Eliassen et al. BMC Public Health 2012, 12:948 http://www.biomedcentral.com/1471-2458/12/948 Table 3 Adjusted odds ratiosa for reporting poorer self-rated healthb Countries and variables Greenland – men (n=509) Subsistence score Language ability (SILA) Very well Not very well Greenland – women (n=553) Subsistence score Language ability (SILA) Very well Not very well Alaska – men (n=284) Subsistence score Language ability (SILA) Very well/relatively well Not well Alaska – women (n=380) Subsistence score Language ability (SILA) Very well/relatively well Not well Norway – men (n=212) Subsistence score Language ability (SILA) Very well Not very well Norway – women (n=215) Subsistence score Language ability (SILA) Very well Not very well OR 2.31 1 1.58 1.67 1 1.42 1.38 1 1.39 1.73 1 0.81 0.82 1 1.31 1.03 1 0.84 Model 1c P-value <0.001 Ref. 0.033 0.014 Ref. 0.075 0.226 Ref. 0.264 0.028 Ref. 0.428 0.564 Ref. 0.428 0.935 Ref. 0.634 95% CI 1.49-3.56 Ref. 1.04-2.42 1.11-2.51 Ref. 0.97-2.09 0.82-2.34 Ref. 0.78-2.48 1.06-2.81 Ref. 0.48-1.37 0.42-1.60 Ref. 0.67-2.57 0.56-1.90 Ref. 0.40-1.74 OR 2.32 1. 1.59 1.71 1. 1.43 1.39 1 1.39 1.73 1 0.81 0.81 1 1.74 1.01 1 0.72 Model 2d P-value <0.001 Ref. 0.032 0.010 Ref. 0.072 0.215 Ref. 0.263 0.026 Ref. 0.427 0.524 Ref. 0.068 0.972 Ref. 0.302 Page 8 of 11 95% CI 1.50-3.58 Ref. 1.04-2.43 1.13-2.56 Ref. 0.97-2.10 0.83-2.35 Ref. 0.78-2.49 1.07-2.82 Ref. 0.48-1.37 0.42-1.56 Ref. 0.96-3.15 0.55-1.86 Ref. 0.38-1.35 a Multivariable ordinal logistic regression on imputed data. b SRH coded in Greenland: 0) Very good, 1) Good, 2) Fair/Poor/Very Poor. SRH coded in Alaska and Norway: 0) Excellent , 1) Very good, 2) Good/Fair/Poor. c Greenland and Alaska: controlling for age, education, smoking, chronic problem, housing condition, living in village or town. Norway: controlling for age, education, smoking, chronic problem, living in Finnmark or not. d Greenland and Alaska: controlling for age, education, smoking, chronic problem, housing condition. Norway: controlling for age, education, smoking, chronic problem. Acculturation - a multidimensional concept The linear acculturation scales have come under criti- cism as they represent a simplification of the accultur- ation process and rely on an assumption of two distinct cultures [47]. The multidimensional models such as Berry’s [50] are designed to identify adaptations beyond the dichotomy of high versus low acculturation. These more complex scales, however, still also rely on the no- tion of culturally distant groups. While individuals may be conceptualised within a multidimensional framework of adaptations, the assumption of two culturally distant groups nevertheless still persist [47]. Furthermore, the criticism of the linear scales has also been related to the fact that many scales have been produced and applied without prior metric analysis of scale reliability or factor structure [48]. As aforementioned, our factor analyses produced consistent results displaying very strong in- ternal consistency in the items, thus suggesting that our approach is an appropriate substitute. As we were un- able to measure multiple dimensions, our estimates be- come thus aggregate or overall effect measures of acculturation. The comparability of our study with ac- culturation studies using Berry’s model is thus perhaps not ideal.