Package index • narcan

Overview

narcan narcan-package: narcan: tools for US multiple cause of death (MCOD) data

Import & download

Read raw fixed-width MCOD files and download source data.

import_mcod_fwf(): Import MCOD fixed-width data (restricted or public tier)
download_mcod_csv(): Download the multiple cause of death data as a CSV file
download_mcod_dta(): Download the multiple cause of death data as a DTA file
download_natality_ascii(): Download NCHS Natality (Live Births) Data from the CDC FTP (ASCII)
download_pop_data(): Download population data (processed asset or primary source)
mkdir_p(): Wrapper to make a directory (and subdirectories) if necessary

Clean & reshape records

Prepare imported records for flagging.

unite_records(): Unite the 20 record columns from MCOD dataframe into a single column
clean_icd9_data(): A wrapper function to perform basic cleaning of ICD-9 dataframes
zap_dta_data(): Clear Stata metadata from MCOD dta files
subset_residents(): Subset to US residents
prefix_to_record(): Add the prefix to appropriate ICD-9 record columns
prefix_e_to_ucod(): Add the external cause flag (E) to appropriate ICD-9 UCOD codes
pad_3char_codes(): Pad ICD-9 codes that do not have a sub-code (i.e., 3-character codes)
trim_5char_record(): Trim ICD-9 record columns that include the nature of injury flag
trim_trailing_whitespace(): Trim trailing whitespace on 3-char ICD-9 codes
rename_ni_flag(): Rename nature of injury columns for consistency

Flag & label deaths (ISW7)

Classify drug, opioid, intent, suicide, and maternal deaths.

flag_all_deaths(): Run the canonical MCOD flagging pipeline
flag_drug_deaths(): Flag drug deaths according to ISW7 rules
flag_heroin_present(): Creates a new column called heroin_present if opioid death involved heroin
flag_maternal_deaths(): Creates a new column called maternal_death with 1 if maternal death
flag_maternal_deaths_late(): Creates a new column called maternal_death with 1 if maternal death (late)
flag_methadone_present(): Creates a column `methadone_present` if opioid death involved methadone
flag_nonheroin(): Flag all opioid deaths that were not from heroin
flag_nonopioid_drug_deaths(): Flag non-opioid drug deaths according to ISW7 rules
flag_od_intent(): Flag overdose deaths by their UCOD intent code
flag_opioid_contributed(): Flag non-opioid deaths that involved opioids
flag_opioid_deaths(): Flag opioid deaths according to ISW7 rules
flag_opioid_types(): Take a processed MCOD dataframe and create indicators for opioid types
flag_opium_present(): Creates a column called `opium_present` if opioid death involved opium
flag_other_natural_present(): Creates a column `other_natural_present` if opioid death involved opium
flag_other_op_present(): Creates a column `other_op_present` for deaths with other unspecified opioid
flag_other_synth_present(): Creates a column called `other_synth_present`
flag_suicide_deaths(): Flag suicide deaths (no accidental poisoning)
flag_suicide_fall(): Flag suicide by fall
flag_suicide_firearm(): Flag suicide by firearm
flag_suicide_other(): Flag suicide by other (not poison, fall, firearm, suffocation)
flag_suicide_poison(): Flag suicide by poison
flag_suicide_suffocation(): Flag suicide by suffocation
flag_suicide_types(): Flag suicide five types: firearm, poisoning, fall, suffocation, or other
label_od_intent(): Label intent from underlying cause column for overdose drugs
label_suicide_type(): Create a new column with labels for suicide type

Recode demographics & geography

Year-aware race, sex, Hispanic origin, age, occupation, and FIPS recodes.

remap_race(): Remaps the race column to a standardized code across data years
categorize_race(): Create a categorical race column from a standardized race column
categorize_sex(): Categorize the NCHS sex field across coding eras
categorize_female(): Flag female deaths across coding eras
categorize_hspanicr(): Create a categorical Hispanic origin/race column from the hspanicr column
add_hspanicr_column(): Add an NA hspanicr column if one doesn't exist
categorize_hispanic_origin(): Collapse hspanicr to the binary Hispanic-origin axis (for population joins)
add_hispanic_origin(): Add a binary Hispanic-origin column from hspanicr
remap_age(): Remap the raw NCHS detail-age field to age in completed years
categorize_age_5(): Create a categorical age column from a converted ager27 column
categorize_age_5u1(): Create a categorical age column from a converted ager27 column
convert_ager27(): Converts the age27 variable in MCOD data to 5-year age groups
convert_ager27u1(): Converts the age27 variable in MCOD data to under-1, 1-4, then 5-year groups
add_county_fips(): Make a new county_fips column that is consistent across years
state_abbrev_to_fips(): Replace state abbreviations with their corresponding FIPS code
add_coded_occupation(): Add harmonized coded occupation and industry columns

Population & rates

Population denominators and (standardized) mortality rates.

get_pop_state(): Retrieve state-level population denominators
get_pop_county(): Retrieve county-level population denominators
pop_sources(): Print the bundled population-data provenance manifest
add_pop_counts(): Join population denominators to a death frame
add_std_pop(): Given a dataframe with age, returns a standard population
calc_asrate_var(): Calculate age-specific rates and variance
calc_stdrate_var(): Calculate age-standardized rates and variance
summarize_binary_columns(): Summarizes all flagged (e.g., 0/1) MCOD columns

Datasets

Bundled reference tables and crosswalks.

appalachia_fips: Dataframe of Appalachian counties with name and FIPS codes
cdc_dict: A dictionary of year:URL key:value pairs for the CDC FTP MCOD files
ihme_fips: Mapping original FIPS codes to temporally stable FIPS codes from IHME
live_births: Dataframe of live births in the US from 2003-2016 by race/ethnicity and age.
mcod_fwf_dicts: Fixed-width column dictionary for RESTRICTED-use MCOD files
mcod_public_fwf_dicts: Fixed-width column dictionary for PUBLIC-use MCOD files
pop_bridged: Bridged-race population estimates, national, 1969-2024
pop_est: Dataframe of annual population counts by age and race, 1979-2020
pop_singlerace: Single-race population estimates, national, 2020-2024
pop_singlerace_full: Single-race population estimates, national, 2000-2024 (backfill)
pop_singlerace_state: Single-race population estimates, state, 2020-2024
st_fips_map: Mapping of US state name to abbreviation to FIPS and NCHS code
std_pops: Dataframe of common standard populations from SEER website.