In the last few decades, the Democratic Party has often pulled ahead of the Republican Party in terms of party identification. However, 2022 saw a shift in party identification, with slightly more Americans identifying with the Republican Party for the first time since 2011, when both parties stood at ** percent in 2011. These values include not only those surveyed who identified with a major political party, but also those who identified as independent, but have leanings towards one party over another.

Since 1988, the share of adults in the U.S. who identify as political independents has continued to grow, often surpassing the that of Democrats or Republicans. In 2024, approximately ** percent of adults rejected identification with the major parties, compared to ** percent of respondents identified with the Democratic Party, and ** percent with the Republican Party.

Welcome to BatchData, your trusted source for comprehensive US homeowner data, contact information, and demographic data, all designed to empower political campaigns. In the fast-paced world of politics, staying ahead and targeting the right audience is crucial for success.

At BatchData, we understand the importance of having the most accurate, up-to-date, and relevant data to help you make informed decisions and connect with your constituents effectively. With our robust data offerings, political campaign agencies can easily reach both homeowners and renters, using direct contact information such as cell phone numbers, emails, and mailing addresses.

The Power of Data in Political Campaigns In the digital age, political campaigns are increasingly reliant on data-driven strategies. Precise targeting, tailored messaging, and efficient outreach have become the cornerstones of successful political campaigning. BatchData equips political campaign agencies with the tools they need to harness the power of data in their campaigns, enabling them to make the most of every interaction. Harness the power of voter data and campaign & election data to effectively run political campaigns.

Key Features of BatchData 1. US Homeowner Data At BatchData, we understand that having access to accurate and comprehensive homeowner data is the bedrock of a successful political campaign. Our vast database includes information on homeowners across the United States, allowing you to precisely target this key demographic. With our homeowner data, you can segment your campaign and craft messages that resonate with this audience. Whether you're running a local, state, or national campaign, our homeowner data is an invaluable asset.

1. Contact Information 258M Phone Numbers (US Phone Number Data) BatchData doesn't just stop at providing you with demographic data; we go a step further by giving you direct contact information. We offer cell phone numbers, email addresses, and mailing addresses, ensuring that you can connect with your audience on multiple fronts. This multifaceted approach allows you to engage with potential voters in a way that suits their preferences and lifestyles. Whether you want to send targeted emails, reach out through phone calls, or even send physical mailers, BatchData has you covered with both the data and the tools. (See BatchDialer for more Info).

2. Demographic Data In addition to homeowner data and contact information, BatchData provides a treasure trove of demographic data. You can refine your campaign strategy by tailoring your messages to specific demographics, including age, gender, income, religious preferences, and more. Our demographic data helps you understand your audience better, allowing you to craft compelling messages that resonate with their values and interests.

3. Targeting Both Homeowners and Renters We understand that not all political campaigns are exclusively focused on homeowners. That's why BatchData caters to a diverse range of campaign needs. Whether your campaign is directed at homeowners or renters, our data sets have you covered. You can effectively target a broader spectrum of the population, ensuring that your message reaches the right people, regardless of their housing status.

Flexible Data Delivery Methods BatchData understands that political campaigns are time-sensitive, and efficiency is paramount. That's why we offer a variety of data delivery methods to suit your specific needs.

1. API Integration For real-time access to data, our API integration is your go-to solution. Easily integrate BatchData's data into your campaign management systems, ensuring that you always have the latest information at your fingertips.

2. Bulk File Delivery When you require a large volume of data in one go, our bulk file delivery option is ideal. We'll deliver the data to you in a format that's easy to import into your campaign databases, allowing you to work with a comprehensive dataset on your terms.

3. S3 Data Storage If you prefer to host your data in an S3 bucket, BatchData can seamlessly deliver your datasets to the cloud storage location of your choice. This option ensures that your data is readily available whenever you need it.

4. Self-Service List Building Our self-service list building tool empowers you to create custom lists based on your specific criteria. You have the flexibility to choose the data elements you need, ensuring that your campaign efforts are tailored to your goals.

5. File Exporting Need to download data for offline use or share it with your team? Our file exporting feature lets you export data in a user-friendly format, making it easy to work with.

