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---
title: "Health Insurance Coverage Estimates in Arizona"
output: flexdashboard::flex_dashboard
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(sf)
library(ggthemes)
library(RColorBrewer)
library(plotly)
# list of catchment counties
uazcc_catchment_counties <- c(
"Cochise",
"Pima",
"Pinal",
"Santa Cruz",
"Yuma"
)
# Primary Color Palette 2
# c("UA Red", "Arizona Blue")
uazcc_primary_palette <- c("#0C234B", "#AB0520")
# read data ####
# data frame
sahie_az <- read_rds("../data/tidy/sahie_az.rds")
# catchment only
sahie_az_uazcc <- read_rds("../data/tidy/sahie_az.rds") %>%
filter(uazcc_catchment == "yes")
# spatial
sahie_az_spatial <- read_rds("../data/tidy/sahie_az_spatial.rds")
# catchment only spatial
sahie_az_uazcc_spatial <- read_rds("../data/tidy/sahie_az_uazcc_spatial.rds")
# set theme ####
# set consistent theme for graphics & data visualizations
theme_uazcc_brand <- theme_clean(base_size = 12) +
theme(
text = element_text(
family = "sans",
# face = "bold",
color = "#001C48",
# size = rel(1.5)
),
panel.background = element_rect(fill = "white"),
panel.grid = element_line(color = "#1E5288"),
plot.background = element_rect(fill = "#EcE9EB"),
# aspect.ratio = 3 / 4,
legend.background = element_rect(fill = "white"),
legend.position = "bottom",
plot.caption = element_text(size = 8),
# plot.subtitle = element_text(size = 12),
# plot.title = element_text(size = 14),
strip.background = element_rect(fill = "#EcE9EB")
)
# spatial
theme_uazcc_brand_spatial <- theme_map() +
theme(
text = element_text(
family = "sans",
face = "bold",
color = "#001C48",
size = 12
),
legend.position = "right",
plot.caption = element_text(size = 8),
plot.subtitle = element_text(size = 12),
plot.title = element_text(size = 14),
strip.background = element_rect(fill = "#EcE9EB")
)
# catchment only in 2019
sahie_az_uazcc_2019 <- sahie_az_uazcc %>%
filter(year == "2019",
countyfips != "000",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
)
```
Arizona
========================================
Column { data-width = 600 }
----------------------------------------
### Rates of Uninsured Across the State
```{r, cache=TRUE}
sahie_az_spatial %>%
filter(year == "2019",
countyfips != "000",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_sf(mapping = aes(fill = pctelig), color = "white") +
geom_sf(data = sahie_az_uazcc_spatial, fill = NA, color = "#AB0520") +
scale_color_viridis_c("Percent uninsured") +
scale_fill_viridis_c("Percent uninsured") +
geom_sf_label(mapping = aes(label = name), size = 1.75) +
labs(
title = "Percent Uninsured in Arizona Counties",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All Incomes",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
)
# +
# theme_uazcc_brand_spatial
```
Column { data-width = 400 }
----------------------------------------
### Percent Uninsured in Each Arizona County
```{r, cache=TRUE}
county <- sahie_az %>%
filter(
year == "2019",
countyfips != "000",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot(mapping = aes(x = reorder(county_name, pctelig), y = pctelig)) +
geom_bar(stat = "identity", mapping = aes(fill = pctelig)) +
geom_bar(data = sahie_az_uazcc_2019, mapping = aes(x = reorder(county_name, pctelig), y = pctelig), color = "#AB0520", stat = "identity", fill = NA) +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
scale_fill_viridis_c() +
coord_flip() +
labs(
title = "Percent Uninsured in Arizona Counties",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All Incomes",
x = "County",
y = "Percent Uninsured",
fill = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand +
theme(legend.position = "none")
ggplotly(county)
