Child Care Relief Funding Report 2021
1 Overview
This report provides an analysis of the types of providers who did and did not apply for the first round of Child Care Relief Funding (CCRF), the differences between providers who did and did not apply, and how providers spent their relief funding. Analyses were completed using relief funding application data for the 2021 application cycle, expenditure data from the 2022 application, and background data from weekly closure reports (e.g., desert status, TRS status) and HHSC CCL Daycare and Residential Operations data (e.g., subsidy status, capacity).
Overall, 73% (9,565/13,091) of eligible providers applied for funding. Among eligible providers, 365 did not have a corresponding match in the weekly closure reports or HHSC data and, therefore, were missing data for background variables of interest. Because the analysis relies on these variables, providers who did not have background data were excluded. Therefore, a total of 12,726 providers with complete background data were included.
1.1 Eligible providers
There are more than twice as many center-based providers as there are home-based. Among center-based providers, about 50% are considered large with a capacity of 100 or more. Among home-based providers, about 63% are registered homes.
1.2 Percent of applicants vs. non-applicants among eligible providers
Among eligible providers with complete background data, 74% (9,413/12,726) applied for the first round of CCRF funding, leaving 3,313 providers that did not apply. Centers applied for funding at a higher rate than home providers, with 76% of center providers applying vs. 69% of home providers. Subsidy providers applied for funding at a higher rate than non-subsidy providers, with 88% of subsidy providers applying for funding compared to only 59% of non-subsidy providers. Urban providers applied for funding at a higher rate than rural providers (75% vs. 65%), and non-desert providers applied at a higher rate than desert providers (74% vs. 67%).
1.3 Average amount paid
Overall, the average total award amount paid was $59,316. Licensed centers were paid on average $80,804, whereas home-based providers were paid about $6,508.
2 Applicants
2.1 By provider type and subsidy status
Subsidy providers consistently applied for funding at higher rates relative to non-subsidy providers, regardless of provider type and capacity. The figure on the left shows the total number of providers by provider type and capacity (e.g., center vs. home, subsidy vs. non-subsidy, large vs. medium, etc.) that applied for funding.
The figure on the right shows the percentage of each type of provider who applied for funding, indicating that large centers who accept subsidies applied at the highest rate, with 91% (2,264/2,489) of large centers applying for funding. Small non-subsidy centers applied at the lowest rate, with only 46% (289/634) of small non-subsidy centers applying for funding.
2.2 By provider type and urban-rural classification
Urban providers applied for funding at a higher rate relative to rural providers. However, both rural and urban centers applied at slightly higher rates (67% and 78%, respectively) compared to rural and urban home providers (58% and 70%, respectively).
2.3 By provider type, subsidy status, and urban-rural classification
The figure below accounts for both subsidy status and urban-rural classification. The width of each bar illustrates that there are more center provider applicants than home provider applicants. Urban centers who accept subsidies make up the largest proportion of providers that applied for funding, accounting for 4,065 providers, or 43% of all applicants.
2.4 By workforce board
In the figures below, workforce boards are sorted by size (i.e., the total number of eligible providers on the left and the total number of eligible subsidy providers on the right). In the figure on the left, the light blue shaded region illustrates the total number of eligible providers in each workforce board, and the dark blue shaded region indicates the proportion of eligible providers in each workforce board area who applied for funding. In the figure on the right, the light red shaded region illustrates the total number of eligible subsidy providers in each workforce board, and the dark red shaded region indicates the proportion of eligible subsidy providers who applied for funding. (See Supplemental Table 1 in Appendix for full data.)
Gulf Coast is by far the largest workforce board, with a total of 3,435 eligible providers. Of those eligible providers, 2,507 applied, which is 73% of eligible providers in the Gulf Coast.
A closer look at the five largest workforce boards (based on the number of eligible providers) reveals that Gulf Coast subsidy centers make up the largest proportion of applicants, accounting for 1,106 providers. Gulf coast non-subsidy homes make up the next largest proportion of applicants, with 587 providers. Applicants from the top five workforce boards account for 61% of all applicants in total.
