Instead of ranking ZIP codes from healthiest to sickest, ask a different question: what kinds of places exist? Cluster every ZIP code on all 26 measures simultaneously — no demographics allowed in — and the algorithm lands on four archetypes. Demographics weren't used to build them, yet each cluster snaps onto a recognizable American landscape.
Four kinds of communities
ZIP centroids colored by cluster assignment
Each archetype's fingerprint
Bars show each measure's deviation from the U.S. ZIP-level norm (in standard deviations) — hover for details
Comfortable suburbs
118.7M people · 10,938 ZIP areas assigned
Affluent, college-educated suburban ZCTAs that sit below the national average on nearly every measure at once — the health advantages of money and place compound.
E.g. 19808 (New Castle County, DE) · 53132 (Milwaukee County, WI) · 60002 (Lake County, IL) · 61571 (Tazewell County, IL)
Young metro strivers
86.4M people · 3,726 ZIP areas assigned
Dense, young, diverse metro ZCTAs. Chronic disease is low — largely an age-structure effect — but loneliness, skipped checkups, and housing strain run well above average.
E.g. 94565 (Contra Costa County, CA) · 93722 (Fresno County, CA) · 93727 (Fresno County, CA) · 94533 (Solano County, CA)
Aging small towns
65.3M people · 12,876 ZIP areas assigned
Low-density, older small-town and rural ZCTAs. Chronic conditions sit moderately above average, consistent with an older population, while social needs stay near the norm.
E.g. 46902 (Howard County, IN) · 47421 (Lawrence County, IN) · 29671 (Pickens County, SC) · 46975 (Fulton County, IN)
Left-behind communities
38.3M people · 4,764 ZIP areas assigned
High-poverty ZCTAs, disproportionately Black and Southern, where chronic disease, behavioral risk, and health-related social needs are all elevated together.
E.g. 28352 (Scotland County, NC) · 72206 (Pulaski County, AR) · 71701 (Ouachita County, AR) · 70427 (Washington Parish, LA)
Fingerprint bars are standard deviations from the U.S. ZIP-level norm, in catalog order:Health outcomes → Mental & functional health → Health behaviors → Access & prevention → Health-related needs. Hover any bar for the measure.
The cluster that breaks the income story
Three of the four clusters line up with the deprivation axis: comfortable suburbs (119 million people) sit below the norm on nearly everything, aging small towns (65 million) sit moderately above, left-behind communities (38 million) far above. The fourth refuses to fit. Young metro strivers — 86 million people in dense, young, diverse ZIP codes — score better than the comfortable suburbs on cancer and heart disease, and dramatically worse on loneliness (+1.38 SD), skipped checkups (+1.36 SD), lack of insurance (+1 SD), and social support.
Much of the chronic-disease advantage is simply age structure — only 10.9% of their residents are 65+, versus 21.1% in the aging small towns. The social strain is not an age artifact. It is the second axis of American place-based health: being young and urban protects your arteries and starves your support network.
A fraction of the population, most of the burden
Left-behind communities hold 38 million people — the smallest of the four groups — yet they sit 1.71+ standard deviations above the norm on self-rated poor health and food insecurity alike, with median household income of about $46k against the suburbs' $96k. Every burden the atlas tracks, this cluster carries at once — the statistical portrait of compounding disadvantage.