In 2023, the gross median household income for Asian households in the United States stood at 112,800 U.S. dollars. Median household income in the United States, of all racial and ethnic groups, came out to 80,610 U.S. dollars in 2023. Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, Black, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. with 8.6 percent unemployed, according to the Bureau of Labor Statistics in 2021. Hispanic individuals (of any race) were most likely to go without health insurance as of 2021, with 22.8 percent uninsured.

In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Weston town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Weston town, the median household income for the households where the householder is White decreased by $22,457(8.24%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $272,458 in 2013 and $250,001 in 2023.
• Black or African American: In Weston town, the median household income for the households where the householder is Black or African American decreased by $104,084(31.69%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $328,437 in 2013 and $224,353 in 2023.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Weston town.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 Weston town median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Weston town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Weston town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 76.08% of the total residents in Weston town. Notably, the median household income for White households is $250,001. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $250,001.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Weston town.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Weston town median household income by race. You can refer the same here

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2016 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2016 American Community Survey 1-Year Estimates

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

Title SNAP Households by Household Types and Demographics 2016-2020 ACS - SNAP_HH_2020

Summary SNAP Households by type and demographics from 2016-2020 5-year period in NM Census tracts

Notes

Source US CENSUS TABLE FOOD STAMPS/SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM (SNAP) S2201 2020 ACS 5-YEAR ESTIMATE

Prepared by EMcRae_NMCDC

Feature Service https://nmcdc.maps.arcgis.com/home/item.html?id=8c3e62b5050f4bcc8853ecf0130f976d

Alias Definition

ID id

GeoName Geographic Area Name

ETH_1 Estimate Total Households

ETH_2 Estimate Total Households With one or more people in the household 60 years and over

ETH_3 Estimate Total Households No people in the household 60 years and over

ETH_4 Estimate Total Households Married-couple family

ETH_5 Estimate Total Households Other family:

ETH_6 Estimate Total Households Other family: Male householder, no spouse present

ETH_7 Estimate Total Households Other family: Female householder, no spouse present

ETH_8 Estimate Total Households Nonfamily households

ETH_9 Estimate Total Households With children under 18 years

ETH_10 Estimate Total Households With children under 18 years Married-couple family

ETH_11 Estimate Total Households With children under 18 years Other family:

ETH_12 Estimate Total Households With children under 18 years Other family: Male householder, no spouse present

ETH_13 Estimate Total Households With children under 18 years Other family: Female householder, no spouse present

ETH_14 Estimate Total Households With children under 18 years Nonfamily households

ETH_15 Estimate Total Households No children under 18 years

ETH_16 Estimate Total Households No children under 18 years Married-couple family

ETH_17 Estimate Total Households No children under 18 years Other family:

ETH_18 Estimate Total Households No children under 18 years Other family: Male householder, no spouse present

ETH_19 Estimate Total Households No children under 18 years Other family: Female householder, no spouse present

ETH_20 Estimate Total Households No children under 18 years Nonfamily households

ETH_POV_1 Estimate Total Households POVERTY STATUS IN THE PAST 12 MONTHS Below poverty level

ETH_POV_2 Estimate Total Households POVERTY STATUS IN THE PAST 12 MONTHS At or above poverty level

ETH_DIS_1 Estimate Total Households DISABILITY STATUS With one or more people with a disability

ETH_DIS_2 Estimate Total Households DISABILITY STATUS With no persons with a disability

ETH_RHO_1 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER White alone

ETH_RHO_2 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Black or African American alone

ETH_RHO_3 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER American Indian and Alaska Native alone

ETH_RHO_4 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Asian alone

ETH_RHO_5 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Native Hawaiian and Other Pacific Islander alone

ETH_RHO_6 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Some other race alone

ETH_RHO_7 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Two or more races

ETH_RHO_8 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Hispanic or Latino origin (of any race)

ETH_RHO_9 Estimate Total Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER White alone, not Hispanic or Latino

ETH_INC_1 Estimate Total Households HOUSEHOLD INCOME IN THE PAST 12 MONTHS (IN 2020 INFLATION-ADJUSTED DOLLARS) Median income (dollars)

