Was following and commenting on a tweet thread by the brilliant @statsepi and the topic of "subjective" and "objective" measures came up and it made me want to have a more extensive twitter thread (without co-opting theirs), for #epitwitter #statstwitter and #medtwitter. 1/n

A lot of people tend to think objective measures as things like blood tests, growth charts, BMI, etc as objective measures, and look at survey instrument and self-reported experiences as subjective measures. However, we don't acknowledge that implicit to that partition is the 2/n

assumption that so-called "objective" measures are unbiased, and approximate "truth" better than "subjective" measures. There's a lot in that assumption but I want to focus on two things. Firstly, if the "objective" measures really are more or less "biased" than subjective 3/n

measures, and secondly, the limitations of the different types of measures in answering certain types of questions. Consider eGFR, something that was, in clinical medicine, treated like an "objective" measure for so long. Thanks to excellent scholarship by @AmakaEMD 4/n

and others, the fallibility and lack of subjectivity of this measure has become increasingly clear. It's the product of white supremacist society, and that is baked into the very fabric of its estimation despite originating in a blood test. I would argue that it is no less 5/n

and is perhaps more biased than a well-designed and validated survey instrument (validation, and what passes as validation is a different discussion altogether but let's assume its done rightand applies to the population of interest) 6/n

Similarly, clinical guidelines and prescribing guidelines still take into account race (Hypertension drug guidelines still have race stratification), and we even teach med students to include race in their objective, one-liner introduction of their patients. But I think that 7/n

most scholars of race would agree that as a social construct (with real ramifications to health), an individuals subjective assessment of another person's race isn't an "objective" measure. My point of all this, is that subjective vs objective is a gray area, and that actually8/n

such a partitioning of measurements might have little value. To my second reason for this discussion. As a social epidemiologist, I spend a lot of time looking at how structures, specifically structural oppression, but also socialization and environments determine health. 9/n

One of the biggest challenges of my field is measurement. How do you measure racism? When its interpersonal and structural...when it's intergenerational and contemporary? When it's internalized or extenral? None of these things can be directly measured but some of them can 10/n

estimated using what others might consider "objective" measurements (such as census tract/block level proxies for socieconomic status ). Still, the true richness and nuance of these systems are arguable best captured with "subjective" information. How people self-report 11/n

their experiences in surveys, or even more richly qualitative interview and ethnographic studies. There is a strong case to be made that much of the health inequities plaguing resource-rich societieis are largely due to social stratification. I would argue that many of the 12/n

leading causes of death in America, heart disease, and diabetes, have a large social inequity component so that studies that use so-called "subjective" measures are the ones with perhaps the most relevance towards achieving health equity. 13/n

These are just my personal ramblings on why it's important to be mindful of our biases when we decide which types of measurements can be informative. It's important to interrogate why we assign value to where we do. TLDR, survey, qualitative, subjective research is important 14/n

social epi and when done right can be just as or more informative as any GWAS, clinical epi, or lab based study. 15/15.