alc_weekmean_adult.RdWe estimate the number of UK standard units of alcohol drunk on average in a week from the questions on drinking in the last 12 months.
alc_weekmean_adult(
data,
abv_data = hseclean::abv_data,
volume_data = hseclean::alc_volume_data
)Data table - the health survey dataset
Data table - our assumptions on the alcohol content of different beverages in (percent units / ml)
Data table - our assumptions on the volume of different drinks (ml).
beer_units - average weekly units of beer
wine_units - average weekly units of wine
spirit_units - average weekly units of spirits
rtd_units - average weekly units of alcopops
weekmean - total average weekly units
perc_spirit_units - percentage of consumption that is spirits
perc_wine_units - percentage of consumption that is wine
perc_rtd_units - percentage of consumption that is alcopops
perc_beer_units - percentage of consumption that is beer
drinker_cat - categories of average weekly consumption
spirits_pref_cat - whether doesn't drink, drinks some or mostly drinks spirits
wine_pref_cat - whether doesn't drink, drinks some or mostly drinks wine
rtd_pref_cat - whether doesn't drink, drinks some or mostly drinks alcopops
beer_pref_cat - whether doesn't drink, drinks some or mostly drinks beer
The calculation has the following steps:
Convert the categorical variables to numeric variables for the frequency with which each beverage is typically consumed (normal beer, strong beer, spirits, sherry, wine, alcopops).
Convert the reported volumes usually consumed (e.g. small glass, large glass) into volumes in ml, using the beverage size assumptions above. In doing so, variations in recording among years and between the interview and self-complete questionnaire are accounted for.
Combine the volumes (ml) usually consumed with the frequency of consumption to give the average volume of each beverage type drunk each week (assuming constant consumption across the year).
Convert the expected volumes of each beverage consumed each week to UK standard units of alcohol consumed, using the alcohol content assumptions above.
Collapse normal and strong beer into a single "beer" variable by summing their units. Collapse wine and sherry into a single "wine" variable by summing their units.
Calculate total weekly units but summing across beverage categories.
Calculate the beverage "preference vector" - the percentage of total consumption contributed by the consumption of each of four beverage types (beer, wine, spirits, alcopops).
Cap the total units consumed in a week at 300 units, assuming that above this already very high level of consumption estimates of variation in consumption are less reliable.
Categorise average weekly consumption into "abstainer", "lower_risk" (less than 14 units/week), "increasing_risk" (greater than or equal to 14 units/week and less than 35 units/week for women, and less than 50 units/week for men), "higher_risk".
Categorise beverage preferences - for each of the four beverages, "does_not_drink", "drinks_some" (less than or equal to 50% of consumption), "mostly_drinks".
In 2007 new questions were added asking which glass size was used when wine was consumed. Therefore the post HSE 2007 unit calculations are not directly comparable to previous years' data.
if (FALSE) {
data <- read_2016()
data <- clean_age(data)
data <- clean_demographic(data)
data <- alc_drink_now(data)
data <- alc_sevenday(data)
data <- alc_weekmean(data)
}