A function used to calculate standardized Energy values in kJ — ENERCKj

This function works as a basic calculator - The values for Total Protein in grams 'PROTg', Total Fat in grams (ideally standardised) 'FATg_standardised', Available Carbohydrate in grams 'CHOAVLDFg', Fibre, Total Dietary in grams 'FIBTGg' and Alcohol in grams 'ALCg' are combined to fins the Energy in kj. Alcohol is optional, whereas the other inputs are required - if Alcohol is missing it is assumed to be 0.

Usage

ENERCKj_standardised(PROTg, FATg_standardised, CHOAVLDFg, FIBTGg, ALCg)

Arguments

PROTg: Required - The Total Protein value (in grams) for the food item being examined.
FATg_standardised: Required - The Total Fat value (in grams) for the food item being examined.
CHOAVLDFg: Required - The Total Available Carbohydrate value (in grams) for the food item being examined.
FIBTGg: Required - The Total Dietary Fibre value (in grams) for the food item being examined.
ALCg: Optional - The Total Alcohol value (in grams) for the food item being examined.

Value

The calculated Energy value in kJ.

Examples

#Three examples will be covered - two variants for a one-off
#calculation, and to create a column with the calculated results.

#Single calculation:

#Bread, wheat, white, unfortified

Protein_value <- 7.5
Fat_value <- 1.3
Carb_value <- 50.5
Fibre_value <- 2.9
Alcohol_value <- 0

standardised_kJ <- ENERCKj_standardised(PROT = Protein_value, FAT = Fat_value,
CHOAVLDF = Carb_value, FIBTG = Fibre_value, ALC = Alcohol_value)

#alternatively:

standardised_kJ <- ENERCKj_standardised(PROT = 7.5, FAT = 1.3,
CHOAVLDF = 50.5, FIBTG = 2.9, ALC = 0)

#data.frame calculation:

#First, an example dataframe is outlined and created -

test_df_WAFCT2019 <- data.frame(
c("Bread, wheat, white, unfortified",
"Beer, European (4.6% v/v alcohol)",
"Maize, yellow, meal, whole grains, unfortified",
"Sweet potato, yellow flesh, raw",
"Cassava, tuber, white flesh, raw"),
c(7.5, 0.3, 9.4, 1.5, 1.3),
c(1.3, 0, 3.7, 0.2, 0.3),
c(50.5, 3.7, 65.2, 25.5, 31.6),
c(2.9, 0, 9.4, 3, 3.7),
c(0, 3.6, 0, NA, 0))

#Then, the columns are renamed:

colnames(test_df_WAFCT2019) <- c("food_name", "protein", "fat", "carbs",
"fb", "alcohol")

#Once renamed, the function is applied. the assigned output is a new column
#in the data.frame, and the inputs are the different columns detailing the
#relevant food nutrient values.

test_df_WAFCT2019$ENERCKj_stnd <- ENERCKj_standardised(
         test_df_WAFCT2019$protein,
         test_df_WAFCT2019$fat,
         test_df_WAFCT2019$carbs,
         test_df_WAFCT2019$fb,
         test_df_WAFCT2019$alcohol)

print(test_df_WAFCT2019)
#>                                        food_name protein fat carbs  fb alcohol
#> 1               Bread, wheat, white, unfortified     7.5 1.3  50.5 2.9     0.0
#> 2              Beer, European (4.6% v/v alcohol)     0.3 0.0   3.7 0.0     3.6
#> 3 Maize, yellow, meal, whole grains, unfortified     9.4 3.7  65.2 9.4     0.0
#> 4                Sweet potato, yellow flesh, raw     1.5 0.2  25.5 3.0      NA
#> 5               Cassava, tuber, white flesh, raw     1.3 0.3  31.6 3.7     0.0
#>   ENERCKj_stnd
#> 1       1057.3
#> 2        172.4
#> 3       1480.3
#> 4        490.4
#> 5        600.0