Economic Security
Households Receiving SNAP, by Race/Ethnicity

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Source: U.S. Census Bureau

What does this measure?

The proportion of households broken out by race and ethnicity that participate in the Supplemental Nutrition Assistance Program (SNAP, formerly known as food stamps).

Why is this important?

The SNAP program provides government funding for people with low incomes to buy food. It therefore is an indication of how many people in a region rely on government assistance to meet their basic needs. Differences among racial and ethnic groups may reflect the economic health of these groups, as well as potential disparities in access to economic opportunity.

How is Westchester County performing?

In 2016-20, 19% of African Americans and 17% of Hispanics in Westchester County participated in the SNAP program, compared to 5% of Asians and 4% of white households. Rates among African Americans and Hispanic households declined 3 points and 2 points from 2011-15 respectively, while rates among Asians and whites were essentially flat.

Participation among all groups in Westchester County was below state and national levels. Rates among African American and Hispanic households were higher in Westchester than both Rockland and Nassau. Rates in Yonkers were higher than the County for all groups: Hispanics (27%), African Americans (24%), Asians (10%) and whites (10%).

Why do these disparities exist?

Historic and current policies and systems, from racist housing policies to employment discrimination to education systems that fail to equitably serve all populations, have prevented people of color from fully participating in our economy, locking them out of economic opportunity. This has increased the need for some groups to access programs to support basic needs such as SNAP.

Notes about the data

The multiyear figures are from the Census Bureau's American Community Survey (ACS). Studies have found that ACS estimates of enrollment in public benefit programs tend to underestimate the true rate. The estimates reported above should be considered a lower bound of the true estimate. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval). The survey provides data on characteristics of the population that used to be collected only during the decennial census.

Studies have found that national survey estimates (including the ACS) of enrollment in public benefit programs tend to underestimate the true rate due to underreporting by participants, compared to state counts of program participants. Underreporting can occur for a variety of reasons, including the social stigma of program participation and participants' confusion about the source of the services they receive. For these reasons, the estimates reported above should be considered a lower bound of the true estimate.

Households Receiving SNAP by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County5%*19%17%4%
Nassau County3%11%7%3%
Putnam County2%***0%***6%***3%*
Rockland County6%*16%*15%10%
New York State13%26%28%10%
Mount Vernon0%***20%21%*9%*
New Rochelle11%***19%*20%*6%*
Peekskill17%***20%***20%**14%***
Rye City0%***0%***8%***1%***
White Plains10%***15%*13%**4%*
Yonkers10%*24%27%10%
Westchester County Towns
Bedford0%***25%***5%***1%***
Cortlandt0%***17%***7%***3%*
Eastchester4%***18%***7%***2%**
Greenburgh2%***10%*5%**2%**
Harrison1%***0%***5%***0%***
Lewisboro0%***N/A***0%***1%***
Mamaroneck0%***15%***5%***2%***
Mount Kisco10%***22%***18%***5%***
Mount Pleasant1%***6%***15%**3%***
New Castle0%***0%***0%***1%***
North Castle3%***0%***4%***1%***
North Salem0%***0%***0%***1%***
Ossining0%***13%***7%**3%**
Pelham6%***0%***4%***1%***
Pound Ridge0%***0%***0%***0%***
Rye17%***23%**11%*4%*
Scarsdale2%***0%***0%***1%***
Somers0%***0%***0%***1%***
Yorktown1%***1%***4%***4%**
Westchester County Villages
Ardsley12%***0%***0%***3%***
Briarcliff Manor0%***0%***0%***3%***
Bronxville7%***N/A***0%***2%***
Buchanan0%***0%***0%***3%***
Croton-on-Hudson0%***18%***2%***1%***
Dobbs Ferry7%***0%***7%***2%***
Elmsford0%***18%***9%***6%***
Village of Harrison1%***0%***5%***0%***
Hastings-on-Hudson0%***0%***35%***2%***
Irvington0%***N/A***0%***0%***
Larchmont0%***0%***0%***1%***
Village of Mamaroneck0%***11%***5%***3%**
Village of Mount Kisco10%***22%***18%***5%***
Village of Ossining0%***16%***7%**3%***
Village of Pelham5%***0%***6%***1%***
Pelham Manor9%***0%***0%***1%***
Pleasantville0%***N/A***0%***4%***
Port Chester37%***30%***12%*7%*
Rye Brook10%***31%***0%***0%***
Village of Scarsdale2%***0%***0%***1%***
Sleepy Hollow0%***12%***21%***7%***
Tarrytown0%***10%***4%***2%***
Tuckahoe0%***30%***17%***4%***

Source: U.S. Census Bureau
Notes: Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




