As of January 2024, around 331.1 million people in the United States accessed the internet, making it one of the largest online markets worldwide. The country currently ranks third after China and India by the online audience size. Overview of internet usage in the United States The digital population in the United States has constantly increased in recent years. Among the most common reasons is the growing accessibility of broadband internet. A big part of the country's digital audience accesses the web via mobile phones. In 2024, the country saw an estimated 97.1 percent mobile internet user penetration. According to a 2024 survey, over 51 percent of U.S. women and 43 percent of men said it is important to them to have mobile internet access anywhere, at any time. Another 41 percent of respondents could not imagine their everyday life without the internet. Google and YouTube are the most visited websites in the country, while music, food, and drinks were the most discussed online topics. Internet usage demographics in the United States While some users can no longer imagine their life without the internet, others do not use it at all. According to 2021 data, 25 percent of U.S. adults 65 and older reported not using the internet. Despite this, online usage was strong across other age groups, especially young adults aged 18 to 49. This age group also reported the highest percentage of smartphone usage in the country as of 2023. Due to a persistent lack of connectivity in rural areas, more online users were based in urban areas of the U.S. than in the countryside.

As of 2024, approximately 97.1 percent of the United States' population accessed the internet, up from approximately 71 percent in 2013. The United States is one of the biggest online markets worldwide. In 2024, over 331 million individuals in the country went online. Furthermore, social media apps were among the most popular category of mobile apps used in the market. Social media usage in the U.S. Social media usage in the United States has seen significant growth in recent years, amassing 300 million as of 2024. By the third quarter of 2023, internet users in the U.S. were spending around two hours on social media out of seven hours of internet usage. The most common activities among U.S. users include sending private messages and liking posts or following people, which highlights widespread engagement with social media platforms among internet users in the United States. TikTok surge in the U.S. TikTok continues to be one of the most popular social media platforms in the United States. As of July 2024, 120 million individuals or 45 percent of internet users in the country used the social network. This surge in popularity is the result of user’s high engagement with short-form videos and quick entertainment in which TikTok managed to capture users’ attention. Users in the United States spent an average of 45 hours and 37 minutes monthly in 2023.

As of February 2025, there were 5.56 billion internet users worldwide, which amounted to 67.9 percent of the global population. Of this total, 5.24 billion, or 63.9 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 2024. In The Netherlands, Norway and Saudi Arabia, 99 percent of the population used the internet as of April 2024. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Asia was home to the largest number of online users worldwide – over 2.93 billion at the latest count. Europe ranked second, with around 750 million internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2023, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in the Arab States and Africa, with around a ten percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller gender gap. As of 2023, global internet usage was higher among individuals between 15 and 24 years across all regions, with young people in Europe representing the most significant usage penetration, 98 percent. In comparison, the worldwide average for the age group 15–24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

This map shows the percent of households with no internet access. Pop-up shows counts of households by type of internet access. Map is mulit-scale, with data for state, county, and tract. Map is mulit-scale, with data for state, county, and tract. Pie-chart categories are households with no internet connection, households with internet access with no subscription, households with Broadband of any type, and households with dial-up internet. Hover over the pie chart pieces to see the count of households in each category.More detailed categories as to the type of Broadband subscription are available in the layers.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

In November 2021, it was found that Idaho had the highest online penetration rate among all the states in the U.S., as 88.6 percent of the state's population used the internet. Wisconsin and Illinois ranked second with 87.8 percent of online access in both states, while Oregon followed, with 87.4 percent.

This layer shows computer ownership and internet access by education. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count of people age 25+ in households with no computer and the percent of the population age 25+ who are high school graduates (includes equivalency) and have some college or associate's degree in households that have no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28006 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

United States US: Fixed Broadband Internet Subscribers: per 100 People data was reported at 33.853 Ratio in 2017. This records an increase from the previous number of 33.002 Ratio for 2016. United States US: Fixed Broadband Internet Subscribers: per 100 People data is updated yearly, averaging 24.639 Ratio from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 33.853 Ratio in 2017 and a record low of 0.256 Ratio in 1998. United States US: Fixed Broadband Internet Subscribers: per 100 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Telecommunication. Fixed broadband subscriptions refers to fixed subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Weighted average; Please cite the International Telecommunication Union for third-party use of these data.

