age_groups {AMR}

Split Ages into Age Groups

Description

Split ages into age groups defined by the split argument. This allows for easier demographic (antimicrobial resistance) analysis.

Usage

age_groups(x, split_at = c(12, 25, 55, 75), na.rm = FALSE)

Arguments

x

age, e.g. calculated with age()

split_at

values to split x at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See Details.

na.rm

a logical to indicate whether missing values should be removed

Details

To split ages, the input for the split_at argument can be:

• A numeric vector. A value of e.g. c(10, 20) will split x on 0-9, 10-19 and 20+. A value of only 50 will split x on 0-49 and 50+. The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).

• A character:

  • "children" or "kids", equivalent of: c(0, 1, 2, 4, 6, 13, 18). This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.

  • "elderly" or "seniors", equivalent of: c(65, 75, 85). This will split on 0-64, 65-74, 75-84, 85+.

  • "fives", equivalent of: 1:20 * 5. This will split on 0-4, 5-9, ..., 95-99, 100+.

  • "tens", equivalent of: 1:10 * 10. This will split on 0-9, 10-19, ..., 90-99, 100+.

Value

Ordered factor

See Also

To determine ages, based on one or more reference dates, use the age() function.

Examples

ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)

# split into 0-49 and 50+
age_groups(ages, 50)

# split into 0-19, 20-49 and 50+
age_groups(ages, c(20, 50))

# split into groups of ten years
age_groups(ages, 1:10 * 10)
age_groups(ages, split_at = "tens")

# split into groups of five years
age_groups(ages, 1:20 * 5)
age_groups(ages, split_at = "fives")

# split specifically for children
age_groups(ages, c(1, 2, 4, 6, 13, 18))
age_groups(ages, "children")


# resistance of ciprofloxacin per age group
if (require("dplyr") && require("ggplot2")) {
  example_isolates %>%
    filter_first_isolate() %>%
    filter(mo == as.mo("Escherichia coli")) %>%
    group_by(age_group = age_groups(age)) %>%
    select(age_group, CIP) %>%
    ggplot_sir(
      x = "age_group",
      minimum = 0,
      x.title = "Age Group",
      title = "Ciprofloxacin resistance per age group"
    )
}