Pseudo-cohort analysis - trends in smoking data using the General Household Survey Melissa Davy...

Pseudo-cohort analysis - trends in smoking data using the General

Household SurveyMelissa Davy

Office for National Statistics

Introduction

• Why we carried out pseudo cohort analysis (PCA)• The advantages and disadvantages• The survey we used in our analysis• The methods we used • Work through an example

Why is it useful to look at cohort analysis?

• Interested in inequalities over time and by birth cohort

• People in different birth cohorts have different experiences

• Cohort analysis provides a better understanding of how events change over time

What is pseudo-cohort analysis?

• Cohort analysis - panel data

- same individual

• Pseudo-cohort analysis - cross-sectional data - average experience of a given cohort

• For example- aged 20 to 25 in a 1980 survey= 21 to 26 in 1981= 22 to 27 in 1982= 44 to 49 in 2004.

Advantages of pseudo-cohort analysis

(1) Uses data that are already available

(2) New sample each year so no problem of non-random attrition

(3) Less burden on respondents

(4) More frequent data

Disadvantages of pseudo-cohort analysis

(1) Variations in the nature of the samples surveyed

(2) Looking at average experience of the cohort limits the use of the data

(3) Recall bias

(4) Not straightforward

(5) Small cell sizes

General Household Survey

• Dataset goes back more than 30 years

• The GHS covers a range of topics

• Relatively large sample size

• High quality data source

Extracting the data

– create a database which includes all survey years

– create a birth cohort variable

• Disadvantages

- Time consuming

• Advantages- Valuable research tool- Exploiting full potential of the GHS data- Makes time series analysis easier

Creating the dataset

• Long process documented in:

Uren Z (2006) The GHS Pseudo Cohort Dataset (GHSPCD): Introduction and Methodology. Survey Methodology Bulletin, no 59, pp25-37.

• Available at: www.statistics.gov.uk/cci/article.asp?ID=1637

• contains over 40 variables,• records for over 800,000 individuals.

The smoking example

Analysis of smoking among men

• trends over time• trends by age• pseudo-cohort analysis

- interaction of time and age

Percentage of male cigarette smokers at the time of interview by year, Great Britain

0%

10%

20%

30%

40%

50%

60%

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004Year

Percentage

Percentage of male cigarette smokers at the time of interview by age in the 1970s, Great Britain

0%

10%

20%

30%

40%

50%

60%

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80

Age

unadjusted

Percentage

Percentage of male cigarette smokers at the time of interview by age in the 1970s, Great Britain

0%

10%

20%

30%

40%

50%

60%

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80

Age

unadjusted

adjusted

Percentage

Percentage of male cigarette smokers at the time of interview by age and decade, Great Britain

0%

10%

20%

30%

40%

50%

60%

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80

Age

1970s

1980s

1990s

2000s

Percentage

Percentage of male cigarette smokers at the time of interview by birth cohort and age, Great Britain

0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONMLK

JIH

G

F

E

D

CB

A

Birth Cohorts

1981-1985 A1976-1980 B1971-1975 C1966-1970 D1961-1965 E1956-1960 F1951-1955 G1946-1950 H1941-1945 I1936-1940 J1931-1935 K1926-1930 L1921-1925 M1916-1920 N1911-1915 O1906-1910 P1901-1905 Q1896-1900 R

Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONML

KJI

H

G

F

E

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONMLK

JIH

G

F

E

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONML

K

JI

H

G

FE

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONMLK

JIH

G

F

E

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80

Age

RQPONMLKJIH

G

FE

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONML

KJI

H

G

F

E

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80

Age

RQPONMLKJIH

G

FE

D

CB

A

Birth Cohorts


Percentage


0

10

20

30

40

50

60

70

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80Age

RQPONMLK

JIH

G

F

E

D

CB

A

Birth Cohorts


Percentage

Main findings

• At every age, men smoke less than the previous generation.

• Not due to established smokers giving up more rapidly

• In the most recent cohorts

- fewer men were starting to smoke - but were then giving up at a slower rate than in the

past.

• Smoking prevalence rates may be stabilising.

Conclusion

• Pseudo-cohort analysis gives us a better understanding of the GHS smoking data

Pseudo-cohort analysis - trends in smoking data using the General Household Survey Melissa Davy...

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