Nutritional values, including Calories and Micro-nutrients from six of the largest and most popular fast food restaurants:

• McDonald's
• Burger King
• Wendy's
• Kentucky Fried Chicken (KFC)
• Taco Bell
• Pizza Hut

Attributes include: Calories, Calories from Fat, Total Fat, Saturated Fat, Trans Fat, Cholesterol, Sodium, Carbs, Fiber, Sugars, Protein, and Weight Watchers Points (where available).

This statistic shows the consumers choosing healthy options at fast-food and fast casual restaurants in the United States as of June 2014. During the survey, ** percent of respondents said they usually look for healthy options at fast-food restaurants.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). This indicator is based on caregiver report. A child is considered to have weekly fast food consumption if they eat any food, including meals and snacks, from a fast food restaurant, such as McDonald’s, Taco Bell, KFC, or another similar type of place at least 1 time per week.Fast food consumption is associated with increased intake of calories, fat, and sodium, as well as with poor diet quality in children and adolescents. Poor diet has contributed to our current obesity epidemic and is a major risk factor for heart disease, diabetes, cancer, and many other chronic health conditions.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This is a list of 10,000 fast food restaurants provided by Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more.

Note that this is a sample of a large dataset. The full dataset is available through Datafiniti.

What You Can Do With This Data

You can use this data to rank cities with the most and least fast food restaurants across the U.S. E.g.:

• Cities with the most and least McDonald's per capita
• Fast food restaurants per capita for all states
• Fast food restaurants with the most locations nationally
• Major cities with the most and least fast food restaurants per capita
• Small cities with the most fast food restaurants per capita
• States with the most and least fast food restaurants per capita
• The number of fast food restaurants per capita

Original Data

Acknowlegement

Foto von Haseeb Jamil auf Unsplash

The Allegheny County Health Department has generated this list of fast food restaurants by exporting all chain restaurants without an alcohol permit from the County’s Fee and Permit System. A chain restaurant defined by the County is any restaurant that has more than one location in the County. Chain restaurants capture both local and national chains (including locally owned national chains) so long as there is one or more establishments in operation within the County.

Respondents from the U.S. generally considered fresh foods as the healthiest category overall. Over ** percent of them picked the category among their top three. The fast food category was most commonly picked among the ***** least healthy picks.

SUMMARYThe number of fast food outlets (as of 31/12/2017) per 1000 population. This statistic is reported at the ward level, except in locations where ward-level data was unavailable. In these instances, district-level data was used to fill in the data gaps.For a full description of the establishments included as ‘fast food outlets’, see: Fast food outlets: density by local authority in England - GOV.UK (www.gov.uk). Note: Public Health England states this is unlikely to be a definitive list of all fast food outlets, but it gives a good estimate.DATA SOURCESNumber of fast food outlets per ward or district: © Public Health England. Population data: Mid-2017 (June 30) Population Estimates for Wards in England and Wales. © Office for National Statistics licensed under the Open Government Licence v3.0. © Crown Copyright 2018.Administrative boundaries: Boundary-LineTM: Contains Ordnance Survey data © Crown copyright and database right 2021. Contains public sector information licensed under the Open Government Licence v3.0.COPYRIGHT NOTICE© Public Health England; © Office for National Statistics licensed under the Open Government Licence v3.0. © Crown Copyright 2018.; Contains Ordnance Survey data © Crown copyright and database right 2021. Contains public sector information licensed under the Open Government Licence v3.0. Data edited for publishing by Ribble Rivers Trust.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

The Johns Hopkins Center for a Livable Future (CLF) obtained the food permit list from the Baltimore City Health Department in August 2011, which includes all sites that sell food, such as stores, restaurants and temporary locations such as farmers' market stands and street carts. The restaurants were grouped into three categories, including full service restaurants, fast food chains and carryouts. Carryout and fast food chain restaurants were extracted from the restaurant layer and spatially joined with the 2010 Community Statistical Area (CSA) data layer, provided by BNIA-JFI. The prepared foods density, per 1,000 people, was calculated for each CSA using the CSA's population and the total number of carryout and fast food restaurants, including vendors selling prepared foods in public markets, in each CSA. Source: Johns Hopkins University, Center for a Livable FutureYears Available: 2011, 2013, 2018, 2019

According to a survey conducted in May 2023, around ** percent of respondents in Vietnam stated that high price was the main reason they did not choose fast food for a meal. Meanwhile, about ** percent of the surveyed respondents did not eat fast food due to health concerns.

Dataset

This dataset was created by AVADIGEPALLI

Contents

This statistic shows the organic and health foods served in chain restaurants in the United States as of the fourth quarter of 2013, by type. During the survey, 55 percent of respondents stated that they served gluten free foods in 2013.

Welcome to the Fast Food Nutrition Dataset, which provides a comprehensive breakdown of the nutritional content of various fast food products from popular fast food chains.

Fast food is known for its convenience and affordability, but it is also infamous for its high-calorie, high-fat, and high-sugar content. This dataset aims to shed light on the nutritional value of these fast food products, helping consumers make more informed decisions about their food choices.

