Main Findings

To be added…

Introduction

Using data from the 5-year American Community Survey (ACS) for 2021, this Census Analysis scans the City of Chicago at the community level to identify key areas of opportunity for the development and targeting of The Roommates Project. The analyzed variables in this report are the following:

  1. Median household income in the past 12 months for householder 65 years and over (Mean for the community area in 2021 inflation-adjusted dollars)
  2. Poverty status of non-family male householder 65 years and over: Income in the past 12 months below poverty level (Population)
  3. Poverty status of non-family female householder 65 years and over: Income in the past 12 months below poverty level (Population)
  4. Vacancy Status: For Rent (Total Housing Units)
  5. Owner Occupied: 65 years and over (Total Housing Units)
  6. Renter Occupied: 65 years and over (Total Housing Units)
  7. Non-Family Household: Owner 65 years and over living alone (Total Housing Units)
  8. Non-Family Household: Owner 65 years and over NOT living alone (Total Housing Units)
  9. Non-Family Household: Renter 65 years and over living alone (Total Housing Units)
  10. Non-Family Household: Renter 65 years and over NOT living alone (Total Housing Units)
  11. Owner occupied 65 years and over: 1.01 to 1.50 occupants per room (Total Housing Units)
  12. Owner occupied 65 years and over: 1.51 or more occupants per room (Total Housing Units)
  13. Owner occupied 65 years and over: 1.00 or less occupants per room (Total Housing Units)
  14. Renter occupied 65 years and over: 1.00 or less occupants per room (Total Housing Units)
  15. Renter occupied 65 years and over: 1.01 to 1.50 occupants per room (Total Housing Units)
  16. Renter occupied 65 years and over: 1.51 or more occupants per room (Total Housing Units)
  17. Total Housing Units with 2 bedrooms
  18. Total Owner Occupied Housing Units with a mortgage (Householder 65 to 74 years)
  19. Median gross rent for occupied housing units with 2 bedrooms (Mean for the Community Area in dollars)
  20. Owner occupied households with 2 bedrooms (Total Housing Units)
  21. Renter occupied households with 2 bedrooms (Total Housing Units)
  22. Rent-Burden: Householders 65 years and over paying 35 percent or more of gross rent from their income (Total Occupied Housing Units)
  23. Non-Rent Cost-Burden of Householders: Householders 65 years and over paying 35 percent or more of selected monthly owner costs from their income (Total Occupied Housing Units)
  24. Total people 65 years and over without a disability that have either public or private health insurance (Population)
  25. Total people 65 years and over without a disability that do not have either public or private health insurance (Population)
  26. Total people 65 years and over with a disability that have either public or private health insurance (Population)
  27. Total people 65 years and over with a disability that do not have either public or private health insurance (Population)

Summary statistics and community level maps per variable are provided. Overall, this report aims to inform the decision making to target the communities that are in most need of The Roommates program and select at the street-level the blocks that could potentially provide affordable housing for low-income older adults.

User Guide

To be added…

Getting ready

setwd("C:/Users/52222/OneDrive - The University of Chicago/Documents/Autumn 23/Health Policy Lab") # set working directory
census_api_key("803708789b76c54ce13110992d660e5ef32cf712") # connect API key
lv <- load_variables(2021, "acs5", cache = TRUE) # load variables

