Reason for Including as Additional Measure:
Median household income is a well-recognized indicator of income and poverty, which can compromise physical and mental health.[1,2] However, it is strongly correlated with children in poverty, which is already ranked, and therefore not included as a ranked measure.
Median Household Income is a Measure of Central Tendency
Median Household Income is the income where half of households in a county earn more and half of households earn less. Income, defined as “Total income,” is the sum of the amounts reported separately for: wage or salary income; net self-employment income; interest, dividends, or net rental or royalty income or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); public assistance or welfare payments; retirement, survivor, or disability pensions; and all other income. Receipts from the following sources are not included as income: capital gains; money received from the sale of property (unless the recipient was engaged in the business of selling such property); the value of income “in kind” from food stamps, public housing subsidies, medical care, employer contributions for individuals, etc.; withdrawal of bank deposits; money borrowed; tax refunds; exchange of money between relatives living in the same household; and gifts and lump-sum inheritances, insurance payments, and other types of lump-sum receipts.
Median Household Income is Created Using Statistical Modeling
Median Household Income is based on one year of survey data and is created using complex statistical modeling. Modeling generates more stable estimates for places with small numbers of residents or survey responses. There are also drawbacks to using modeled data. The smaller the population or sample size of a county, the more the estimates are derived from the model itself and the less they are based on survey responses. Models make statistical assumptions about relationships that may not hold in all cases. Finally, there is no perfect model and each model generally has limitations specific to their methods. For more detailed information on the modeling methodology please visit: https://www.census.gov/programs-surveys/saipe/technical-documentation/methodology/counties-states/county-level.html
This measure can be used to measure progress with some caveats. Modeled estimates have specific drawbacks with regard to their usefulness in tracking progress in communities. Modeled data are not particularly good at incorporating the effects of local conditions, such as health promotion policies or unique population characteristics, into their estimates. Counties trying to measure the effects of programs and policies on the data should use great caution when using modeled estimates. In order to better understand and validate modeled estimates, confirming this data with additional sources of data at the local level is particularly valuable.
Years of Data Used
Small Area Income and Poverty Estimates
The US Census Bureau, with support from other federal agencies, created the Small Area Income and Poverty Estimates (SAIPE) program to provide more current estimates of selected income and poverty statistics than those from the most recent decennial census. The main objective of this program is to provide updated estimates of income and poverty statistics for the administration of federal programs and the allocation of federal funds to local jurisdictions. These estimates combine data from administrative records, intercensal population estimates, and the decennial census, along with direct estimates from the American Community Survey, to provide consistent and reliable single-year estimates. These model-based single-year estimates are more reflective of current conditions than multi-year survey estimates. At the county level, SAIPE provides estimates on children ages 5-17 in families in poverty, children under age 18 in poverty, all people in poverty, and median household income. Estimates are created for school districts, counties, and states.
 Galea S, Tracy M, Hoggatt KJ, DiMaggio C, Karpati A. Estimated deaths attributable to social factors in the United States. AJPH. 2011;101(8):1456-1465.
 McCarty AT. Child poverty in the United States: A tale of devastation and the promise of hope. Soc. Compass. 2016;10(7):623-639.
To learn more, view our interactive model