In nutriverse/zscorer: Child Anthropometry z-Score Calculator

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

if(!require(zscorer)) install.packages("zscorer")

Calculating anthropometric z-scores using `zscorer`

The main function in the zscorer package is addWGSR().

To demonstrate its usage, we will use the accompanying dataset in zscorer called anthro3. We inspect the dataset as follows:

head(anthro3)

which returns:

head(anthro3)

anthro3 contains anthropometric data from a Rapid Assessment Method (RAM) survey from Burundi.

Anthropometric indices (e.g. weight-for-height z-scores) have not been calculated and added to the data.

We will use the addWGSR() function to add weight-for-height (wfh) z-scores to the example data:

svy <- addWGSR(data = anthro3, sex = "sex", firstPart = "weight",
               secondPart = "height", index = "wfh")

A new column named wfhz has been added to the dataset:

head(svy)

The wfhz column contains the weight-for-height (wfh) z-scores calculated from the sex, weight, and height columns in the anthro3 dataset. The calculated z-scores are rounded to two decimals places unless the digits option is used to specify a different precision (run ?addWGSR to see description of various parameters that can be specified in the addWGSR() function).

The addWGSR() function takes up to nine parameters to calculate each index separately, depending on the index required. These are described in the Help files of the zscorer package which can be accessed as follows:

?addWGSR

The standing parameter specifies how “stature” (i.e. length or height) was measured. If this is not specified, and in some special circumstances, height and age rules will be applied when calculating z-scores. These rules are described in the table below.

The addWGSR() function will not produce error messages unless there is something very wrong with the data or the specified parameters. If an error is encountered in a record then the value NA is returned. Error conditions are listed in the table below.

+--------------------------------------------------+----------------------------------------+ | Error condition | Action | +==================================================+========================================+ | Missing or nonsense value in standing parameter| Set standing to 3 (unknown) and | | | apply appropriate height or age rules. | +--------------------------------------------------+----------------------------------------+ | Unknown index specified | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | Missing sex | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | Missing firstPart | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | Missing secondPart | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | sex is not male (1) or female (2) | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | firstPart is not numeric | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | secondPart is not numeric | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | Missing thirdPart when index = "bfa" | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | thirdPart is not numeric when index = "bfa" | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+ | secondPart is out of range for specified index | Return NA for z-score. | +--------------------------------------------------+----------------------------------------+

We can see this error behaviour using the example data:

table(is.na(svy$wfhz))

We can display the problem record:

svy[is.na(svy$wfhz), ]

The problem is due to the value 9 in the sex column, which should be coded 1 (for male) and 2 (for female). Z-scores are only calculated for records with sex specified as either 1 (male) or 2 (female). All other values, including NA, will return NA.

The addWGSR() function requires that data are recorded using the required units or required codes (see Table Z1).

The addWGSR() function will return incorrect values if the data are not recorded using the required units. For example, this attempt to add weight-for-age z-scores to the example data:

svy <- addWGSR(data = svy, sex = "sex", firstPart = "weight", 
               secondPart = "age", index = "wfa")

will give incorrect results:

summary(svy$wfaz)

The odd range of values is due to age being recorded in months rather than days.

It is simple to convert all ages from months to days:

svy$age <- svy$age * (365.25 / 12)
head(svy)

before calculating and adding weight-for-age z-scores:

svy <- addWGSR(data = svy, sex = "sex", firstPart = "weight", 
               secondPart = "age", index = "wfa")
head(svy)
summary(svy$wfaz)

The muac column in the example dataset is recorded in millimetres (mm). We need to convert this to centimetres (cm):

svy$muac <- svy$muac / 10
head(svy)

before using the addWGS() function to calculate MUAC-for-age z-scores:

svy <- addWGSR(svy, sex = "sex", firstPart = "muac",    
               secondPart = "age", index = "mfa")
head(svy)

As a last example we will use the addWGSR() function to add body mass index-for-age (bfa) z-scores to the data to create a new variable called bmiAgeZ with a precision of 4 decimal places as:

svy <- addWGSR(data = svy, sex = "sex", firstPart = "weight", 
               secondPart = "height", thirdPart = "age", index = "bfa", 
               output = "bmiAgeZ", digits = 4)
head(svy)

Calculating z-scores using the legacy functions

The zscorer package comes with the original legacy functions included in its version 0.1.0. These functions allow for the calculation of weight-for-age, height-for-age and weight-for-height z-scores for individual children and for a cohort of children.

