poverty

Data Drives Community Change in Southwest Missouri

In southwest Missouri, there is a bit of a chicken and egg problem.

What came first, the high teen birth rates or the low access to primary care physicians?  Children eligible for free and reduced lunch or the unemployment rate? What is the root cause of the disparities in southwest Missouri?

Birth rates for teens in McDonald County are four times that of the national average. Over 30 percent of the population is living below the Federal Poverty Level (FPL). Sixty-nine percent of schoolchildren are enrolled in free and reduced lunch programming. Twenty-five percent of children experienced food insecurity, while six percent of those children were deemed ineligible for assistance. More than 5,000 families are eligible to utilize the Women, Infants, and Children (WIC) program – but only about 11 percent of those families are are using the WIC services.

“It is difficult to move out of McDonald County,” Debbie Markman, Resource Development Director for the Economic Security Corporation (ESC) said. “You either have zero income or less than $300 per month or you make over the 50 percent of the area median gross income because you work at the chicken plants that they pay well and provide good benefits. We have people doing ‘sustenance living’ – growing their own food and sometimes are living in places that don’t have electricity or running water. It’s like the county is split in two.”

For four counties in southwest Missouri – Barton, Jasper, Newton, and McDonald – navigating the challenges of their community needs falls under the mission of the Economic Security Corporation (ESC). ESC works with communities to alleviate the conditions of poverty and provide individuals and families with opportunities that will enable them to achieve economic security.

When the time came to update the community needs assessments for the four counties, ESC turned to Community Commons to explore the areas of greatest need in their communities and to present that data in a compelling way to board members. The utilization of the community data provided unparalleled insight into a path toward community-wide economic security.

“The data we discovered has started so many conversations and really has given us a place to start from,” Markman said. “We’ve been able to talk about why things are happening and what can be done to fix it. Our goal is developing programs that have evidence-based processing behind it.”

ESC is now leading an effort to address three to five major priorities and hope to start implementation on these priorities over the next five years.

Poverty and the Risk for Severe Influenza Outcomes

From access to quality education and job opportunities, to adequate sidewalks and green spaces, social and environmental factors have a huge impact on the health and well being of residents within a community, especially communities in poverty. Access to health care – including vaccinations and treatment for influenza – is no different.

On average, tens of thousands of people die from influenza each year, anywhere from 3,300 to 49,000. Influenza, a vaccine preventable disease, is incredibly contagious and can be spread by people who cough, sneeze, or even talk near someone. It is most dangerous for people with preexisting health conditions such as hearth and lung disease, as well as the very young, very old, and pregnant women. Knowing what we know about the spread of flu and those who are historically at risk, it’s important to consider how poverty and access to health care come into play.

According to the Centers for Disease Control and Prevention (CDC), those living in poverty are at increased risk for severe influenza outcomes, resulting in hospitalization or even death. Communities with high populations in poverty also tend to have ever-present barriers to immunization –decreased access to transportation, medical care, financial resources, and sick leave, to name a few. When barriers like these factor into an individual’s ability to live their healthiest life, the consequences can be dire. As a result, communities across the nation have begun to “meet people where they are” – both physically and financially, to provide immunization education information, and low or no cost vaccines.

Data published by the American Academy of Pediatrics suggests that community-based immunization programs often serve as a conduit to increasing vaccination rates across the board, especially with the flu vaccine. Programs such as school-based vaccination clinics, funded in part or whole by community partners and national organizations, focus on children in their community. Clinics in these settings are incredibly effective at providing vaccines for a large number of children while also reducing the spread of the flu in their schools, homes, communities.

It’s important for communities to be engaged in and increasing focus for flu vaccination outreach and early use of antiviral treatment in order to prevent the spread of the flu. Anyone can become sick from influenza. Education about what resources are available in your community is an easy first step to keep your community happy and healthy. Are you working on unique ways of reaching out to your community during this flu season? Let us know in the comments!

Collaboration Is Key to Producing Timely School District Poverty Estimates

This article was written by Carolyn Gann, Social, Economic and Housing Statistics Division. It was originally published to the Census blog, Random Samplings, on December 14, 2016.

Many factors play a role in a child’s educational success, and it is the mission of the U.S. Department of Education to promote excellence in education and ensure equal access. To help achieve this goal, the Department of Education plans to provide over $15 billion in federal funds to qualifying Title I school districts for the next school year. These funds will improve the academic achievement of children living in poverty. To identify school districts with children in poverty, the Department of Education partners with the U.S. Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program. The SAIPE program produces the only source of single-year statistics of childhood poverty for the nation’s more than 13,000 public school districts.

To estimate the number of children living in poverty within a school district, the SAIPE program pays special attention to school district boundary changes. Today’s release of the 2015 SAIPE reflects the most recent school district boundary update.

In the latest update, for 2015 and 2016, there are 13,245 U.S. public school districts. This is down from 13,486 school districts from the previous update for 2013 and 2014, a decrease of 241 school districts. Changes are typically the result of school districts shifting, splitting or consolidating boundaries, often driven by state or local policy changes.

Figure 1 shows a hypothetical secondary (often grades 9-12) school district (Sec. D) that covers the same geographical boundaries as three distinct elementary (often

grades K-8) school districts (Elem. A, Elem. B, and Elem. C). As they stand in the figure, each school district would be financially responsible to provide services to school-aged children within their district’s grade range. For these four hypothetical school districts, the Department of Education would use SAIPE along with other data sources to determine Title I eligibility and funding allocations.

We often see elementary and secondary school districts (like those in Figure 1) consolidated into one unified school district. In the latest boundary update, this type of consolidation occurred throughout Vermont as well as other states. Additionally, many neighboring unified school districts consolidated to form larger entities. Figure 2 displays a side-by-side comparison of the unified and elementary school district boundaries in Vermont before and after the latest boundary update. Before the latest boundary update, Vermont had 276 school districts. Now Vermont has only 60 school districts.

Figure 2 illustrates the kind of widespread boundary changes that can occur after a school district boundary update. When a school district boundary changes, there is a change in the number of school-aged children living in the district, including children who are living in poverty. Capturing the latest school district boundary changes is crucial for the SAIPE program to produce timely and accurate estimates of childhood poverty.

Given the SAIPE data’s timeliness and adaptability, we can examine how childhood poverty in school districts changes over time. To illustrate these changes, the recent SAIPE data release includes an animated map displaying data from 2007 through 2015. The year 2007 serves as a base year before the most recent recession. In the animated map, the lighter colors represent lower poverty rates, and the darker colors represent higher poverty rates. The animation allows us to see the changes in childhood poverty before, during and after the recession.