ETH_WS_1 Estimate Total WORK STATUS Families

ETH_WS_2 Estimate Total WORK STATUS Families No workers in past 12 months

ETH_WS_3 Estimate Total WORK STATUS Families 1 worker in past 12 months

ETH_WS_4 Estimate Total WORK STATUS Families 2 or more workers in past 12 months

EPH_2 Estimate Percent Households With one or more people in the household 60 years and over

EPH_3 Estimate Percent Households No people in the household 60 years and over

EPH_4 Estimate Percent Households Married-couple family

EPH_5 Estimate Percent Households Other family:

EPH_6 Estimate Percent Households Other family: Male householder, no spouse present

EPH_7 Estimate Percent Households Other family: Female householder, no spouse present

EPH_8 Estimate Percent Households Nonfamily households

EPH_9 Estimate Percent Households With children under 18 years

EPH_10 Estimate Percent Households With children under 18 years Married-couple family

EPH_11 Estimate Percent Households With children under 18 years Other family:

EPH_12 Estimate Percent Households With children under 18 years Other family: Male householder, no spouse present

EPH_13 Estimate Percent Households With children under 18 years Other family: Female householder, no spouse present

EPH_14 Estimate Percent Households With children under 18 years Nonfamily households

EPH_15 Estimate Percent Households No children under 18 years

EPH_16 Estimate Percent Households No children under 18 years Married-couple family

EPH_17 Estimate Percent Households No children under 18 years Other family:

EPH_18 Estimate Percent Households No children under 18 years Other family: Male householder, no spouse present

EPH_19 Estimate Percent Households No children under 18 years Other family: Female householder, no spouse present

EPH_20 Estimate Percent Households No children under 18 years Nonfamily households

EPH_POV_1 Estimate Percent Households POVERTY STATUS IN THE PAST 12 MONTHS Below poverty level

EPH_POV_2 Estimate Percent Households POVERTY STATUS IN THE PAST 12 MONTHS At or above poverty level

EPH_DIS_1 Estimate Percent Households DISABILITY STATUS With one or more people with a disability

EPH_DIS_2 Estimate Percent Households DISABILITY STATUS With no persons with a disability

EPH_RHO_1 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER White alone

EPH_RHO_2 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Black or African American alone

EPH_RHO_3 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER American Indian and Alaska Native alone

EPH_RHO_4 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Asian alone

EPH_RHO_5 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Native Hawaiian and Other Pacific Islander alone

EPH_RHO_6 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Some other race alone

EPH_RHO_7 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Two or more races

EPH_RHO_8 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER Hispanic or Latino origin (of any race)

EPH_RHO_9 Estimate Percent Households RACE AND HISPANIC OR LATINO ORIGIN OF HOUSEHOLDER White alone, not Hispanic or Latino

EPH_WS_2 Estimate Percent WORK STATUS Families No workers in past 12 months

EPH_WS_3 Estimate Percent WORK STATUS Families 1 worker in past 12 months

EPH_WS_4 Estimate Percent WORK STATUS Families 2 or more workers in past 12 months

SNAP_1 Estimate Households receiving food stamps/SNAP Households

SNAP_2 Estimate Households receiving food stamps/SNAP Households With one or more people in the household 60 years and over

SNAP_3 Estimate Households receiving food stamps/SNAP Households No people in the household 60 years and over

SNAP_4 Estimate Households receiving food stamps/SNAP Households Married-couple family

SNAP_5 Estimate Households receiving food stamps/SNAP Households Other family:

SNAP_6 Estimate Households receiving food stamps/SNAP Households Other family: Male householder, no spouse present

SNAP_7 Estimate Households receiving food stamps/SNAP Households Other family: Female householder, no spouse present

SNAP_8 Estimate Households receiving food stamps/SNAP Households Nonfamily households

SNAP_9 Estimate Households receiving food stamps/SNAP Households With children under 18 years

SNAP_10 Estimate Households receiving food stamps/SNAP Households With children under 18 years Married-couple family

SNAP_11 Estimate Households receiving food stamps/SNAP Households With children under 18 years Other family:

SNAP_12 Estimate Households receiving food stamps/SNAP Households With children under 18 years Other family: Male householder, no spouse present

SNAP_13 Estimate Households receiving food stamps/SNAP Households With children under 18 years Other family: Female householder, no spouse present

