Map physical activity values to NHANES population quantiles

map_nhanes_pa_quantiles() adds a population-level quantile column to a participant-level data frame. Quantiles are evaluated from NHANES accelerometer cumulative distribution functions stratified by age category, sex/gender, measure, and optionally survey wave.

Usage

acti_map_nhanes(
  data,
  id = NULL,
  age = "age",
  sex = "sex",
  measure = "measure",
  value = "value",
  wave = NULL,
  age_category = NULL,
  quantile_col = "acti_pa_quantile"
)

Arguments

data: A data frame with one row per participant-measure observation.
id: Optional participant identifier column name. The column is checked when supplied, but otherwise left unchanged.
age, sex, measure, value: Column names in data containing age in years, sex/gender, physical activity measure, and observed value. Set age = NULL to use the age-overall CDFs. Set sex = NULL to use the sex/gender-overall CDFs. Setting both to NULL uses the overall CDF across both dimensions.
wave: Optional NHANES wave column name or scalar value. Supported values are 7, 8, "2011-2012", and "2013-2014". If NULL, the combined wave CDFs are used.
age_category: Optional column name containing NHANES age categories such as "[20,30)" or "Overall". When supplied, it is used instead of age.
quantile_col: Name of the output quantile column.

Value

data with an added quantile column.

Examples

example_data <- data.frame(
  id = 1:2,
  age = c(25, 62),
  sex = c("Female", "Male"),
  measure = c("mims", "ssl_steps"),
  value = c(15000, 7500)
)

acti_map_nhanes(example_data)
#>   id age    sex   measure value acti_pa_quantile
#> 1  1  25 Female      mims 15000        0.5349443
#> 2  2  62   Male ssl_steps  7500        0.3527381