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      Mortality differences and inequalities within and between ‘protected characteristics’ groups, in a Scottish Cohort 1991–2009

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          Abstract

          Background

          Little is known about the interaction between socio-economic status and ‘protected characteristics’ in Scotland. This study aimed to examine whether differences in mortality were moderated by interactions with social class or deprivation. The practical value was to pinpoint population groups for priority action on health inequality reduction and health improvement rather than a sole focus on the most deprived socioeconomic groups.

          Methods

          We used data from the Scottish Longitudinal Study which captures a 5.3 % sample of Scotland and links the censuses of 1991, 2001 and 2011. Hazard ratios for mortality were estimated for those protected characteristics with sufficient deaths using Cox proportional hazards models and through the calculation of European age-standardised mortality rates. Inequality was measured by calculating the Relative Index of Inequality (RII).

          Results

          The Asian population had a polarised distribution across deprivation deciles and was more likely to be in social class I and II. Those reporting disablement were more likely to live in deprived areas, as were those raised Roman Catholic, whilst those raised as Church of Scotland or as ‘other Christian’ were less likely to. Those aged 35-54 years were the least likely to live in deprived areas and were most likely to be in social class I and II. Males had higher mortality than females, and disabled people had higher mortality than non-disabled people, across all deprivation deciles and social classes. Asian males and females had generally lower mortality hazards than majority ethnic (‘White’) males and females although the estimates for Asian males and females were imprecise in some social classes and deprivation deciles. Males and females who reported their raised religion as Roman Catholic or reported ‘No religion’ had generally higher mortality than other groups, although the estimates for ‘Other religion’ and ‘Other Christian’ were less precise.Using both the area deprivation and social class distributions for the whole population, relative mortality inequalities were usually greater amongst those who did not report being disabled, Asians and females aged 35-44 years, males by age, and people aged <75 years. The RIIs for the raised religious groups were generally similar or too imprecise to comment on differences.

          Conclusions

          Mortality in Scotland is higher in the majority population, disabled people, males, those reporting being raised as Roman Catholics or with ‘no religion’ and lower in Asians, females and other religious groups. Relative inequalities in mortality were lower in disabled than nondisabled people, the majority population, females, and greatest in young adults. From the perspective of intersectionality theory, our results clearly demonstrate the importance of representing multiple identities in research on health inequalities.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12939-015-0274-8) contains supplementary material, which is available to authorized users.

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          Most cited references39

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          Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale.

          Following individuals sampled in a large-scale health survey for the development of diseases and/or death offers the opportunity to assess the prognostic significance of various risk factors. The proportional hazards regression model, which allows for the control of covariates, is frequently used for the analysis of such data. The authors discuss the appropriate time-scale for such regression models, and they recommend that age rather than time since the baseline survey (time-on-study) be used. Additionally, with age as the time-scale, control for calendar-period and/or birth cohort effects can be achieved by stratifying the model on birth cohort. Because, as discussed by the authors, many published analyses have used regression models with time-on-study as the time-scale, it is important to assess the magnitude of the error incurred from this type of incorrect modeling. The authors provide simple conditions for when incorrect use of time-on-study as the time-scale will nevertheless yield approximately unbiased proportional hazards regression coefficients. Examples are given using data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Study. Additional issues concerning the analysis of longitudinal follow-up of survey data are briefly discussed.
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            Life expectancy: women now on top everywhere.

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              Deprivation: explaining differences in mortality between Scotland and England and Wales.

              To detect reasons for the difference in mortality between Scotland and England and Wales a measure of deprivation was studied, comprising overcrowding, unemployment of men, low social class, and not having a car. Data for Scotland for 1980-2 showed this measure to be strongly associated with mortality, with gradients being particularly steep in young adults. Deprivation was much severe in Scotland than in England and Wales. These findings suggest that much excess mortality may be ascribed to more adverse conditions. Standardising the mortality ratios to take account of the relative affluence and deprivation of the two populations led to the differentials observed being radically adjusted, while standardising for social class had little effect. Deprivation measures based on areas overcome many of the limitations associated with social class analysis and also show much greater discrimination between populations. Measures of deprivation apparently provide a powerful basis for explanation of health differences. Such measures should therefore form part of the 1991 census output to facilitate their use on a consistent basis.
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                Author and article information

                Contributors
                +0141 414 2752 , Andrewmillard@nhs.net
                gillian.raab@ed.ac.uk
                phileaglesham@nhs.net
                Pauline.craig1@nhs.net
                Jim.Lewsey@glasgow.ac.uk
                kevralston@yahoo.com
                gmccartney@nhs.net
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                25 November 2015
                25 November 2015
                2015
                : 14
                : 142
                Affiliations
                [ ]NHS Health Scotland, Meridian Court, 5, Cadogan Street, Glasgow, G2 6QE UK
                [ ]University of Glasgow (Institute of Health and Wellbeing), 1 Lilybank Gardens, Glasgow, G12 8RZ UK
                [ ]University of Edinburgh, Edinburgh, EH8 9YL UK
                Author information
                http://orcid.org/0000-0003-3824-7458
                Article
                274
                10.1186/s12939-015-0274-8
                4658811
                26606921
                702b9adb-9393-4a38-94c8-e5e62cec366f
                © Millard et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 31 March 2015
                : 17 November 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Health & Social care
                Health & Social care

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