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Compute all available HealthMarkers categories

Source: R/health_markers.R
all_health_markers.Rd

Compute all available HealthMarkers categories

Usage

all_health_markers(
  data,
  col_map,
  which = "all",
  include_insulin = TRUE,
  normalize = c("none", "z", "inverse", "range", "robust"),
  mode = c("both", "IS", "IR"),
  verbose = TRUE,
  na_action = c("keep", "omit", "error")
)

Arguments

data

A data.frame or tibble.

col_map

Named list for column mapping forwarded to underlying functions. If col_map is NULL or missing, all_health_markers() calls hm_infer_cols() once at the top level to guess a column map from common synonyms (for example TG vs triglycerides, BMI vs bmi, HDL_c vs HDL). The inferred col_map is then reused for all groups that require it, and an error is thrown if required keys (e.g. TG, HDL_c, LDL_c, TC, BMI, age, sex) cannot be inferred.

which

"all" or a vector of registry keys (see Details).

include_insulin

Logical; include all_insulin_indices() first.

normalize

One of c("none","z","inverse","range","robust").

mode

One of c("both","IS","IR") passed to insulin indices.

verbose

Logical.

na_action

One of c("keep","omit","error"); forwarded to underlying calculators (HM-CS v2).

Value

Data frame with original columns plus many derived markers.

Details

Common group names for which include:

  • "lipid", "liver", "glycemic", "mets", "oxidative"

  • "bone", "allostatic_load", "nutrient", "vitamin", "vitamin_d_status"

  • "renal", "ckd_stage", "kidney_kfre"

  • "frailty_index", "charlson", "sarc_f"

  • "nfl", "iAge", "calcium_corrected", "kyn_trp"

Note

For academic / clinical references tied to each derived marker or index, consult the help pages of the source functions (e.g. ?allostatic_load, ?bone_markers, ?vitamin_markers, ?inflammatory_markers, etc.). This aggregator provides integration only and does not restate citations.

References

Aggregator wrapper. See underlying function help pages for full references across categories included by which.

Examples

df <- data.frame(
  TC = 200, HDL_c = 50, TG = 150, LDL_c = 120,
  ALT = 30, AST = 20, BMI = 25
)
all_health_markers(df, col_map = list(), which = c("lipid","liver"),
                   include_insulin = FALSE, normalize = "none", mode = "both",
                   verbose = FALSE, na_action = "keep")
#>    TC HDL_c  TG LDL_c ALT AST BMI non_HDL_c remnant_c ratio_TC_HDL ratio_TG_HDL
#> 1 200    50 150   120  30  20  25       150        30            4            3
#>   ratio_LDL_HDL ApoB_ApoA1
#> 1           2.4         NA