Literature DB >> 22030211

Rising premature mortality in the U.K.'s persistently deprived areas: only a Scottish phenomenon?

Paul Norman1, Paul Boyle, Daniel Exeter, Zhiqiang Feng, Frank Popham.   

Abstract

In the international literature, many studies find strong relationships between area-based measures of deprivation and mortality. In the U.K., mortality rates have generally fallen in recent decades but the life expectancy gap between the most and least deprived areas has widened, with a number of Scottish studies highlighting increased mortality rates in deprived areas especially in Glasgow. However, these studies relate health outcomes at different time points against period-specific measures of deprivation which may not be comparable over time. Using longitudinal deprivation measures where levels of area deprivation are made comparable over time, a recent study demonstrated how levels of mortality change in relation to changing or persistent levels of (non-) deprivation over time. The results showed that areas which were persistently deprived in Scotland experienced a rise in premature mortality rates by 9.5% between 1981 and 2001. Here, focussing on persistently deprived areas we extended the coverage to the whole of the U.K. to assess whether, between 1991 and 2001, rising premature mortality rates in persistently deprived areas are a Scottish only phenomenon or whether similar patterns are evident elsewhere and for men and women separately. We found that male premature mortality rates rose by over 14% in Scotland over the 10-year period between the early 1990s and 2000s in persistently deprived areas. We found no significant rise in mortality elsewhere in the U.K. and that the rise among men in Scotland was driven by results for Glasgow where mortality rates rose by over 15% during the decade. Our analyses demonstrate the importance of identifying areas experiencing persistent poverty. These results justify even more of a public health focus on Glasgow and further work is needed to understand the demographic factors, such as health selective migration, immobility and population residualisation, which may contribute to these findings.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 22030211     DOI: 10.1016/j.socscimed.2011.09.034

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  21 in total

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2.  Why do males in Scotland die younger than those in England? Evidence from three prospective cohort studies.

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3.  Rural-urban patterns of disability: The role of migration.

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4.  How much of the difference in life expectancy between Scottish cities does deprivation explain?

Authors:  R Seaman; R Mitchell; R Dundas; A H Leyland; F Popham
Journal:  BMC Public Health       Date:  2015-10-16       Impact factor: 3.295

Review 5.  Vitamin D and subsequent all-age and premature mortality: a systematic review.

Authors:  Lynne Rush; Gerry McCartney; David Walsh; Daniel MacKay
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6.  Exploring the social, emotional and behavioural development of preschool children: is Glasgow different?

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7.  Developing a new small-area measure of deprivation using 2001 and 2011 census data from Scotland.

Authors:  Mirjam Allik; Denise Brown; Ruth Dundas; Alastair H Leyland
Journal:  Health Place       Date:  2016-04-12       Impact factor: 4.078

8.  Increasing inequality in age of death at shared levels of life expectancy: A comparative study of Scotland and England and Wales.

Authors:  Rosie Seaman; Alastair H Leyland; Frank Popham
Journal:  SSM Popul Health       Date:  2016-12

9.  Longitudinal methods to investigate the role of health determinants in the dynamics of income-related health inequality.

Authors:  Paul Allanson; Dennis Petrie
Journal:  J Health Econ       Date:  2013-07-24       Impact factor: 3.883

10.  Explaining the excess mortality in Scotland compared with England: pooling of 18 cohort studies.

Authors:  Gerry McCartney; Tom C Russ; David Walsh; Jim Lewsey; Michael Smith; George Davey Smith; Emmanuel Stamatakis; G David Batty
Journal:  J Epidemiol Community Health       Date:  2014-09-12       Impact factor: 3.710

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