Calculate Food Consumption Score (FCS)
Arguments
- df
A data.frame with FCS data.
- var_map
A named list of FCS food groups mapped to corresponding variable names in
df. This can be produced usingfcs_fg_map_variables().- weights
A numeric vector of FCS weights applied to corresponding food groups. The weights should be ordered as that for staples, pulses, vegetables, fruits, meat and fish, dairy, sugar, oil, and condiments. Default to NULL which uses the weights based on current FCS recommendations. Only change this if new recommendations have been provided or for testing/studying new/experimental FCS weighting systems.
- add
Logical. Should the resulting FCS scores be added to
df? Default to TRUE.
Value
If add = TRUE, a data.frame based on df with a new variable
named fcs for the calculated food consumption scores. Otherwise, a
numeric vector of the calculated food consumption scores.
Examples
var_map <- fcs_fg_map_variables(
staples = "FCSStap",
pulses = "FCSPulse",
vegetables = "FCSVeg",
fruits = "FCSFruit",
meatfish = "FCSPr",
milk = "FCSDairy",
sugar = "FCSSugar",
oil = "FCSFat",
condiment = "FCSCond"
)
fcs_calculate(df = fcs01, var_map = var_map)
#> FCSStap FCSPulse FCSVeg FCSFruit FCSPr FCSDairy FCSSugar FCSFat FCSCond fcs
#> 1 7 4 5 3 2 1 6 0 2 49.0
#> 2 1 2 2 3 1 5 4 2 6 40.0
#> 3 7 4 4 2 2 1 2 0 7 45.0
#> 4 2 5 4 7 7 0 5 0 0 60.5
#> 5 1 1 1 3 0 4 7 5 0 31.0
#> 6 2 1 2 3 5 4 4 7 0 53.5
#> 7 3 0 4 6 2 2 0 0 2 32.0
#> 8 6 4 1 2 3 2 0 4 0 49.0
#> 9 5 0 1 2 0 4 3 6 4 33.5
#> 10 3 6 1 2 1 5 4 4 0 55.0
#> 11 4 0 4 5 7 3 6 1 5 60.5
#> 12 0 0 7 7 5 5 7 5 1 60.0
#> 13 1 3 4 6 7 6 1 7 1 77.0
#> 14 0 3 5 3 0 4 4 5 4 37.5
#> 15 4 5 5 7 5 3 7 0 2 70.5
#> 16 0 5 4 6 1 6 1 1 5 54.0
#> 17 3 6 6 7 7 3 6 0 1 80.0
#> 18 0 6 3 1 3 0 3 6 2 38.5
#> 19 0 3 3 5 3 0 5 7 1 35.0
#> 20 4 5 2 7 5 3 4 7 7 69.5
#> 21 3 6 6 3 5 3 6 0 4 68.0
#> 22 3 6 5 4 1 7 6 5 0 70.5
#> 23 1 2 3 1 3 6 2 3 1 50.5
#> 24 6 2 3 1 5 1 6 7 5 52.5
#> 25 0 0 0 0 0 0 0 0 0 0.0
#> 26 1 1 1 1 1 1 1 1 1 16.0