EVALUACIÓN

Various measures of socioeconomic circumstances used in the health literature have been thoroughly reviewed by several authors (Krieger et al., 1997, Lynch and Kaplan, 2000, Galobardes et al., 2006b, Galobardes et al., 2006a,

Galobardes et al., 2007). This section will discuss the major individual- and composite area-based measures of socioeconomic position, which are used in epidemiological research, and the measures of SEP that will be used in this body of work.

2.3.2.1 Individual-level measures of SEP

Individual-level measures of SEP used in health research measure some form of individual wealth or asset and to some extent are correlated because they all measure aspects of the underlying socioeconomic stratification, acting at various stages of the life course (Galobardes et al., 2007). However, comparing

measures between countries and cultures is often difficult as levels may be country or culturally specific.

2.3.2.1.1 Education

Education is one of the most frequently used measure of SEP (Galobardes et al., 2006a). It attempts to capture the knowledge-associated assets of an individual and can in part measure early life SEP in a life course approach. It can be

measured as a categorical variable based on definite educational levels achieved and/or as a continuous variable based on the number of years in formal

education. The strengths of education as a measure of SEP include its relative simplicity of measurement in self-administered questionnaires, its relevance to people regardless of age, gender, ethnicity or working status, relatively less stigmatisation (compared to income) and that it remains broadly stable over a life course (Krieger et al., 1997, Galobardes et al., 2006a). However, limitations involve the potential of obscuring social mobility as more individuals in recent years have higher years of education compared to the older cohorts (Galobardes et al., 2006a). When considering the span of educational levels, the range for income and/or wealth is far-reaching, thus making it a relatively less sensitive measure in assessing the magnitude of socioeconomic inequalities in health (Krieger and Fee, 1994). This measure of SEP may pose some challenges in international studies due to differences between educational systems in various countries.

The importance of measuring parental educational level as a measure of

childhood SEP affecting health has been emphasised (Krieger et al., 1997). More specifically, educational attainment has been attributed to the acquisition of health related knowledge, attitudes and beliefs, lifestyle behaviours and optimal use of health services (Galobardes et al., 2006a), parental characteristics highly associated with health (Finlayson et al., 2007).

2.3.2.1.2 Occupational- based measures

Occupation-based measures are traditionally used for measuring SEP in the UK, where social stratification has historically been conceptualized in terms of occupation (Galobardes et al., 2007).

There are various indicators based on occupation, with most studies using the current or the longest held occupation as a measure of adult SEP. The oldest and the best known official measure of social class in the UK until 2001 was the British Registrar General’s social class (RGSC) which summarized occupations to represent ‘‘social grades’’ (1990).

Galobardes et al. (2006b) outlines the limitations of the RGSC for its weak theoretical basis, considering the subjectivity of assigning individuals into categories based on prestige. In addition, it does not take into account

continuous changes in the occupational structure, such as the reduced number of people working in unskilled and semi-skilled manual occupations, or the increased number of working women. It also struggles with categorizing groups outside the active labour force (non-retired unemployed, homemakers, retired adults etc.) and its limited recognition of differences between individuals in the same occupation group in terms of both education and income (Krieger et al., 1997). Nevertheless, the RGSC has widely been used to describe socioeconomic inequalities in health mainly due to its past widespread use in the UK in many censuses and surveys over a long period and its adaptations used in many

European countries, making comparability between studies easier (Galobardes et al., 2006b).

Due to the limitations discussed above, in 2001 the Office for National Statistics in the UK adopted the UK National Statistics socioeconomic classification (NS SEC) as its official occupation classification (Table 2-1) (2005). The NS-SEC is based on the Goldthorpe Schema (Erikson and Goldthorpe, 2002) and measures employment relations and conditions of occupations as opposed to skill and social standing. It can be derived based on the level of detail of the employment status available (full, reduced and simplified) as a categorical measure.

Additionally, there are procedures for classifying the unemployed (2005). While there is an order to the occupational groups in the NS-SEC classification, it is not in a strict hierarchical order.

One of the strengths to using NS-SEC is its theoretical base, which may help in the development of causal narratives to explain a part of the frequently observed socioeconomic gradient in health.

Table 2-1: The National Statistics Socio-economic Classification Analytic Classes

There are various other occupational social classification schemes detailed by Lynch and Kaplan (Lynch and Kaplan, 2000) and Galaborades et al. (2006b). However, most have not been updated regularly.