2.5 By TRS status
TRS-rated providers were more likely to apply than providers who are not participating in the TRS program. For example, 94% of all TRS 4-star center providers applied for funding.
3 Non-applicants
3.1 By provider type and subsidy status
Non-subsidy providers were much less likely to apply for funding than subsidy providers. The figure on the left shows the total number of non-applicants by type and size, illustrating that non-subsidy providers accounted for 78% (2,573/3,313) of the providers who did not apply. The figure on the right shows the percent of each type of provider who applied for funding. Non-subsidy large centers and registered homes make up the largest fraction of providers that did not apply.
3.2 By provider type and urban-rural classification
Compared to urban providers, rural providers were less likely to apply for funding, regardless of provider type. For example, 42% of eligible rural home providers did not apply for funding.
3.3 By provider type, subsidy status, and urban-rural classification
The figure below accounts for both urban-rural classification and subsidy status. Urban centers that do not accept subsidies make up the largest fraction of providers that did not apply for funding, accounting for 1,258 providers or 38% of all non-applicants.
3.4 By workforce board
In the figures below, workforce boards are again sorted by size. For the figure on the left, the light blue shaded region illustrates the total number of eligible providers in each workforce board, and the dark blue shaded region indicates what proportion of eligible providers in each workforce board did not apply for funding. For the figure on the right, the light red shaded region illustrates the total number of eligible subsidy providers in each workforce board, and the dark red shaded region indicates what proportion of eligible subsidy providers did not apply for funding.
Within the Gulf Coast, 928 providers did not apply out of 3,435 eligible providers.
A closer look at the top five largest workforce boards (based on the number of eligible providers) reveals that Gulf Coast non-subsidy centers make up the largest proportion of non-applicants, accounting for 419 providers. The next largest group of non-applicants is non-subsidy homes in the Gulf Coast, accounting for 365 providers. Non-subsidy providers in the Gulf Coast alone account for 24% of the total eligible providers that did not apply for funding.
4 Predictors of application
A linear probability model was used to predict the likelihood that childcare providers applied for CCRF funding, using variables from the weekly closure reports and HHSC data, as well as social vulnerability index (SVI) data obtained from the CDC. Among eligible providers, 998 did not match to the background or SVI data. Therefore, a total of 11,728 providers with complete background and SVI data were included in this analysis. Subsidy status is the largest predictor of application. Providers that accept child care subsidies were about 27 percentage points more likely to apply for grant funding compared to non-subsidy providers. Subsidy status may be correlated with other unmeasured attributes that led them to be more likely to apply for funding, such as a closer connection to TWC or a more up-to-date email address on file with TWC. This could have led subsidy providers to be more likely to learn about the grant when the application was open or be more likely to trust information coming from TWC.
Licensed and registered homes were also slightly more likely to apply for grant funding than licensed centers. Licensed homes were about 8 percentage points more likely to apply relative to licensed centers, and registered homes were about 4 percentage points more likely to apply relative to licensed centers. This is not driven by home providers being more likely to accept subsidies, as about 29% of home providers accept the subsidy compared to 60% of licensed centers.
The location of the childcare provider also impacts the likelihood of applying for the grant. Providers located in urban counties (defined as a population greater than 100,000) were about 9 percentage points more likely to apply for funding. This again is not driven by subsidy status, as 50% of urban providers accept the subsidy, and 56% of rural providers accept the subsidy. However, whether the provider is located in a child care desert did not have a significant impact on the likelihood of applying.
Additionally, measures of social vulnerability were controlled to determine whether this predicts the likelihood of applying. Providers in more socially vulnerable areas were less likely to apply for funding, with those in the most socially vulnerable areas being the least likely to apply. Providers were split into four categories based on their social vulnerability index (SVI): those located in low SVI areas, mid-low SVI, mid-high SVI, and high SVI. While there is no statistically significant difference between the likelihood of applying among low and mid-low SVI providers, those in mid-high SVI areas are about 3 percentage points less likely to apply for funding relative to low SVI areas. Those in high SVI areas are 6 percentage points less likely to apply for funding relative to low SVI areas. There are a total of 1,317 non-applicants in mid-high and high SVI areas (with 697 mid-high and 620 high non-applicants). However, we do not find that homes in socially vulnerable areas are any more or less likely to apply for funding relative to centers in socially vulnerable areas.
