From Awareness to Action:Child Marriage Predictors,

Hotspots, and Program Approaches

Kathleen Kurz and Saranga Jain

IGWG Technical Update on Child Marriage

July 11, 2006

Outline of Presentation

Background

Prevalence

Consequences

Reasons

From Awareness to Action

Predictors

Hotspots

Program Scan

Recommendations

Prevalence of Child Marriage –

Top 20 Countries Girls Married Before Age 18 (%)

1 Niger (1998) 76 2 Chad (2004) 71 3 Bangladesh (2004) 68 4 Mali (2001) 65 5 Guinea (1999) 64 6 CAR (1994/95) 57 7 Nepal (2001) 56 8 Mozambique (2003) 55 9 Uganda (2000/01) 54 10 Burkina Faso (2003) 51 11 India (1998/99) 50 12 Ethiopia (2000) 49 13 Liberia (1986) 48 13 Yemen (1997) 48 15 Cameroon (2004) 47 16 Eritrea (2002) 47 17 Malawi (2000) 46 18 Nicaragua (2001) 43 18 Nigeria (2003) 43 20 Zambia (2001/02) 42

Child Marriage (CM): Constraints to Health &

Development

•Worse reproductive health outcomes

•Wasted investment in development efforts

436

575

223

6.2

1270

1100

526

6.60

200

400

600

800

1000

1200

1400

Ethiopia Indonesia Nigeria United States

Maternal mortality rate (per 100,000 live

births)

20-34 years

15-19 years

Sources: Family care international, 1998; CDC 2002 Vital Statistics Report

Maternal Mortality by Age

Infant Mortality Rates by Age of the Mother

Outcomes•Maternal mortality•Maternal morbidities•Low birth weight & prematurity•Infant mortality

Reasons•Still growing•First birth•Inadequate prenatal care•Low socioeconomic status

Poor Health Outcomes

0

10

20

30

40

50

60

0 20 40 60 80 100 120 140 160 180

HDI Rank

% married girls aged 15-19

Chad

Sources: PRB 2000 State of the World's Youth; UNDP HDR 2002

Brazil

U.S.

India

MaliBangladesh

Indonesia

Child Marriage and Rank on

Human Development Index (HDI)

Reasons: Why Does Child Marriage

Persist?•Gender roles

– Families see girls as financial and social burdens

– Lack of socially acceptable alternatives for girls

•Family and community honor tied to early marriage

– Reinforce ties between families and communities

– Desire to protect girls

•Lack of political will

•Cultural norm

Outline of Presentation

Background

Prevalence

Consequences

Reasons

From Awareness to Action

Predictors

Hotspots

Program Scan

Recommendations

Possible Predictors of CM Considered in the Multivariate Analysis

Practices programs could support to reduce CM

• Primary Education• Secondary Education• Higher Education• Primary Education -- Partner• Secondary Education -- Partner• Higher Education -- Partner• Lower Age Gap Husband-Wife

Factors programs could target to reduce CM

• Current Place of Residence • Childhood Place of Residence • Region• Ethnicity• Religion• Polygyny• Number of Siblings• Wealth/Electricity

Strength of Predictors of CM <18 yrs vs ≥18yrs

02468

101214161820

Number of Countries

"Tipping Point" Age at which CM Accelerates:

Example Bangladesh - Age 13

0

10

20

30

40

50

60

70

80

90

100

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Age

Cumulative Percent of CM

Country Tipping Point Age

Median Age of Marriage

Cameroon, India, Mozambique

13 17

Uganda, Zambia, Malawi 14 17

Burkina Faso 15 17

Ethiopia 12 16

Nigeria, Mali, Liberia, Nicaragua

13 16

Central African Republic, Nepal

14 16

Bangladesh, Niger, Chad, Guinea

13 15

Tipping Point Ageand Median Age of Marriage

Prevalence of CM by Secondary School

Enrollment

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

42 43 43 47 47 49 50 52 54 56 56 57 65 65 69 72 77

Median Age Gap (yrs)

Prevalence of CM

Zambia

Nicaragua

Nigeria

Malawi

CameroonEthiopia

India

Burkina Faso

UgandaMozambique

Nepal

Central African Rrepublic

Guinea

MaliBangladesh

Chad

Niger

Prevalence of CM by Age Gap Husband-Wife

A Variety of Religious Affiliations Associated with Higher CM

Country

Religious Affiliation and Highest CM in Country

Malawi Catholic

Chad Muslim

Cameroon Catholic

Ethiopia Orthodox

Nigeria Catholic

Burkina Faso Muslim

India Hindu

Bangladesh Muslim

Are Regional Differences within Countries Significant?

