Responses ARE NOT WEIGHTED by race.

Rural communities are defined as zipcodes with density smaller than 500 people per square mile. Urban areas are zipcodes with density greater than 1000 people per square mile. Zipcodes between these two extremes are omitted.

Sample sizes

Comparison Group 1 Group 2
1 Black White
771 6541
2 Black + LatinX White
2186 5797
3 POC (minus Asian) White
2554 5797
4 POC White
2875 5797

Well-being

Anxiety

Black

## 
##  Welch Two Sample t-test
## 
## data:  anxiety by compare1
## t = 5.8653, df = 957.37, p-value = 6.168e-09
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  4.739698 9.506118
## sample estimates:
## mean in group 0 mean in group 1 
##        41.73164        34.60873

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  anxiety by compare2
## t = 6.2848, df = 4003, p-value = 3.634e-10
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  3.396554 6.476471
## sample estimates:
## mean in group 0 mean in group 1 
##        42.05911        37.12260

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  anxiety by compare3
## t = 5.6188, df = 4950.8, p-value = 2.028e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  2.728334 5.652483
## sample estimates:
## mean in group 0 mean in group 1 
##        42.05911        37.86870

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  anxiety by compare4
## t = 6.8855, df = 5858.9, p-value = 6.362e-12
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  3.508842 6.302134
## sample estimates:
## mean in group 0 mean in group 1 
##        42.05911        37.15362

By income

## Analysis of Variance Table
## 
## Response: anxiety
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   58223   58223  58.794 1.962e-14 ***
## Residuals  7811 7735119     990                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: anxiety
##             Df  Sum Sq Mean Sq F value Pr(>F)
## region       3     377  125.63  0.1261 0.9447
## Residuals 8761 8730421  996.51

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  anxiety by rural
## t = -0.12772, df = 3755.3, p-value = 0.8984
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.910430  1.676755
## sample estimates:
## mean in group rural mean in group urban 
##            41.21829            41.33513

Depression

Black

## 
##  Welch Two Sample t-test
## 
## data:  depress by compare1
## t = 0.61504, df = 946.45, p-value = 0.5387
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.523277  2.913885
## sample estimates:
## mean in group 0 mean in group 1 
##        30.04077        29.34547

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  depress by compare2
## t = 0.79911, df = 3898, p-value = 0.4243
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.8487723  2.0167131
## sample estimates:
## mean in group 0 mean in group 1 
##        30.02358        29.43961

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  depress by compare3
## t = 0.39147, df = 4839.9, p-value = 0.6955
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.084310  1.625393
## sample estimates:
## mean in group 0 mean in group 1 
##        30.02358        29.75304

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  depress by compare4
## t = 1.6078, df = 5735.7, p-value = 0.1079
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.232457  2.352504
## sample estimates:
## mean in group 0 mean in group 1 
##        30.02358        28.96356

By income

## Analysis of Variance Table
## 
## Response: depress
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1  138824  138824  170.14 < 2.2e-16 ***
## Residuals  7809 6371710     816                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: depress
##             Df  Sum Sq Mean Sq F value Pr(>F)
## region       3    2860  953.24  1.1412 0.3309
## Residuals 8757 7314594  835.29

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  depress by rural
## t = 1.485, df = 3801.1, p-value = 0.1376
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.396176  2.870366
## sample estimates:
## mean in group rural mean in group urban 
##             30.8747             29.6376

Stress

Black

## 
##  Welch Two Sample t-test
## 
## data:  stress by compare1
## t = 4.5915, df = 924.04, p-value = 5.01e-06
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  3.434278 8.561756
## sample estimates:
## mean in group 0 mean in group 1 
##        56.06363        50.06562

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  stress by compare2
## t = 2.9924, df = 3723.1, p-value = 0.002786
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.8661328 4.1578448
## sample estimates:
## mean in group 0 mean in group 1 
##        56.05049        53.53850

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  stress by compare3
## t = 2.1381, df = 4621.6, p-value = 0.03256
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.1408149 3.2490806
## sample estimates:
## mean in group 0 mean in group 1 
##        56.05049        54.35554

