Which Sámi? Sámi inclusion criteria in population-based studies of Sámi health and living conditions in Norway - an exploratory study exemplified with data from the SAMINOR study

• Main Authors: Pettersen, Torunn, Brustad, Magritt
• Format: Article in Journal/Newspaper
• Language: English
• Published: CoAction Publishing 2013
• Subjects: VDP::Medical disciplines: 700::Health sciences: 800::Community medicine; Social medicine: 801; VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin; sosialmedisin: 801; Arctic; Norway; Sámi
• Online Access: https://hdl.handle.net/10037/5924

Background: In a situation where national censuses do not record information on ethnicity, studies of the indigenous Sámi people’s health and living conditions tend to use varying Sámi inclusion criteria and categorizations. Consequently, the basis on which Sámi study participants are included and categorized when Sámi health and living conditions are explored and compared differs. This may influence the results and conclusions drawn. Objective: To explore some numerical consequences of applying principles derived from Norway’s Sámi Act as a foundation for formalized inclusion criteria in population-based Sámi studies in Norway. Design: We established 1 geographically based (G1) and 3 individual-based Sámi example populations (I1–I3) by applying diverse Sámi inclusion criteria to data from 17 rural municipalities in Norway north of the Arctic Circle. The data were collected for a population-based study of health and living conditions in 2003–2004 (the SAMINOR study). Our sample consisted of 14,797 participants aged 36–79 years. Results: The size of the individual-based populations varied significantly. I1 (linguistic connection Sámi) made up 35.5% of the sample, I2 (self-identified Sámi) made up 21.0% and I3 (active language Sámi) 17.7%. They were also noticeably unevenly distributed between the 5 Sámi regions defined for this study. The differences for the other characteristics studied were more ambiguous. For the population G1 (residents in the Sámi language area) the only significant difference found between the Sámi and the corresponding non-Sámi population was for household income (OR=0.69, 95% CI: 0.63–0.74). For the populations I1–I3 there were significant differences on all measures except for I2 and education (OR=1.09, 95% CI: 0.99–1.21). Conclusions: The choice of Sámi inclusion criterion had a clear impact on the size and geographical distribution of the defined populations but lesser influence on the selected characteristics for the Sámi populations relative to the respective non-Sámi ones.