Description Usage Arguments Value References See Also Examples
Generates mid upper arm circumference (MUAC) for age z-scores and percentiles based on LMS-method for children and adolescents aged 3 months to 19 years.
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Datafm |
A DataFrame with variables including pid (unique subject identification), age (in months), sex (1, 2 or "Male", "Female"), muac (numeric: in cm). |
age_range |
age range in months. Input has to be characters. Options allowed are: "3-60" which is the default, or "60-228" |
digits.zscore |
The number of digits for z-score variable |
digits.perc |
The number of digits for percentile variable |
Notes |
Is FALSE by default. If set to TRUE, 'notes' will be printed on the console about the nature, range of variables allowed and number of records processed. |
A DataFrame with MUAC z scores for age and percentiles.
Mramba L., Ngari M., Mwangome M., Muchai L., Bauni E., Walker A.S., Gibb D.M., Fegan G. and Berkley J.A. (2017) A growth reference for mid upper arm circumference for age among school age children and adolescents, and validation for mortality: growth curve construction and longitudinal cohort study BMJ 2017;358:j3423 <doi:10.1136/bmj.j3423>
<https://www.bmj.com/content/358/bmj.j3423>
<https://www.bmj.com/content/358/bmj.j3423/related#datasupp>
<https://www.who.int/childgrowth/standards/Technical_report.pdf>
<https://www.who.int/childgrowth/standards/ac_for_age/en/>
indivmuaczs
, bmizs
, muacz.bmiz
, plotmuac
and plotbmi
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ## Example 1: younger age range is the default: 3 months - 5 years
# Creating a hypothetical dataset
dat1 <- data.frame(age = c(3, 5, 12, 18, 23, 24, 36, 48, 60, 24, 36, 48, 60),
sex = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2),
muac = c(15.6, 14.1, 15.8, 18.7, 12.9, 13,
14.5, 16.1, 21.7, 12.7, 14.4, 16.2, 22.5))
# Run the function
ans1 <- muaczs(Datafm = dat1) # save the output
# ans1
## Example 2: For children 5-19 years old, specify their age range "61-228"
# Creating a hypothetical dataset
dat1 <- data.frame(age = c(60, 65, 90, 120, 220),
sex = c("Male","Female","Male","Male","Female"),
muac = c(20, 14.3, 15.4, 17.8, 25.1))
ans1 <- muaczs(Datafm = dat1, age_range = "60-228")
# ans1
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