Calculating z-score for each of the three anthropometric indices for a single child

For this example, we will use the getWGS() function and apply it to dummy data of a 52 month old male child with a weight of 14.6 kg and a height of 98.0 cm.

# weight-for-age z-score
waz <- getWGS(sexObserved = 1,     # 1 = Male / 2 = Female
              firstPart = 14.6,    # Weight in kilograms up to 1 decimal place
              secondPart = 52,     # Age in whole months
              index = "wfa")       # Anthropometric index (weight-for-age)

waz

# height-for-age z-score
haz <- getWGS(sexObserved = 1,
              firstPart = 98,      # Height in centimetres
              secondPart = 52,
              index = "hfa")       # Anthropometric index (height-for-age)

haz

# weight-for-height z-score
whz <- getWGS(sexObserved = 1,
              firstPart = 14.6,
              secondPart = 98,
              index = "wfh")       # Anthropometric index (weight-for-height)

whz

Applying the getWGS() function results in a calculated z-score for one child.

Calculating z-score for each of the three anthropometric indices for a cohort or sample of children

For this example, we will use the getCohortWGS() function and apply it to sample data anthro1 that came with zscorer.

# Make a call for the anthro1 dataset
anthro1

As you will see, this dataset has the 4 variables you will need to use with getCohortWGS() to calculate the z-score for the corresponding anthropometric index. These are age, sex, weight and height.

library(zscorer)

head(anthro1)

To calculate the three anthropometric indices for all the children in the sample, we execute the following commands in R:

# weight-for-age z-score
waz <- getCohortWGS(data = anthro1,
                    sexObserved = "sex",
                    firstPart = "weight",
                    secondPart = "age",
                    index = "wfa")
head(waz, 50)

# height-for-age z-score
haz <- getCohortWGS(data = anthro1,
                    sexObserved = "sex",
                    firstPart = "height",
                    secondPart = "age",
                    index = "hfa")
head(haz, 50)

# weight-for-height z-score
whz <- getCohortWGS(data = anthro1,
                    sexObserved = "sex",
                    firstPart = "weight",
                    secondPart = "height",
                    index = "wfh")
head(whz, 50)

Applying the getCohortWGS() function results in a vector of calculated z-scores for all children in the cohort or sample.

Calculating z-scores for all of the three anthropometric indices in one function

For this example, we will use the getAllWGS() function and apply it to sample data anthro1 that came with zscorer.

# weight-for-age z-score
zScores <- getAllWGS(data = anthro1,
                     sex = "sex",
                     weight = "weight",
                     height = "height",
                     age = "age",
                     index = "all")
head(zScores, 20)

Applying the getAllWGS() function results in a data frame of calculated z-scores for all children in the cohort or sample for all the anthropometric indices.

nutriverse/zscorer documentation built on Dec. 28, 2020, 10:32 p.m.

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nutriverse/zscorer
Child Anthropometry z-Score Calculator

In nutriverse/zscorer: Child Anthropometry z-Score Calculator

Calculating anthropometric z-scores using `zscorer`

Calculating z-scores using the legacy functions

Calculating z-score for each of the three anthropometric indices for a single child

Calculating z-score for each of the three anthropometric indices for a cohort or sample of children

Calculating z-scores for all of the three anthropometric indices in one function

R Package Documentation

Browse R Packages

We want your feedback!

nutriverse/zscorer Child Anthropometry z-Score Calculator

In nutriverse/zscorer: Child Anthropometry z-Score Calculator

Calculating anthropometric z-scores using zscorer

Calculating z-scores using the legacy functions

Calculating z-score for each of the three anthropometric indices for a single child

Calculating z-score for each of the three anthropometric indices for a cohort or sample of children

Calculating z-scores for all of the three anthropometric indices in one function

R Package Documentation

Browse R Packages

We want your feedback!

nutriverse/zscorer
Child Anthropometry z-Score Calculator

Calculating anthropometric z-scores using `zscorer`