Yes No Chad Bangladesh Mali Guinea Mozambique Central African Republic Ethiopia Liberia Burkina Faso Cameroon Zambia Malawi

Niger Uganda

Nepal Nigeria Nicaragua India

Regional Variation -- Ethiopia

48% of CM in Ethiopia occurs in the north:

Amhara90%Tigray 82%Affar 77%Ben-Gumz75%

Regional Variation - India

5 states in India have highest percentages of child marriage:

Madhya Pradesh: 73%

Andhhra Pradesh: 71%

Rajasthan: 68%

Bihar: 67%

Uttar Pradesh: 64%

Regional Variation – Nigeria

71% of CM in Nigeria occurs in the north:        83% in North West        78% in North East

 

9 Other Countries and their Regions

with High CM Prevalence Country Region(s) with highest prevalence

Niger North(North West, North East)

Chad South Central(Hadjer Lumis, Chari Baguirmi, Batha, Guéra, Saramat)

Mali Western Region Excluding Bamako(Kayes, Koulikoro)

Nepal Far-Western

Mozambique

North East(Nampula, Cabo Delgado, Zambezia, Niassa)

Uganda Northern and Eastern Regions

Burkina Faso

North and East(Sahel, Centre-Nord, Est)

Nicaragua East and Southeast(Atlantico Sur, Rivas, Atlantico Norte, Chontales, Granada, Rio San Juan)

Zambia Central and North East(Central, Eastern, Northern, Luapula and Copperbelt regions)

Outline of Presentation

Background

Prevalence

Consequences

Reasons

From Awareness to Action

Predictors

Hotspots

Program Scan

Recommendations

Scan of Programs that Address CM: Methods

• Thinking about child marriage beyond awareness

• Web-based scan of programs

• Directly or indirectly addressing child marriage

• Global Focus

• Search included:

• Search engines (35+ keywords)

• Organization websites

• Online journals, publications and books

Scan of Programs: Methods (cont.)• Noting:

• Categories of programs

• Location

• Programs and government policy in high prevalence countries

• Target groups

• Reproductive health component

• Evaluation

• Many double-counted programs (total >100%)

• Gaps: programs without web presence and those that do not describe CM as an outcome

Where Are CM Programs Found?

1 program

2-4 programs

≥5 programs

Scan by Program Categories

Program Category No. %

Education for family & community 35 53

Education for girls 30 45

Law & policy 20 30

Economic opportunities 11 17

Safeguarding rights 9 14

Research 4 6

Health services to married girls 1 2

TOTAL PROGRAMS 66 100

Program Category/Sub-Category No. %

Education for family & community 35 53

Community sensitization/awareness raising

29 44

Social marketing/edutainment 10 15

Education for girls 30 45

Life skills 15 23

Non-formal education 12 18

Livelihood/vocational skills 9 14

Formal education 7 11

Law & Policy 20 30

Legal mechanisms 10 15

Advocacy 8 12

Community mobilization 6 9

Policy 2 3

Scan by Program Sub-Categories

Scan by Target Sub-Categories (cont.)

Program Category/Sub-Category No. %

Economic opportunities 11 17

Income generation for girls 7 11

Monetary incentives for families 4 6

Safeguarding rights 9 14

Shelter/creating safe spaces 5 8

Keeping birth or marriage records 3 5

Other rights (e.g. to education) 1 2

Research 4 6

Health Services to married girls 1 2

TOTAL PROGRAMS 66 100

Where is Reproductive Health?

• Not a program category

• Not a program sub-category

• But is a component in some sub-categories47% have some RH componentIncluding community sensitization,

life skills and/or non-formal education

• What is role of RH?

Scan by Program Target Audiences

Program Target Group No. %

Targeting family & community 46 70

Targeting girls 39 59

Only marrieds 1 3

Only unmarrieds 24 62

Both marrieds and unmarrieds

13 33

Targeting policy makers 14 21

Are These ProgramsReducing Child Marriage?

We don’t know –

Evaluations lacking

Recommendations1) Work early on CM efforts – before tipping points of

ages 12-15 2) Vigorously promote secondary school education for

girls3) Investigate age gap between husbands and wives,

and how to reduce its negative consequences4) Target CM efforts within countries, or regions

within countries, where CM is more prevalent 5) Discuss RH community’s role in reducing CM

prevalence – supporting RH component in existing, integrated programs or starting one’s own

6) Balance efforts to prevent CM with efforts to meet health needs of child brides

7) Evaluate programs for reductions in CM