ii Labs
Modeling U.S. Communities:

Use this demo to explore a model of people’s real, lived outcomes in the state of Washington.

This analytical methodology was developed by Interactive Impact Labs to evaluate dozens of socio-economic datasets (across a single state, even across the entire USA) and ask a higher-level question: where on the map will residents be experiencing a higher quality of life? And in what areas are residents suffering the worst lived experiences?

There are only a few commercial services that can map the hundreds of social measures taken by the US Census, the CDC, and other NGOs. These ‘data layers’ are overlapped, one by one, on a particular area of interest. Unfortunately, there are too many data layers for a single person to hold in their head: the old method does little to provide a synthesis. Likewise, it cannot readily provide comparisons across twenty (or two hundred) different areas, and it cannot provide comparisons on multiple factors at the same time.

The goal of ii Labs’ model is an ability to compare multiple geographies instantly, and to collapse the analysis into a summary that can be widely understood and shared. Scroll down below the map to see our baseline model of the social determinants of a healthy community, on four different axes. These four dimensions are subsequently combined into a single Overall Composite Score. Using these five numerical scores, a researcher can rapidly zero-in on communities that match their intended interest... and even discover other areas that had not been considered, having a similar summary profile.

The individual components to each score are also customizable in our client engagements.

Explore the Map:
eg., try: ‘South Tacoma’
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50.6
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Scores are relative to a national mean. For example, a hypothetical area that experienced exactly the national average on every data indicator would have an Overall composite score of 50.6 (slightly off from 50.0 due to statistical outliers.)

Overall Composite Score

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The Overall Composite is a score between 0 and 100 that is the sum of the four component indices (below), each of which attempt to measure various social determinants of a healthy community. All of these scores are centered around a mean value for the entire United States. For example, a hypothetical area that experienced exactly the national average on every data indicator would have an Overall composite score of 50. Thus, very low scores reveal places that are consistently experiencing outcomes below the national average, whereas those with very high scores are consistently enjoying the most beneficial outcomes in all of the United States.

  • Customizations: At a client’s request, the scores can alternately be centered around the mean value for one particular state of interest.

Educational Strength Index

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  •  1.1 Quality of Public Education

    This score attempts to summarize the current outcomes experienced in an area’s public education options. We have used these data indicators:

    • School district's student/teacher ratio USDOE – 2016

    • School Proficiency Index of 4th grade students HUD – 2015

    Customizations: These data indicators may be available, depending on a specific state's policies:

    • Graduation rate by school district State Dept of Education

  •  1.2 Access to Educational Aspirations

    This score attempts to quantify the community context in which minors grow up (e.g. adult role-models, students who may not perceive the option of higher education).

    • Pct of population aged 25+ with B.A. or above Census 5Yr ACS

    • Pct of youth aged 10-17 not enrolled in school Census 5Yr ACS

    • Pct of population aged 25+ who are not high school graduates Census Planning DB

Economic Strength Index

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  •  2.1 Socio-economic Outcomes

    Socio-economic outcomes attempt to quantify the current state of class privilege in an area.

    • Pct of youth aged 10-17 not enrolled in school Census 5Yr ACS

    • Gini Index of income inequality Census 5Yr ACS

    • Pct of population classified as below the poverty level Census Planning DB

    • Pct of children (age 0-17) classified below the poverty level Census Planning DB

    • Pct of children living under the poverty level, where both parents are foreign-born/or solo parent is foreign-born Census 5Yr ACS

    • Pct of households as Female householder, no husband present Census Planning DB

    • Probability of Incarceration: Fraction of children born in 1978-1983 birth cohorts with parents at the 25th percentile of the national income distribution who were incarcerated on April 1st, 2010 Opportunity Atlas

    • Median income in last 12 months for Women working other than Fulltime-Year-Round Census 5Yr ACS

    • Per Capita income in last 12 months Census 5Yr ACS

    • Pct of households receiving public assistance income Census Planning DB

    • Pct of households receiving food stamps/SNAP in the past 12 months Census 5Yr ACS

    • Pct of adult population (age 30+) who are Grandparents living with, and responsible for, own grandchildren <18 Census 5Yr ACS

    • Census tracts with Long Term Persistent Poverty, scored by pct change in their poverty rate 1990→2014 Census 5Yr ACS/Brown Univ.

