Statistics

Restaurant cuisine statistics

Key U.S. restaurant cuisine stats on Asian, Mexican, and local market patterns.

Restaurant cuisine statistics at a glance

Restaurant cuisine mix is easier to talk about in broad labels than in hard numbers, but the statistics below make the shape of the market visible.

The picture is not just about what diners order. It is also about where cuisines cluster, how menus are composed, which regions are saturated, and how restaurant formats vary by category. The data set here combines national, county, state, local-market, and menu-level findings, so the result is a practical map of restaurant cuisine statistics rather than a single narrow trend.

Quick takeaways

  • Asian and Mexican food are both deeply embedded in the U.S. restaurant landscape, but they appear differently across states and counties.
  • County coverage is often broader than people expect: 73% of all U.S. counties have at least one Asian restaurant, and 85% have at least one Mexican restaurant (Pew Research Center 2023 Asian restaurants analysis; Pew Research Center 2024 Mexican restaurants analysis).
  • Category concentration is real. Chinese food is the largest share among Asian restaurants at 39%, while Japanese is 28% and Thai is 11% (Pew Research Center 2023 Asian restaurants analysis).
  • Mexican restaurants are heavily concentrated in a handful of states: 51% of all Mexican restaurants are in California, Texas, Florida, New York, or Illinois (Pew Research Center 2024 Mexican restaurants analysis).
  • Local menus can look very different from national counts. In Los Angeles County, restaurant cuisine shares are spread across American/Southern, Asian, Latino, coffee-bakery-dessert, burger, pizza, sandwich-deli, and European categories (UCLA/Los Angeles County public health study).

Table of contents

How restaurant cuisine statistics are distributed

The most useful way to read restaurant cuisine statistics is to separate them into four layers.

First are national share figures, which tell you how common a cuisine is among all restaurants. Second are geographic concentration figures, which show whether a cuisine is widespread or clustered in a few states and counties. Third are format figures, which explain whether a cuisine tends to appear as fast food, casual dining, or multi-cuisine operations. Fourth are menu and nutrition figures, which show how cuisine labels connect to the content and behavior of restaurants themselves.

That layered view matters because the same cuisine can be common nationally and still uneven geographically. It can also be common in a county without being common in every neighborhood. The statistics in this dataset repeatedly show that restaurant cuisine is not a flat market. It is a pattern of concentration, dispersion, and overlap.

At-a-glance comparison

TopicStatisticSource label
Asian restaurants among all U.S. restaurants12%Pew Research Center 2023 Asian restaurants analysis
Mexican restaurants among all U.S. restaurants11%Pew Research Center 2024 Mexican restaurants analysis
U.S. counties with at least one Asian restaurant73%Pew Research Center 2023 Asian restaurants analysis
U.S. counties with at least one Mexican restaurant85%Pew Research Center 2024 Mexican restaurants analysis
Chinese restaurants in every U.S. state100% state coveragePew Research Center 2023 Asian restaurants analysis
Mexican restaurants rated one dollar sign on Yelp61% of those with pricing dataPew Research Center 2024 Mexican restaurants analysis

That table captures a core theme: restaurant cuisine statistics are not just about popularity. They are also about access, location, and the structure of the market.

Asian restaurant patterns

Asian food accounts for 12% of all restaurants in the United States (Pew Research Center 2023 Asian restaurants analysis). That share is large enough to be a major category on the national restaurant map, but the composition within the category is even more revealing.

Chinese restaurants make up 39% of Asian restaurants in the U.S., Japanese restaurants make up 28%, Thai restaurants make up 11%, Indian restaurants make up 7%, and Filipino restaurants make up 1% (Pew Research Center 2023 Asian restaurants analysis). Put simply, the term “Asian restaurant” covers a very uneven mix of cuisines. One cuisine category dominates while others are much smaller.

This is one reason restaurant cuisine statistics are useful for menu planning, market research, and location strategy. A broad cuisine label can conceal a lot of variation. In this dataset, Chinese and Japanese together account for a large share of Asian restaurants, while Thai and Indian contribute smaller but still meaningful slices. Filipino restaurants, by contrast, are comparatively rare as a share of Asian restaurants.

Geographic spread of Asian restaurants

Coverage across the country is broader than the category split alone might suggest. 73% of all U.S. counties have at least one Asian restaurant (Pew Research Center 2023 Asian restaurants analysis). Chinese restaurants are found in every U.S. state and in 70% of all U.S. counties (Pew Research Center 2023 Asian restaurants analysis). Japanese restaurants are present in 45% of U.S. counties, Thai restaurants are present in 33%, and about one-fifth of U.S. counties have Vietnamese restaurants or Indian restaurants (Pew Research Center 2023 Asian restaurants analysis).