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  stress by compare4
## t = 3.53, df = 5443.1, p-value = 0.000419
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  1.190769 4.165283
## sample estimates:
## mean in group 0 mean in group 1 
##        56.05049        53.37246

By income

## Analysis of Variance Table
## 
## Response: stress
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   76001   76001  72.926 < 2.2e-16 ***
## Residuals  7758 8085062    1042                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: stress
##             Df  Sum Sq Mean Sq F value Pr(>F)
## region       3    2800   933.3  0.8766 0.4523
## Residuals 8707 9270291  1064.7

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  stress by rural
## t = 0.295, df = 3722, p-value = 0.768
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.563473  2.117292
## sample estimates:
## mean in group rural mean in group urban 
##            55.82796            55.55105

Loneliness

Black

## 
##  Welch Two Sample t-test
## 
## data:  lonely by compare1
## t = 6.4494, df = 925.78, p-value = 1.806e-10
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  5.047386 9.462751
## sample estimates:
## mean in group 0 mean in group 1 
##        49.56026        42.30519

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  lonely by compare2
## t = 6.2014, df = 3655.6, p-value = 6.218e-10
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  3.048005 5.866303
## sample estimates:
## mean in group 0 mean in group 1 
##        49.85761        45.40046

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  lonely by compare3
## t = 5.5112, df = 4513.2, p-value = 3.762e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  2.413907 5.079529
## sample estimates:
## mean in group 0 mean in group 1 
##        49.85761        46.11089

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  lonely by compare4
## t = 6.5765, df = 5326.7, p-value = 5.275e-11
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  2.996714 5.542039
## sample estimates:
## mean in group 0 mean in group 1 
##        49.85761        45.58824

By income

## Analysis of Variance Table
## 
## Response: lonely
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   46774   46774  62.336 3.291e-15 ***
## Residuals  7810 5860239     750                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: lonely
##             Df  Sum Sq Mean Sq F value Pr(>F)
## region       3    3998 1332.69  1.7376 0.1569
## Residuals 8757 6716295  766.96

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  lonely by rural
## t = 2.3755, df = 3714.2, p-value = 0.01757
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.3307875 3.4569118
## sample estimates:
## mean in group rural mean in group urban 
##            49.71409            47.82024

Child Externalizing

Black

## 
##  Welch Two Sample t-test
## 
## data:  fussy by compare1
## t = 5.2345, df = 948.51, p-value = 2.037e-07
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  4.292275 9.441015
## sample estimates:
## mean in group 0 mean in group 1 
##        52.42800        45.56136

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  fussy by compare2
## t = 3.4869, df = 3797.6, p-value = 0.0004943
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  1.327078 4.736509
## sample estimates:
## mean in group 0 mean in group 1 
##        52.54926        49.51746

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  fussy by compare3
## t = 3.0938, df = 4690.5, p-value = 0.001988
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.9338376 4.1646761
## sample estimates:
## mean in group 0 mean in group 1 
##        52.54926        50.00000

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  fussy by compare4
## t = 4.0536, df = 5528.3, p-value = 5.113e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  1.650638 4.742487
## sample estimates:
## mean in group 0 mean in group 1 
##        52.54926        49.35269

By income

## Analysis of Variance Table
## 
## Response: fussy
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   51018   51018  44.242 3.098e-11 ***
## Residuals  7791 8984293    1153                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: fussy
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   51018   51018  44.242 3.098e-11 ***
## Residuals  7791 8984293    1153                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  fussy by rural
## t = 1.8004, df = 3739.7, p-value = 0.07188
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1562683  3.6689042
## sample estimates:
## mean in group rural mean in group urban 
##            53.13024            51.37392

Child Internalizing

Black

## 
##  Welch Two Sample t-test
## 
## data:  fear by compare1
## t = 2.5303, df = 967.79, p-value = 0.01155
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.7050749 5.5782944
## sample estimates:
## mean in group 0 mean in group 1 
##        26.83620        23.69452

