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Perfil sociodemogr?fico dos idosos nas capitais do Nordeste e a mortalidade por doen?as cr?nico-degenerativas desse segmento populacional em Natal (RN)

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Previous issue date: 2015-08-28 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / No contexto do enfrentamento das consequ?ncias da transi??o demogr?fica, o envelhecimento populacional se caracteriza como um importante desafio para a sociedade brasileira. Nesse sentido, este estudo foi desenvolvido em dois objetivos principais. No primeiro artigo, foram empregadas vari?veis de contextos socioecon?micos e demogr?ficos para a identifica??o de perfis multidimensionais dos idosos residentes nas capitais do Nordeste, a partir de indicadores espec?ficos provenientes das informa??es do Censo Demogr?fico 2010. Para tanto, foi utilizado o m?todo Grade of Membership (GoM), cujo delineamento de perfis admite que um indiv?duo perten?a a diferentes graus de pertin?ncia a m?ltiplos perfis, de modo a identificar fatores socioecon?micos e demogr?ficos associados ?s condi??es de vida dos idosos das capitais nordestinas, e mostrar diferen?as na combina??o entre eles. Os principais resultados mostram a forma??o de tr?s perfis extremos: Perfil 1(35,5%), Perfil 2 (24,8%) e Perfil 3 (29,7%). De modo geral, os resultados apontam para perfis com condi??es de vida prec?rias que s?o expressos principalmente pelos baixos n?veis de escolaridade e pela renda mensal domiciliar per capita. O segundo artigo analisou rela??o entre a mortalidade por doen?as cr?nicas (Neoplasias, Doen?as Hipertensivas, Infarto Agudo do Mioc?rdio, Doen?as Cerebrovasculares, Pneumonia e Doen?as Cr?nicas das vias ?reas Inferiores) na popula??o de idosos, dos 137 bairros de Natal, desagregados por faixas et?rias decenais (60 a 69 anos, 70 a 79 anos e 80 anos e mais), e indicadores socioecon?micos. Foram utilizados os microdados do Sistema de Informa??o de Mortalidade (SIM), disponibilizados pela Secretaria de Sa?de de Natal, e as informa??es populacionais s?o provenientes do Censo Demogr?fico 2010. O m?todo utilizado refere-se ? l?gica de vizinhan?a do ?ndice Global e Local (LISA) de Moran, cuja espacializa??o a partir dos mapas coropl?ticos permitiu analisar a mortalidade dos idosos por bairros, segundo indicadores socioecon?micos e demogr?ficos, de acordo com a presen?a de signific?ncia espacial. Os resultados mostram maior propor??o de idosos concentrada nos bairros de melhor condi??o socioecon?mica, como Petr?polis e Lagoa Seca. As taxas de mortalidade, segundo as causas de morte e padronizadas pelo M?todo Bayesiano Emp?rico, distribu?ram-se localmente da seguinte forma: Neoplasias (Santos Reis, Nova Descoberta, Cidade Nova, Capim Macio e Ponta Negra); Doen?as Hipertensivas (Lagoa Azul, Potengi, Redinha, Santos Reis, Ribeira, Lagoa Nova, Capim Macio, Ne?polis e Ponta Negra); Infarto Agudo do Mioc?rdio (Nordeste, Guarap?s e Capim Macio); Doen?as Cerebrovasculares (Petr?polis e M?e Lu?za); Pneumonia (Ribeira, Praia do Meio, Nova Descoberta, Capim Macio e Ponta Negra); Doen?as Cr?nicas das Vias A?reas Inferiores (Igap?, Nordeste e Quintas). Os achados presentes no trabalho poder?o contribuir para outros estudos sobre o tema e fomento de pol?ticas espec?ficas para os idosos. / Population aging is a global demographic trend. This process is a reality that merits attention and importance in recent years, and cause considerable impact in terms of greater demands on the health sector, social security and special care and attention from families and society as a whole. Thus, in the context of addressing the consequences of demographic transition, population aging is characterized as a major challenge for Brazilian society. Therefore, this study was conducted in two main objectives. In the first article, variables of socioeconomic and demographic contexts were employed to identify multidimensional profiles of elderly residents in the Northeast capitals, from specific indicators from the 2010 Census information Therefore, we used the Grade of Membership Method (GoM), whose design profiles admits that an individual belongs to different degrees of relevance to multiple profiles in order to identify socioeconomic and demographic factors associated with living conditions of the elderly in the Northeastern capitals. The second article examined the possible relationship between mortality from chronic diseases and socio-economic indicators in the elderly population, of the 137 districts in Natal, broken down by ten-year age groups (60 to 69 years, 70-79 years and 80 and over. The microdata from the Mortality Information System (SIM), was used, provided by the Health Secretariat of Christmas, and population information came from the Population Census 2010. The method refers to the Global and Local Index neighborhood logic (LISA) Moran, whose spatial distribution from the choropleth maps allowed us to analyze the mortality of the elderly by neighborhoods, according to socioeconomic and demographic indicators, according to the presence of special significance. In the first article, the results show the identification of three extreme profiles. The Profile 1 which is characterized by median socioeconomic status and contributes 35.5% of elderly residents in the area considered. The profile 2 which brings together seniors with low socioeconomic status characteristics, with a percentage of 24.8% of cases. And the Profile 3 composing elderly with features that reveal better socioeconomic conditions, about 29.7% of the elderly. Overall, the results point to poor living conditions represented by the definition of these profiles, mainly expressed by the results observed in more than half of the northeastern elderly experience a situation of social vulnerability given the large percentage that makes up the Profile 1 and Profile 2, adding 60% of the elderly. In the second article, the results show a higher proportion of elderly concentrated in the neighborhoods of higher socioeconomic status, such as Petr?polis and LagoaSeca. Mortality rates, according to the causes of death and standardized by the empirical Bayesian method were distributed locally as follows: Neoplasms (Reis Santos, New Discovery, New Town, Grass Soft and Ponta Negra); Hypertensive diseases (Blue Lagoon, Potengi, Redinha, Reis Santos, Riverside, Lagoa Nova, Grass Soft, Ne?polis and Ponta Negra); Acute Myocardial Infarction (Northeast, Guarapes and grass Soft); Cerebrovascular diseases (Petr?polis and Mother Luiza); Pneumonia (Ribeira, Praia do Meio, New Discovery, Grass Soft and Ponta Negra); Chronic Diseases of the Lower Way Airlines (Igap?, Northeast and Thursdays). The present findings at work may contribute to other studies on the subject and development of specific policies for the elderly.

Identiferoai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/20973
Date28 August 2015
CreatorsSilva, Eliana Mesquita da
Contributors70407690425, http://lattes.cnpq.br/0327817672623352, Formiga, Maria C?lia de Carvalho, 07123213491, http://lattes.cnpq.br/3924849172758348, Silva, Alexandre Sousa da, 27861314804, http://lattes.cnpq.br/4763659817918925, Spyrides, Maria Helena Constantino, Andrade, Lara de Melo Barbosa
PublisherUniversidade Federal do Rio Grande do Norte, PROGRAMA DE P?S-GRADUA??O EM DEMOGRAFIA, UFRN, Brasil
Source SetsIBICT Brazilian ETDs
LanguagePortuguese
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis
Sourcereponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN
Rightsinfo:eu-repo/semantics/openAccess

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