Multiple Indicator Cluster SurveysData dissemination and further analysis workshop

Further Analysis:Youth and Adolescents

MICS4 Data dissemination and Further Analysis

Outline

• Terminology• Why study youth and adolescents?• What MICS already has to offer• Ideas for further analysis (using Bhutan MICS4

data for examples)• Further thoughts about producing thematic

analysis reports

Terminology: who are they?• Adolescents (UN): 10-19 years

– (early 10-14, late 15-19)

• Youth (UN GA): 15-24 years• Young people (UN GA): 10-24 years

• Children (UNICEF): 0-17 years• Adolescents (UNICEF): 10-19 years

Why study youth and adolescents?

• Gains in young child survival but later loss in youth and adolescent years

• Key focus of programmatic intervention in many countries– A keener focus on the development and

human rights of adolescents to enhance and accelerate the fight against poverty, inequality and gender discrimination – State of the Worlds Children 2011

Adolescents account for nearly one fifth of the world’s population

Population of adolescents 10-19 years old as a proportion of the total population, by region, 2010

More than half of the world’s adolescents live in Asia

Population of adolescents 10-19 years old by region, 2010

Source: United Nations, Department of Economic and Social Affairs, Population Division,

World Population Prospects: The 2010 revision, CD-ROM edition, 2011.

By 2050, Sub-Saharan Africa is projected to have more adolescents than any other region

Population of adolescents 10-19 years old in millions, by region, 1950-2010

Injuries and neuropsychiatric disorders are major causes of mortality and morbidity among adolescents in all regions

Major causes of disease burden in disability-adjusted life years (DALYs) per 1,000 adolescents 10-19 years old, by region and by sex

Source: WHO, The Global Burden of Disease: 2004 update, 2008/

How did we arrive at data on youth and adolescents?

Data collected in Household QuestionnaireDirect interviewing

Individual Women Questionnaire administered to women age 15 – 49, a subset of which is 15-24

When applicable Individual Male Questionnaire administered to men age 15 – 49, a subset of which is 15-24

• Retrospective data from Women’s questionnaire – find out about past events that occurred at younger ages e.g. marriage before age 15

What MICS can offer

1. MICS indicators and tables already available covering adolescents and youth (age groups 15-19, 20-24)

2. In MICS Reports: Information already available in existing MICS standard tables for age groups 15-49, 2-14, 5-14, 0-17, etc.

3. Additional information that can be extracted from MICS datasets not covered in the main MICS reports

Additional information that can be extracted from MICS datasets

• Percentage of children age 10-17 years not living with a biological parent

• Educational attendance for adolescents/youth 10-24 (Adolescents/youth out of school)

• Percentage of household members age 10-24 without access to improved drinking water

• Percentage of household members age 10-24 without access to improved sanitation facilities

MICS 4 - Added Modules for Youth

• Access to media and use of information/ communication technology

• Use of alcohol and tobacco

• Life satisfaction

Ideas for further analysis

Thematic Analysis on Youth and Adolescents

Understanding who youth and adolescents are: • Where they live• How they live: affected

by poverty? • With whom they live:

alone, nuclear families, extended families

Thematic Analysis on Youth and Adolescents

Studying the outcomes for youth and adolescents in health, protection, education, and other issues:

• Key: Are they different to adults?

Further Analysis: Living arrangements against other outcomes

Living with Both Parents Living with one parent Not living with a biological parent

One or both parents dead0

5

10

15

20

25

30

Percentage of women age 15-17 with comprehensive knowledge of HIV/AIDS by living ar -rangements, Bhutan, 2010

Living Arrangements

Perc

enta

ge

Education: Further analysis ideas No Formal Education

Percentage of individuals age 15-24 who have never attended formal education by sex, Bhutan, 2010

Male Female Total

Never been to school

Number of individuals age 15-24

Never been to school

Number of individuals age 15-24

Never been to school

Number of individuals age 15-24

Area Urban 5.5 1687 16.4 2112 11.6 3798Rural 26.7 4447 37.4 4256 31.9 8704

Age 15-19 15.8 3349 19.7 3181 17.7 653020-24 27.0 2785 41.1 3187 34.5 5972

Wealth index quintiles

Poorest 39.6 1258 57.0 1061 47.6 2318Second 32.5 1266 42.1 1112 37.0 2378Middle 20.2 1250 33.8 1228 26.9 2478Fourth 8.2 1177 20.4 1387 14.8 2564Richest 1.8 1183 10.5 1580 6.8 2764