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  fear by compare2
## t = -0.90295, df = 3822.2, p-value = 0.3666
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.436724  0.899994
## sample estimates:
## mean in group 0 mean in group 1 
##        26.48129        27.24965

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  fear by compare3
## t = -1.3103, df = 4723.8, p-value = 0.1902
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.6390822  0.5246155
## sample estimates:
## mean in group 0 mean in group 1 
##        26.48129        27.53852

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  fear by compare4
## t = -0.41279, df = 5598.5, p-value = 0.6798
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.825851  1.190675
## sample estimates:
## mean in group 0 mean in group 1 
##        26.48129        26.79888

By income

## Analysis of Variance Table
## 
## Response: fear
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   29558 29557.7   26.73 2.398e-07 ***
## Residuals  7780 8602974  1105.8                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Geographic Region

## Analysis of Variance Table
## 
## Response: fear
##              Df  Sum Sq Mean Sq F value    Pr(>F)    
## poverty150    1   29558 29557.7   26.73 2.398e-07 ***
## Residuals  7780 8602974  1105.8                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  fear by rural
## t = 1.1802, df = 3773.5, p-value = 0.238
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.7472624  3.0076203
## sample estimates:
## mean in group rural mean in group urban 
##            27.22300            26.09282

Work benefits

Income

Black

## 
##  Welch Two Sample t-test
## 
## data:  income by compare1
## t = 2.4216, df = 755.97, p-value = 0.01569
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   5164.122 49382.310
## sample estimates:
## mean in group 0 mean in group 1 
##        88849.34        61576.13

Black + LatinX

## 
##  Welch Two Sample t-test
## 
## data:  income by compare2
## t = 3.4932, df = 3904, p-value = 0.0004827
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  13122.79 46697.80
## sample estimates:
## mean in group 0 mean in group 1 
##        91045.53        61135.23

People of Color (minus Asian)

## 
##  Welch Two Sample t-test
## 
## data:  income by compare3
## t = 3.7733, df = 3904.6, p-value = 0.0001635
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  15161.87 47959.16
## sample estimates:
## mean in group 0 mean in group 1 
##        91045.53        59485.01

People of Color

## 
##  Welch Two Sample t-test
## 
## data:  income by compare4
## t = 2.3625, df = 4131, p-value = 0.0182
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   3470.649 37324.641
## sample estimates:
## mean in group 0 mean in group 1 
##        91045.53        70647.88

Geographic Region

## Analysis of Variance Table
## 
## Response: income
##             Df     Sum Sq    Mean Sq F value  Pr(>F)  
## region       3 1.0970e+12 3.6567e+11  2.6299 0.04848 *
## Residuals 4273 5.9412e+14 1.3904e+11                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Rural/Urban

## 
##  Welch Two Sample t-test
## 
## data:  income by rural
## t = -3.2647, df = 952.12, p-value = 0.001135
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -54647.98 -13614.37
## sample estimates:
## mean in group rural mean in group urban 
##            63034.15            97165.32

Sick Leave

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$compare1
## X-squared = 1.4212, df = 1, p-value = 0.2332

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$compare2
## X-squared = 0.27466, df = 1, p-value = 0.6002

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$compare3
## X-squared = 0.00024085, df = 1, p-value = 0.9876

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$compare4
## X-squared = 0.074761, df = 1, p-value = 0.7845

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$poverty150
## X-squared = 407.09, df = 1, p-value < 2.2e-16

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$sick_leave and scored$region
## X-squared = 58.52, df = 3, p-value = 1.217e-12

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$sick_leave and scored$rural
## X-squared = 21.556, df = 1, p-value = 3.436e-06

Employment

Unemployed

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$compare1
## X-squared = 4.8389, df = 1, p-value = 0.02783

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$compare2
## X-squared = 15.485, df = 1, p-value = 8.315e-05

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$compare3
## X-squared = 17.15, df = 1, p-value = 3.453e-05

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$compare4
## X-squared = 14.95, df = 1, p-value = 0.0001104

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$poverty150
## X-squared = 219.93, df = 1, p-value < 2.2e-16

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$unemployed and scored$region
## X-squared = 27.241, df = 3, p-value = 5.241e-06

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$unemployed and scored$rural
## X-squared = 8.2554, df = 1, p-value = 0.004063

Lost employment

“Has your level of employment decreased due to the coronavirus (COVID-19) pandemic?”

