This dataset includes all individuals from the 1870 US census.
All manuscripts (and other items you'd like to publish) must be submitted to
phsdatacore@stanford.edu for approval prior to journal submission.
We will check your cell sizes and citations.
For more information about how to cite PHS and PHS datasets, please visit:
https:/phsdocs.developerhub.io/need-help/citing-phs-data-core
This dataset was developed through a collaboration between the Minnesota Population Center and the Church of Jesus Christ of Latter-Day Saints. The data contain demographic variables, economic variables, migration variables and race variables. Unlike more recent census datasets, pre-1900 census datasets only contain individual level characteristics and no household or family characteristics, but household and family identifiers do exist.
The official enumeration day of the 1870 census was 1 June 1870. The main goal of an early census like the 1870 U.S. census was to allow Congress to determine the collection of taxes and the appropriation of seats in the House of Representatives. Each district was assigned a U.S. Marshall who organized other marshals to administer the census. These enumerators visited households and recorder names of every person, along with their age, sex, color, profession, occupation, value of real estate, place of birth, parental foreign birth, marriage, literacy, and whether deaf, dumb, blind, insane or “idiotic”.
Sources: Szucs, L.D. and Hargreaves Luebking, S. (1997). Research in Census Records, The Source: A Guidebook of American Genealogy. Ancestry Incorporated, Salt Lake City, UT Dollarhide, W.(2000). The Census Book: A Genealogist’s Guide to Federal Census Facts, Schedules and Indexes. Heritage Quest, Bountiful, UT
The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.
The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.
All manuscripts (and other items you'd like to publish) must be submitted to
phsdatacore@stanford.edu for approval prior to journal submission.
We will check your cell sizes and citations.
For more information about how to cite PHS and PHS datasets, please visit:
https:/phsdocs.developerhub.io/need-help/citing-phs-data-core
Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.
In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.
The historic US 1920 census data was collected in January 1920. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.
Notes
We provide household and person data separately so that it is convenient to explore the descriptive statistics on each level. In order to obtain a full dataset, merge the household and person on the variables SERIAL and SERIALP. In order to create a longitudinal dataset, merge datasets on the variable HISTID.
Households with more than 60 people in the original data were broken up for processing purposes. Every person in the large households are considered to be in their own household. The original large households can be identified using the variable SPLIT, reconstructed using the variable SPLITHID, and the original count is found in the variable SPLITNUM.
Coded variables derived from string variables are still in progress. These variables include: occupation and industry.
Missing observations have been allocated and some inconsistencies have been edited for the following variables: SPEAKENG, YRIMMIG, CITIZEN, AGE, BPL, MBPL, FBPL, LIT, SCHOOL, OWNERSHP, MORTGAGE, FARM, CLASSWKR, OCC1950, IND1950, MARST, RACE, SEX, RELATE, MTONGUE. The flag variables indicating an allocated observation for the associated variables can be included in your extract by clicking the ‘Select data quality flags’ box on the extract summary page.
Most inconsistent information was not edited for this release, thus there are observations outside of the universe for some variables. In particular, the variables GQ, and GQTYPE have known inconsistencies and will be improved with the next release.
%3C!-- --%3E
This dataset was created on 2020-01-10 18:46:34.647
by merging multiple datasets together. The source datasets for this version were:
IPUMS 1920 households: This dataset includes all households from the 1920 US census.
IPUMS 1920 persons: This dataset includes all individuals from the 1920 US census.
IPUMS 1920 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1920 datasets.
https://www.icpsr.umich.edu/web/ICPSR/studies/6836/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/6836/terms
This data collection constitutes a portion of the historical data collected by the project "Early Indicators of Later Work Levels, Disease, and Death." With the goal of constructing datasets suitable for longitudinal analyses of factors affecting the aging process, the project is collecting military, medical, and socioeconomical data on a sample of white males mustered into the Union Army during the Civil War. The project seeks to examine the influence of environmental and host factors prior to recruitment on the health performance and survival of recruits during military service, to identify and show relationships between socioeconomic and biomedical conditions (including nutritional status) of veterans at early ages and mortality rates from diseases at middle and late ages, and to study the effects of health and pensions on labor force participation rates of veterans at ages 65 and over. This installment of the collection, Version C-3, supersedes all previous collections (Versions C-1 and C-2), and contains data from the censuses of 1850, 1860, 1900, and 1910 on veterans who were originally mustered into the Union Army in Connecticut, Delaware, District of Columbia, Illinois, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Vermont, and West Virginia. This version of the collection also contains observations from Wisconsin, Indiana, California, and New Mexico. Census Data, Part 1, includes place of residence, relationship to head of household, date and place of birth, number of children, education, disability status, employment status, number of years in the United States, literacy, marital status, occupation, parents' birthplace, and property/home ownership. The variables in Part 2, Linkage Data, indicate which document sources were located for each recruit.
