A function used to calculate standardized Energy values in kcal

Development on 'ENERCKcal_standardised()' is completed, and has been superceeded by 'ENERCKcal_calculator()'. It is recommended to switch to 'ENERCKcal_calculator()'.

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 kcal. Alcohol is optional, whereas the other inputs are required - if Alcohol is missing it is assumed to be 0.

Usage

ENERCKcal_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 kcal.

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

#alternatively:

standardised_kcal <- ENERCKcal_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$ENERCKcal_stnd <- ENERCKcal_standardised(
         test_df_WAFCT2019$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
#>   ENERCKcal_stnd
#> 1          249.5
#> 2           41.2
#> 3          350.5
#> 4          115.8
#> 5          141.7