Figure 4 focuses on school districts with high poverty (at or above 20.0 percent). This figure displays annual SAIPE data back through 1999 and constructs a fuller picture of pre- and post-recession trends for school districts with high poverty. Since the most recent recession, there has been an increase in the percentage of school districts with high poverty. Since 2013, we are only just beginning to see that percentage decrease.
As the composition of childhood poverty changes over time, it is necessary for the Department of Education to identify all Title I qualifying districts and distribute funding where it is needed most. This work by the School District Review and SAIPE programs are two of many examples of how agencies work together to meet administrative needs for delivering resources, while ensuring the quality and accuracy of the information available to all stakeholders.

New Data Shows Poverty Rates Lower in 23 States

This article was written by Brian Glassman, Poverty Statistics Branch. It was originally published to the Census blog, Random Samplings, on October 13, 2016.

The official poverty rate for the United States declined in 2015 to 13.5 percent from a rate of 14.8 percent in 2014. However, this decrease in poverty was not uniform across states or Metropolitan Statistical Areas when looking at data from the American Community Survey — another key data source for examining poverty at state and local levels. In fact, poverty rates decreased in 23 states and did not increase in any state in 2015, as shown in Figure 1. However, poverty rates in 27 states and Washington, D.C., were statistically unchanged.

Many factors contribute to a change in a state’s poverty rate. The bar chart below shows several possibly related economic factors that give a broader sense of the economic changes happening within states. From 2014 to 2015, unemployment rates decreased and median household income increased in each of the 23 states where poverty decreased. For the 27 states and Washington, D.C., that had no change in poverty in 2015, unemployment decreased in 14 states and Washington, D.C., and median income increased in 16 states and Washington, D.C.

Estimates of households with income under $10,000 and households receiving food stamp/SNAP benefits are two other conditions potentially related to poverty status. In 2015, there were 12 states where both poverty rates and the percentage of households with food stamp/SNAP benefits decreased. In 11 states, the poverty rates did not decrease but the percentage of households receiving food stamp/SNAP benefits fell.

There were 16 states where poverty rates fell and the percentage of households with income less than $10,000 also fell. However, in three states and Washington, D.C., the percentage of households with income less than $10,000 fell without a drop in the poverty rate. To see changes from 2014 to 2015 in poverty rates, unemployment rates, median income, food stamp/SNAP participation and percentage of households with income below $10,000 for each state, visit <https://www.census.gov/data/tables/2016/demo/income-poverty/glassman-acs.html>.

The chart below shows that changes were not uniform across metropolitan statistical areas (MSAs), even for those MSAs in a state that experienced a decline in poverty. Between 2014 and 2015, out of a total of 380 MSAs, poverty rates decreased in 63 and increased in 14. The Washington, D.C., MSA is not included in this analysis. The chart also separates MSAs into two categories: (1) those in the 23 states that experienced a decrease in poverty rates from 2014 to 2015 and (2) those in the 27 states that experienced no change in poverty rates. If an MSA crosses state borders, it is assigned to the state where the majority of its population resides.

The key thing to note from the chart is that a decline in the state poverty rate may not be shared by all MSAs in the state. Poverty rates increased in some MSAs located in states in which poverty rates decreased (this includes Asheville, N.C.; Redding, Calif.; Hinesville, Ga.; Sebring, Fla.; Corpus Christi, Texas; Killeen-Temple, Texas; and Lubbock, Texas). Similarly, even in states that experienced no significant change in state poverty rates, some MSA poverty rates did change.

Click the map to zoom to your area.

Teen Pregnancy in New Mexico

Pregnancy for teen girls (age 15-19) has decreased nationwide over the past two decades. Between 1990 and 2011 the teen pregnancy rate decreased from 116.9 to 52.4 pregnancies per 1,000 teen girls.

Rates fell among all racial/ethnic groups. Among Hispanic and Black teen girls, the decline has been the most dramatic, with each group seeing a 50 percent and 44 percent decline, respectively.

Much of the decline can be attributed to fewer teen girls having sex (a 7 percent decline from 1988 to 2013), better use of contraception, and more effective messaging around teen pregnancy prevention.

However, in rural areas across the U.S., teen pregnancy rates are still high. Places like New Mexico contend with not only large, rural counties, but also high rates of poverty.

Teen pregnancy in New Mexico

While teen pregnancy rates declined in New Mexico by 42 percent between 1998 and 2011, it’s not decreasing as quickly compared to the rest of the U.S. New Mexico currently ranks 50th in teen pregnancy rate and 46th in teen birth rates. Moreover, in New Mexico, the rate for teen pregnancies is 72 per 1,000 teen girls (age 15-19).

Living in rural, impoverished areas is a significant factor for the higher rates of teen pregnancy. Teens who drop out of high school are more likely to become pregnant. New Mexico’s dropout rate in 2011 was 37 percent; the national average is 22 percent. It’s also noted that teens who live in more rural areas are more likely to become pregnant – and of New Mexico’s 33 counties, 26 are designated as rural.

Another challenge many rural areas are working to overcome is the shortage of hospitals and clinics that offer access to obstetrics services.

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Access to OB/GYNs in New Mexico

Rural areas across the U.S. struggle with limited access to hospitals, health professionals and specialists like OB/GYNs. In New Mexico, many expectant mothers drive more than 100 miles to reach the nearest obstetrics services. In New Mexico, 11 counties lacked any OB/GYN services and seven lacked and OB/GYN doctor or certified nurse midwife. According to William Rayburn, an OB/GYN professor at the University of New Mexico, the lack of doctors and services is due to the supply of OB/GYNs not keeping up with New Mexico’s growing population.

Click on image to zoom to specific area or to create your own map.

While economic and geographical factors can play a significant in teen pregnancy, there’s a wider social issue at play. Many teens who drop out of high school don’t believe they have any chance of economic opportunity or advancement  because they were born into impoverished households. They don’t only drop out of high school, but also the economic mainstream, as one study suggests. So the same mentality (and poverty) is passed onto their kids.

Mapping Student Achievement in Areas of Poverty

There are many factors that influence performance and educational outcomes for children. One of the key factors that research highlights time and time again is poverty. Students who grow up in poverty are less likely to complete higher education, more likely to live in single parent households, experience poorer health outcomes, and rely more on public assistance. While achievement gaps among races have narrowed, achievement gaps between poor and non poor are widening.

