Child Protection

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Multiple Indicator Cluster Surveys Data Interpretation, Further Analysis and

Dissemination Workshop

Child Protection

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Overview

Preventing and responding to violence, exploitation and abuse of all children in all contexts.

MICS is the largest household survey program in terms of child protection topics covered

Several measurement approaches have been developed by MICS/UNICEF

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Overview

18 tables: Birth registration (1) Child labour (3) Child discipline (2) Early marriage (5) Female genital mutilation/cutting (3) Attitudes towards domestic violence (2) Children's living arrangements & orphanhood

(2)

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Overview

Birth registration (1) Child labour (3) Child discipline (2) Early marriage (5) Female genital mutilation/cutting (3) Attitudes towards domestic violence (2) Children's living arrangements & orphanhood (2)

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Birth registration

CRC: Every child has the right to a name and nationality and the right to protection from being deprived of his/her identity

Birth registration is a fundamental of securing these rights – ensuring the registration of every child at or shortly after birth

MICS indicator: Percentage of children under age 5 whose birth is registered

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Total

SexMaleFemale

RegionRegion 1Region 2Region 3

Table CP.1: Birth registration

Number of children under age 5 w ithout birth

registration

Percentage of children under age 5 by w hether birth is registered and percentage of children not registered w hose mothers/caretakers know how to register birth, Country, Year

Total registered1

No birth certif icate

Has birth certificate

Seen Not seen

Children under age 5 whose birth is registered w ith civil authorities

Percent of children w hose mother/caretaker know s

how to register birth

Number of children

under age 5

Children under age 5 whose birth is not registered

Proper customization is needed, to identify the authority in charge of official recording of births and to use the right terminology

Concepts/terms might change from one country to another:Birth certificateCivil authorities

Registration

Overall summary MICS indicator

Includes children registered with

“civil authorities”

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Expected patterns in data

Unregistered children are almost always children From poor, marginalized or displaced families, Living in rural areas, and Of mothers with no/low education

Significant differences in birth registration levels may exist between regions and ethnicities within the same country

Levels of registration tend to increase with child’s age Usually, very small differences are observed in birth

registration levels between boys and girls

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Things to consider

Careful analysis of the questionnaire and sample size needed before assessing trends in the level of birth registration

Questions may have been different in past surveys (e.g. due to customization differences, inclusion of deceased children)

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Things to look for in the tables

Proportion of children with a birth certificate (especially if “seen”) as compared to the proportion of children who are registered

If a parent does not have a certificate this may represent an obstacle in a child’s life for example enrolment in school

Proportion of mothers/caretakers who do not know how to register the child may be very useful for the design of programmatic interventions – however, sample sizes might be too small in some surveys

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Some ideas for further analyses

Explore associations in the dataset, for example: Early childhood services may provide an access point for

registration: The likelihood that the child is registered might be related

to whether the birth was assisted by a skilled attendant, or whether the child received vaccinations

Compare with population/vital registration system Further qualitative research to understand reasons for

not registering births in those groups where non-registration was high

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Overview


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Random selection

Random selection of one child age 1-17 per household If age 5-17, child labour module If age 1-14, child discipline moduleadministered

Analysis: Sample weight is multiplied by the number of children age 1-17 in each household, and the resulting “weight” normalized The denominator is equal to the number of all

children age 1-17 in the interviewed houeholds

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Overview


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“Child labour” in MICS

Age Economic activity

Household chores Hazardous conditions

5-11 At least one hour 28 hours or more Any

12-14 14 hours or more 28 hours or more Any

15-17 43 hours or more 43 hours or more Any

Children who fall into any of these cells are included in the numerator of the child labour indicator

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Economic activity (paid or unpaid) is any of the following:• Work on plot / farm / food garden / looking after animals• Help in family / relative’s business/ran own business• Produce / sell articles / handicrafts / clothes / food or

agricultural products • Any other activity in return for income in cash or in kind

Economic activity less than 14 hours

Economic activity for 14 hours or

moreEconomic activity

less than 43 hours

Economic activity for 43 hours or

more

Total

SexMaleFemale


Table CP.2: Children's involvement in economic activities

Percentage of children age 5-11 years

involved in economic activity for at least

one hour

Number of children age 5-11 years


Percentage of children age 12-14 years involved in:

Percentage of children by involvement in economic activities during the last w eek, according to age groups, Country, Year



