17 resultados para Figo - Doenças e pragas
Resumo:
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 Petrópolis 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, Neópolis and Ponta Negra); Acute Myocardial Infarction (Northeast, Guarapes and grass Soft); Cerebrovascular diseases (Petrópolis and Mother Luiza); Pneumonia (Ribeira, Praia do Meio, New Discovery, Grass Soft and Ponta Negra); Chronic Diseases of the Lower Way Airlines (Igapó, Northeast and Thursdays). The present findings at work may contribute to other studies on the subject and development of specific policies for the elderly.
Resumo:
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 Petrópolis 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, Neópolis and Ponta Negra); Acute Myocardial Infarction (Northeast, Guarapes and grass Soft); Cerebrovascular diseases (Petrópolis and Mother Luiza); Pneumonia (Ribeira, Praia do Meio, New Discovery, Grass Soft and Ponta Negra); Chronic Diseases of the Lower Way Airlines (Igapó, Northeast and Thursdays). The present findings at work may contribute to other studies on the subject and development of specific policies for the elderly.