This layer shows computer ownership and internet access by income group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of households without a broadband internet subscription. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28004Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

As of 2024, the estimated number of internet users worldwide was 5.5 billion, up from 5.3 billion in the previous year. This share represents 68 percent of the global population. Internet access around the world Easier access to computers, the modernization of countries worldwide, and increased utilization of smartphones have allowed people to use the internet more frequently and conveniently. However, internet penetration often pertains to the current state of development regarding communications networks. As of January 2023, there were approximately 1.05 billion total internet users in China and 692 million total internet users in the United States. Online activities Social networking is one of the most popular online activities worldwide, and Facebook is the most popular online network based on active usage. As of the fourth quarter of 2023, there were over 3.07 billion monthly active Facebook users, accounting for well more than half of the internet users worldwide. Connecting with family and friends, expressing opinions, entertainment, and online shopping are amongst the most popular reasons for internet usage.

Market Overview:

The United States wireless connectivity market size is projected to exhibit a growth rate (CAGR) of 14.10% during ​2024-2032​. The growing proliferation of smartphones and other connected devices, the introduction of fifth generation (5G) networks promising lightning-fast speeds, reduced latency, and enhanced reliability, and the widespread adoption of wireless connectivity to safeguard sensitive data represent some of the key factors driving the market.

Wireless connectivity is a technology that enables devices to communicate with each other or access the internet without the need for physical wired connections. It is an integral part of daily life, powering everything from smartphones and laptops to home automation systems and industrial machinery. It is essential in ensuring seamless communication and data transfer, which allows devices such as computers, smartphones, and tablets to connect to the internet through radio waves, which is transforming the way information is accessed, allowing individuals to browse the web, stream videos, and connect with others from virtually anywhere within the Wi-Fi coverage area. For instance, Bluetooth is another popular wireless technology that facilitates short-range communication between devices. It is commonly used for connecting wireless headphones, speakers, and peripheral devices to smartphones and computers. Bluetooth's versatility and low power consumption make it a preferred choice for personal area networks. Additionally, cellular networks provide wide-area wireless connectivity and use a network of cell towers to enable mobile devices to communicate over long distances, which is the backbone of mobile communications, allowing users to make calls, send texts, and access the internet on the go. It also extends to the Internet of Things (IoT), where sensors and devices are interconnected to gather and transmit data in various fields, including healthcare, agriculture, and smart cities.

United States Wireless Connectivity Market Trends:

The market is primarily driven by the proliferation of smartphones and other connected devices. Also, Americans rely on their devices for work, entertainment, and communication, which requires improved wireless connectivity, thus contributing to the market growth. Moreover, the introduction of fifth-generation (5G) networks promises lightning-fast speeds, reduced latency, and enhanced reliability, representing another major growth-inducing factor. As telecom companies continue to invest in 5G infrastructure, consumers and businesses are eager to tap into its potential. Along with this, smart homes, connected vehicles, and industrial applications depending on wireless connectivity led to the adoption of the Internet of Things (IoT), further propelling the market growth. Besides this, the coronavirus disease (COVID-19) pandemic accelerated the shift to remote work and telehealth services, which require dependable wireless connections, creating a substantial market for connectivity providers. Apart from this, federal and state governments are taking steps to expand broadband access in underserved areas, which aim to bridge the digital divide and ensure that all citizens have access to high-speed internet, further driving the market growth. Additionally, many U.S. cities are investing in becoming smart cities, which rely on wireless connectivity for various applications such as traffic management, energy efficiency, and public safety, thus influencing market growth. Furthermore, the increasing use of wireless connectivity by businesses and individuals to safeguard sensitive data and provide uninterrupted service is creating a positive market outlook.

United States Wireless Connectivity Market Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for ​2024-2032​. Our report has categorized the market based on technology, network type, and end user.

Technology Insights:

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• Bluetooth
• Wi-Fi
• Ultra-Wide Band
• NFC
• Cellular
• Zigbee
• GPS
• Others
  

The report has provided a detailed breakup and analysis of the market based on the technology. This includes bluetooth, wi-fi, ultra-wide band, NFC, cellular, zigbee, GPS, and others.

Network Type Insights:

• Wireless Wide Area Network (WWAN)
• Wireless Personal Area Network (WPAN)
• Wireless Local Area Network (WLAN)
  

A detailed breakup and analysis of the market based on the network type have also been provided in the report. This includes wireless wide area network (WWAN), wireless personal area network (WPAN), and wireless local area network (WLAN).

