Following the Money: Do Block Grant Resources Reach Rural Communities?

Research center:
Lead researcher:
Contact:
Project funded:
September 2021
Anticipated completion date:
August 2022

The overarching goal of this project is to document the distribution of block grant resources from federal agencies through states to local communities, particularly rural communities. We will work closely with the Federal Office of Rural Health Policy (FORHP) to identify two or three block grant programs for inclusion. The project will primarily consist of two sets of analyses. First, we will conduct a secondary data analysis to explore the distribution of block grant resources based on multiple dimensions of state-level rurality across all 50 states. We will further examine the relationships between resource allocation and state-level structural and demographic characteristics, including by race and ethnicity. State-level data from multiple sources will be combined to create a national dataset for the analysis.

Key sources include:

  • Documentation of funding amounts allocated to each state for selected block grant programs (2018, 2019)
  • American Community Survey data (e.g., state-level data on indicators such as percentage of population below the poverty level, percentage of state population who is non-White, and percentage of state rural population who is non-White)
  • U.S. Census Bureau data on indicators such as state-level population estimate and population density
  • Information on state public health governance structure and health agency structure from Association of State and Territorial Health Officials' 2019 Profile.

Additional secondary data will be integrated as appropriate, such as state-level mortality data available through the National Vital Statistics System. Second, we will conduct a case study analysis using quantitative and qualitative methods to explore the distribution of block grant resources from states to the local level, comparing distributions and allocation strategies between rural versus non-rural jurisdictions, in up to six states. We will apply a data-driven approach to purposefully select states. For each selected state, we will request quantifiable information on the distribution of block grant funding from the state to local levels, comparing urban and rural distributions using Rural-Urban Community Area (RUCA) code definitions. These data will be supplemented through structured interviews with key informants in each state. We will combine the quantitative results and qualitative findings to generate a robust understanding of the dynamics of federal resource distribution in local communities.

We will test the hypotheses listed below, with analyses to include per capita funding as appropriate.

  1. The amount of block grant resources allocated to states may differ by state-level rurality, public health governance structure (i.e., centralized/decentralized/mixed/shared), state health agency structure (i.e., freestanding or part of combined health and human services agency), and/or demographic characteristics.
  2. The amount of block grant resources allocated from states to local jurisdictions may differ by rurality, local public health governance, state health agency structure, and/or demographic characteristics.
  3. Block grant resources will be allocated disproportionately to non-rural communities.
  4. The allocation of block grant resources to local communities will vary by the total amount of block grant resources allocated to states, with smaller block grants more likely to skew towards non-rural communities.

In addition to the secondary data analysis and case study analysis, we will conduct a targeted and rigorous review of the Notice of Funding Opportunities (NOFOs; 2018, 2019) for block grant programs (2018, 2019). We will again work closely with FORHP to select block grant programs for inclusion and secure copies of the NOFOs for review. Findings will guide the development of recommendations for how NOFOs could be improved to promote equitable distribution of block grant resources to rural populations.