Childcare providers that only serve school-aged children or who were temporarily closed were less likely to apply for funding. Provider capacity and being open just one or two days per week did not have an impact on the likelihood of applying for funding. In addition, the number of children served using the subsidy did not have an impact on the probability of applying.
5 Utilization of relief funding
Overall, 89% (8,471/9,565) of providers who applied for and received 2021 CCRF funding reported their expenditures during the 2022 application cycle. We examine how these 8,471 recipients spent their relief funding for the 2021 reporting period.
5.1 Expenditures overview
The figure below illustrates the categories on which providers spent their funding for the 2021 reporting period. Overall, the two most common spending categories were personnel costs and rent, mortgage, or utilities, with 87% and 85% of providers, respectively, reporting that they had used their money on related expenses. Only 21% and 13% of providers reported expenditures on parent tuition or copays and mental health support, respectively.
Differences in expenditures were most apparent between home and center providers. The most common expense categories among centers were personnel costs (94%) and rent, mortgage or utilities (83%), while homes were more likely to report expenses on rent, mortgage, or utilities (91%) and personal protective equipment (83%). This is to be expected, as home-based providers generally do not have large staffing structures, and personnel-related costs are of greater concern to centers. Differences between subsidy status (non-subsidy vs. subsidy) and county type (rural vs. urban) were marginal.
| Expense category | Provider type | Subsidy status | County type | Overall | |||
|---|---|---|---|---|---|---|---|
| Center | Home | Non-subsidy | Subsidy | Rural | Urban | ||
| Personnel costs | 94% | 67% | 82% | 90% | 90% | 86% | 87% |
| Rent/Mortgage/Utilities | 83% | 91% | 84% | 86% | 82% | 86% | 85% |
| Personal Protective Equipment | 69% | 83% | 73% | 72% | 72% | 73% | 73% |
| Goods and services | 69% | 79% | 70% | 73% | 72% | 72% | 72% |
| Purchases/updates to equipment and supplies | 60% | 78% | 67% | 64% | 61% | 66% | 65% |
| Parent tuition/copays | 23% | 16% | 16% | 24% | 21% | 21% | 21% |
| Mental health support | 13% | 13% | 12% | 13% | 11% | 13% | 13% |
| Other allowable expenses | 6% | 7% | 6% | 6% | 6% | 6% | 6% |
The figure below illustrates the breakdown of top expenditures among providers by provider characteristic. Overall, the majority of providers indicated that their top expenditure category was personnel costs, with 59% of providers reporting that the personnel costs were their greatest expense. Twenty-eight percent of providers reported that rent, mortgage, or utilities was their greatest expense. Again, the greatest differences are between home and center providers due to difference in personnel and staffing structures. Compared to just 18% of homes, 74% of centers reported that personnel costs were their greatest expense. Home providers were far more likely to report that rent, mortgage, or utilities was their top spending category (52%).
| Top expense category | Provider type | Subsidy status | County type | Overall | |||
|---|---|---|---|---|---|---|---|
| Center | Home | Non-subsidy | Subsidy | Rural | Urban | ||
| Personnel costs | 74% | 18% | 51% | 64% | 66% | 58% | 59% |
| Rent/Mortgage/Utilities | 19% | 52% | 32% | 25% | 18% | 29% | 28% |
| Goods and services | 4% | 15% | 9% | 6% | 9% | 7% | 7% |
| Personal Protective Equipment | 1% | 7% | 3% | 2% | 3% | 2% | 2% |
| Purchases/updates to equipment and supplies | 1% | 5% | 3% | 2% | 2% | 2% | 2% |
| Other | 1% | 2% | 2% | 1% | 1% | 1% | 1% |
Apparent differences between subsidy status categories and county type categories appear to be driven by differences between center and home providers. That is, differences between non-subsidy and subsidy providers and rural and urban providers appear to be the result of the unequal distribution of home and center providers within each provider characteristic. For example, while subsidy providers were slightly more likely than non-subsidy providers to report personnel costs as their top spending category, these differences largely disappear when accounting for provider type (i.e., differences between subsidy and non-subsidy providers within homes and centers, respectively, become smaller). (See Supplemental Table 2 in Appendix.)
