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

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Standard

Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations. / Rachet, Bernard; Maringe, Camille; Woods, Laura M; Ellis, Libby; Spika, Devon; Allemani, Claudia.

I: BMC Public Health, Vol. 15, 16.12.2015.

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Harvard

APA

CBE

MLA

Vancouver

Author

Rachet, Bernard ; Maringe, Camille ; Woods, Laura M ; Ellis, Libby ; Spika, Devon ; Allemani, Claudia. / Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations. I: BMC Public Health. 2015 ; Vol. 15.

RIS

TY - JOUR

T1 - Multivariable flexible modelling for estimating complete, smoothed life tables for sub-national populations

AU - Rachet, Bernard

AU - Maringe, Camille

AU - Woods, Laura M

AU - Ellis, Libby

AU - Spika, Devon

AU - Allemani, Claudia

PY - 2015/12/16

Y1 - 2015/12/16

N2 - 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.

AB - 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.

KW - Adolescent

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Child

KW - Child, Preschool

KW - England/epidemiology

KW - Female

KW - Humans

KW - Infant

KW - Infant, Newborn

KW - Life Expectancy

KW - Life Tables

KW - Male

KW - Middle Aged

KW - Models, Statistical

KW - Multivariate Analysis

KW - Poisson Distribution

KW - Young Adult

U2 - 10.1186/s12889-015-2534-3

DO - 10.1186/s12889-015-2534-3

M3 - Article

VL - 15

JO - BMC Public Health

T2 - BMC Public Health

JF - BMC Public Health

SN - 1471-2458

ER -