Determine if a given observation in the data set is wasted or not, and its respective form of wasting (global, severe or moderate) on the basis of z-scores of weight-for-height (WFHZ), muac-for-age (MFAZ), raw MUAC values and combined case-definition.
Usage
define_wasting(
df,
zscores = NULL,
muac = NULL,
edema = NULL,
.by = c("zscores", "muac", "combined")
)Arguments
- df
A
tibbleobject. It must have been wrangled using this package's wrangling functions for WFHZ or MUAC, or both (for combined) as appropriate.- zscores
A vector of class
doubleof WFHZ or MFAZ values.- muac
An
integerorcharactervector of raw MUAC values in millimeters.- edema
A
charactervector indicating edema status. Default is NULL. Code values should be "y" for presence and "n" for absence of nutritional edema.- .by
A choice of the criterion by which a case is to be defined. Choose "zscores" for WFHZ or MFAZ, "muac" for raw MUAC and "combined" for combined. Default value is "zscores".
Value
The tibble object df with additional columns named named gam,
sam and mam, each of class numeric containing coded values of either
1 (case) and 0 (not a case). If .by = "combined", additional columns are
named cgam, csam and cmam.
Examples
## Case-definition by z-scores ----
z <- anthro.02 |>
define_wasting(
zscores = wfhz,
muac = NULL,
edema = edema,
.by = "zscores"
)
head(z)
#> # A tibble: 6 × 17
#> province strata cluster sex age weight height edema muac wtfactor wfhz
#> <chr> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
#> 1 Zambezia Rural 391 1 6.01 8.2 68 n 152 825. 0.349
#> 2 Zambezia Rural 404 2 6.01 7.1 65.1 n 139 287. -0.006
#> 3 Zambezia Rural 399 1 6.11 7.6 64.1 n 155 130. 0.9
#> 4 Zambezia Urban 430 2 6.14 7.9 65.9 n 148 1277. 0.876
#> 5 Zambezia Urban 468 2 6.28 6.6 59.7 n 132 792. 1.38
#> 6 Zambezia Urban 517 2 6.34 6 61.8 n 129 480. -0.583
#> # ℹ 6 more variables: flag_wfhz <dbl>, mfaz <dbl>, flag_mfaz <dbl>, gam <dbl>,
#> # sam <dbl>, mam <dbl>
## Case-definition by MUAC ----
m <- anthro.02 |>
define_wasting(
zscores = NULL,
muac = muac,
edema = edema,
.by = "muac"
)
head(m)
#> # A tibble: 6 × 17
#> province strata cluster sex age weight height edema muac wtfactor wfhz
#> <chr> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
#> 1 Zambezia Rural 391 1 6.01 8.2 68 n 152 825. 0.349
#> 2 Zambezia Rural 404 2 6.01 7.1 65.1 n 139 287. -0.006
#> 3 Zambezia Rural 399 1 6.11 7.6 64.1 n 155 130. 0.9
#> 4 Zambezia Urban 430 2 6.14 7.9 65.9 n 148 1277. 0.876
#> 5 Zambezia Urban 468 2 6.28 6.6 59.7 n 132 792. 1.38
#> 6 Zambezia Urban 517 2 6.34 6 61.8 n 129 480. -0.583
#> # ℹ 6 more variables: flag_wfhz <dbl>, mfaz <dbl>, flag_mfaz <dbl>, gam <dbl>,
#> # sam <dbl>, mam <dbl>
## Case-definition by combined ----
c <- anthro.02 |>
define_wasting(
zscores = wfhz,
muac = muac,
edema = edema,
.by = "combined"
)
head(c)
#> # A tibble: 6 × 17
#> province strata cluster sex age weight height edema muac wtfactor wfhz
#> <chr> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
#> 1 Zambezia Rural 391 1 6.01 8.2 68 n 152 825. 0.349
#> 2 Zambezia Rural 404 2 6.01 7.1 65.1 n 139 287. -0.006
#> 3 Zambezia Rural 399 1 6.11 7.6 64.1 n 155 130. 0.9
#> 4 Zambezia Urban 430 2 6.14 7.9 65.9 n 148 1277. 0.876
#> 5 Zambezia Urban 468 2 6.28 6.6 59.7 n 132 792. 1.38
#> 6 Zambezia Urban 517 2 6.34 6 61.8 n 129 480. -0.583
#> # ℹ 6 more variables: flag_wfhz <dbl>, mfaz <dbl>, flag_mfaz <dbl>, cgam <dbl>,
#> # csam <dbl>, cmam <dbl>