Mortality, Income Distribution, and Rural-Urban Residence in Brazil
Bibliographic Data
| ID | 4122147 |
|---|---|
| Authors | José Alberto Magno De Carvalho (0000-0002-2303-1892), Charles H Wood |
| Year | 1978 |
| Volume | 4 |
| Issue | 3 |
| Pages | 405 |
| Publication date | 1978-09-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Population and Development Review (JOURNAL) |
| Journal identifiers | ISSN: 0098-7921 • E-ISSN: 1728-4457 |
| Publisher | JSTOR (PUBLISHER) |
| DOI | 10.2307/1972857 |
| OpenAlex | W1992226958 |
| Language | EN |
| Citations received | 22 |
| References cited | 1 |
Historically the transition from high to low mortality levels has been regarded as an integral part of broader transformations in economic and social organization. The specific factors associated with length of life are numerous and complex. They include such things as income, education, housing conditions, public health services, the control of communicable diseases, nutritional levels, medical facilities, and sanitation. Because mortality levels respond to the combined impact of all these factors, quantitative estimates of the influence of any one variable are difficult to obtain. Whether the long-run downward trend in mortality rates can be attributed primarily to improved living conditions, innovations in medical technology, or economic development is a long-standing controversy that is far from settled.' Notwithstanding the debate regarding the relative impact of these factors, mortality levels can serve as summary indicators of the general conditions of a population.2 In this study, estimates of life expectancy-the average number of years of life expected at birth-are used to reflect the mortality levels that characterize subgroups of the Brazilian population. Special tabulations of the 1970 census allow us to estimate life expectancy rates by region, rural or urban residence, and household income. The values provide quantitative indicators with which to determine the magnitude of the differences in quality of life that separate the rich from the poor in the cities and countryside for ten geographic subregions. These estimates are particu
Demographic economics · Distribution (mathematics) · Economics · Geography · Income distribution · Inequality · Residence · Socioeconomics · Global Health Care Issues · Health disparities and outcomes · Mathematics
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| Unique citing works | 22 |
|---|---|
| Citations per year | 0.49 |
| Citation span | 1981 - 2026 (46) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 15 |