6. On-Demand Concierge Services For those campaigns that require a more personalized touch, BatchData offers on-demand concierge services. Our experienced team is here to assist you in building lists, refining your targeting, and providing support as needed. This high-touch service ensures that you have t...

Supplementary Empirical Teaching Units in Political Science (SETUPS) for American Politics are computer-related modules designed for use in teaching introductory courses in American government and politics. The modules are intended to demonstrate the process of examining evidence and reaching conclusions and to stimulate students to independent, critical thinking and a deeper understanding of substantive content. They enable students with no previous training to make use of the computer to analyze data on political behavior. The data for this module were taken from the pre- and post-election surveys of the AMERICAN NATIONAL ELECTION STUDY, 1984 (ICPSR 8298), conducted by Warren E. Miller and the National Election Studies Board. Only respondents who completed both waves of the survey were included in this subset. Variables provide information on respondents' level of political involvement and knowledge of political issues, and their opinions of the 1984 presidential candidates, Ronald Reagan and Walter Mondale, and the vice-presidential candidates, George Bush and Geraldine Ferraro. Also included are respondents' views on the economy, domestic and foreign affairs, and their general political attitudes and beliefs. Demographic items specify age, sex, race, marital status, education, occupation, income, social class identification, religion, and size and type of community in which respondents resided.

According to a 2024 survey, ** percent of social media users in the United States used Facebook, and ** percent of left-leaning users used the social network. Overall, ** percent of social media users who were politically left-leaning used Pinterest, compared to ** percent of right-leaning users.

According to a 2023 survey, Americans between 18 and 29 years of age were more likely to identify with the Democratic Party than any other surveyed age group. While 39 percent identified as Democrats, only 14 percent identified ad Republicans. However, those 50 and older identified more with the Republican Party.

PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau... Visit https://dataone.org/datasets/sha256%3A05707c1dc04a814129f751937a6ea56b08413546b18b351a85bc96da16a7f8b5 for complete metadata about this dataset.

Political situation in Germany. Attitudes towards political parties.

Topics: Turnout intention and voting intention (Sunday question); Alternative voting intention; other electable party: Pirate Party; other electable party: Free voters; voting behaviour in the last federal election in 2009 (recall); positive or negative association with terms (people´s party, compassion, conservative, christian, social, close to the economy, middle-class, liberal, opportunities, achievement, cohesion, freedom, security, stability, order, performance justice, social market economy, centre, qualified immigration, budget consolidation, freedom of choice for families, intelligent saving, respect, demographic change, values, tradition, home, trust); annoyance about political decisions; issues about which one was annoyed; affected by political decisions (current); decisions by which one was personally affected (current); positive or negative impact of the decision; affected by political decisions (prospective); decisions by which one will be personally affected (prospective); party with which one feels most comfortable; subjective affiliation with ´little people´.

Political positions (politics takes care of the problems of the little people, concern about limiting living standards, debt reduction to maintain prosperity, public debt is good if it is made for the future of the children, fear of going out alone in the evening, problems keeping up with the pace of everyday life, state support for those who are willing to perform, acceptance of the performance principle, people´s parties prevent the assertion of individual interests, 30 km/h speed limit in cities, support for large-scale projects); association of certain terms with parties (people´s party, modern, compassionate, conservative, christian, down-to-earth, social, close to the economy, middle-class, liberal, advancement, opportunities, achievement, cohesion, freedom, security, stability, order, performance fairness, future, social market economy, centre, prosperity, qualified immigration, budget consolidation, freedom of choice for families, intelligent savings, demographic change, values, tradition, home, good governance, expertise, cares for citizens, party for all, can move Germany forward, strong leadership, energetic, honest, reliable, credible, responsible, trust).

Demography: age; highest school-leaving qualification; intended school-leaving qualification, completed studies; completed apprenticeship; occupation; profession; household size; frequency of churchgoing; party identification (direction, strength, stability); sex.

Additionally coded were: Federal state; inhabitant of place of residence; target persons in the household; number of telephone numbers; indicator replenishment sample; weighting factors.

