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Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations

Lookup NU author(s): Dr Laura WoodsORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2015 Rachet et al. Background: The methods currently available to estimate age- and sex-specific mortality rates for sub-populations are subject to a number of important limitations. We propose two alternative multivariable approaches: a relational model and a Poisson model both using restricted cubic splines. Methods: We evaluated a flexible Poisson and flexible relational model against the Elandt-Johnson approach in a simulation study using 100 random samples of population and death counts, with different sampling proportions and data arrangements. Estimated rates were compared to the original mortality rates using goodness-of-fit measures and life expectancy. We further investigated an approach for determining optimal knot locations in the Poisson model. Results: The flexible Poisson model outperformed the flexible relational and Elandt-Johnson methods with the smallest sample of data (1%). With the largest sample of data (20%), the flexible Poisson and flexible relational models performed comparably, though the flexible Poisson model displayed a slight advantage. Both approaches tended to underestimate infant mortality and thereby overestimate life expectancy at birth. The flexible Poisson model performed much better at young ages when knots were fixed a priori. For ages 30 and above, results were similar to the model with no fixed knots. Conclusions: The flexible Poisson model is recommended because it derives robust and unbiased estimates for sub-populations without making strong assumptions about age-specific mortality profiles. Fixing knots a priori in the final model greatly improves fit at the young ages.

Publication metadata

Author(s): Rachet B, Maringe C, Woods LM, Ellis L, Spika D, Allemani C

Publication type: Article

Publication status: Published

Journal: BMC Public Health

Year: 2015

Volume: 15

Issue: 1

Online publication date: 16/12/2015

Acceptance date: 20/11/2015

Date deposited: 16/05/2022

ISSN (electronic): 1471-2458

Publisher: BioMed Central

URL: https://doi.org/10.1186/s12889-015-2534-3

DOI: 10.1186/s12889-015-2534-3

PubMed id: 27129577

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