Poverty

The US has more than 1 in 5 children living in poverty. Needless to say, many of these students are concentrated  in schools located in areas of poverty. Free and reduced price lunches are a measure for the concentration of low income students in a school. Poverty levels in schools are categorized based on the percentage of students receiving FRPL.

  • Low- poverty schools: 25 percent or less of students eligible for FRPL
  • Mid- low poverty schools: 25.1-50 percent of students eligible for FRPL
  • Mid- high poverty schools: 50.1-75 percent of students eligible for FRPL
  • High-poverty schools: 75 percent or more of students eligible for FRPL

Cities have higher percentages of public schools located in areas of poverty. In 2012-2013, 40 percent of students in cities attended high poverty schools, compared to 17 percent for students in suburban areas and 14 percent for students in rural areas (see table, here).  Higher percentage of Asian students, White students, and students of two or more races attend low- poverty schools, whereas higher percentages of Black, Hispanic, American Indian/Native American students attend high- poverty schools.

The maps below demonstrate education outcomes for students who attend schools in areas of poverty.

free-or-reduced-lunch

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Proficiency Scores

Legislation requires states report standardized test scores to the Department of Education. The data below shows student performance on standardized Math tests in the 4th and 8th grade. The test scores were lower in 2015 than in 2012, but higher than 1990. However, there are clear achievement gaps when comparing races. White and Asian students had higher average math scores than Black and Hispanic students in 1990, 2012, and 2015; though achievement gaps have narrowed in recent years. Perhaps not too surprising, average math scores were lowest in high-poverty schools, but increased, respectively, in mid-high, mid-low, and low poverty schools. The map below looks at majority-minority schools performance on math proficiency tests.

san-antonio-tx-math-test-scores-not-proficient

Graduation Rate

The 2013-2014 school year saw a record cohort high graduation rate of 82 percent. That’s measuring the percentage of students who graduated with a high school diploma within 4 years of the first time they started the 9th grade. The problem is that in every state that reported graduation rates, low-income students graduate at lower rates than their non low-income peers. In states like Minnesota, the difference was a staggering 28 percent. Unfortunately, many of these students will remain low-income – continuing the cycle of poverty.

grad-rate

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Limited English Proficiency

Another important indicator to look at related to school performance is English proficiency. In the 2013-2014 school year, 9.3 percent of students were English Language Learners (ELL)- that’s higher than previous years. While school performance for ELLs varies across states, the achievement gap between them and non ELL students is still significant. In the US, not quite one-third of ELLs scored at the basic level or above in 8th grade math, compared to three-quarters of non-ELLs.

san-antonio-tx-population-with-limited-english-proficiency-age-5-to-17

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School District Spending Per Student

The map below shows spending per student for school districts. As you can see, many areas, especially those with lower test scores and graduation rates, receive anywhere from 10-33 percent less spending on students compared to the U.S. average. There’s a lot of complexities to account for, but it’s interesting to see how spending in your area correlates with student performance – and to see where spending is concentrated.

Based on an Education Week analysis of federal data, this map displays spending per student for school districts in the 2013 fiscal year. Expenditure amounts have been adjusted for regional differences in cost of living, using the NCES Comparable Wage Index 2013 as updated by Lori Taylor of Texas A&M University. The map displays “regular” school districts and does not include supervisory unions, regional education service agencies, other non-standard agency configurations, or districts missing student enrollment information. Some school district boundaries may have changed since this analysis. Source: Education Week, U.S. Census Bureau Credit: Katie Park, Alyson Hurt, Tyler Fisher and Lisa Charlotte Rost/NPR

Based on an Education Week analysis of federal data, this map displays spending per student for school districts in the 2013 fiscal year. Expenditure amounts have been adjusted for regional differences in cost of living, using the NCES Comparable Wage Index 2013 as updated by Lori Taylor of Texas A&M University. The map displays “regular” school districts and does not include supervisory unions, regional education service agencies, other non-standard agency configurations, or districts missing student enrollment information. Some school district boundaries may have changed since this analysis.
Source: Education Week, U.S. Census Bureau
Credit: Katie Park, Alyson Hurt, Tyler Fisher and Lisa Charlotte Rost/NPR

Creating a level playing field in education will require policy to look at how poverty impacts student achievement. As the data shows it takes more than “pulling yourself up by the bootstraps” for students to achieve educational success and become economically mobile like their peers in more affluent areas- especially when there are factors at play that can impact the trajectory their life before they are even born. Students who grow up in poverty are not resigned to that condition, but as more children and families are being aversely impacted by poverty, its role should play a more meaningful part in the education debate moving forward.

Seven Things You Should Know About Childhood Poverty

This article was written by Caroline Ratcliffe and Nicole Levins. It was originally published in October of 2016 on Urban Wire.

For millions of poor children, the United States is not the land of opportunity. Childhood poverty can have lifelong consequences, affecting future health, education, earnings, and more.

These consequences can even stretch into future generations. Many poor children grow up to become poor adults, and as they have children of their own, the cycle of poverty continues.

What else should you know about childhood poverty?

Children in Poverty

Racial breakdown of children in poverty in the counties of Maricopa and Pima, AZ.

Racial breakdown of children in poverty in the counties of Maricopa and Pima, AZ.

  1. Reaching poor children as early as the day they’re born. Since most children in the United States are born in hospitals, that’s a great place to start. Social workers could connect newborns and new moms to programs that can help them avoid the poverty trap, such as public health insurance, food assistance, and even home-visiting opportunities and parenting classes.
  2. Ramping up educational opportunities for children and their parents. Getting children in Head Start and other school readiness programs prepares them for primary school. Additional funding for Early Head Start would expand the reach of educational and other supports for younger children and their families. And workforce programs that help parents gain skills, get jobs, and advance in the workplace can help the whole family. headstart and poverty
  3. Helping kids stay in the same schools when struggling families move. Poverty and housing instability are deeply connected, and a family move can disrupt a child’s education. Flexible policies that let kids stay in the same school when they move across school boundary lines could improve academic performance.
  4. Enacting place-conscious strategies. We need policies that address neighborhood conditions and help poor families move out of disadvantaged neighborhoods to places with better schools and more opportunities.

To read the original article, click here.

Aging in America Part 2: Healthy Aging Initiatives

September is Healthy Aging Month. To help raise awareness we are featuring a two part series that focuses on the unique challenges aging adults in the US face and initiatives that support them in living healthy, active lives. 

One in three Americans is 50 years old or older; by 2030 one in five Americans will be 65 or older. America’s look is changing and so should our communities.

