Congress Has Reached a Crucial Stage in Farm Bill Negotiations that Could Make Work of Food Banks More Difficult / Senator Casey Leads Senate Colleagues in Letter to Strengthen Partnership Between USDA, Food Banks / Food Aid Will Help Struggling Seniors and Children, Boost Economy / County-by-County Numbers Show Importance of Food Aid for PA Children
Washington, DC- With Thanksgiving approaching, U.S. Senator Bob Casey (D-PA) called on Congress to increase emergency assistance to food banks that are already struggling to keep up with demand. Currently, Congress has entered a critical stage in farm bill negotiations that will feature significant decisions on food security programs such as the Emergency Food Assistance Program (TEFAP) and the Supplemental Nutrition Assistance Program (SNAP).
“Food assistance programs like TEFAP and SNAP play a critical role in the battle against hunger for children, seniors and families across Pennsylvania and throughout our nation,” Senator Casey said. “In this time of economic recovery, there is an urgent need for food assistance. Congress must work on a bipartisan basis to develop policies for ensuring that all Americans have access to safe, affordable, and nutritious foods.”
Casey’s effort encourages Congress to increase support for a program that allows the U.S. Department of Agriculture to aid food banks around the country so they can continue to serve residents in need. Joined by 25 additional Senators, Casey’s letter makes the case that failing to increase support for this program will negatively impact struggling children and seniors and cause harm to the economy.
With the support of TEFAP funding, food banks serve an integral role in combating hunger in the state. Feeding Pennsylvania food banks annually provide food assistance to more than 2 million low-income men, women, and children. Feeding America has said that following a 46 percent increase in demand during the recession, food banks are already struggling to meet need in their communities and will be unable to make up the difference.
Additionally, more than 1.7 million Pennsylvanians annually rely on the Supplemental Nutrition Assistance Program (SNAP), the nation’s single most important program in the fight against hunger. The House Farm Bill cuts SNAP by $39 billion, which would mean a loss of over 93 million meals in Pennsylvania in 2014 alone.
Almost 15 percent of Pennsylvanians experience food insecurity, and over 20 percent of children in Pennsylvania are food insecure (the household experienced a shortage of food). According to Feeding America, 35 percent of food insecure children are likely not eligible for SNAP or other income-based Federal nutrition programs.
Below are county-by-county numbers of child food insecurity in Pennsylvania, as well as the full text of Senator Casey’s letter:
|
|
|
||||||||||
|
Map the Meal Gap 2013 |
|||||||||||
|
Pennsylvania Child Food Insecurity by County in 20111 |
|||||||||||
|
County |
Population under 18 years old |
Child food insecurity rate2 |
Estimated number food insecure children (rounded) |
