Narrowing geographic inequality in life expectancy in Brazil: a multilevel analysis between 1991 and 2010

How economic development affects healthcare access for people with disabilities: A multilevel study in China

Meeting the healthcare needs of people with disabilities is an important challenge in achieving the central promise of "leave no one behind" during the Sustainable Development Goals era. In this study, we describe the accessibility of healthcare for people living with disabilities, as well as the potential influences of individuals' socioeconomic status and regional economic development. Our data covered 324 prefectural cities in China in 2019 and captured the access to healthcare services for people with disabilities. First, we used linear probability regression models to investigate the association between individual socioeconomic status, including residence, poverty status, education, and healthcare access. Second, we conducted an ecological analysis to test the association between prefectural economic indicators, including GDP (gross domestic product) per capita, urbanization ratio, average years of education, Engel's coefficient, and the overall prevalence of access to healthcare for people with disabilities within prefectures. Third, we used multilevel regression models to explore the association between the individual's socio-economic status, prefectural economic indicators, and access to healthcare at the individual level for people with disabilities. The results showed, first, that higher individual socioeconomic status (urban residence or higher educational level) was associated with better access to healthcare for people with disabilities. Second, regional economic indicators were positively associated with access to healthcare at the aggregate and individual levels. This study suggests that local governments, particularly in low- and middle-income countries, should promote economic development and conduct poverty alleviation policies to improve healthcare access for disadvantaged groups.

A new method for multispace analysis of multidimensional social exclusion

Social phenomena are multidimensional and dependent on geographic space. Numerous methods are capable of representing multidimensional social phenomena through a composite indicator. Among these methods, principal component analysis (PCA) is the most used when considering the geographical perspective. However, the composite indicators built by the method are sensitive to outliers and dependent on the input data, implying informational loss and specific eigenvectors that make multi-space-time comparisons impossible. This research proposes a new method to overcome these problems: the Robust Multispace PCA. The method incorporates the following innovations. The sub-indicators are weighted according to their conceptual importance in the multidimensional phenomenon. The non-compensatory aggregation of these sub-indicators guarantees the function of the weights as of relative importance. Aggregating indicators in dimensions balances the weight structure of dimensions in the composite indicator. A new scale transformation function that eliminates outliers and allows multispatial comparison reduces by 1.52 times the informational loss of the composite indicator of social exclusion in eight cities' urban areas. The Robust Multispace-PCA has a high potential for appropriation by researchers and policymakers, as it is easy to follow, offers more informative and accurate representations of multidimensional social phenomena, and favors the development of policies at multiple geographic scales.

Modeling Years of Life Lost Due to COVID-19, Socioeconomic Status, and Nonpharmaceutical Interventions: Development of a Prediction Model

Background

Research in the COVID-19 pandemic focused on the health burden, thereby largely neglecting the potential harm to life from welfare losses.

Objective

This paper develops a model that compares the years of life lost (YLL) due to COVID-19 and the potential YLL due to the socioeconomic consequences of its containment.

Methods

It improves on existing estimates by conceptually disentangling YLL due to COVID-19 and socioeconomic status. By reconciling the normative life table approach with socioeconomic differences in life expectancy, it accounts for the fact that people with low socioeconomic status are hit particularly hard by the pandemic. The model also draws on estimates of socioeconomic differences in life expectancy to ascertain potential YLL due to income loss, school closures, and extreme poverty.

Results

Tentative results suggest that if only one-tenth of the current socioeconomic damage becomes permanent in the future, it may carry a higher YLL burden than COVID-19 in the more likely pandemic scenarios. The model further suggests that the socioeconomic harm outweighs the disease burden due to COVID-19 more quickly in poorer and more unequal societies. Most urgently, the substantial increase in extreme poverty needs immediate attention. Avoiding a relatively minor number of 4 million unemployed, 1 million extremely poor, and 2 million students with a higher learning loss may save a similar amount of life years as saving 1 million people from dying from COVID-19.

Conclusions

Primarily, the results illustrate the urgent need for redistributive policy interventions and global solidarity. In addition, the potentially high YLL burden from income and learning losses raises the burden of proof for the efficacy and necessity of school and business closures in the containment of the pandemic, especially where social safety nets are underdeveloped.

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998-2017

Background: What is the spatial pattern of mortality by cause and sex in Brazil? Even considering the main causes of death, such as neoplasms, cardiovascular diseases, external causes, respiratory diseases, and infectious diseases, there are still important debate regarding the spatial pattern of mortality by causes in Brazil. Evidence shows that there is an overlap in transitional health states, due to the persistence of infectious diseases (e.g., dengue, cholera, malaria, etc.,) in parallel with the increase in chronic degenerative diseases. The main objective of this paper is to analyze the spatio-temporal evolution of three groups of causes of death in Brazil across small areas from 1998 to 2017, by sex. Methods: We use publicly available data from the System Data Mortality Information (SIM-DATASUS) from 1998 to 2017. We focus on this period due to the better quality of information, in addition to all deaths are registered following the Tenth Revision of the International Classification of Diseases (ICD-10). We estimate standardized mortality rates by sex and cause aggregated into three main groups. We use a ternary color scheme to maximize all the information in a three-dimensional array of compositional data. Results: We find improvements in mortality from chronic degenerative diseases; faster declines are observed in the Southern regions of the country; but the persistence of high levels of mortality due to infectious diseases remained in the northern parts of the country. We also find impressive differences in external causes of deaths between males and females and an increase in mortality from these causes in the interior part of the country. Conclusions: This study provides useful information for policy makers in establishing effective measures for the prevention of deaths and public health planning for deaths from external and non-communicable causes. We observed how the distribution of causes of death varies across regions and how the patterns of mortality also vary by gender.

Health-related quality of life of institutionalized older adults: Influence of physical, nutritional and self-perceived health status

INTRODUCTION

Institutionalized older adults have higher risks of diseases and worse health-related quality of life (HRQoL) than noninstitutionalized.

OBJECTIVE

To evaluate the influence of physical state, nutritional status and self-perceived general health and oral health on the quality of life of institutionalized older adults in two Brazilian cities.

METHODS

A multicenter cross-sectional study was conducted in 17 homes for the aged of two Brazilian cities. Six trained researchers interviewed 344 older adults. The performance of activities of daily living (Katz scale) and frailty status (Fried scale) were applied to evaluate the physical state. The Mini Nutritional Assessment Short-Form (MNA-SF®) and the body composition were used to screening the nutritional status. A hand dynamometer was used to measure the dominant hand grip strength. The 12-Item Short Form Survey for self-perceived health (SF-12) was used to determine the HRQoL. A Likert scale was used to assess the general and oral health self-perception. Multiple Poisson regression model was applied to analyze the data (α = 0.05).

RESULTS

The mean (SD) score of the SF-12 was 60.89 (14.50) points. The factors associated with the highest SF-12 score were being able to walk, being nonfrail, being normal nourished, taking fewer medications, having greater dominant hand grip strength and higher self- perceived general health (p < 0.05).

CONCLUSION

Better HRQoL in institutionalized older adults was associated with better physical state, nutritional status and self-perceived general health.