|Year : 2020 | Volume
| Issue : 1 | Page : 4-8
Socioeconomic status: A theoretical framework for the development and use of assessment tools
Pradeep R Deshmukh, Sujiv Akkilagunta
Department of Community Medicine, AIIMS, Nagpur, Maharashtra, India
|Date of Submission||15-Apr-2020|
|Date of Acceptance||21-Apr-2020|
|Date of Web Publication||5-Jun-2020|
Department of Community Medicine, AYUSH Building, AIIMS Campus, Plot No. 2, Sector-20, MIHAN, Nagpur - 441 108, Maharashtra
Source of Support: None, Conflict of Interest: None
Decades of research have established the relationship between socioeconomic status (SES) and health. The tools for the assessment of SES have evolved ever since, growing in complexity over time. The purpose of measuring SES in health research is twofold – to causally link the exposure to poor SES with health state and to find out the causal mechanisms to devise programmatic interventions. In health research, SES should be viewed as a determinant of unequal distribution of health resources that further leads to health disparities. We refer to socioeconomic position as an umbrella term for social stratification that defines individuals/households based on the present circumstances. Socioeconomic position can be measured in three distinctly varied ways – socioeconomic disadvantage, social class, and SES (or position). Tools for the measurement of SES can be classified as indices based on income and expenditure, indices bases on occupation and education, wealth index combining education, and asset-based wealth index. Each tool has its own theoretical assumptions – Weberian, Marxist, or Functionalist perspectives. The choice of tool should depend on theoretical assumptions. The tool should be comprehensive, including all three dimensions – education, occupation, and income. Life-course perspective, linking the timing of exposure to poor SES over the life course is useful in the development of interventions. Study tools incorporating a life course perspective in the measurement of SES are the need of the hour.
Keywords: Life course perspective, Marx philosophy, questionnaire tools for socioeconomic status, social class, socioeconomic status, Weberian philosophy
|How to cite this article:|
Deshmukh PR, Akkilagunta S. Socioeconomic status: A theoretical framework for the development and use of assessment tools. Indian J Community Fam Med 2020;6:4-8
|How to cite this URL:|
Deshmukh PR, Akkilagunta S. Socioeconomic status: A theoretical framework for the development and use of assessment tools. Indian J Community Fam Med [serial online] 2020 [cited 2020 Oct 20];6:4-8. Available from: https://www.ijcfm.org/text.asp?2020/6/1/4/286026
| Introduction|| |
The relationship between socioeconomic status (SES) and health has been observed since times immemorial. Published literature on social disparities in health can be dated back as far as the 1800s. Edwin Chadwick reported a difference in age at death among different social classes as early as 1840., Whitehall study in the 1960s demonstrated not only an association between employment grade and cardiovascular mortality, but also a definitive gradient across categories. The administrative personnel had least mortality, whereas clerical and other lower-class workers had the highest mortality.
The interest in health outcomes then slowly progressed over the years, from mortality to morbidity, and then, finally to the level of risk factors. Further research focused on the causal mechanisms linking one or more components of SES with these health outcomes. Based on the available data, a framework was developed by Solar and Irwin to understand how social determinants are linked to health outcomes. This entire gamut of research was intended to develop interventions that reduce socioeconomic disparities in health.
It remains the fact that SES was and will be a common exposure studied in research of health outcomes. Unless it is causally linked to the health outcome and the causal mechanism delineated, it would be of little use in the development of population-based interventions.
Although several tools have been developed to measure SES, only a handful of them have been used routinely. Our understanding of SES measurement has evolved in terms of the philosophy, perspectives, variables, and their interplay.
| Theoretical Background for Social Stratification in Health Research|| |
Social stratification can be termed as the process of classifying individuals, households, and communities on the basis of socioeconomic parameters. The purpose of social stratification may vary with the field of research. In the field of health research, it should be viewed as a determinant of unequal distribution of health resources, thereby leading to health disparities [Figure 1]. It is, therefore, pertinent to answer these questions before formulating a study tool – i. What resources affect health? ii. Is it only material resources as determined by economic capital? or Is there a role of cultural and social capital?