5.2 Expenditures by provider type
To gain further insight into the differences between home and center providers, the impact of provider capacity and licensing on expenditures was examined. Differences between provider types are much greater than differences within. While centers with small capacity were slightly more likely to spend funding on personal protective equipment compared to large-capacity centers (74% vs. 66%), and licensed homes were slightly more likely to spend money on personnel costs compared to registered homes (72% vs. 63%), expenditures were generally consistent within provider types.
| Expense category | Center | Home | |||
|---|---|---|---|---|---|
| Small (0-50) | Medium (51-99) | Large (100+) | Licensed Home | Registered Home | |
| Personnel costs | 91% | 95% | 95% | 72% | 63% |
| Rent/Mortgage/Utilities | 86% | 83% | 82% | 89% | 93% |
| Personal Protective Equipment | 74% | 70% | 66% | 81% | 84% |
| Purchases/updates to equipment and supplies | 68% | 64% | 56% | 74% | 80% |
| Goods and services | 72% | 70% | 68% | 78% | 80% |
| Mental health support | 13% | 13% | 12% | 12% | 14% |
| Parent tuition/copays | 23% | 24% | 21% | 18% | 15% |
| Other allowable expenses | 7% | 6% | 6% | 8% | 5% |
Top spending categories also did not differ significantly within provider types. While larger-capacity centers were more likely to report personnel costs as top spending category compared to small-capacity centers (79% vs. 63%), as expected, there were no other notable differences between top spending categories within home and center providers.
| Top expense category | Center | Home | |||
|---|---|---|---|---|---|
| Small (0-50) | Medium (51-99) | Large (100+) | Licensed Home | Registered Home | |
| Personnel costs | 63% | 74% | 79% | 21% | 16% |
| Rent/Mortgage/Utilities | 26% | 20% | 16% | 50% | 54% |
| Goods and services | 6% | 4% | 3% | 15% | 15% |
| Purchases/updates to equipment and supplies | 2% | 1% | 1% | 5% | 6% |
| Other | 1% | 1% | 1% | 3% | 2% |
| Personal Protective Equipment | 1% | 1% | 0% | 6% | 7% |
5.3 Expenditures by workforce board
Expenditures were also compared between the five largest workforce boards: Gulf Coast, North Central, Dallas, Alamo, and Tarrant. While providers located in the North Central local workforce developmental area were slightly less likely to report expenditures on purchases or updates to equipment and supplies and parent tuition or copays, expenditures were not notably different between workforce boards. (See Supplemental Table 3 in Appendix for full expenditure data by workforce board.)
| Expense category | Gulf Coast | North Central | Dallas | Alamo | Tarrant | Overall |
|---|---|---|---|---|---|---|
| Personnel costs | 86% | 88% | 88% | 89% | 91% | 87% |
| Rent/Mortgage/Utilities | 84% | 87% | 89% | 87% | 84% | 85% |
| Personal Protective Equipment | 71% | 71% | 80% | 78% | 75% | 73% |
| Purchases/updates to equipment and supplies | 66% | 56% | 71% | 72% | 69% | 65% |
| Goods and services | 72% | 72% | 75% | 75% | 75% | 72% |
| Mental health support | 14% | 11% | 13% | 10% | 17% | 13% |
| Parent tuition/copays | 24% | 15% | 25% | 20% | 25% | 21% |
| Other allowable expenses | 6% | 5% | 8% | 4% | 5% | 6% |
Again, top spending categories were consistent across the top five workforce boards. For each, over half of providers indicated that personnel costs were their top spending category, followed by rent, mortgage, or utilities (25-31%). A marginally larger share of providers located in the Dallas and Alamo board areas reported goods and services as their top spending category. (See Supplemental Table 4 in Appendix for full expenditure data by workforce board.)