Extract variables

# Get data for variables of interest and convert it to table
tractsShp <- get_acs(geography = 'tract', variables = c(medinc = "B19049_005", # block group
                                                        poverty_male = "B17017_025", # block group
                                                        poverty_female = "B17017_030", # block group
                                                        hh_for_rent = "B25004_002", # block group
                                                        hh_owners = "B25015_011", # block group
                                                        hh_renters = "B25015_024", # block group
                                                        hh_alone = "B25011_021", # tract
                                                        hh_not_alone = "B25011_025", # tract
                                                        renter_alone = "B25011_045", # tract
                                                        renter_not_alone = "B25011_049", # tract
                                                        less_one_own = "B25015_012", # block group
                                                        one_half_own = "B25015_013", # block group
                                                        more_half_own = "B25015_014", # block group
                                                        less_one_ren = "B25015_025", # block group
                                                        one_half_ren = "B25015_026", # block group
                                                        more_half_ren = "B25015_027", # block group
                                                        two_bd = "B25017_003",# block group
                                                        hh_mortgage = "B25027_008", # tract
                                                        hh_no_mortgage = "B25027_016", # tract
                                                        med_gross_rent = "B25031_004", # tract
                                                        own_2bd = "B25042_005", # block group
                                                        ren_2bd = "B25042_012", # block group
                                                        rent_burden = "B25072_028", # block group
                                                        cost_burden = "B25093_028", # block group
                                                        no_disab_ins = "B18135_031", # tract
                                                        no_disab_no_ins = "B18135_034", # tract
                                                        disab_ins = "B18135_026", # tract
                                                        disab_no_ins = "B18135_029" # tract
                                                        ),
                     year = 2021, state  = 'IL', geometry = TRUE) %>%
  select(GEOID, NAME, variable, estimate) %>% 
  spread(variable, estimate)
summary(tractsShp)
##     GEOID               NAME            cost_burden      disab_ins     
##  Length:3265        Length:3265        Min.   :  0.0   Min.   :   0.0  
##  Class :character   Class :character   1st Qu.: 24.0   1st Qu.: 100.0  
##  Mode  :character   Mode  :character   Median : 51.0   Median : 166.0  
##                                        Mean   : 66.2   Mean   : 188.2  
##                                        3rd Qu.: 89.0   3rd Qu.: 248.0  
##                                        Max.   :800.0   Max.   :1120.0  
##                                                                        
##   disab_no_ins        hh_alone     hh_for_rent      hh_mortgage    
##  Min.   :  0.000   Min.   :   0   Min.   :  0.00   Min.   :  0.00  
##  1st Qu.:  0.000   1st Qu.:  50   1st Qu.:  0.00   1st Qu.: 33.00  
##  Median :  0.000   Median :  98   Median : 16.00   Median : 66.00  
##  Mean   :  1.462   Mean   : 118   Mean   : 32.32   Mean   : 79.25  
##  3rd Qu.:  0.000   3rd Qu.: 160   3rd Qu.: 46.00   3rd Qu.:112.00  
##  Max.   :153.000   Max.   :1488   Max.   :587.00   Max.   :533.00  
##                                                                    
##  hh_no_mortgage   hh_not_alone      hh_owners        hh_renters    
##  Min.   :  0.0   Min.   :  0.00   Min.   :   0.0   Min.   :  0.00  
##  1st Qu.: 44.0   1st Qu.:  0.00   1st Qu.: 156.0   1st Qu.: 21.00  
##  Median : 88.0   Median :  0.00   Median : 285.0   Median : 52.00  
##  Mean   :100.2   Mean   :  6.94   Mean   : 305.1   Mean   : 83.33  
##  3rd Qu.:141.0   3rd Qu.: 10.00   3rd Qu.: 415.0   3rd Qu.:112.00  
##  Max.   :607.0   Max.   :164.00   Max.   :2699.0   Max.   :826.00  
##                                                                    
##   less_one_own     less_one_ren    med_gross_rent       medinc      
##  Min.   :   0.0   Min.   :  0.00   Min.   : 266.0   Min.   :  7411  
##  1st Qu.: 154.0   1st Qu.: 21.00   1st Qu.: 811.5   1st Qu.: 37946  
##  Median : 283.0   Median : 51.00   Median :1023.0   Median : 51094  
##  Mean   : 303.8   Mean   : 82.53   Mean   :1126.2   Mean   : 56146  
##  3rd Qu.: 414.0   3rd Qu.:110.00   3rd Qu.:1317.0   3rd Qu.: 67981  
##  Max.   :2699.0   Max.   :795.00   Max.   :3501.0   Max.   :250001  
##                                    NA's   :554      NA's   :311     
##  more_half_own      more_half_ren      no_disab_ins    no_disab_no_ins  
##  Min.   :  0.0000   Min.   :  0.000   Min.   :   0.0   Min.   :  0.000  
##  1st Qu.:  0.0000   1st Qu.:  0.000   1st Qu.: 227.0   1st Qu.:  0.000  
##  Median :  0.0000   Median :  0.000   Median : 370.0   Median :  0.000  
##  Mean   :  0.3979   Mean   :  0.461   Mean   : 404.1   Mean   :  3.967  
##  3rd Qu.:  0.0000   3rd Qu.:  0.000   3rd Qu.: 530.0   3rd Qu.:  0.000  
##  Max.   :111.0000   Max.   :109.000   Max.   :2920.0   Max.   :261.000  
##                                                                         
##   one_half_own      one_half_ren        own_2bd       poverty_female  
##  Min.   : 0.0000   Min.   : 0.0000   Min.   :   0.0   Min.   :  0.00  
##  1st Qu.: 0.0000   1st Qu.: 0.0000   1st Qu.:  99.0   1st Qu.:  0.00  
##  Median : 0.0000   Median : 0.0000   Median : 182.0   Median : 12.00  
##  Mean   : 0.9406   Mean   : 0.3308   Mean   : 214.4   Mean   : 21.85  
##  3rd Qu.: 0.0000   3rd Qu.: 0.0000   3rd Qu.: 284.0   3rd Qu.: 29.00  
##  Max.   :66.0000   Max.   :66.0000   Max.   :2146.0   Max.   :380.00  
##                                                                       
##   poverty_male        ren_2bd        rent_burden      renter_alone   
##  Min.   :  0.000   Min.   :   0.0   Min.   :  0.00   Min.   :  0.00  
##  1st Qu.:  0.000   1st Qu.:  67.0   1st Qu.:  0.00   1st Qu.:  9.00  
##  Median :  0.000   Median : 151.0   Median : 17.00   Median : 31.00  
##  Mean   :  9.534   Mean   : 197.7   Mean   : 37.48   Mean   : 59.98  
##  3rd Qu.: 12.000   3rd Qu.: 278.0   3rd Qu.: 50.00   3rd Qu.: 79.00  
##  Max.   :270.000   Max.   :1171.0   Max.   :601.00   Max.   :795.00  
##                                                                      
##  renter_not_alone      two_bd                 geometry   
##  Min.   :  0.000   Min.   :   0.00   MULTIPOLYGON :3265  
##  1st Qu.:  0.000   1st Qu.:   0.00   epsg:4269    :   0  
##  Median :  0.000   Median :  14.00   +proj=long...:   0  
##  Mean   :  2.231   Mean   :  43.29                       
##  3rd Qu.:  0.000   3rd Qu.:  47.00                       
##  Max.   :236.000   Max.   :1729.00                       
##

