Prepare the disease specific functions that describe how a change in alcohol consumption gradually has an effect on the relative risk of disease incidence over time (up to 20 years) since alcohol consumption changed.

AlcLags(disease_name = c("Pharynx", "Oral_cavity"), n_years = 20)

Arguments

disease_name

Character - the name of the disease under consideration.

n_years

Integer - the number of years from 1 to n over which the effect of a change in consumption emerges. Defaults to 20 years to fit with the current lag data.

Value

Returns a data table with two columns - one for the years since consumption changed, and the other that gives the proportion by which the effect of a change in consumption on an individual's relative risk of disease has so far emerged.

Details

All lag times are taken from the review by Holmes et al. (2012) , and are the numbers used in the current version of SAPM.

References

Holmes J, Meier PS, Booth A, Guo Y, Brennan A (2012). “The temporal relationship between per capita alcohol consumption and harm: a systematic review of time lag specifications in aggregate time series analyses.” Drug and alcohol dependence, 123(1-3), 7--14.

Examples

if (FALSE) {
AlcLags("Pharynx")
}