| Top expense category | Gulf Coast | North Central | Dallas | Alamo | Tarrant | Overall |
|---|---|---|---|---|---|---|
| Personnel costs | 58% | 62% | 57% | 56% | 61% | 59% |
| Rent/Mortgage/Utilities | 31% | 29% | 27% | 28% | 25% | 28% |
| Goods and services | 6% | 5% | 9% | 11% | 6% | 7% |
| Personal Protective Equipment | 2% | 2% | 2% | 2% | 3% | 2% |
| Purchases/updates to equipment and supplies | 2% | 1% | 2% | 2% | 3% | 2% |
| Other | 1% | 1% | 2% | 1% | 1% | 1% |
6 Appendix
Applicants and eligible providers by workforce board
| Supplemental Table 1. Applications by workforce board | ||||||
|---|---|---|---|---|---|---|
| Workforce board | All providers | Subsidy providers | ||||
| Total eligible | Number applied | Percent applied | Total eligible | Number applied | Percent applied | |
| Gulf Coast | 3435 | 2507 | 73% | 1479 | 1335 | 90% |
| North Central | 1386 | 1041 | 75% | 505 | 450 | 89% |
| Dallas | 1014 | 750 | 74% | 481 | 434 | 90% |
| Alamo | 990 | 758 | 77% | 481 | 420 | 87% |
| Tarrant | 913 | 714 | 78% | 479 | 414 | 86% |
| Capital Area | 584 | 411 | 70% | 273 | 246 | 90% |
| Rural Capital | 582 | 453 | 78% | 268 | 242 | 90% |
| Lower Rio Grande Valley | 480 | 403 | 84% | 367 | 362 | 99% |
| Borderplex | 321 | 265 | 83% | 259 | 225 | 87% |
| Central Texas | 296 | 210 | 71% | 206 | 150 | 73% |
| East Texas | 264 | 184 | 70% | 170 | 139 | 82% |
| Coastal Bend | 257 | 144 | 56% | 135 | 101 | 75% |
| Cameron County | 224 | 162 | 72% | 145 | 141 | 97% |
| South Plains | 206 | 157 | 76% | 120 | 110 | 92% |
| Panhandle | 177 | 114 | 64% | 101 | 75 | 74% |
| Heart of Texas | 170 | 119 | 70% | 102 | 95 | 93% |
| Permian Basin | 164 | 104 | 63% | 72 | 60 | 83% |
| Brazos Valley | 163 | 112 | 69% | 103 | 93 | 90% |
| West Central Texas | 155 | 115 | 74% | 86 | 81 | 94% |
| Southeast Texas | 147 | 122 | 83% | 96 | 88 | 92% |
| South Texas | 129 | 108 | 84% | 106 | 99 | 93% |
| North Texas | 121 | 86 | 71% | 68 | 57 | 84% |
| Deep East Texas | 106 | 65 | 61% | 71 | 57 | 80% |
| Golden Crescent | 104 | 54 | 52% | 50 | 37 | 74% |
| North East Texas | 91 | 73 | 80% | 56 | 51 | 91% |
| Texoma | 88 | 65 | 74% | 58 | 46 | 79% |
| Concho Valley | 83 | 67 | 81% | 51 | 47 | 92% |
| Middle Rio Grande | 76 | 50 | 66% | 38 | 31 | 82% |
| Total | 12726 | 9413 | 74% | 6426 | 5686 | 88% |
Expenditures table by provider type, subsidy status, and county classification
| Supplemental Table 2. Comparison of expenditures and top spending categories by provider type, subsidy status, and county classification | ||||||||
|---|---|---|---|---|---|---|---|---|
| Center | Home | |||||||
| Subsidy | Non-subsidy | Rural | Urban | Subsidy | Non-subsidy | Rural | Urban | |