End User Insights:

• Automotive and Transportation
• Building Automation
• Consumer Electronics and Wearables
• Energy and Utilities
• Healthcare
• Industrial
• IT and Telecom
• Others
  

The report has provided a detailed breakup and analysis of the market based on the end user. This includes automotive and transportation, building automation, consumer electronics and wearables, energy and utilities, healthcare, industrial, IT and telecom, and others.

Regional Insights:

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• Northeast
• Midwest
• South
• West
  

The report has also provided a comprehensive analysis of all the major regional markets, which include the Northeast, Midwest, South, and West.

Competitive Landscape:

The market research report has also provided a comprehensive analysis of the competitive landscape. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

United States Wireless Connectivity Market Report Coverage:

The population share with internet access in the United States was forecast to continuously increase between 2024 and 2029 by in total 1.5 percentage points. After the ninth consecutive increasing year, the internet penetration is estimated to reach 95.37 percent and therefore a new peak in 2029. Notably, the population share with internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via any means. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

This layer shows which parts of the United States and Puerto Rico fall within ten minutes' walk of one or more grocery stores. It is estimated that 20% of U.S. population live within a 10 minute walk of a grocery store, and 92% of the population live within a 10 minute drive of a grocery store. The layer is suitable for looking at access at a neighborhood scale.When you add this layer to your web map, along with the drivable access layer and the SafeGraph grocery store layer, it becomes easier to spot grocery stores that sit within a highly populated area, and grocery stores that sit in a shopping center far away from populated areas. Add the Census block points layer to show a popup with the count of stores within 10 minutes' walk and drive. This view of a city begins to hint at the question: how many people have each type of access to grocery stores? And, what if they are unable to walk a mile regularly, or don't own a car?How to Use This Layer in a Web MapUse this layer in a web map to introduce the concepts of access to grocery stores in your city or town. This is the kind of map where people will want to look up their home or work address to validate what the map is saying. See this example web map which you can use in your projects, storymaps, apps and dashboards.The layer was built with that use in mind. Many maps of access use straight-line, as-the-crow-flies distance, which ignores real-world barriers to walkability like rivers, lakes, interstates and other characteristics of the built environment. Block analysis using a network data set and Origin-Destination analysis factors these barriers in, resulting in a more realistic depiction of access.Lastly, this layer can serve as backdrop to other community resources, like food banks, farmers markets (example), and transit (example). Add a transit layer to immediately gauge its impact on the population's grocery access. You can also use this map to see how it relates to communities of concern. Add a layer of any block group or tract demographics, such as Percent Senior Population (examples), or Percent of Households with Access to 0 Vehicles (examples).The layer is a useful visual resource for helping community leaders, business and government leaders see their town from the perspective of its residents, and begin asking questions about how their community could be improved.Data sourcesPopulation data is from the 2010 U.S. Census blocks. Each census block has a count of stores within a 10 minute walk, and a count of stores within a ten minute drive. Census blocks known to be unpopulated are given a score of 0. The layer is available as a hosted feature layer.Grocery store locations are from SafeGraph, reflecting what was in the data as of October 2020. Access to the layer was obtained from the SafeGraph offering in ArcGIS Marketplace. For this project, ArcGIS StreetMap Premium was used for the street network in the origin-destination analysis work, because it already has the necessary attributes on each street segment to identify which streets are considered walkable, and supports a wide variety of driving parameters.The walkable access layer and drivable access layers are rasters, whose colors were chosen to allow the drivable access layer to serve as backdrop to the walkable access layer. Alternative versions of these layers are available. These pairs use different colors but are otherwise identical in content.Data PreparationArcGIS Network Analyst was used to set up a network street layer for analysis. ArcGIS StreetMap Premium was installed to a local hard drive and selected in the Origin-Destination workflow as the network data source. This allows the origins (Census block centroids) and destinations (SafeGraph grocery stores) to be connected to that network, to allow origin-destination analysis.The Census blocks layer