About this dataset

Context

The dataset tabulates the population of United States by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for United States. The dataset can be utilized to understand the population distribution of United States by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in United States. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for United States.

Key observations

Largest age group (population): Male # 30-34 years (11.65 million) | Female # 30-34 years (11.41 million). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the United States population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the United States is shown in the following column.
• Population (Female): The female population in the United States is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in United States for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Gender. You can refer the same here

Historical chart and dataset showing U.S. population growth rate by year from 1961 to 2023.

About this dataset

Context

The dataset tabulates the State Line population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for State Line. The dataset can be utilized to understand the population distribution of State Line by age. For example, using this dataset, we can identify the largest age group in State Line.

Key observations

The largest age group in State Line, ID was for the group of age 25 to 29 years years with a population of 3 (100%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in State Line, ID was the Under 5 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the State Line is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of State Line total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for State Line Population by Age. You can refer the same here

Graph and download economic data for Population ages 65 and above for the United States (SPPOP65UPTOZSUSA) from 1960 to 2024 about 65-years +, population, and USA.

Context

The world's population has undergone remarkable growth, exceeding 7.5 billion by mid-2019 and continuing to surge beyond previous estimates. Notably, China and India stand as the two most populous countries, with China's population potentially facing a decline while India's trajectory hints at surpassing it by 2030. This significant demographic shift is just one facet of a global landscape where countries like the United States, Indonesia, Brazil, Nigeria, and others, each with populations surpassing 100 million, play pivotal roles.

The steady decrease in growth rates, though, is reshaping projections. While the world's population is expected to exceed 8 billion by 2030, growth will notably decelerate compared to previous decades. Specific countries like India, Nigeria, and several African nations will notably contribute to this growth, potentially doubling their populations before rates plateau.

Content

This dataset provides comprehensive historical population data for countries and territories globally, offering insights into various parameters such as area size, continent, population growth rates, rankings, and world population percentages. Spanning from 1970 to 2023, it includes population figures for different years, enabling a detailed examination of demographic trends and changes over time.

Dataset

Structured with meticulous detail, this dataset offers a wide array of information in a format conducive to analysis and exploration. Featuring parameters like population by year, country rankings, geographical details, and growth rates, it serves as a valuable resource for researchers, policymakers, and analysts. Additionally, the inclusion of growth rates and world population percentages provides a nuanced understanding of how countries contribute to global demographic shifts.

This dataset is invaluable for those interested in understanding historical population trends, predicting future demographic patterns, and conducting in-depth analyses to inform policies across various sectors such as economics, urban planning, public health, and more.

Structure

This dataset (world_population_data.csv) covering from 1970 up to 2023 includes the following columns:

Acknowledgment

The primary dataset was retrieved from the World Population Review. I sincerely thank the team for providing the core data used in this dataset.

© Image credit: Freepik

About this dataset

Context

The dataset tabulates the data for the State Line, MS population pyramid, which represents the State Line population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for State Line, MS, is 22.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for State Line, MS, is 8.6.
• Total dependency ratio for State Line, MS is 31.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for State Line, MS is 11.6.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the State Line population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the State Line for the selected age group is shown in the following column.
• Population (Female): The female population in the State Line for the selected age group is shown in the following column.
• Total Population: The total population of the State Line for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for State Line Population by Age. You can refer the same here

Graph and download economic data for Population, Total for United States (POPTOTUSA647NWDB) from 1960 to 2024 about population and USA.

Historical chart and dataset showing U.S. birth rate by year from 1950 to 2025.

About this dataset

Context

The dataset tabulates the Slate Springs population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Slate Springs across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Slate Springs was 98, a 2% decrease year-by-year from 2022. Previously, in 2022, Slate Springs population was 100, an increase of 1.01% compared to a population of 99 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Slate Springs decreased by 26. In this period, the peak population was 124 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Slate Springs is shown in this column.
• Year on Year Change: This column displays the change in Slate Springs population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Slate Springs Population by Year. You can refer the same here

Graph and download economic data for Population (POPTHM) from Jan 1959 to May 2025 about population and USA.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

About this dataset

Context

The dataset tabulates the data for the Norwood Young America, MN population pyramid, which represents the Norwood Young America population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Norwood Young America, MN, is 29.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Norwood Young America, MN, is 30.7.
• Total dependency ratio for Norwood Young America, MN is 59.8.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Norwood Young America, MN is 3.3.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Norwood Young America population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Norwood Young America for the selected age group is shown in the following column.
• Population (Female): The female population in the Norwood Young America for the selected age group is shown in the following column.
• Total Population: The total population of the Norwood Young America for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Norwood Young America Population by Age. You can refer the same here