Food insecure children likely income-eligible for federal nutrition assistance3 |
Food insecure children likely NOT income-eligible for federal nutrition assistance3 |
||||||
|
Adams |
9.8% |
22,750 |
16.7% |
3,800 |
64% |
36% |
|||||
|
Allegheny |
13.6% |
243,928 |
16.4% |
40,110 |
63% |
37% |
|||||
|
Armstrong |
11.9% |
14,373 |
20.6% |
2,960 |
73% |
27% |
|||||
|
Beaver |
12.1% |
35,170 |
18.7% |
6,590 |
69% |
31% |
|||||
|
Bedford |
12.6% |
10,864 |
21.3% |
2,310 |
84% |
16% |
|||||
|
Berks |
12.3% |
98,178 |
20.9% |
20,530 |
64% |
36% |
|||||
|
Blair |
12.1% |
27,069 |
20.1% |
5,440 |
75% |
25% |
|||||
|
Bradford |
10.9% |
14,354 |
19.6% |
2,820 |
80% |
20% |
|||||
|
Bucks |
9.7% |
144,695 |
14.1% |
20,360 |
40% |
60% |
|||||
|
Butler |
10.1% |
41,543 |
15.6% |
6,490 |
52% |
48% |
|||||
|
Cambria |
13.2% |
28,454 |
21.8% |
6,210 |
73% |
28% |
|||||
|
Cameron |
14.9% |
1,006 |
25.2% |
250 |
84% |
16% |
|||||
|
Carbon |
12.4% |
13,636 |
21.5% |
2,940 |
69% |
31% |
|||||
|
Centre |
13.8% |
24,357 |
16.0% |
3,890 |
61% |
39% |
|||||
|
Chester |
9.5% |
123,545 |
13.0% |
16,020 |
39% |
62% |
|||||
|
Clarion |
14.3% |
7,932 |
22.6% |
1,790 |
77% |
23% |
|||||
|
Clearfield |
12.9% |
16,967 |
22.9% |
3,890 |
77% |
23% |
|||||
|
Clinton |
13.1% |
8,078 |
20.4% |
1,650 |
80% |
20% |
|||||
|
Columbia |
13.2% |
12,608 |
19.5% |
2,460 |
74% |
26% |
|||||
|
Crawford |
12.9% |
20,065 |
22.4% |
4,490 |
79% |
21% |
|||||
|
Cumberland |
10.5% |
48,498 |
15.4% |
7,450 |
52% |
48% |
|||||
|
Dauphin |
14.4% |
62,018 |
17.9% |
11,070 |
64% |
36% |
|||||
|
Delaware |
13.7% |
130,631 |
14.9% |
19,420 |
57% |
43% |
|||||
|
Elk |
10.9% |
6,785 |
20.8% |
1,410 |
83% |
17% |
|||||
|
Erie |
14.0% |
64,102 |
21.0% |
13,450 |
71% |
29% |
|||||
|
Fayette |
14.9% |
28,201 |
26.1% |
7,350 |
80% |
20% |
|||||
|
Forest |
12.5% |
1,012 |
18.8% |
190 |
95% |
5% |
|||||
|
Franklin |
10.9% |
35,460 |
16.9% |
5,990 |
65% |
35% |
|||||
|
Fulton |
12.9% |
3,440 |
22.0% |
760 |
76% |
24% |
|||||
|
Greene |
12.4% |
7,679 |
21.2% |
1,630 |
86% |
14% |
|||||
|
Huntingdon |
13.1% |
9,162 |
20.4% |
1,870 |
75% |
25% |
|||||
|
Indiana |
13.7% |
16,903 |
20.3% |
3,430 |
76% |
24% |
|||||
|
Jefferson |
12.4% |
9,808 |
21.5% |
2,110 |
81% |
19% |
|||||
|
Juniata |
10.7% |
5,839 |
19.0% |
1,110 |
89% |
12% |
|||||
|
Lackawanna |
13.8% |
44,060 |
21.7% |
9,550 |
69% |
31% |
|||||
|
Lancaster |
11.2% |
128,997 |
17.8% |
23,020 |
66% |
35% |
|||||
|
Lawrence |
12.6% |
19,560 |
20.9% |
4,080 |
72% |
28% |
|||||
|
Lebanon |
10.5% |
30,623 |
18.2% |
5,560 |
68% |
32% |
|||||
|
Lehigh |
13.0% |
82,327 |
21.0% |
17,280 |
64% |
36% |
|||||
|
Luzerne |
14.0% |
64,807 |
22.6% |
14,620 |
71% |
30% |
|||||
|
Lycoming |
13.2% |
24,463 |
20.7% |
5,060 |
75% |
25% |
|||||
|
McKean |
13.2% |
9,328 |
22.0% |
2,050 |
81% |
19% |
|||||
|
Mercer |
13.1% |
25,418 |
20.3% |
5,170 |
77% |
23% |
|||||
|
Mifflin |
12.8% |
10,880 |
22.6% |
2,460 |
85% |
15% |
|||||
|
Monroe |
12.9% |
41,048 |
17.7% |
7,250 |
65% |
36% |
|||||
|
Montgomery |
10.5% |
182,938 |
12.9% |
23,620 |
41% |
59% |
|||||
|
Montour |
10.6% |
3,956 |
17.9% |
710 |
