnicity/ marital status/disability status/orphan hood/ literacy and educational status/ classification by industry occupation and status in employment/ earnings and weekly hours of work/ location of work place/ reasons for not attending school/ reasons for working/ types of unpaid household services done and weekly hours performed/ etc); (ii) To obtain information to support the analysis of the causes and consequences of children engaged in work, including household earnings and debt, perceptions of parents/ guardians/ children, and the hazards and abuses faced by children at their work; (iii) To obtain (through FGDs and KIIs) information on (a) the various forms of child labour prevailing in the districts, particularly on WFCL such as CSEC, street children, children engaged for illicit activities, and forced work by children (b) the underlying forces leading to the persistence of child labour especially the impact of HIV/AIDS, poverty, adult unemployment, OVC issue, and lack of proper schooling facilities; (c) Child trafficking (iv) To provide policy makers, researchers and other stakeholders with a comprehensive information and a set of indicators on child labour to guide interventions; (v) To act as a basis for the creation of a long-term database on child labour in Uganda.

Geographic coverage

The Child Labour Baseline Survey (2009) was carried out in the districts of Rakai, Wakiso and Mbale.

Analysis unit

Household, individual

Universe

The survey covered all de jure household members aged 5 years and above resident in the household, and all children aged 5 - 17 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Enumeration Areas (EAs) from the 2002 Population and Housing Census household counts were used as the sampling frame for each of the districts. Each EA was accurately and uniquely identified together with the number of households in it. Independent representative samples were selected from each of the districts using population proportional to size (PPS) with the number of households in the EA with children taken as a measure of size. A representative sample was selected from each of these focus districts. In order to ensure that reliable estimates are got for each district, EAs were distributed among the districts according to the measures of size.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two sets of questionnaires were used in the study. The household questionnaire was the main questionnaire and collected information on all sampled households. The second set of the questionnaire was used as a guide to collect responses during focus group discussions (FGDs) and key informant interview (KIIs).

The household questionnaire collected detailed information on usual members of the target households, and was used to filter out the children (5-17 years) who were asked additional questions about children’s work. The following were the broad areas from which data was collected during the Baseline Survey: (i) Background characteristics of household members; (ii) Education and Training; (iii) Labour Force Status and hours of work; (iv) Time spent on non-market activities; (v) Occupational health and safety; (vi) Perceptions of Parents /Guardians on working children; (vii) Household and Housing conditions.

Cleaning operations

Due to the need to have the child labour baseline survey records processed fast enough, this exercise started shortly after the commencement of fieldwork. The office editing/coding and data capture process for the survey took approximately 2 weeks. It involved double data entry which ensured that the accuracy of the captured data was checked in the second data capture routine hence increasing on its accuracy. After the data capture machine editing involving structural and consistency edits was carried out before data analysis. The data capture screen was developed using the CSPro (Census and Survey Processing) software.

Response rate

A total of 1,617 households were selected for the Child Labour Baseline Survey (CLBS) sample. Out of these, 1,585 households were successfully interviewed, yielding a household response rate of 98 percent. A total of 4,431 children aged 5-17 years were listed from the selected households in the household schedule, of which 4,306 children successfully responded to questions about activity status. This gave a children response rate of 97.2 percent

Sampling error estimates

Annex 3 of the final report presents the standard errors, CVs and confidence intervals for selected indicators.

Abstract

The objectives of the 2001 Ethiopia Stand-alone Child Lobour Survey was to provide Statistical data on children's activities focusing on the status of schooling non-economic and economic activities. Specifically, the Survey was aimed at to provide statistical data that will help to: (a) establish the demographic and socio-economic characteristics of children: age, sex, status and levels of education and training occupations, skill-levels, hours of work, earnings and other working and living conditions; (b) assess the working situation of children and the influence on their education, health physical and mental development; (c) examine the characteristics of the sectors that employ most children; (d) identify where and how long the children have been working and the factors that lead children to work or families to put children to work and; (e) assess the health and welfare status of working children.

The survey collected information for all members of selected households as well as for children aged 5-17 years. Data collected for all members of the household include particulars of household members, like age, sex, religion, ethnicity, school attendance and training and marital status; economic activity status of the population aged 5 years and over during the last seven days, if non-working (economically and active) reason for not working, number of hours worked, ... etc.; economic activities of population aged 10 years and over during the last twelve months; housing conditions, housing facilities and household income and expenditure were collected.