These queries help us to freely list the items required to build an assessment tool. The inclusion or non-inclusion of these items ought to be further guided by the theories of social stratification. These theories discussed later in the text provide a basis to understand how social stratification is linked to damaging exposures, health-protective resources and ultimately health.
Before proceeding further, it is necessary to clarify the terms used to denote social stratification. The terms can be broadly classified based on whether the stratification is based on the individual's family of origin (socioeconomic background) or the present circumstances. The conceptual framework adapted from a report on measurement of SES by the Australian National University is presented in [Figure 2]. In this article, we refer to socioeconomic position as an umbrella term for those that define individuals/households based on the present circumstances. Socioeconomic position can be measured in three distinctly varied ways arranged in the order of complexity: socioeconomic disadvantage, social class, and SES (or position).
Socioeconomic disadvantage classifies people into two groups (dichotomous) based on their position of social disadvantage. For example, certain ethnic, racial, and caste groups suffer from systematic socioeconomic disadvantage. In India, belonging to a backward caste is expected to confer socioeconomic disadvantage and adequate policies are adopted to alleviate it. Since socioeconomic disadvantage is often defined on verifiable characteristics, it is easier to measure.
Social class denotes the classification of groups based on their relationships to production. The term has its origin in the Marxist philosophy, where the proposed means of relationship is exploitation. The laborers are exploited by owners, and the middle class may be exploiters or exploited. Social class is measured as a nominal variable. The examples include the International Standard Classification of Occupations by ILO, Australian Standard Classification of Occupations, and Occupational classification by Ministry of Labor (India). Since it is dependent on economic relationships in society, it is difficult to measure them meaningfully at different levels – individual, household, and society and over life span., It is often a tedious task, either to group the occupations under one head or to rank them from high to low. Such ranking of occupations may raise a couple of questions – Is the ranking true in terms of distribution of resources? and Does the ranking reflect the gradient of risk for the specific disease in question?
Socioeconomic position includes both resource-based and prestige-based measures. Resources may be material resources, social resources, assets including income and wealth, and educational qualification. Prestige-based measures refer to the ranking of individuals or households in the social hierarchy with reference to people's access to and consumption of goods, services, and knowledge. SES and socioeconomic position are often used interchangeably. Since the term SES seems to emphasize on prestige measures, socioeconomic position is preferred. These are further related to the status of their occupation, income, and educational level. Socioeconomic position has its roots in the Weberian philosophy. Weber's philosophy uses multiple dimensions such as education, occupation, and income to classify the society. However, these dimensions may, in turn, be determined by the individual's relationship to production. Socioeconomic position can be measured as a continuous variable, thus providing an advantage over social class which can only be measured as a nominal categorical variable.
Functionalist theory, on the other hand, may be viewed on the surface as an amalgamation of Marxist and Weberian theories. It assumes that stratification is necessary for society to progress. Stratification is based on the characteristics of the individual and the occupying position. The relative importance of a position depends on its functional importance in society. Occupational prestige scale is an example of a tool based on functionalist theory.
Since socioeconomic position has definitive advantages over other measures, it is most often used in health research. After laying down the theoretical foundations, the next step would be to choose the specific measures that can be included in the final assessment tool. How each of these specific measures is formulated, will have an impact on the study outcomes.
| Dimensions of Socioeconomic Position|| |
Socioeconomic position is measured along three domains – education, occupation, and income. Several scales have been devised using these domains individually or in combination.
The impact of education on health is well established. However, it is pertinent to ask how education is measured? In some studies, literacy had shown better relationship compared to the years of education. Some studies have shown the highest degree achieved is a better predictor when compared to the years of schooling. However, the researcher should have a hypothesis on how education is linked to the study outcome. The choice of measure should be based on the hypothesis and the sociocultural context of the study population.