  •  2.2 Economic Opportunities

    The Economic opportunities score attempts to quantify the local economic environment in which residents operate and pursue their livelihoods.

    • Official unemployment Rate BLS – 2017

    • Functional unemployment rate derived from Census 5Yr ACS

    • Pct change in number of jobs from 2007→2017 BLS QCEW

    • Jobs Proximity Index HUD – 2015

    • Pct of Form 1040 filers taking the earned income tax credit IRS

    • Average # usual hours worked in past 12 mo. for Workers aged 16-64 Census 5Yr ACS

    • Pct of 16-19 year olds who are not a high-school graduate and not working Census 5Yr ACS

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Pct of population aged 25+ w/ some college or higher who lived in same house 1 year ago (or moved within the same county) Census 5Yr ACS

    • Low transportation cost index HUD – 2015

  •  2.3 Occupational/Industry Diversity

    The Occupational/Industry diversity score attempts to categorize the variety and monetary reward of occupations in an area. All of these are measured at the county level:

    • Pct change Agriculture, Forestry, Fishing & Hunting jobs 2007→2017 BLS QCEW

    • Pct change Manufacturing jobs 2007→2017 BLS QCEW

    • Pct change Retail jobs 2007→2017 BLS QCEW

    • Pct change Healthcare jobs 2007→2017 BLS QCEW

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Pct of workers who are self-employed or unpaid family workers Census 5Yr ACS

Neighborhood Strength Index

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  •  3.1 Housing Security

    The Housing security score attempts to summarize various factors which contribute to the precariousness of long-term/stable housing in one's neighborhood.

    • Pct of Homeowner housing units having >2 occupants/room Census 5Yr ACS

    • Pct of Renter-occupied housing units having >2 occupants/room Census 5Yr ACS

    • Pct of Housing Units with a mortgage where owners are paying 30% or more of Household income on Owner Costs Census 5Yr ACS

    • Pct of Renter-occupied housing units where renter is paying 30% or more of Household income on Gross Rent Census 5Yr ACS

    • Pct of Housing Units lacking complete plumbing facilities Census Planning DB

    • Pct of Housing Units that are vacant Census Planning DB

    • Pct of Housing Units that are mobile-homes Census Planning DB

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Pct of Housing Units owner-occupied Census Planning DB

    • Pct of Housing Units renter-occupied Census Planning DB

    • Pct of Housing Units built on or after 2010 Census Planning DB

    • Loan to Income “Leverage” Ratio in Home Mortgages Home Mortgage Disclosure Act – (2010-15)

  •  3.2 Neighborhood Segregation

    Such an index is a commonly-used measure of community-level segregation within a county.

    • Residential segregation Index: Non-white/white Census 5Yr ACS

  •  3.3 Proximal Violence + Deaths of Despair

    This score attempts to characterize the context of violence and pressures for self-destruction in which residents operate. All of these are measured at the county level:

    • Number of reported violent crime offenses per 100K population FBI UCR – (2012-14)

    • Homicide rate per 100k population CDC – (2009-15)

    • Mortality rate from alcohol use disorders IHME – 2014

    • Mortality rate from drug use disorders IHME – 2014

    • Mortality rate from intentional self-harm IHME – 2014

    • Mortality rate from interpersonal violence IHME – 2014

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Change in mortality rate 2005→2014 from alcohol use IHME

    • Change in mortality rate 2005→2014 from drug use IHME

    • Change in mortality rate 2005→2014 from intentional self-harm IHME

Health Index

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  •  4.1 Health Outcomes

    Health outcomes attempt to quantify the current state of physical health in an area.

