Modelling Mortality in Kenya

Jackson K. Njenga, I. C. Kipchirchir
{"title":"Modelling Mortality in Kenya","authors":"Jackson K. Njenga, I. C. Kipchirchir","doi":"10.9734/arjom/2024/v20i1777","DOIUrl":null,"url":null,"abstract":"This research work seeks to analysis the mortality trend experienced in Kenya over the sample period 1950 to 2021 using a multidimensional modeling framework. Life table functions, namely; life expectancy, survival function and age at death distribution are applied to depict mortality characteristics. Life expectancy and survival rate have significantly improved. There has been a shift in mortality status from a high mortality population, to an intermediate stage and mortality risk factors have increased across age. Mortality concentration curve and index within the Lorenz curve and Gini coefficient framework are used to analyze the lifespan inequality. Lifespan inequality is high with negligible improvements over time. Gompertz force of mortality is then estimated, which is statistically significant at 5% level. Deaths at exact age 25 is about 35 per ten thousand, with the rate death rate increasing by 6.09% per year starting from age 25. Under the assumptions of stable population, where the mortality and fertility functions are independent of time, Malthusian parameter is estimated which is less than zero for selected years. Kenya is a shrinking population and death rate decrease with increase in Malthusian parameter. Finally, to model long-term mortality rate forecast, Lee-Carter model is estimated. The model is statistically significant at 5% level explaining 78.4% of the variations. Expected life expectancy at a given age is projected to increase, with life expectancy at birth in 2030 and 2071 being 65.6 and 70.5 years respectively.","PeriodicalId":281529,"journal":{"name":"Asian Research Journal of Mathematics","volume":"147 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Research Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/arjom/2024/v20i1777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This research work seeks to analysis the mortality trend experienced in Kenya over the sample period 1950 to 2021 using a multidimensional modeling framework. Life table functions, namely; life expectancy, survival function and age at death distribution are applied to depict mortality characteristics. Life expectancy and survival rate have significantly improved. There has been a shift in mortality status from a high mortality population, to an intermediate stage and mortality risk factors have increased across age. Mortality concentration curve and index within the Lorenz curve and Gini coefficient framework are used to analyze the lifespan inequality. Lifespan inequality is high with negligible improvements over time. Gompertz force of mortality is then estimated, which is statistically significant at 5% level. Deaths at exact age 25 is about 35 per ten thousand, with the rate death rate increasing by 6.09% per year starting from age 25. Under the assumptions of stable population, where the mortality and fertility functions are independent of time, Malthusian parameter is estimated which is less than zero for selected years. Kenya is a shrinking population and death rate decrease with increase in Malthusian parameter. Finally, to model long-term mortality rate forecast, Lee-Carter model is estimated. The model is statistically significant at 5% level explaining 78.4% of the variations. Expected life expectancy at a given age is projected to increase, with life expectancy at birth in 2030 and 2071 being 65.6 and 70.5 years respectively.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
肯尼亚死亡率模型
这项研究工作旨在利用多维建模框架,分析 1950 年至 2021 年样本期内肯尼亚的死亡率趋势。采用预期寿命、存活率和死亡年龄分布等生命表函数来描述死亡率特征。预期寿命和存活率有了显著提高。死亡率状况已从高死亡率人口转变为中间阶段,各年龄段的死亡风险因素都有所增加。洛伦兹曲线和基尼系数框架内的死亡率集中曲线和指数用于分析寿命不平等。随着时间的推移,寿命不平等程度很高,改善程度微乎其微。然后估算了死亡率的 Gompertz 力,在 5%的水平上具有统计意义。25 岁时的死亡率约为万分之 35,死亡率从 25 岁开始每年增长 6.09%。在人口稳定的假设下,死亡率和生育率函数与时间无关,马尔萨斯参数的估计值在选定年份小于零。肯尼亚人口不断减少,死亡率随着马尔萨斯参数的增加而下降。最后,为了建立长期死亡率预测模型,对 Lee-Carter 模型进行了估算。该模型在 5%的水平上具有统计意义,可解释 78.4%的变化。预计特定年龄段的预期寿命将增加,2030 年和 2071 年出生时的预期寿命分别为 65.6 岁和 70.5 岁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Irredundant and Almost Irredundant Sets in \(\mathbb{M}_2\)(\(\mathbb{C}\)) Modeling HIV-HBV Co-infection Dynamics: Stochastic Differential Equations and Matlab Simulation with Euler-Maruyama Numerical Method Finite-Time Synchronization of Fractional-Order Quaternion-Valued Neural Networks under Aperiodically Intermittent Control: A Non-Separation Method Conditions of Safe Dominating Set in Some Graph Families Correlates of Ghanaian Teachers' Understanding of Mathematics Strands and Cognitive Domains in Basic Education Certificate Examination
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1