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Berks County, PA — 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. 51 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 — 0.71× the U.S. rate (between 0.71× and 0.86× 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. 29 ZIP cells in this county are withheld, 26 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

Below the U.S. rate   Berks County fast food — 71–86% of the U.S. rate

244 fast food are counted in Berks County — 4.7 per 10,000 people present (residents + daytime workers), 71% of the U.S. rate of 6.7.

On the comparable ZIP set (ZIPs with a published count in every year), the total has stayed roughly flat between 2015 and 2023 (236 → 238).

Measured supply density is highest in 19610 (Reading), 19605 (Reading), 19560 (Temple) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 19508 (Birdsboro), 19602 (Reading), 19604 (Reading).

BLS QCEW puts the latest county-wide count (2026 Q1) at 273 establishments, the freshest available signal.

Measured density: Berks County sits at 71% of the U.S. rate for fast food. 26 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 71% and 86% of the U.S. rate. Why. The highest measured density is in 19610 and 19605; the lowest measured density is in 19508 and 19602.

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
244–302
published count; upper bound counts each withheld ZIP cell as 2 (29 cells) (2023)
Per 10,000 present
4.7
residents + daytime workers
U.S. average
6.7
per 10,000 present
County index
0.71×
vs. U.S.
Latest quarter (QCEW)
273
2026 Q1 — county total
Residents
430,466
48 ZIPs with data
Workers
167,711
jobs located in county

Is the area growing?

Population
439,117
Census PEP, July 1 2024
Change since 2020
+2.4%
+10,424 people
Net migration 2024
+3,443
international +3,558, domestic −115
Jobs located here
176,751
LODES 2022, −4.5% since 2019

Berks County had an estimated 439,117 residents on July 1, 2024 — 2.4% more than in 2020 (+10,424). In the latest year it gained 3,833 people: births minus deaths +395, international migration +3,558, domestic migration −115. Components are published separately and may not sum exactly.

176,751 jobs were located in the county in 2022 (−4.5% since 2019), and 203,645 employed residents lived there (−0.0% 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
19518 Douglassville
+8.0%
ZIP losing residents
2015–19 → 2020–24
Change

No ZIP had a statistically significant decrease.

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
147
no paid employees (2024)
Receipts
$6.6M
published gross receipts
Receipts per business
$45K
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 1% since 2015

Number of fast food in Berks 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.

236
2015
248
2018
243
2020
246
2021
237
2022
238
2023

Highest measured density

ZIP
vs. U.S. average
Index
19610 Reading
185%
19605 Reading
150%
19560 Temple
142%
19526 Hamburg
108%
19609 Reading
105%
19543 Morgantown
105%
19611 Reading
102%
19607 Reading
91%
19530 Kutztown
91%
19606 Reading
90%
19510 Blandon
82%
19608 Reading
70%
19512 Boyertown
68%
19567 Womelsdorf
65%
19518 Douglassville
64%

Lowest measured density

ZIP
vs. U.S. average
Index
19508 Birdsboro
36%
19602 Reading
37%
19604 Reading
39%
19601 Reading
54%
19518 Douglassville
64%
19567 Womelsdorf
65%
19512 Boyertown
68%
19608 Reading
70%
19510 Blandon
82%
19606 Reading
90%
19530 Kutztown
91%
19607 Reading
91%
19611 Reading
102%
19543 Morgantown
105%
19609 Reading
105%
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
19523Geigertown Employment hub 41106 0–2 —
19536Lyon Station Destination 4668,668 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
19610Reading 16,58120,419 33 12.3 185% High density
19505Bechtelsville 3,1351,142 4 10.8 162% High density
19605Reading 21,41917,185 30 10.0 150% Above average
19560Temple 9,1372,810 10 9.5 142% Above average
19562Topton 2,947687 3 9.1 137% Above average
19547Oley 4,579926 4 7.9 119% Above average
19526Hamburg 11,5817,295 11 7.2 108% Above average
19609Reading 9,8743,152 8 7.0 105% Above average
19543Morgantown 6,4014,399 6 7.0 105% Above average
19611Reading 10,98613,137 12 6.8 102% Above average
19607Reading 24,04511,354 18 6.1 91% Below average
19530Kutztown 15,5735,267 11 6.0 91% Below average
19606Reading 35,85311,951 25 6.0 90% Below average
19510Blandon 8,0102,360 5 5.4 82% Below average
19608Reading 24,1787,447 13 4.7 70% Below average
19512Boyertown 15,7943,922 8 4.5 68% Below average
19567Womelsdorf 6,0571,628 3 4.4 65% Below average
19518Douglassville 16,8053,752 8 4.3 64% Below average
19601Reading 36,4799,911 15 3.6 54% Below average
19604Reading 30,1241,754 8 2.6 39% Far below average
19602Reading 18,4953,842 5 2.4 37% Far below average
19508Birdsboro 14,8713,434 4 2.4 36% Far below average
18056Hereford 1,48967 0–2 — — Not published
19503Bally 1,149959 0–2 — — Not published
19504Barto 5,335552 0–2 — — Not published
19506Bernville 7,108744 0–2 — — Not published
19507Bethel 3,5632,583 0–2 — — Not published
19511Bowers 3323 0–2 — — Not published
19516Centerport 17651 0–2 — — Not published
19522Fleetwood 14,1272,623 0–2 — — Not published
19523Geigertown 41106 0–2 — — Not published
19529Kempton 3,109236 0–2 — — Not published
19533Leesport 8,6484,488 0–2 — — Not published
19534Lenhartsville 1,970321 0–2 — — Not published
19536Lyon Station 4668,668 0–2 — — Not published
19538Maxatawny 6435 0–2 — — Not published
19539Mertztown 3,823303 0–2 — — Not published
19540Mohnton 11,9571,882 0–2 — — Not published
19541Mohrsville 4,367157 0–2 — — Not published
19544Mount Aetna 19976 0–2 — — Not published
19545New Berlinville 868131 0–2 — — Not published
19548Pine Forge —334 0–2 — — Not published
19550Rehrersburg 488239 0–2 — — Not published
19551Robesonia 4,7781,752 0–2 — — Not published
19554Shartlesville 338168 0–2 — — Not published
19555Shoemakersville 3,5771,463 0–2 — — Not published
19559Strausstown 302164 0–2 — — Not published
19564Virginville 26514 0–2 — — Not published
19565Wernersville 9,3022,132 0–2 — — Not published
19603Reading —324 0–2 — — Not published
19612Reading —4,110 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in Reading

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 Reading retail space →
Crexi
Free listings + market data
Browse Reading retail space →
CityFeet
Retail space for lease
Browse Reading 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 Berks 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 273 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.