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A dataset containing the number of deaths due to 9 causes in 6 regions for 2019.

Usage

data(deaths2019)

Format

A dataframe with 2754 rows and 7 variables:

The variables are as follows:

location

character, France, Germany, Global, Italy, United Kingdom, United States of America

sex

character, Female, Male, Both

age

character, age groups from <1 to 85+ each 5 years

cause

character, Alzheimer's disease and other dementias, Breast cancer, Chronic obstructive pulmonary disease, Colon and rectum cancer, Diabetes and kidney diseases, Lower respiratory infections, Road injuries, Stroke, Tracheal, bronchus, and lung cancer

val

numeric, deaths number estimation

upper

numeric, upper value estimation

lower

numeric, lower value estimation

Source

2019 data from the IHME website

Examples

data(deaths2019)
head(deaths2019)
#> # A tibble: 6 × 7
#>   location sex    age   cause                           dx upper  lower
#>   <chr>    <chr>  <ord> <chr>                        <dbl> <dbl>  <dbl>
#> 1 UK       male   <1    Lower respiratory infections 39.7  51.0  29.5  
#> 2 UK       female <1    Lower respiratory infections 30.0  38.0  22.6  
#> 3 UK       both   <1    Lower respiratory infections 69.7  88.3  53.3  
#> 4 UK       male   <1    Stroke                        1.33  2.41  0.850
#> 5 UK       female <1    Stroke                        1.04  1.84  0.669
#> 6 UK       both   <1    Stroke                        2.38  4.21  1.55