Mathematical Mortality Models and Modeling Urbanization? s Influence on Deaths in Jamaica

Type Journal Article - Arts and Social Sciences Journal
Title Mathematical Mortality Models and Modeling Urbanization? s Influence on Deaths in Jamaica
Author(s)
Volume 6
Issue 2
Publication (Day/Month/Year) 2015
URL http://www.omicsonline.com/open-access/mathematical-mortality-models-and-modeling-urbanizations-infl​uence-on-deaths-in-jamaica-2151-6200-1000102.pdf
Abstract
Background: Inspite of the body of knowledge which exists on mortality, the literature is void of a study on ‘Time-specific Mortality’. Objectives: This study aims to evaluate ‘Time-specific Mortality’ in Jamaica, the role of urbanization, and sexratio on mortality. Materials and method: The data were derived from various Jamaica Government Publications including The Economic and Social Survey of Jamaica; 2011 Census of Population and Housing report for Jamaica and the Demographic Statistics, and the Statistical Department of the Jamaica Constabulary Force. Data were recorded, stored and retrived using the Statistical Packages for the Social Sciences for Windows, Version 21.0, as well as Microsoft Excel. The level of significance that is used to determine statistical significance is less than 5% (0.05). Results: The annual probability of mortality in Jamaica, for the studied period is 0.005 = px = 0.008. The probability of dying in Kingston and Saint Andrew is generally greater than that of Jamaica, which is equally the case in Saint James (i.e., 0.005 = px = 0.008), Manchester (i.e., 0.006 = px = 0.008), with the probability of dying being the least in Hanover (0.003 = px = 0.005). The majority of deaths occurred in January (9.8%), with the least being in December (7.8%). Although on average the least number of deaths occurred in December 2011 (7.8%), 11% of Jamaicans died in December compared to 8% in Feburary and 9% in August as well as April-to-June. Urbanization and the sex-ratio explain 88% of the variability in mortality in Jamaica, with urbanization explaining 79.9% of the variability and the sex-ratio contributing the remaining 8.1%. Conclusion: The results presented in this study speaks to the dominance of urbanization in the mortality discourse, urbanization’s role in reducing life expectancy and that the time as well as the sex-ratio, which offers some insights into changes in mortality. These findings offer policy makers critical information that can be used to develop intervention programmes as well as provide scholars with new insights into the mortality discourse.

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