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Pima County, AZ — Fast food Saturation

How many fast food exist per person present — residents plus daytime workers — by ZIP code, compared with the U.S. average. Establishment data: Census ZBP 2023. Population: ACS 2024 5-year. 63 ZIP codes analyzed.

Includes: Fast food · Quick-service restaurants · Takeout & delivery counters · Pizza delivery · Sandwich & burger chains. Counted together because official statistics use one 722513 code.

Measured density: Below average — 0.96× the U.S. rate (between 0.96× and 1.00× once withheld ZIP cells are counted)

Why a range: Census does not publish a ZIP-by-industry count when that ZIP has 0–2 businesses. 32 ZIP cells in this county are withheld, 14 of them with residents. Each could hold 0, 1, or 2 businesses: counting them all as 0 gives the low end, counting them all as 2 gives the high end — the data cannot say where the truth sits. The density range uses only the populated cells, since ZIPs without residents are excluded from per-person rates. How ranges work

In line with the U.S. rate   Pima County fast food — 96–100% of the U.S. rate

798 fast food are counted in Pima County — 6.4 per 10,000 people present (residents + daytime workers), 96% of the U.S. rate of 6.7.

On the comparable ZIP set (ZIPs with a published count in every year), the total has risen 24% between 2015 and 2023 (627 → 779). That set is smaller than today's county total. 2020–2021 were pandemic-distorted, and Census rounds counts, so small moves are within noise.

Measured supply density is highest in 85701 (Tucson), 85711 (Tucson), 85719 (Tucson) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 85756 (Tucson), 85641 (Vail), 85658 (Marana).

BLS QCEW puts the latest county-wide count (2026 Q1) at 623 establishments, the freshest available signal.

Measured density: Pima County sits at 96% of the U.S. rate for fast food. 14 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 96% and 100% of the U.S. rate. Why. The highest measured density is in 85701 and 85711; the lowest measured density is in 85756 and 85641.

This is a supply-side read: it counts existing fast food and the people present, not foot traffic, income, rent, or whether locals want more. Treat low density as a question to check, not an answer.

Fast food
798–862
published count; upper bound counts each withheld ZIP cell as 2 (32 cells) (2023)
Per 10,000 present
6.4
residents + daytime workers
U.S. average
6.7
per 10,000 present
County index
0.96×
vs. U.S.
Latest quarter (QCEW)
623
2026 Q1 — county total
Residents
1,072,121
45 ZIPs with data
Workers
336,499
jobs located in county

Is the area growing?

Population
1,080,149
Census PEP, July 1 2024
Change since 2020
+3.3%
+34,922 people
Net migration 2024
+12,394
international +8,351, domestic +4,043
Jobs located here
369,943
LODES 2022, +0.9% since 2019

Pima County had an estimated 1,080,149 residents on July 1, 2024 — 3.3% more than in 2020 (+34,922). In the latest year it gained 11,570 people: births minus deaths −873, international migration +8,351, domestic migration +4,043. Components are published separately and may not sum exactly.

369,943 jobs were located in the county in 2022 (+0.9% since 2019), and 398,246 employed residents lived there (+1.4% since 2019). LODES counts wage and salary jobs covered by unemployment insurance plus federal jobs; it excludes the self-employed and military, and counts jobs rather than unique people. 2019→2022 spans the pandemic, so read it as one change, not a trend.

Population and migration say whether the customer base is growing. They do not say whether people want another business of this type. Definitions and limits →  ·  Full county detail →

ZIP gaining residents
2015–19 → 2020–24
Change
85658 Marana
+39.8%
85641 Vail
+28.3%
85629 Sahuarita
+22.9%
ZIP losing residents
2015–19 → 2020–24
Change
85634 Sells
−23.3%

ACS 5-year estimates for 2015–2019 and 2020–2024. Only ZIPs with at least 2,000 residents in both windows and a change larger than the survey margin of error (90%) are listed — small ZIPs move a lot on paper without a real signal.

Nonemployer businesses (no paid employees)

Nonemployer businesses
195
no paid employees (2024)
Receipts
$8.3M
published gross receipts
Receipts per business
$43K
gross, not profit

Census Nonemployer Statistics counts businesses with no paid employees — a separate universe from the employer establishments counted above; a business is in one or the other, never both. They are not storefronts by definition: many are home-based, mobile, or part-time.

We show them beside the density index, not inside it. In categories such as nail and beauty salons, child care, and pet care, one-person businesses can outnumber employer establishments, so the employer-only count understates how many businesses exist. That is not evidence of higher demand.