| Reported expenditures | ||||||||
| Personnel costs | 94% | 96% | 95% | 94% | 69% | 65% | 70% | 66% |
| Rent/Mortgage/Utilities | 85% | 77% | 81% | 83% | 92% | 91% | 87% | 92% |
| Goods and services | 71% | 64% | 71% | 69% | 80% | 79% | 76% | 79% |
| Personal Protective Equipment | 70% | 66% | 69% | 69% | 84% | 82% | 82% | 83% |
| Purchases/updates to equipment and supplies | 61% | 58% | 58% | 61% | 78% | 78% | 69% | 79% |
| Parent tuition/copays | 25% | 17% | 23% | 22% | 19% | 15% | 14% | 16% |
| Mental health support | 13% | 12% | 11% | 13% | 14% | 13% | 11% | 13% |
| Other allowable expenses | 6% | 6% | 5% | 6% | 8% | 5% | 8% | 6% |
| Top expenditure category | ||||||||
| Personnel costs | 73% | 77% | 79% | 74% | 17% | 19% | 22% | 18% |
| Rent/Mortgage/Utilities | 20% | 16% | 11% | 20% | 53% | 51% | 44% | 53% |
| Goods and services | 4% | 4% | 6% | 4% | 14% | 15% | 22% | 14% |
| Other | 1% | 1% | 1% | 1% | 3% | 2% | 1% | 3% |
| Purchases/updates to equipment and supplies | 1% | 1% | 2% | 1% | 6% | 5% | 4% | 5% |
| Personal Protective Equipment | 1% | 1% | 1% | 1% | 7% | 7% | 8% | 7% |
Expenditures tables by workforce board
| Supplemental Table 3. Comparison of expenditures by workforce board | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Workforce board | N | Personnel costs | Rent, mortgage, or utilities | Personal Protective Equipment | Purchases or updates to equipment and supplies | Goods and services | Mental health support | Parent tuition or copays | Other allowable expenses |
| Gulf Coast | 2254 | 86% | 84% | 71% | 66% | 72% | 14% | 24% | 6% |
| North Central | 938 | 88% | 87% | 71% | 56% | 72% | 11% | 15% | 5% |
| Dallas | 692 | 88% | 89% | 80% | 71% | 75% | 13% | 25% | 8% |
| Alamo | 680 | 89% | 87% | 78% | 72% | 75% | 10% | 20% | 4% |
| Tarrant | 636 | 91% | 84% | 75% | 69% | 75% | 17% | 25% | 5% |
| Rural Capital | 405 | 74% | 83% | 53% | 48% | 58% | 9% | 14% | 4% |
| Lower Rio Grande Valley | 370 | 87% | 92% | 81% | 75% | 76% | 14% | 17% | 8% |
| Capital Area | 364 | 91% | 77% | 68% | 59% | 61% | 11% | 14% | 7% |
| Borderplex | 239 | 85% | 92% | 77% | 73% | 76% | 18% | 20% | 8% |
| Central Texas | 184 | 82% | 89% | 77% | 76% | 74% | 20% | 13% | 5% |
| East Texas | 167 | 86% | 82% | 76% | 66% | 75% | 17% | 23% | 5% |
| Cameron County | 152 | 83% | 91% | 76% | 70% | 71% | 12% | 19% | 11% |
| South Plains | 145 | 88% | 84% | 72% | 73% | 73% | 6% | 20% | 3% |
| Coastal Bend | 127 | 87% | 88% | 76% | 62% | 76% | 12% | 19% | 6% |
| Southeast Texas | 115 | 93% | 87% | 80% | 70% | 74% | 17% | 36% | 6% |
| Brazos Valley | 104 | 89% | 83% | 76% | 52% | 71% | 10% | 18% | 4% |
| Heart of Texas | 103 | 87% | 80% | 65% | 56% | 67% | 15% | 24% | 12% |
