Frequently Asked Questions
What do the ADI values mean?
The ADI values on this website are provided in national percentile rankings from 1 to 100 at the census block group level. The percentiles are constructed by ranking the ADI from low to high for the nation and categorizing the census block groups/neighborhoods into groups corresponding to each 1% range of the ADI. Group 1 is the lowest ADI (least disadvantaged) and group 100 is the highest ADI (most disadvantaged). A census block group/neighborhood with a ranking of 1 indicates the lowest level of disadvantage within the nation (lowest exposure to adverse social exposome) and an ADI with a ranking of 100 indicates the highest level of disadvantage (highest exposure to adverse social exposome).
ADI values are also available in deciles from 1 to 10 for each individual state. The state deciles are constructed by ranking the ADI from low to high for each state alone without consideration of national ADIs. Again, group 1 is the lowest ADI and 10 is the highest ADI.
What methodology was used to create these ADI datasets?
The following article explains the underlying methodology that was used to create the ADI datasets:
See the ADI changelog for notations of additional minor, validated changes in ADI calculation methods made in response to evolutions in ACS data.
Why are some block groups missing ADI ranks?
When a census block group has less than 100 people, less than 30 housing units, more than 33% of the population living in group quarters, or census data labeled as N/A or missing in the core component variables, the ADI rank is replaced with a code describing the suppression reason. Three possible codes will appear in the ADI field: "PH" for suppression due to low population and/or housing, "GQ" for suppression due to a high group quarters population, and "PH-GQ" for suppression due to both types of suppression criteria. A code of "QDI" designates block groups without an ADI due to Questionable Data Integrity, stemming from missing data in the source ACS data.
How is the ADI used in research publications?
Use of the ADI is widespread in research. The following is a sampling of current papers using the ADI:
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Al-Aly, Z., Xie, Y. and Bowe, B., 2021. High-dimensional characterization of post-acute sequelae of COVID-19.Nature, 594(7862), pp.259-264.
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Durfey, S.N., Kind, A.J., Buckingham, W.R., DuGoff, E.H. and Trivedi, A.N., 2019. Neighborhood disadvantage and chronic disease management.Health services research, 54, pp.206-216.
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Goel, N., Hernandez, A., Thompson, C., Choi, S., Westrick, A., Stoler, J., Antoni, M.H., Rojas, K., Kesmodel, S., Figueroa, M.E. and Cole, S., 2023. Neighborhood disadvantage and breast cancer–specific survival. JAMA network open, 6(4), pp.e238908-e238908.
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Hamad, R., Penko, J., Kazi, D.S., Coxson, P., Guzman, D., Wei, P.C., Mason, A., Wang, E.A., Goldman, L., Fiscella, K. and Bibbins-Domingo, K., 2020. Association of low socioeconomic status with premature coronary heart disease in US adults. JAMA cardiology, 5(8), pp.899-908.
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Hunt, J.F., Buckingham, W., Kim, A.J., Oh, J., Vogt, N.M., Jonaitis, E.M., Hunt, T.K., Zuelsdorff, M., Powell, R., Norton, D. and Rissman, R.A., 2020. Association of neighborhood-level disadvantage with cerebral and hippocampal volume. JAMA neurology, 77(4), pp.451-460.
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Hunt, J.F., Vogt, N.M., Jonaitis, E.M., Buckingham, W.R., Koscik, R.L., Zuelsdorff, M., Clark, L.R., Gleason, C.E., Yu, M., Okonkwo, O. and Johnson, S.C., 2021. Association of neighborhood context, cognitive decline, and cortical change in an unimpaired cohort. Neurology, 96(20), pp.e2500-e2512.
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Kershaw, K.N., Magnani, J.W., Diez Roux, A.V., Camacho-Rivera, M., Jackson, E.A., Johnson, A.E., Magwood, G.S., Morgenstern, L.B., Salinas, J.J., Sims, M. and Mujahid, M.S., 2024. Neighborhoods and cardiovascular health: a scientific statement from the American Heart Association. Circulation: Cardiovascular Quality and Outcomes, 17(1), p.e000124.
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Kind, A.J. and Buckingham, W.R., 2018. Making neighborhood-disadvantage metrics accessible—the neighborhood atlas. The New England journal of medicine, 378(26), p.2456.
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Krzyzanowski, B., Searles Nielsen, S., Turner, J.R. and Racette, B.A., 2023. Fine particulate matter and Parkinson disease risk among Medicare beneficiaries. Neurology, 101(21), pp.e2058-e2067.
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Kurani, S.S., Heien, H.C., Sangaralingham, L.R., Inselman, J.W., Shah, N.D., Golden, S.H. and McCoy, R.G., 2022. Association of area-level socioeconomic deprivation with hypoglycemic and hyperglycemic crises in US adults with diabetes. JAMA Network Open, 5(1), pp.e2143597-e2143597.
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Powell, W.R., Buckingham, W.R., Larson, J.L., Vilen, L., Yu, M., Salamat, M.S., Bendlin, B.B., Rissman, R.A. and Kind, A.J., 2020. Association of neighborhood-level disadvantage with Alzheimer disease neuropathology. JAMA network open, 3(6), pp.e207559-e207559.
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Ross, C.E. and Mirowsky, J., 2001. Neighborhood disadvantage, disorder, and health. Journal of health and social behavior, pp.258-276.
