Categorise weight-for-length/height z-scores into wasting strata

Usage

categorise_wasting(wlz, outliers = FALSE)

Arguments

wlz: A numeric vector of length one or more containing weight-for-length/height z-scores (WLZs).
outliers: A single TRUE or FALSE value specifying whether implausible z-score thresholds should be applied. Default = FALSE.

Value

An object of class factor with the same length as wlz, containing wasting classifications. Its levels are c("wasting_severe", "wasting", "not_wasting", "overweight") if outliers = FALSE (the default), else c("wasting_severe", "wasting", "not_wasting", "overweight", "outlier"). By default, gigs will inform you this object contains unused factor levels. You can change this behaviour using the GIGS package-level option .gigs_options$handle_unused_levels.

Details

Cut-offs for wasting categories are:

Category	Factor level	Z-score bounds
Severe wasting	`"wasting_severe"`	`wlz` =< -3
Wasting	`"wasting"`	-3 < `wlz` =< -2
No wasting	`"not_wasting"`	`abs(wlz)` < 2
Overweight	`"overweight"`	`wlz` >= 2
Outlier	`"outlier"`	`abs(wlz)` > 5

Note

This function assumes that your measurements were taken according to WHO guidelines, which stipulate that recumbent length should not be measured after 730 days. Instead, standing height should be used. Implausible z-score bounds are sourced from the referenced WHO report, and classification cut-offs from the DHS manual.

References

'Implausible z-score values' in World Health Organization (ed.) Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old. Geneva: World Health Organization and the United Nations Children's Fund UNICEF, (2019). pp. 64-65.

'Percentage of children stunted, wasted, and underweight, and mean z-scores for stunting, wasting and underweight' in Guide to DHS Statistics DHS-7 Rockville, Maryland, USA: ICF (2020). pp. 431-435. https://dhsprogram.com/data/Guide-to-DHS-Statistics/Nutritional_Status.htm

Examples

wlz <- c(-5.5, -3, 0, 3, 5.5)
categorise_wasting(wlz, outliers = FALSE)
#> ! Unused factor levels kept after wasting categorisation: "wasting".
#> [1] wasting_severe wasting_severe not_wasting    overweight     overweight    
#> Levels: wasting_severe wasting not_wasting overweight
categorise_wasting(wlz, outliers = TRUE)
#> ! Unused factor levels kept after wasting categorisation: "wasting".
#> [1] outlier        wasting_severe not_wasting    overweight     outlier       
#> Levels: wasting_severe wasting not_wasting overweight outlier