to achieve this goal. People with jobs requiring computer skills could work at home and remain employed. Conversely, lesser educated individuals were more likely to work in jobs with greater exposure to infection or be unemployed as the pandemic progressed over time. An exception regarding exposure would be health care workers on the front-line battling the infection in their patients.
When fundamental cause theory is reduced to its most basic proposition, it is the idea that resources consisting of money, knowledge, power, prestige, and social connections are vital to maintaining a health advantage. Conversely, an absence or shortage of these resources causes poor health outcomes and earlier deaths. People with resources have less risk of exposure to preventable diseases in the first place and are better able to achieve positive outcomes when they occur by employing their resources. Persons with lower income, education, and social status lacking such resources not only have greater exposure to risk and more likelihood of the risk being realized, but also a diminished capacity for preventing negative consequences. This is seen in a study by Virginia Chang and Diane Lauderdale (2009), who observed how people in higher socioeconomic groups embraced the widespread use of statin drugs to reduce cholesterol levels and lower their risk of heart attacks before those lower on the social gradient. Once generic, lower-cost statin drugs became readily available, their use extended more extensively into the working and lower classes but, more slowly, as tests for high cholesterol required visits to physicians on the part of the individual.
Another study by Karen Lutfey and Freese (2005) of patients at two diabetes management clinics in a large Midwestern American city confirmed the role of SES as a fundamental cause in health outcomes as suggested by Link and Phelan. One clinic (Park Clinic) had a primarily white, upper and upper-middle-class clientele, while the other clinic (County Clinic) served a largely racial minority, working-class, and uninsured population. The study focused on the control of blood sugar levels that is essential for the survival of diabetics, since high glucose levels, as previously noted, damage the body. The high SES patients had their own physicians that they saw regularly at Park Clinic and they joined health clubs for exercise, ate healthily, and made other lifestyle adjustments to effectively manage their diabetes. Not surprisingly, the high SES patients had significantly better blood glucose management, health, and survivability.
The patients at County Clinic saw whatever doctor was on duty at the time, had significantly longer waiting times to see a physician, lacked the financial resources to afford some needed diabetic supplies, had jobs that interfered with medication schedules, and had to take time away from their jobs to have their prescriptions filled at the clinic pharmacy since the medications there were subsidized by the state. Some of the patients needed an insulin pump but could not afford to buy one. Getting prescriptions filled was time consuming. One doctor at County Clinic called the long waits a travesty, saying a businessman would fire any doctor who made him leave work, take a bus, and then wait 30–40 minutes in line to fill a prescription, before getting on another bus to be transported back to work.
By comparing patients in two clinics that served two very different social clienteles, Lutfey and Freese found several mechanisms, what they called “meta-mechanisms,” by which SES influenced the design and implementation of diabetic control programs. These meta-mechanisms included the organizational features of the clinics (e.g., staff specialties, diabetic education services, continuity of care), structural constraints on patients (e.g., incomes, job demands, types of occupations, availability of private health insurance, location of pharmacy), and influences on patient motivation (e.g., waiting times, need to refill prescriptions, benefits and costs to compliance, lifestyle adjustments) and cognitive abilities (e.g., patient communication skills and ability to follow a regimen).
As for the medical interviews, Lutfey and Freese (2005: 1363) determined that: “Lower-SES patients may be the least skilled at articulating their problems to physicians and so would seem to gain the most from experienced medical interviewers, but, instead, the bulk of the interviewing of low SES patients was conducted by inexperienced [physician] residents.” Park Clinic also had vastly better in-clinic diabetic education services that were unavailable to the County Clinic patients who might have benefited more, since their need for improvement was greater and their predilection for self-education outside the clinic was less.
The finding that a number of meta-mechanisms reflecting differences in SES either enhanced or harmed the enactment of a successful diabetic control regimen was consistent with the fundamental cause theory. Link and Phelan (1995) indicate that SES qualifies as a “fundamental cause” of health outcomes for the very reason that it causes disease and mortality in multiple – not singular – ways. Therefore, as Lutfey and Freese (2005: 1327) point out, the fundamental cause concept does not imply a theory of specific proximate mechanisms responsible for a persistent association; rather, the theory is one of meta-mechanisms responsible for how several specific and varied mechanisms that affect health are generated over time. Consequently, the overall direction of the enduring association is maintained even though the potency of some specific social mechanisms may change or disappear over time due to medical innovations, social change, or some other factor.
Lutfey and Freese did not study the origin of diabetes, genetic or otherwise, in their respondents. But they made an important contribution to understanding the social causation thesis by demonstrating the multiple effects of SES on diabetes regimens. These effects shaped the capacity of the diabetics to cope successfully or unsuccessfully with their disease as poor control could end their lives. While it might be argued that the biological pathologies inherent in diabetes are responsible for patient mortality, this argument overlooks the fact that social mechanisms brought the patient much more rapidly to the point that biology ended their life or was a means to maintain or extend it. In this situation, social mechanisms have a causal role not only in the onset of the disease (e.g., unhealthy diets and lack of exercise), but also in the effectiveness of the body’s defenses to cope successfully with the affliction.
Although fundamental cause theory was formulated to explain the lasting effects of SES on health and mortality, Phelan and Link (2013) note that it is likely other social statuses, such as race, ethnicity, or gender, also may function as a fundamental cause, although the case for these possibilities has yet to be fully made. An exception is racism. In a subsequent paper, Phelan and Link (2015) argued that racism could be considered a fundamental cause of health inequalities. They made three logical deductions – all based on research evidence and each linking into the other – to support their contention: (1) racism is a fundamental cause of racial differences in SES; (2) SES is a fundamental cause of health inequalities; and (3) racism is a fundamental cause of racial differences in health and mortality independent of SES. They “conclude that racial inequalities in health endure primarily because racism is a fundamental cause of racial differences in SES and SES is a fundamental cause of health inequalities” (Phelan and Link 2015: 311).
Measuring Structural Effects
The recognition of social factors inherent in causing sickness or mortality has been late in coming. One reason may be methodological difficulties in specifying the exact underlying explanatory social mechanisms that affect health, since these mechanisms are multiple, complex, and difficult to isolate in order to determine their precise effects. Such difficulties are increased when trying to determine the direct effects of social structures on individuals because of the possible role of other variables that may intervene in the relationship. Nevertheless, the scientific method requires proof that independent variables have specific and measurable effects on dependent variables whether they are structural or not.
Qualitative methods such as participant observation that concentrate on individuals face shortcomings in determining the effects of structure on people. Roger Sibeon (2004) suggests there are limits to what can be achieved by micro-level methods in addressing structural questions, since such methods are not equipped theoretically or methodologically to measure macro-phenomena. However, the Lutfey and Freese (2005) study of diabetic clinics was qualitative, relying on ethnographic data consisting of observations at the clinics; consultations with patients and medical practitioners; video recordings; semi-structured