Total 20.9 6134 30.4 6368 25.7 12502

Education: Further analysis ideas

Tertiary Level Education Attendance Attendance ratios of young men and women in tertiary education, Bhutan, 2010

Tertiary

education net attendance ratio (NAR),

boys

Total number of men 18-24

Tertiary education

net attendance ratio (NAR),

girls

Total number of

women 18-24

Tertiary education

net attendance ratio (NAR),

all

Total number of youth age

18-24

Gender parity

index (GPI) for tertiary

school adjusted

NARArea Urban 8.9 1086 8.1 1527 9.9 2613 .92

Rural 5.8 2910 3.3 2888 4.6 5798 .57

Wealth index quintiles

Poorest 2.2 805 .3 704 1.2 1509 .14

Second 4.7 834 1.9 751 3.1 1584 .41

Middle 5.1 847 3.7 860 4.4 1706 .72

Fourth 6.6 780 4.7 1020 6.4 1801 .72

Richest 15.5 730 11.5 1080 16.1 1810 .74

Total 6.6 3995 5.0 4415 6.1 8410 .75

Early marriage: Further Analysis

0%

10%

20%

30%

40%

50%

60%

70%

59.4%

0.5%

Secondary school attendance among women age 15-18 by marital status, Bhutan, 2010

Never married/in union Ever married/in union

Per

cen

tag

e

0

10

20

30

40

50

60

70

80

90

100

15-19 20-24 25-49

Indicators by Age Group

Per

cen

tag

eReproductive and newborn health indicators by

age of woman at birth, Bhutan, 2010

Early child bearing: further analysis ideas

Early childbearing and mother’s education:

Literacy

Number of non-early mothers

age 20-24 Literacy

Number of early mothers age 20-

24

Urban 55.6 292 31.8 91 383

Rural 30.3 669 15.5 292 962

None 4.2 532 6.6 278 810

Primary 38.4 141 37.3 77 219

Secondary + 100.0 288 100.0 27 315

Poorest 12.3 189 5.7 85 274

Second 21.6 169 12.6 73 242

Middle 35.4 207 21.3 84 291

Fourth 45.2 242 22.6 105 347

Richest 79.5 154 51.5 36 191

Total 38.0 961 19.4 383 1344

Area

Education

Wealth index quintiles

YATA18B: Literacy rate of mothers age 20-24 by whether they gave birth before age 18

Percentage of mothers who

Number of mothers age 20-

24

Had first birth after age 18 Had first birth before age 18

Sexual behavior and HIV: Further Analysis Ideas

Associations between

sexual behavior in the

past 12 month and

use of contraception,

knowledge of HIV,

HIV testing etc.

Use of contraceptionPercentage of women age 15-24 who have had sex in last 12 months who are using (or whose partner is using)

a contraceptive method, Bhutan, 2010

Percent of women age 15-24 who are using:

Number of womenNo method

Any modern method

Any method

Area Urban 32.1 52.9 52.9 528

Rural 36.5 50.6 50.6 1410

Age 15-19 53.7 28.1 28.1 338

20-24 31.4 56.1 56.1 1600

Number of living children 0 58.4 11.9 12.0 537

1 28.8 62.2 62.2 905

2 21.3 74.5 74.5 422

3 29.0 67.3 67.3 68

Marital status Currently married/in union 33.3 52.7 52.8 1843

Formerly married/in union or never married

75.3 21.2 21.2 95

Education None 34.7 52.5 52.5 1103

Primary 33.9 53.8 53.8 305

Secondary + 37.5 46.9 47.1 530

Wealth index quintiles Poorest 36.1 53.1 53.1 387

Second 42.5 45.3 45.5 395

Middle 37.1 49.8 49.8 430

Fourth 27.6 56.8 56.8 461

Richest 33.9 49.7 49.7 264

Total 35.3 51.2 51.2 1938

Attitudes towards domestic violence

15-19 20-24 25-29 30-34 35-39 40-44 45-49Age

50

55

60

65

70

75

80

70.1 70.3

65.4

68.8 68.3 68.6 67.7

Percentage of women age 15-49 who believe a husband is justified in beating his wife for any of five reasons by age group, Bhutan,

2010

Perc

enta

ge

Further analysis

• Special sub-populations among youth

• Eg. 1: Are Urban youth more at risk for poor health outcomes?

• Eg. 2: Are children in youth-headed households more deprived of basic needs?

Keep in mind the limitations of the data related to sample design and sample size

Thank you