Spatial Gender Differences in Life Expectancy at Birth

Bálint, Lajos

doi:10.15196/rs02108

Cited by 1 publication

(1 citation statement)

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“…In this article, we apply spatial exploratory analysis to a large database containing the life expectancy at birth, e0, both sexes together, in the French départements. Our aim is to detect the patterns of spatial clusters and the presence of spatial spillover effects in e0 and its relationships with the indices of overall fertility (If ), marital fertility (Ig) and nuptiality (Im) in the metropolitan French départements over the period 1833-1982. Various spatial and spatio-temporal statistical methods have been applied to the study of life expectancy and mortality in different countries, although they have all been used in the context of very recent time period: for Poland, Malczewski (2010Malczewski ( ): 2001Malczewski ( -2002for Greece, Tsimbos et al (2011, 2014 for Hungary, Bálint (2012Bálint ( ): 2005Bálint ( -2009; for the USA, Yang et al (2015); Sparks and Sparks (2010); Brazil (2015Brazil ( ): 1998Brazil ( -2009; for West Africa, Balk et al (2004. Windenberger et al (2012 applied spatial analysis techniques to analyse mortality in the French cantons from 1997 to 2001.…”

Section: Introductionmentioning

confidence: 99%

Evolution of Life Expectancy at Birth in French Départements Over the Period 1833–1982

et al. 2017

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This paper deals with spatial aspects of trends in life expectancy at birth in the French metropolitan départements over the 19th and 20th centuries. Data from the censuses conducted from 1833 to 1982 were used to calculate the life expectancy at birth for both sexes togheter, e0 . The overall fertility index (If ), marital fertility index (Ig) and nuptiality index (Im) were also calculated for each five-year period within the same time span. The analysis has two facets: a first, descriptive part in which we establish clusters of départements with similar or different patterns of evolution over the period above mentioned; and a second part in which the effect of covariables in changes in e0 are examined. In addition their coefficients were interpreted including the direct and spatial spillover effects. Unlike earlier studies, in which a spatio-temporal analysis was performed, the time function showing changes in e0 is reduced to a single value which measures the distance or affinity between the functions of time in each de ´partement, which enables us to carry out an exploratory spatial data analysis (ESDA) and apply spatial econometric models.

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