In an effort to help older adults “age in place”, the Community Innovations for Aging in Place Initiative (CIAIP) was authorized by Congress in 2006. CIAIP began funding community projects that sought to identify barriers for older adults in their communities and find ways to sustain their independence at home and in the community.

As we emphasized in our previous post about aging in America, creating livable communities for all citizens, especially senior citizens, requires mobilization at the local level.

Here are some initiatives that are helping older adults live healthy, active lives.

Atlanta Regional Commission- Lifelong Communities

ARC’s Lifelong Communities initiative focuses on providing a high quality of life for residents of all ages and abilities. They focus on three areas:

  • Housing and transportation options
  • Encouraging healthy lifestyles
  • Expanding information and access to services
ccMapExport (69)

Click image to see specific area.

In 2014 part of the Old 4th Ward in Atlanta was turned into a model of what a Lifelong Community looks like. It’s an example of how any community can become a Lifelong Community.

SOWN: Growing Healthy Lives Together

Located in Philadelphia, PA, SOWN (Supportive Older Women’s Network) supports adults 50+, mostly women, to lead healthy lives in their homes and in the community. They specifically work to reduce isolation through five programs:

  • GrandFamily Resource Center
  • Philly Families Eat Smart
  • Counseling for Homebound Adults: Telephone Support Groups
  • Parkinson’s Care Partners Support Groups
  • Healthy Lives: Community Support Groups & Workshops
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Click image to see specific area.

They reach more than 800 older adults annually in the Philadelphia area through in-person and teleconferencing services and are the only Pennsylvania provider who provides teleconferencing mental health services for older adults.

NORC Health Plus (NHP)

New York City Department for the Aging’s Naturally Occurring Retirement Communities (NORC) Health Plus program is part of the Neighborhood Health Plan (NHP) in four New York City NORCs in Queens, Manhattan, the Bronx, and Brooklyn. Their goal is to empower older residents so they can self-manage their physical and mental health needs. Through partnerships with health associations, colleges, and organizations focused on helping older adults, they have made great improvements in NORCs residents’ access to mental health services. Here are some of the following highlights:

These are great starts to caring for aging adults in our communities and more will be needed as our population gets older over the coming decades. With rising costs of living it’s becoming all the more important to focus on initiatives that can ease the burden at the local level and create healthy, active places where children and older adults can age with ease.

CIAIP’s website has resources and tools communities can use to implement programs that help older adults sustain their independence.

Aging in America Part 1: Challenges for Senior Citizens

September is Healthy Aging Month. To help raise awareness we are featuring a two part series that focuses on the unique challenges aging adults in the US face, and initiatives that support them in living healthy, active lives. 

Did you know roughly 10,000 Baby Boomers turn 65 everyday? Did you know, currently, more than 25 million of them live at or below 250 percent of the federal poverty level? While millions had good jobs where they could save and invest in 401(k) plans, others impacted by job loss, the financial crisis, or other circumstances find themselves relying solely on Social Security- which on average, is $1,262 a month. That wouldn’t even cover rent in some of the US’s coastal cities.

Budgeting on this amount when you have the added expense of food, transportation, and medical bills, the “Golden Years” of retirement become anything but, for millions. With nearly 1 in 10 seniors (aged 65+) living in poverty it can be a challenge to get by just day to day.

Below is a map showing poverty levels among senior citizens in Pittsburgh, PA- one of America’s most senior-dominated cities.

Click image to see specific area.

Click image to see specific area.

The struggles associated with poverty are felt in every corner of the US, but for seniors, it’s a unique struggle in a country built around the young and mobile.

Lack of transportation

Transportation is one of those overlooked issues for seniors. For many of us, we simply get in our car or hop on a bike when we want to go somewhere. For seniors it’s not that easy- and often comes at an additional cost. Seniors on a fixed income must not only keep up with the cost of rising housing, medical costs, and food, but also the cost that comes with not having your own transportation.

Many seniors don’t want to feel like they are a burden so often forgo asking friends and relatives for a ride; others simply can’t afford the bus fare or live in areas where bus schedules are limited or nonexistent.

 

Click image to to see specific area.

Click image to see specific area.

For those with frequent medical appointments it’s a costly inconvenience that can affect their health. Which is why it is good to see how some hospitals are coming up with innovative ways to make sure their patients don’t miss an appointment by partnering with Uber and Lyft.

Rising cost of rent

We all know housing costs are rising across the board- for everyone. The lack of affordable housing impacts everyone from single parents working two to three part-time jobs to older adults.

Most seniors spend 35 percent of their income on housing. If they are just living on government benefits like Social Security, their housing is likely taking up at least 40 percent of their income (30 percent is generally the recommended threshold). This isn’t necessarily adequate housing either. In some housing units living conditions could be overcrowded, in need of serious maintenance, and/or lack plumbing.

Click image to see specific area.

Click image to see specific area.

For aging seniors in need of assistance with daily activities, options are grossly limited as well. Assisted living facilities aren’t always a viable option due to the expense- averaging more than $3,000/month. Fortunately, the US Department of Housing and Urban Development has counselors that help seniors explore housing options, whether it’s continuing to live at home, finding approved housing units, or learning how to protect against housing discrimination.

Health care costs

With the senior population growing- expected to number more than 87 million by 2050- health care will become even more impacted than it is now. Because most seniors are eligible for Medicare, and some for Medicaid, the government pays for most of seniors’ medical expenses.

However, out-of-pocket costs are still high for seniors. To put in perspective, it’s estimated that a 65 year old couple retiring in 2013 would need to save $240,000 to cover future medical expenses– not including long-term care. Premiums, deductibles, co-pays, out-of-pocket prescription drugs, and non covered items like hearing aids and glasses are calculated into that cost. And on average, Medicare beneficiaries spend 15 percent of their household income on health care costs, that’s three times more than non Medicare households.

Access to nutritional foods

Food insecurity is a serious issue among seniors. Seventeen percent of Feeding America’s clients are seniors. And in the US nearly 5.5 million seniors are food insecure, 1.2 million of them live alone. 

Click image to see specific area.

Click image to see specific area.

Most seniors report that the greatest benefit of aging is having more time to spend with loved ones. Still, there are challenges millions of seniors contend with on a daily basis, which is why it is all the more important to focus on what we can do at the local level, together and as individuals. Through the MetLife Foundation, communities all around the country are reimagining ways to not only keep seniors mentally and physically healthy, but also strengthen their connection to the community- which is key.

It’s a strategy that fits into the overall movement of transforming the places we live, work, and play into vibrant, connected communities where we consider the needs of all our citizens, from kids walking to school to young and middle-aged adults biking to work to enabling seniors’ ability to get to medical appointments or activities around town.