SNAP_14 Estimate Households receiving food stamps/SNAP Households With children under 18 years Nonfamily households

SNAP_15 Estimate Households receiving food stamps/SNAP Households No children under 18 years

SNAP_16 Estimate Households receiving food stamps/SNAP Households No children under 18 years Married-couple family

SNAP_17 Estimate Households receiving food stamps/SNAP Households No children under 18 years Other family:

SNAP_18 Estimate Households

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available...Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2013-2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .Accuracy of the Data..). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates

IntroductionPregnant women and their offspring are particularly vulnerable to food insecurity and its adverse effects during critical periods of fetal development. Racially/ethnically minoritized women in the United States (US) who are pregnant are additionally burdened by food insecurity, which may exacerbate cardiovascular health (CVH) disparities. Despite heightened social vulnerability, few studies have employed an intersectional framework, including race and gender, to assess the food insecurity and CVH relationship.MethodsWe used 2012–2018 and 2020 National Health Interview Survey data among US pregnant women aged 18–49 years old (N = 1,999) to assess the prevalence of food insecurity status by race/ethnicity and to investigate household food security status in relation to ideal CVH, using a modified ideal CVH (mICVH) metric. We categorized food security status as “very low/low”, “marginal”, or “high”. To assess mICVH, a summary score of 7 clinical characteristics and health behaviors was dichotomized as yes [(7)] vs. no [<7]. Prevalence ratios (PRs) and 95% confidence intervals (CIs) of associations between food security status and mICVH were estimated using Poisson regression with robust variance. Models were adjusted for age, household income, educational attainment, geographic region, marital status, alcohol consumption, survey year, and race/ethnicity (in overall model).ResultsThe mean age ± standard error was 29.0 ± 0.2 years. Among pregnant women, 12.7% reported “very low/low”, 10.6% reported “marginal”, and 76.7% reported “high” food security. “Very low/low” food security prevalence was higher among NH-Black (16.2%) and Hispanic/Latina (15.2%) pregnant women compared to NH-White (10.3%) and NH-Asian (3.2%) pregnant women. The mICVH prevalence was 11.6% overall and 14.5% for NH-White, 4.1% for NH-Black, 5.0% for Hispanic/Latina, and 26.7% for NH-Asian pregnant women. Among all pregnant women, “very low/low” and “marginal” vs. “high” food security status was associated with a lower prevalence of mICVH {[PRvery low/low = 0.26 (95% CI: 0.08–0.75)]; [PRmarginal = 0.47 (95% CI: 0.23 −0.96)]}.ConclusionHousehold food insecurity was higher among pregnant women in minoritized racial/ethnic groups and was associated with lower mICVH prevalence. Given the higher burden of food insecurity among minoritized racial/ethnic groups, food security may be an important intervention target to help address disparities in poor CVH among pregnant women.

This dataset contains yearly certified enrollment for all public school districts in Wisconsin since the 2008-2009 school year. This data is also available in the WISEdash Public Portal. This dataset is derived from publicly available files on the WISEdash Download Page. Enrollment Count is the number of students enrolled on specific dates as determined by school enrollment/exit dates that cover those dates. Percent Enrollment by Student Group is a percent of the enrollment count for all student groups combined. Reporting Disability is indicated in the pupil’s individualized education program (IEP) or individualized service plan (ISP). A person's race or ethnicity is the racial and/or ethnic group to which the person belongs or with which he or she most identifies. Ethnicity is self-reported as either Hispanic/Not Hispanic. Race is self-reported as any of the following 5 categories: Asian, American Indian or Alaskan Native, Black or African American, Native Hawaiian or other Pacific Islander, or White. The data displayed reflects the race/ethnicity that is reported by school districts to DPI.An economically disadvantaged student is one who is identified by Direct Certification (only if participating in the National School Lunch Program) OR a member of a household that meets the income eligibility guidelines for free or reduced-price meals (less than or equal to 185 percent of Federal Poverty Guidelines) under the National School Lunch Program (NSLP) OR identified by an alternate mechanism, such as the alternate household income form.English Learner status is any student whose first language, or whose parents' or guardians' first language, is not English and whose level of English proficiency requires specially designed instruction, either in English or in the first language or both, in order for the student to fully benefit from classroom instruction and to be successful in attaining the state's high academic standards expected of all students at their grade level.A child is eligible for the Migrant Education Program (MEP) (and thereby eligible to receive MEP services) if the child: meets the definition of “migratory child” in section 1309(3) of the ESEA,[1] and is an “eligible child” as the term is used in section 1115(c)(1)(A) of the ESEA and 34 C.F.R. § 200.103; and has the basis for the State’s determination that the child is a “migratory child” properly recorded on the national Certificate of Eligibility (COE). Eligibility determination is made by a Wisconsin state migrant recruiter during a face-to-face family interview.