Occupational measures are often not standardized across health research. The classification of occupation varies in relation to the health event studied. For example, when it comes to a relationship with obesity, an occupational stratification using physical activity may be preferred. Some occupations may be associated with definite health exposures. For example, famers are exposed to pesticides, exposure to radiation among nuclear plant workers, etc., If occupation is being studied as a determinant of health, it needs to be assessed in terms of the social status and the level of income. If an individual is unemployed, it is necessary to explore the reason for unemployment.
Income assessment may be deemed simple in developed countries where a large proportion of the working sector is organized. However, in developing countries like India, where majority still belong to the unorganized sector, data on income are often unreliable. Since income is related to welfare measures, the individuals may not report the true income. Hence, wealth assessment in the form of assets is preferred.
Inclusion of measures from all three dimensions results in some level of collinearity. It is a well-known fact that education improves the employment opportunities and thereby income. Hence, it is often argued that education cannot be an independent determinant for health. This is also termed as sheepskin effect. However, on the contrary, education may influence health by increasing the awareness of health promotion measures. Formal schooling improves cognitive skills, increases the chance of healthy social environment, and reduces the chance of involvement in health detrimental behavior – all of which improve health. Collinearity between the measures can be assessed and reduced to some extent using the statistical tools.
| Review of Tools|| |
With this background, we will review the tools available for the assessment of socioeconomic position. A narrative review on the usage of SES tools in South Asia has classified them into five groups: indices based on income and expenditure, indices bases on occupation and education, wealth index combining education, asset-based wealth index (using principal component and factor analysis methods), and others. Asset-based wealth indices were most commonly used reported by 54% of the studies, followed by indices based on income and expenditure (30%), and wealth index combining education (8%).
Modified BG Prasad classification is an example of income-based index and carries with it all the drawbacks of reporting. Modified Kuppuswamy Scale is an example of wealth index combining education. It suffers from the drawbacks of classifying education and occupation. Asset-based wealth indices such as wealth index and standard of living index are by far the most comprehensive including multiple items for each dimension and adjustment for collinearity by the use of factor analysis methods.
There is a wide variation in the assessment of socioeconomic position by these scales. A study comparing wealth indices such as Kuppuswamy Scale, Modified Kuppuswamy Scale, Below Poverty Line Index, and Multidimensional Poverty Index showed wide variations in the assessment and poor agreement between the tools. The agreement ranged between kappa of 0.01 and 0.15. The proportion of low SES varied between 1% and 55.3%. Such wide variation calls for a valid comprehensive tool adaptable to different contexts.
| Socioeconomic Status and Causality|| |
The goal of assessment of SES is establishing causality to health events and delineates the mechanism of causation. Temporality of association is an important criterion for causation. However, the studies associating SES with health are often cross-sectional in nature. Although there is little doubt on overall relationship between SES and health, the possibility of reverse causation cannot be excluded. It is established that poor educational status is associated with smoking. However, initiation of smoking often occurs during adolescence. The researcher in his/her assessment should rather be asking – What was the educational status of the individual when he/she initiated smoking?
While temporality strengthens causal argument, it is important to understand how timing of exposure to low SES over life course could lead to a given health event. This information is crucial to develop interventions. For example, it has been reported that exposure to low SES during childhood and adolescence is related to obesity in adults. This is termed as sensitive or critical period perspective. In such cases, it is important to intervene during childhood to prevent adverse outcomes.
The accumulation of risk perspective, on the other hand, suggests that exposure to low SES at multiple time periods cumulatively causes the health event. Such association has been observed in studies on mortality. The social mobility perspective suggests that it is a change in SES which affects health. Upward mobility from low to high SES is deemed favorable and vice versa.
Thus, it is not enough to just measure SES using a valid tool. However, the timing of its measurement over the life course is crucial to understand the causal mechanisms.
| Conclusion|| |
SES is often included in research as an exposure variable, with little understanding of how it affects the health event in question. In the context of health research, it should be viewed as the quantification of unequal distribution of health resources. The choice of tool should depend on the theoretical assumptions. The tool should be comprehensive including all three dimensions – education, occupation, and income. The assessment of the time of exposure over the life course is crucial for the development of interventions. Incorporating a life course perspective in the measurement of SES is the need of the hour.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]