At the smaller end, fewer than 10% of U.S. counties have Filipino, Pakistani, Mongolian, or Burmese restaurants (Pew Research Center 2023 Asian restaurants analysis). That gap matters. It shows that even inside one broad regional category, some cuisines are distributed much more widely than others.

A useful way to read this is:

  • Chinese cuisine is the widest-reaching Asian category in the dataset.
  • Japanese and Thai have substantial county presence but less than Chinese.
  • Vietnamese and Indian cuisines appear in a moderate share of counties.
  • Several other Asian cuisines are much more localized.

Five-state concentration

Another concentration pattern appears at the state level. 55% of U.S. Asians live in five states: California, New York, Texas, New Jersey, and Washington (Pew Research Center 2023 Asian restaurants analysis). Those same five states contain 45% of all Asian restaurants (Pew Research Center 2023 Asian restaurants analysis).

That does not mean Asian restaurants are absent elsewhere. Instead, it shows that population concentration and restaurant concentration overlap in major ways, but not perfectly. The restaurants are widely distributed enough to show up in most counties, while still clustering strongly in a few states.

Multi-origin Asian restaurants

The dataset also includes restaurants that combine cuisines from more than one Asian origin group. Only 9% of Asian restaurants in the U.S. offer cuisines from multiple Asian origin groups (Pew Research Center 2023 Asian restaurants analysis). Among those multi-origin restaurants, 36% combine Chinese and Japanese food, 18% combine Chinese and Thai food, 15% combine Japanese and Thai food, and 10% combine Japanese and Korean food (Pew Research Center 2023 Asian restaurants analysis).

That pattern suggests that fusion or hybridization exists, but it is not the dominant structure of the category. Most Asian restaurants are still organized around a primary cuisine label rather than a blended one.

Mexican restaurant patterns

Mexican restaurants account for 11% of all restaurants in the United States (Pew Research Center 2024 Mexican restaurants analysis). Like Asian restaurants, they are a major national category. Unlike many categories that are visible only in certain metros, Mexican restaurants appear in 85% of all U.S. counties (Pew Research Center 2024 Mexican restaurants analysis).

That county coverage is extremely broad. It means the category is not only urban or regional. It is present across the country in a way that makes it one of the most geographically accessible major restaurant categories.

State and county concentration

The state concentration figures are equally important. 22% of all Mexican restaurants are in California and 17% are in Texas (Pew Research Center 2024 Mexican restaurants analysis). Taken with Florida, New York, and Illinois, the top five states contain 51% of all Mexican restaurants in the U.S. (Pew Research Center 2024 Mexican restaurants analysis).

Within those states, the concentration can become even sharper. 30% of California’s Mexican restaurants are in Los Angeles County (Pew Research Center 2024 Mexican restaurants analysis). In Texas, 17% are in Harris County, 9% are in Bexar County, and 9% are in Dallas County (Pew Research Center 2024 Mexican restaurants analysis).

That is a strong reminder that state totals can hide very dense county-level clustering. A cuisine can be widespread in the national sense and still be highly concentrated inside a few large counties.

Share of all restaurants by state

Mexican restaurants account for 22% of all restaurants in New Mexico, 20% in Texas, 18% in Arizona, and 17% in California (Pew Research Center 2024 Mexican restaurants analysis). In 10 U.S. counties, Mexican restaurants account for more than one-third of all restaurants (Pew Research Center 2024 Mexican restaurants analysis).

That level of penetration is notable because it shows Mexican food as more than a niche category. In several states, it is one of the defining restaurant types in the overall dining landscape.

Format and pricing

Mexican restaurants also have a distinct business-format profile. 22% are fast food restaurants, 12% specialize in tacos, 8% are food trucks or carts, and 6% offer Tex-Mex food (Pew Research Center 2024 Mexican restaurants analysis).

Pricing data adds another layer. 61% of Mexican restaurants with pricing data are rated one dollar sign on Yelp, and fewer than 1% have a three- or four-dollar-sign Yelp rating, totaling 251 restaurants (Pew Research Center 2024 Mexican restaurants analysis).

That combination points to a category that is often value-oriented and accessible. It also shows why restaurant cuisine statistics should be read alongside business-model statistics rather than in isolation.

Overlap with other Hispanic or Latino cuisines

The category boundaries are not perfectly sealed. 2% of U.S. restaurants serve Hispanic or Latino cuisine other than Mexican (Pew Research Center 2024 Mexican restaurants analysis). Among related restaurants, 38% of Salvadoran restaurants and 25% of Honduran restaurants in the U.S. also serve Mexican food, while only 3% of Mexican restaurants also serve other kinds of Hispanic or Latino food (Pew Research Center 2024 Mexican restaurants analysis).

