Analysis of the relationship between life expectancy and social determinants in a north-eastern region of Brazil, 2010-2017

Abstract

The process of population aging is a worldwide reality becoming a global public health challenge. Although population aging is especially noticeable in more developed regions, there has also been a significant advance in the quantity of elderly people in areas with unfavourable socioeconomic indicators, and a rapid growth in countries with a low level of economic development. This article presents an analysis based on spatial autocorrelation of the relationship between life expectancy and social determinants in a north-eastern region of Brazil. An ecological study was conducted using the secondary data of social, demographic, and health indicators of elderly people collected in the Brazilian Demographic Census of the 75 municipalities of the state of Sergipe. Spatial autocorrelation was evaluated using the Moran global index and the local indicators of space association. Multiple linear regression models were used to identify the relationship between life expectancy and social determinants. The South-eastern region of the state presented clusters with all indicators pointing to acceptable lifestyles, whereas the municipalities of the north-western and far-eastern regions were characterized by values demonstrating precarious living conditions. The high dependency ratio, illiteracy rate, and unemployment rate among elderly people had a negative impact on life expectancy. The evidence confirms that there is an autocorrelation between social determinants and life expectancy, indicating that the worse the social, economic, and health indicators are, the lower the life expectancy. This finding indicates the need to redirect public policies and formulate strategies aimed at reducing social and health inequalities.

Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China

“…In general, the areas with the lowest BR were usually economically developed, such as Shanghai and Beijing. The social welfare in these areas was also higher than that of other areas [39]. Moreover, areas with a lowest BR tended to have the fewest number of families members (NORPH) and the lowest total dependency ratio (TDR).…”

“…Many previous studies have shown that LE was mainly affected by economic factors [36,38,39]. For example, one study found that the main reason for the spatial distribution pattern of LE in China was the economy [40].…”

Quality of tuberculosis information systems after record linkage

“…However, the older the age, the higher the proportion of underreporting in SINAN, with higher proportions for individuals over 50 years old. This result can be justified by the difficulty in diagnosing TB in elderly people (20)(21) and by existence of other comorbidities that mask TB occurrence, increasing underreporting cases and increasing difficulties of access to health services in this age group. Correlation between age and mortality from TB demonstrates the importance of early diagnosis in individuals older than 60 years (22) .…”

Life Expectancy in Chinese Cities: Spatially Varied Role of Socioeconomic Development, Population Structure, and Natural Conditions

“…In recent years, studying the influence of different factors on life expectancy has become a hot point of academic research [ 6 , 9 , 12 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. In addition, scholars have been greatly interested in the influence of economic development on life expectancy.…”