BMC Public Health 2007, 7:285 http://www.biomedcentral.com/1471-2458/7/285 We repeated this imputation procedure 10 times. We ana- lysed the 10 resulting datasets separately, and subse- quently combined the results into one estimate. Standard errors were based on the standard errors from each set of imputed data combined with inter-imputation variation. Results Table 1 presents the characteristics of the CHSNS dataset for men and women separately. It shows that men were slightly more likely to report poor health than women. A gender difference was found for social class: men were more often classified as III M (skilled manual), and women more often as III NM (skilled non-manual). There were also some small differences with regard to employ- ment status: whereas men were more likely to be employed, women were more likely to be a student or to look after the home and/or children. Men and women appeared to have similar perceptions of the neighbour- hood environment. Table 2 shows the bivariate correlations between the dif- ferent neighbourhood variables and self rated health. Neighbourhood quality, neighbourhood disorder and deprivation had the strongest associations with poor health at the neighbourhood level. Neighbourhood dep- rivation, neighbourhood quality, and neighbourhood dis- order were strongly interrelated, suggesting that they may measure the same thing or are part of the same underlying social processes. The associations between access to amen- ities and social cohesion on the one hand and poor health on the other were weaker but still significant. Access to amenities had the lowest correlations with the other neighbourhood variables. Its associations with neigh- bourhood disorder and social cohesion were non-signifi- cant. We found that a modest part of the variation in self-rated health can be found at the neighbourhood level (3.7%). Model 1 found strong associations between the different socio-demographic variables and self rated health (see Table 3). Respondents who were classified as skilled man- Access to amenities Neighbourhood quality Neighbourhood disorder Social cohesion Deprivation Neighbourhood quality Neighbourhood disorder 0.19 0.07 0.81 ual, partly and unskilled manual, and 'other' social class were more likely to report poor health. Similarly, people who were unemployed, retired, disabled, or with an 'other' employment status were more likely to report poor health. Non-homeowners were also more likely to report poor health. Model 2a shows the unadjusted associations between the neighbourhood variables and self rated health. Poor access to amenities, poor neighbourhood quality, neighbourhood disorder, a lack of social cohe- sion, and neighbourhood deprivation were all signifi- cantly associated with the reporting of poor health. Model 2b shows that the associations between the neighbour- hood variables and self rated health were attenuated when controlling for socio-demographic differences. However, all associations remained significant. Model 2c addition- ally controlled for neighbourhood deprivation. All associ- ations were further attenuated. The association between social cohesion and self rated health was rendered non- significant, as well as the association between neighbour- hood disorder and self rated health. Some interesting differences were found in the gender- stratified analyses (see Table 4). Model 1 shows that indi- vidual socio-economic status affected men and women differently. Unemployment significantly increased the odds of men reporting poor health, but did not do so for women. Model 2b shows that social cohesion was signifi- cantly associated with women's self-rated health, with a lack of social cohesion increasing the odds of women reporting poor health. However, social cohesion was not significantly associated with men's self-rated health. Remodelling the complete dataset with gender interac- tions terms showed that the interaction with unemploy- ment was significant (OR = 1.82; 95%CI = 1.03–3.20); and that the interaction with social cohesion was margin- ally significant (OR = 1.07; 95%CI = 1.00–1.14). These interactions show that the odds of unemployed men reporting poor health are 82% higher than the odds of unemployed women reporting poor health; and that for each standard deviation change in neighbourhood social cohesion the odds of women reporting poor health are Social cohesion Deprivation Poor health(2) 0.05 0.33 0.36 0.14 0.61 0.50 0.31 0.19 0.53 0.43 0.25 0.54 Table 2: Ecological correlations between the different neighbourhood variables and self rated health (n = 325 EDs) (1) (1) Higher scores on the different neighbourhood variables represent a more negative evaluation of the neighbourhood. (2) Proportion of people reporting fair or poor health. Page 5 of 10 (page number not for citation purposes)