Categorise length/height-for-age z-scores into stunting strata

Usage

categorise_stunting(lhaz, outliers = FALSE)

Arguments

lhaz: A numeric vector of length one or more containing length/height-for-age z-scores (LHAZs).
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 the longest input vector, containing stunting classifications. Its levels are c("stunting_severe", "stunting", "not_stunting") if outliers = FALSE (the default), else c("stunting_severe", "stunting", "not_stunting", "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 stunting categories are:

Category	Factor level	Z-score bounds
Severe stunting	`"stunting_severe"`	`lhaz` =< -3
Stunting	`"stunting"`	-3 < `lhaz` =< -2
No stunting	`"not_stunting"`	`lhaz` > -2
Outlier	`"outlier"`	`abs(lhaz)` > 6

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

lhaz <- c(-6.5, -5, -3, 0, 3, 5, 6.5)
categorise_stunting(lhaz, outliers = FALSE)
#> ! Unused factor levels kept after stunting categorisation: "stunting".
#> [1] stunting_severe stunting_severe stunting_severe not_stunting   
#> [5] not_stunting    not_stunting    not_stunting   
#> Levels: stunting_severe stunting not_stunting
categorise_stunting(lhaz, outliers = TRUE)
#> ! Unused factor levels kept after stunting categorisation: "stunting".
#> [1] outlier         stunting_severe stunting_severe not_stunting   
#> [5] not_stunting    not_stunting    outlier        
#> Levels: stunting_severe stunting not_stunting outlier