1

Multiple Indicator Cluster Surveys Data Interpretation, Further Analysis and

Dissemination Workshop

Access to Mass Media and Use of ICTLife Satisfaction

Tobacco and Alcohol Use

2

Background

Added as a result of work on adolescents and young people

Limited experience (mainly MICS) Both in Women and Men questionnaires

3

Overview of MICS5 contents

Access to Mass Media and Use of Information & Communication Technologies

Exposure to mass media - 1 table for women and 1 table for men

Use of computers and internet- 1 table for women and 1 table for men

4

Background

Mass media Newspapers Radio Television

ICT Computers Internet

Exposure to influences outside the local community.

Can be used as a starting point for any mass media campaigns

Exposure to global influences, communication, learning opportunities

Even for the less educated

5

Table MT.1: Exposure to mass media (women)Percentage of women age 15-49 years who are exposed to specific mass media on a weekly basis, Country, Year

Percentage of women age 15-49 years who:

All three media at

least once a week1

Any media at

least once a week

None of the media

at least once a week

Number of

women age 15-49 years

Read a newspaper at least once a

week

Listen to the radio at

least once a week

Watch television at least once a

week

1 MICS indicator 10.1 - Exposure to mass media

MT.1M - Men

Percentages do not add to 100

Individual items All three

6

Table MT.1: Exposure to mass media: Percentage of women age 15-49 years who are exposed to specific mass media on a weekly basis, Serbia 2010

Percentage of women age 15-49 who:

All three media at

least once a week [1]

No media at least once a week

Number of women

age 15-49 years

Read a newspaper at least once a

week

Listen to the radio at least once a week

Watch television at least once a

weekAge 15-19 76.3 78.6 97.9 63.6 0.5 659

20-24 79.4 79.8 97.5 65.2 0.3 70525-29 75.4 73.6 97.3 58.2 0.9 84630-34 74.2 69.5 98.0 57.2 1.0 77535-39 76.1 73.0 98.3 58.9 0.7 79140-44 69.4 69.9 99.3 52.6 0.3 70345-49 71.9 65.3 99.0 49.8 0.0 905

Area Urban 79.8 70.7 98.1 60.4 0.6 3155Rural 67.2 74.9 98.3 53.6 0.5 2230

Education None (.0) (52.1) (96.6) (0.0) (0.0) 27Primary 44.2 63.7 97.5 34.4 1.9 704Secondary 76.2 72.3 99.0 58.4 0.3 3067Higher 86.2 76.9 97.0 67.3 0.4 1587

Wealth index quintiles

Poorest 44.6 66.2 97.0 35.2 1.9 751Second 71.2 77.2 99.2 57.9 0.2 1175Middle 79.2 71.1 98.5 60.2 0.1 1134Fourth 81.7 72.7 97.5 62.3 1.0 1172Richest 85.7 72.7 98.3 64.6 0.1 1153

Total 74.6 72.4 98.2 57.6 0.5 5385

Upper middle income country

with high level of education

7

Table MT.1: Exposure to mass media: Percentage of women age 15-49 years who are exposed to specific mass media on a weekly basis, Serbia 2010

Percentage of women age 15-49 who:

All three media at

least once a week [1]

No media at least once a week

Number of women

age 15-49 years

Read a newspaper at least once a

week

Listen to the radio at least once a week

Watch television at least once a

weekAge 15-19 76.3 78.6 97.9 63.6 0.5 659

20-24 79.4 79.8 97.5 65.2 0.3 70525-29 75.4 73.6 97.3 58.2 0.9 84630-34 74.2 69.5 98.0 57.2 1.0 77535-39 76.1 73.0 98.3 58.9 0.7 79140-44 69.4 69.9 99.3 52.6 0.3 70345-49 71.9 65.3 99.0 49.8 0.0 905

Area Urban 79.8 70.7 98.1 60.4 0.6 3155Rural 67.2 74.9 98.3 53.6 0.5 2230

Education None (0.0) (52.1) (96.6) (0.0) (0.0) 27Primary 44.2 63.7 97.5 34.4 1.9 704Secondary 76.2 72.3 99.0 58.4 0.3 3067Higher 86.2 76.9 97.0 67.3 0.4 1587

Wealth index quintiles

Poorest 44.6 66.2 97.0 35.2 1.9 751Second 71.2 77.2 99.2 57.9 0.2 1175Middle 79.2 71.1 98.5 60.2 0.1 1134Fourth 81.7 72.7 97.5 62.3 1.0 1172Richest 85.7 72.7 98.3 64.6 0.1 1153

Total 74.6 72.4 98.2 57.6 0.5 5385Similar radio and newspaper access, TV universal

Some age

differentials

Strong correlation with wealth – due to:(1) newspaper reading (2) radio

8

Further analysis/ Further work A first step for understanding access and exposure; more

detail possible May be followed up with more detailed data collection

on the nature of exposure to fine-tune media messages – frequency, timing, type

Follow-up is applicable in both cases: very high or low percentages

Data quality: check with TV ownership, literacy Supplement educational level with media May be used as a valuable independent variable for

analyzing outcomes

9

Overview of MICS5 contents

Access to Mass Media and Use of Information & Communication Technologies

Exposure to mass media - 1 table for women and 1 table for men

Use of computers and internet- 1 table for women and 1 table for men

10

Background

Mass media Newspapers Radio Television

ICT Computers Internet

Exposure to influences outside the local community.