Stay-tuned for our upcoming “Aging in the US Part 2” post that will feature initiatives from around the country that are supporting aging adults in living healthy, active lives.

 

Three Ways to Invest in Banking Deserts

We have seen countless innovative and impactful programs rise up from the local level, whether it’s working to reduce health disparities or to improve food access. That’s often where the most meaningful work happens. Just take a look at the mobile food market program by the Chattanooga-Hamilton County Health Department who drive their truck around to underserved communities or a grant services coordinator at a community college trying to improve access to mental health services for students. For them, it’s about creating equity where they see it’s needed.

With growing economic disparities, in rural and urban areas alike, state and local governments are exploring ways to revitalize their communities. Poverty and unemployment are still high in many communities, with some never rebounding from the economic downturn in 2009.

poverty

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Since poverty is associated with limited access to basics like healthy food, health care, and jobs, it’s perhaps not too surprising to see that they also lack access to mainstream financial services. That means they are either geographically isolated from mainstream financial institutions, or they simply do not qualify for any type of home, auto, or small business loan. The lack of accessibility, both geographically and economically, makes it that much harder to invest in the residents and the community as a whole.

Nearly 5,000 bank branches have closed since the economic downturn. That’s roughly a 5 percent decrease in the total number of branches. It might not seem like a startling statistic, but the impact is disproportionately felt in low income communities. The absence of these branches creates a “banking desert” or a census tract area that has no branches within 10 miles. Even this small distance can reduce the amount of mortgages and small business credits in an area.

As families try to balance low-wage jobs and rising costs of living, life in a banking desert makes it more difficult to seize those opportunities that help families build their “American Dream.” The engine that once helped fuel small businesses and job opportunities in communities has all but come to a halt.

jobsmaps

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Since the recession, loans to small businesses have decreased by 20 percent, while loans to larger businesses have grown by 4 percent. This impacts small business owners, families, and their communities. But it does not have to stay that way. With new, innovative ideas, state and local governments are finding ways to fill the growing financial services gap in their communities.

Banking and Credit Union Development Districts

Texas is one of the most “unbanked” states in the US, and Dallas the most unbanked city in the US. More than 35 percent of households either have no bank account or just rely on check cashers. To improve access to mainstream financial services State Representative Eric Johnson, who saw the lack of financial services offered in the communities he represents, helped pass legislation to improve access in unbanked and underbanked areas.

The idea is to allow local and state governments to “seed” banking and credit union development districts. The newly opened branches would receive deposits from the city treasury to help get them up and ready to do business. In turn, the branches would be eligible for tax breaks and other incentives. A similar model ran in New York in 1997 and was met with success. More than 60,000 bank accounts were opened and loans totaling $538.8 million were extended to residents for mortgages and businesses.

Prize-Linked Savings and Lotteries

Prize-linked savings go hand in hand with banking and credit union development districts. To incentivize locals to open bank accounts, apply for loans, and use other financial services, bank branches offer chances to win a lottery. For example, every time a customer deposits $25 in their account, they are entered for a chance to win $10,000. Since 2009 these efforts have resulted in 50,000 new savings accounts and more than $94 million in total savings.

Community-Driven Financial Institutions (CDFIs)

CDFIs are banks, credit unions, loan funds, or venture capital providers that expand opportunity in low-income communities. They’ve been a great response to the growth of banking deserts, but even more, have provided economic opportunity in all types of communities across the US.

cdfi

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Unlike traditional lenders who work for shareholders, CDFIs look beyond the bottom line to opportunities that help revitalize communities, whether through financing homes for first-time buyers, investing in needed schools and health centers, or lending to residents who want to open their own businesses. CDFIs are funded through federal, state, and local governments, religious institutions, individuals, and public donations.

In 2011, Starbucks launched its Create Jobs for USA Fund which has donated more than $7 million to CDFIs. The money is used to help business owners gain access to capital they otherwise wouldn’t have access to in low-income areas. However, it doesn’t stop there. CDFIs also provide business education opportunities to small business owners on topics like business marketing strategies, cash-flow management, accounting, and employee training. There are countless success stories of how CDFIs helped small businesses grow and revitalize their communities.

While CDFI interest rates tend to be higher, and they are limited in how much they can lend, they continue to provide capital (and opportunity) for hardworking individuals and businesses that simply need a hand up during tough times.

Member Spotlight: Alleviating Food Insecurity in Rural North Carolina

sandi rice manna

Over the last 5 years, MANNA FoodBank’s food distribution has increased from 7 million pounds annually to now, more than 15 million pounds. With food insecurity increasing across the country, foodbanks like MANNA must continually look for partnerships that help them get “meals on the ground” wherever needed in their 16 county network. In her AmeriCorps Vista position, Sandi Rice was tasked with identifying underserved areas in MANNA’s western North Carolina network. For the next 7 months Rice spent time creating census tract level data maps of children living in poverty and found that the data also correlated with child food insecurity rates. The result is an impressive series of maps that have not only helped MANNA identify underserved areas, but also help inform their decisions on what partners to reach out to in those areas.

Hi Sandi. Thanks for talking with us! Could you start off by telling us a little bit about MANNA FoodBank?

MANNA Food Bank is a non-profit organization that is affiliated with Feeding America, the National Food Bank Association, and MANNA FoodBank, is one of seven food banks in North Carolina. We’re located in Asheville, North Carolina and serve the sixteen western North Carolina counties. Buncombe County, which is where Asheville is, has about 250,000 people and it goes down dramatically after that, as far as counties are concerned. Last fiscal year – so 2014/2015, MANNA provided over 15 million pounds of food to those in need.

We serve approximately 240+ partner agencies in those communities- most of which are food pantries and other food sites, whether it’s a soup kitchen or a senior center that provides assistance to low-income individuals and families.

Can you talk some about food access issues in your region? What populations are most impacted by food insecurity?

Well, in North Carolina, what we’re seeing are people who are at 185% of the poverty level and that in particular, are families with children who qualify for FNS, food stamps, SNAP- also poverty among the elderly, 65+. But rural communities have those living in extreme poverty. We have one entire county, Clay County, where the childhood poverty for the entire county is above 55%.

Is that just due to lack of good employment opportunities, low wages?

Yes. Rural communities in western North Carolina are not industry hubs. There have always been rural farming communities where people were self-sufficient; most were farmers. And it hasn’t changed much in several decades.

So would you say you have seen an increase in food insecurity in the regions MANNA serves or about the same?