The average American family in 2023 consisted of 3.15 persons. Families in the United States According to the U.S. Census Bureau, a family is a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered as members of one family. As of 2023, the U.S. Census Bureau counted about 84.33 million families in the United States. The average family consisted of 3.15 persons in 2021, down from 3.7 in the 1960s. This is reflected in the decrease of children in family households overall. In 1970, about 56 percent of all family households had children under the age of 18 living in the household. This percentage declined to about 40 percent in 2020. The average size of a family household varies greatly from state to state. The largest average families can be found in Utah, California, and Hawaii, while the smallest families can be found in Wisconsin, Vermont and Maine.
The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates
Effective Date: December 2018
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.
The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates
Effective Date: December 2018
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Indian Head, MD, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.
Key observations
https://i.neilsberg.com/ch/indian-head-md-median-household-income-by-household-size.jpeg" alt="Indian Head, MD median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Head median household income. You can refer the same here
The typical American picture of a family with 2.5 kids might not be as relevant as it once was: In 2023, there was an average of 1.94 children under 18 per family in the United States. This is a decrease from 2.33 children under 18 per family in 1960.
Familial structure in the United States
If there’s one thing the United States is known for, it’s diversity. Whether this is diversity in ethnicity, culture, or family structure, there is something for everyone in the U.S. Two-parent households in the U.S. are declining, and the number of families with no children are increasing. The number of families with children has stayed more or less constant since 2000.
Adoptions in the U.S.
Families in the U.S. don’t necessarily consist of parents and their own biological children. In 2021, around 35,940 children were adopted by married couples, and 13,307 children were adopted by single women.
The average American household consisted of 2.51 people in 2023.
Households in the U.S.
As shown in the statistic, the number of people per household has decreased over the past decades.
The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”
The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.
Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.
In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.
The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates
Effective Date: December 2018
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Brooklyn Town, Green County, Wisconsin, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Brooklyn Town, Green County, Wisconsin reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Brooklyn town households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Brooklyn town median household income. You can refer the same here
The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates
Effective Date: December 2018
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Dunbarton, New Hampshire, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Dunbarton, New Hampshire reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Dunbarton town households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Dunbarton town median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Fuquay-Varina, NC, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Fuquay-Varina, NC reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Fuquay-Varina households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Fuquay-Varina median household income. You can refer the same here
The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.
Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates
Effective Date: December 2018
Last Update: December 2019
Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.
The layer was compiled from the U.S. Census Bureau’s 2018 Planning Database (PDB), a database that assembles a range of housing, demographic, socioeconomic, and census operational data. The data is from the 2012 – 2016 American Community Survey 5-Year Estimates. The purpose of the data is for 2020 Census planning purposes.
Source: 2018 PDB, U.S. Census Bureau
Effective Date: June 2018
Last Update: January 2020
Update Cycle: Generally, annually as needed. 2018 PDB is vintage used for 2020 Census planning purposes by Nation and County.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Flora, IL, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Flora, IL reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Flora households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Flora median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Brasher, New York, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Brasher, New York reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Brasher town households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Brasher town median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Fenton, IA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Fenton, IA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Fenton households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Fenton median household income. You can refer the same here
This dataset includes all individuals from the 1870 US census.
All manuscripts (and other items you'd like to publish) must be submitted to
phsdatacore@stanford.edu for approval prior to journal submission.
We will check your cell sizes and citations.
For more information about how to cite PHS and PHS datasets, please visit:
https:/phsdocs.developerhub.io/need-help/citing-phs-data-core
This dataset was developed through a collaboration between the Minnesota Population Center and the Church of Jesus Christ of Latter-Day Saints. The data contain demographic variables, economic variables, migration variables and race variables. Unlike more recent census datasets, pre-1900 census datasets only contain individual level characteristics and no household or family characteristics, but household and family identifiers do exist.
The official enumeration day of the 1870 census was 1 June 1870. The main goal of an early census like the 1870 U.S. census was to allow Congress to determine the collection of taxes and the appropriation of seats in the House of Representatives. Each district was assigned a U.S. Marshall who organized other marshals to administer the census. These enumerators visited households and recorder names of every person, along with their age, sex, color, profession, occupation, value of real estate, place of birth, parental foreign birth, marriage, literacy, and whether deaf, dumb, blind, insane or “idiotic”.
Sources: Szucs, L.D. and Hargreaves Luebking, S. (1997). Research in Census Records, The Source: A Guidebook of American Genealogy. Ancestry Incorporated, Salt Lake City, UT Dollarhide, W.(2000). The Census Book: A Genealogist’s Guide to Federal Census Facts, Schedules and Indexes. Heritage Quest, Bountiful, UT