| West Central Texas | 99 | 85% | 83% | 61% | 52% | 72% | 8% | 19% | 11% |
| South Texas | 98 | 91% | 94% | 81% | 74% | 72% | 8% | 16% | 3% |
| Panhandle | 97 | 79% | 75% | 71% | 73% | 75% | 11% | 28% | 9% |
| Permian Basin | 89 | 89% | 74% | 62% | 52% | 55% | 8% | 15% | 3% |
| North Texas | 81 | 89% | 77% | 54% | 46% | 62% | 12% | 23% | 6% |
| North East Texas | 65 | 92% | 75% | 82% | 58% | 82% | 14% | 22% | 6% |
| Deep East Texas | 62 | 97% | 90% | 76% | 69% | 76% | 23% | 31% | 10% |
| Texoma | 60 | 85% | 88% | 75% | 62% | 73% | 15% | 23% | 5% |
| Concho Valley | 50 | 86% | 78% | 70% | 56% | 56% | 0% | 4% | 4% |
| Golden Crescent | 48 | 85% | 77% | 67% | 60% | 73% | 6% | 12% | 4% |
| Middle Rio Grande | 47 | 91% | 87% | 83% | 83% | 79% | 9% | 23% | 6% |
| Total | 8471 | 87% | 85% | 73% | 65% | 72% | 13% | 21% | 6% |
| Supplemental Table 4. Comparison of top expenditures by workforce board | |||||||
|---|---|---|---|---|---|---|---|
| Workforce board | N | Personnel costs | Rent, mortgage, or utilities | Goods and services | Purchases or updates to equipment and supplies | Personal Protective Equipment | Other |
| Gulf Coast | 2254 | 58% | 31% | 6% | 2% | 2% | 1% |
| North Central | 938 | 62% | 29% | 5% | 1% | 2% | 1% |
| Dallas | 692 | 57% | 27% | 9% | 2% | 2% | 2% |
| Alamo | 680 | 56% | 28% | 11% | 2% | 2% | 1% |
| Tarrant | 636 | 61% | 25% | 6% | 3% | 3% | 1% |
| Rural Capital | 405 | 56% | 35% | 5% | 2% | 1% | 0% |
| Lower Rio Grande Valley | 370 | 55% | 29% | 9% | 3% | 3% | 1% |
| Capital Area | 364 | 73% | 21% | 4% | 0% | 0% | 2% |
| Borderplex | 239 | 53% | 33% | 5% | 5% | 3% | 1% |
| Central Texas | 184 | 54% | 27% | 8% | 5% | 4% | 2% |
| East Texas | 167 | 67% | 21% | 7% | 2% | 1% | 2% |
| Cameron County | 152 | 44% | 43% | 5% | 3% | 3% | 1% |
| South Plains | 145 | 70% | 21% | 4% | 1% | 4% | 0% |
| Coastal Bend | 127 | 55% | 28% | 10% | 3% | 2% | 2% |
| Southeast Texas | 115 | 68% | 18% | 8% | 3% | 3% | 1% |
| Brazos Valley | 104 | 64% | 21% | 9% | 3% | 3% | 0% |
| Heart of Texas | 103 | 66% | 22% | 6% | 2% | 3% | 1% |
| West Central Texas | 99 | 57% | 19% | 13% | 2% | 7% | 2% |
| South Texas | 98 | 55% | 33% | 5% | 2% | 2% | 3% |
| Panhandle | 97 | 52% | 22% | 12% | 8% | 2% | 4% |
| Permian Basin | 89 | 73% | 17% | 6% | 1% | 0% | 3% |
| North Texas | 81 | 63% | 25% | 10% | 1% | 1% | 0% |
| North East Texas | 65 | 66% | 20% | 8% | 2% | 2% | 3% |
| Deep East Texas | 62 | 82% | 10% | 5% | 0% | 2% | 2% |
| Texoma | 60 | 55% | 30% | 13% | 0% | 0% | 2% |
| Concho Valley | 50 | 72% | 16% | 6% | 2% | 2% | 2% |
| Golden Crescent | 48 | 58% | 21% | 6% | 6% | 4% | 4% |
| Middle Rio Grande | 47 | 64% | 6% | 21% | 2% | 6% | 0% |
| Total | 8471 | 59% | 28% | 7% | 2% | 2% | 1% |