    • Pct of infants born with a low birth weight NCHS – (2008-14)

    • Teen birth rate per 1,000 female population, ages 15-19 NCHS – (2008-14)

    • Life expectancy at birth IHME – 2014

    • Mortality risk for children age 0-5 IHME – 2014

    • Mortality rate from Cancers: deaths per 100,000 IHME – 2014

    • Mortality rate from Cardiovascular diseases: deaths per 100,000 IHME – 2014

    • Proportion of Adults with Diagnosed & Undiagnosed Diabetes IHME – 2012

    • Obesity prevalence: Pct of adults that report a BMI of 30 or more CDC – 2013

    • Pct of population with one/more disability Census 5Yr ACS

    • Deaths due to injury per 100,000 Census 5Yr ACS

    • Motor vehicle crash deaths: mortality rate per 100,000 –CDC – (2009-15)

    • Pct of driving deaths with alcohol involvement Fatality Analysis Reporting System – (2011-15)

    • Any Mental Illness in the Past Year among ages 18+ SAMHSA – (2014-16)

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Mortality risk for people age 5-25 IHME – 2014

    • New diagnoses of HIV CDC – 2016

    • HIV prevalence rate among ages 13-24 CDC – 2015

  •  4.2 Structural Health

    A Structural Health score attempts to quantify the level at which residents have ready access to resources that sustain health.

    • Pct of population with no health insurance coverage Census Planning DB

    • Pct of population with Public health insurance Census 5Yr ACS

    • Child food insecurity rate Feeding America – 2016

    • Medically Underserved Areas (MUA) & Populations (MUP) designation HRSA

    • Tracts with Low access to supermarkets/groceries USDA – 2015

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Disparity in HIV prevalence rate between NonWhite and White persons CDC – 2015

    • Environmental health index score: potential exposure to harmful toxins HUD – 2015

    • Pct of students who receive free/reduced price lunches USDOE – 2016

  •  4.3 Health Behaviors

    The Health Behaviors score attempts to summarize the level at which residents participate in behaviors that promote their own health.

    • Marijuana Use in the Past Year: ages 12+ SAMHSA – (2014-16)

    • Cocaine Use in the Past Year: ages 12+ SAMHSA – (2014-16)

    • Heroin Use in the Past Year: ages 12+ SAMHSA – (2014-16)

    • Cigarette Use in the Past Month: ages 12+ SAMHSA – (2014-16)

    • Alcohol Use in the Past Month: ages 12+ SAMHSA – (2014-16)

    • Alcohol Use Disorder in the Past Year: ages 12+ SAMHSA – (2014-16)

    • Pct of adults (age 20+) reporting no Leisure-time Physical Activity CDC – 2013

    Customizations: These data indicators can also be incorporated at our client’s request:

    • Underage Alcohol Use in the Past Month: (ages 12-20) SAMHSA – (2014-16)

A note about granularity:

A number of data is collected at the county level, especially government economic data and many health indicators. County-wide data is useful for comparing the difference across states, and/or urban areas against rural ones, but it is far too generalized to illuminate the variances within individual neighborhoods.

ZIP codes are often used to organize marketing and consumer data, but not commonly used for socio-economic measures. This is because ZIP codes are fluid over time (subject to changes in postal routes) and generally regarded as neither a precise nor stable unit of measure.

Most of the data of the US Census is published according to Census tract, which have precise boundaries defined by the government, usually attempting to encompass about 4000 people. Tracts fit neatly inside counties, which makes their data compatible using statistical techniques. Furthermore, most urban areas have dozens of Census tracts (or more), providing a granularity to understand the trends within a city. There are some 73,000 tracts in the United States.

Better still are data reported as Census block groups, which are smaller areas attempting to encompass around 1,500 people. However, the government does not release all data at the level of block group, due sometimes to the statistical sampling involved, or when it becomes difficult to ensure the anonymity of its residents. Block groups are much more fine-grained; there are some 217,000 block groups in the United States.

ZIP codes are relatively large areas, and even larger outside of cities. For example, our map pinpoints MANY lived experiences within Spokane’s ZIP code 99202.

Because about 25% of the data indicators we utilize are reported at the block group level, our final index scoring even distinguishes the nuanced differences inside of a single Census tract.