Number of Households Receiving SNAP by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County1,081*10,27612,48510,045
Nassau County1,3165,0144,0178,891
Putnam County9***0***233***1,000*
Rockland County322*1,884*2,2997,364
New York State70,559285,199324,607476,247
Mount Vernon0***3,400809*542*
New Rochelle203***1,269*1,358*951*
Peekskill45***511***616**595***
Rye City1***0***36***45***
White Plains197***444*755**563*
Yonkers378*3,5456,9294,122
Westchester County Towns
Bedford0***32***47***68***
Cortlandt0***201***134***350*
Eastchester47***56***56***240**
Greenburgh66***388*211**403**
Harrison7***0***41***31***
Lewisboro0***0***0***33***
Mamaroneck0***50***71***143***
Mount Kisco13***43***168***185***
Mount Pleasant8***27***365**318***
New Castle0***0***0***53***
North Castle6***0***19***28***
North Salem0***0***0***14***
Ossining0***132***226**263**
Pelham17***0***17***40***
Pound Ridge0***0***0***0***
Rye74***169**581*455*
Scarsdale13***0***0***49***
Somers0***0***0***82***
Yorktown6***9***46***472**
Westchester County Villages
Ardsley20***0***0***38***
Briarcliff Manor0***0***0***67***
Bronxville9***0***0***49***
Buchanan0***0***0***21***
Croton-on-Hudson0***12***5***31***
Dobbs Ferry9***0***34***52***
Elmsford0***63***47***43***
Village of Harrison7***0***41***31***
Hastings-on-Hudson0***0***36***59***
Irvington0***0***0***0***
Larchmont0***0***0***18***
Village of Mamaroneck0***31***71***153**
Village of Mount Kisco13***43***168***185***
Village of Ossining0***132***226**183***
Village of Pelham8***0***17***16***
Pelham Manor9***0***0***24***
Pleasantville0***0***0***80***
Port Chester60***156***581*408*
Rye Brook14***13***0***0***
Village of Scarsdale13***0***0***49***
Sleepy Hollow0***27***320***155***
Tarrytown0***20***30***86***
Tuckahoe0***56***48***83***

Source: U.S. Census Bureau
Notes: Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.








INDICATORS TREND | WESTCHESTER
Early Prenatal Care, by Mother's Race/Ethnicity 1
Increasing
Infant Mortality Rate, by Race/Ethnicity 10 Not Applicable*
Children with Elevated Blood Lead Levels 0
Maintaining
Children Receiving Subsidized Child Care -1
Decreasing
Children Living in Poverty, by Race/Ethnicity 1
Increasing
Disengaged Youth, Ages 16 to 19 -1
Decreasing
Single-Parent Families, by Race/Ethnicity 1
Increasing
Single Female-Headed Households 0
Maintaining
Contributions as a Percentage of Income 0
Maintaining
Voter Registration Rate 1
Increasing
Voter Participation Rate 1
Increasing
Serious Crimes -1
Decreasing
Victims of Domestic Violence -1
Decreasing
Arrest Rates, by Race/Ethnicity 10 Not Applicable*
Households With Internet Access, by Race/Ethnicity 10 Not Applicable*
Households without Vehicles -1
Decreasing
Means of Transportation to Work, by Race/Ethnicity -1
Decreasing
Air Quality 1
Increasing
Population Density 0
Maintaining
Water Quality of the Long Island Sound 1
Increasing
Open Space in Westchester County 1
Increasing
Change in Total Population 1
Increasing
Change in Population, by Race/Ethnicity 1
Increasing
Change in Population, by Age -1
Decreasing
People with Disabilities 1
Increasing
Language Diversity 1
Increasing
People 65 or Older Living Alone 1
Increasing
Change in Total Jobs -1
Decreasing
Change in Jobs by Sector 10 Not Applicable*
Business Ownership, by Race/Ethnicity 10 Not Applicable*
Average Salary by Sector 10 Not Applicable*
Median Household Income, by Race/Ethnicity 0
Maintaining
Female to Male Earnings Ratio 0
Maintaining
Unemployment Rate, by Race/Ethnicity 1
Increasing
People Living in Poverty -1
Decreasing
People Living in Poverty, by Race/Ethnicity 0
Maintaining
Seniors Living in Poverty 0
Maintaining
Seniors Living in Poverty, by Race/Ethnicity 1
Increasing
Food Insecurity -1
Decreasing
Households Receiving SNAP, by Race/Ethnicity 0
Maintaining
Public Assistance 0
Maintaining
People Receiving Supplemental Security Income 1
Increasing
Homeownership Rate, by Race/Ethnicity 1
Increasing
Cost of Homeownership, by Race/Ethnicity 10 Not Applicable*
Overall Housing Cost Burden -1
Decreasing
Cost of Rent, by Race/Ethnicity 10 Not Applicable*
Rent Burdened Households -1
Decreasing
Homelessness, by Race/Ethnicity 10 Not Applicable*
Homelessness, by Sex 10 Not Applicable*
Per-Student Spending 0
Maintaining
Student Suspensions -1
Decreasing
Student Performance on Grade 3 English, by Race/Ethnicity 1
Increasing
High School Cohort Graduation Rate, by Race/Ethnicity 1
Increasing
College Admission Rate, by Race/Ethnicity 1
Increasing
College Enrollment Rate, by Race/Ethnicity -1
Decreasing
Education Levels of Adults, by Race/Ethnicity 1
Increasing
People Without Health Insurance -1
Decreasing
Mortality Rate, by Race/Ethnicity 10 Not Applicable*
Mortality Rate from Chronic Lower Respiratory Disease, by Race/Ethnicity 10 Not Applicable*
Diabetes Mortality, by Race/Ethnicity 10 Not Applicable*
Suicide Rates, by Race/Ethnicity 10 Not Applicable*


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