This data collection contains electoral and demographic data for Massachusetts counties and cities during 1848-1876. The data for this collection were compiled to study electoral changes in Massachusetts politics during the Civil War period and to link the changes to socioeconomic determinants of support for the Republican and Democratic parties. Specific variables include number of voters for specific years and demographic information such as number of males and females and number of males employed in certain trades. Electoral data consists of election results.

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

NYU Libraries has licensed access to the L2 Political Academic Voter File. The file is a continuously updated dataset consisting of public information for every registered voter in the United States and includes basic socio-demographic indicators (some of which are modeled), consumer preferences, political party affiliation, voting history, and more.

The data consists of .tab files organized into individual state folders (all states and DC). Each state folder contains two files: demographics data and voter history data, with a data dictionary for each dataset. The size of the folders vary by state and data for all states adds up to approximately 40 GB. The data is organized into releases, generally two per year (spring and fall), which represent a snapshot of the country's voters at the time of the dataset creation.

NYU has also licensed access to L2 Political historical backlog of data. This backlog includes versions of the L2 Processed voter file going back to 2008 (for most U.S. states) and unprocessed "raw" state voter rolls, also going back to 2008 for most U.S. states.

This collection is available to NYU faculty and students only, and requires user to first submit a data management plan to account for how access and storage of the data will be handled. Information on how to submit a request to use this data and create a data management plan is available at https://guides.nyu.edu/l2political.

The Detroit Area Study (DAS) is a face-to-face survey of adults in the Detroit, Michigan metropolitan area. Information was collected on the political attitudes and behavior of 596 adults in the period during the fall of 1956 and early spring 1957. This collection was a combination of two separate studies: PARTY LEADERSHIP AND POLITICAL BEHAVIOR by Daniel Katz and Samuel Eldersveld, and INTRA-CLASS CORRELATION OF ATTITUDES IN DETROIT by Leslie Kish. Of the 596 respondents, 149 were categorized as belonging to a leadership sample consisting of 77 Republicans and 72 Democratic precinct leaders. For data on the political activities and attitudes of party leaders, see the related collection, DETROIT AREA STUDY, 1957: LEADER SURVEY (ICPSR 7107) (ICPSR 07107). Items in this survey focused on perceptions, attitudes, and behavior of the adult public toward party structures and organizations at the county, district, and precinct levels. In order to assess the sources of influence on the respondents' political attitudes and behavior, they were asked about the mass media they depended on most heavily for political information, as well as the frequency with which politics was discussed in meetings of their families, friends, neighbors, and other groups to which they belonged. A series of questions asked for whom respondents had voted in the 1956 presidential, gubernatorial, and congressional races, as well as which presidential candidate their family, friends, co-workers, and neighbors voted for. Other questions elicited information about the respondents' knowledge of and involvement in local party politics and their knowledge of precinct workers and their state party chairman. Also explored were respondents' feelings about the importance of voting, their general attitudes toward politics and political figures such as Adlai Stevenson and Dwight Eisenhower, their perception of the differences between the major parties on various issues, and their opinions on several controversial issues such as a national health care, school integration, ending the military draft, and monetary aid to countries that were not anti-communist. Additional items covered the use of telephones in respondents' homes, their living experiences before coming to Detroit, their handling of change of residences since coming to Detroit, and their feelings about their neighborhood. Demographic variables include the respondent's age, sex, race, education level, place of birth, marital status, number of children, religious preference, frequency of religious attendance, political party affiliation, voter registration status and participation history, employment status, occupation, labor union membership, perceived social class, relationship to the head of household, length of time at present residence, and length of residence in the Detroit area. Demographic information was collected on the nationality, occupation, and political party affiliation of the respondent's father. Information was also collected on the number and ages of household members, the number of household members employed, labor union membership in the household, household income, whether anyone in the household was employed by the government, and the occupation and employment status of the head of the household.

