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

BMC Public Health

Technical Advance

Laura M. Woods¹  Libby Ellis¹  Camille Maringe¹  Claudia Allemani¹  Devon Spika¹  Bernard Rachet¹ 

[1] Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel street, WC1E 7HT, London, UK;

关键词: Life tables;    Model life tables;    Mortality rates;    Life expectancy;    Generalised linear model;    Cubic splines;    Deprivation;    Small areas;   

DOI  :  10.1186/s12889-015-2534-3

 received in 2015-08-18, accepted in 2015-11-20,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundThe 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.MethodsWe 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.ResultsThe 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.ConclusionsThe 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.

【 授权许可】

CC BY   
© Rachet et al. 2015

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