socialize: Consider socio-economic aspects in the attributable health...
In healthiar: Quantifying and Monetizing Health Impacts Attributable to Exposure

socialize

R Documentation

Consider socio-economic aspects in the attributable health impacts

Description

This function analyzes differences in attributable health impacts across study areas looking at the value of a socio-economic indicator (e.g. multiple deprivation index). If nothing is entered in the argument output_attribute, it is assumed that all data come from a table and the argument refer to the columns of that table.

Usage

socialize(
  output_attribute = NULL,
  age_group,
  geo_id_micro,
  social_indicator = NULL,
  increasing_deprivation = TRUE,
  n_quantile = NULL,
  social_quantile = NULL,
  population = NULL,
  ref_prop_pop = NULL,
  impact = NULL,
  exp = NULL,
  bhd = NULL,
  pop_fraction = NULL
)

Arguments

`output_attribute`	`List` containing the outputs of the `healthiar::attribute_health()` assessments for each age group (each list element should be an age group-specific assessment).
`age_group`	`String vector` with the age groups included in the age standardization. The vector refers to age-dependent data in this function and to `output_attribute` (if provided).
`geo_id_micro`	`Numeric vector` or `string vector` specifying the unique ID codes of each geographic area considered in the assessment (`geo_id_micro`).
`social_indicator`	`Numeric vector` showing the social indicator used for the analysis, e.g. a deprivation score (indicator of economic wealth) for each geographic unit. The length and the values must correspond with `geo_id_micro`. If `geo_id_micro` is not entered when using argument `output_attribute`, `social_indicator` must correspond to the column `geo_id_micro` in `results_by_age_group` of `output_attribute`.
`increasing_deprivation`	`Boolean` variable (`TRUE`/`FALSE`) specifying whether an increase in `social_indicator` corresponds to an increase (`TRUE`) or decrease `FALSE` in deprivation. Default: `TRUE`.
`n_quantile`	`Integer value` specifying the number of quantiles in the analysis.
`social_quantile`	`Integer vector` showing the values from 1 to the number of quantiles assigned to each geographic unit. Either enter `social_indicator` and `n_quantile` or `social_quantile`
`population`	`Numeric vector` specifying the population by age group and geographic unit.
`ref_prop_pop`	`Numeric vector` specifying with the reference proportion of population for each age group. If this argument is empty, the proportion of `population` by age group in the provided data will be used.
`impact`	(only if `output_attribute` not specified) `Numeric vector` containing the attributable health impacts by both age group and geo id.
`exp`	(only if `output_attribute` not specified) `Numeric vector` specifying the exposure level(s) to the environmental stressor.
`bhd`	(only if `output_attribute` not specified) `Numeric vector` specifying the baseline health data of the health outcome of interest per age group.
`pop_fraction`	(only if `output_attribute` not specified) `Numeric vector` specifying the population attributable fraction by age group and geographic unit.

Details

Methodology

This function estimates the absolute and relative differences in attributable health impacts comparing study areas with different values for a socio-economic indicator \insertCiteRenard2019_bmchealthiar.

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

Health impact attributable to social indicator

Value

This function returns a list containing the impact (absolute and relative) theoretically attributable to the difference in the social indicator (e.g. degree of deprivation) between the quantiles:

1) social_main (tibble) containing the main results;

difference_value (numeric column) attributable health burden/impact due to differences in deprivation levels
And more

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

input_data_with_quantile (tibble) containing input data and information about the social quantile
results_all_parameters (tibble) containing deprivation-related results
parameters_overall (tibble) containing overall results for different input variables
parameters_per_quantile (tibble) containing quantile-specific results for different input variables

If the argument output_attribute was specified, then the two lists are added next to the existing attribute output.

Author(s)

Alberto Castro & Axel Luyten

References

\insertAllCited

Examples

# Goal: determine fraction of attributable health impact that can
# be attributed to differences in deprivation between the geographic
# units under analysis

## Create assessments for multiple geographic units for the age group
## 40 years and younger
results_age_groups <-
   healthiar::attribute_health(
     age_group = exdat_socialize$age_group,
     exp_central = exdat_socialize$pm25_mean,
     cutoff_central = 0,
     rr_central = exdat_socialize$rr,
     erf_shape = "log_linear",
     rr_increment = 10,
     bhd_central = exdat_socialize$mortality,
     population = exdat_socialize$population,
     geo_id_micro = exdat_socialize$geo_unit)

## Difference in attributable impacts between geographic units
## that is attributable to differences in deprivation
results <- socialize(
  output_attribute = results_age_groups,
  age_group = exdat_socialize$age_group, # The same as in attribute_health()
  ref_prop_pop = exdat_socialize$ref_prop_pop,
  geo_id_micro = exdat_socialize$geo_unit,
  social_indicator = exdat_socialize$score,
  n_quantile = 10,
  increasing_deprivation = TRUE)


results$social_main |>
  dplyr::filter(difference_type == "relative") |>
  dplyr::filter(difference_compared_with == "overall") |>
  dplyr::select(first, last, difference_type, difference_value, comment)

healthiar documentation built on March 12, 2026, 5:07 p.m.