2.3.2.1.3 Income

Galobardes et al. (2006a) considers income as the most direct measure of material circumstances with a cumulative effect over the life course, measured through direct reporting of monthly or yearly income. However, it is considered to be a ‘sensitive’ indicator as individuals may be reluctant to provide such information. This measure also has limitations of being most likely to change over a time period and might only partly capture SEP, as it does not include assets, inherited wealth etc. It is more difficult than education to be compared across countries. Furthermore, income for young and older adults may be a less reliable indicator of their true SEP as it varies with age. To be comparable across households, it is recommended that household rather than individual

1 Higher managerial and professional occupations 1.1 Large employers and higher managerial

occupations

1.2 Higher professional occupations

2 Lower managerial and professional occupations 3 Intermediate occupations

4 Unskilled

5 Small employers and own account workers 6 Lower supervisory and technical occupations 7 Semi-routine occupations

8 Routine occupations

income is collected along with family size and number of dependents under the reported income.

2.3.2.1.4 Benefits claimant

Individuals claiming/entitled to certain benefits or whose income is fully derived from benefits may be used as an indicator of low income and therefore low SEP. The main strength of this measure is the availability of robust sources for this data that are regularly updated; for e.g. The Department for Work and Pensions. However, this measure only gives a picture about those at one end of the

socioeconomic spectrum. In addition, only those who claim benefits may be identified and not those who are eligible for benefits. They are also arbitrary indicators of low income that do not have a scientific definition, but projecting rules defined by the Government (Shaw et al., 2007).

2.3.2.1.5 Housing tenure

Housing tenure is a marker of material circumstances (Galobardes et al. 2006a) and differences in housing tenure have shown patterns of inequalities in health in Scotland previously (Macintyre et al., 1998). It is measured by checking if the housing of the individual is owned (owned/being bought with a mortgage), or rented from a private or social landlord (Galobardes et al. 2006a). Although it has the advantage of being relatively easy to collect, it has limitations of area specificity, consequently proving difficult to compare across studies (Shaw et al., 2007).

2.3.2.1.6 Other measures

A vast number of other measures of individual SEP exists; they include: a range of country-specific occupational indices, housing conditions, household

amenities (Galobardes et al. 2006a), indicators of wealth (Lynch and Kaplan, 2000) etc. Other ‘proxy’ measures of individual SEP described by Galobardes et al. (2006a) include: number of siblings, marital status and some health measures (e.g. infant or maternal mortality)

2.3.2.2 Area-based measures (Indices of deprivation)

Area-based measures utilise data from census or other administrative databases to aggregate the data at a small area level (Galobardes et al., 2006b) and

classify individuals by the socioeconomic properties of their area of residence (usually based on postcode). However, there is a potential for misclassifying individuals, as all individuals in an area may not necessarily be of the same SEP.

2.3.2.2.1 Carstairs index

The Carstairs score and its deprivation categories (DEPCAT) has been a commonly used indicator of deprivation in Scotland which is calculated from various census variables- Overcrowding, male unemployment, car ownership and low social class (IV & V). Geographical areas are based on postcode sectors with an average population of 5,000. A DEPCAT score is calculated for each postcode sector, classified from DEPCAT 1 (most affluent) to DEPCAT 7 (most deprived) (Carstairs and Morris, 1990).

2.3.2.2.2 Scottish Index of Multiple Deprivation

The Scottish Executive, in response to the August 2003 report ‘Measuring Deprivation in Scotland: Developing a Long-Term Strategy’, developed the Scottish Index of Multiple Deprivation (SIMD) which identifies small area concentrations of multiple deprivation across Scotland. The SIMD 2009 used in this body of work combines 38 indicators across seven domains, namely: income, employment, health, education, skills and training, housing, geographic access and crime at the level of ‘data zones’. Data zones are groups of 2001 census output areas and have populations of between 500 and 1,000 residents with arguably similar social characteristics. SIMD ranks are divided into quintiles, with quintile 1 covering the most deprived 20% of Scottish postcode areas (The

Scottish Government, 2009b). Criticisms against SIMD arise from the use of an area-based measure to identify individuals as some who are materially

disadvantaged live in areas that are not particularly deprived in terms of SIMD and vice-versa (Shaw et al., 2009). SIMD 2009 has now been superseded by SIMD 2012. However, it is considered appropriate to use the SIMD most close to data collection.