A multilevel analysis of mortality following XXXX in Norway: do municipal health services make a difference?

@entity1 @entity303 @entity583 @entity204 @entity65
OBJECTIVES: Studies link area features such as neighbourhood socioeconomic deprivation to poor health outcomes. However, there is a paucity of research based on representative data investigating the effects of area-level health services on mortality. This study examines the extent to which municipal health services account for municipal variation in all-cause and @entity65 ( @entity65 ) mortality. We hypothesise that unfavourable municipal features (eg, fewer available places for rehabilitation) are associated with higher risk of mortality after accounting for @entity1 ' characteristics. DESIGN: Population data from Norwegian national/municipal registrars are analysed using multilevel logistic regression in this prospective cohort study. SETTING AND @entity1 : The analytic sample (9412 @entity1 aged 18+ from 336 municipalities) constitutes 87.7% of the nationwide population of Norwegian adults who were hospitalised for @entity583 ( @entity583 ) in 2009 and discharged alive. PRIMARY OUTCOME MEASURES: All-cause and @entity65 mortality occurring within 365   days after the first day of hospitalisation for @entity583 . RESULTS: There was a small but significant variation at the municipal level in all-cause mortality (0.5%; intraclass correlation coefficient=0.005) but not @entity65 mortality. There were no significant fixed effects of municipal health services on mortality in bivariate models. @entity1 ' characteristics (eg, gender, comorbidities) fully accounted for the observed municipal variation in mortality. Being male versus female (OR=1.21, 95% CI 1.02 to 1.43), or having been previously diagnosed with @entity303 versus not (OR=2.06, 95% CI 1.53 to 2.77) were also linked to higher odds of @entity204 . CONCLUSIONS: Municipal variation in all-cause mortality for Norwegian @entity1 with @entity583 appears to be driven not by differences across municipalities in health service levels, but by differences across municipalities in the composition of @entity1 . Focusing on chronic disease prevention and treatment, and tackling personal and structural risk factors embedded within @entity1 ' sociodemographic characteristics, may be especially beneficial for longevity.
