'Small' data, isolated populations, and new categories of rare diseases in Finland and Poland.
Małgorzata RajtarPublished in: Anthropology & medicine (2023)
Health policy and academic discourses on rare diseases and people with rare conditions frequently employ terms such as 'low prevalence' and 'unique' to characterize the smallness of the population under consideration and to justify targeted action toward these patient groups. This paper draws from recent anthropological scholarship on smallness and data, ethnographic research in Finland and Poland, as well as document and media analysis to examine how data is utilized in the context of isolated populations that are considered sites of rare diseases in these two countries. Specifically, this paper juxtaposes the notion of Finnish Disease Heritage (FDH) with that of a 'Kashubian gene' in Poland. The concept of FDH was developed by Finnish researchers in the 1970s; it encompasses almost forty rare hereditary diseases that are significantly more prevalent in Finland than elsewhere globally. On the other hand, the notion of the 'Kashubian gene' was first utilized by the media and some members of the Polish medical community around 2008. Based on 'unstable' data gathered during genetic research, the term referred to the high prevalence of a rare metabolic disorder (Long-Chain 3-Hydroxyacyl-CoA Dehydrogenase (LCHAD) deficiency) among Kashubians, an ethnic minority that resides in Northern Poland's Pomerania region. Whereas FDH facilitated the production and branding of 'a unique Finnish genetic identity' (Tupasela 2016b, 61), the notion of the 'Kashubian gene' has engendered health policy interventions targeting members of this ethnic minority and has contributed to stigmatizing practices carried out against Kashubians.
Keyphrases
- healthcare
- public health
- mental health
- genome wide
- copy number
- electronic health record
- big data
- primary care
- risk factors
- physical activity
- cancer therapy
- health information
- case report
- machine learning
- genetic diversity
- climate change
- genome wide identification
- data analysis
- fatty acid
- human health
- replacement therapy
- medical students