With information on calories, fat, carbohydrates, protein, and other key nutrients, this dataset provides a valuable resource for nutritionists, researchers, and health-conscious individuals. By analyzing this dataset, we can gain a better understanding of the nutritional impact of fast food consumption and work towards creating healthier food options in the fast food industry.

Dataset updated:

Feb 14, 2024

Dataset provided by:

data.world, Inc.

Authors:

Datafiniti

Area covered:

North Pacific Ocean, Pacific Ocean

Data Description:

This is a list of 10,000 fast food restaurants provided by Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more. Note that this is a sample of a large dataset. The full dataset is available through Datafiniti. You can use this data to rank cities with the most and least fast food restaurants across the U.S. E.g.:

Cities with the most and least McDonald's per capita
Fast food restaurants per capita for all states
Fast food restaurants with the most locations nationally
Major cities with the most and least fast food restaurants per capita
Small cities with the most fast food restaurants per capita
States with the most and least fast food restaurants per capita
The number of fast food restaurants per capita

Download Free Sample
The fast food market insights helps market vendors to identify the challenges that will affect the revenue of the market players and may hinder the growth of the fast food market during the forecast period.

the health concerns pertaining to the excessive consumption of fast foods will be one of the key challenges that the market vendors have to overcome during the forecast period. To gather more information regarding the market challenges, click here for a free sample report.

ABSTRACT This narrative literature review aimed to analyze the results of studies on the food intake of university students. A literature search was conducted in July 2014 and updated in July 2016 in the Scopus, MedLine/PubMed, and SciELO databases, using descriptors related to university students and food intake in English and Portuguese. Overall, 37 studies that analyzed university students’ food intake were included in this review, eight of which were conducted in Brazil. The results demonstrated that most university students have unhealthy eating behaviors, such as high intake of fast foods, snacks, sweets, soft drinks, and alcoholic beverages, and low intake of fruits, vegetables, fish, whole grains, and legumes. Undergraduate students of health sciences, such as nursing, nutrition, and medicine, did not have healthier diets. University students’ food intake was characterized as unhealthy, regardless of undergraduate program or sex, especially among students who left the parents’ home and became responsible for their own food. Therefore, there is a need of developing public policies that promote healthy eating habits among students, such as interventions to change their eating habits and increase their access to healthy foods at the university environment.

Cooks working in fast food restaurants in the United States had a median hourly wage of 14.50 U.S. dollars as of May 2024. Meanwhile, 10 percent of fast food cooks earned less than 10.76 U.S. dollars per hour.

Fast Food Nutrition is a website operated by the Center for Science in the Public Interest, a non-profit consumer advocacy organization dedicated to promoting health and safety in the food industry. With a focus on transparency and public education, the company's goal is to empower consumers to make informed choices about the food they eat.

Through its website, Fast Food Nutrition provides access to nutritional data and information about popular fast food chains, as well as resources and tools for consumers to make healthier choices. The company's data set includes nutritional information, ingredient lists, and health ratings for a wide range of fast food menu items, making it a valuable resource for health-conscious consumers.

This statistic shows the plans of chain restaurants in the United States to serve organic and health foods in 2014, by type. During the survey, 30 percent of respondents stated that they planned to serve locally sourced foods more often in 2014, whereas 54 percent said they had no plans to serve locally sourced foods.

Point-of-purchase receipt and survey data was collected from 1,156 adults at fast food restaurants in order to measure the impact of a New York City law mandating the labeling of calories in all chain restaurants. The data was collected over a four week period in 2008 both before and after the law was implemented. Data was collected in two locations: in New York City, where the law was implemented, and in neighboring Newark, NJ where it was not. Data points include the nutritional value of food purchased, such as the amount of calories, saturated fat, sodium, and sugar. Other variables collected include age, gender, race and ethnicity, education level, and whether the food was eaten at the restaurant or ordered 'to go.' Participants were recruited via street-intercept method outside of fast food restaurants (McDonald's, Burger King, KFC, Subway, and Wendy's).

This project is superceded by:
Clarke, Philippa, Gomez-Lopez, Iris, Li, Mao, and Finlay, Jessica. National Neighborhood Data Archive (NaNDA): Eating and Drinking Places by Census Tract, United States, 2006-2015. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-05. https://doi.org/10.3886/E115404V1

The objective of the National Neighborhood Data Archive (NaNDA) is to create measures of neighborhood context that impact clinical, social, and psychological health and healthy aging outcomes. This dataset contains measures of the number and per capita density of fast-food restaurants per United States census tract from 2006 through 2015. Fast-food restaurants are those classified as “limited-service restaurants” under the North American Industry Classification System (NAICS code 722513). According to the NAICS website, code 722513 “comprises establishments primarily engaged in providing food services (except snack and nonalcoholic beverage bars) where patrons generally order or select items and pay before eating.” Examples include pizza delivery shops, fast-food restaurants, and takeout sandwich shops.