Can be used as a starting point for any mass media campaigns

Exposure to global influences, communication, learning opportunities

Even for the less educated

11

Table MT.2: Use of computers and internet (women)Percentage of young women age 15-24 years who have ever used a computer and the internet, percentage who have used during the last 12 months, and percentage who have used at least once weekly during the last one month, Country, Year

Percentage of women age 15-24 years who have:

Number of

women age 15-24 years

Ever used a

computer

Used a computer during the

last 12 months1

Used a computer at least once a week during the last one

month

Ever used the

internet

Used the internet

during the last 12

months2

Used the internet at

least once a week during the last one

month

1 MICS indicator 10.2 - Use of computers2 MICS indicator 10.3 - Use of internet

MT.2M - Men

Ever use

Recent use

Frequency of use

Computer Internet

Internet use likely to be lower, but fairly close to computer useEver use should always be higher

12

Table MT.2: Use of computers and internet

Percentage of women age 15-24 who have:

Percentage of women age 15-24 who have:

Number of women

age 15-24 years

Ever used a compu

ter

Used a computer during the

last 12 months

Used a computer at least once a week during the last one

month

Ever used the

internet

Used the internet during the last

12 months

Used the internet at least once

a week during the

last one month

Age 15-19 95.9 94.0 86.5 89.0 86.9 79.0 65920-24 92.7 89.0 77.7 85.4 83.2 73.1 705

Area Urban 97.2 96.2 90.0 94.0 92.6 87.1 814Rural 89.9 84.3 70.0 77.0 73.7 59.4 549

Education None (*) (*) (*) (*) (*) (*) 6Primary 60.8 50.9 27.8 39.1 32.9 15.5 112Sec. 96.3 93.6 82.1 87.7 85.5 74.5 789Higher 100.0 98.7 96.1 99.0 97.9 94.2 457

Wealth index quintiles

Poorest 74.2 65.1 41.6 51.7 47.3 28.8 199Second 93.3 88.5 74.6 82.2 79.6 66.1 300Middle 98.7 97.6 89.7 94.0 90.7 82.8 272Fourth 98.8 98.8 94.2 97.0 96.8 91.0 281Richest 99.9 99.0 97.1 99.7 98.7 96.1 311

Total 94.2 91.4 82.0 87.1 85.0 76.0 1364

Sharp correlation with age and other background characteristics

13

Further work/Further analysis Check, analyze together with other media exposure May be followed up with collection of more detailed

data – social networks, type and nature of use Questionnaire allows more detailed assessment of

frequency (almost everyday, once a week, less) Further analyze, compare by gender Supplement educational level with other mass media

information May be used as a valuable independent variable for

analyzing outcomes

14

Overview of MICS5 contents

Life Satisfaction (Subjective Well-Being) Life satisfaction and happiness

- 2 tables for women and 2 tables for men

Perception of a better life - 1 table for women and 1 table for men

15

Background: Subjective Well-Being Subjective perceptions of well-being play an important

role, autonomously from objective conditions, such as income, health

Can help create a fuller picture of well-being Life satisfaction: summation of evaluation regarding a

person’s life as a whole Happiness – a fleeting, transient condition that can be

affected by numerous current factors (weather, recent incident)

Life satisfaction and happiness are sometimes used interchangeably

16

Background: Subjective Well-Being

Perceptions of a better life is also an important correlate of both life satisfaction and happiness

All of these (life satisfaction, happiness and perceptions of a better life) complete a large portion of subjective well-being

Life satisfaction included in Human Development Report in 2010 Reports on a scale out of 10, on job, health,

standard of living, purposeful life, treatment with respect, social support network

17

Background: Subjective Well-Being

World Happiness Day, since 2012World Happiness Report, since 2013New OECD guidelines 2013 –

recommendation to all national statistical agencies: Include Life Satisfaction in annual household surveys.

18

Table SW.1: Domains of life satisfaction (women)Percentage of women age 15-24 years who are very or somewhat satisfied in selected domains of satisfaction, Country, Year

Percentage of women age 15-24 years who are very or somewhat satisfied in selected domains:

Family life Friendships HealthLiving

environmentTreatment by others

The way they look

SW.1M - Men

Individual items reported – very or somewhat satisfied

19

Table SW.1: Domains of life satisfaction (women)Percentage of women age 15-24 years who are very or somewhat satisfied in selected domains of satisfaction, Country, Year

Percentage of women age 15-24

years who:Numbe

r of women age 15-

24 years

Percentage of women age 15-24 years who

are very or somewhat satisfied with

school

Number of

women age 15-24 years

attending school

Percentage of women age 15-24

years who are very

or somewhat satisfied with their

job

Number of

women age 15-24 years

who have a

job

Percentage of women age 15-24

years who are very

or somewhat satisfied with their

income

Number of women age 15-24 years who

have an income

Are attendi

ng school

Have a job

Have an

income

Continued ……..