Population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2023 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries as of July 1, 2023. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/)released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Fields:CT20: 2020 Census tractFIP22: 2023 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2023) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP23CSA: 2020 census tract with 2023 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP23_AGE_0_4: 2023 population 0 to 4 years oldPOP23_AGE_5_9: 2023 population 5 to 9 years old POP23_AGE_10_14: 2023 population 10 to 14 years old POP23_AGE_15_17: 2022 population 15 to 17 years old POP23_AGE_18_19: 2023 population 18 to 19 years old POP23_AGE_20_44: 2023 population 20 to 24 years old POP23_AGE_25_29: 2023 population 25 to 29 years old POP23_AGE_30_34: 2023 population 30 to 34 years old POP23_AGE_35_44: 2023 population 35 to 44 years old POP23_AGE_45_54: 2023 population 45 to 54 years old POP23_AGE_55_64: 2023 population 55 to 64 years old POP23_AGE_65_74: 2023 population 65 to 74 years old POP23_AGE_75_84: 2023 population 75 to 84 years old POP23_AGE_85_100: 2023 population 85 years and older POP23_WHITE: 2023 Non-Hispanic White POP23_BLACK: 2023 Non-Hispanic African AmericanPOP23_AIAN: 2023 Non-Hispanic American Indian or Alaska NativePOP23_ASIAN: 2023 Non-Hispanic Asian POP23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific IslanderPOP23_HISPANIC: 2023 HispanicPOP23_MALE: 2023 Male POP23_FEMALE: 2023 Female POV23_WHITE: 2023 Non-Hispanic White below 100% Federal Poverty Level POV23_BLACK: 2023 Non-Hispanic African American below 100% Federal Poverty Level POV23_AIAN: 2023 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV23_ASIAN: 2023 Non-Hispanic Asian below 100% Federal Poverty Level POV23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV23_HISPANIC: 2023 Hispanic below 100% Federal Poverty Level POV23_TOTAL: 2023 Total population below 100% Federal Poverty Level POP23_TOTAL: 2023 Total PopulationAREA_SQMil: Area in square mile.POP23_DENSITY: 2023 Population per square mile.POV23_PERCENT: 2023 Poverty rate/percentage.How this data created?Population by age groups, ethnic groups and gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Notes:1. Population and poverty data estimated as of July 1, 2023. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundaries are as of July 1, 2023.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.

The Gross Domestic Product per capita in the United States was last recorded at 66682.61 US dollars in 2024. The GDP per Capita in the United States is equivalent to 528 percent of the world's average. This dataset provides - United States GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Historical chart and dataset showing U.S. life expectancy by year from 1950 to 2025.

Note: Starting April 27, 2023 updates change from daily to weekly. Summary The rate of confirmed COVID-19 cases among Marylanders per 100,000 people in each Maryland jurisdiction. Description The MD COVID-19 cases per 100K population, by jurisdiction layer is the rate of confirmed daily COVID-19 cases among Marylanders per 100,000 people in each Maryland jurisdiction. This rate is a 7-day average, calculated using the CasesByCounty layer and the 2019 estimated county populations (Maryland Department of Planning). Any negative value may be attributed to changes in reporting by jurisdiction. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

About this dataset

Context

The dataset tabulates the Tony population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Tony across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Tony was 98, a 1.01% decrease year-by-year from 2022. Previously, in 2022, Tony population was 99, a decline of 1% compared to a population of 100 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Tony decreased by 6. In this period, the peak population was 113 in the year 2010. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Tony is shown in this column.
• Year on Year Change: This column displays the change in Tony population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Tony Population by Year. You can refer the same here

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

NOTE: This dataset replaces a previous one. Please see below.

Chicago residents who are up to date with COVID-19 vaccines by ZIP Code, based on the reported home address and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE).

“Up to date” refers to individuals who meet the CDC’s updated COVID-19 vaccination criteria based on their age and prior vaccination history. For surveillance purposes, up to date is defined based on the following criteria:

People ages 5 years and older: · Are up to date when they receive 1+ doses of a COVID-19 vaccine during the current season.

Children ages 6 months to 4 years: · Children who have received at least two prior COVID-19 vaccine doses are up to date when they receive one additional dose of COVID-19 vaccine during the current season, regardless of vaccine product. · Children who have received only one prior COVID-19 vaccine dose are up to date when they receive one additional dose of the current season's Moderna COVID-19 vaccine or two additional doses of the current season's Pfizer-BioNTech COVID-19 vaccine. · Children who have never received a COVID-19 vaccination are up to date when they receive either two doses of the current season's Moderna vaccine or three doses of the current season's Pfizer-BioNTech vaccine.

This dataset takes the place of a previous dataset, which covers doses administered from December 15, 2020 through September 13, 2023 and is marked as historical: - https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccinations-by-ZIP-Code/553k-3xzc.

Data Notes:

Weekly cumulative totals of people up to date are shown for each combination ZIP Code and age group. Note there are rows where age group is "All ages" so care should be taken when summing rows.

Coverage percentages are calculated based on the cumulative number of people in each ZIP Code and age group who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. For ZIP Codes mostly outside Chicago, coverage percentages are not calculated reliable Chicago-only population counts are not available. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller ZIP Codes with smaller populations. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination, which may lead to over- or underestimation of vaccination coverage by geography. All coverage percentages are capped at 99%.

Weekly cumulative counts and coverage percentages are reported from the week ending Saturday, September 16, 2023 onward through the Saturday prior to the dataset being updated.

All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.

Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined.

The Chicago Department of Public Health uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Individuals may receive vaccinations that are not recorded in the Illinois immunization registry, I-CARE, such as those administered in another state, causing underestimation of the number individuals who are up to date. Inconsistencies in records of separate doses administered to the same person, such as slight variations in dates of birth, can result in duplicate records for a person and underestimate the number of people who are up to date.

For all datasets related to COVID-19, please visit: https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census