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

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.