This is a useful asymmetry. It suggests that Mexican cuisine often acts as a secondary or companion category for some other Hispanic or Latino restaurants, but Mexican restaurants themselves are less likely to broaden into other Hispanic or Latino types.

Local market concentration

National and county-level data can still miss the texture of local restaurant economies. The Los Angeles County data in this set gives a more detailed view.

In Los Angeles County, 18.4% of restaurants serve American/Southern cuisine, 18.3% serve Asian cuisine, 15.5% serve Latino cuisine, 13.2% serve coffee-bakery-dessert cuisine, 8.0% serve burger cuisine, 7.0% serve pizza cuisine, 6.5% serve sandwich or deli cuisine, 6.3% serve European cuisine, and 6.1% serve other cuisines (UCLA/Los Angeles County public health study).

That spread is valuable because it shows how a major county can host a very diverse restaurant ecosystem without any single cuisine fully dominating the market. The shares are close enough that several categories compete for attention.

Business structure in Los Angeles County

The same study shows that 62.2% of restaurants are independent single-location businesses, while 26.5% are large chains by national location count (UCLA/Los Angeles County public health study). By service style, 39.4% are quick service and 26.7% are casual dining (UCLA/Los Angeles County public health study).

Two practical observations follow from those numbers:

  • Independence is still the majority model, even in a large and competitive county market.
  • Fast service and casual dining together cover a substantial share of the restaurant base, which helps explain how cuisine mix and service format interact in local food environments.

The study also reports an average of 94.4 restaurants per neighborhood and 2.3 restaurants per 1,000 residents in Los Angeles County (UCLA/Los Angeles County public health study). Those figures are useful because they translate restaurant density into neighborhood-scale exposure rather than just citywide totals.

Restaurant cuisine statistics are not only about where restaurants are located. They also show what kinds of items and operations dominate a menu system.

Among U.S. chain restaurants, 47% of menu items came from full-service restaurants, 43.3% came from fast-food restaurants, and 9.7% came from fast-casual restaurants (PMC11757062). In large UK chain restaurants, 36.72% of menu items were from family or sit-down restaurants, 31.44% were from cafes, 28.95% were from Western-style fast-food restaurants, and 2.89% were from Asian-style fast-food restaurants (PMC8718418).

These menu-mix statistics are not the same thing as restaurant counts. But they are useful because they show where menu volume is concentrated. A cuisine or service model can produce a large share of menu items even if it is not the majority of outlets.

Nutrition labeling and cuisine type

One U.S. restaurant menu labeling study found that burger restaurants had 7.16 times the odds of reporting nutrition information compared with American restaurants, sandwich restaurants had 7.61 times the odds, fast casual restaurants had 3.06 times the odds compared with fast-food restaurants, and upscale restaurants had 0.21 times the odds compared with fast-food restaurants (PMC10271328).

That pattern suggests that cuisine category and service category can influence transparency behavior. The numbers do not say that every restaurant in a category behaves the same way, but they do indicate a strong relationship between format and reporting likelihood.

What the comparisons suggest

When you put the data points together, a few themes become clear.

First, restaurant cuisine in the U.S. is both widespread and uneven. Asian and Mexican food are common across the country, yet the exact mix inside each category is very different (Pew Research Center 2023 Asian restaurants analysis; Pew Research Center 2024 Mexican restaurants analysis).

Second, county coverage is often broader than the state-level concentration might imply. Chinese restaurants are in every U.S. state, Mexican restaurants are in 85% of counties, and Asian restaurants are in 73% of counties (Pew Research Center 2023 Asian restaurants analysis; Pew Research Center 2024 Mexican restaurants analysis).

Third, the most important market signals often come from combinations of metrics rather than single statistics. A cuisine’s national share, county coverage, state concentration, format split, and pricing profile together tell a more complete story than any one of those measures alone.

Fourth, local markets can look very different from national averages. Los Angeles County shows a broad and balanced cuisine mix, while the county-level and state-level concentration figures for Asian and Mexican restaurants show how quickly the national picture can tilt toward geographic clustering (UCLA/Los Angeles County public health study; Pew Research Center 2023 Asian restaurants analysis; Pew Research Center 2024 Mexican restaurants analysis).

If you are using restaurant cuisine statistics to analyze competition, choose locations, compare menu strategies, or understand dining access, the safest reading is to keep all four layers in view: national share, geographic spread, format structure, and menu composition. The numbers in this dataset show that cuisine categories are not just labels. They are market structures.

Written by

tommyskitchenandcatering.com Editorial Team

Editorial team

tommyskitchenandcatering.com publishes practical how-to guides and educational articles with clear steps and useful context.