Receipts are gross revenue reported for these businesses — not profit, and not the size of the local market. Census publishes this only at county level, so it is not shown on the ZIP map. See methodology.

Saturation map

Each ZIP area is shaded by its density of this business type per person present (residents + workers) vs. the U.S. average. Click any ZIP to zoom to its boundary, see its numbers, and switch to aerial imagery. Individual mapped shops appear as dots at street level — Show locations zooms you in to them (scroll or double-click to zoom).

Basemap:
Under 50% 50–100% 100–150% 150–250% 250%+ 0–2 (not published) / no data ZIP total (dot size) Mapped shop (OpenStreetMap, street level)

Map data © OpenStreetMap contributors, tiles by OpenFreeMap.

White dots are ZIP totals from the official Census count — the bigger the dot, the more fast food in that ZIP. They are aggregated, not individual shops. Turquoise dots are individual locations mapped in OpenStreetMap, shown only at street level; they are crowd-sourced and indicative, may be incomplete, and do not equal the official counts. Only the official ZIP totals feed the saturation index.

Market trend — up 24% since 2015

Number of fast food in Pima County across 2015–2023, on a consistent set of ZIP codes present in every year — so changes are real, not ZIP-boundary artifacts. 2015/2018 are pre-pandemic baselines; 2020/2021 are COVID-distorted.

627
2015
702
2018
694
2020
707
2021
731
2022
779
2023

Highest measured density

ZIP
vs. U.S. average
Index
85701 Tucson
228%
85711 Tucson
190%
85719 Tucson
180%
85712 Tucson
171%
85741 Tucson
160%
85714 Tucson
157%
85713 Tucson
142%
85715 Tucson
141%
85716 Tucson
138%
85704 Tucson
131%
85705 Tucson
129%
85745 Tucson
129%
85614 Green Valley
119%
85737 Tucson
106%
85710 Tucson
106%

Lowest measured density

ZIP
vs. U.S. average
Index
85756 Tucson
10%
85641 Vail
13%
85658 Marana
27%
85629 Sahuarita
40%
85718 Tucson
43%
85750 Tucson
45%
85653 Marana
48%
85739 Tucson
53%
85743 Tucson
56%
85748 Tucson
56%
85742 Tucson
59%
85746 Tucson
69%
85730 Tucson
69%
85749 Tucson
75%
85706 Tucson
89%
Low measured density is not evidence of opportunity. A ZIP with few fast food may simply lack foot traffic, retail space, or demand. We rank only residential and mixed ZIPs here; employment hubs and visitor destinations are listed separately below. ZIPs where Census did not publish a count (0–2 businesses) are not ranked: they may be the least served of all, but the data cannot tell 0 from 1 or 2. Verify those locally.

Employment hubs & destinations

These ZIPs have far more workers (or visitors) than residents, so their counts are driven by daytime and visitor demand — not a place to read "shortage" from resident numbers alone.

ZIPNeighborhoodType ResidentsWorkersFast foodIndex
85723Tucson Destination 2443,287 0–2 —

Scroll the table sideways to see all columns.

All ZIP codes

Click a column header to sort. Index = fast food per 10,000 people present (residents + 0.5×workers) ÷ the U.S. average. 100% = exactly average.