Data cleaning and boundary merging

# Load chicago boundaries shapefile
chicago_bound <- st_read("Boundaries - City")
## Reading layer `geo_export_c6730356-d5a0-4e1e-80f6-64462990cd9c' from data source `C:\Users\52222\OneDrive - The University of Chicago\Documents\Autumn 23\Health Policy Lab\Boundaries - City' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 1 feature and 4 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -87.94011 ymin: 41.64454 xmax: -87.52414 ymax: 42.02304
## Geodetic CRS:  WGS84(DD)
# Transform to same CRS format
chicago_bound <- st_transform(chicago_bound, 4326)
tractsShp <- st_transform(tractsShp, 4326)

# Join census tracts with chicago boundaries
tract_acs_shp <- st_intersection(tractsShp, chicago_bound)

# Extract file of census tract by community area
chi_tracts_comm <-read.csv(file = "Census_Tracts_in_Chicago_Community_Areas.csv")

# Merge Chicago ACS Tracts Income Data with the Census Tracts in Chicago Community Areas Data
chi_tracts_merge <- merge(tract_acs_shp, chi_tracts_comm, by.x = "GEOID", by.y = "Tract")

# Group Census Tracts by Chicago Community Area
acs_est <- chi_tracts_merge %>%
  group_by(CommunityAreaName) %>%
  summarize(mean_medinc = mean(medinc,na.rm=TRUE),
            poverty_male_tot = sum(poverty_male,na.rm=TRUE),
            poverty_female_tot = sum(poverty_female,na.rm=TRUE),
            hh_for_rent_tot = sum(hh_for_rent,na.rm=TRUE),
            hh_owners_tot = sum(hh_owners,na.rm=TRUE),
            hh_alone_tot = sum(hh_alone,na.rm=TRUE),
            hh_renters_tot = sum(hh_renters,na.rm=TRUE),
            hh_not_alone_tot = sum(hh_not_alone,na.rm=TRUE),
            renter_alone_tot = sum(renter_alone,na.rm=TRUE),
            renter_not_alone_tot = sum(renter_not_alone,na.rm=TRUE),
            less_one_ren_tot = sum(less_one_ren,na.rm=TRUE),
            one_half_ren_tot = sum(one_half_ren,na.rm=TRUE),
            more_half_ren_tot = sum(more_half_ren,na.rm=TRUE),
            less_one_own_tot = sum(less_one_own,na.rm=TRUE),
            one_half_own_tot = sum(one_half_own,na.rm=TRUE),
            more_half_own_tot = sum(more_half_own,na.rm=TRUE),
            two_bd_tot = sum(two_bd,na.rm=TRUE),
            hh_mortgage_tot = sum(hh_mortgage,na.rm=TRUE),
            hh_no_mortgage_tot = sum(hh_no_mortgage,na.rm=TRUE),
            med_gross_rent_tot = mean(med_gross_rent,na.rm=TRUE),
            own_2bd_tot = sum(own_2bd,na.rm=TRUE),
            ren_2bd_tot = sum(ren_2bd,na.rm=TRUE),
            rent_burden_tot = sum(rent_burden,na.rm=TRUE),
            cost_burden_tot = sum(cost_burden,na.rm=TRUE),
            no_disab_ins_tot = sum(no_disab_ins,na.rm=TRUE),
            no_disab_no_ins_tot = sum(no_disab_no_ins,na.rm=TRUE),
            disab_ins_tot = sum(disab_ins,na.rm=TRUE),
            disab_no_ins_tot = sum(disab_no_ins,na.rm=TRUE)
            )

