healthiar (version 0.2.3)

daly: Attributable disability-adjusted life years

Description

This function quantifies the attributable disability-adjusted life years (DALY) by summing the two DALY components: years of life lost (YLL) and years lived with disability (YLD).

Usage

daly(output_attribute_yll, output_attribute_yld)

Value

This function returns a list containing:

1) health_main (tibble) containing the main results;

• impact (numeric column) attributable health burden/impact in DALY

• impact_yld (numeric column) attributable health burden/impact in YLD

• impact_yll (numeric column) attributable health burden/impact in YLL

• dw (numeric column) disability weight used for YLD calculation

• And many more

2) health_detailed (list) containing detailed (and interim) results.

• results_raw (tibble) containing results for each combination of input uncertainty

• results_by_geo_id_micro (tibble) containing results for each geographic unit under analysis (specified in geo_id_micro argument)

• input_args (list) containing all the argument inputs used in the background

Arguments

output_attribute_yll, output_attribute_yld

variable containing YLL or YLD results of a attribute_...() function call, respectively.

Author

Alberto Castro & Axel Luyten

Details

Methodology

This function sums the years of life lost (YLL) and years lived with disability (YLD) to obtain the disability-adjusted lost years (DALY) GBD2020_tlhealthiar.

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

• dalys

References

See Also

• Upstream: attribute_health, attribute_lifetable

Examples

# Goal: obtain DALY (disability-adjusted life years) from two existing \code{attribute_...} outputs
# Step 1: Create YLL (years of life lost) assessment
results_yll <- attribute_lifetable(
  health_outcome = "yll",
  approach_exposure = "single_year",
  approach_newborns = "without_newborns",
  exp_central = 8.85,
  prop_pop_exp = 1,
  cutoff_central = 5,
  rr_central =  1.118,
  rr_increment = 10,
  erf_shape = "log_linear",
  age_group = exdat_lifetable$age_group,
  sex = exdat_lifetable$sex,
  bhd_central = exdat_lifetable$deaths,
  population = exdat_lifetable$midyear_population,
  year_of_analysis = 2019,
  min_age = 20
)
# Step 2: Create YLD (years lived with disability) assessment
results_yld  <- attribute_health(
  exp_central = 8.85,
  prop_pop_exp = 1,
  cutoff_central = 5,
  bhd_central = 1000,
  rr_central = 1.1,
  rr_increment = 10,
  erf_shape = "log_linear",
  duration_central = 100,
  dw_central = 0.5,
  info = "pm2.5_yld"
)
# Step 3: obtain DALY
results <- daly(
  output_attribute_yll = results_yll,
  output_attribute_yld = results_yld
)
# Attributable impact in DALY
results$health_main |>
  dplyr::select(impact, impact_yll, impact_yld)