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..

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

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.