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      Disparities in mortality among 25–44-year-olds in England: a longitudinal, population-based study

      research-article
      , Prof, PhD a , e , * , , Prof, MD a , d , , Prof, PhD b , f , g , , Prof, PhD c , f , , Prof, MD h , , Prof, MD i
      The Lancet. Public Health
      Elsevier, Ltd

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          Summary

          Background

          Since the mid-1990s, excess mortality has increased markedly for adults aged 25–44 years in the north compared with the south of England. We examined the underlying causes of this excess mortality and the contribution of socioeconomic deprivation.

          Methods

          Mortality data from the Office of National Statistics for adults aged 25–44 years were aggregated and compared between England's five most northern versus five most southern government office regions between Jan 1, 1981, and Dec 31, 2016. Poisson regression models, adjusted for age and sex, were used to quantify excess mortality in the north compared with the south by underlying cause of death (accidents, alcohol related, cardiovascular disease and diabetes, drug related, suicide, cancer, and other causes). The role of socioeconomic deprivation, as measured by the 2015 Index of Multiple Deprivation, in explaining the excess and regional variability was also explored.

          Findings

          A mortality divide between the north and south appeared in the mid-1990s and rapidly expanded thereafter for deaths attributed to accidents, alcohol misuse, and drug misuse. In the 2014–16 period, the northern excess was incidence rate ratio (IRR) 1·47 (95% CI 1·39–1·54) for cardiovascular reasons, 2·09 (1·94–2·25) for alcohol misuse, and 1·60 (1·51–1·70) for drug misuse, across both men and women aged 25–44 years. National mortality rates for cardiovascular deaths declined over the study period but a longstanding gap between north and south persisted (from 33·3 [95% CI 31·8–34·8] in 1981 to 15·0 [14·0–15·9] in 2016 in the north vs from 23·5 [22·3–24·8] to 9·9 [9·2–10·5] in the south). Between 2014 and 2016, estimated excess numbers of death in the north versus the south for those aged 25–44 years were 1881 (95% CI 726–2627) for women and 3530 (2216–4511) for men. Socioeconomic deprivation explained up to two-thirds of the excess mortality in the north (IRR for northern effect reduced from 1·15 [95% CI 1·14–1·15; unadjusted] to 1·05 [1·04–1·05; adjusted for Index of Multiple Deprivation]). By 2016, in addition to the persistent north–south gap, mortality rates in London were lower than in all other regions, with IRRs ranging from IRR 1·13 (95% CI 1·12–1·15) for the East England to 1·22 (1·20–1·24) for the North East, even after adjusting for deprivation.

          Interpretation

          Sharp relative rises in deaths from cardiovascular reasons, alcohol misuse and drug misuse in the north compared with the south seem to have created new health divisions between England's regions. This gap might be due to exacerbation of existing social and health inequalities that have been experienced for many years. These divisions might suggest increasing psychological distress, despair, and risk taking among young and middle-aged adults, particularly outside of London.

          Funding

          Medical Research Council and Wellcome Trust.

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          Most cited references22

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          The causal relation between human papillomavirus and cervical cancer.

          The causal role of human papillomavirus infections in cervical cancer has been documented beyond reasonable doubt. The association is present in virtually all cervical cancer cases worldwide. It is the right time for medical societies and public health regulators to consider this evidence and to define its preventive and clinical implications. A comprehensive review of key studies and results is presented.
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            Attributable risk of psychiatric and socio-economic factors for suicide from individual-level, population-based studies: a systematic review.

            The overall importance of a risk factor for suicide in a population is determined not only by the relative risk (RR) of suicide but also the prevalence of the risk factor in the population, which can be combined with the RR to calculate the population attributable risk (PAR). This study compares risk factors from two well studied domains of suicide research - socio-economic deprivation (relatively low RR, but high population prevalence) and mental disorders (relatively high RR risk, but low population prevalence). RR and PAR associated with suicide was estimated for high prevalence ICD-10/DSM-IV psychiatric disorders and measures of socio-economic status (SES) from individual-level, population-based studies. A systematic review and meta-analysis was conducted of population-based case-control and cohort studies of suicide where relative risk estimates for males and females could be extracted. RR for any mental disorder was 7.5 (6.2-9.0) for males and 11.7 (9.7-14.1) for females, compared to RR for the lowest SES groups of 2.1 (1.5-2.8) for males and 1.5 (1.2-1.9) for females. PAR in males for low educational achievement (41%, range 19-47%) and low occupational status (33%, range 21-42%) was of a similar magnitude to affective disorders (26%, range 7-45%) and substance use disorders (9%, range 5-24%). Similarly in females the PAR for low educational achievement (20%, range 19-22%) was of a similar magnitude to affective disorders (32%, range 19-67%), substance use disorder (25%, range 5-32%) and anxiety disorder (12%, range 6-22%). The findings of the present study suggest that prevention strategies which focus on lower socio-economic strata (more distal risk factors) have the potential to have similar population-level effects as strategies which target more proximal psychiatric risk factors in the prevention and control of suicide. Copyright © 2010 Elsevier Ltd. All rights reserved.
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              Unemployment and suicide. Evidence for a causal association?

              To determine the independent associations of labour force status and socioeconomic position with death by suicide. Cohort study assembled by anonymous and probabilistic record linkage of census and mortality records. 2.04 million respondents to the New Zealand 1991 census aged 18-64 years. Suicide in the three years after census night. The age adjusted odds ratios (95% confidence intervals) of death by suicide among 25 to 64 year olds who were unemployed compared with employed were 2.46 (1.10 to 5.49) for women and 2.63 (1.87 to 3.70) for men. Similarly increased odds ratios were observed for the non-active labour force compared with the employed. Strong age only adjusted associations of suicide death with the socioeconomic factors of education (men only), car access, and household income were observed. Compared with those who were married on census night, the non-married had odds ratios of suicide of 1.81 (1.22 to 2.69) for women and 2.08 (1.66 to 2.61) for men. In a multivariable model the association of socioeconomic factors with suicide reduced to the null. However, marital status and labour force status remained strong predictors of suicide death. Unemployment was also strongly associated with suicide death among 18-24 year old men. Sensitivity analyses suggested that confounding by mental illness might explain about half, but not all, of the association between unemployment and suicide. Being unemployed was associated with a twofold to threefold increased relative risk of death by suicide, compared with being employed. About half of this association might be attributable to confounding by mental illness.
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                Author and article information

                Contributors
                Journal
                Lancet Public Health
                Lancet Public Health
                The Lancet. Public Health
                Elsevier, Ltd
                2468-2667
                31 October 2018
                December 2018
                31 October 2018
                : 3
                : 12
                : e567-e575
                Affiliations
                [a ]Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
                [b ]Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
                [c ]Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
                [d ]Public Health and Clinical Informatics, Department of Public Health and Policy, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
                [e ]National Institute for Health Research, School for Primary Care Research, University of Manchester, Manchester, UK
                [f ]NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, UK
                [g ]Manchester Academic Health Sciences Centre, Manchester, UK
                [h ]Keele Cardiovascular Research Group, Centre for Prognosis Research, Institute of Primary Care and Health Sciences, Keele University, UK
                [i ]Department of Health Sciences, Seebohm Rowntree Building, University of York, York, UK
                Author notes
                [* ]Correspondence to: Prof Evangelos Kontopantelis, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK e.kontopantelis@ 123456manchester.ac.uk
                Article
                S2468-2667(18)30177-4
                10.1016/S2468-2667(18)30177-4
                6277813
                30389570
                66e4f69f-e3cb-4364-a8a7-42b51a0fa2d8
                © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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