contains the centroid of each Census block. The data allows a simple popup to be created. This layer's block figures can be summarized further, to tract, county and state levels.The SafeGraph grocery store locations were created by querying the SafeGraph source layer based on primary NAICS code. After connecting to the layer in ArcGIS Pro, a definition query was set to only show records with NAICS code 445110 as an initial screening. The layer was exported to a local disk drive for further definition query refinement, to eliminate any records that were obviously not grocery stores. The final layer used in the analysis had approximately 53,600 records. In this map, this layer is included as a vector tile layer.MethodologyEvery census block in the U.S. was assigned two access scores, whose numbers are simply how many grocery stores are within a 10 minute walk and a 10 minute drive of that census block. Every census block has a score of 0 (no stores), 1, 2 or more stores. The count of accessible stores was determined using Origin-Destination Analysis in ArcGIS Network Analyst, in ArcGIS Pro. A set of Tools in this ArcGIS Pro package allow a similar analysis to be conducted for any city or other area. The Tools step through the data prep and analysis steps. Download the Pro package, open it and substitute your own layers for Origins and Destinations. Parcel centroids are a suggested option for Origins, for example. Origin-Destination analysis was configured, using ArcGIS StreetMap Premium as the network data source. Census block centroids with population greater than zero were used as the Origins, and grocery store locations were used as the Destinations. A cutoff of 10 minutes was used with the Walk Time option. Only one restriction was applied to the street network: Walkable, which means Interstates and other non-walkable street segments were treated appropriately. You see the results in the map: wherever freeway overpasses and underpasses are present near a grocery store, the walkable area extends across/through that pass, but not along the freeway.A cutoff of 10 minutes was used with the Drive Time option. The default restrictions were applied to the street network, which means a typical vehicle's access to all types of roads was factored in.The results for each analysis were captured in the Lines layer, which shows which origins are within the cutoff of each destination over the street network, given the assumptions about that network (walking, or driving a vehicle).The Lines layer was then summarized by census block ID to capture the Maximum value of the Destination_Rank field. A census block within 10 minutes of 3 stores would have 3 records in the Lines layer, but only one value in the summarized table, with a MAX_Destination_Rank field value of 3. This is the number of stores accessible to that census block in the 10 minutes measured, for walking and driving. These data were joined to the block centroids layer and given unique names. At this point, all blocks with zero population or null values in the MAX_Destination_Rank fields were given a store count of 0, to help the next step.Walkable and Drivable areas are calculated into a raster layer, using Nearest Neighbor geoprocessing tool on the count of stores within a 10 minute walk, and a count of stores within a ten minute drive, respectively. This tool uses a 200 meter grid and interpolates the values between each census block. A census tracts layer containing all water polygons "erased" from the census tract boundaries was used as an environment setting, to help constrain interpolation into/across bodies of water. The same layer use used to "shoreline" the Nearest Neighbor results, to eliminate any interpolation into the ocean or Great Lakes. This helped but was not perfect.Notes and LimitationsThe map provides a baseline for discussing access to grocery stores in a city. It does not presume local population has the desire or means to walk or drive to obtain groceries. It does not take elevation gain or loss into account. It does not factor time of day nor weather, seasons, or other variables that affect a person's commute choices. Walking and driving are just two ways people get to a grocery store. Some people ride a bike, others take public transit, have groceries delivered, or rely on a friend with a vehicle. Thank you to Melinda Morang on the Network Analyst team for guidance and suggestions at key moments along the way; to Emily Meriam for reviewing the previous version of this map and creating new color palettes and marker symbols specific to this project. Additional ReadingThe methods by which access to food is measured and reported have improved in the past decade or so, as has the uses of such measurements. Some relevant papers and articles are provided below as a starting point.Measuring Food Insecurity Using the Food Abundance Index: Implications for Economic, Health and Social Well-BeingHow to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, WashingtonAccess to Affordable and Nutritious Food: Measuring and Understanding Food Deserts and Their ConsequencesDifferent Measures of Food Access Inform Different SolutionsThe time cost of access to food – Distance to the grocery store as measured in minutes

