growthcleanr (version 2.2.0)

ext_bmiz: Calculate extended BMI measures

Description

ext_bmiz Calculates the sigma (scale parameter for the half-normal distribution), extended BMI percentile, extended BMIz, and the CDC LMS Z-scores for weight, height, and BMI for children between 2 and 19.9 years of age. Note that for BMIs <= 95th percentile of the CDC growth charts, the extended values for BMI are equal to the LMS values. The extended values differ only for children who have a BMI > 95th percentile.

Usage

ext_bmiz(
  data,
  age = "agem",
  wt = "wt",
  ht = "ht",
  bmi = "bmi",
  adjust.integer.age = TRUE,
  ref.data.path = ""
)

Value

Expanded data frame containing computed BMI values

Arguments

data

Input data frame or data table

age

Name of input column containing subject age in months in quotes, default "agem"

wt

Name of input column containing weight (kg) value in quotes, default "wt"

ht

Name of input column containing height (cm) value in quotes, default "ht"

bmi

Name of input column containing calculated BMI in quotes, default "bmi"

adjust.integer.age

If age inputs are all integer, add 0.5 if TRUE; default TRUE

ref.data.path

Path to directory containing reference data

Details

This function should produce output equivalent to the SAS macro provided at https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm. The macro was updated in December, 2022, according to the findings of the NCHS report available at https://dx.doi.org/10.15620/cdc:121711. This function has been updated to match it as of growthcleanr v2.1.0.

The extended BMIz is the inverse cumulative distribution function (CDF) of the extended BMI percentile. If the extended percentile is very close to 100, the qnorm function in R produces an infinite value. This occurs only if the the extended BMI percentile is > 99.99999999999999. This occurs infrequently, such as a 48-month-old with a BMI > 39, and it is likely that these BMIs represent data entry errors. For these cases, extended BMIz is set to 8.21, a value that is slightly greater than the largest value that can be calculated.

See the README.md file for descriptions of the output columns generated by this function.

data must have columns for at least age, sex, weight, height, and bmi.

age should be coded in months, using the most precise values available. To convert to months from age in years, multiply by 12. To convert to months from age in days, divide by 30.4375 (365.25 / 12).

sex is coded as 1, boys, Boys, b, B, males, Males, m, or M for male subjects or 2, girls, Girls, g, G, females, Females, f, or F for female subjects. Note that this is different from cleangrowth, which uses 0 (Male) and 1 (Female).

wt should be in kilograms.

ht should be in centimeters.

Specify the input data parameter names for age, wt, ht, bmi using quotation marks. See example below.

If the parameter adjust.integer.age is TRUE (the default), 0.5 will be added to all age if all input values are integers. Set to FALSE to disable.

By default, the reference data file CDCref_d.csv, made available at https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm, is included in this package for convenience. If you are developing this package, use ref.data.path to adjust the path to this file from your working directory if necessary.

Examples

# \donttest{
# Run on a small subset of given data
df <- as.data.frame(syngrowth)
df <- df[df$subjid %in% unique(df[, "subjid"])[1:5], ]
df <- cbind(df,
            "gcr_result" = cleangrowth(df$subjid,
                                       df$param,
                                       df$agedays,
                                       df$sex,
                                       df$measurement))
df_wide <- longwide(df) # convert to wide format for ext_bmiz
df_wide_bmi <- simple_bmi(df_wide) # compute simple BMI

# Calling the function with default column names
df_bmiz <- ext_bmiz(df_wide_bmi)

# Specifying different column names; note that quotes are used
dfc <- simple_bmi(df_wide)
colnames(dfc)[colnames(dfc) %in% c("agem", "wt", "ht")] <-
  c("agemos", "weightkg", "heightcm")
df_bmiz <- ext_bmiz(dfc, age="agemos", wt="weightkg", ht="heightcm")

# Disabling conversion of all-integer age in months to (age + 0.5)
dfc <- simple_bmi(df_wide)
df_bmiz <- ext_bmiz(dfc, adjust.integer.age=FALSE)
# }