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      Mortality, material deprivation and urbanization: exploring the social patterns of a metropolitan area

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          Abstract

          Introduction

          Socioeconomic inequalities affecting health are of major importance in Europe. The literature enhances the role of social determinants of health, such as socioeconomic characteristics and urbanization, to achieve health equity. Yet, there is still much to know, mainly concerning the association between cause-specific mortality and several social determinants, especially in metropolitan areas.

          This study aims to describe the geographical pattern of cause-specific mortality in the Lisbon Metropolitan Area (LMA), at small area level (parishes), and analyses the statistical association between mortality risk and health determinants (material deprivation and urbanization level). Fourteen causes have been selected, representing almost 60 % of total mortality between 1995 and 2008, particularly those associated with urbanization and material deprivation.

          Methods

          A cross-sectional ecological study was carried out. Using a hierarchical Bayesian spatial model, we estimated sex–specific smoothed Standardized Mortality Ratios (sSMR) and measured the relative risks (RR), and 95 % credible intervals, for cause-specific mortality relative to 1. urbanization level, 2. material deprivation and 3. material deprivation adjusted by urbanization.

          Results

          The statistical association between mortality and material deprivation and between mortality and urbanization changes by cause of death and sex. Dementia and MN larynx, trachea, bronchus and lung are the causes of death showing higher relative risk associated with urbanization. Infectious and parasitic diseases, Chronic liver disease and Diabetes are the causes of death presenting higher relative risk associated with material deprivation. Ischemic heart disease was the only cause with a statistical association with both determinants, and MN female breast was the only without any statistical association. Urbanization level reduces the impact of material deprivation for most of the causes of death. Men face a higher impact of material deprivation and urbanization level, than women, in most cause-specific mortality, even when considering the adjusted model.

          Conclusions

          Our findings explore the specific pattern of fourteen causes of death in LMA and reveals small areas with an excess risk of mortality associated with material deprivation, thereby identifying problematic areas that could potentially benefit from public policies effecting social inequalities.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12939-015-0182-y) contains supplementary material, which is available to authorized users.

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          Most cited references51

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          Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization.

          This two-part article provides an overview of the global burden of atherothrombotic cardiovascular disease. Part I initially discusses the epidemiologic transition which has resulted in a decrease in deaths in childhood due to infections, with a concomitant increase in cardiovascular and other chronic diseases; and then provides estimates of the burden of cardiovascular (CV) diseases with specific focus on the developing countries. Next, we summarize key information on risk factors for cardiovascular disease (CVD) and indicate that their importance may have been underestimated. Then, we describe overarching factors influencing variations in CVD by ethnicity and region and the influence of urbanization. Part II of this article describes the burden of CV disease by specific region or ethnic group, the risk factors of importance, and possible strategies for prevention.
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            Urbanization, malaria transmission and disease burden in Africa.

            Many attempts have been made to quantify Africa's malaria burden but none has addressed how urbanization will affect disease transmission and outcome, and therefore mortality and morbidity estimates. In 2003, 39% of Africa's 850 million people lived in urban settings; by 2030, 54% of Africans are expected to do so. We present the results of a series of entomological, parasitological and behavioural meta-analyses of studies that have investigated the effect of urbanization on malaria in Africa. We describe the effect of urbanization on both the impact of malaria transmission and the concomitant improvements in access to preventative and curative measures. Using these data, we have recalculated estimates of populations at risk of malaria and the resulting mortality. We find there were 1,068,505 malaria deaths in Africa in 2000 - a modest 6.7% reduction over previous iterations. The public-health implications of these findings and revised estimates are discussed.
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              Interpreting Posterior Relative Risk Estimates in Disease-Mapping Studies

              There is currently much interest in conducting spatial analyses of health outcomes at the small-area scale. This requires sophisticated statistical techniques, usually involving Bayesian models, to smooth the underlying risk estimates because the data are typically sparse. However, questions have been raised about the performance of these models for recovering the “true” risk surface, about the influence of the prior structure specified, and about the amount of smoothing of the risks that is actually performed. We describe a comprehensive simulation study designed to address these questions. Our results show that Bayesian disease-mapping models are essentially conservative, with high specificity even in situations with very sparse data but low sensitivity if the raised-risk areas have only a moderate ( 50 per area). Semiparametric spatial mixture models typically produce less smoothing than their conditional autoregressive counterpart when there is sufficient information in the data (moderate-size expected count and/or high true excess risk). Sensitivity may be improved by exploiting the whole posterior distribution to try to detect true raised-risk areas rather than just reporting and mapping the mean posterior relative risk. For the widely used conditional autoregressive model, we show that a decision rule based on computing the probability that the relative risk is above 1 with a cutoff between 70 and 80% gives a specific rule with reasonable sensitivity for a range of scenarios having moderate expected counts (~ 20) and excess risks (~1.5- to 2-fold). Larger (3-fold) excess risks are detected almost certainly using this rule, even when based on small expected counts, although the mean of the posterior distribution is typically smoothed to about half the true value.
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                Author and article information

                Contributors
                00351239851349 , paulasantana.coimbra@gmail.com
                claudiampcosta@gmail.com
                mmari@aspb.cat
                mgotsens@aspb.cat
                cborrell@aspb.cat
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                9 June 2015
                9 June 2015
                2015
                : 14
                : 55
                Affiliations
                [ ]Departamento de Geografia, Centro de Estudos de Geografia e Ordenamento do Território, Universidade de Coimbra, Colégio S. Jerónimo, Largo D. Dinis, 3000-043 Coimbra Portugal
                [ ]CIBER Epidemiología y Salud Pública (CIBERESP), 3-5, Pabellón 11. Planta 0, Monforte de Lemos, 28029 Madrid Spain
                [ ]Agència de Salut Pública de Barcelona, Plaça Lesseps, 1, 08023 Barcelona, Spain
                [ ]Institut d’Investigació Biomèdica (IIB Sant Pau), Sant Antoni Maria Claret, 167, 08025 Barcelona, Spain
                [ ]Universitat Pompeu Fabra, Doctor Aiguader, 80, 08003 Barcelona, Spain
                Article
                182
                10.1186/s12939-015-0182-y
                4483227
                26051558
                793caadb-c03d-4e9c-8a7e-3c7f9ac59897
                © Santana et al. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
                : 3 December 2014
                : 4 May 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Health & Social care
                mortality,material deprivation,metropolitan area,urbanization,small area,bayesian model,inequalities,social/spatial determinants

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