05), they did not alter the coefficients

of the cities (the main focus of the analysis), and so are not reported selleck chemicals here.iv As a number of commentators argue the need for multilevel modelling to explore and distinguish between individual and area influences on health,35–37 the main SoC model was also run as a multilevel linear regression model using MLwiN software (V.2.26). There were two levels: individual and neighbourhood (sampling points with an average population size of approximately 300 people33). However, there was virtually no difference between results in terms of the coefficients for the cities. An additional set of models was run to establish whether differences in SoC were associated with differences in levels of self-assessed health (SAH). Previous research into excess poor health in Scotland and Glasgow has emphasised the need to concentrate of outcomes of mortality, given the demographic, socioeconomic and cultural factors that have been shown to influence

self-assessment of health between different countries and populations.38–40 However, given the evidence cited above linking SoC to a range of adverse health-related outcomes, it was still of interest to know whether this was the case for this representative sample of three UK post-industrial cities. Multivariate logistic regression modelling was employed, with a binary outcome of ‘bad’ or ‘very bad’ SAH (two of the five possible answersv to the question ‘How is your health in general?’) and the same predictor variables listed in table 1 together with smokingvi (given its relevance to the outcome measure) and SoC (included as both a continuous variable). Results Contrary to the suggested hypothesis, SoC was found to be substantially higher, not lower, among the Glasgow sample compared to the samples of the two English cities. Descriptive analyses

showed that it was higher overall, and in comparison of all strata of gender, age, area deprivation and social class (data not shown). These findings were confirmed by the modelling analyses. Table 2 shows that adjusting for all differences in the characteristics of the samples, residents of Liverpool were associated with a mean SoC score of 5.1 lower (regression coefficient: −5.05 (95% CI −6.04 to −4.07)) than residents of Glasgow, with the adjusted mean score of the Manchester sample being 8.1 lower than that of Glasgow (−8.14 (95% CI −9.12 to −7.16)). Table 2 Multivariate linear regression Anacetrapib analysis of the factors associated with Sense of Coherence (SOC-13) score Differences between the cities were also seen in the modelling of the comprehensibility (regression coefficient for Liverpool: −2.42 (95% CI −2.83 to −2.00); Manchester −2.74 (95% CI −3.15 to −2.32), manageability (Liverpool: −1.37 (95% CI −1.71 to −1.04); Manchester −2.44 (95% CI −2.77 to −2.11))), and meaningfulness (Liverpool: −1.23, (95% CI −1.58 to −0.88); Manchester −2.93 (95% CI −3.27 to −2.58))) scores (data not shown).