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Household chores less

than 28 hours

Household chores for 28

hours or more


than 28 hours


hours or more


than 43 hours


hours or more

Total

SexMaleFemale

RegionRegion 1Region 2Region 3Region 4

Table CP.3: Children's involvement in household choresPercentage of children by involvement in household chores during the last w eek, according to age groups, Country, Year


Number of children age 5-11

years


Number of children

age 12-14 years


Number of children

age 15-17 years

Household chores is any of the following:• Fetch water or collect firewood for household use• Shopping for household• Repair household equipment• Cooking / cleaning utensils /house • Washing clothes • Caring for children • Caring for old / sick • Other household tasks

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Below the age specif ic

threshold

At or above the age specif ic

threshold

Below the age specif ic threshold

At or above the age specif ic

threshold

Total

SexMaleFemale


Table CP.4: Child labourPercentage of children age 5-17 years by involvement in economic activities or household chores during the last w eek, percentage w orking under hazardous conditions during the last w eek, and percentage engaged in child labour during the last w eek, Country, Year

Children involved in economic activities for a total number of

hours during last week:

Children involved in household chores for a total number of

hours during last week:Children w orking under

hazardous conditions

Total child labour1


Numerator: Children age 5-17 years who were involved in economic activities or household chores above the age specific thresholds, or worked under hazardous conditions (any age) last week

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Expected patterns

Children living in rural areas, children from poor families and children whose mothers have no/low education are more likely to be engaged in child labour

Significant differences or levels of child labour may exist between regions within the same country, especially in countries with high levels of economic specialization

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Expected patterns

Girls are more likely than boys to be engaged in household chores

Most children are engaged in some form of activity (working children – work below age-specific thresholds) but only a minority of them are engaged in child labour

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Variations in prevalence of child labour by sex/age of the child and socio-demographic characteristics of their families

Levels of gender specialization by type of activity and intensity of involvement in labour and work by sex

Caution: Seasonality

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Child labour and school attendance by sex of the child and other background characteristics: assess the relative impact of child labour and sex on school participation

Relationship between school drop outs and labour Child labour (family business/household chores) and

child discipline

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Overview


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Any Severe

Total

SexMaleFemale

RegionRegion 1Region 2Region 3Region 4Region 5

Table CP.5: Child discipline


Percentage of children age 1-14 years who experienced:

Percentage of children age 1-14 years by child disciplining methods experienced during the last one month, Country, Year

Only non-violent

disciplinePsychological aggression

Any violent discipline method1

Physical punishment

Psychological aggression: shouting, yelling and screaming at the child, and addressing her or him with offensive names.

Physical punishment: Cause child physical pain or discomfort but not injuries: shaking the child & slapping or hitting on hand, arm, leg or bottom, hitting child on face, head or ears, or hitting the child hard or repeatedly.

Only non-violent discipline: Taking away privileges, forbidding something child likes, grounding, explaining why behaviour is wrong, giving something else to do

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Respondent believes that a child

needs to be physically punished

Number of respondents to

the child discipline module

Total

SexMaleFemale


Table CP.6: Attitudes toward physical punishment Percentage of respondents to the child discipline module w ho believe that physical punishment is needed to bring up, raise, or educate a child properly, Country, Year

…and is not necessarily a parent or caretaker of the selected child

Respondent is reporting on disciplinary practices used by any adult household member (not his/her own practices)

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Expected patterns

Non-violent discipline is more common than violent discipline.

Psychological violence is more common than physical violence. However, these forms of violence are linked and

occur together: most children are likely to experience both physical punishment and psychological aggression

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Expected patterns

Family wealth and levels of education of household members are significantly associated with attitudes in most countries, but not always with disciplinary practices

Larger variations in attitudes than in practices

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Variations in the use of violent disciplinary practices by sex/age of the child, as well as socio-demographic characteristics of their families that may predict which children are most at risk of violent discipline

Variations in the support for physical punishment by sex, education, wealth of the respondent

Comparison between proportion of children who experience physical punishment and proportion of respondents who believe physical punishment is necessary – at aggregate level

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Things to look out for, things to remember

Previous MICS tables presented data on physical punishment separated for moderate and severe

Prevalence of severe punishment has to be lower than prevalence for any physical punishment – needs another look at the data

Proportion of children who do not receive any discipline at all should be minimal

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Ideas for further analyses

Types of specific disciplining methods, comparison of severe, moderate etc, overlaps

Experience of violent discipline by family setting (household size and number of children, present of parents in the household, type of marital union)

Experience of violent discipline and use of alcohol in the household

Attitudes towards physical punishment and attitudes towards domestic violence exposure to media