This layer shows computer ownership and internet access by age and race. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count of population age 18 to 64 in households and percent of population age 18 to 64 in households with no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2016-2020ACS Table(s): B28005, B28003, B28009B, B28009C, B28009D, B28009E, B28009F, B28009G, B28009H, B28009I Data downloaded from: Census Bureau's API for American Community Survey Date of API call: March 17, 2022The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This layer shows computer ownership and internet access by age and race. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of population age 18 to 64 in households with no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2016-2020ACS Table(s): B28005, B28003, B28009B, B28009C, B28009D, B28009E, B28009F, B28009G, B28009H, B28009I Data downloaded from: Census Bureau's API for American Community Survey Date of API call: March 17, 2022The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

An analysis of average internet speeds across U.S. states in 2023, highlighting the fastest and slowest regions.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle.."With a computer" includes those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer..Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html..Estimates of urban and rural populations, housing units...

In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the 20th round of the survey (April 2021) include self-reported health status, health insurance coverage, access to health care, awareness of Marketplace and Medicaid coverage options, use of public benefits, telehealth, COVID-19 vaccine attitudes, forgone care because of the COVID-19 pandemic, and unfair treatment in health care settings. Additional information collected by the survey includes age, gender, sexual orientation, marital status, education, race and ethnicity, United States citizenship, housing type, home ownership, internet access, income, and employment status.

Users can access data pertaining to individuals with disabilities. Topics include but are not limited to: people with disabilities’ access to employment, technology, healthcare, and community based services. Background The Disability Statistics Center is based at the Institute for Health and Aging at the University of California, San Francisco (UCSF). The Disability Statistics Center generates reports ranging from employment opportunities, Medicaid home and community-based services, mobility device use, computer and internet use, wheelchair use, vocational rehabilitation, education, medical expenditures, and functional limitations among people with disabilities. User functiona lity Data is presented in report or abstract form and can be downloaded in PDF or HTML formats by clicking on the publications link. All reports and abstracts use United States data. Additional data sources are listed under “Finding Disability Data” and include data from the United States as well as international data. Data Notes The data sources are clearly referenced for each article. The most recent publications are from 2003. There is no indication on the site when the data will be updated.

The population share with mobile internet access in the United States was forecast to continuously increase between 2024 and 2029 by in total 2.7 percentage points. After the ninth consecutive increasing year, the mobile internet penetration is estimated to reach 92.51 percent and therefore a new peak in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

"The Statistical Abstract of the United States, published since 1878, is the standard summary of statistics on the social, political, and economic organization of the United States. It is designed to serve as a convenient volume for statistical reference and as a guide to other statistical publications and sources. The latter function is served by the introductory text to each section, the source note appearing below each table, and Appendix I, which comprises the Guide to Sources of Statisti cs, the Guide to State Statistical Abstracts, and the Guide to Foreign Statistical Abstracts. The Statistical Abstract sections and tables are compiled into one Adobe PDF named StatAbstract2009.pdf. This PDF is bookmarked by section and by table and can be searched using the Acrobat Search feature. The Statistical Abstract on CD-ROM is best viewed using Adobe Acrobat 5, or any subsequent version of Acrobat or Acrobat Reader. The Statistical Abstract tables and the metropolitan areas tables from Appendix II are available as Excel(.xls or .xlw) spreadsheets. In most cases, these spreadsheet files offer the user direct access to more data than are shown either in the publication or Adobe Acrobat. These files usually contain more years of data, more geographic areas, and/or more categories of subjects than those shown in the Acrobat version. The extensive selection of statistics is provided for the United States, with selected data for regions, divisions, states, metropolitan areas, cities, and foreign countries from reports and records of government and private agencies. Software on the disc can be used to perform full-text searches, view official statistics, open tables as Lotus worksheets or Excel workbooks, and link directly to source agencies and organizations for supporting information. Except as indicated, figures are for the United States as presently constituted. Although emphasis in the Statistical Abstract is primarily given to national data, many tables present data for regions and individual states and a smaller number for metropolitan areas and cities.Statistics for the Commonwealth of Puerto Rico and for island areas of the United States are included in many state tables and are supplemented by information in Section 29. Additional information for states, cities, counties, metropolitan areas, and other small units, as well as more historical data are available in various supplements to the Abstract. Statistics in this edition are generally for the most recent year or period available by summer 2006. Each year over 1,400 tables and charts are reviewed and evaluated; new tables and charts of current interest are added, continuing series are updated, and less timely data are condensed or eliminated. Text notes and appendices are revised as appropriate. This year we have introduced 72 new tables covering a wide range of subject areas. These cover a variety of topics including: learning disability for children, people impacted by the hurricanes in the Gulf Coast area, employees with alternative work arrangements, adult computer and Internet users by selected characteristics, North America cruise industry, women- and minority-owned businesses, and the percentage of the adult population considered to be obese. Some of the annually surveyed topics are population; vital statistics; health and nutrition; education; law enforcement, courts and prison; geography and environment; elections; state and local government; federal government finances and employment; national defense and veterans affairs; social insurance and human services; labor force, employment, and earnings; income, expenditures, and wealth; prices; business enterprise; science and technology; agriculture; natural resources; energy; construction and housing; manufactures; domestic trade and services; transportation; information and communication; banking, finance, and insurance; arts, entertainment, and recreation; accommodation, food services, and other services; foreign commerce and aid; outlying areas; and comparative international statistics." Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.