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Shen, J., Fuemmeler, B.F., Sheppard, V.B., Bear, H.D., Song, R., Chow, W.H. and Zhao, H., 2022. Neighborhood disadvantage and biological aging biomarkers among breast cancer patients. Scientific Reports, 12(1), p.11006.
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Shour, A.R., Hamberger, L.K., Meurer, J., Kostelac, C. and Cassidy, L., 2022. Context matters: assessing the association between area deprivation and the severity of injury and types of domestic violence victimization among women. Journal of interpersonal violence, 37(23-24), pp.NP22352-NP22374.
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Triplett, R.L., Lean, R.E., Parikh, A., Miller, J.P., Alexopoulos, D., Kaplan, S., Meyer, D., Adamson, C., Smyser, T.A., Rogers, C.E. and Barch, D.M., 2022. Association of prenatal exposure to early-life adversity with neonatal brain volumes at birth. JAMA network open, 5(4), pp.e227045-e227045.
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Tsoy, E., Kiekhofer, R.E., Guterman, E.L., Tee, B.L., Windon, C.C., Dorsman, K.A., Lanata, S.C., Rabinovici, G.D., Miller, B.L., Kind, A.J. and Possin, K.L., 2021. Assessment of racial/ethnic disparities in timeliness and comprehensiveness of dementia diagnosis in California. JAMA neurology, 78(6), pp.657-665.
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Xiao, Y., Mann, J.J., Chow, J.C.C., Brown, T.T., Snowden, L.R., Yip, P.S.F., Tsai, A.C., Hou, Y., Pathak, J., Wang, F. and Su, C., 2023. Patterns of social determinants of health and child mental health, cognition, and physical health. JAMA pediatrics, 177(12), pp.1294-1305.
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Zuelsdorff, M., Larson, J.L., Hunt, J.F., Kim, A.J., Koscik, R.L., Buckingham, W.R., Gleason, C.E., Johnson, S.C., Asthana, S., Rissman, R.A. and Bendlin, B.B., 2020. The Area Deprivation Index: a novel tool for harmonizable risk assessment in Alzheimer's disease research. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 6(1), p.e12039.
How is the ADI used across the US?
See the ADI Use Case map (coming soon!) detailing uses of the ADI across the US.
What is the difference between a percentile and a decile?
A percentile splits the ADI scores into 100 equal sections, categorizing the individual block group/neighborhood, with those in the first percentile having the lowest exposure to adverse social exposome, and those in the hundredth having the most. A decile groups the ADI scores into 10 equal sections.
Percentiles are created using the ADI scores for the entire nation, and deciles are created for each state individually.
Do you have a 5-digit ZIP Code dataset available, or a ZCTA-level dataset?
No. 5-digit ZIP Codes are primarily used for mail delivery. Multiple studies demonstrate the substantial loss of exposome measure precision introduced when using 5-digit ZIP code geographies as opposed to core Census geographies. Such 5-digit ZIP code or ZCTA approaches may be convenient, but they introduce substantial error and the large geographic areas they represent do not align well with Census block groups. The ADI should not be used at any levels other than the core Census geographies for which it is validated, specifically the Census block group.
Those with interest in using a ZIP-based methodology may still employ the 9-digit ZIP Code crosswalk, which was built by our team to correspond directly to census block groups and accompanies the census block group level ADI. 9-digit ZIP Codes represent smaller geographic areas that can be more precisely matched to Census block groups.
"Employment of ZIP Code Tabulation Areas to link geographic data is a convenient but, ultimately, inferior method for this sort of assessment1. It results in relatively large geographic zones with linkages that can lead to less precise estimates, especially in areas in which concentrated poverty abuts more wealthy regions."
– Excerpt drawn directly from Kind et al., Health Affairs, Sept 15, 2016.
Why are some 9-digit ZIP Codes missing ADI ranks?
When a nine-digit ZIP Code file does not include ADI values, it is due to one of three conditions: A "P" indicates that the ZIP Code is a post office box and not geographically representative nor included within ACS metrics. A "U" indicates a unique ZIP Code, often assigned to businesses or large footprint entities that have large volumes of mail delivery and would also be omitted from the ACS. Lastly, a blank ADI value indicates that the conversion of the block group ADI score to ZIP+4 did not produce a match. These are most common in coastal areas where a generalized ZIP+4 may be outside of a block group or offshore.
What versions of the ADI are available?
The 2022 vintage ADI, constructed exclusively using the v4 methodology, the 2020 vintage ADI updated with the v4 methodologies, and the 2015 vintage ADI updated with the v4 methodologies are the only versions of the ADI currently available on the Neighborhood Atlas.
Can I request a different version of the ADI?
If you have a research question or need a different version of the ADI please fill out this form.
Who do I contact if I need help?
Please contact the Neighborhood Atlas team using our contact form.
I am having trouble creating an account or logging in.
The form to create an account is available on the home page. When you first create your account, you should receive a confirmation email. You will need to validate your email. If you cannot find the validation email, please check your spam folder. Otherwise, please request a new confirmation email.
If you have validated your email, using a different browser may be helpful. We have found that Chrome and Firefox work best; sometimes switching between the two also solves the problem. If you continue to have trouble, please contact the Neighborhood Atlas team.