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Overview


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Early/Child marriage

Violation of human rights, compromising girls’ development, often resulting in early pregnancy and social isolation, with little education and poor vocational training

The right to 'free and full' consent to a marriage (Universal Declaration of Human Rights) – consent cannot be 'free and full' when one of the parties involved is not sufficiently mature to make an informed decision

http://www.childinfo.org/files/childmarriage_Universaldeclarationhumanrights.pdf



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Percentage married

before age 151

Number of w omen age 15-49 years

Percentage married

before age 15

Percentage married

before age 182


Percentage currently married/in

union3


Percentage in polygynous

marriage/ union4

Number of w omen age 15-

49 years currently

married/in union

Total


Table CP.7: Early marriage and polygyny (women)Percentage of w omen age 15-49 years w ho first married or entered a marital union before their 15th birthday, percentages of w omen age 20-49 years w ho first married or entered a marital union before their 15th and 18th birthdays, percentage of w omen age 15-19 years currently married or in union, and the percentage of w omen w ho are in a polygynous marriage or union, Country, Year

Women age 15-49 years Women age 20-49 years Women age 15-19 years Women age 15-49 years

Give an indication of the most recent situation

Same table also produced for men

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Percentage of w omen

married before age

15


Percentage of w omen

married before age

18


Total

Age15-19 na na20-2425-2930-3435-3940-4445-49

Table CP.8: Trends in early marriage (women)

All

Percentage of w omen w ho w ere f irst married or entered into a marital union before age 15 and 18, by area and age groups, Country,Year

na: not applicable

Trends in the proportion of women/men married/in union before age 18 and 15 can be obtained by comparing age cohorts (20-24, 25-29, 30-34…)

Same table also produced

for men

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Younger

0-4 years older

5-9 years older

10+ years older1

Husband/Partner's

age unknow n Total Younger

0-4 years older

5-9 years older

10+ years older2

Husband/Partner's

age unknow n Total

Total 100.0 100.0

RegionRegion 1 100.0 100.0Region 2 100.0 100.0

Percent distribution of w omen currently married/in union age 15-19 and 20-24 years according to the age difference w ith their husband or partner, Country, Year

Table CP.9: Spousal age difference

Percentage of currently married/in union women age 20-24 years whose husband or

partner is:

Percentage of currently married/in union women age 15-19 years whose husband or

partner is:

Number of w omen age

20-24 years

currently married/ in

union

Number of w omen age

15-19 years

currently married/ in

union

Spousal age differences : produced using the age of the current husband, even

if formerly married

Contributes to abuse

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Expected patterns

Decline in the prevalence of child marriage, particularly for marriages below age 15

Significant differences in prevalence of child marriage between women and men

Higher levels of child marriage among the poorest women/men, women/men living in rural areas, women/men with no/low education

Compare proportions married by 15 and 18 to calculate proportion married between 15 and 18

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Things to look out for, things to remember

Some cases in the tables should be empty as they are not applicable

Some values should be the same across the tables Proportion of women for which age of the partner is

unknown may be problematic Sample size issues, especially women 15-19 and 20-

24 who are currently married

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Child marriage and attitudes towards domestic violence, early childbearing (before 15, 18), contraceptive use

Calculate means, medians

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Zambia Nigeria Burkina Faso Kenya Benin Cameroon Zimbabwe0

10

20

30

40

50

60

70

80

90

100

Married before age 18Married between ages 18-24Married at age 25 or later

Percentage of currently married women who agree that a husband is justified in beating his wife if she goes out without telling him, by

age at first marriage, DHS 2002-2009

Women who marry as children are more likely to justify wife-beating

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Overview


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Had flesh removed Were nicked

Were sew n closed

Form of FGM/C not determined

Total 100.0

RegionRegion 1 100.0Region 2 100.0Region 3 100.0Region 4 100.0Region 5 100.0

AreaUrban 100.0

Table CP.10: Female genital mutilation/cutting (FGM/C) among womenPercentage of w omen age 15-49 years by FGM/C status and percent distribution of w omen w ho had FGM/C by type of FGM/C, Country, Year

Number of w omen age 15-49 years w ho

had FGM/C

Percent distribution of women age 15-49 years who had FGM/C:

Total

Percentage of w omen w ho had any form

of FGM/C1

Number of w omen

age 15-49 years

Indicator is on ANY form of GM/C : forms are, removal of flesh from the genital area, the nicking of the flesh of the genital area and sewing closed the genital area

