Mathematical Mortality Models and Modeling UrbanizationÃ¢ÂÂs Influence on Deaths in Jamaica
Paul Andrew Bourne1*, Angela Hudson-Davis2, Charlene Sharpe-Pryce3, Jeffery Clarke4, Ikhalfani Solan5, Joan Rhule4, Cynthia Francis5, Olive Watson-Coleman6, Anushree Sharma7 and Janinne Campbell-Smith8
- *Corresponding Author:
- Bourne PA
Director, Socio-Medical Research Institute
Tel: (1 876) 566-3088
E-mail: [email protected]
Received Date: April 10, 2015; Accepted Date: May 18, 2015; Published Date: May 22, 2015
Citation: Bourne PA, Hudson-Davis A, Sharpe-Pryce C, Clarke J, Solan I, et al. (2015) Mathematical Mortality Models and Modeling Urbanization’s Influence on Deaths in Jamaica. Arts Social Sci J 6:102. doi:10.4172/2151-6200.1000102
Copyright: © 2015 Bourne PA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.