NUR 610 Module 1 Social Determinants and Genomics Discussion Example

Discussion Board: Social Determinants of Health and Genomics

A Gene Shared by One in 300, Found in Far Fewer: Social Determinants and Familial Hypercholesterolemia

Initial Post

Familial hypercholesterolemia (FH) is one of the most common inherited conditions in the world. A meta-analysis of studies covering about 11 million people estimated its prevalence at 0.32%, roughly one person in 313 (Beheshti et al., 2020). People with FH have very high LDL cholesterol from birth and, without treatment, a much higher risk of early heart attack. Effective treatment exists, and each diagnosis can lead to relatives through cascade screening, in which family members of a known case are tested. Yet most people with FH in the United States have never been diagnosed (Knowles et al., 2017).

This week's readings helped me see why. Braveman et al. (2011) argue that upstream social determinants, such as economic resources, education and racial discrimination, shape the downstream factors, like behavior and access to care, that most interventions target. A genetic condition seems purely biological, but finding it is a social process.

Using the socioecological model, I mapped the barriers I see as a public health nurse.

Individual: A 38-year-old man with an LDL of 260 mg/dL may not know that his father's heart attack at 45 is relevant, or may fear what a genetic diagnosis means for life insurance.

Interpersonal: Cascade screening depends on families telling relatives. In families separated by migration, estrangement or language differences, the message often stops with the first person diagnosed.

Organizational: Many primary care clinics do not flag very high LDL or ask about early heart disease in relatives, and genetic counselors are scarce outside Phoenix and Tucson.

Community: In rural and tribal communities in Arizona, the nearest lipid specialist may be hours away, and mistrust of genetic research, rooted in past abuses, can make families wary of testing.

Policy: Insurance coverage for genetic testing and for newer cholesterol drugs varies, and uninsured people are unlikely to be screened at all.

West et al. (2017) warn that genomics research has focused on discovery while neglecting the structural factors that drive disparities. FH is a clear example: the science to find and treat it is decades old, but the benefit flows to people with insurance, time and connected families.

For public health nursing, this suggests that FH programs should be designed for the people least likely to be found, not only for those who already reach a cardiologist. That could mean screening for very high LDL in community clinics, offering help with family notification in Spanish and other languages, and working with tribal health programs on their own terms.

Reply to Andrea

Andrea, your point that genetic information can feel like a burden as well as a benefit fits FH well. In my experience, the hardest conversation is not explaining the diagnosis but asking a patient to tell siblings they have not spoken to in years. Your post made me wonder whether the socioecological model needs a place for family history itself as a social determinant, since a family's story about heart disease shapes whether anyone thinks to ask for a cholesterol check. In families where a father's early death was explained as stress or bad luck, the genetic explanation may feel unfamiliar or even unwelcome. A public health approach could offer to contact relatives directly, with the patient's permission, which some programs outside the United States already do. I would be curious whether you think American families would accept a letter from the health department about a relative's genetic test, or whether that would feel intrusive. My guess is that acceptance would depend on who sends it and how it is worded, which brings us back to trust at the community level. In my own county, a letter on health department letterhead might be trusted by some families and feared by others, especially families with mixed immigration status, who may worry about any government contact. A program that lets families choose between a letter, a phone call from a nurse or support for the patient to tell relatives might reach more people than any single approach.

Reply to Marcus

Marcus, you described newborn screening as a model of genomics reaching everyone regardless of social position, and I agree that it is one of public health's great equity successes. Every baby born in Arizona is screened, whatever the family's insurance, because the program is built into hospital routine and paid for publicly. FH shows the contrast: because it is usually found in adulthood through individual clinical care, it depends on all the social determinants that newborn screening avoids. A few countries have tested screening children's cholesterol at the time of routine vaccinations and then testing parents, which turns a clinical process into a population one. That kind of approach would raise its own questions about consent and cost, but it would reach families that the current system misses. Your post made me think that the most equitable genomic programs are the ones that require the least effort from individual families. Do you think the same logic applies to adult screening for other conditions, such as hereditary cancer syndromes? I suspect the answer depends on whether a simple, inexpensive first test exists. For FH, a cholesterol level is cheap and widely available, which makes population approaches realistic in a way that is harder for conditions that require genetic testing from the start.

References

Beheshti, S. O., Madsen, C. M., Varbo, A., & Nordestgaard, B. G. (2020). Worldwide prevalence of familial hypercholesterolemia: Meta-analyses of 11 million subjects. Journal of the American College of Cardiology, 75(20), 2553-2566. https://doi.org/10.1016/j.jacc.2020.03.057

Braveman, P., Egerter, S., & Williams, D. R. (2011). The social determinants of health: Coming of age. Annual Review of Public Health, 32, 381-398. https://doi.org/10.1146/annurev-publhealth-031210-101218

Knowles, J. W., Rader, D. J., & Khoury, M. J. (2017). Cascade screening for familial hypercholesterolemia and the use of genetic testing. JAMA, 318(4), 381-382. https://doi.org/10.1001/jama.2017.8543

West, K. M., Blacksher, E., & Burke, W. (2017). Genomics, health disparities, and missed opportunities for the nation's research agenda. JAMA, 317(18), 1831-1832. https://doi.org/10.1001/jama.2017.3096