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Had flesh removed Were nicked

Were sew n closed

Form of FGM/C not determined

Total 100.0

RegionRegion 1 100.0Region 2 100.0Region 3 100.0Region 4 100.0

Number of daughters age

0-14 years w ho had FGM/C

Table CP.11: Female genital mutilation/cutting (FGM/C) among girlsPercentage of daughters age 0-14 years by FGM/C status and percent distribution of daughters w ho had FGM/C by type of FGM/C, Country, Year

Percent distribution of daughters age 0-14 years who had FGM/C:

Percentage of daughters w ho had any form

of FGM/C1

Number of daughters age 0-14

years Total

Information on the FGM/C status of daughters: obtained by asking the questions on FGM/C to women age 15-49 years, on their daughters below the age of 15.

May brake down by smaller age intervals, such as 0-1, 2-4 or 10-12, 13-14,

Prevalence do not represent all girls age 0-14 years in the population: Girls whose mothers are, deceased, above age 49, and living in another country are not captured. However, figures in the table very closely approximate the FGM/C status among girls age 0-14.

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Continued1 Discontinued Depends DK/Missing Total

Total 100.0


Table CP.12: Approval of female genital mutilation/cutting (FGM/C)Percentage of w omen age 15-49 years w ho have heard of FGM/C, and percent distribution of w omen according to attitudes tow ards w hether the practice of FGM/C should be continued, Country, Year

Percent distribution of women who believe the practice of FGM/C should be:

Number of w omen age 15-49 years w ho have heard of

FGM/C


Percentage of w omen w ho have heard of FGM/C

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Overview


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If she goes out w ithout telling him

If she neglects the

children

If she argues w ith

him

If she refuses sex

w ith him

If she burns the

food

For any of these f ive reasons1

Total


Table CP.13: Attitudes toward domestic violence (women)Percentage of w omen age 15-49 years w ho believe a husband is justif ied in beating his w ife in various circumstances, Country, Year


Percentage of women age 15-49 years who believe a husband is justified in beating his w ife:

Standard questions – may have been customized. Important to calculate the standard indicator

Each refer to a domain of gender roles

Social acceptability of domestic violence, not necessarily a predictor of the prevalence

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Expected patterns

Women from the poorest quintiles and women with no education are more likely to justify wife-beating

High level of consistency across regions/groups of women in the pattern of agreement with reasons justifying wife beating

Neglecting the children and going out without telling the husband are the most common reasons

Women, especially girls, are more likely to justify domestic violence than their male counterparts

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Disparities by place of residence/ethnicity/ wealth quintile/education

Attitudes by age of the respondent Attitudes by marital status Main reasons for justifying wife beating

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Compare men’s and women's attitudes (both levels and patterns)

Relationship with attitudes towards violent discipline Age at first marriage and/or spousal difference Regular media exposure, household composition

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Overview


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Only father alive

Only mother alive

Both alive

Both dead

Father alive

Father dead

Mother alive

Mother dead

Total 100.0

SexMale 100.0Female 100.0


Table CP.14: Children's living arrangements and orphanhoodPercent distribution of children age 0-17 years according to living arrangements, percentage of children age 0-17 years not living w ith a biological parent and percentage of children w ho have one or both parents dead, Country, Year

Living w ith both

parents

Living w ith neither biological parent

Living w ith mother only

Living w ith father only Missing

information on father/

mother Total

Living w ith

neither biological parent1

One or both

parents dead 2

Number of

children age 0-17

years

Children who are not living with at least one biological parent, either because the parents live elsewhere or because the parents are dead

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Only mother abroad

Only father abroad

Both mother and father abroad

Total 100.0

SexMale 100.0Female 100.0


Table CP.15: Children with parents living abroadPercent distribution of children age 0-17 years by residence of parents in another country, Country, Year

Percentage of children age 0-17 years w ith at least one parent living

abroad¹


Percent distribution of children age 0-17 years:With at least one parent living abroad With neither

parent living abroad Total

New topic in MICS, in response to growing demand and analysis of data on “children left behind”

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Expected patterns in data

Low prevalence of children with one or both parents dead (generally less than 10 percent)

No significant differences between males and females

Orphanhood levels increase with age High HIV prevalence and orphanhood correlated

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Children's living arrangements and orphanhood might be related to birth registration, malnutrition, school attendance, child discipline or child development

Orphanhood, and the relationship to the household head

Children left behind and their primary caretakers – who is taking care?

Well-being of children left behind

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Child Protection

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