Convert multi-year life table to single year life table

This function determines populations and deaths by one year age groups.

Usage

prepare_lifetable(age_group, population, bhd, fraction_lived = 0.5)

Arguments

age_group: Numeric vector referring to the first years of the age groups. E.g. c(0, 20, 40, 60) means [0, 20), [20, 40), [40, 60), [60, )
population: Numeric vector referring to mid-year populations by age group.
bhd: Numeric vector referring to the baseline health data (deaths) by age group.
fraction_lived: Numeric vector Numeric vector or single numeric scalar referring to the average fraction of the age interval lived by individuals who die within that interval. Default is 0.5.

Value

This function returns a tibble containing the columns:

population_for_attribute (numeric) containing population values for each age
bhd_for_attribute (numeric) containing baseline health data values for each age
fraction_lived_for_attribute (numeric) containing the fraction of the year lived for each age
and more columns containing input data or results

Details

Methodology

The conversion follows the methodology of the WHO tool. See the AirQ+ manual "Health impact assessment of air pollution: AirQ+ life table manual" for guidance on how to convert larger age groups to 1 year age groups, section "Estimation of yearly values" (WHO 2020) .

fraction_lived is by default 0.5 for all age groups, i.e. the value that AirQ+ assumes. It determines the probability of dying in the age interval and how the mid-year population of the age group is split over the single years of age it contains. It is not a way to control how the deaths of the age group are distributed over those single years of age.

The same value of fraction_lived has to be used when the resulting single-year life table is passed on to attribute_lifetable(). The output column fraction_lived_for_attribute is provided for that purpose.

Last age group

attribute_lifetable() closes the life table at the last age group. The age groups entered here should therefore reach an age in which essentially all remaining deaths occur. See more information in the vignette.

Detailed information about the methodology (including equations) is available in the package vignette. More specifically, see chapters:

References

WHO (2020). “Health impact assessment of air pollution: AirQ+ life table manual.” World Health Organization - Regional Office for Europe. https://www.who.int/europe/publications/i/item/WHO-EURO-2020-1559-41310-56212.

Author

Alberto Castro & Axel Luyten

Examples

# Goal: Convert 5-year population and death data into single year life table
results <- prepare_lifetable(
  age_group = c(0, 5, 10, 15),
  population = c(3387900, 3401300, 3212300, 3026100),
  bhd = c(4727, 472, 557, 1323)
)