```
### Uninsured by Race and Sex in Arizona
```{r}
# try instead adding the images ![](image here){ width=20% }
# to chunk options, out.width = "20%"
# ? flex dashboard enlarge or zoom image?
#
sex_by_race <- sahie_az %>%
filter(year == "2019",
countyfips == "000",
iprcat == "0",
agecat == "0"
) %>%
ggplot(mapping = aes(x = reorder(racecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
facet_wrap(~sexcat_labels) +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Arizona by Race",
subtitle = "2019, Under 65 years, All Incomes, All Counties",
x = "Race",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
ggplotly(sex_by_race)
```
UAZCC
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips != "000",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
group_by(uazcc_catchment, year) %>%
summarise(
nui = sum(nui),
nipr = sum(nipr)
) %>%
mutate(pct_ui = (nui / nipr) * 100) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pct_ui, color = uazcc_catchment), size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Arizona Counties",
subtitle = "Under 65 years, All Races, Both Sexes, Aggregate values",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
scale_color_manual(values = uazcc_primary_palette) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(year == "2019",
sexcat == "0",
agecat == "0") %>%
group_by(county_name) %>%
ggplot(mapping = aes(x = reorder(county_name, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
facet_wrap(~iprcat_labels) +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Arizona UAZCC Catchment Counties by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(year == "2019",
sexcat == "0",
iprcat == "0") %>%
group_by(county_name) %>%
ggplot(mapping = aes(x = reorder(county_name, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
facet_wrap(~agecat_labels) +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Arizona UAZCC Catchment Counties by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(year == "2019",
iprcat == "0") %>%
group_by(county_name) %>%
ggplot(mapping = aes(x = reorder(county_name, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
facet_wrap(~agecat_labels) +
coord_flip() +
labs(
title = "Percent Uninsured in Arizona UAZCC Catchment Counties by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```
Cochise
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips == "003",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pctui), color = "#AB0520", size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Cochise County ",
subtitle = "Under 65 years, All Races, Both Sexes",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(countyfips == "003",
year == "2019",
sexcat == "0",
agecat == "0") %>%
ggplot(mapping = aes(x = reorder(iprcat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Cochise County by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "Income Category",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(countyfips == "003",
year == "2019",
sexcat == "0",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Cochise County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "Age Group",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(countyfips == "003",
year == "2019",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(
title = "Percent Uninsured in Cochise County by Age Group",
subtitle = "2019, Under 65 years, All Races, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```
Pima
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips == "019",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pctui), color = "#AB0520", size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Pima County ",
subtitle = "Under 65 years, All Races, Both Sexes",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(countyfips == "019",
year == "2019",
sexcat == "0",
agecat == "0") %>%
ggplot(mapping = aes(x = reorder(iprcat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Pima County by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "Income Category",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(countyfips == "019",
year == "2019",
sexcat == "0",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Pima County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "Age Group",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(countyfips == "019",
year == "2019",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(
title = "Percent Uninsured in Pima County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```
Pinal
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips == "021",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pctui), color = "#AB0520", size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Pinal County ",
subtitle = "Under 65 years, All Races, Both Sexes",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(countyfips == "021",
year == "2019",
sexcat == "0",
agecat == "0") %>%
ggplot(mapping = aes(x = reorder(iprcat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Pinal County by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "Income Category",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(countyfips == "021",
year == "2019",
sexcat == "0",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Pinal County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "Age Group",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(countyfips == "021",
year == "2019",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(
title = "Percent Uninsured in Pinal County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```
Santa Cruz
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips == "023",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pctui), color = "#AB0520", size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Santa Cruz County ",
subtitle = "Under 65 years, All Races, Both Sexes",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(countyfips == "023",
year == "2019",
sexcat == "0",
agecat == "0") %>%
ggplot(mapping = aes(x = reorder(iprcat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Santa Cruz County by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "Income Category",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(countyfips == "023",
year == "2019",
sexcat == "0",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Santa Cruz County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "Age Group",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(countyfips == "023",
year == "2019",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(
title = "Percent Uninsured in Santa Cruz County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```
Yuma
========================================
Row
-------------------------------------
### Over time
```{r}
sahie_az %>%
filter(countyfips == "027",
agecat == "0",
racecat == "0",
sexcat == "0",
iprcat == "0"
) %>%
ggplot() +
geom_line(mapping = aes(x = year, y = pctui), color = "#AB0520", size = 2) +
ylim(c(0,20)) +
labs(
title = "Percent Uninsured in Yuma County ",
subtitle = "Under 65 years, All Races, Both Sexes",
x = "Year",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
color = "UAZCC Catchment"
) +
theme_uazcc_brand
```
### By income group
```{r}
sahie_az_uazcc %>%
filter(countyfips == "027",
year == "2019",
sexcat == "0",
agecat == "0") %>%
ggplot(mapping = aes(x = reorder(iprcat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Yuma County by Income Category",
subtitle = "2019, Under 65 years, All Races, Both Sexes",
x = "Income Category",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
Row
-------------------------------------
### By age
```{r}
sahie_az_uazcc %>%
filter(countyfips == "027",
year == "2019",
sexcat == "0",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig)) +
geom_bar(fill = "#1E5288", stat = "identity", position = "dodge") +
geom_errorbar(aes(ymin = (pctelig - pctelig_moe), ymax = (pctelig + pctelig_moe)), color = "#001C48") +
coord_flip() +
labs(
title = "Percent Uninsured in Yuma County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "Age Group",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program"
) +
theme_uazcc_brand
```
### By age and sex
```{r}
sahie_az_uazcc %>%
filter(countyfips == "027",
year == "2019",
iprcat == "0") %>%
ggplot(mapping = aes(x = reorder(agecat_labels, pctelig), y = pctelig, fill = sexcat_labels)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(
title = "Percent Uninsured in Yuma County by Age Group",
subtitle = "2019, Under 65 years, All Races, Both Sexes, All income levels",
x = "County",
y = "Percent Uninsured",
caption = "Source: U.S. Census Bureau, 2019 Small Area Health Insurance Estimates (SAHIE) program",
fill = "Sex"
) +
theme_uazcc_brand +
scale_fill_brewer(palette = "Set1")
```