summary(acs_est)
##  CommunityAreaName   mean_medinc     poverty_male_tot poverty_female_tot
##  Length:77          Min.   : 14534   Min.   :  0.0    Min.   : 24.0     
##  Class :character   1st Qu.: 33123   1st Qu.: 58.0    1st Qu.:108.0     
##  Mode  :character   Median : 42585   Median :106.0    Median :210.0     
##                     Mean   : 45599   Mean   :144.3    Mean   :271.3     
##                     3rd Qu.: 52708   3rd Qu.:194.0    3rd Qu.:398.0     
##                     Max.   :128974   Max.   :679.0    Max.   :754.0     
##  hh_for_rent_tot  hh_owners_tot   hh_alone_tot    hh_renters_tot
##  Min.   :   0.0   Min.   : 105   Min.   :  28.0   Min.   : 128  
##  1st Qu.: 102.0   1st Qu.: 867   1st Qu.: 392.0   1st Qu.: 459  
##  Median : 335.0   Median :1613   Median : 601.0   Median : 928  
##  Mean   : 486.7   Mean   :1806   Mean   : 758.6   Mean   :1139  
##  3rd Qu.: 674.0   3rd Qu.:2285   3rd Qu.:1010.0   3rd Qu.:1631  
##  Max.   :3267.0   Max.   :7853   Max.   :4032.0   Max.   :4075  
##  hh_not_alone_tot renter_alone_tot renter_not_alone_tot less_one_ren_tot
##  Min.   :  0.00   Min.   :  15.0   Min.   :  0.00       Min.   : 128    
##  1st Qu.: 11.00   1st Qu.: 310.0   1st Qu.:  0.00       1st Qu.: 459    
##  Median : 33.00   Median : 629.0   Median : 26.00       Median : 928    
##  Mean   : 49.08   Mean   : 800.3   Mean   : 33.64       Mean   :1119    
##  3rd Qu.: 76.00   3rd Qu.:1082.0   3rd Qu.: 49.00       3rd Qu.:1577    
##  Max.   :202.00   Max.   :2572.0   Max.   :143.00       Max.   :3977    
##  one_half_ren_tot more_half_ren_tot less_one_own_tot one_half_own_tot
##  Min.   : 0.000   Min.   :  0.00    Min.   : 105     Min.   : 0.00   
##  1st Qu.: 0.000   1st Qu.:  0.00    1st Qu.: 867     1st Qu.: 0.00   
##  Median : 0.000   Median :  0.00    Median :1611     Median : 0.00   
##  Mean   : 8.597   Mean   : 11.44    Mean   :1789     Mean   :11.43   
##  3rd Qu.:16.000   3rd Qu.: 11.00    3rd Qu.:2285     3rd Qu.:18.00   
##  Max.   :86.000   Max.   :143.00    Max.   :7853     Max.   :98.00   
##  more_half_own_tot   two_bd_tot      hh_mortgage_tot  hh_no_mortgage_tot
##  Min.   :  0.000   Min.   :    0.0   Min.   :  19.0   Min.   :  13.0    
##  1st Qu.:  0.000   1st Qu.:  104.0   1st Qu.: 256.0   1st Qu.: 256.0    
##  Median :  0.000   Median :  265.0   Median : 444.0   Median : 481.0    
##  Mean   :  5.065   Mean   :  818.5   Mean   : 491.3   Mean   : 539.6    
##  3rd Qu.:  4.000   3rd Qu.:  576.0   3rd Qu.: 652.0   3rd Qu.: 646.0    
##  Max.   :118.000   Max.   :12940.0   Max.   :2014.0   Max.   :2737.0    
##  med_gross_rent_tot  own_2bd_tot     ren_2bd_tot    rent_burden_tot 
##  Min.   : 442.5     Min.   :   23   Min.   :  134   Min.   :  32.0  
##  1st Qu.: 946.5     1st Qu.:  719   1st Qu.:  961   1st Qu.: 193.0  
##  Median :1088.0     Median : 1198   Median : 2010   Median : 448.0  
##  Mean   :1213.8     Mean   : 1943   Mean   : 2766   Mean   : 551.9  
##  3rd Qu.:1351.6     3rd Qu.: 2530   3rd Qu.: 4168   3rd Qu.: 791.0  
##  Max.   :2919.8     Max.   :10180   Max.   :11204   Max.   :2466.0  
##  cost_burden_tot no_disab_ins_tot no_disab_no_ins_tot disab_ins_tot 
##  Min.   :  39    Min.   :  242    Min.   :  0.00      Min.   : 144  
##  1st Qu.: 278    1st Qu.: 1563    1st Qu.:  6.00      1st Qu.: 918  
##  Median : 421    Median : 2452    Median : 28.00      Median :1264  
##  Mean   : 556    Mean   : 2787    Mean   : 56.74      Mean   :1496  
##  3rd Qu.: 767    3rd Qu.: 3435    3rd Qu.: 76.00      3rd Qu.:1920  
##  Max.   :2348    Max.   :11683    Max.   :437.00      Max.   :6467  
##  disab_no_ins_tot          geometry 
##  Min.   :  0.00   MULTIPOLYGON : 2  
##  1st Qu.:  0.00   POLYGON      :75  
##  Median :  0.00   epsg:4326    : 0  
##  Mean   : 22.47   +proj=long...: 0  
##  3rd Qu.: 28.00                     
##  Max.   :191.00

Mapping

Note: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.

1. Median household income in the past 12 months for householder 65 years and over (Mean for the community area in 2021 inflation-adjusted dollars)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="mean_medinc", n=5, style="quantile", palette="YlOrBr", interactive=TRUE)

2. Poverty status of non-family male householder 65 years and over: Income in the past 12 months below poverty level (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="poverty_male_tot", n=5, style="quantile", palette="YlOrBr" )

3. Poverty status of non-family female householder 65 years and over: Income in the past 12 months below poverty level (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="poverty_female_tot", n=5, style="quantile", palette="YlOrBr" )

4. Vacancy Status: For Rent (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_for_rent_tot", n=5, style="quantile", palette="YlOrBr" )