For children aged 5-17 years, information on movement of children between households; school attendance and reason for dropouts; domestic activities and idleness; health and welfare situations of children who have been working at any time in the past; conditions of employment of children who are working for a non-relative person for pay; perception of parents of those children that are engaged in economic activity about the children’s working conditions were collected from their parents or guardians. Similar information about children aged 10-17 years were also collected from children themselves.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Children aged 5-17 years

Universe

The survey is not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The Enumeration Area (EA) delineated for the 1994 Population and Housing Census of Ethiopia was used as a sampling frame for the selection of Primary Sampling Units (PSU). The sampling frame used for the selection f ultimate sampling units (households) as a fresh list of households, which was prepared b y the enumerator in the sampled E A at the time of the survey.

Sample Design: The 2001 Stand-alone National Child Labour Survey of Ethiopia covered both rural and urban parts of the country. However, it has not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey. For the purpose of the survey, the population of the country was divided into three major categories namely, rural, major urban centers and other urban centers.

Category I: Rural parts of each regional state were grouped in this category. Each of the regions was a reporting level: thus, there are 11 reporting levels in this category.

Category II: Major urban centers were grouped under this category. The list of urban centers included in this category (domain of study). Each of them were used as the survey domains for which the survey results were reported, hence, the reporting levels under this category are totally 11 major urban centers, namely, Mekele, Gonder, Dessie, Bahir Dar, Nazreth, Debre Zeit, Jimma, Awassa, Harar, Addis Ababa and DireDawa.

Category III: Other urban centers, which were not included in category II, were included in this category. Except for Harari Region, Addis Ababa and Dire Dawa administrations, each region was serving as a reporting level independently by their respective regional states. As we can see from Table 2.3 this category has 8 reporting levels.

In addition to the above domains of study, the survey results were also reported at regional and country levels by aggregating the survey results from the corresponding domains. All in all 48 basic survey domains (reporting levels) including urban part of each regional state, total (urban + rural) part of each region, country level urban, country level rural and country level total were defined for the survey.

Sample Size Selection Schema: A sample size of 1,257 EAs was fixed based upon the required precision level and available resource for the survey. The 1999 National Labor Force Survey result was used to determine the required number of sample households per PSU/EA. For this survey, it was found that about 35 households per EA would give fair and reasonable estimates at a required reporting level for the variables under study.

In category II, and I stratified two-stage cluster sampling was used for the selection of ultimate sampling units. The Primary Sampling Units (PSUs) are EAs and secondary sampling units are households. In category III stratified three-stages cluster sampling was used for the selection of ultimate sampling units. In this category the PSUs are towns, the Secondary Sampling Units (SSUs) are EAs and the tertiary sampling units are households t he probability proportional to size (PPS) systematic sampling, size being total number of households obtained from the 1994 population and housing census was used for selection of towns and E As.

From category I a total of 723 EAs, from category II a total of 305 EAs and from category III a total of 229 EAs were selected after generating afresh listing of households within each sample EA at the beginning of the field work the survey questionnaire was administered to 35 systematically selected households for rural and both categories of the urban domains. Based on the results of the survey coverage rate of sample EAs was 100 percent and response rate of sampled household was 99.1percent.

Mode of data collection

Face-to-face [f2f]

Research instrument

At the inception of the survey design, the ILO has provided the Central Statistical Authority (CSA) a draft module questionnaire that was tested and applied in other African countries to be used as a base and to decide on the content and format of the Ethiopia Stand-alone Child Labour Survey. The ILO's module questionnaire was then redesigned to reflect the existing conditions of the country, in close consultation with Ministry of Labour and Social Affairs (MOLSA) and the ILO in order to satisfy the data requirements of the country as well as the feasibility in the data collection operations. Accordingly, the survey questionnaire modified into three forms, where Form-I of the questionnaire that refers to demographic and socio-economic condition of household members was administered to each member of the selected households. Form-II of the survey questionnaire refers to children aged 5-17 years and the information was collected by interviewed from the parents or guardians of the children, while Form-III was addressed to children aged 10-17 years and the children themselves give the responses to the questions.