MANNA, as far as food insecurity and demand, is like many other agencies serving those who are dealing with food security issues since the call out box 1economic downturn in 2008; things really got difficult for many people in our service area. And there just hasn’t been a pickup among lower income individuals regaining or rebounding as quickly as some others might have. In the last five-seven years, MANNA has doubled its output of food. So we went, in a five-year period, from approximately 7 million pounds of food product distributed to more than 15 million pounds last year.

Can you talk a little bit about your role with MANNA FoodBank and how you’ve used Community Commons to address food insecurity?

I was finishing up my Masters in Public Health and needed an internship and was fortunate because MANNA had an open position for an AmeriCorps Vista position which allowed me to do some capacity improvement work, as well as my capstone project with MANNA. What MANNA
wanted to see was where were the areas of need across the 16 county- network that were underserved or not served by the MANNA network. So, that was the beginning of me working on capacity improvement and my capstone project and was able to do so using Community Commons. The data that you guys provide, along with statistical programs, brought several key areas of need to light.

In school, I was able to do something really incredible for MANNA FoodBank. I was able to correlate childhood food insecurity and childhood poverty numbers for our network so that we could drill down from the county level for the 16 counties we serve. Now MANNA has a tool that allows them to look at census tract level data in each of the county’s service areas, and make more informed decisions about resource allocations.

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Explore the service area data maps in more detail by clicking the image.

That’s wonderful! Sounds like you’ve really been able to maximize the potential of Community Commons’ tools.

It’s huge because here in Buncombe County, the childhood poverty rate is approximately 25%. But when you start drilling down into the census tract data, looking at the poverty level you get an entirely different picture. Those numbers are correlated; the poverty level will correlate with childhood food insecurity level. So in my neighborhood, which is a fairly middle class, working class, mixed neighborhood, the childhood poverty rate is 74%. You look at that and you go ‘oh wow.’ The childhood food insecurity rate for Buncombe County is 24.9% but if you use that corollary data, you know it’s much different.

Has this had any impact on how MANNA identifies and connects with partners?

What MANNA is now doing with my research- and much to the great credit of Community Commons- is we are able to pull up maps of our entire 16 call out box 2county network and chart underserved areas where we don’t have a current partner or where there’s not enough service provided in low income areas.

There was one county, that we thought things were pretty good and it turned out that there were areas where childhood poverty that was over 95 percent. It just showed the organization that there was a whole section where there were no MANNA network partners serving that community. So of course that begins to immediately make MANNA start reaching out to try to form new partnerships in that area. It is a higher priority right now.

We actually shared some of what I was able to do and access in Community Commons with the other 6 food banks, just to let them know what capability is out there.

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What would you say the main strength of using Community Commons is?

For me, as a non-computer person, I was going to try to teach myself GIS through ARC or something like that and that just wasn’t happening for me. I’m a nontraditional student in that I am 51 years old and I am not writing a code in any way, shape, or form. So being able to use Community Commons was so applicable and so common sense that it was just easy to go and pull those statistical maps and go ‘oh look at that’ and you know here’s the tools for mapping, making sure we get to map the 16 counties in the agency network. It was user-friendly. A lot of it you could get down to that tract level data for poverty, which was important for me for my correlation. So, for me, Community Commons was just a beautiful tool that I could not have done my research without.

Sounds like you’ve definitely done some incredible things with it so far.

I hope to do more, I really do. I want to do more for the agency. Right now, I’m working for them in call out box 4a contract position doing something entirely different but people keep coming back to me saying, “Hey listen, we’re writing this grant…” The agency has really been excited about this capability, especially our resource development department. They’re very happy with the imagery that Community Commons is able to produce. You see one of your maps in full color, it’s sobering when you look at it and you’ve got the statistical data behind it to know that those are areas where children are going without. It’s just so beautifully, even sadly, but a wonderful tool.

One of the things that I’m hearing is that this has really increased your understanding of the community. Has it increased your efficiency or has it changed how you actually implement any of your programming?

As an agency, we have been going through a capital campaign-building project so we’re moving into new space. There hasn’t been an incredible amount of time to look at how to best utilize the information that we have gained and gathered and put together. But I know for one instance it was able to identify an area where there was a great need and the agency went out to look for a partner to be able to help address some of that need in that community for the children.

I am very interested in that correlation data that you guys calculated out because I think there are other youth cases that might benefit from that.

What I would love to see and I’m thinking about it from the Food Bank standpoint, but I sure would love if more food banks would be able to work with graduate schools to be able to do this kind of statistical analysis. To be able to pinpoint areas within county levels and state levels, to be able to drill down and see what local level data looks like and direct those that need numbers.

I am going to be presenting at a public health conference in the fall and one of the topics for the conference is innovation and public health and how you use innovative techniques in public health to find public health needs and I was asked to present my research. I would love to see more people utilizing this kind of data on a regular basis because it just makes sense.

It was so funny because last fall I was trying to find the best way to map the data that we needed and I was beating my head against the wall and one of the staff here just happened to mention Community Commons after a workshop. She said something about maps and gave me the website for Community Commons, and that’s how I got your website, and when I did it was like the choir began to sing. It required some effort to plot specific points on the maps, but it was a 99% satisfaction on my part by being able to use it as effectively as we have and moving forward as an agency, having people’s interest and being able, instead of an Excel spreadsheet. Being able to do the mapping, it’s much more of an effective tool.

What’s great is that you’ve created a framework other food banks and community organizations can learn from. What’s the most significant impact your research and the tools have had on the work MANNA does?

MANNA FoodBank now has access to areas that they didn’t know about- where the need is great and that correlates; I mean that literally turns into meals on the ground. That means children are getting fed that might not have had access to food before someone used the data and intervened. call out box 3That’s huge! Being able to show someone, here is where your agency is located and this is the area around it, 86% of the children here are living in poverty and food insecure. And someone said, “Well I knew it was bad but I didn’t have a clue it was that bad, we have to work harder.” It’s that anecdotal kind of feedback we’ve gotten just in the last couple months.

What I would love to see in Buncombe County is more people working together with technology, like Community Commons, to really address those core issues, those underlying issues. Hunger is a symptom of a greater issue, which is poverty.

Over the course of a few weeks to a few months, we will have new partnerships that will literally mean children are being fed. I cannot think of any greater compliment to give your group than to say, “Because Community Commons exists, children are being fed in Western North Carolina that weren’t being fed previously”. So, thank you.