ZIPNeighborhood ResidentsWorkersFast food Per 10kIndexStatus
85701Tucson 5,4987,408 14 15.2 228% High density
85711Tucson 42,55823,824 69 12.7 190% High density
85719Tucson 51,83316,135 72 12.0 180% High density
85712Tucson 31,57122,712 49 11.4 171% High density
85741Tucson 33,67915,130 44 10.7 160% High density
85714Tucson 14,49814,969 23 10.5 157% High density
85713Tucson 46,43919,275 53 9.5 142% Above average
85715Tucson 19,1988,358 22 9.4 141% Above average
85716Tucson 32,9769,840 35 9.2 138% Above average
85704Tucson 35,21016,716 38 8.7 131% Above average
85705Tucson 54,70030,065 60 8.6 129% Above average
85745Tucson 36,9999,686 36 8.6 129% Above average
85614Green Valley 25,3817,321 23 7.9 119% Above average
85737Tucson 22,7855,110 18 7.1 106% Above average
85710Tucson 56,12517,797 46 7.1 106% Above average
85747Tucson 27,7536,918 21 6.7 101% Above average
85706Tucson 54,23626,512 40 5.9 89% Below average
85749Tucson 18,8432,361 10 5.0 75% Below average
85730Tucson 39,3993,478 19 4.6 69% Below average
85746Tucson 42,8355,877 21 4.6 69% Below average
85742Tucson 31,6133,130 13 3.9 59% Below average
85748Tucson 20,1032,376 8 3.8 56% Below average
85743Tucson 31,3006,912 13 3.7 56% Below average
85739Tucson 18,4782,402 7 3.6 53% Below average
85653Marana 23,5742,469 8 3.2 48% Far below average
85750Tucson 24,8863,162 8 3.0 45% Far below average
85718Tucson 28,12512,865 10 2.9 43% Far below average
85629Sahuarita 31,6683,364 9 2.7 40% Far below average
85658Marana 16,0511,782 3 1.8 27% Far below average
85641Vail 34,7521,412 3 0.8 13% Far below average
85756Tucson 37,70015,263 3 0.7 10% Far below average
85321Ajo 3,555406 0–2 — — Not published
85341Lukeville 3724 0–2 — — Not published
85601Arivaca 26880 0–2 — — Not published
85619Mount Lemmon 073 0–2 — — Not published
85622Green Valley 6,518699 0–2 — — Not published
85634Sells 5,038460 0–2 — — Not published
85645Amado 1,24994 0–2 — — Not published
85654Rillito 0343 0–2 — — Not published
85702Tucson —43 0–2 — — Not published
85707Tucson 581679 0–2 — — Not published
85708Tucson 4,31246 0–2 — — Not published
85709Tucson 094 0–2 — — Not published
85717Tucson —51 0–2 — — Not published
85721Tucson 099 0–2 — — Not published
85723Tucson 2443,287 0–2 — — Not published
85724Tucson 03,438 0–2 — — Not published
85726Tucson 0109 0–2 — — Not published
85728Tucson —29 0–2 — — Not published
85731Tucson —743 0–2 — — Not published
85732Tucson —122 0–2 — — Not published
85733Tucson —16 0–2 — — Not published
85734Tucson 4,79778 0–2 — — Not published
85735Tucson 10,718349 0–2 — — Not published
85736Tucson 4,219155 0–2 — — Not published
85738Catalina —59 0–2 — — Not published
85740Tucson —57 0–2 — — Not published
85744Tucson —597 0–2 — — Not published
85751Tucson —144 0–2 — — Not published
85752Tucson —42 0–2 — — Not published
85754Tucson —107 0–2 — — Not published
85755Tucson 18,5605,103 0–2 — — Not published
85757Tucson 21,259410 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in Tucson

The numbers above tell you how the market looks. To find a specific storefront, these marketplaces list available retail space for lease.

LoopNet
Largest commercial marketplace
Browse Tucson retail space →
Crexi
Free listings + market data
Browse Tucson retail space →
CityFeet
Retail space for lease
Browse Tucson retail space →

Open vacancy data (actual empty units) is only published by some cities; where it exists we show it directly. Listings above are third-party.

Census withholds some ZIP-by-industry cells to protect small businesses. 0–2 means the cell was not published (Census publishes industry counts only at 3+ per ZIP), so the ZIP is left unranked rather than counted as zero. ~ means the count is estimated from the broader industry group and can be off by a business or two.

Follow Pima County and fast food

When a data vintage changes or a section of this report is revised, we post it to a public update feed. No email address, no account, no tracking — and nothing is sent unless something actually changed.

Subscribe to updates (RSS) How these numbers are built →

Methodology & sources

Establishments. U.S. Census ZIP Code Business Patterns (ZBP 2023), NAICS 722513 — limited-service restaurants. Counts establishments with paid employees. ZBP is published annually with a ~2-year lag.

Fresh county signal. BLS QCEW (quarterly) is newer than ZBP — 2026 Q1 shows 623 establishments county-wide for this industry. It cannot be broken down by ZIP.

Population. U.S. Census American Community Survey 2024 5-year ZCTA population (table B01003). Workers are the ZIP's total employment from the same 2023 ZBP file.

Demand ("people present"). Demand comes from residents and daytime workers: residents + 0.5 × workers. This is the single documented assumption in the model and can be tuned.

Index. index = (ZIP establishments ÷ ZIP demand × 10,000) ÷ the U.S. average for this industry (6.67 per 10,000 present). It is a supply-side density measure; it does not capture income, rent, tourism, or whether locals actually want more.

Read the full methodology →  ·  Data sources & vintages →

BizGapMap — free, no-login small-business saturation reports for major U.S. counties. Built entirely from public U.S. Census, BLS, and IRS data (ZBP 2023, ACS 2024 5-year, PEP 2024, LODES, QCEW, IRS SOI). No forecasts, no revenue guesses — withheld cells are marked, and the few derived counts are labelled as estimates.