81% |
19% |
|||||
|
Northampton |
11.7% |
65,267 |
18.0% |
11,730 |
55% |
45% |
|||||
|
Northumberland |
13.3% |
19,241 |
22.4% |
4,300 |
81% |
19% |
|||||
|
Perry |
10.6% |
10,682 |
18.8% |
2,010 |
71% |
29% |
|||||
|
Philadelphia |
23.2% |
345,973 |
22.3% |
77,300 |
65% |
35% |
|||||
|
Pike |
12.0% |
13,625 |
18.9% |
2,570 |
64% |
36% |
|||||
|
Potter |
13.1% |
3,954 |
22.7% |
900 |
88% |
12% |
|||||
|
Schuylkill |
12.8% |
29,868 |
20.7% |
6,190 |
70% |
30% |
|||||
|
Snyder |
11.6% |
8,909 |
19.8% |
1,760 |
77% |
23% |
|||||
|
Somerset |
12.2% |
15,317 |
20.9% |
3,200 |
88% |
12% |
|||||
|
Sullivan |
10.6% |
1,062 |
19.0% |
200 |
100% |
0% |
|||||
|
Susquehanna |
11.2% |
9,322 |
19.6% |
1,830 |
79% |
22% |
|||||
|
Tioga |
11.9% |
8,711 |
20.9% |
1,820 |
83% |
17% |
|||||
|
Union |
12.4% |
8,271 |
18.8% |
1,560 |
81% |
19% |
|||||
|
Venango |
12.4% |
12,011 |
23.0% |
2,760 |
74% |
26% |
|||||
|
Warren |
11.1% |
8,775 |
19.8% |
1,740 |
75% |
26% |
|||||
|
Washington |
11.1% |
43,009 |
16.7% |
7,200 |
60% |
40% |
|||||
|
Wayne |
10.7% |
10,312 |
19.0% |
1,960 |
83% |
18% |
|||||
|
Westmoreland |
11.1% |
73,377 |
17.9% |
13,100 |
63% |
37% |
|||||
|
Wyoming |
12.5% |
6,213 |
21.6% |
1,340 |
70% |
30% |
|||||
|
York |
11.4% |
101,941 |
17.5% |
17,800 |
59% |
41% |
|||||
|
State Total4 |
14.9% |
2,757,475 |
20.5% |
559,120 |
65% |
35% |
|||||
|
For additional data and maps by county, state, and congressional district, please visit www.feedingamerica.org/mapthegap. |
|||||||||||
|
Gundersen, C., Waxman, E., Engelhard, E., Satoh, A., & Chawla, N. Map the Meal Gap: Child Food Insecurity 2013. This research is generously supported by the Howard G. Buffett Foundation and The Nielsen Company. |
|||||||||||
|
1Map the Meal Gap's child food insecurity rates are determined using data from the 2001-2011 Current Population Survey on children under 18 years old in food insecure households; data from the 2011 American Community Survey on median family incomes for households with children, child poverty rates, home ownership, and race and ethnic demographics among children; and 2011 data from the Bureau of Labor Statistics on unemployment rates. |
|||||||||||
|
2 The statistical model for estimating food insecurity in 2013 differs slightly from the model used in 2012. The updated 2013 model includes "homeownership" in addition to the variables used in previous years to account for household assets and help produce more accurate estimates of food insecurity at the local level. For more information about these factors, please see the technical brief or supplemental methodology information on HungerNet. |
|||||||||||
|
3Numbers reflect percentage of food insecure children living in households with incomes above or below 185% of the federal poverty guideline for 2011. Eligibility for federal child nutrition programs is determined in part by income thresholds which can vary by state. |
|||||||||||
|
4Data in the state totals row do not reflect the sum of all counties in that state. The state totals are aggregated from the congressional districts data in that state. |
