computePredimed: computePredimed

In MedDietScore: Scores of Adherence to Mediterranean Diet and Other Tools for Nutriepidemiological Research

Description

Computes the Mediterranean Diet adherence score used in PreDiMed trial (Prevencion con Dieta Mediterranea, Spanish which means Prevention with Mediterranean Diet)

Usage

computePredimed(data, OliveOil, OOmeasure = "gr", OOprincipal,
                Vegetables, Fruit, RedMeat, Butter, SoftDrinks,
                Wine, Legumes, Fish, Pastries, Nuts, WhiteMeat,
                Sofritos, output = "percent", rm.na = FALSE, frequency = NULL)

Arguments

data	Your data set with nutritional information about food or nutrient consumption. Each row is expected to be a person, and food or nutrient intake are in columns.
OliveOil	Numeric with olive oil consumption. Units are set with the argument 'OOmeasure'.
OOmeasure	Character string which informs about the unit of the argument 'OliveOil'. Allowed values are 'gr', 'ml' and 'serving', which means respectively grams, mililiters and servings of 1 table spoon (10 ml).
OOprincipal	Integer. This item scores wether olive oil is the main dietary fat as a dichotomous variable (1-yes, 0-no).
Vegetables	Numeric. Vegetables consumption measured as servings.
Fruit	Numeric. Fruit consumption measured as servings.
RedMeat	Numeric. RedMeat consumption measured as servings.
Butter	Numeric. Butter consumption measured as servings.
SoftDrinks	Numeric. SoftDrinks consumption measured as servings.
Wine	Numeric. Wine consumption measured as servings (glasses).
Legumes	Numeric. Legumes consumption measured as servings.
Fish	Numeric. Fish consumption measured as servings.
Pastries	Numeric. Pastries consumption measured as servings.
Nuts	Numeric. Nuts consumption measured as servings.
WhiteMeat	Integer. This item scores wether wite meats are preferred over red meats. So it is a dichotomous variable (1-yes, 0-no).
Sofritos	Numeric. Number of times 'sofrito' is consumed (see Details).
output	A character string to set which output should the formula give, allowed values are 'data.frame', 'score' and 'percent' (default).
rm.na	Logical. If set to FALSE (default), a diet score will be computed only if a person has all score components informed. If set to TRUE, NA values in score components will be drop off and a value of available components will be returned, but percent of score adherence will be computed with basis of the whole score range (see Details)
frequency	A character string. Allowed values are 'daily', 'weekly' and 'monthly'. It informs about the frequency which food or nutrient consumption refers to (i.e. wether the rest of arguments are 'grams per day' or 'grams per week' or 'grams per month')

Details

This score was used in the landmark PreDiMed trial (Prevencion con Dieta Mediterranea, Spanish which means Prevention with Mediterranean Diet) (Estruch et al. 2013). It can also be found under the name MEDAS (MEditerranean Diet Adherence Screener) (Schroder et al. 2011)

Please note that olive oil is in thtree items: one measuring the amount of servings, other measuring if it is the main dietary fat, and another asking about 'sofrito' consumption. Supplementary material of Estruch et al. 2013 informs that one tablespoon is 10ml.

'Sofrito' is a special way to cook, a sauce made with tomato and onion, leek, or garlic, simmered with olive oil.

Value

Computed Predimed score. Depending on 'output' argument, value can be a data.frame, or a vector:

if output = 'data.frame'	A data frame with a row corresponding to each person in data. Columns are the score of each component, as well as the global score as natural sum ('absolute' column) and as percentage ('percent' column)
if output = 'score'	Instead of the full data.frame, just the integer vector corresponding to the absolute points of adherence to Mediterranean Diet for each person, from 0 (min.) to 9 (max.)
if output = 'percent'	Instead of the full data.frame, just the numeric vector corresponding to the percent of adherence to Mediterranean Diet for each person, from 0 (min. adherence) to 100 percent (max. adhrence)

Author(s)

Miguel Menendez

References

Estruch, Ramon, Emilio Ros, Jordi Salas-Salvado, Maria-Isabel Covas, Dolores Corella, Fernando Aros, Enrique Gomez-Gracia, et al. 2013. "Primary Prevention of Cardiovascular Disease with a Mediterranean Diet." New England Journal of Medicine 368 (14): 1279-90. doi:10.1056/NEJMoa1200303. (Supplementary material available at http://www.nejm.org/action/showSupplements?doi=10.1056

Martinez-Gonzalez, Miguel Angel, Dolores Corella, Jordi Salas-Salvado, Emilio Ros, Maria Isabel Covas, Miquel Fiol, Julia Warnberg, et al. 2012. "Cohort Profile: Design and Methods of the PREDIMED Study." International Journal of Epidemiology 41 (2): 377-385. http://ije.oxfordjournals.org/content/41/2/377.short.

Schroder, Helmut, Montserrat Fito, Ramon Estruch, Miguel A. Martinez-Gonzalez, Dolores Corella, Jordi Salas-Salvado, Rosa Lamuela-Raventos, et al. 2011. 'A Short Screener Is Valid for Assessing Mediterranean Diet Adherence among Older Spanish Men and Women'. The Journal of Nutrition 141 (6): 1140-45. doi:10.3945/jn.110.135566.

Examples

data(nutriSample)
MedDiet <- computePredimed(data = nutriSample, OliveOil = Aceitegr, OOmeasure = "gr",
                  OOprincipal = ifelse(nutriSample$AceiteTipo == 1, 1, 0),
                  Vegetables = P41rac + P42rac,
                  Fruit = P50rac + P52rac,
                  RedMeat = P29rac + P31rac,
                  Butter = P79rac,
                  SoftDrinks = P89rac + P90rac,
                  Wine = P96rac,
                  Legumes = P46rac,
                  Fish = P35rac + P36rac + P37rac + P38rac,
                  Pastries = P69rac + P70rac + P71rac + P72rac + P73rac,
                  Nuts = P53rac,
                  WhiteMeat = ifelse(nutriSample$P30rac > nutriSample$P29rac, 1, 0),
                  Sofritos = rep(0, nrow(data)), # data lacks this variable, so we go on without it
                  output = "percent", rm.na = FALSE, frequency = "daily")
hist(MedDiet)

MedDietScore documentation built on April 3, 2017, 4:01 p.m.