Stochastic Mortality Models with Birth Cohort Effects in Older People: A Systematic Review

Abigail Yeboah Boateng; Akoto Yaw Omari-Sasu; Maxwell Akwasi Boateng

doi:10.51867/ajernet.5.4.125

Authors

Abigail Yeboah Boateng
abby.boateng20@gmail.com
Kwame Nkrumah University of Science and Technology, Ghana
Akoto Yaw Omari-Sasu Kwame Nkrumah University of Science and Technology, Ghana https://orcid.org/0000-0002-1655-1515
Maxwell Akwasi Boateng Kwame Nkrumah University of Science and Technology, Ghana https://orcid.org/0000-0003-4895-4754

Keywords:

Birth Cohort Effect, Mortality Rate, Stochastic Mortality Model

Abstract

As populations age, comprehending the factors that influence mortality rates becomes ever more critical. Age, period and birth cohort are now acknowledged as essential determinants in analyzing (and projecting) mortality trends. This systematic review investigates the impact of birth cohort effects on mortality rates among individuals aged 60 and older, with a particular emphasis on stochastic mortality models. A thorough literature search was performed to identify studies published over the past three decades that examine stochastic mortality models incorporating birth cohort effects in older adults. Five primary mortality models were assessed and data were extracted concerning study characteristics, participant demographics and mortality outcomes. The findings underscore the significance of cohort effects in mortality modeling, particularly for senior demographics. These effects encompass social and historical elements that shape generational health; thus, they enhance the precision of mortality projections and guide effective policy formulation. Stochastic models that integrate cohort effects were shown to more accurately capture distinct mortality trends. This indicates that exposure to advancements in healthcare and environmental influences, significantly affects mortality results among older cohorts. However, this review identifies several challenges in model estimation and proposes avenues for future inquiry. It advocates for adapting models to more accurately mirror the unique characteristics of aging populations, improving validation techniques for mortality models and applying the results to real-world contexts to bolster decision-making in public health and social policy.

Dimensions

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