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The UK National Statistics Socio-economic Classification and an Illustration of its Uses in Research on Health Inequalities

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Title: The UK National Statistics Socio-economic Classification and an Illustration of its Uses in Research on Health Inequalities


1
The UK National Statistics Socio-economic
Classification and an Illustration of its Uses in
Research on Health Inequalities
  • David Rose
  • Institute for Social and Economic Research
  • University of Essex

2
Overview
  • UK Government and health inequalities
  • The ESRC Review of Government SECs
  • Conceptual basis of NS-SEC
  • (4) Criterion validation of NS-SEC
  • (5) Construct validation of NS-SEC in relation
    to health data

3
Health Inequalities and Government (1)
  • Measuring and monitoring socio-economic
    differentials in mortality and other health
    inequalities in the UK has been a key part of the
    work of the office responsible for the
    registration of deaths since the establishment of
    the General Register Office (GRO) in 1837.
  • The GRO has since been subsumed within the Office
    for National Statistics (ONS) and it is now ONS
    that carries on the tradition of reporting on
    health variations today.
  • This role continues to be of major importance as
    health inequalities are as much a public health
    issue today as they were 170 years ago, when the
    GRO was set up.

4
Health Inequalities and Government (2)
  • The earliest analyses of mortality differences
    were undertaken by reference to occupation and
    industry.
  • However, from the beginning of the twentieth
    century, the development of RGSC gave a clearer
    framework for identifying and understanding
    health differentials within the population.

5
Health Inequalities and Government (3)
  • It was demonstrated that there was a class
    gradient in health in particular in mortality
    rates and despite the creation of the National
    Health Service in 1948, class inequalities in
    health and life expectancy have persisted.
  • Overall, those in partly skilled and
    unskilled occupations in RGSC IV and V had far
    higher mortality rates and lower life expectancy
    than those in professional and managerial
    occupations in Classes I and II.

6
Social Class based on Occupation
  • I Professional occupations
  • II Managerial and technical occupations
  • IIIN Skilled occupations, non-manual
  • IIIM Skilled occupations, manual
  • IV Partly skilled occupations
  • V Unskilled occupations

7
(No Transcript)
8
Health Inequalities and Government (4)
  • The Acheson Inquiry 1998
  • The weight of scientific evidence supports a
    socio-economic explanation of health
    inequalities.
  • The research task is to trace the paths from
    social structure, represented by SES, through to
    inequalities in health.
  • Health inequalities are the outcome of causal
    chains which run back into and from the basic
    structure of society.

9
Problems with RGSC (1)
No coherent conceptual basis
Therefore
  • Difficult to interpret in use
  • Difficult to maintain

10
Problems with RGSC (2)
Use outmoded industrial distinctions
  • Skill
  • Manual/Non-manual divide

11
Registrar Generals Social Classes
Simon Szreter (1984)
  • The RGSC might best be classified as a
    pseudo-analytical construction. (It never had
    any relationship to) a recognised, coherent and
    examinable body of social theory.

(The propositions that underlie RGSC are those)
of nineteenth century anthropometric and
biometric science, only with the explicit
commitment to a naturalistic and hereditarian
theory of ultimate explanation removed.
12
Registrar Generals Social Classes
Simon Szreter (1984)
  • RGSC is the Crude Inequality Index.

13
Tasks for ESRC Review
To create a single occupationally-based SEC which
would be
  • Clear conceptually
  • Analytically transparent
  • Thus easy to maintain and interpret
  • Nested
  • Bridgeable to RGSC
  • Applicable to a wide range of data

14
Conceptual basis for the NS-SEC(Goldthorpe)
  • Employment relations and conditions are central
    to delineating the structure of socio-economic
    positions in modern societies

15
The Derivation of the NS-SEC
16
Typical elements of the Labour Contract
  • Short-term exchange of money for effort
  • Payment by the time or piece
  • No occupational pension or health scheme
  • Contract easily terminated
  • Low level of job security

17
Typical elements of the Service Relationship
  • Long-term exchange of service for compensation
  • Greater job security and employability
  • Salary
  • Incremental or similar payment systems
  • Occupational pension and health schemes
  • Greater control over the job and thus trust
    between employer and employee

18
Dimensions of work as sources of contractual
hazard
Specificity of human assets
high
Difficulty of monitoring
low
high
low
19
Dimensions of work as sources of contractual
hazard, forms of contract and class locations
Specificity of human assets
high
1
5
Service relationship
mixed
Difficulty of monitoring
low
high
mixed
Labour contract
3
low
7
20
The Derivation of the NS-SEC
(1.1) (1,2,4) (4) (1.1,1.2,2)
(3,5) (6,7) (8) (8)
21
The NS-SEC
  • 1 Higher managerial
  • and professional occupations
  • (1.1 Large employers and higher managerial)
  • (1.2 Higher professional)
  • 2 Lower managerial
  • and professional occupations
  • 3 Intermediate occupations
  • 4 Small employers and own account workers
  • 5 Lower supervisory and
  • technical occupations
  • 6 Semi-routine occupations
  • 7 Routine occupations
  • 8 Never worked and long-term unemployed

22
NS-SEC 8-Class by Sex, Aged 16-74, Census 2001
23
Categories of the Operational Version of the
NS-SEC
24
Collapsing the Operational Version
The 34 categories and sub-categories may be
collapsed into
  • a nine class variable
  • an eight class variable (the official
    NS-SEC)
  • a seven class variable
  • a five class variable
  • a three class variable

