Difference between revisions of "Food intake in Finland"

library(OpasnetUtils)
library(ggplot2)

objects.get("84Sg6BQDs7potVJr")

#oprint(head(foodFI))

fishlong <- c(
	"Atlantic salmon (Salmo salar)",
	"Baltic herring (Clupea harengus membras)",
	"Fish and other seafood(by species, these are examples - variation by country):",
	"Herring (Clupea harengus)",
	"Pike (Esox lucius)",
	"Rainbow trout (Onchorchys mykiss)" 
)

fishshort <- c(
	"Atlantic salmon",
	"Baltic herring", 
	"Fish and seafood", 
	"Herring", 
	"Pike", 
	"Rainbow trout"
)

# Why do we need to reorder the factor? It should be ordered already.

age =  c("6 mo", "7 mo", "8 mo", "9 mo", "7-11 mo", "10 mo", "11 mo", "1", "2", "3", "4-5", "6-9", "10-13", "14-17", 
	"18-24", "25-34", "35-44", "45-54", "55-64", "65-74")
foodFI$Age <- factor(foodFI$Age, age, ordered = TRUE)

#levels(foodFI$Food)[levels(foodFI$Food) %in% fishlong]
levels(foodFI$Food)[levels(foodFI$Food) %in% fishlong] <- fishshort

cat("Fish intake data based on results from Beneris project (child data mainly from DIPP study.)\n")

#head(foodFI[foodFI$Food %in% fishshort , ])

ggplot(foodFI[foodFI$Parameter == "Fractile0.5" & foodFI$Food == fishshort , ], aes(x = Age, y = Result)) + #
	geom_point(aes(colour = Food)) + 
	theme_grey(base_size = 24) +
	theme(axis.text.x = element_text(angle = 90, hjust = 1))

library(OpasnetUtils)
library(reshape2)
library(ggplot2)

importFoodTables <- function(
	dat = table, # Data sheet from Excel or elsewhere
	cols = c("mean", "SD", "Fractile0.05", "Fractile0.25", "Fractile0.5", "Fractile0.75", "Fractile0.95", "Userfraction"),
	sheet = "General population",
	obs, 
	sex = c("Male", "Female"),
	block, 
	age
) {
	out <- data.frame()
	for(i in 1:length(obs)) {	
		for(j in 1:length(block)) {
			temp <- dat[obs[[i]], block[[j]]]
			colnames(temp) <- cols
			temp <- data.frame(Population = sheet, Sex = sex[[i]], Age = age[[j]], Food  = dat[obs[[i]], 1], temp)
			temp[["Userfraction"]] <- as.numeric(gsub("%", "", temp[["Userfraction"]])) / 100
			temp <-  melt(temp, measure.vars = cols, variable.name = "Parameter", value.name = "Result")
			out <- rbind(out, temp)
		}
	}
	out$Result <- as.numeric(out$Result)
	out$Age <- factor(out$Age, age, ordered = TRUE)
	return(out)
}

# Food consumption FINLAND.xls / Main food categories. http://en.opasnet.org/en-opwiki/index.php/Special:R-tools?id=7YsAYvWNMy7wRqIR

objects.get("7YsAYvWNMy7wRqIR")

fooddata1 <- importFoodTables(
	obs = list(c(5:22, 25:33, 35:37), c(40:57, 60:68, 70:72)),
	block =  list(10:17, 26:33, 42:49, 74:81, 82:89, 90:97, 98:105),
	age =  c("1", "3", "6", "25-34", "35-44", "45-54", "55-64")
)

# Food consumption FINLAND.xls / Fish categories. http://en.opasnet.org/en-opwiki/index.php/Special:R-tools?id=E03tfupLAj1MNRur

objects.get("E03tfupLAj1MNRur")

fooddata2 <- importFoodTables(
	obs = list(4:16, 19:31),
	block =  list(3:10, 12:19, 21:28, 30:37, 39:46, 48:55, 57:64, c(65, 65:71), 73:80, 82:89, 91:98, 100:107, 109:116, 
	118:125, 127:134, 136:143, 151:158, 160:167, 169:176, 178:185),
	age =  c("6 mo", "7 mo", "8 mo", "9 mo", "10 mo", "11 mo", "1", "7-11 mo", "2", "3", "4-5", "6-9", "10-13", "14-17", 
	"18-24", "25-34", "35-44", "45-54", "55-64", "65-74")
)

foodFI <- rbind(fooddata1, fooddata2)

oprint(head(foodFI))

temp <- fooddata2
temp <- temp[temp$Parameter == "Fractile0.5" & 
	temp$Food %in% c(
		"Fish and other seafood(by species, these are examples - variation by country):", 
		"Baltic herring (Clupea harengus membras)", 
		"Herring (Clupea harengus)", 
		"Pike (Esox lucius)", 
		"Rainbow trout (Onchorchys mykiss)", 
		"Atlantic salmon (Salmo salar)"
	) , ]

oprint(head(temp))
ggplot(temp, aes(x = Age, y = Result)) + geom_point(aes(colour = Food)) + theme_grey(base_size = 24)

objects.put(foodFI)

cat("Object foodFI saved.\n")