Residential Mobility

The Residential Mobility indicator gauges the stability of the population by evaluating the percent of the population living in the same house as the previous year. High levels of mobility reflected by a low percent of residents remaining in the same home from year to year are considered a proxy for multiple, disruptive moves. Residential instability can be economically detrimental to adults, and stress inducing as well, which can contribute to mental and physical health outcomes. The impact of residential instability on children is striking, too. Longitudinal studies show that children who experience housing instability are more likely to experience negative childhood events such as abuse, neglect, depression, criminal activity, household dysfunction, and increased likelihood of smoking and suicide. Residential instability can also affect education outcomes among children, as they are more likely to repeat grades and face school suspensions. Although high residential instability is usually a sign of distress, some neighborhoods have high residential mobility because of less concerning reasons. For example, many college students move between school years. Posted under the Social Cohesion domain, the Residential Mobility indicator is also linked to the Housing, Economic Health, Educational Opportunities, Employment Opportunities and Health Systems and Public Safety domains. This indicator is available from the U.S. Census..

Neighborhoodsort descending Indicator Value Rank
Acipco-Finley 85.0% 40
Airport Highlands 95.6% 5
Apple Valley 87.2% 32
Arlington - West End 84.8% 43
Belview Heights 84.9% 41
Bridlewood 69.5% 93
Brown Springs 79.2% 69
Brownsville Heights 95.5% 6
Brummitt Heights 95.3% 7
Bush Hills 73.0% 85
Central City 54.5% 99
Central Park 70.2% 91
Central Pratt 92.6% 12
College Hills 90.2% 17
Collegeville 88.1% 27
Crestline 74.1% 81
Crestwood North 81.9% 56
Crestwood South 83.9% 48
Dolomite 85.6% 37
Druid Hills 73.0% 85
East Avondale 69.9% 92
East Birmingham 74.2% 80
East Brownville 85.1% 39
East Lake 78.0% 71
East Thomas 97.9% 2
Eastwood 74.8% 76
Echo Highlands 79.3% 68
Enon Ridge 88.9% 24
Ensley 74.4% 79
Ensley Highlands 80.4% 65
Evergreen 88.6% 25
Fairmont 90.8% 16
Fairview 84.1% 46
Five Points South 55.6% 98
Forest Park 74.5% 78
Fountain Heights 75.0% 75
Garden Highlands 73.7% 82
Gate City 81.7% 59
Germania Park 81.8% 57
Glen Iris 60.6% 97
Grasselli Heights 96.1% 3
Graymont 85.6% 37
Green Acres 81.8% 57
Harriman Park 83.6% 49
Highland Park 71.5% 89
Hillman 94.5% 9
Hillman Park 84.1% 46
Hooper City 88.1% 27
Huffman 88.1% 27
Industrial Center 73.2% 84
Inglenook 89.4% 20
Jones Valley 82.0% 54
Killough Springs 84.9% 41
Kingston 84.6% 45
Liberty Highlands 83.0% 50
Maple Grove 86.1% 35
Mason City 84.8% 43
North Avondale 74.7% 77
North Birmingham 95.8% 4
North East Lake 86.9% 33
North Pratt 93.4% 11
North Titusville 78.0% 71
Norwood 62.0% 96
Oak Ridge 88.6% 25
Oak Ridge Park 82.0% 54
Oakwood Place 81.6% 61
Overton 82.4% 52
Oxmoor 68.2% 94
Penfield Park 86.0% 36
Pine Knoll Vista 95.3% 7
Powderly 86.2% 34
Redmont Park 82.8% 51
Riley 91.5% 13
Rising - West Princeton 72.0% 87
Roebuck 91.5% 13
Roebuck Springs 88.1% 27
Roosevelt 81.1% 62
Sandusky 87.9% 31
Sherman Heights 89.4% 20
Smithfield 90.1% 18
Smithfield Estates 91.5% 13
South East Lake 75.3% 74
South Pratt 81.7% 59
South Titusville 82.2% 53
South Woodlawn 80.2% 66
Southside 71.6% 88
Spring Lake 89.9% 19
Sun Valley 81.0% 63
Tarpley City 75.5% 73
Thomas 78.7% 70
Tuxedo 65.8% 95
Wahouma 80.5% 64
West Brownville 71.5% 89
West End Manor 94.5% 9
West Goldwire 73.6% 83
Woodland Park 99.2% 1
Woodlawn 89.1% 23
Wylam 79.8% 67
Zion City 89.3% 22

Key Citations:
1. Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents. American Journal of Epidemiology. 1979;109(2):186-204.
2. Bures RM. 2003. Childhood residential stability and health at midlife. American Journal of Public Health 93:1144-8.
3. Cooper, Merrill. 2001. Housing Affordability: A Children's Issue. Ottawa: Canadian Policy Research Networks Discussion Paper.
4. Dong M. 2005. Childhood residential mobility and multiple health risks during adolescence and adulthood. Archives of Pediatrics and Adolescent Medicine 159:11-4-1110.
5. Gilman SE, Kawachi I, Fizmaurice GM Buka L. 2003. Socio-economic status, family disruption and residential stability in childhood: relation to onset, recurrence and remission of major depression. Psychol Medicine 33:1341-55.