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$compare1
## X-squared = 27.033, df = 1, p-value = 2e-07

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$compare2
## X-squared = 74.038, df = 1, p-value < 2.2e-16

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$compare3
## X-squared = 81.018, df = 1, p-value < 2.2e-16

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$compare4
## X-squared = 72.955, df = 1, p-value < 2.2e-16

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$poverty150
## X-squared = 181.22, df = 1, p-value < 2.2e-16

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$employment_decreased and scored$region
## X-squared = 1.9427, df = 3, p-value = 0.5844

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$employment_decreased and scored$rural
## X-squared = 2.5619, df = 1, p-value = 0.1095

Among unemployed

Comparison Group 1 Group 2
1 Black White
176 1272
2 Black + LatinX White
507 1113
3 POC (minus Asian) White
592 1113
4 POC White
654 1113

Have access to free food

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$compare1
## X-squared = 11.313, df = 1, p-value = 0.0007695

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$compare2
## X-squared = 7.0257, df = 1, p-value = 0.008035

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$compare3
## X-squared = 11.58, df = 1, p-value = 0.0006665

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$compare4
## X-squared = 5.3255, df = 1, p-value = 0.02102

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$poverty150
## X-squared = 244.22, df = 1, p-value < 2.2e-16

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  unemployed$free_food and unemployed$region
## X-squared = 4.7261, df = 3, p-value = 0.193

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$free_food and unemployed$rural
## X-squared = 0.30867, df = 1, p-value = 0.5785

Lost free lunch for child(ren)

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$compare1
## X-squared = 3.7391, df = 1, p-value = 0.05315

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$compare2
## X-squared = 2.7094, df = 1, p-value = 0.09976

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$compare3
## X-squared = 3.825, df = 1, p-value = 0.05049

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$compare4
## X-squared = 2.2655, df = 1, p-value = 0.1323

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$poverty150
## X-squared = 23.075, df = 1, p-value = 1.558e-06

Geographic Region

## 
##  Chi-squared test for given probabilities
## 
## data:  unemployed$lost_free_lunch
## X-squared = 1686, df = 1806, p-value = 0.9789

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  unemployed$lost_free_lunch and unemployed$rural
## X-squared = 0.85934, df = 1, p-value = 0.3539

Childcare

Plans for next month

Same as right now

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$compare1
## X-squared = 20.81, df = 1, p-value = 5.073e-06

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$compare2
## X-squared = 22.375, df = 1, p-value = 2.243e-06

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$compare3
## X-squared = 21.889, df = 1, p-value = 2.888e-06

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$compare4
## X-squared = 17.105, df = 1, p-value = 3.536e-05

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$poverty150
## X-squared = 28.128, df = 1, p-value = 1.136e-07

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$plan_cc_samenow and scored$region
## X-squared = 3.7043, df = 3, p-value = 0.2952

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_samenow and scored$rural
## X-squared = 0.0015298, df = 1, p-value = 0.9688

Different arrangement

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$compare1
## X-squared = 9.9784, df = 1, p-value = 0.001584

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$compare2
## X-squared = 10.671, df = 1, p-value = 0.001088

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$compare3
## X-squared = 7.5562, df = 1, p-value = 0.00598

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$compare4
## X-squared = 6.1717, df = 1, p-value = 0.01298

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$poverty150
## X-squared = 0.1158, df = 1, p-value = 0.7336

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$plan_cc_differ and scored$region
## X-squared = 1.4694, df = 3, p-value = 0.6894

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_differ and scored$rural
## X-squared = 4.4619, df = 1, p-value = 0.03466

Same as during pandemic

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$compare1
## X-squared = 0.67446, df = 1, p-value = 0.4115