This dataset contains simulated data for social media users' demographics, behaviors, and perceptions related to political content. It includes features such as age, gender, education level, occupation, social media usage frequency, exposure to political content, and perceptions of accuracy and relevance.

the features included in the "Social Media Political Content Analysis Dataset":

1. Age: Age of the user.
2. Gender: Gender identity of the user.
3. Education Level: Highest level of education attained by the user.
4. Occupation: Current occupation of the user.
5. Political Affiliation: Political leaning or affiliation of the user (e.g., Liberal, Conservative, Independent).
6. Geographic Location: Country or region where the user is located (e.g., USA, UK, Canada, Australia).
7. Social Media Usage Frequency: Frequency of social media usage by the user (e.g., 0-1 hour, 1-2 hours, 2-4 hours, 4+ hours).
8. Preferred Social Media: Social media platform preferred by the user (e.g., Facebook, Twitter, Instagram).
9. Political Content Exposure: Frequency of exposure to political content on social media (e.g., Once a day, Few times a week, Rarely, Several times a day).
10. Types of Political Content: Types of political content consumed by the user (e.g., News articles, Opinion pieces, Memes).
11. Sources of Political Content: Sources from which the user obtains political content (e.g., Mainstream media, Political parties, Independent bloggers).
12. Recency of Exposure: Recency of the user's exposure to political content (e.g., Within the last hour, Within the last 24 hours, Within the last week, Longer than a week ago).
13. Interactions Frequency: Frequency of user interactions with political content on social media (e.g., Once a day, Few times a week, Rarely, Several times a day).
14. Political Content Topics: Topics of political content that interest the user (e.g., Economy, Healthcare, Immigration, Environment).
15. Perception of Accuracy: User's perception of the accuracy of political content on social media (e.g., Very accurate, Somewhat accurate, Not accurate).
16. Awareness of Algorithms: Whether the user is aware of algorithms that determine their social media feed (e.g., Yes, No).
17. Perception of Relevance: User's perception of the relevance of political content on social media (e.g., Very relevant, Somewhat relevant, Not relevant).
18. Personal Impact: User's perception of the personal impact of political content on social media (e.g., Strong impact, Moderate impact, No impact).
19. Trust in Social Media: User's level of trust in social media as a source of political information (e.g., Trust a lot, Trust somewhat, Do not trust).
20. Concerns about Algorithms: User's level of concern about algorithms shaping their social media experience (e.g., Very concerned, Somewhat concerned, Not concerned).
21. Overall Quality of Discourse: User's perception of the overall quality of political discourse on social media (e.g., High quality, Moderate quality, Low quality).
22. Views on Influence: User's perception of the influence of political content on social media (e.g., Very influential, Somewhat influential, Not influential).
23. Suggestions for Improvement: User's suggestions for improving the quality or experience of political content on social media (e.g., Increase transparency, Provide more diverse sources, Improve fact-checking, Enhance user controls).

This special topic poll, conducted November 6-10, 1996, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of political and social issues. The focus of this data collection was on the presidential and congressional elections held November 5, 1996. In the days following the election, respondents who had voted were asked about their choice for president, when they decided on their candidate, whether they had known enough about the candidates to make an informed choice, and whether factors such as leadership and a candidate's stance on issues were major or minor reasons for their vote. Respondents were quizzed on their knowledge of the presidential and vice-presidential candidates, as well as party platforms, campaign funding, and which party had the most members in the United States Congress. Views were sought on the media's treatment of the presidential candidates, campaign advertisements featuring the issue of Medicare, whether the presidential campaigns were more negative than in the past, and whether the news media should report public opinion poll results. Other topics addressed the condition of the national economy, abortion, sources of campaign information, types of negative news media coverage, and how much attention respondents paid to media coverage of the presidential campaign. Demographic variables include sex, age, race, ethnicity, education level, marital status, household income, political party affiliation, political philosophy, labor union membership, voter registration status, religious preference, and whether respondents thought of themselves as born-again or evangelical Christians.

This panel data set includes survey waves between October 2012 and October 2020 measuring various attitudes and political behaviors among a population-based panel of Americans who were at least 18 in 2008. The waves were administered by Knowledge Networks/GfK/Ipsos.

According to a survey conducted in 2023, Gen Z teens were more likely than other generations to identify as independents in the United States, at ** percent. A further ** percent of Gen Z teens identified as Democratic, while ** percent identified as Republicans.

This Gallup Poll aims to gather the Canadians' opinons of politics. Included is data regarding voting habits, election interest, favoured political parties, and attitudes towards the careers of politicians. Information regarding demographics, geographic location and social class was also collected from the respondents. Topics of interest include: car ownership; family problems; the federal election; phone ownership; political careers for the respondents' sons; political parties; union membership; and voting behaviour. Basic demographics variables are also included.

