Old age mortality in South Africa, 1985-2011

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dc.contributor.advisorDorrington, Roben_ZA
dc.contributor.authorRichman, Ronald Daviden_ZA
dc.date.accessioned2018-02-09T12:52:49Z
dc.date.available2018-02-09T12:52:49Z
dc.date.issued2017en_ZA
dc.description.abstractEstimating the level and trend in population mortality rates at advanced ages in South Africa is complicated by problems with both the population and death data. Population and death data, particularly in developing countries, often suffer from age misreporting - age exaggeration and digit preference. Also, censuses may under- or overestimate the population and registration of deaths is usually incomplete in developing countries (Dorrington, Moultrie and Timæus 2004). To avoid these problems, the research in this dissertation relies on the method of extinct generations and its extensions (Thatcher, Kannisto and Andreev 2002) to re-estimate the population using only the death data, which is often recorded more accurately than the population data. Since deaths are not reported completely in South Africa, the death data must be corrected before use. Death Distribution Methods (Moultrie, Dorrington, Hill et al. 2013) are used to correct the death data for incomplete registration of deaths. After correction, Near Extinct Generation methods (NEG) are used to re-estimate the population by projecting future deaths of nearly extinct cohorts. After showing that mortality rates produced using the original NEG methods are biased because of age and year of birth heaping present in the South African death data, the NEG methods are adapted to the South African context. The adapted NEG model smooths the age and year of birth heaping in the death data and produces mortality rates that are less biased than the original NEG methods. This model - referred to as the NEG-GAM model in this research - is used to re-estimate the population at each age from 70 and above and to calculate mortality rates since 1985. The population estimates aged 70+ produced using the NEG-GAM model match those from the 2011 census well. It is found that both the population and death data suffer from the same pattern of heaping, that the population and death data are affected by age exaggeration and that the death data are less affected by age exaggeration than the population data. The level and trend in mortality rates calculated using the NEG-GAM model are discussed and compared to the mortality rates in the Human Mortality Database and other studies of South African mortality. The mortality rates produced for the African and Coloured population groups appear too low at the older ages due to age exaggeration in the death data, while those for the Indian and White population groups appear to be reasonable over the entire age range. Mortality appears to be improving in the age range 70-79 for the Coloured, Indian and White population groups and deteriorating slowly for the African population group.en_ZA
dc.identifier.apacitationRichman, R. D. (2017). <i>Old age mortality in South Africa, 1985-2011</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science. Retrieved from http://hdl.handle.net/11427/27486en_ZA
dc.identifier.chicagocitationRichman, Ronald David. <i>"Old age mortality in South Africa, 1985-2011."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2017. http://hdl.handle.net/11427/27486en_ZA
dc.identifier.citationRichman, R. 2017. Old age mortality in South Africa, 1985-2011. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Richman, Ronald David AB - Estimating the level and trend in population mortality rates at advanced ages in South Africa is complicated by problems with both the population and death data. Population and death data, particularly in developing countries, often suffer from age misreporting - age exaggeration and digit preference. Also, censuses may under- or overestimate the population and registration of deaths is usually incomplete in developing countries (Dorrington, Moultrie and Timæus 2004). To avoid these problems, the research in this dissertation relies on the method of extinct generations and its extensions (Thatcher, Kannisto and Andreev 2002) to re-estimate the population using only the death data, which is often recorded more accurately than the population data. Since deaths are not reported completely in South Africa, the death data must be corrected before use. Death Distribution Methods (Moultrie, Dorrington, Hill et al. 2013) are used to correct the death data for incomplete registration of deaths. After correction, Near Extinct Generation methods (NEG) are used to re-estimate the population by projecting future deaths of nearly extinct cohorts. After showing that mortality rates produced using the original NEG methods are biased because of age and year of birth heaping present in the South African death data, the NEG methods are adapted to the South African context. The adapted NEG model smooths the age and year of birth heaping in the death data and produces mortality rates that are less biased than the original NEG methods. This model - referred to as the NEG-GAM model in this research - is used to re-estimate the population at each age from 70 and above and to calculate mortality rates since 1985. The population estimates aged 70+ produced using the NEG-GAM model match those from the 2011 census well. It is found that both the population and death data suffer from the same pattern of heaping, that the population and death data are affected by age exaggeration and that the death data are less affected by age exaggeration than the population data. The level and trend in mortality rates calculated using the NEG-GAM model are discussed and compared to the mortality rates in the Human Mortality Database and other studies of South African mortality. The mortality rates produced for the African and Coloured population groups appear too low at the older ages due to age exaggeration in the death data, while those for the Indian and White population groups appear to be reasonable over the entire age range. Mortality appears to be improving in the age range 70-79 for the Coloured, Indian and White population groups and deteriorating slowly for the African population group. DA - 2017 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2017 T1 - Old age mortality in South Africa, 1985-2011 TI - Old age mortality in South Africa, 1985-2011 UR - http://hdl.handle.net/11427/27486 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/27486
dc.identifier.vancouvercitationRichman RD. Old age mortality in South Africa, 1985-2011. [Thesis]. University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2017 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/27486en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDivision of Actuarial Scienceen_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherActuarial Scienceen_ZA
dc.titleOld age mortality in South Africa, 1985-2011en_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMPhilen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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