How residential mobility and school choice challenge assumptions of neighborhood place-based interventions.
OBJECTIVE
Explore the importance of residential mobility and use of services outside neighborhoods when interventions targeting low-income families are planned and implemented.


METHODS
Analysis of cross-sectional telephone household survey data on childhood mobility and school enrollment in four large distressed cities.


METHODS
Baltimore, Maryland; Detroit, Michigan; Philadelphia, Pennsylvania; and Richmond, Virginia.


METHODS
Total of 1723 teens aged 10 to 18 years and their parents.


METHODS
Continuous self-report of the number of years parents lived in the neighborhood of residence and city; self-report of whether the child attends school in their neighborhood; and categorical self report of parents' marital status, mother's education, parent race, family income, child's age, and child's sex.


METHODS
Chi-square and multivariate logistic regression.


RESULTS
In this sample, 85.2% of teens reported living in the city where they were born. However, only 44.4% of black teens lived in neighborhoods where they were born, compared with 59.2% of white teens. Although 50.3% of black teens attended schools outside of their current neighborhoods, only 31.4% of whites did. Residential mobility was more common among black than white children (odds ratio = 1.82; p < .001), and black teens had 43% lesser odds of attending school in their home communities.


CONCLUSIONS
Mobility among low-income and minority families challenges some assumptions of neighborhood interventions premised on years of exposure to enriched services and changes in the built environment.
Department of Nutrition, Food Studies and Public Health, Steinhardt School of Culture, Education and Human Development, New York University, 35 West 4th Street, New York, NY 10003, USA. diana.silver@nyu.edu
Diana
D
Silver
Beth C
BC
Weitzman
Tod
T
Mijanovich
Martha
M
Holleman
D000293:Adolescent; D002648:Child; D002755:Choice Behavior; D003430:Cross-Sectional Studies; D003625:Data Collection; D003657:Decision Making; D004779:Environment Design; D005260:Female; D006293:Health Promotion / Q000379:methods; D006801:Humans; D016015:Logistic Models; D008297:Male; D008913:Minority Groups; D015999:Multivariate Analysis; D011203:Poverty / Q000706:statistics & numerical data*; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012574:Schools; D040241:Social Marketing; D012959:Socioeconomic Factors; D013223:Statistics as Topic; D013334:Students; D014481:United States