Public Assisted Households

Income is one of the strongest and most consistent predictors of health and disease in public health research. There are several safety nets administered by the federal government. The Public Assisted Household indicator accounts for these safety nets by measuring the proportion of neighborhood households that receive Supplemental Security Income (SSI), cash public assistance, and/or Supplemental Nutrition Assistance Program (SNAP) benefits , also commonly referred to as food stamps, to support their income. Studies show that households not earning a self-sufficient wage may be subject to increases in premature death from all causes for working adults, lower educational outcomes, and a higher risk of premature childbirth. Self-sufficiency is considered as having an income high enough to meet basic needs without public subsidies such as public housing, food stamps, Medicaid or childcare, or the private market, or informal networks. The higher the number of neighborhood households dependent on public assistance, the lower the likelihood household incomes reach a self-sufficient standard. Although posted under the Employment Opportunities domain, the Public Assisted Households indicator is also strongly tied to the Educational Opportunities, Economic Health, Neighborhood Characteristics, and Housing domains. Data for the Public Assisted Households indicator is available from the U.S. Census.

Neighborhoodsort descending Indicator Value Rank
Acipco-Finley 43.1% 49
Airport Highlands 31.8% 29
Apple Valley 30.6% 27
Arlington - West End 58.2% 69
Belview Heights 33.3% 34
Bridlewood 42.1% 47
Brown Springs 41.6% 44
Brownsville Heights 31.7% 28
Brummitt Heights 15.5% 10
Bush Hills 47.3% 56
Central City 29.2% 25
Central Park 53.3% 65
Central Pratt 50.9% 60
College Hills 59.3% 71
Collegeville 84.8% 94
Crestline 6.9% 2
Crestwood North 7.9% 3
Crestwood South 9.3% 5
Dolomite 33.3% 34
Druid Hills 37.1% 37
East Avondale 29.0% 24
East Birmingham 37.5% 38
East Brownville 63.6% 81
East Lake 38.9% 40
East Thomas 30.1% 26
Eastwood 20.0% 13
Echo Highlands 26.7% 20
Enon Ridge 52.3% 62
Ensley 61.9% 75
Ensley Highlands 51.7% 61
Evergreen 52.7% 63
Fairmont 59.6% 72
Fairview 58.9% 70
Five Points South 14.2% 9
Forest Park 22.2% 16
Fountain Heights 67.5% 88
Garden Highlands 63.3% 79
Gate City 116.7% 99
Germania Park 47.3% 56
Glen Iris 21.8% 15
Grasselli Heights 42.1% 47
Graymont 103.1% 97
Green Acres 38.8% 39
Harriman Park 68.4% 89
Highland Park 10.9% 7
Hillman 65.4% 85
Hillman Park 65.4% 85
Hooper City 63.6% 81
Huffman 21.4% 14
Industrial Center 71.0% 90
Inglenook 60.0% 73
Jones Valley 32.4% 32
Killough Springs 25.2% 18
Kingston 57.7% 68
Liberty Highlands 34.5% 36
Maple Grove 32.2% 30
Mason City 63.0% 78
North Avondale 79.9% 92
North Birmingham 39.8% 41
North East Lake 46.1% 54
North Pratt 62.2% 76
North Titusville 76.8% 91
Norwood 62.3% 77
Oak Ridge 40.7% 42
Oak Ridge Park 44.2% 50
Oakwood Place 47.5% 58
Overton 2.8% 1
Oxmoor 8.2% 4
Penfield Park 32.2% 30
Pine Knoll Vista 15.5% 10
Powderly 55.8% 66
Redmont Park 9.8% 6
Riley 45.4% 53
Rising - West Princeton 63.3% 79
Roebuck 26.8% 21
Roebuck Springs 11.1% 8
Roosevelt 42.0% 46
Sandusky 46.5% 55
Sherman Heights 45.3% 52
Smithfield 81.0% 93
Smithfield Estates 26.4% 19
South East Lake 41.9% 45
South Pratt 53.1% 64
South Titusville 23.6% 17
South Woodlawn 91.6% 95
Southside 91.9% 96
Spring Lake 17.6% 12
Sun Valley 40.9% 43
Tarpley City 64.1% 83
Thomas 28.1% 23
Tuxedo 105.3% 98
Wahouma 50.2% 59
West Brownville 56.3% 67
West End Manor 44.2% 50
West Goldwire 64.7% 84
Woodland Park 32.7% 33
Woodlawn 60.2% 74
Wylam 67.0% 87
Zion City 27.3% 22

Key Citations:
1. Braveman, Paula, et al. “Issue Brief #4 Exploring the Social Determinants of Health – April 2011; Income, Wealth and Health” (2011). Robert Wood Johnson Foundation.
2. Bhatia, Rajiv and Mitchell Katz. “Estimation of Health Benefits from a Local Living Wage Ordinance” (2001). American Journal of Public Health.
3. Pickett, K.E. and M. Pearl. “Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review” (2001). Journal of Epidemiology and Community Health.
4. Pollack, C.E., et al. “Should Health Studies Measure Wealth?” (2007). American Journal of Preventive Medicine.
5. Subramanian, S.V. and Ichiro Kawachi. “Income Inequality and Health: What Have We Learned So Far?” (2004). Epidemiologic Reviews, Johns Hopkins Bloomberg School of Public Health.