With Versium REACH Demographic Append you will have access to many different attributes for enriching your data.

Basic, Household and Financial, Lifestyle and Interests, Political and Donor.

Here is a list of what sorts of attributes are available for each output type listed above:

Basic: - Senior in Household - Young Adult in Household - Small Office or Home Office - Online Purchasing Indicator
- Language - Marital Status - Working Woman in Household - Single Parent - Online Education - Occupation - Gender - DOB (MM/YY) - Age Range - Religion - Ethnic Group - Presence of Children - Education Level - Number of Children

Household, Financial and Auto: - Household Income - Dwelling Type - Credit Card Holder Bank - Upscale Card Holder - Estimated Net Worth - Length of Residence - Credit Rating - Home Own or Rent - Home Value - Home Year Built - Number of Credit Lines - Auto Year - Auto Make - Auto Model - Home Purchase Date - Refinance Date - Refinance Amount - Loan to Value - Refinance Loan Type - Home Purchase Price - Mortgage Purchase Amount - Mortgage Purchase Loan Type - Mortgage Purchase Date - 2nd Most Recent Mortgage Amount - 2nd Most Recent Mortgage Loan Type - 2nd Most Recent Mortgage Date - 2nd Most Recent Mortgage Interest Rate Type - Refinance Rate Type - Mortgage Purchase Interest Rate Type - Home Pool

Lifestyle and Interests: - Mail Order Buyer - Pets - Magazines - Reading
- Current Affairs and Politics
- Dieting and Weight Loss - Travel - Music - Consumer Electronics - Arts
- Antiques - Home Improvement - Gardening - Cooking - Exercise
- Sports - Outdoors - Womens Apparel
- Mens Apparel - Investing - Health and Beauty - Decorating and Furnishing

Political and Donor: - Donor Environmental - Donor Animal Welfare - Donor Arts and Culture - Donor Childrens Causes - Donor Environmental or Wildlife - Donor Health - Donor International Aid - Donor Political - Donor Conservative Politics - Donor Liberal Politics - Donor Religious - Donor Veterans - Donor Unspecified - Donor Community - Party Affiliation

Previous research finds that Republicans report being happier or more satisfied with their lives than Democrats. Using representative American samples from 2002, 2005, 2007, 2009, and 2010, we tested a Person × Situation interactionist account in which political affiliation (Democrat, Republican) and political climate (favorable when the president in office is of the same party) are proposed to affect past, present, and anticipated future life satisfaction. Meta-analyses of related tests of key hypotheses confirmed that (a) life satisfaction was greater when the political climate was favorable rather than unfavorable and (b) Republicans were more sensitive to political climate than Democrats. As predicted, Republicans also were more politically polarized than Democrats. Taken together, the findings indicate that, compared to Democrats, Republicans are more apt to self-identify in political terms, and core aspects of their subjective well-being are more easily affected by the outcome of political events.

This table contains data on the percent of adults (18 years or older) who are registered voters and the percent of adults who voted in general elections, for California, its regions, counties, cities/towns, and census tracts. Data is from the Statewide Database, University of California Berkeley Law, and the California Secretary of State, Elections Division. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Political participation can be associated with the health of a community through two possible mechanisms: through the implementation of social policies or as an indirect measure of social capital. Disparities in political participation across socioeconomic groups can influence political outcomes and the resulting policies could have an impact on the opportunities available to the poor to live a healthy life. Lower representation of poorer voters could result in reductions of social programs aimed toward supporting disadvantaged groups. Although there is no direct evidentiary connection between voter registration or participation and health, there is evidence that populations with higher levels of political participation also have greater social capital. Social capital is defined as resources accessed by individuals or groups through social networks that provide a mutual benefit. Several studies have shown a positive association between social capital and lower mortality rates, and higher self- assessed health ratings. There is also evidence of a cycle where lower levels of political participation are associated with poor self-reported health, and poor self-reported health hinders political participation. More information about the data table and a data dictionary can be found in the About/Attachments section.