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$compare2
## X-squared = 0.504, df = 1, p-value = 0.4777

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$compare3
## X-squared = 0.6699, df = 1, p-value = 0.4131

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$compare4
## X-squared = 0.90868, df = 1, p-value = 0.3405

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$poverty150
## X-squared = 0.086435, df = 1, p-value = 0.7688

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$plan_cc_sameCOVID and scored$region
## X-squared = 3.0154, df = 3, p-value = 0.3893

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_sameCOVID and scored$rural
## X-squared = 4.5959, df = 1, p-value = 0.03205

Don’t know

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$compare1
## X-squared = 14.216, df = 1, p-value = 0.000163

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$compare2
## X-squared = 13.412, df = 1, p-value = 0.00025

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$compare3
## X-squared = 16.14, df = 1, p-value = 5.883e-05

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$compare4
## X-squared = 14.656, df = 1, p-value = 0.000129

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$poverty150
## X-squared = 33.766, df = 1, p-value = 6.214e-09

Geographic Region

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$poverty150
## X-squared = 33.766, df = 1, p-value = 6.214e-09

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$rural
## X-squared = 2.7611, df = 1, p-value = 0.09658

Lost type of childcare

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$lostCC and scored$compare1
## X-squared = 0.40809, df = 1, p-value = 0.5229

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$lostCC and scored$compare2
## X-squared = 1.7122, df = 1, p-value = 0.1907

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$lostCC and scored$compare3
## X-squared = 1.1796, df = 1, p-value = 0.2774

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$lostCC and scored$compare4
## X-squared = 0.74367, df = 1, p-value = 0.3885

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$plan_cc_dontknow and scored$poverty150
## X-squared = 33.766, df = 1, p-value = 6.214e-09

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$plan_cc_dontknow and scored$region
## X-squared = 1.1743, df = 3, p-value = 0.7592

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$lostCC and scored$rural
## X-squared = 0.56361, df = 1, p-value = 0.4528

Type of care for the next month

Center-based

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$compare1
## X-squared = 0.73597, df = 1, p-value = 0.391

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$compare2
## X-squared = 2.6121, df = 1, p-value = 0.106

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$compare3
## X-squared = 1.2627, df = 1, p-value = 0.2611

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$compare4
## X-squared = 0.93472, df = 1, p-value = 0.3336

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$poverty150
## X-squared = 1.6588, df = 1, p-value = 0.1978

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$expect_center and scored$region
## X-squared = 2.4723, df = 3, p-value = 0.4803

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_center and scored$rural
## X-squared = 0.013, df = 1, p-value = 0.9092

Care by relatives

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$compare1
## X-squared = 0.028474, df = 1, p-value = 0.866

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$compare2
## X-squared = 2.3755, df = 1, p-value = 0.1233

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$compare3
## X-squared = 2.4451, df = 1, p-value = 0.1179

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$compare4
## X-squared = 1.6884, df = 1, p-value = 0.1938

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$poverty150
## X-squared = 3.1149, df = 1, p-value = 0.07758

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$expect_relative and scored$region
## X-squared = 0.51307, df = 3, p-value = 0.916

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_relative and scored$rural
## X-squared = 0.005328, df = 1, p-value = 0.9418

Professional (non-centerbased)

Black

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$compare1
## X-squared = 3.448e-27, df = 1, p-value = 1

Black + LatinX

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$compare2
## X-squared = 0.091306, df = 1, p-value = 0.7625

People of Color (minus Asian)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$compare3
## X-squared = 2.0345e-26, df = 1, p-value = 1

People of Color

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$compare4
## X-squared = 2.7225e-27, df = 1, p-value = 1

By income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$poverty150
## X-squared = 6.1753e-27, df = 1, p-value = 1

Geographic Region

## 
##  Pearson's Chi-squared test
## 
## data:  scored$expect_pro and scored$region
## X-squared = 3.631, df = 3, p-value = 0.3042

Rural/Urban

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  scored$expect_pro and scored$rural
## X-squared = 0.029907, df = 1, p-value = 0.8627