pedbp (version 2.0.2)

bmi_for_age: BMI for Age - Pediatric Growth Standard

Description

BMI for age quantile, distribution, and zscore function based on LMS data from the CDC and WHO.

Usage

p_bmi_for_age(q, male, age, source = getOption("pedbp_pgs_source", "CDC"), ...)
q_bmi_for_age(p, male, age, source = getOption("pedbp_pgs_source", "CDC"), ...)
z_bmi_for_age(q, male, age, source = getOption("pedbp_pgs_source", "CDC"), ...)

Value

p_ method return values from the estimated distribution function.

q_ methods return values from the estimated quantile function.

z_ methods return standard scores.

Arguments

q

a vector of quantiles

male

integer value, 1 = male, 0 = female

age

numeric age, in months

source

a character string denoting the data source providing the parameters needed for the estimate. Valid values are "CDC" and "WHO". This can be set explicitly, or by using the pedbp_pgs_source option.

...

pass through

p

a vector of probabilities

Notes

CDC Recommends using WHO growth charts for infants and children ages 0 to 2 years of age in the U.S. and CDC growth charts to monitor growth for children age 2 years and older in the U.S.

References

https://www.cdc.gov/growthcharts/percentile_data_files.htm, https://www.who.int/tools/child-growth-standards/standards

See Also

• Distribution functions:

  • bmi_for_age

  • head_circumference_for_age

  • height_for_age

  • length_for_age

  • weight_for_age

  • weight_for_length

  • weight_for_height

• Plotting functions:

  • gs_chart

  • gs_cdf

• Vignette:

  • vignette(topic = "growth-standards", package = "pedbp")

Examples

# The 54th quantile BMI (kg * m^(-2)) for a six year (72 month) old female
# is
bmi <- q_bmi_for_age(p = 0.54, male = 0, age = 72.0)
all.equal(p_bmi_for_age(q = bmi, male = 0, age = 72), 0.54)
all.equal(z_bmi_for_age(q = bmi, male = 0, age = 72), qnorm(0.54))

# Find the 29th percentile for females from ages 0 through 6 years in three
# month increments.  Sourcing the only CDC will generate a warning;
# suppressed in this example.
ages <- seq(0, 72, by = 1)
bmi_29 <-
  data.frame(
    age = ages
  , "CDC"     = suppressWarnings(q_bmi_for_age(p = 0.29, male = 0, age = ages, source = "CDC"))
  , "WHO"     = q_bmi_for_age(p = 0.29, male = 0, age = ages, source = "WHO")
  )

plot(
    x = bmi_29$age
  , y = bmi_29$WHO
  , col = 1
  , pch = 16
  , xlab = "Age (months)", ylab = "29th percentile BMI (kg * m^(-2))"
  , type = "b"
)
points(x = bmi_29$age, y = bmi_29$CDC, col = 2, pch = 17, type = "b")
legend("bottomright", col = 1:2, pch = 16:17, legend = c("WHO", "CDC"))