Counts of people experiencing homelessness from two sources. PIT refers to the annual Point-in-Time count done in January each year. HMIS is a unique count of shelter users over the calendar year from the Homelessness Management Information System (HMIS).

Count of lobby visits for a cash or food interview each month with two timeliness measures.

Participant data for children participating in Children's Services programs. Cells with numbers smaller than six were removed to protect individual privacy.

Financial Assistance Services expenditures broken out by service area and personnel and administrative costs and contracted and other service costs.

Participant information on people served by Aging and Disability Services that includes Medial Assistance Waiver case management and Rule 185 non-waiver case management.

Program participant information on people served in Financial Assistance programs, such as cash, food, and medical assistance as well as the Family Homelessness Prevention and Assistance Program.

Participant data on Adult Mental Health Programs. When there were less than six people in a racial/ethnic group, that cell was left blank to protect individual privacy. Targeted Case Management includes services provided by Ramsey County and services contracted for with community providers.

This data displays the percentage of children under age 18 living in poverty for the years 2012-2016 by three geographies: Minnesota, Ramsey County and Saint Paul. Among these regions, Saint Paul has the highest percentage of children in poverty at 30.5 percent in 2016, which has decreased from 33.6 percent in 2012. Footnote 6.

Premature death rate measures mortality by counting deaths at earlier ages more than deaths at later ages. For example, when a person dies at 20, this death contributes 55 years of potential life lost. In contrast, when a person dies at age 70, this death contributes only five years of potential life lost to a county. For our purposes, premature deaths occur before age 75. Counties with older populations are more likely to have higher crude premature death rates than counties with younger populations. Therefore, when age-adjusted, we remove the effect of differently aged populations as a risk factor for premature death. This allows us to make a fair comparison of premature death rates across counties.

Financial Assistance Services revenue with local levy dollars and revenue from state, federal, and other sources.