5. Owner Occupied: 65 years and over (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_owners_tot", n=5, style="quantile", palette="YlOrBr" )

6. Renter Occupied: 65 years and over (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_renters_tot", n=5, style="quantile", palette="YlOrBr" )

7. Non-Family Household: Owner 65 years and over living alone (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_alone_tot", n=5, style="quantile", palette="YlOrBr" )

8. Non-Family Household: Owner 65 years and over NOT living alone (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_not_alone_tot", n=5, style="quantile", palette="YlOrBr" )

9. Non-Family Household: Renter 65 years and over living alone (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="renter_alone_tot", n=5, style="quantile", palette="YlOrBr" )

10. Non-Family Household: Renter 65 years and over NOT living alone (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="renter_not_alone_tot", n=5, style="quantile", palette="YlOrBr" )

11. Owner occupied 65 years and over: 1.01 to 1.50 occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="one_half_own_tot", n=5, style="quantile", palette="YlOrBr" )

12. Owner occupied 65 years and over: 1.51 or more occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="more_half_own_tot", n=5, style="quantile", palette="YlOrBr" )

13. Owner occupied 65 years and over: 1.00 or less occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="less_one_own_tot", n=5, style="quantile", palette="YlOrBr" )

14. Renter occupied 65 years and over: 1.00 or less occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="less_one_ren_tot", n=5, style="quantile", palette="YlOrBr" )

15. Renter occupied 65 years and over: 1.01 to 1.50 occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="one_half_ren_tot", n=5, style="quantile", palette="YlOrBr" )

16. Renter occupied 65 years and over: 1.51 or more occupants per room (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="more_half_ren_tot", n=5, style="quantile", palette="YlOrBr" )

17. Total Housing Units with 2 bedrooms

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="two_bd_tot", n=5, style="quantile", palette="YlOrBr" )

18. Total Owner Occupied Housing Units with a mortgage (Householder 65 to 74 years)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="hh_mortgage_tot", n=5, style="quantile", palette="YlOrBr" )

19. Median gross rent for occupied housing units with 2 bedrooms (Mean for the Community Area in dollars)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="med_gross_rent_tot", n=5, style="quantile", palette="YlOrBr" )

20. Owner occupied households with 2 bedrooms (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="own_2bd_tot", n=5, style="quantile", palette="YlOrBr" )

21. Renter occupied households with 2 bedrooms (Total Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="ren_2bd_tot", n=5, style="quantile", palette="YlOrBr" )

22. Rent-Burden: Householders 65 years and over paying 35 percent or more of gross rent from their income (Total Occupied Housing Units)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="rent_burden_tot", n=5, style="quantile", palette="YlOrBr" )

23. Non-Rent Cost-Burden of Householders: Householders 65 years and over paying 35 percent or more of selected monthly owner costs from their income (Total Occupied Housing Units)

Note: Selected monthly owner costs are the sum of payments for mortgages, deeds of trust, contracts to purchase, or similar debts on the property (including payments for the first mortgage, second mortgages, home equity loans, and other junior mortgages); real estate taxes; fire, hazard, and flood insurance on the property; utilities (electricity, gas, and water and sewer); and fuels (oil, coal, kerosene, wood, etc.). It also includes, where appropriate, the monthly condominium fee for condominiums and mobile home costs (personal property taxes, site rent, registration fees, and license fees).

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="cost_burden_tot", n=5, style="quantile", palette="YlOrBr" )

24. Total people 65 years and over without a disability that have either public or private health insurance (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="no_disab_ins_tot", n=5, style="quantile", palette="YlOrBr" )

25. Total people 65 years and over without a disability that do not have either public or private health insurance (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="no_disab_no_ins_tot", n=5, style="quantile", palette="YlOrBr" )

26. Total people 65 years and over with a disability that have either public or private health insurance (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="disab_ins_tot", n=5, style="quantile", palette="YlOrBr" )

27. Total people 65 years and over with a disability that do not have either public or private health insurance (Population)

tmap_mode("view")
tm_shape(acs_est) + 
  tm_polygons(col="disab_no_ins_tot", n=5, style="quantile", palette="YlOrBr" )

References and Data Sources