with physicians, nurses, dietitians, social workers, and diabetes educators; and telephone interviews with patients. The study was narrowly focused on capturing the pervasiveness of the causal relationship between socioeconomic status and outcomes for diabetes. Consequently, qualitative studies that are alert to structural influences on the individual behaviors they observe and monitor do have potential for increasing our understanding.
Determining the effects of structure in quantitative studies requires the construction of independent variables having collective properties indicative of such structures. The most powerful structural predictor of poor health is social class or SES typically consisting of measures of income, education, and occupational prestige. Even though each of these variables is distinct and reflects differing dimensions of social stratification, they are nevertheless interrelated and structurally connected (Adler et al. 1994; Wolfe 2015). They can be viewed separately or in combination with each other as structural variables within which class-based behaviors and norms are created and imposed on individuals through socialization and experience. Age, gender, and race can also be measured as structural variables influencing health. Another strategy is to apply class categories to the family/household rather than the respondent/individual. The status of the person (or perhaps persons) in the family/household with the highest level of labor market participation can be conceptualized as providing a master social status to the household representing its collective position vis-à-vis the marketplace. This outcome is evident when the parent’s social standing is passed to their children and the household as a whole is accorded a particular social standing in the community.
As for the effects of neighborhoods on health, an index of living conditions can be constructed from the value of homes in particular neighborhoods or census tracts and the extent of basic utilities, modern plumbing, heating, air-conditioning, hot water, and the like, as well as the presence of parks, recreational facilities, restaurants, pharmacies, and grocery stores. Other health-related variables are the ready availability of physicians, clinics, and hospitals, along with crime rates and various measures of public safety. Variables such as these are not the properties of similar individuals, but those of structures that constrain or enable individuals to lead healthy lives.
Recent developments in statistics for estimating hierarchical linear models now provide efficient estimations for a wider range of applications than previously possible. Hierarchical linear modeling (HLM) makes it feasible to test hypotheses about relationships occurring at different levels and also assess the amount of variation at each level (Raudenbush and Bryk 2002). Briefly stated, HLM tests the strength of the interaction between variables that describe individuals at one level (level 1), structural entities (like households) at the next level (level 2), and sequentially higher levels (e.g., neighborhoods, communities, social classes, nations), if necessary, depending on the variable’s conceptual position in a structural hierarchy. By comparing changes in the regression equations, the relative effects of each level of variables on health outcomes can be simultaneously determined. As Stephen Raudenbush and Anthony Bryk (2002: 5) point out, “the barriers to the use of an explicit hierarchal modeling framework have now been removed.” Therefore, the capability to examine complex social dynamics and the links extending from society to the individual is now possible.
A caveat concerning multilevel measures of social settings involving both collectives and individuals is that such measures in the past have often been subject to problems of ecological inference. What this means is that the association of two variables at aggregated levels may not reflect the association between the same two variables at the individual level. However, rather than treat structural variables as an aggregation or sum of individual-level variables, problems of ecological inference can be overcome by using structural variables that are a direct measure of the structure itself, such as measures of neighborhood characteristics that reflect the neighborhood not the individuals who reside in it (Thisted 2003). This way the direct effects of the neighborhood on individuals can be determined since they are not confounded by individual characteristics. Properly employed, multilevel measures can ascertain the effects of higher levels of social organization on individuals.
There are other multilevel statistical techniques like variance component analysis by maximum likelihood (VARCL) and procedures like MLn and MLWIN that can be used. The point is that adequate statistical methods now exist that allow sociologists to test hierarchical models that better reflect the reality of everyday situations in which individuals experience the layers of social structures that exist in their lives and affect their health.
Conclusion
A number of factors, including the pervasiveness of the biomedical model in conceptualizing health problems, a research focus on health from the standpoint of the individual, and the former lack of appropriate statistical techniques, have all combined to relegate social structural factors to the background in the quest to discover the social connections to health. But this situation is changing in the direction of a more realistic approach in which the relevance of structure is not only being recognized but endowed with causal properties with regard to health and disease.
In fact, it can be argued that a major paradigm shift toward a neo-structural perspective is now appearing in twenty-first-century medical sociology. This is seen in the greater emphasis upon structure in both theory and research that is stimulated by the need to acquire a more comprehensive understanding of the social causes of health and illness in contemporary society. Considerable work in medical sociology is evidence of this paradigm shift (see for example, Cockerham 2013a, 2013b; Hargrove 2018; Karlsen and Nazroo 2002; Lippert 2016; Mollborn and Lawrence 2018; Simons et al. 2019; G. Williams 2003). As the old gives way to the new in medical sociology, the field is headed toward a fundamentally different orientation than the one prevailing in the late twentieth century, requiring new theoretical orientations and the adaption of older ones to account for change.
We now know that the biomedical model is limited in its application to problems in living and behavioral models emphasizing the individual’s failure to connect with structural effects on health. However, hierarchical linear modeling can be used to investigate multiple levels of social life simultaneously and so new ways of explaining the causal effects of structure on health are likely to be forthcoming. Society does act back on individuals and, in doing so, affects their health, diseases, and mortality. This outcome needs to be more fully explained by medical sociologists in their future work.
This does not mean that micro-level methods and theories like symbolic interaction are obsolete. Quite the contrary, qualitative research provides some of the most insightful data available on social relationships and situations. It puts a human face on what would otherwise be only a narrative of numbers. However, a neo-structuralist approach, in turn, allows medical sociologists to more accurately measure the effects of structure on individuals and assess structure’s causal qualities. The fact that structure may be able to overwhelm the influence of agency or individual-directed action in some social situations does not negate the need to account for micro-level phenomena. The ultimate goal of medical sociology, and, for that matter, all of sociology, is an accurate assessment of social life at all levels, which is only possible by accounting for the interplay of the individual and society in empirical settings. By incorporating methods which span levels of social reality, the new medical sociology should be able to take the field to an even higher level of development. The next chapter will examine the current state of sociological theory in relation to the social causation thesis and the remainder of this book will explore the coming neo-structural component of the field by further examining the causal qualities of structure in relation to health and disease.
Critical Thinking Questions
1 Do you agree that society can make people sick? If so, how?
2 What is the key link in the social transmission of smoking?
3 What are the four stages of epidemiologic transmission theory?
4 Describe the relationship between genes and
