Multiple Indicator Cluster Surveys
Data 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 Questionnaire
 Direct 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 1524
• 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
Percentage of women age 15-17 with comprehensive knowledge of HIV/AIDS by living arrangements,
Bhutan, 2010
30
25
Percentage
20
15
10
5
0
Living with Both Parents
Living with one parent
Not living with a biological parent
Living Arrangements
One or both parents dead
Education: Further analysis ideas
No Formal Education
Percentage of individuals age 15-24 who have never attended formal education by sex, Bhutan, 2010
Male
Area
Age
Wealth index
quintiles
Total
Urban
Rural
15-19
20-24
Poorest
Second
Middle
Fourth
Richest
Never been
to school
5.5
26.7
15.8
27.0
39.6
32.5
20.2
8.2
1.8
20.9
Number of
individuals
age 15-24
1687
4447
3349
2785
1258
1266
1250
1177
1183
6134
Female
Never been
to school
16.4
37.4
19.7
41.1
57.0
42.1
33.8
20.4
10.5
30.4
Number of
individuals
age 15-24
2112
4256
3181
3187
1061
1112
1228
1387
1580
6368
Total
Never been
to school
11.6
31.9
17.7
34.5
47.6
37.0
26.9
14.8
6.8
25.7
Number of
individuals
age 15-24
3798
8704
6530
5972
2318
2378
2478
2564
2764
12502
Education: Further analysis ideas
Tertiary Level Education Attendance
Attendance ratios of young men and women in tertiary education, Bhutan, 2010
Area
Wealth index
quintiles
Total
Urban
Gender
Tertiary
Tertiary
parity
Tertiary
education
education
index (GPI)
education net Total
net
Total
net
Total for tertiary
attendance number attendance number of attendance number of school
ratio (NAR), of men ratio (NAR), women ratio (NAR), youth age adjusted
boys
18-24
girls
18-24
all
18-24
NAR
8.9
1086
8.1
1527
9.9
2613
.92
Rural
5.8
2910
3.3
2888
4.6
5798
.57
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
6.6
3995
5.0
4415
6.1
8410
.75
Early marriage: Further Analysis
Secondary school attendance among women age 15-18 by
marital status, Bhutan, 2010
70%
60%
59.4%
Percentage
50%
40%
30%
20%
10%
0.5%
0%
Never married/in union
Ever married/in union
Reproductive and newborn health indicators by
age of woman at birth, Bhutan, 2010
100
90
80
Percentage
70
60
50
40
30
20
10
0
Received
Received
Protected against Received skilled
Delivered in
antenatal care at antenatal care 4+ neonatal tetanus birth assistance
health facility
least once by
times
skilled provider
Indicators by Age Group
15-19
20-24
25-49
Received
Child weight at
postnatal care birth below 2500
within two days
grams
Early child bearing: further analysis ideas
Early childbearing and mother’s education:
YATA18B: Literacy rate of mothers age 20-24 by whether they gave birth before age 18
Percentage of mothers who
Had first birth after age 18
Number of nonearly mothers
age 20-24
Literacy
Area
Education
Literacy
55.6
292
31.8
91
383
Rural
30.3
669
15.5
292
962
None
4.2
532
6.6
278
810
38.4
141
37.3
77
219
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
38.0
961
19.4
383
1344
Secondary +
Total
Number of early
Number of
mothers age 20- mothers age 2024
24
Urban
Primary
Wealth
index
quintiles
Had first birth before age 18
Sexual behavior and HIV: Further Analysis Ideas
Use of contraception
Percentage 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:
Associations between
sexual behavior in the
past 12 month and
use of contraception,
knowledge of HIV,
HIV testing etc.
Area
Age
Number of living children
Marital status
Education
Wealth index quintiles
Total
No method
32.1
Any
modern
method
52.9
Rural
36.5
50.6
50.6
1410
15-19
53.7
28.1
28.1
338
20-24
31.4
56.1
56.1
1600
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
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
None
34.7
52.5
52.5
1103
Primary
33.9
53.8
53.8
305
Secondary +
37.5
46.9
47.1
530
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
35.3
51.2
51.2
1938
Urban
Any
Number of
method
women
52.9
528
Attitudes towards domestic violence
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
80
75
Percentage
70
70.1
70.3
68.8
68.3
68.6
30-34
35-39
40-44
67.7
65.4
65
60
55
50
15-19
20-24
25-29
Age
45-49
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