25
Summary (1)
  • NS-SEC is first a conceptual construction (hence
    NS-SEC is a schema)
  • To operationalise the schema we need an algorithm
    to a detailed set of occupation-by-employment
    status units

26
Summary (2)
How well the NS-SEC schema is operationalised
depends upon two things
  • (a) how closely the basic occupational and
    employment status classifications available
    map onto the categories of the NS-SEC (i.e.
    adequacy of the derivation matrix)
  • (b) how much information is available relevant to
    the construction of the algorithm linking these
    classifications to the schema (i.e. issues of
    criterion validity)

27
Creating the NS-SEC
Data required on
  • occupation
  • employment status
  • establishment size

These then linked via the NSSEC derivation matrix
of OUG by ES units to NSSEC classes
28
The NS-SEC Derivation Matrix
29
Reduced Simplified versions of NS-SEC
  • Reduced NS-SEC - if no information on
    establishment size
  • Simplified NS-SEC - if data only
    on occupation

30
Validation studies
  • (a) CRITERION VALIDATION
  • Do measures of employment relations
    discriminate between the categories of the
    NS-SEC?
  • (b) CONSTRUCT VALIDATION
  • How well does the NS-SEC explain variance in
    theoretically relevant dependent variables?

31
Criterion validation
MEASURES OF EMPLOYMENT RELATIONS
Three conceptually separable respects in which
employment relations are differentiated according
to whether a service relationship or labour
contract prevails
  • 1 form of remuneration
  • 2 career opportunities
  • 3 autonomy with regard to time

32
Construct validation
  • NS-SEC and Health Data
  • NS-SEC and Labour Market Data

33
Table 8.6 SMRs by NS-SEC for Our Healthier
Nation causes of death, men aged 20-64, England
and Wales 1991-93
34
Hazard ratios for mortality 1986-1995 by NS-SEC
35
Figure 8.2 SMRs by NS-SEC, men aged 20-64,
England and Wales 1991-93
36
Figure 8.4 Age-specific mortality rates by
NS-SEC, men aged 20-64, England and Wales 1991-93
37
Table 8.8 Stillbirth and infant mortality rates
by NS-SEC, England and Wales, 1996
38
Table 9.5 Odds ratios and 95 confidence
intervals of low birth weight and very low birth
weight for classes of the National Statistics
Socio-economic Classification for live, singleton
births within marriage 1996-98 England and Wales
(n114,382)
39
Table 10.3 Logistic regression odds ratios of
NS-SEC inequalities in health for men and women
aged 18-59separating the long-term unemployed
and never worked
40
Table 10.4 Logistic regression odds ratios of
NS-SEC inequalities in health for men and women
aged 18-59classifying the long-term unemployed
by last main occupation
41
Causal narratives (1)
  • NS-SEC offers not improved statistical
    associations over other SES measures, but the
    possibility of explaining the associations we
    find
  • NS-SEC is measuring employment relations and
    conditions, i.e. aspects of the work situation
    and the employment contract.

42
Causal narratives (2)
  • So we can construct causal narratives which
    specify how the NS-SEC links to a range of
    outcomes via a variety of intervening variables
  • Not the case for the former government SECs,
    since it is not clear what they measure. They may
    show statistical associations with dependent
    variables of interest, but they do not lend
    themselves to causal explanations. Same for e.g.
    housing tenure, car access etc.

43
Causal narratives (3)
  • One of the major uses of SECs has been in
    studies of fertility, morbidity and mortality,
    i.e. as a means of obtaining a macro or societal
    perspective on these issues
  • NS-SEC defines structural positions which can be
    seen conceptually to exist independently of the
    individuals who occupy those positions at any
    particular time. The positions condition and
    shape the lives of their occupants
  • We are therefore linking health with social
    organisation or social structure.

44
The Whitehall Studies
  • The Whitehall Studies growing evidence that the
    amounts of control and autonomy a person has at
    work are important factors in explaining heart
    disease
  • The prospective perspective associated with
    secure, career employment among top managers and
    professionals is associated with greater control
    and autonomy at work, more self-esteem, greater
    self-care with regard to factors such as diet and
    exercise, more choice over medical treatment and
    so on.

45
Advantages of the NS-SEC
  • Conceptually clear and rigorous
  • Simple to create
  • Flexible in use
  • Improved classification of women
  • Easier to maintain
  • Better explanatory tool

46
Possible ESeC Classes (Level 1)
  1. Large employers, higher managerial and
    professional occupations
  2. Lower managerial and professional occupations
  3. Intermediate occupations
  4. Small employers and own account workers
  5. Self-employed in agriculture etc
  6. Lower supervisory and technician occupations
  7. Lower services etc occupations
  8. Lower technical occupations
  9. Routine occupations
  10. Never worked and long-term unemployed

47
The conceptual derivation of ESeC
48
Underlying ESeC Socio-economic Groups (Level 2)
Class 1 Large employers, higher managerial and
professional occupations
  • 11. Employers (other than in agriculture) with
    10 employees
  • 12. Farmers with full-time employees (or large
    business farmers)
  • 13. Higher managerial occupations
  • 14. Higher professional occupations (employees)
  • 15. Self-employed professional occupations
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