2017
DOI: 10.1136/jech-2016-208176
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Do differences in religious affiliation explain high levels of excess mortality in the UK?

Abstract: Background High levels of mortality not explained by differences in socioeconomic status (SES) have been observed for Scotland and its largest city, Glasgow, compared with elsewhere in the UK. Previous crosssectional research highlighted potentially relevant differences in social capital, including religious social capital (the benefits of social participation in organised religion). The aim of this study was to use longitudinal data to assess whether religious affiliation (as measured in UK censuses) attenuat… Show more

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Cited by 5 publications
(11 citation statements)
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“…More research is needed to understand what unique effects mean—for example, what does it mean to be religious but not spiritual as compared with being religious and spiritual in terms of health behaviors? In addition, survivors' religious affiliation may influence their health behaviors, a potentially key issue that should be examined in future research.…”
Section: Discussionmentioning
confidence: 99%
“…More research is needed to understand what unique effects mean—for example, what does it mean to be religious but not spiritual as compared with being religious and spiritual in terms of health behaviors? In addition, survivors' religious affiliation may influence their health behaviors, a potentially key issue that should be examined in future research.…”
Section: Discussionmentioning
confidence: 99%
“…Statistical techniques such as eDataShield [15] will provide a workable interim solution. This technique facilitates combined analysis of physically separated datasets, including datasets such as the Census where strict security access usually prevents these data being pooled [16,17]. However, there is obviously a potential need to move towards scenarios where the individual-level data across the UK are combined and analysed in one setting.…”
Section: Discussionmentioning
confidence: 99%
“…The Scottish Longitudinal Study19 (a 5.3% sample of the Scotland Census linked to life events data including death registrations) and the Office for National Statistics Longitudinal Study of England and Wales20 (a 1% sample of the England and Wales Census, also linked to life events data including individual mortality records) were employed. Analyses of these ‘restricted access’ data sets were enabled by the use of E-DataSHIELD methodology, which has been described previously 6 21…”
Section: Methodsmentioning
confidence: 99%
“…The analyses compared all-cause mortality rates in Glasgow with Manchester (both cities defined by local authority boundaries, as used previously4 6), and in Scotland with England and Wales, using Poisson regression models, adjusting for age, sex, various measures of socioeconomic position (SEP), ethnicity and country of birth (all defined below). Manchester has been previously identified as the most appropriate comparator city for the analyses, given its much greater levels of ethnic diversity compared with Glasgow 7.…”
Section: Methodsmentioning
confidence: 99%
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