Very or somewhat satisfied

20

Table SW.2: Overall life satisfaction and happiness (women)

Percentage of women age 15-24 years who are very or somewhat satisfied with their life overall, the average overall life satisfaction score, and percentage of women age 15-24 years who are very or somewhat happy, Country, Year

Percentage of women with

overall life satisfaction1

Average life satisfaction

score

Percentage of women who are very or

somewhat happy 2

Number of women age 15-

24 years

1 MICS Indicator 11.1 - Life satisfaction 2 MICS indicator 11.2 - Happiness

Satisfied with life, overall: very satisfied or somewhat satisfied

Average of responses to overall life satisfaction. Lower scores indicate higher satisfaction levels.

SW.2M - Men

Very or somewhat happy

21

Table SW.3: Perception of a better life (women)Percentage of women age 15-24 years who think that their lives improved during the last one year and those who expect that their lives will get better after one year, Country, Year

Percentage of women who think that their lifeNumber of women age 15-24 years

Improved during the last one year

Will get better after one year Both1

1 MICS indicator 11.3 - Perception of a better life

SW.3M - Men

Hopelessness prevalent among youth in middle income countries

The relationship between perceptions of improvement during last year and hope for the next year

Women who think their life has been improving and will continue to improve

22

Country example

23

Further analysis

Correlate with measures of objective well-being: income, education, wealth

Identify groups and compare life satisfaction: Does vulnerability correlate with life satisfaction?

Correlate happiness and perceptions with tobacco and alcohol abuse

Use as dependent variables: Determinants of satisfaction, happiness, and hope

24

Further analysis

25

Overview of MICS5 contents

Use of tobacco and alcohol Tobacco (cigarette, tobacco)

- 1 table for women and 1 table for men Cigarette (only)

- 1 table for women and 1 table for men Alcohol

- 1 table for women and 1 table for men

26

Background: Use of tobacco and alcohol

Tobacco: known risk factor for cardiovascular disease, lung and other cancers

Alcohol abuse is a serious problem in many countries. Associated with: Increased risk of accidents, cirrhosis,

hypertension, psychological illnesses, and congenital malformations. Aggravates risk of family problems

27

Background: Use of tobacco and alcohol

Information collected: Ever and current use of cigarettes and the age at

which cigarette smoking first started Ever and current use of smoked and smokeless

tobacco products The intensity of use of cigarettes, and smoked and

smokeless tobacco products Ever and current use of alcohol, and intensity of

use

28

Background: Use of tobacco

Any intensity of tobacco use is considered a (potential) health problem (Indicator 12.1)

Intensity is directly correlated with poor health outcomes

Early initiation increases length of exposure

29

Table TA.1: Current and ever use of tobacco (women)Percentage of women age 15-49 years by pattern of use of tobacco, Country, Year

Never smoked

cigarettes or used other

tobacco products

Ever users

Users of tobacco products at any time during the last one

month Number of

women age 15-

49 years

Only cigarettes

Cigarettes and other

tobacco products

Only other

tobacco products

Any tobacco product

Only cigarettes

Cigarettes and other

tobacco products

Only other

tobacco products

Any tobacco product1

Under-5s in the same household

At least one None

1 MICS indicator 12.1 - Tobacco use

"Any tobacco product" refers to cigarettes, smoked tobacco products, and smokeless tobacco products.

TA.1M - Men

30

Table TA.2: Age at first use of cigarettes and frequency of use (women)Percentage of women age 15-49 years who smoked a whole cigarette before age 15, and percent distribution of current smokers by the number of cigarettes smoked in the last 24 hours, Country, Year

Percentage of women who

smoked a whole cigarette before

age 151

Number of

women age 15-49 years

Number of cigarettes in the last 24 hours

Number of women age 15-49 years who are

current cigarette smokers

Less than 5 5-9 10-19 20+ Total

1 MICS indicator 12.2 - Smoking before age 15

TA.2M - Men

31

Table TA.3: Use of alcohol (women)Percentage of women age 15-49 years who have never had an alcoholic drink, percentage who first had an alcoholic drink before age 15, and percentage of women who have had at least one alcoholic drink at any time during the last one month, Country, Year

Percentage of women who:

Number of women age 15-49 years

Never had an alcoholic drink

Had at least one alcoholic drink before

age 151

Had at least one alcoholic drink at any time during the

last one month2

1 MICS indicator 12.3 - Use of alcohol 2 MICS indicator 12.4 - Use of alcohol before age 15

TA.3M - Men

32

Country example

33

Further analysis

Joint analysis of tobacco and alcohol use Correlate with measures of life satisfaction,

happiness, perceptions of better life Comparisons of ever and current use of tobacco

use may be indicative of reversing trends Sex differentials by social/economic groups Children and mother’s smoking habits Any correlation of alcohol with domestic violence?