Mapping Poverty in the Appalachian Region

The Appalachian region is home to hardworking individuals who value their families, community, and living in the natural beauty of one of America’s most beautiful regions. For generations, families have earned a living on jobs provided by the region’s primary industry- coal. In its heyday of the 1910s and 20s, more than 700,000 jobs were provided by the coal industry. In Appalachia, that number now hovers around 44,000 – with not much coming in to fill the void.

When the demise of the coal industry began in the 1940s, unemployment and poverty hit the region hard. Those with higher education went to other states for better jobs and higher wages- a trend we still see today, especially among young adults. More recently, the outsourcing of jobs overseas has caused soaring unemployment in a number of counties.

The outlook for coal is only expected to worsen as federal regulations, the decreasing cost of natural gas and the increasing costs of mining in the region continue. However, people in some of Appalachia’s most impoverished counties are coming up with their own ways of building a future without coal.

Still, poverty, unemployment, and low-paying wages persist. While communities across the US struggle with poverty, some of the most impoverished- and unnoticed- are in Appalachia.

Poverty in Appalachian Counties 

Appalachia has some of the highest poverty rates in the US. The US poverty rate is 15.6 percent, while the Appalachian region is 19.7 percent. However, what is most revealing is when you compare an Appalachian state’s poverty level to the same state’s Appalachian region’s poverty level. For example, in Virginia the poverty rate is 11.5 percent, much lower than the US rate. However, when you look at Virginia’s Appalachian region’s poverty rate, it increases considerably to 18.8 percent (Fahe.org). As depicted in the map below, the same is true for states like Kentucky and West Virginia as well. That’s the difference that frequently goes unnoticed.

CC Map Poverty3

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Unemployment in Appalachian Counties Relative to US Rate

Unemployment in the Appalachian region is 6.5 percent, and in the US it’s 6.2 percent. While this difference is not startling at first glance, when you look to specific counties, it becomes a much bigger issue. When coal companies and manufacturing plants close their doors, a jobs void affects workers in the surrounding areas. In Lewis County, KY, when Nine West shoe company closed their plant to move overseas, the county’s unemployment rate climbed to 12 percent.

CC Map Unemployment

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Appalachian Counties’ Per Capita Income

Unemployment is only one facet of the poverty in the region. As you can see from the map below, the Appalachian region has some of the lowest wages in the US. The average income in the Appalachian region is $37,260 and $46,049 in the US. What’s perhaps most telling is the labor market engagement map. It’s an index that describes the level of employment, labor force participation, and level of education in a census tract. Much of the region is plagued by poor labor market engagement, a direct reflection of poor job prospects and low wages.

CC Map Per Capita Income

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CC Map labr mrkt engagement

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Building Opportunity in Appalachia

The data and statistics look disheartening, but fortunately one of the greatest assets the region has are its people.

In an interview with The Atlantic, Peter Hillie, President of the Mountain Association for Community Economic Development (MACED) says unlike the past, Appalachia’s future prosperity will require more than one industry to come in and save the region, “There’s not a silver bullet,” he said, “There’s just a lot of little silver BBs.” One of those BBs is getting young people to stay.

In the same interview, Ada Smith from Lechter County, KY said “For people who grow up here or have roots in this place, parents and grandparents who know there’s not a lot of opportunity here encourage their loved ones to go and find jobs elsewhere.” Some counties are beginning to see the return of young people who left. One man returned from Louisville to open a tattoo parlor, others have opened restaurants, t-shirt companies and record shops. With a loan from MACED, one former coal miner even bought sheep from Vermont to start his own business- Good Shepherd Cheese.

Perhaps most inspiring is the work done by Smith and other young people from Appalachian states. Dismayed by the perception that staying in poor Appalachia counties is equated with failure, the group created Stay Together Appalachian Youth (STAY). Made up of young people from Appalachian states, the group discusses how they can better their local communities and work to encourage other young people to stay and work towards the same goal. “I feel like people are having conversations and willing to try different things that they never would have before,” Smith said. The enthusiasm for the movement is catching on, as more young people are moving to Whitesburg (where Smith lives) for the sense of community among other young adults that live there.

Building prosperity in Appalachia requires a homegrown effort, with commitments and investments from everyone. It needs people thinking about how they can work across county lines and state lines to move forward as a region –with its young people as the catalyst.

Catalyzing Health Care Investment in Healthier Food Systems

Health Care Without Harm is undertaking a national study of non-profit hospitals’ community benefit practices to improve healthy food access and reduce risk of diet-related disease. We’re excited to share information about the initiative below.

Recent changes under the ACA to IRS regulations governing the community benefit obligations of tax-exempt hospitals build on a movement by health industry leaders to promote greater community engagement and a population health orientation in community benefit practices. There is now a powerful new opportunity for non- profit hospitals to collaborate with other stakeholders to implement community health improvement plans that address social determinants of health such as housing, environmental and safety conditions, and the availability of quality, affordable food.

Health Care Survey

In this three-year project, funded by the Robert Wood Johnson Foundation, Health Care Without Harm is conducting a national study of non-profit hospitals’ community benefit practices targeted to strengthening food system resilience and sustainability, improving physical and economic access to healthy foods, and promoting healthier dietary patterns and healthy body weight. Through a national survey, in-depth interviews, and case studies, the study will identify best hospital community benefit practices as well as model programs promoting sustainable and healthy food systems.

Research Aims

  • Examine the extent to which hospital facilities are integrating food access, food insecurity, dietary patterns, obesity, and diet-related non-communicable disease (DR-NCD) in their Community Health Needs Assessments (CHNAs)
  • Analyze the kinds of Community Benefit (CB) investments that are taking place to strengthen food system resilience and sustainability, promote physical and economic access to healthy foods, improve dietary patterns, and reduce obesity and DR-NCD risk
  • Identify facilitators and obstacles to hospitals’ choosing to direct CB funds to obesity and food- related interventions
  • Identify best CB practices. These will include best practices in CHNAs; collaboration with public health agencies, community groups, and other stakeholders; implementation plans; and program evaluation based on criteria derived from a literature review and from the study
  • Identify model programs targeting food & nutrition-related community health impacts and improvements to food systems sustainability, which are currently or potentially could be supported by CB funds, based on criteria derived from a literature review and from the study

Desired Outcomes

  • Strengthen collaboration among stakeholders
  • Develop and disseminate tools for hospital facilities, the public health community, food security and environmental advocacy groups
  • Promote best practices

Survey invitations will be sent to a random sample of tax-exempt hospitals to learn about how hospitals include food insecurity, healthy food access, and diet-related health conditions in their community health needs assessments and implementation plans. If you receive an invitation to complete the brief survey, please do so! Your contribution is vital. Findings will be made available through various learning networks, including Community Commons.