In the process of designing the survey questionnaire, a pilot survey was conducted where the questionnaires and other survey instruments were tested in the field and amended accordingly. Furthermore, a half day user-producer forum was prepared that involved the Ministry of Labour and Social Affairs, other concerned government agencies, the ILO Area Office in Addis Ababa and NGO's that are involved in child issues. Comments and inputs on the draft content of the survey questionnaire from the users aspect were obtained and are used as inputs in finalizing the questionnaire.

Briefly the major variables included in the three Forms of the questionnaire are presented below.

Form - I: Area Identification of the Selected Household and Socio-demographic Characteristics of Household Members Section 1: Area identification of the selected household. Section 2: Particulars of respondents and household members, that is, socio-demographic characteristics of the population like age, sex, religion, ethnicity, schooling and training and marital status.
Section 3: Economic activities of the population aged 5 years and over during the last seven days; this section identifies working and non-working population and reason for not working, number of hours worked, amount and source of earnings of children as well as other members of household.
Section 4: Economic activities of population aged 10 years and over during the last twelve months. Section 5: Household section of the questionnaire that deals with housing conditions, housing facilities and household income and expenditure.

Form - II: Economic Activity Status of Children Aged 5-17 Years - to be addressed to Parents, Guardians or Heads of Households Section 6: Movement of children between households; Section 7: Schooling and reason for dropouts; Section 8: Domestic activities without payment and idleness; Section 9: Health and welfare situations of children who have been working at any time in the past; Section 10: Conditions of employment of children who are working for a non-relative person for pay; Section 11: Perception of parents of those children that

As of October 2023, it was estimated that 678,000 working children aged five to 17 years in the Philippines were engaged in child labor. This indicates a decrease from the previous year's total. The majority of working children engaged in child labor were males.

Congo, The Democratic Republic of the CD: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data was reported at 9.183 Hour in 2014. This records a decrease from the previous number of 11.000 Hour for 2010. Congo, The Democratic Republic of the CD: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data is updated yearly, averaging 10.091 Hour from Dec 2010 (Median) to 2014, with 2 observations. The data reached an all-time high of 11.000 Hour in 2010 and a record low of 9.183 Hour in 2014. Congo, The Democratic Republic of the CD: Average Working Hours of Children: Working Only: Aged 7-14: Hours per Week data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Democratic Republic of Congo – Table CD.World Bank: Labour Force. Average working hours of children working only refers to the average weekly working hours of those children who are involved in economic activity and not attending school.; ; Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.; ;

Child labor can significantly impact the health, welfare, and development of children engaged in labor. The spread of child labor around the globe is predicted to accelerate as a consequence of the COVID-19 pandemic. To this end, a scoping review was conducted to (a) synthesize emerging themes and results from recent research on child labor during the COVID-19 pandemic, (b) identify factors that increase the risk of children falling into child labor and (c) provide recommendations that can inform the development of policies and programs to ensure that previous efforts to combat child labor are not lost. Six electronic databases (Medline, EMBASE, Scopus, CINAHL, Global health, and Web of Science) were searched on January 21, 2022. The database searches, along with the grey literature search, identified 5,244 studies, of which 45 articles were included in the final review. Several of those articles (8 of 45 articles) reviewed concluded that the pandemic could increase child labor worldwide including the worst forms of child labor. The reviewed studies identified primary risk factors for child labor during the COVID-19 pandemic including economic challenges, temporary school closure and a greater demand for child labor, mortality among parents, and limited social protection. This scoping review identified the need for more field research on child labor following the COVID-19 pandemic to detect emerging patterns of child labor and to develop effective intervention measures. There is also a need for further empirical research on the consequences of the COVID-19 pandemic on gender differences in occupational exposure and health outcomes among working children and marginalized groups such as migrants, refugees, and minority groups. Based on the conclusions drawn from this review, it is evident that addressing child labor in the wake of the pandemic necessitates a multi-sectoral response by the government, businesses, civil society, and funding/donor agencies. This response should address various areas such as education, social and child protection, and legislation to support vulnerable children and their families in order to combat child labor subsequent to the pandemic.