Keynote at RAI conference, "Mobilising Methods in Medical Anthropology"

I am grateful for the opportunity to deliver a keynote lecture at the virtual conference organized by the Medical Anthropology Committee of the Royal Anthropological Institute, “Mobilising Methods in Medical Anthropology.” I was particularly glad to share my work in this venue, as the conference theme draws together multiple strands of my research and teaching.

The video recording remains available for registered attendees of the conference. For others, the abstract is below. My thanks to the conference organizers!

Boundary Making and Boundary Crossing in Medical Anthropology: Methods at the Intersections

Medical anthropology is an expansive field: at once a humanistic and scientific enterprise that crosses (sub)disciplinary boundaries, values multiple ways of knowing, appreciates both basic and applied research, and encompasses the human condition across time and space. This holistic and integrative approach is medical anthropology’s distinctive strength. It also poses a challenge in delineating the range of research methods relevant to the field: Medical anthropologists draw on the whole toolkit of social science, and many also integrate methods from the humanities, public health, biomedicine, and the life sciences. The discipline’s location at so many intersections presents both pitfalls and promise.

In this talk, I sketch a vision of medical anthropology that relishes its role at the intersections and argue for a methodological approach that crosses rather than erects boundaries. I challenge the constraints of three common boundaries in particular: between qualitative and quantitative, social and biological, and researcher and researched. To illustrate the value of transcending these boundaries I draw on collaborative, mixed-methods, biocultural research on health inequities among racialized populations in the Americas—before, during, and likely after the COVID-19 pandemic. I draw attention to the ways that mobilising boundary-crossing methods both contributes to core theoretical interests of medical anthropology and resolves seemingly intractable problems in medicine, public health, and the broader health sciences.

New paper: Obesity in the context of systemic inequalities

My mother is a retired nurse, so I’m a little embarrassed that it took me this long to publish in a nursing journal. Thanks to fantastic collaborators Michelle Cardel and Faith Newsome for making it happen!

In this new paper in Nursing Clinics of North America, we review environmental contributors to obesity inequities among racialized groups in the U.S. and suggest questions clinicians can ask to elicit information about how social context shapes obesity risk.

I really like how the paper starts:

Health inequities are preventable, unjust differences in disease burden that adversely impact oppressed, stigmatized, or medically underserved groups, such as people with lower socioeconomic status, people with disabilities, members of the LGBTQ community, individuals in rural areas, and marginalized racial and ethnic groups. Racial and ethnic health inequities in the United States are pervasive, because of the harms of structural racism. These harms include higher rates of heart disease, cancer, diabetes, HIV/AIDS, and other leading causes of death among marginalized racial and ethnic groups, as compared with White patients. In the United States, these inequities are attributed largely to long-standing, systemic inequalities in health care, interpersonal discrimination, and structural racism in housing, education, banking, law enforcement, and other policy domains. We recognize race and ethnicity as social classifications rooted in a political system of racialized oppression, not as proxies for genetic differences among people or populations.

Check it out or let me know if you need a copy. Constructive feedback is always welcome.

New paper: Social networks, financial strain, and genetic risk for depressive symptoms

Alternative models for the contribution of psychosocial stressors and genetic susceptibility to the risk of depressive symptoms. From Fuller et al. (2021).

Alternative models for the contribution of psychosocial stressors and genetic susceptibility to the risk of depressive symptoms. From Fuller et al. (2021).

Collaborators and I have a new paper just out in the American Journal of Physical Anthropology, based on data from the HEAT Heart Health Study. The central question is to what extent variation in depressive symptoms is associated with individual-level genetic differences and exposure to psychosocial stressors. We tested two alternative models, shown at right.

Model (a) says that psychosocial stressors are primary contributors to the risk of depressive symptoms, but that individual-level genetic differences may make some people more sensitive to psychosocial stressors. Model (b) says that genetic susceptibility and psychosocial stressors contribute independently to the risk of depressive symptoms. The thickness of the lines in these diagrams is meant to illustrate expectations about the relative magnitude of each association.

Contrary to some prior theory, our results fit model (b), not (a). We tested five single-nucleotide polymorphisms (SNPs) that had been associated with depressive symptoms in other studies. None was associated with CES-D in our sample. By contrast, a regression model including two psychosocial stressors (difficulty paying bills and the proportion of people in one’s social network who are a source of stress or worry) accounted for 17% of the variance in depressive symptoms. When we tested psychosocial stressors and genetic susceptibility variants simultaneously, one SNP (rs1360780 inFKBP5) was associated with CES-D—but only when psychosocial stressors were in the model.

This paper adds to the weight of evidence pointing to the primacy of social context in the risk of depressive symptoms. It also suggests that genetic influences on depression-related phenotypes can’t be understood without attention to the social and material conditions in which people live. By extension, improving measurement of those conditions may empower genetic association studies.