Heath CHealth Care Without Harm Logoare Without Harm seeks to transform the health sector worldwide, without compromising patient safety or care, to become ecologically sustainable and a leading advocate for environmental health and justice. This project is being conducted by our Healthy Food in Health Care program. To learn more, please contact: Susan Bridle-Fitzpatrick, Senior Researcher, Healthy Food in Health Care Program, HCWH at sbridlefitzpatrick@hcwh.org, 1-888-264-7721 or visit www.noharm.org.

Mapping Factors that Influence Social Mobility

Upward social and economic mobility from one generation to the next is harder in the U.S. compared to other developed countries. While many Americans have access to resources and opportunities that bolster their chances of achieving the  “American Dream” for their families, many more lack the opportunity to simply break from the cycle of poverty. The difference between the two is often separated by just one street.

In a study looking at social and economic mobility in the US, Harvard and UC-Berkeley economics professors aptly stated, “The U.S. is better described as a collection of societies, some of which are `lands of opportunity’ with high rates of mobility across generations, and others in which few children escape poverty.”

The researchers describe high mobility areas as generally having:

  • Less residential segregation
  • Less income inequality
  • Better primary schools
  • Greater social capital
  • Greater family stability

The income gap between wealthy and non-wealthy Americans shows no signs of slowing down or reversing. Of course, this is not a new or unique trend, especially in some of America’s major cities. However, the starkest disparity is seen in the nation’s capitol. Poorer Americans not only have lower incomes, but also have more debt and less savings than higher income earners. In Washington, D.C., for example, the top 20 percent earn $151,132 per year, while the bottom 20 percent earn Less than $20,151 per year. In an area with one of America’s highest costs of living, the disparities echoe across neighborhoods, schools, and family households.

Let’s look at how the researcher’s indicators of social mobility play out in Washington, D.C.

Segregation in Residential Areas

RacialSegnMajMoinSchlsDC

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Income Inequality and Poverty

Average Family IncomeDC

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PopBelowPovDC

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Quality of Schools

SchoolProfIndexDC

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Family Stability

SingFemHousDC

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Outlook for social mobility in the U.S.

So, where are the most upwardly mobile cities?  Salt Lake City, Pittsburgh, and San Jose top the list. That means, children born into low income families in these cities generally fare better at moving up the income ladder as they age compared to other U.S. cities.

Why do these areas see higher intra- and intergenerational mobility? It depends.

San Jose has less concentrated poverty, proximity to innovative areas like Silicon Valley, and fewer single-family households, yet it’s schools under-perform and it has a higher level of racial and economic segregation. In Salt Lake City, they have a strong public school system, solid middle-class, and less income inequality.

However, despite these high rankings, the all too familiar trends of increasing rent and fewer middle class jobs, which many parts of the country are already experiencing, is beginning to impact even these cities. A similar problem is beginning to grow in San Jose as housing becomes unaffordable and middle class jobs dwindle. And as Salt Lake City becomes more diverse, increasing segregation and intergenerational poverty is making community workers take notice.

Issues like the non-ceasing, coast to coast trend of unaffordable housing and a weakening middle class have gained national attention. But it’s at the local level  where we’ll see real change- school funding, neighborhoods, access to jobs, affordable transportation, more housing options, and inclusive communities – are all factors researchers have underscored time and time again as having the greatest impact on upward mobility. When segregation of affluence, race, and resources exists, all members of the community see less upward social mobility. Most factors that impact social mobility are conditions children are born into- and where they’re born into it. For the U.S., creating one “land of opportunity” means building from the neighborhood on up.

To locate areas of opportunity in your community, check out Community Commons’ Location Opportunity Footprint Tool (LOFT).

Nutrition Data Represents Collaboration Between Government Agencies

Originally published on the U.S. Census Bureau Random Samplings Blog on December 9, 2015 by Lucinda Dalzell, Sara Stefanik and David Powers

In 2015, the U.S. Census Bureau released the 2014 Small Area Income and Poverty Estimates (SAIPE) for all school districts, counties, and states. These estimates are used to allocate federal funds to school districts for the next school year. Also released were counts of Supplemental Nutrition Assistance Program participants at the county and state levels for most years between 1989 and 2013. These counts are drawn from the source data of the SAIPE, and are the only source of SNAP participant total all U.S. counties.

SAIPE

Formerly known as the Food Stamp Program, SNAP is a nutrition assistance program for low-income individuals and families administered by the U.S. Department of Agriculture’s Food and Nutrition Service. The Food Stamp Act of 1977 requires that states report the number of SNAP participants by program area to USDA each year. USDA receives and makes available county-level SNAP data from roughly half of all states. In order to obtain and validate county-level data for the remaining states, each year a team of Census Bureau staff members collaborates with USDA and state government agencies.

This multi-agency collaboration allows the Census Bureau to publish a full county-level SNAP data set that otherwise would not be available. This unique SNAP data set is also an important input for the SAIPE program.

SAIPE Change

By utilizing other Census Bureau population data, data users can create SNAP statistics by metropolitan statistical area status and by census region. Table 1 presents SNAP participation rates, shares of SNAP participants, and shares of population by metropolitan statistical area status and by census region. We compute the SNAP “participation rate” as the number of SNAP participants divided by the population size.

Table 1 SAIPE repost

Table 1. SNAP and Population Data by Metro Area Status and by Region. Source: U.S. Census Bureau. Based on authors’ calculations, using SNAP data, population estimates, and metropolitan statistical area definitions.

The 2013 SNAP participation rate is 14.4 percent in metropolitan areas and 17.3 percent in non-metropolitan areas. At the regional level, the 2013 SNAP participation rate is 13.9 percent in the Northeast, 14.4 percent in the Midwest, 16.7 percent in the South, and 12.7 percent in the West.

The SNAP data are also available in our new interactive treemap web tool for years 2013 back through 2000.

Tree Map

Screenshot of Treemap of 2013 SNAP Participation Rates. Source: U.S. Census Bureau, Small Area Income and Poverty Estimates (SAIPE) program.

The treemap allows the data user to click on an individual box to view the specific county-level data. The larger the box for a given county, the greater the number of people or SNAP participants (depending on the selection) who reside there. Also, each box is color-shaded to indicate the SNAP participation rate range for the corresponding county.

The county and state SNAP data sets we have discussed here are available for download from the data input area of the SAIPE program website. Data users can reach our office with any questions or comments at sehsd.saipe@census.gov or at 301-763-3193.