When appropriate, means ± standard deviations are provided.p-values were calculated using the Student's t-test or chi-square test where appropriate.*Based on the US Department of Housing and Urban Development method for comparing family income levels as a function of regional costs of living.**The ‘Other’ category includes American Indian, Alaskan Native, Asian, Native Hawaiian or Other Pacific Islander, and those for which ethnicity or race was not provided or for which parents came from different racial or ethnic background.***WASI IQ data available for only 380 subjects out of 431 that were initially recruited.

This graph shows the Percentage of households led by a female householder with no spouse present with own children under 18 years living in the household in the U.S. in 2021, by state. In 2021, about 4.24 percent of Californian households were single mother households with at least one child.

Additional information on single mother households and poverty in the United States

For most single mothers a constant battle persists between finding the time and energy to raise their children and the demands of working to supply an income to house and feed their families. The pressures of a single income and the high costs of childcare mean that the risk of poverty for these families is a tragic reality. Comparison of the overall United States poverty rate since 1990 with that of the poverty rate for families with a female householder shows that poverty is much more prevalent in the latter. In 2021, while the overall rate was at 11.6 percent, the rate of poverty for single mother families was 23 percent. Moreover, the degree of fluctuation tends to be lower for single female household families, suggesting the rate of poverty for these groups is less affected by economic conditions.

The sharp rise in the number of children living with a single mother or single father in the United States from 1970 to 2022 suggests more must be done to ensure that families in such situations are able to avoid poverty. Moreover, attention should also be placed on overall racial income inequality given the higher rate of poverty for Hispanic single mother families than their white or Asian counterparts.

NA: Not applicable, for cells where the zero percent of the population fell into that category.(1) Prevalences and standard errors are calculated using the survey weights from the 5-year visit provided with the dataset. These adjust for unequal probability of selection and response. Survey and subclass estimation commands were used to account for complex sample design.(2) Overweight/obesity is defined as body mass index (BMI) z-score >2 standard deviations (SD) above age- and sex- specific WHO Childhood Growth Standard reference mean at all time points except birth, where we define overweight/obesity as weight-for-age z-score >2 SD above age- and sex- specific WHO Childhood Growth Standard reference mean.(3) To represent socioeconomic status, we used a composite index to capture multiple of the social dimensions of socioeconomic status. This composite index was provided in the ECLS-B data that incorporates information about maternal and paternal education, occupations, and household income to create a variable representing family socioeconomic status on several domains. The variable was created using principal components analysis to create a score for family socioeconomic status, which was then normalized by taking the difference between each score and the mean score and dividing by the standard deviation. If data needed for the composite socioeconomic status score were missing, they were imputed by the ECLS-B analysts [9].(4) We created a 5-category race/ethnicity variable (American Indian/Alaska Native, African American, Hispanic, Asian, white) from the mothers' report of child's race/ethnicity, which originally came 25 race/ethnic categories. To have adequate sample size in race/ethnic categories, we assigned a single race/ethnic category for children reporting more than one race, using an ordered, stepwise approach similar to previously published work using ECLS-B (3). First, any child reporting at least one of his/her race/ethnicities as American Indian/Alaska Native (AIAN) was categorized as AIAN. Next, among remaining respondents, any child reporting at least one of his/her ethnicities as African American was categorized as African American. The same procedure was followed for Hispanic, Asian, and white, in that order. This order was chosen with the goal of preserving the highest numbers of children in the American Indian/Alaska Native group and other non-white ethnic groups in order to estimate relationships within ethnic groups, which is often not feasible due to low numbers.