10  Race and Ethnicity

Each of the three datasets defines Race / Ethnicity differently. The California dataset uses numeric codes, the Los Angeles County dataset uses full text labels, and the population dataset uses abbreviated text.

To resolve this, we created a crosswalk file (race_ethnicity_map.csv) that aligns the three formats. By joining this crosswalk to each dataset, we ensure that all three contain a consistent set of race and ethnicity variables: each with the numeric code, the abbreviated text, and the full text label.

race_ethnicity_map <- read.csv(file = here("data/race_ethnicity_map.csv")) %>%
  mutate(
    race_long = clean(race_long),
    race_short = clean(race_short),
    race_coded = as.character(race_coded)
  )

step2_ca_df <- step2_ca_df %>%
  rename("race_coded" = "race_ethnicity") %>%
  mutate(race_coded = as.character(race_coded)) %>%
  left_join(race_ethnicity_map, by = "race_coded") %>%
  relocate(race_coded, race_short, race_long, .after = sex)

step2_la_cnty_df <- step2_la_cnty_df %>%
  mutate(race_long = clean(race_ethnicity)) %>%
  select(-race_ethnicity) %>%
  left_join(race_ethnicity_map, by = "race_long") %>%
  relocate(race_coded, race_short, race_long, .after = sex)

Race and Ethnicity Crosswalk Table:

race_coded	race_long	race_short
1	White, Non-Hispanic	White NH
2	Black, Non-Hispanic	Black NH
3	American Indian or Alaska Native, Non-Hispanic	AIAN NH
4	Asian, Non-Hispanic	Asian NH
5	Native Hawaiian or Pacific Islander, Non-Hispanic	NHPI NH
6	Multiracial (two or more of above races), Non-Hispanic	MR NH
7	Hispanic (any race)	Hispanic
9	Unknown	Unknown

Each dataset now contains 3 columns for each unique race/ethnicity format, for example:

step2_ca_df %>%
select(
    county, age_cat, sex, race_coded, 
    race_short, race_long
)%>%
group_by(race_short) %>%
slice_head(n=1) %>%
arrange(race_coded) %>%
  
rename_with(
~cell_spec(
    .x,
    "html",
    bold = TRUE,
    color = "#0f172a",
    background = "#ffde59",
    font_size = 16
  ), 4:6
) %>%
kbl(escape = FALSE, align = "c") %>%
row_spec(0, 
  bold = TRUE, 
  background = "#0f172a",
  extra_css = 
   "font-size: 16px!important;color:#ffffff;"
) %>%
kable_styling(bootstrap_options = c("bordered"))

county	age_cat	sex	race_coded	race_short	race_long
Alameda	0-17	FEMALE	1	White NH	White, Non-Hispanic
Alameda	0-17	FEMALE	2	Black NH	Black, Non-Hispanic
Alameda	0-17	FEMALE	3	AIAN NH	American Indian or Alaska Native, Non-Hispanic
Alameda	0-17	FEMALE	4	Asian NH	Asian, Non-Hispanic
Alameda	0-17	FEMALE	5	NHPI NH	Native Hawaiian or Pacific Islander, Non-Hispanic
Alameda	0-17	FEMALE	6	MR NH	Multiracial (two or more of above races), Non-Hispanic
Alameda	0-17	FEMALE	7	Hispanic	Hispanic (any race)