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The association of estimated vs. observed county rates was assessed by Spearman correlation. Estimated rates of settlement and population densities as continuous variables were calculated. However, Oxygenase these rates did not perform better than the rates based on categorical variables, and were therefore not used. PASW Statistics v.18.0 (SPSS, Inc., Chicago, IL) software was used for statistical analysis, and statistical significance was set at p?selleck products road users. Thirty-nine (8.4%) and 57 (12.3%) deaths were caused by assaults and self-harm, respectively. The majority of deaths (58.4%) occurred before arriving at hospital (Table 1). After stratifying cases according to municipal centrality, the level 2 municipalities had the highest total mortality rates (Table 1). The injury mechanisms differed significantly according to the different levels of centrality (Table 1). In the two most rural groups (levels 1 and 2), 47.6% of deaths were due to transport injuries, compared to 34.7% in the more urban areas (levels 3 and 4; p?=?.008). Assaults were responsible for twice the proportion of deaths in the more central municipalities (levels 3 and 4: 10.1%) vs. the more rural areas (levels 1 and 2: 4.8%); however, the total number of assaults was low, and this difference did not reach statistical significance (p?=?.059). The proportion of deaths caused by self-harm was more evenly distributed than deaths from assault ( Table 1). In total 270 of all deaths were confirmed to have occurred in the pre-hospital phase. With 84 (44.2%) of deaths in the most central (level 4) areas occurring in hospital and two-thirds of deaths in the most rural areas occurring before reaching hospital, the more rural areas tended towards more pre-hospital deaths. This, however, Dactolisib cell line did not reach statistical significance for all four groups (Table 1). At the municipal level, the lesser two levels of centrality and population density, and all lower levels of settlement density were associated with higher mortality rates (Table 2). When aggregating the characteristics of the municipalities, each county's level of centrality, settlement and population density can be seen in Fig. 1, Fig. 2?and?Fig. 3. Oslo had a population density of 1129.50?inh/km2, whilst the median national population density was 14.14?inh/km2 (IQR: 6.